scientific research on memory loss

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Inside the Science of Memory

When Rick Huganir, Ph.D. , was a teenager, he set out to better understand the physical and emotional changes of adolescence. “I was wondering what was happening to me, and I realized it was my brain changing,” says Huganir, director of the Johns Hopkins Department of Neuroscience.

That led to a senior project on protein synthesis and memory in goldfish, as well as a lifelong fascination in how we learn and remember things.

“Memories are who we are,” says Huganir. “But making memories is also a biological process.” This process raises many questions. How does the process affect our brain? How do experiences and learning change the connections in our brains and create memories?

Those are just some of the issues Huganir and his colleagues are studying. Their work may lead to new treatments for post-traumatic stress syndrome, as well as ways to improve memory in people with dementia and other cognitive problems.

Memory: It’s All About Connections

When we learn something—even as simple as someone’s name—we form connections between neurons in the brain. These synapses create new circuits between nerve cells, essentially remapping the brain. The sheer number of possible connections gives the brain unfathomable flexibility—each of the brain’s 100 billion nerve cells can have 10,000 connections to other nerve cells.

Those synapses get stronger or weaker depending on how often we’re exposed to an event. The more we’re exposed to an activity (like a golfer practicing a swing thousands of times) the stronger the connections. The less exposure, however, the weaker the connection, which is why it’s so hard to remember things like people’s names after the first introduction.

“What we’ve been trying to figure out is how does this occur, and how do you strengthen synapses at a molecular level?” Huganir says.

New Discoveries in Memory

Many of the research questions surrounding memory may have answers in complex interactions between certain brain chemicals—particularly glutamate—and neuronal receptors, which play a crucial role in the signaling between brain cells. Huganir and his team discovered that when mice are exposed to traumatic events, the level of neuronal receptors for glutamate increases at synapses in the amygdala, the fear center of the brain, and encodes the fear associated with the memory. Removing those receptors, however, reduces the strength of these connections, essentially erasing the fear component of the trauma but leaving the memory.

Now Huganir and his lab are developing drugs that target those receptors. The hope is that inactivating the receptors could help people with post-traumatic stress syndrome by reducing the fear associated with a traumatic memory, while strengthening them could improve learning, particularly in people with cognitive dysfunction or Alzheimer’s disease .

#TomorrowsDiscoveries: Using Data to Diagnose Brain Diseases | Michael I. Miller, Ph.D.

Johns Hopkins researcher Michael Miller explains how we can use data to create better diagnostic tools for neurodegenerative disorders like Alzheimer's disease.

Definitions

Dementia (di-men-sha) : A loss of brain function that can be caused by a variety of disorders affecting the brain. Symptoms include forgetfulness, impaired thinking and judgment, personality changes, agitation and loss of emotional control. Alzheimer’s disease, Huntington’s disease and inadequate blood flow to the brain can all cause dementia. Most types of dementia are irreversible.

Post-traumatic stress disorder (PTSD) : A disorder in which your “fight or flight,” or stress, response stays switched on, even when you have nothing to flee or battle. The disorder usually develops after an emotional or physical trauma, such as a mugging, physical abuse or a natural disaster. Symptoms include nightmares, insomnia, angry outbursts, emotional numbness, and physical and emotional tension.

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Memory: Myth Versus Truth

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Journal of Applied Research in Memory and Cognition

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Journal snapshot

Journal scope statement

The Journal of Applied Research in Memory and Cognition (JARMAC) publishes the highest-quality applied research in memory and cognition, in the format of empirical reports, review articles, and target papers with invited peer commentary. The goal of this unique journal is to reach psychological scientists and other researchers working in this field and related areas, as well as professionals and practitioners who seek to understand and apply research on memory and cognition. In pursuit of these aims, we encourage submissions of original and rigorous work that examines memory and cognitive processes and mechanisms and that informs policies and practices. We further encourage brevity and crisp, lively prose that appeals to a wide audience. Each paper also includes a general audience summary, clearly describing the paper and its practical implications in language accessible to non-specialists.

Empirical reports should convey significant experimental findings. The combined number of words in the introduction and discussion sections should not exceed 2,200 words for single-study reports and 3,000 words for multiple studies (counting the introduction and discussion for each study). These are upper bounds, and authors are expected to keep the report as succinct as possible. This limit is not set for the entire manuscript because the journal seeks to encourage a detailed description of method and a results section that reports outcomes from all tasks.

Target articles should not exceed 10,000 words. Authors considering a target article should contact the editor prior to submission.

JARMAC is an official journal of Society for Applied Research in Memory & Cognition .

Calls for papers

Call for letters of intent: Autobiographical processing and psychopathology
Call for letters of intent: A special forum of JARMAC: Applied cognitive science around the globe

Editor’s Choice

One article from each issue of Journal of Applied Research in Memory and Cognition will be highlighted as an “ Editor’s Choice ” article. Selection is based on the recommendations of the associate editors, the paper’s potential impact to the field, the distinction of expanding the contributors to, or the focus of, the science, or its discussion of an important future direction for science. Editor’s Choice articles are featured alongside articles from other APA published journals in a bi-weekly newsletter and are temporarily made freely available to newsletter subscribers.

Author and editor spotlights

Explore journal highlights : free article summaries, editor interviews and editorials, journal awards, mentorship opportunities, and more.

Prior to submission, please carefully read and follow the submission guidelines detailed below. Manuscripts that do not conform to the submission guidelines may be returned without review.

Please complete the author formatting checklist before submitting your manuscript.

To submit to the editorial office of Qi Wang, please submit manuscripts electronically through the Manuscript Submission Portal in Microsoft Word format (.doc) or LaTex (.tex) as a zip file with an accompanied Portable Document Format (.pdf) of the manuscript file.

Double space all copy. Prepare manuscripts according to the Publication Manual of the American Psychological Association using the 7 th edition. Manuscripts may be copyedited for bias-free language (see Chapter 5 of the Publication Manual ). APA Style and Grammar Guidelines for the 7 th edition are available.

Submit Manuscript

Manuscript types

Empirical articles should report significant experimental findings. The combined number of words in the introduction and discussion sections should not exceed 2,200 words for single-study reports and 3,000 words for multiple studies (counting the introduction and discussion of each study). These are upper bounds, and authors are expected to keep the report as succinct as possible. The limit is not set for the entire manuscript because we want to encourage detailed description of method and a results section that reports outcomes from all tasks. The editor may consider exceptions to these limits if special circumstances are justified in the cover letter, but these exceptions will be rare.

Review articles should critically review a topic or topics of importance to the readership of JARMAC , and have no restrictions on length.

Target articles and related peer commentaries are typically invited by the editor. Authors may suggest topics by writing a précis and sending it to the editorial office for consideration. Target articles should not exceed 10,000 words. Authors considering a target article should contact the editor prior to submission.

In Memoriam section An annual In Memoriam section of the journal will celebrate the life and contributions of SARMAC members who have contributed significantly to research in any area of applied cognition and memory. Submissions should be authored by individuals who personally knew or collaborated with the honoree; collaborative contributions are encouraged. Contributions should not exceed 1,000 words and include three to five recommended readings that are selected from the honoree’s contributions. A black-and-white photograph of the honoree may be included. Submissions will be peer-reviewed by scholars familiar with the honoree’s work prior to publication.

Double masked review and the option to bypass

To prepare for (double) masked review (where the names of the authors are withheld from the reviewers and vice versa), authors should make every effort to remove any identifying information from the manuscript and references. All information pertaining to identification, title, institutional affiliation, etc. should be included on the title page, which is submitted separately; only the title of the manuscript should appear on the first page of the manuscript. Alternatively , authors who choose not to have their identities concealed may simply keep the title page as part of the manuscript, submit a blank page as a separate title page, and eschew the other means of removing identifying content. Authors should indicate which option they are choosing in their cover letter.

Authors may submit the names and email addresses of two potential referees. Also indicate whether you believe any potential referees should be excluded. Note that the action editor retains the sole right to decide whether or not the suggested reviewers are used or excluded.

Title. Concise and informative. Titles are often used in information-retrieval systems. Avoid abbreviations and formulae where possible.

Author names and affiliations Please clearly indicate the given name(s) and family name(s) of each author and check that all names are accurately spelled. Present the authors' affiliations (where the actual work was done, including the country name). Indicate all affiliations with a lower- case superscript letter immediately after the author's name and in front of the appropriate address. If the manuscript is by a single author or if all authors are from the same institution, there is no need to use superscripts.

Corresponding author. Clearly indicate who will handle correspondence at all stages of refereeing publication, and post-publication. Provide the email and full postal address of the corresponding author. Ensure that contact details are kept up to date by the corresponding author.

Present/permanent address. If an author has moved since the work described in the article was done, or was visiting at the time, a 'Present address' (or 'Permanent address') may be indicated as a footnote to that author's name. The address at which the author actually did the work must be retained as the main, affiliation address. Superscript Arabic numerals are used for such footnotes.

Word count. For all articles, please declare the word count of your manuscript (upon first submission as well as resubmission). For empirical articles, please also declare the word count of sections identifiable as introduction and discussion.

Abstract and keywords

A concise and factual abstract is required and must contain 150 words or fewer, presented in paragraph form on a separate page (page 2 of the manuscript). The abstract should state briefly the purpose of the research, method, principal results, and major conclusions. An abstract is often presented separately from the article, so it must be able to stand alone. For this reason, references should be avoided, but if essential, then cite the author(s) and year(s). Also, nonstandard or uncommon abbreviations should be avoided, but if essential they must be defined at their first mention in the abstract itself.

Immediately after the abstract, provide a maximum of 6 keywords, using US spelling and avoiding general terms, plural terms, and multiple concepts (e.g., ones connected by conjunctions and prepositions). Be sparing with abbreviations: only abbreviations firmly established in the field may be eligible. These keywords will be used for indexing purposes.

General audience summary

On a separate page, between the abstract and the introduction, type a summary of the research that can be understood by generally educated adults with no particular experience with experimental design and statistical analyses. The paragraph should capture the issue under investigation, the method, the most important outcome, and its implication for or application to real-world settings. This summary, limited to 300 words, should be suitable for circulation to popular media. Like the abstract, the general audience summary will ALSO be uploaded as a separate document during submission, but please do not forget to include both in the document or pdf of your submitted manuscript.

Please read the Guidance for translational abstracts and public significance statements page to help you write this text.

Research transparency and openness

Data and materials sharing.

The policy of the Journal of Applied Research in Memory and Cognition is to publish papers in which data, methods used in the analysis, and materials used to conduct the research are clearly and precisely documented and are maximally available to any researcher for purposes of reproducing the results or replicating the procedure. Recommended repositories include APA’s repository on the Open Science Framework (OSF), or authors can access a full list of other recommended repositories .

Authors must share their data, analytic methods, and research materials and provide a repository link in their manuscript and during the submission process. If the data and materials on which study conclusions are based are unavailable, the authors should note their legal or ethical reasons for not doing so and are expected to abide by APA’s data preservation policies, specified below under “Ethical Principles.”

For example:

All data have been made publicly available at the [repository name] and can be accessed at [persistent URL or DOI].
Materials and analysis code for this study are available by emailing the corresponding author.
Materials and analysis code for this study are not available.
The code behind this analysis/simulation has been made publicly available at the [repository name] and can be accessed at [persistent URL or DOI].

Authors must disclose any prior uses of data reported in the manuscript in the author note and in the cover letter, which should include a complete reference list of these articles as well as a description of the extent and nature of any overlap between the present submission and the previous work.

Funding support and conflict of interest

Authors must disclose all sources of financial support for the conduct of the research (e.g., "This research was supported by NIDA grant X") in the author note. If the funding source was involved in any other aspects of the research (e.g., study design, analysis, interpretation, writing), then clearly state the role. If the funding source had no other involvement other than financial support, then simply state that the funding source had no other role other than financial support. Also provide a conflict-of-interest statement disclosing any real or potential conflict(s) of interest, including financial, personal, or other relationships with other organizations or companies that may inappropriately impact or influence the research and interpretation of the findings. If there are no conflicts of interest, this should be clearly stated.

Informed consent and institutional review board approval

Authors must include a statement describing how informed consent was obtained from the participants (or their parents/guardians) and indicate that the study was conducted in compliance with an appropriate Institutional Review Board (IRB). If approval was not obtained, the authors must provide a detailed statement explaining why it was not needed.

Open science badges

JARMAC articles are eligible for open science badges recognizing publicly available data, materials, and/or preregistration plans and analyses. These badges are awarded on a self-disclosure basis .

Applying for open science badges is optional.

Articles are eligible for open science badges recognizing publicly available data, materials, and/or preregistered plans and analyses. These badges are awarded on a self-disclosure basis.

At submission, authors must confirm that criteria have been fulfilled in a signed badge disclosure form (PDF, 42KB) that must be submitted as supplemental material. If all criteria are met as confirmed by the editor, the form will then be published with the article as supplemental material.

Authors should also note their eligibility for the badge(s) in the cover letter.

For all badges, items must be made available on an open-access repository with a persistent identifier in a format that is time-stamped, immutable, and permanent. For the preregistered badge, this is an institutional registration system.

Data and materials must be made available under an open license allowing others to copy, share, and use the data, with attribution and copyright as applicable. Available badges are:

Manuscript preparation

Submission checklist.

Please complete the author formatting checklist before submitting your manuscript. The list will be useful during the final checking of an article prior to sending it to the journal for review. Please consult this Guide for Authors for further details of any item.

Journal Article Reporting Standards

Authors should review the APA Style Journal Article Reporting Standards (JARS) for quantitative , qualitative , and mixed methods . Updated in 2018, the standards offer ways to improve transparency in reporting to ensure that readers have the information necessary to evaluate the quality of the research and to facilitate collaboration and replication.

The new JARS:

recommend the division of hypotheses, analyses, and conclusions into primary, secondary, and exploratory groupings to allow for a full understanding of quantitative analyses presented in a manuscript and to enhance reproducibility;
offer modules for authors reporting on replications, clinical trials, longitudinal studies, and observational studies, as well as the analytic methods of structural equation modeling and Bayesian analysis; and
include guidelines on reporting on of study preregistration (including making protocols public); participant characteristics (including demographic characteristics; inclusion and exclusion criteria) psychometric characteristics of outcome measures and other variables, and planned data diagnostics and analytic strategy.

The guidelines focus on transparency in methods reporting, recommending descriptions of how the researcher’s own perspective affected the study, as well as the contexts in which the research and analysis took place.

Introduction

Describe the objectives of the work and provide an adequate background, but avoid a detailed literature survey or a summary of the results. Begin the first page with the title of the article, not the word Introduction. Remember that the page count applies to all introductory and discussion sections.

Provide sufficient detail to allow the work to be reproduced. Methods already published can be reported by citing the original report and describing modifications. Regardless, authors must include enough detail to make the report comprehensible. Authors must also state their method for determining sample size and report all tasks and procedures conducted prior to the last measure to be analyzed. Procedures not directly relevant to the research question can be described briefly, but they should not be omitted.

Report participant age, gender, race/ethnicity, and other relevant demographic information regarding sample characteristics.

Results should be clear and concise. Describe the outcome both in terms of the statistical analyses and in the language of the research. Include exact p values for statistical tests, measures of effect size, and confidence intervals when appropriate. For experimental reports, effects should be accompanied by their corresponding means and standard deviations, either within the text or in a table. Correlational reports should also include these descriptive statistics. Please consult the APA Style recommendations for reporting all statistical outcomes. Take care to report all experimental conditions and dependent variables associated with the research design, although less central outcomes can be described briefly in summary form or footnotes. Report all data exclusions and the method of determining sample size. Sections that are entitled "Results and Discussion" should minimize discussion. Avoid excessive use of tables and figures. Put nonessential material in "Supplementary Material."

This section should begin with a brief summary of the results in the context of the research issue and continue with a more detailed discussion of their meaning. Be sure to describe the implications of your research for both theoretical concerns and real-world situations and applications. Address important limitations in each domain, as well.

Use of inclusive language

Inclusive language acknowledges diversity, conveys respect to all people, is sensitive to differences, and promotes equal opportunities. Content should make no assumptions about the beliefs or commitments of any reader; contain nothing which might imply that one individual is superior to another on the grounds of age, gender, race, ethnicity, culture, sexual orientation, disability or health condition; and use inclusive language throughout. Authors should ensure that writing is free from bias, stereotypes, slang, reference to dominant culture and/or cultural assumptions. We advise to seek gender neutrality by using plural nouns ("clinicians, patients/clients") as default/wherever possible to avoid using "he, she," or "he/she." We recommend avoiding the use of descriptors that refer to personal attributes such as age, gender, race, ethnicity, culture, sexual orientation, disability or health condition unless they are relevant and valid. These guidelines are meant as a point of reference to help identify appropriate language but are by no means exhaustive or definitive.

Author contribution statements using CRediT

The APA Publication Manual ( 7th ed. ) , which stipulates that "authorship encompasses…not only persons who do the writing but also those who have made substantial scientific contributions to a study." In the spirit of transparency and openness, Journal of Applied Research in Memory and Cognition has adopted the Contributor Roles Taxonomy (CRediT) to describe each author's individual contributions to the work. CRediT offers authors the opportunity to share an accurate and detailed description of their diverse contributions to a manuscript.

Submitting authors will be asked to identify the contributions of all authors at initial submission according to the CRediT taxonomy. If the manuscript is accepted for publication, the CRediT designations will be published as an author contributions statement in the author note of the final article. All authors should have reviewed and agreed to their individual contribution(s) before submission.

CRediT includes 14 contributor roles, as described below:

Conceptualization : Ideas; formulation or evolution of overarching research goals and aims.
Data curation : Management activities to annotate (produce metadata), scrub data and maintain research data (including software code, where it is necessary for interpreting the data itself) for initial use and later re-use.
Formal analysis : Application of statistical, mathematical, computational, or other formal techniques to analyze or synthesize study data.
Funding acquisition : Acquisition of the financial support for the project leading to this publication.
Investigation : Conducting a research and investigation process, specifically performing the experiments, or data/evidence collection.
Methodology : Development or design of methodology; creation of models.
Project administration : Management and coordination responsibility for the research activity planning and execution.
Resources : Provision of study materials, reagents, materials, patients, laboratory samples, animals, instrumentation, computing resources, or other analysis tools.
Software : Programming, software development; designing computer programs; implementation of the computer code and supporting algorithms; testing of existing code components.
Supervision : Oversight and leadership responsibility for the research activity planning and execution, including mentorship external to the core team.
Validation : Verification, whether as a part of the activity or separate, of the overall replication/reproducibility of results/experiments and other research outputs.
Visualization : Preparation, creation and/or presentation of the published work, specifically visualization/data presentation.
Writing — original draft : Preparation, creation and/or presentation of the published work, specifically writing the initial draft (including substantive translation).
Writing — review and editing : Preparation, creation and/or presentation of the published work by those from the original research group, specifically critical review, commentary or revision: including pre- or post-publication stages.

Authors can claim credit for more than one contributor role, and the same role can be attributed to more than one author.

Math formulae and display equations

We strongly encourage you to use MathType (third-party software) or Equation Editor 3.0 (built into pre-2007 versions of Word) to construct your equations, rather than the equation support that is built into Word 2007 and Word 2010. Equations composed with the built-in Word 2007/Word 2010 equation support are converted to low-resolution graphics when they enter the production process and must be rekeyed by the typesetter, which may introduce errors.

To construct your equations with MathType or Equation Editor 3.0:

Go to the Text section of the Insert tab and select Object.
Select MathType or Equation Editor 3.0 in the drop-down menu.

If an equation has already been produced using Microsoft Word 2007 or 2010 and authors have access to the full version of MathType 6.5 or later, they can convert this equation to MathType by clicking on MathType Insert Equation. Copy the equation from Microsoft Word and paste it into the MathType box. Verify that the equation is correct, click File, and then click Update. The equation has now been inserted into your Word file as a MathType Equation.

Use Equation Editor 3.0 or MathType only for equations or for formulas that cannot be produced as Word text using the Times or Symbol font.

Computer code

Because altering computer code in any way (e.g., indents, line spacing, line breaks, page breaks) during the typesetting process could alter its meaning, we treat computer code differently from the rest of the article in the production process. Supply separate files for computer code.

In online supplemental material

Runnable source code should be included as supplemental material to the article. For more information, visit supplementing your article with online material .

In the text of the article

If authors would like to include code in the text of the published article, submit a separate file with your code exactly as it should appear, using Courier New font with a type size of 8 points. An image will be made of each segment of code in your article that exceeds 40 characters in length. (Shorter snippets of code that appear in text will be typeset in Courier New and run in with the rest of the text.) If an appendix contains a mix of code and explanatory text, please submit a file that contains the entire appendix, with the code keyed in 8-point Courier New.

Use Word's insert table function when you create tables. Using spaces or tabs in your table will create problems when the table is typeset and may result in errors.

Review APA's Journal Manuscript Preparation Guidelines before submitting your article. Tables can be placed either next to the relevant text in the article, or on separate page(s) at the end.

Preferred formats for graphics files are TIFF and JPG, and preferred format for vector-based files is EPS. Graphics downloaded or saved from web pages are not acceptable for publication. Multipanel figures (i.e., figures with parts labeled a, b, c, d, etc.) should be assembled into one file. When possible, please place symbol legends below the figure instead of to the side.

All color line art and halftones: 300 DPI
Black and white line tone and gray halftone images: 600 DPI

Line weights

Color (RGB, CMYK) images: 2 pixels
Grayscale images: 4 pixels
Stroke weight: 0.5 points

APA offers authors the option to publish their figures online in color without the costs associated with print publication of color figures.

The same caption will appear on both the online (color) and print (black and white) versions. To ensure that the figure can be understood in both formats, authors should add alternative wording (e.g., “the red (dark gray) bars represent”) as needed.

For authors who prefer their figures to be published in color both in print and online, original color figures can be printed in color at the editor's and publisher's discretion provided the author agrees to pay:

$900 for one figure
An additional $600 for the second figure
An additional $450 for each subsequent figure

Academic writing and English language editing services

Authors who feel that their manuscript may benefit from additional academic writing or language editing support prior to submission are encouraged to seek out such services at their host institutions, engage with colleagues and subject matter experts, and/or consider several vendors that offer discounts to APA authors .

Please note that APA does not endorse or take responsibility for the service providers listed. It is strictly a referral service. Use of such service is not mandatory for publication in an APA journal. Use of one or more of these services does not guarantee selection for peer review, manuscript acceptance, or preference for publication in any APA journal.

Submitting supplemental materials

APA can place supplemental materials online, available via the published article in the APA PsycArticles ® database. Please see supplementing your article with online material for more details.

List references in alphabetical order. Each listed reference should be cited in text, and each text citation should be listed in the references section.

Examples of basic reference formats:

Journal article

McCauley, S. M., & Christiansen, M. H. (2019). Language learning as language use: A cross-linguistic model of child language development. Psychological Review , 126 (1), 1–51. https://doi.org/10.1037/rev0000126

Authored book

Brown, L. S. (2018). Feminist therapy (2nd ed.). American Psychological Association. https://doi.org/10.1037/0000092-000

Chapter in an edited book

Balsam, K. F., Martell, C. R., Jones. K. P., & Safren, S. A. (2019). Affirmative cognitive behavior therapy with sexual and gender minority people. In G. Y. Iwamasa & P. A. Hays (Eds.), Culturally responsive cognitive behavior therapy: Practice and supervision (2nd ed., pp. 287–314). American Psychological Association. https://doi.org/10.1037/0000119-012

Data set citation

Alegria, M., Jackson, J. S., Kessler, R. C., & Takeuchi, D. (2016). Collaborative Psychiatric Epidemiology Surveys (CPES), 2001–2003 [Data set]. Inter-university Consortium for Political and Social Research. https://doi.org/10.3886/ICPSR20240.v8

Software/Code citation

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software , 36(3), 1–48. https://www.jstatsoft.org/v36/i03/

Wickham, H. et al., (2019). Welcome to the tidyverse. Journal of Open Source Software, 4 (43), 1686, https://doi.org/10.21105/joss.01686

All data, program code, and other methods must be appropriately cited in the text and listed in the references section.

Permissions

Authors of accepted papers must obtain and provide to the editor on final acceptance all necessary permissions to reproduce in print and electronic form any copyrighted work, including test materials (or portions thereof), photographs, and other graphic images (including those used as stimuli in experiments).

On advice of counsel, APA may decline to publish any image whose copyright status is unknown.

Download Permissions Alert Form (PDF, 13KB)

Publication policies

For full details on publication policies, including use of Artificial Intelligence tools, please see APA Publishing Policies .

APA policy prohibits an author from submitting the same manuscript for concurrent consideration by two or more publications.

See also APA Journals ® Internet Posting Guidelines .

APA requires authors to reveal any possible conflict of interest in the conduct and reporting of research (e.g., financial interests in a test or procedure, funding by pharmaceutical companies for drug research).

Download Full Disclosure of Interests Form (PDF, 41KB)

In light of changing patterns of scientific knowledge dissemination, APA requires authors to provide information on prior dissemination of the data and narrative interpretations of the data/research appearing in the manuscript (e.g., if some or all were presented at a conference or meeting, posted on a listserv, shared on a website, including academic social networks like ResearchGate, etc.). This information (2–4 sentences) must be provided as part of the author note.

Visit Open Access with APA Publishing for more information.

Artificial intelligence

When artificial intelligence (AI) is used in the drafting of a manuscript, the use of AI must be disclosed in the methods section and cited. AI cannot be named as an author on a JARMAC article.

When AI is cited in a manuscript, the author must employ the software citation template, which includes specifying in the methods section how, when, and to what extent AI was used. Authors are required to upload the full output of the AI as an appendix or supplemental material.

Visit APA Style for more information about how to cite ChatGPT .

Ethical Principles

It is a violation of APA Ethical Principles to publish "as original data, data that have been previously published" (Standard 8.13).

In addition, APA Ethical Principles specify that "after research results are published, psychologists do not withhold the data on which their conclusions are based from other competent professionals who seek to verify the substantive claims through reanalysis and who intend to use such data only for that purpose, provided that the confidentiality of the participants can be protected and unless legal rights concerning proprietary data preclude their release" (Standard 8.14).

APA expects authors to adhere to these standards. Specifically, APA expects authors to have their data available throughout the editorial review process and for at least 5 years after the date of publication.

Authors are required to state in writing that they have complied with APA ethical standards in the treatment of their sample, human or animal, or to describe the details of treatment.

Download Certification of Compliance With APA Ethical Principles Form (PDF, 26KB)

The APA Ethics Office provides the full Ethical Principles of Psychologists and Code of Conduct electronically on its website in HTML, PDF, and Word format. You may also request a copy by emailing or calling the APA Ethics Office (202-336-5930). You may also read "Ethical Principles," December 1992, American Psychologist , Vol. 47, pp. 1597–1611.

Other information

See APA’s Publishing Policies page for more information on publication policies, including information on author contributorship and responsibilities of authors, author name changes after publication, the use of generative artificial intelligence, funder information and conflict-of-interest disclosures, duplicate publication, data publication and reuse, and preprints.

Visit the Journals Publishing Resource Center for more resources for writing, reviewing, and editing articles for publishing in APA journals.

Qi Wang , PhD Cornell University Department of Human Development, NY, United States

Associate editors

Ullrich Ecker, PhD University of Western Australia, Perth, Australia

Lorraine Hope, PhD University of Portsmouth, Portsmouth, United Kingdom

Sean Kang, PhD The University of Melbourne, Melbourne, Australia

Kamala London Newton, PhD The University of Toledo, OH, United States

Daniel Reisberg, PhD Reed College, Portland, OR, United States

Karl Szpunar, PhD Ryerson University, Toronto, ON, Canada

Melanie Takarangi, PhD Flinders University, Adelaide, Australia

Editorial assistant

Nazike Mert

Peer review coordinator

Efrem Tuquabo

Editorial board members

Magdalena Abel, PhD University of Regensburg, Regensburg, Germany

Dorthe Berntsen, PhD Aarhus University, Aarhus, Denmark

Hartmut Blank, PhD University of Portsmouth, Portsmouth, United Kingdom

Susan Bluck, PhD University of Florida, FL, United States

Andrew Butler, PhD Washington University in St Louis, Saint Louis, MO, United States

Shana Carpenter, PhD Iowa State University, Ames, IA, United States

Alin Coman, PhD Princeton University, NJ, United States

Arnaud D'Argembeau, PhD University of Liège, Liège, Wallonia, Belgium

Chad Dodson, PhD University of Virginia, Charlottesville, VA, United States

Jacqueline Evans, PhD Florida International University, Miami, FL, United States

Lisa Fazio, PhD Vanderbilt University, Nashville, TN, USA

Ronald Fisher, PhD Florida International University, Miami, FL, United States

Robyn Fivush, PhD Emory University, Atlanta, GA, United States

Maryanne Garry, PhD University of Waikato, Hamilton, New Zealand

Sami Gülgöz, PhD Koç University, College of Social Sciences and Humanities, İstanbul, Turkey

Celia Harris, PhD Western Sydney University, Sydney, Australia

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Mayo Clinic scientists define new type of memory loss in older adults

Samiha Khanna

Scientists Reverse Alzheimer’s Memory Loss by Repairing Damaged Synapses

By Buck Institute for Research on Aging February 5, 2024

KIBRA-Dependent Recovery of Functional Plasticity at Synapses Despite Tau-Induced Toxicity in the Brain

Kauwe, Pareja-Navarro et al. identify a KIBRA-dependent mechanism to repair the plasticity at synapses that is dysregulated in neurons underlying the loss of memory in tauopathy. The art depicts the recovery of the functional plasticity at synapses on neurons despite tau-induced toxicity in the brain. Credit: Larissa Brown

A groundbreaking study presents a novel Alzheimer’s treatment strategy focusing on memory restoration through the repair of damaged synapses, leveraging the critical role of the KIBRA protein. This approach shows promise in reversing memory loss without directly addressing the accumulation of toxic proteins.

While newly approved drugs for Alzheimer’s show some promise for slowing the memory-robbing disease, the current treatments fall far short of being effective at regaining memory. What is needed are more treatment options targeted to restore memory, said Buck Assistant Professor Tara Tracy, PhD, the senior author of a study that proposes an alternate strategy for reversing the memory problems that accompany Alzheimer’s disease and related dementias.

Exploring New Avenues for Alzheimer’s Treatment

Since most current research on potential treatments for Alzheimer’s focuses on reducing the toxic proteins, such as tau and amyloid beta, that accumulate in the brain as the disease progresses, the team veered away from this route to explore an alternative. “Rather than trying to reduce toxic proteins in the brain, we are trying to reverse the damage caused by Alzheimer’s disease to restore memory,” said Tracy. The findings appear in the February 1 issue of The Journal of Clinical Investigation .

The work hinges on a protein called KIBRA, named because it is found in the kidney and the brain. In the brain, it is primarily localized at the synapses, which are the connections between neurons that allow memories to be formed and recalled. Research has shown that KIBRA is required for synapses to form memories, and Tracy’s team has found that brains with Alzheimer’s disease are deficient in KIBRA.

The Role of KIBRA in Memory Restoration

“We wondered how the lower levels of KIBRA affected signaling at the synapse , and whether understanding that mechanism better could yield some insight into how to repair the synapses damaged during the course of Alzheimer’s disease,” said Buck Staff Scientist Grant Kauwe, PhD, co-first author of the study. “What we identified is a mechanism that could be targeted to repair synaptic function, and we are now trying to develop a therapy based on this work.”

The team first measured the levels of KIBRA in the cerebrospinal fluid of humans. They found that higher levels of KIBRA in the cerebrospinal fluid, but lower levels in the brain, corresponded to the severity of dementia.

“We also found this amazing correlation between increased tau levels and increased KIBRA levels in the cerebrospinal fluid,” said Tracy. “It was very surprising how strong the relationship was, which really points to the role of KIBRA being affected by tau in the brain.” The team is exploring this phenomenon further, in hopes that KIBRA could be used as a biomarker of synaptic dysfunction and cognitive decline that could be useful for diagnosis, treatment planning, and tracking disease progression and response to therapy.

Promising Results from KIBRA Research

To figure out how KIBRA affects synapses, the team created a shortened functional version of the KIBRA protein. In laboratory mice that have a condition mimicking human Alzheimer’s disease, they found that this protein can reverse the memory impairment associated with this type of dementia. They found that KIBRA rescues mechanisms that promote the resilience of synapses.

“Interestingly, KIBRA restored synaptic function and memory in mice, despite not fixing the problem of toxic tau protein accumulation,” said Kristeen Pareja-Navarro, co-first author of the study. “Our work supports the possibility that KIBRA could be used as a therapy to improve memory after the onset of memory loss, even though the toxic protein that caused the damage remains.”

Along with other treatments that already exist or will come in the future, a KIBRA therapy to repair synapses could be a valuable addition. “Reducing toxic proteins is of course important, but repairing synapses and improving their function is another critical factor that could help,” said Tracy. “That’s how I see this making the biggest impact in the future.”

Reference: “KIBRA repairs synaptic plasticity and promotes resilience to tauopathy-related memory loss” by Grant Kauwe, Kristeen A. Pareja-Navarro, Lei Yao, Jackson H. Chen, Ivy Wong, Rowan Saloner, Helen Cifuentes, Alissa L. Nana, Samah Shah, Yaqiao Li, David Le, Salvatore Spina, Lea T. Grinberg, William W. Seeley, Joel H. Kramer, Todd C. Sacktor, Birgit Schilling, Li Gan, Kaitlin B. Casaletto and Tara E. Tracy, 1 February 2024, The Journal of Clinical Investigation . DOI: 10.1172/JCI169064

Other Buck researchers involved in the study are: Lei Yao, Jackson H. Chen, Ivy Wong, Helen Cifuentes, Samah Shah, and Birgit Schilling

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6 comments on "scientists reverse alzheimer’s memory loss by repairing damaged synapses".

I see sperms.

The title of this article is misleading. They did not reverse dementia. They identifies a possible (but untested) cause of dementia.

I suggest you reread the article and you will find they think they partially restored memory in mice.

The title of this article is misleading. They did not reverse dementia. They identified a possible (but untested) cause of dementia.

Steveneeds KIRBA.

So now what do we believe I had Lazer they said they could stop it but can’t reverse .What do we believe?

Stanford researchers observe memory formation in real time

By Alan Toth

Why is it that someone who hasn’t ridden a bicycle in decades can likely jump on and ride away without a wobble, but could probably not recall more than a name or two from their 3rd grade class?

This may be because physical skills — dubbed motor memories by neuroscientists — are encoded differently in our brains than our memories for names or facts.

Now, a new study by scientists with the Wu Tsai Neurosciences Institute is revealing exactly how motor memories are formed and why they are so persistent. It may even help illuminate the root causes of movement disorders like Parkinson’s disease.

“We think motor memory is unique,” said Jun Ding , an associate professor of neurosurgery and of neurology. “Some studies on Alzheimer’s disease included participants who were previously musicians and couldn’t remember their own families, but they could still play beautiful music. Clearly, there’s a huge difference in the way that motor memories are formed.”

Memories are thought to be encoded in the brain in the pattern of activity in networks of hundreds or thousands of neurons, sometimes distributed across distant brain regions. The concept of such a memory trace — sometimes called a memory engram — has been around for more than a century, but identifying exactly what an engram is and how it is encoded has proven extremely challenging. Previous studies have shown that some forms of learning activate specific neurons, which reactivate when the learned memory is recalled. However, whether memory engram neurons exist for motor skill learning remains unknown.

Ding and postdoctoral scholars Richard Roth and Fuu-Jiun Hwang wanted to know how these engram-like groups of cells get involved in learning and remembering a new motor skill.

“When you’re first learning to shoot a basketball, you use a very diverse set of neurons each time you throw, but as you get better, you use a more refined set that’s the same every time,” said Roth. “These refined neuron pathways were thought to be the basis of a memory engram, but we wanted to know exactly how these pathways emerge.”

In their new study, published July 8, 2022 in Neuron , the researchers trained mice to use their paws to reach food pellets through a small slot. Using genetic wizardry developed by the lab of Liqun Luo , a Wu Tsai Neurosciences Institute colleague in the Department of Biology, the researchers were able to identify specific neurons in the brain’s motor cortex — an area responsible for controlling movements — that were activated during the learning process. The researchers tagged these potential engram cells with a fluorescent marker so they could see if they also played a role in recalling the memory later on.

When the researchers tested the animals’ memory of this new skill weeks later, they found that those mice that still remembered the skill showed increased activity in the same neurons that were first identified during the learning period, showing that these neurons were responsible for encoding the skill: the researchers had observed the formation of memory engrams.

But how do these particular groups of neurons take on responsibility for learning a new task in the first place? And how do they actually improve the animal’s performance?

To answer these questions, the researchers zoomed in closer. Using two-photon microscopy to observe these living circuits in action, they observed the so-called “engram neurons” reprogram themselves as the mice learned. Motor cortex engram cells took on new synaptic inputs — potentially reflecting information about the reaching movement — and themselves formed powerful new output connections in a distant brain region called the dorsolateral striatum — a key waystation through which the engram neurons can exert refined control over the animal’s movements. It was the first time anyone had observed the creation of new synaptic pathways on the same neuron population — both at the input and the output levels — in these two brain regions.

Graphical abstract summarizing the current study

The ability to trace new memories forming in the mouse brain allowed the research team to weigh in on a long-standing debate about how skills are stored in the brain: are they controlled from one central memory trace, or engram, or is the memory redundantly stored across many different brain areas? Though this study cannot discount the idea of centralized memory, it does lend credibility to the opposing theory. Another fascinating question is whether the activation of these engram neurons is required for the performance of already learned motor tasks. The researchers speculated that by suppressing the activity of neurons that had been identified as part of the motor cortex memory engram, the mice probably still would be able to perform the task.

“Think of memory like a highway. If 101 and 280 are both closed, you could still get to Stanford from San Francisco, it would just take a lot longer,” said Ding.

These findings suggest that, in addition to being dispersed, motor memories are highly redundant. The researchers say that as we repeat learned skills, we are continually reinforcing the motor engrams by building new connections — refining the skill. It’s what is meant by the term muscle memory — a refined, highly redundant network of motor engrams used so frequently that the associated skill seems automatic.

Jun Ding, associate professor of neurology and of neurosurgery and Wu Tsai Neurosciences Institute affiliate

Ding believes that this constant repetition is one reason for the persistence of motor memory, but it’s not the only reason. Memory persistence may also be affected by a skill being associated with a reward, perhaps through the neurotransmitter dopamine. Though the research team did not directly address it in this study, Ding’s previous work in Parkinson’s disease suggests the connection.

“Current thinking is that Parkinson’s disease is the result of these motor engrams being blocked, but what if they’re actually being lost and people are forgetting these skills?” said Ding. “Remember that even walking is a motor skill that we all learned once, and it can potentially be forgotten.”

It’s a question that the researchers hope to answer in a follow-up study, because it may be the key to developing effective treatments for motor disorders. If Parkinson’s disease is the result of blocked motor memories, then patients should be able to improve their movement abilities by practicing and reinforcing these motor skills. On the other hand, if Parkinson’s destroys motor engrams and inhibits the creation of new ones — by targeting motor engram neurons and their synaptic connection observed in the team’s new study — then a completely different approach must be taken to deliver effective treatments.

“Our next goal is to understand what’s happening in movement disorders like Parkinson’s,” Ding said. “Obviously, we’re still a long way from a cure, but understanding how motor skills form is critical if we want to understand why they’re disrupted by disease.”

The research was published July 8 in Neuron: https://doi.org/10.1016/j.neuron.2022.06.006

Study authors were Fuu-Jiun Hwang, Richard H. Roth, Yu-Wei Wu, Yue Sun, Destany K. Kwon, Yu Liu, and Jun B. Ding.

The research was supported by the National Institutes of Health (NIH) and National Institute for Neurological Disease and Stroke (NINDS); the Klingenstein Foundation's Aligning Science Across Parkinson’s initiative; and GG gift fund, the Stanford School of Medicine Dean’s Postdoctoral Fellowship; and Parkinson’s Foundation Postdoctoral Fellowship.

The Science Behind Memory

Summary: Researchers explore the science behind memory and memory loss, including why forgetting things is a crucial part of memory formation.

Source: Boston College

Explaining the science behind memory and memory loss—including why forgetting is a crucial property of memory, as well as strategies that help people remember better—is the subject of a new book co-authored by Professor and Chair of Psychology and Neuroscience Elizabeth A. Kensinger.

In “Why We Forget and How to Remember Better: The Science Behind Memory,” Kensinger and Boston University Professor of Neurology Andrew E. Budson, M.D., examine how memories exist in the short term and how they get stored for longer-term access, Kensinger said.

The book explains how memory influences our behavior without our awareness, underscoring the fact that what and how we remember influences everything from our social relationships to the decisions we make on a daily basis.

“When most of us talk about our memory, we are referring to our ability to bring specific past events to mind,” said Kensinger.

“But memory is so much more than that, encompassing all the ways our past experiences influence our current thoughts and behavior.

“Everyone relies on memory, for everything from remembering how to type, to navigating a familiar environment, to remembering a favorite dish at a restaurant,” said Kensinger.

“Yet most of us are also surprised by how our memory works—sometimes we are pleasantly surprised by what we’ve managed to remember, and other times we are frustrated by what we’ve forgotten.”

Memory is an active and cyclical process, Kensinger said, analogous to building a structure out of blocks.

“As you experience an event, you’re representing different features of the event in different regions of the brain; one portion of your brain is representing the sounds, another the sights, another the emotions,” she said.

“A particular region of your brain, the hippocampus, is serving as the tape that binds those blocks together, and that stores the blueprints for how to later rebuild that memory structure.”

When we need to access that memory, we have to use the blueprints for that structure to actively rebuild memory, she said.

“Thinking of memory in this way can help to understand how memory errors and omissions can arise. It’s easy to grab an incorrect block, perhaps one that should be in another memory structure, or to omit a set of blocks that might change the overall structure or interpretation of a past event.”

Kensinger and Budson discuss memory as a cycle because, as individuals rebuild a memory, they’re likely to update it with current information—such as, has a friend changed their appearance by growing a beard, or cutting their hair? Once updated or modified, these revised blueprints are stored again.

“In this way, memory is a continually changing representation; it is not a static representation of the past,” said Kensinger.

At a time of increased attention to memory and brain health, Why We Forget examines a range of cognitive issues that affect people on a daily basis: changes that accompany normal aging, Alzheimer’s disease, depression, anxiety, PTSD, ADHD, and other disorders—including COVID brain fog.

As they incorporated their own findings, as well as the body of research on the subject, the co-authors were surprised to discover that memory is not really about the past.

“Memory can be thought of as a powerful source of data that the brain can use to make sense of the present moment and to make predictions about the future,” Kensinger said.

“Memory holds onto the features that are going to be the most useful pieces of data for the brain to use for these purposes. Most of the time, those features don’t include very specific details about an experience but rather are broader representations of the gist or general concept of what happened.”

“Why We Forget and How to Remember Better” offers evidence-based lessons and strategies readers can use to improve their memory, including:

Ways to control what you remember and what you forget
Ways to distinguish between a true and false memory
Effective methods to study for an exam
How exercise, nutrition, alcohol, cannabis, sleep, mindfulness and music affect memory
How to remember people’s names, 50 digits of Pi and anything else you desire

“We hope that by reading this book, individuals will come to understand their memories in a broader way and will benefit from science-backed strategies to minimize unwanted forgetting,” said Kensinger.

About this memory research news

Author: Press Office Source: Boston College Contact: Press Office – Boston College Image: The image is in the public domain

Name of the book please

So is Kensinger the name of the professor or the name of the school?

book co-authored by Professor and Chair of Psychology and Neuroscience Elizabeth A. Kensinger

I am interested to learn more about the brain functions and how to improve my mindset,memory, behaviours,taking new habits and learn new things with efficiency.

Comments are closed.

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Study across multiple brain regions discerns Alzheimer’s vulnerability and resilience factors

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Two panels show blue cells on a black background. Some cells have magenta and green speckles. Below, each panel two subpanels show magnified views.

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An open-access MIT study published today in Nature provides new evidence for how specific cells and circuits become vulnerable in Alzheimer’s disease, and hones in on other factors that may help some people show resilience to cognitive decline, even amid clear signs of disease pathology.

To highlight potential targets for interventions to sustain cognition and memory, the authors engaged in a novel comparison of gene expression across multiple brain regions in people with or without Alzheimer’s disease, and conducted lab experiments to test and validate their major findings.

Brain cells all have the same DNA but what makes them differ, both in their identity and their activity, are their patterns of how they express those genes. The new analysis measured gene expression differences in more than 1.3 million cells of more than 70 cell types in six brain regions from 48 tissue donors, 26 of whom died with an Alzheimer’s diagnosis and 22 of whom without. As such, the study provides a uniquely large, far-ranging, and yet detailed accounting of how brain cell activity differs amid Alzheimer’s disease by cell type, by brain region, by disease pathology, and by each person’s cognitive assessment while still alive.

“Specific brain regions are vulnerable in Alzheimer’s and there is an important need to understand how these regions or particular cell types are vulnerable,” says co-senior author Li-Huei Tsai , Picower Professor of Neuroscience and director of The Picower Institute for Learning and Memory and the Aging Brain Initiative at MIT. “And the brain is not just neurons. It’s many other cell types. How these cell types may respond differently, depending on where they are, is something fascinating we are only at the beginning of looking at.”

Co-senior author Manolis Kellis , professor of computer science and head of MIT’s Computational Biology Group, likens the technique used to measure gene expression comparisons, single-cell RNA profiling, to being a much more advanced “microscope” than the ones that first allowed Alois Alzheimer to characterize the disease’s pathology more than a century ago.

“Where Alzheimer saw amyloid protein plaques and phosphorylated tau tangles in his microscope, our single-cell ‘microscope’ tells us, cell by cell and gene by gene, about thousands of subtle yet important biological changes in response to pathology,” says Kellis. “Connecting this information with the cognitive state of patients reveals how cellular responses relate with cognitive loss or resilience, and can help propose new ways to treat cognitive loss. Pathology can precede cognitive symptoms by a decade or two before cognitive decline becomes diagnosed. If there’s not much we can do about the pathology at that stage, we can at least try to safeguard the cellular pathways that maintain cognitive function.”

Hansruedi Mathys, a former MIT postdoc in the Tsai Lab who is now an assistant professor at the University of Pittsburgh; Carles Boix PhD '22, a former graduate student in Kellis’s lab who is now a postdoc at Harvard Medical School; and Leyla Akay, a graduate student in Tsai’s lab, led the study analyzing the prefrontal cortex, entorhinal cortex, hippocampus, anterior thalamus, angular gyrus, and the midtemporal cortex. The brain samples came from the Religious Order Study and the Rush Memory and Aging Project at Rush University.

Neural vulnerability and Reelin

Some of the earliest signs of amyloid pathology and neuron loss in Alzheimer’s occur in memory-focused regions called the hippocampus and the entorhinal cortex. In those regions, and in other parts of the cerebral cortex, the researchers were able to pinpoint a potential reason why. One type of excitatory neuron in the hippocampus and four in the entorhinal cortex were significantly less abundant in people with Alzheimer’s than in people without. Individuals with depletion of those cells performed significantly worse on cognitive assessments. Moreover, many vulnerable neurons were interconnected in a common neuronal circuit. And just as importantly, several either directly expressed a protein called Reelin, or were directly affected by Reelin signaling. In all, therefore, the findings distinctly highlight especially vulnerable neurons, whose loss is associated with reduced cognition, that share a neuronal circuit and a molecular pathway.

Tsai notes that Reelin has become prominent in Alzheimer’s research because of a recent study of a man in Colombia. He had a rare mutation in the Reelin gene that caused the protein to be more active, and was able to stay cognitively healthy at an advanced age despite having a strong family predisposition to early-onset Alzheimer’s. The new study shows that loss of Reelin-producing neurons is associated with cognitive decline. Taken together, it might mean that the brain benefits from Reelin, but that neurons that produce it may be lost in at least some Alzheimer’s patients.

“We can think of Reelin as having maybe some kind of protective or beneficial effect,” Akay says. “But we don’t yet know what it does or how it could confer resilience.”

In further analysis the researchers also found that specifically vulnerable inhibitory neuron subtypes identified in a previously study from this group in the prefrontal cortex also were involved in Reelin signaling, further reinforcing the significance of the molecule and its signaling pathway.

To further check their results, the team directly examined the human brain tissue samples and the brains of two kinds of Alzheimer’s model mice. Sure enough, those experiments also showed a reduction in Reelin-positive neurons in the human and mouse entorhinal cortex.

Resilience associated with choline metabolism in astrocytes

To find factors that might preserve cognition, even amid pathology, the team examined which genes, in which cells, and in which regions, were most closely associated with cognitive resilience, which they defined as residual cognitive function, above the typical cognitive loss expected given the observed pathology.

Their analysis yielded a surprising and specific answer: across several brain regions, astrocytes that expressed genes associated with antioxidant activity and with choline metabolism and polyamine biosynthesis were significantly associated with sustained cognition, even amid high levels of tau and amyloid. The results reinforced previous research findings led by Tsai and Susan Lundqvist in which they showed that dietary supplement of choline helped astrocytes cope with the dysregulation of lipids caused by the most significant Alzheimer’s risk gene, the APOE4 variant. The antioxidant findings also pointed to a molecule that can be found as a dietary supplement, spermidine, which may have anti-inflammatory properties, although such an association would need further work to be established causally.

As before, the team went beyond the predictions from the single-cell RNA expression analysis to make direct observations in the brain tissue of samples. Those that came from cognitively resilient individuals indeed showed increased expression of several of the astrocyte-expressed genes predicted to be associated with cognitive resilience.

Microscope images show astrocyte cells with magenta staining. Small blue dots are visible around some of the astrocyte cells and those dots are indicated by large white arrows.

Previous item Next item

New analysis method, open dataset

To analyze the mountains of single-cell data, the researchers developed a new robust methodology based on groups of coordinately-expressed genes (known as “gene modules”), thus exploiting the expression correlation patterns between functionally-related genes in the same module.

“In principle, the 1.3 million cells we surveyed could use their 20,000 genes in an astronomical number of different combinations,” explains Kellis. “In practice, however, we observe a much smaller subset of coordinated changes. Recognizing these coordinated patterns allow us to infer much more robust changes, because they are based on multiple genes in the same functionally-connected module.”

He offered this analogy: With many joints in their bodies, people could move in all kinds of crazy ways, but in practice they engage in many fewer coordinated movements like walking, running, or dancing. The new method enables scientists to identify such coordinated gene expression programs as a group.

While Kellis and Tsai’s labs already reported several noteworthy findings from the dataset, the researchers expect that many more possibly significant discoveries still wait to be found in the trove of data. To facilitate such discovery the team posted handy analytical and visualization tools along with the data on Kellis’s website .

“The dataset is so immensely rich. We focused on only a few aspects that are salient that we believe are very, very interesting, but by no means have we exhausted what can be learned with this dataset,” Kellis says. “We expect many more discoveries ahead, and we hope that young researchers (of all ages) will dive right in and surprise us with many more insights.”

Going forward, Kellis says, the researchers are studying the control circuitry associated with the differentially expressed genes, to understand the genetic variants, the regulators, and other driver factors that can be modulated to reverse disease circuitry across brain regions, cell types, and different stages of the disease.

Additional authors of the study include Ziting Xia, Jose Davila Velderrain, Ayesha P. Ng, Xueqiao Jiang, Ghada Abdelhady, Kyriaki Galani, Julio Mantero, Neil Band, Benjamin T. James, Sudhagar Babu, Fabiola Galiana-Melendez, Kate Louderback, Dmitry Prokopenko, Rudolph E. Tanzi, and David A. Bennett.

Support for the research came from the National Institutes of Health, The Picower Institute for Learning and Memory, The JPB Foundation, the Cure Alzheimer’s Fund, The Robert A. and Renee E. Belfer Family Foundation, Eduardo Eurnekian, and Joseph DiSabato.

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Mayo Clinic researchers define a new memory loss syndrome often mistaken for Alzheimer’s

ROCHESTER, Minn. (KTTC) – According to Mayo Clinic , more than six million people in the United States age 65 and older live with Alzheimer’s Disease .

Researchers here at home have established new criteria for a memory loss syndrome often mistake for Alzheimer’s Disease, and they think it could be quite common.

“Prior to introducing this new concept of LANS we really wouldn’t be able to help them very much and we would say I don’t know what you have its not Alzheimer’s disease though,” Dr. David Jones.

Mayo Clinic researchers are learning more about Limbic-Predominant Amnestic Neurodegenerative Syndrome or LANS, which according to Dr. David Jones, can often be mistaken for Alzheimer’s only it’s far milder.

“It will allow us to finally find a cure for these conditions tailored to the way in which the degeneration is occurring,” Dr. Jones said.

Alzheimer’s attacks the brain’s neocortex, whereas Dr. Nick Corriveau-Lecavalier explains LANS impacts the limbic system which involves your emotions and behaviors.

“A memory dominant profile, very little involvement of the cortex in language, behavior, executive function and so on,” Dr. Corriveau-Lecavalier said.

There are multiple causes, but a protein called TDP-43 is what researchers say is the main culprit.

One patient’s case has stuck with Dr. Jones throughout his studies.

“It made sense to me that we would find the TDP at autopsy, I followed her for many years. She did end up donating her brain to the research program and we found the TDP protein,” Dr. Jones explained.

The protein can only be detected through an autopsy, but with the new clinical criteria, there will be dedicated research studies to help diagnosed those living with memory loss.

“Now, we can not only start to give them answers but now we can start to do research to find better treatments,” Dr. Jones said.

Researchers said they believe LANS may be common in older adults but don’t want to give out numbers until there has been proper, widespread research.

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J Gerontol B Psychol Sci Soc Sci

Theories of Memory and Aging: A Look at the Past and a Glimpse of the Future

The present article reviews theories of memory and aging over the past 50 years. Particularly notable is a progression from early single-mechanism perspectives to complex multifactorial models proposed to account for commonly observed age deficits in memory function. The seminal mechanistic theories of processing speed, limited resources, and inhibitory deficits are discussed and viewed as especially important theories for understanding age-related memory decline. Additionally, advances in multivariate techniques including structural equation modeling provided new tools that led to the development of more complex multifactorial theories than existed earlier. The important role of neuroimaging is considered, along with the current prevalence of intervention studies. We close with predictions about new directions that future research on memory and aging will take.

One of the most striking aspects of aging is that memory processes show decline. This was recognized as early as 700 BC by Solon, a Greek philosopher who, in his Elegy on the Ages of Men , noted that intellectual capacities began to diminish around age 56–63 (see Cokayne, 2003 ). Moreover, Virgil, a Roman poet, alluded to the degradation in memory over time in Eclogues IX , writing, “Time robs us of all, even of memory” ( Cokayne, 2003 , p. 67). Although some level of cognitive frailty has always been viewed as an aspect of aging, the study of cognitive aging came into its own right as the science of human behavior advanced and as significant increases in human longevity were realized. Today the study of memory and aging has taken on particular significance and is a center-stage issue due primarily to the increased longevity resulting from the heightened ability to extend life in the face of major diseases. Indeed, due to longevity, Alzheimer’s disease has become a major cause of death and disability for society today, sparking a quest to develop early interventions to prevent or delay neuropathological aging.

In the present article, we review major theories of aging and memory and how they have emerged over the past 50 years (see Figure 1 for a depiction of the exponential growth in research on memory and aging from 1965 to 2013). We start by discussing some of the earliest empirical findings on aging and memory and follow by reviewing initial theoretical explanations for these findings. These early theories were surprisingly insightful, and many versions of them are still viable today. Contemporary models of memory decline build upon these early influential theories, and many have also begun to show a shift toward the brain. Hence, we summarize prominent mechanisms that have been hypothesized to explain why memory declines as we get older, noting early theories that are still dominant today along with newer theories that place additional focus on neural contributions to memory impairment. We also discuss specific memory domains that appear to be more age invariant. Finally, we close with current trends in the field of memory and aging, providing reflections on what we expect for future research.

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Depiction of the exponential increase in research on memory and aging. The number of articles published each year is plotted, after using Medline trend: Automated yearly statistics of PubMed results for any query ( Corlan, 2004 ) and the query terms “memory” and “age”. Website: http://dan.corlan.net/medline-trend.html

Early Evidence of Memory Impairment with Age

Some of the earliest findings about age differences in memory stem directly from verbal learning paradigms, which dominated the study of human memory when psychology was in the grip of behaviorism. In 1929, Willoughby documented a gradual age-related differences in incidental memory for digit–symbol pairs, such that recall decreased from age 20 through age 70. Moreover, using an intentional paired-associate learning paradigm, Ruch (1934) demonstrated that adults aged 60–82 years exhibited worse memory than adults aged 34–59 years, and that 12- to 17-year-olds displayed the best performance (for a detailed review, see Kausler, 1991 ). Some early work also assessed strategy use and noted that, compared with younger adults, older adults were less likely to use imagery or to create verbal mnemonics when attempting to remember paired associates ( Hulicka & Grossman, 1967 ). Furthermore, older adults took longer to learn newly re-paired paired associates to criterion in an A–B A–C list-learning paradigm, indicating either greater negative transfer (i.e., interference) for older participants or greater positive transfer from repeated cue presentations in younger adults ( Arenberg, 1967 ).

Another major early finding was that memory effects associated with age were typically larger when participants were asked to recall a list of words, compared with merely recognize them (e.g., Schonfield, 1965 ; Smith, 1977 ). Schonfield (1965) reported that older adults had equivalent recognition performance to younger adults but markedly impaired recall (but see e.g., Erber, 1974 ; Harwood & Naylor, 1969 , who report both impaired recall and impaired recognition in older adults). Also of interest was that picture memory appeared to be protected from dramatic age effects, as older adults recalled and recognized pictures better than words (e.g., Park, Puglisi, & Sovacool, 1983 ). Perhaps the most well-recognized finding of all was that on virtually any task that had a speed component, participants became slower with age (e.g., Brinley, 1965 ). Given these empirical results, scientists began proposing mechanistic theories to account for the commonly observed age differences in memory.

Theoretical Models of Aging and Memory Decline

Speed of processing as a mechanism of memory decline.

The initial theories on speed were pioneered by James Birren, and then by John Cerella and Timothy Salthouse (e.g., Birren, 1965 ; Birren, Woods, & Williams, 1980 ; Cerella, 1985 ; Salthouse, 1996 ). In an early study, Birren noted that participants showed increasingly slower processing time for a broad range of cognitive tasks as a function of age ( Birren, 1965 ), resulting in the hypothesis that slowed processing speed was a fundamental mechanism that governed many age deficits, including memory. Cerella suggested that slowing resulted from deletion of random links in the memory network, which created longer, more circuitous memorial processing paths ( Cerella, 1990 ). In a large corpus of work beginning in the 1980s, Salthouse further validated and expanded this notion that processing speed was fundamental to explain age differences in memory ( Salthouse, 1985a , 1985b , 1996 ). His view is best summarized in an article where he proposes that older adults are deficient in two important mechanisms that account for age-related differences in attention, memory, and reasoning ( Salthouse, 1996 ). He posited a limited time mechanism , in which older adults have greater difficulty performing higher-level operations because it takes them longer to process early operations, and a simultaneity mechanism , in which older adults cannot consider as many task-relevant components together compared with younger adults because the products of earlier processing may not be available once ongoing processing is completed. Salthouse repeatedly showed that most age-related variance in cognitive tasks, including memory, could be accounted for by measures of speed.

The Processing Resource Model of Memory Deficits in Cognitive Aging

Age differences in levels of processing.

In 1972, Craik and Lockhart presented the levels of processing theory of memory, which marked an important transition between basic stimulus–response verbal learning to the study of mental models. They provided evidence that an intention to learn was not the most critical component for remembering. Rather, it was the quality of the encoding operation—not the time on task—that best predicted memory. Specifically, they reported that guiding participants to engage in deep semantic processing, even when they were not intentionally trying to remember, resulted in memory recall that was equivalent or superior to that of participants who were actively studying (see also Hyde & Jenkins, 1969 ). The finding that quality of processing could be more important than intention to learn was highly influential in the research community and led to the notion that older adults were deficient in spontaneously engaging in deep processing, as age effects were particularly large when learning was intentional. The inefficiency of older adults spontaneously performing higher-level encoding strategies was termed the production deficit hypothesis ( Kausler, 1970 ). If, however, older adults were guided to process meaning and engage in elaborative encoding, memory could be repaired to be more similar to that of younger adults.

Environmental support

The notion that cognition could be repaired led logically to the concept of environmental support. Environmental support, also termed contextual support, involved the presentation of external cues or processing guidance, which provided “mental crutches” that made stimuli easier to remember, especially for older adults (e.g., Craik, 1986 ). For example, if during a list-learning experiment one was presented with the word “feather” to remember, the provision of the cue word “chicken” at encoding would be a type of environmental support that would facilitate recall of the studied word at test. Experimental research has demonstrated that older adults tend to have better memory when external cues are provided (e.g., Craik & McDowd, 1987 ; Smith, 1977 ). However, even when environmental support is afforded, age differences may be reduced but not entirely alleviated (e.g., Park & Shaw, 1992 ). There is a lengthy literature suggesting that the amount of mental effort required to effectively utilize environmental support determines its effectiveness in minimizing age deficits. For instance, fewer age deficits are observed in familiar situations, whereas novel experiences that require substantial self-initiated processing are more difficult for older adults (e.g., see Craik, 1994 ; Park & Gutchess, 2000 ).

Age-limited processing resources

The discovery that external cues could facilitate memory for older adults contributed to two further theoretical mechanisms of age-related memory decline. First was the hypothesis that older adults possessed fewer processing resources , also termed attentional resources and mental energy , and that the limited availability of processing resources served to restrict the quality and quantity of memory operations ( Craik & Byrd, 1982 ). Older adults’ limited resources were subsequently proposed to induce general processing that led to retention of broad semantic information but left a deficit in specificity (e.g., Rabinowitz & Ackerman, 1982 ; Rabinowitz, Craik, & Ackerman, 1982 ). Under conditions of divided attention (i.e., thought to mimic the inherent impoverished processing capacity of older adults), younger adults were argued to show more general encoding because they exhibited better memory with general as opposed to specific retrieval cues ( Rabinowitz et al., 1982 ). However, additional research questioned the validity of this general encoding theory due to inconsistent and incompatible findings (see Light, 1991 ). For example, Park, Puglisi, Smith, and Dudley (1987) varied the presence or absence of pictorial cues at encoding and retrieval and found that younger and older adults were equally aided by specific encoding and retrieval cues, indicating similar usage of contextual information, and that even when resources were limited by divided attention, older and younger adults still showed equivalent patterns of memory facilitation from specific cues.

Shortly following this general encoding debate, there was burgeoning interest in false memories and the increased susceptibility of older adults to remember information that was never presented but that was semantically similar to the studied material (e.g., Norman & Schacter, 1997 ). Despite the concerns about the validity of general encoding in describing verbal learning, the false memory literature, nevertheless, made it clear that older adults tended to rely on gist at the expense of detail.

The issue of whether age-limited processing resources served as an important mechanism of age-related memory deficits reached a head after publication of a chapter by Leah Light (1988) , where she criticized the circularity of the theory. The limited resource explanation was routinely invoked when older adults showed poor memory performance, yet there was no independent measure or evidence that processing resource was actually depleted. This argument triggered a paradigm shift in the study of cognitive aging. Researchers began focusing on the measurement of individual resource pools that participants possessed, examining candidate cognitive primitives that could be the instantiation of the “limited resource” (i.e., working memory, attention, processing speed, executive function).

This movement gained further momentum by the great success Timothy Salthouse had in using speed as an individual differences variable that accounted for considerable age-related variance on memory tasks ( Salthouse, 1985b , 1996 ). That is, processing speed could be the limited resource sought by researchers. Serendipitously, around the same time, Baddeley and Hitch (1974) developed their model of working memory, which posited two separate resource pools (visuospatial and verbal), which were controlled by a central executive system. This model became a prominent way to envision the structure of the mind. Working memory, which was a combination of storage and processing capacity, quickly became viewed as an excellent way to measure processing resource, independent of any specific experimental manipulations. Arthur Wingfield and Elizabeth Stine conducted some of the earliest work on this topic. They reported that older adults had poorer verbal working memory than younger adults, and that better verbal working memory was correlated with better vocabulary ( Wingfield, Stine, Lahar, & Aberdeen, 1988 ). In a follow-up study, they demonstrated that working memory capacity was also associated with simple text recall, confirming its potential explanatory power ( Stine & Wingfield, 1990 ). This research was followed by other articles that offered a broad perspective of additional cognitive mechanisms that could affect memory decline, such as frontal lobe function and executive control (e.g., Moscovitch & Winocur, 1995 ; West, 1996 ).

Inhibitory Theory of Memory Deficits With Age

Like Craik and Lockhart (1972) ’s article, Hasher and Zacks (1988) ’s theorizing on inhibition represented an important innovation that forever changed the way memory was conceptualized. Reminiscent of Rabbitt (1965) ’s finding that older adults had difficulty ignoring irrelevant information, Hasher and Zacks proposed the hypothesis that the ability to suppress attention to irrelevant thoughts within working memory was an important predictor of episodic memory. Inhibition, they argued, served to reduce the activation level of off-goal-path thoughts in working memory, and facilitated efficient memorial processing. Older adults were thought to be deficient in inhibition, and, consequently, to be easily distracted and to focus on contextual information at the expense of target information. Poor inhibition was posited to lead to a cluttered working memory that also had limited capacity for the entrance of new relevant information. Moreover, this “mental clutter” amplified competition during memory retrieval, which contributed to higher intrusion rates and heightened memorial interference in older adults. This inhibitory theory was very influential for the field, and it still plays a big role today.

Disuse, Motivational, and Other Noncognitive Theories

Although not the most prominent, certain noncognitive theories were also hypothesized to explain age-related memory deficits. It was suggested that perhaps older adults exhibited differential memory performance due to (a) lower motivation, (b) reduced memory self-efficacy, (c) greater test anxiety, (d) different performance goals, (e) greater time out of school, (f) lower formal education, and (g) poorer health. Although these factors may have influenced performance under certain conditions, there was little support that these noncognitive factors contributed entirely to age-related memory differences, especially because not all domains of memory exhibited similar deficits (i.e., implicit memory, semantic memory; see Burke & Light, 1981 ; Light, 1991 ) and because age effects were observed in samples matched on health and education (see Kausler, 1991 ). Consequently, these noncognitive hypotheses have not played a major role in theories of memory and aging.

Age Invariance in Specific Memory Domains

Not all research was focused on mechanisms of memory differences. Some research sought to identify and explain age-invariant memory domains, that is, domains in which memory performance was equivalent for younger and older adults. In an early instantiation of this concept, Hasher and Zacks (1979) suggested that certain stimulus attributes were encoded automatically and, consequently, showed little effect of age. They reported that both younger and older adults had equivalent memory for the frequency and spatial location of words, whereas older adults demonstrated decreased memory for the words themselves. Later work suggested, however, that age differences could be observed in spatial memory if the tasks were sufficiently demanding (e.g., Park, Puglisi, & Lutz, 1982 ; Puglisi, Park, Smith, & Hill, 1985 ).

Semantic memory was also initially considered to be relatively age invariant. Darlene Howard and colleagues showed comparable semantic memory as a function of age (e.g., Howard, Lasaga, & McAndrews, 1980 ), as did Lars Nyberg, who found age differences for episodic but not semantic memory ( Nyberg, Bäckman, Erngrund, Olofsson, & Nilsson, 1996 ). Nevertheless, under conditions of higher demand, semantic memory deficits appeared. For example, Bowles and Poon (1985) found no evidence for age effects during easy lexical decisions, but when the task required active retrieval of words based on provided definitions, age differences were observed. Similarly, event-based prospective memory was originally claimed to be age invariant (e.g., Einstein & McDaniel, 1990 ), but later studies called this into question (e.g., Park, Hertzog, Kidder, Morrell, & Mayhorn, 1997 ). An analogous pattern of results occurred for picture memory. Early work in this domain suggested that old and young performed similarly on tests of complex picture recognition of real-world scenes ( Park, Puglisi, & Smith, 1986 ). However, later work showed that age effects were evident when the pictures were abstract ( Smith, Park, Cherry, & Berkovsky, 1990 ) and when they required active integration of target and context ( Park, Smith, Morrell, Puglisi, & Dudley, 1990 ).

There are two interesting points about the appealing possibility that some types of memory are protected from the effects of aging. First and most importantly, in retrospect, the question of whether age effects could be observed in each of these domains was not the most crucial question. Rather, the critical focus should have been whether the magnitude of the age effects differed for various types of memory (it did). Second, if so, what mechanism(s) contributed to the observed differences? For each of the domains just discussed, subsequent work yielded evidence that the demands of a given task were more important than the domain of the task, providing strong support for the notion of cognitive resource limitations being the basis for age-related memory dysfunction. That is, when the difficulty of these tasks was increased, age effects were apparent (i.e., Bowles & Poon, 1985 ; Puglisi et al., 1985 ). The findings from each of these memory domains posed perplexing results for current memory theories, and ultimately pointed toward lower resource requirements for tasks where age invariance was observed.

Inadequacy of Single-mechanism Theories of Age-related Memory Decline

At this point, the field of memory and aging was confronted with multiple rich theoretical viewpoints (i.e., speed, limited resources, inhibition) that plausibly accounted for age-related memory decline. The research was dominated by experimental psychology paradigms that relied on systematic manipulation of variables and analysis of variance techniques to compare performance between younger and older adults. Based on this approach, troubling studies were presented by each theorist that could be explained by their mechanism of choice but not by other models. Discussion of these competing theories was at a fever pitch in the research community, with resolution of which theory was actually correct seemingly unresolvable. Auspiciously, an alternate data analysis approach emerged that simultaneously considered multiple possible antecedents of age-related memory decline and offered a fresh viewpoint—one that allowed for multiple theories to be correct.

There were a number of research groups working on theories of intelligence and aging led by luminaries such as K. Warner Schaie, John Horn, Earl Hunt, and Christopher Hertzog. They began developing nonexperimental, interrelated models of the aging mind that relied on individual differences, multiple constructs, and structural equation modeling to predict cognitive performance (e.g., Hertzog, 1985 ; Horn, 1989 ). Individual differences research made it increasingly obvious that the mechanisms underlying memory and aging were multifactorial, and these new modeling approaches allowed for complex multicausal views of age-related deficits in memory. For the next several years, many influential articles in cognitive aging would take a broad individual differences approach, measuring numerous mechanisms purported to underlie memory function and using structural equation models to predict memory performance.

One article that illustrates this transition was by Park and colleagues (1996) . In this article, multiple measures of speed and working memory were used to predict three types of memory that varied in their degree of environmental support: spatial recall (which was hypothesized to be more automatic), cued recall (which provided some environmental support), and free recall (which required the most mental effort). Speed and working memory constructs provided independent measures of two types of cognitive resource. The resulting model demonstrated that speed contributed to all three types of memory. However, working memory explained additional variance in the two more effortful memory tasks: cued recall and free recall. This result provided support both for the fundamental nature of speed (see also e.g., Lindenberger, Mayr, & Kliegl, 1993 ) and for the additional role that working memory contributed for demanding memory tasks. In a later article, Hedden, Lautenschlager, and Park (2005) demonstrated that both processing resource and knowledge were important mechanisms for successful memory, but their relative contributions varied as a function of task and age. Processing resource (i.e., speed + working memory) explained significant variance in free recall, cued recall, and verbal fluency, whereas knowledge was only related to verbal fluency and cued recall. Moreover, knowledge was more important for older than younger adults in explaining variance in cued recall, suggesting that older adults increasingly rely on knowledge to compensate for processing declines.

Overall, this multifaceted theoretical approach helped identify particular constructs that were most critical in accounting for large amounts of age-related variance in memory, while also delineating the inadequacy of single-mechanism theories of memory. Unquestionably, the construct that controlled the most age-related variance in cognition was speed, even when modeled with measures of resource (i.e., working memory) and measures of crystallized knowledge (i.e., vocabulary). Thus, along with the realization that multiple factors could influence observed age-related memory effects, speed was confirmed as perhaps the most important contributor to age differences in memory.

Insights From Neuroimaging

The next innovation that transformed the conceptualization of memory was the introduction of structural and functional neuroimaging. In the following sections, we briefly note how theories of memory and aging were influenced by neuroimaging.

The advent of magnetic resonance imaging allowed researchers to measure the volume of brain structures in older adults and to relate these measures to memory performance. Naftali Raz conducted influential work in this domain and demonstrated that older adults with smaller brain volume (i.e., hippocampal, parahippocampal) tended to have impaired explicit memory (e.g., Raz, Gunning-Dixon, Head, Dupuis, & Acker, 1998 ; although Raz & Rodrigue, 2006 note that these effects are modest). Analysis of white matter integrity further revealed poorer memory in older adults with white matter hyperintensities (e.g., DeCarli et al., 1995 ; Van Petten et al., 2004 ). Starting in the 2000s, researchers were additionally able to examine the quality of specific white matter tracts in the brain with diffusion tensor imaging, revealing some associations between white matter connectivity and memory in older adults (see Madden, Bennett, & Song, 2009 ). Thus, structural imaging methods enabled links to be drawn between brain structure and memory performance, helping identify physiological factors that were related to age-related memory differences.

Functional neuroimaging also offered insights into how the aging brain performed encoding and retrieval processes. One influential finding was that, under certain task conditions, older adults exhibited greater levels of neural activity than younger adults (e.g., Cabeza et al., 1997 ; Reuter-Lorenz et al., 2000 ). Given that most other age effects documented decrements in older versus younger groups, this somewhat counterintuitive finding led to the hypothesis that older adults might be recruiting additional neural resources to compensate for other neural inefficiency and to boost performance (e.g., Cabeza, 2002 ; Reuter-Lorenz & Cappell, 2008 ). Questions remain about whether this pattern of activation truly reflects compensation (e.g., see Kalpouzos, Persson, & Nyberg, 2012 ). Nevertheless, the ability to track changes in neural reactivity in response to task demands gave cognitive neuroscientists the ability to posit brain-based functional theories of memory and aging.

Other biological factors such as altered neurotransmission and vascular dysfunction have been proposed to contribute to age-related memory differences (e.g., see Bäckman, Nyberg, Lindenberger, Li, & Farde, 2006 ; Braver et al., 2001 ; Buckner, 2004 ). Moreover, the development of in vivo β-amyloid and tau imaging has allowed researchers to examine the relationship between neuropathological insults and memory, even in cognitively normal older adults. Greater levels of amyloid have been associated with worse episodic memory ( Hedden, Oh, Younger, & Patel, 2013 ), deficits in other domains of cognition (e.g., Rodrigue et al., 2012 ), and altered patterns of functional activation during memory encoding (e.g., Kennedy et al., 2012 ; Mormino et al., 2012 ). Although tau imaging is still very new, theories posit that greater levels of tau may also be linked with impaired memory (see Villemagne & Okamura, 2016 ). Ongoing work in this field will help characterize the neuropathology associated with memory performance and the transition from normal aging to Alzheimer’s disease.

In addition to continued research utilizing neuroimaging, which will help characterize biological underpinnings of memory impairment in old age, and to experimental psychology methods, which will continue to critically inform theories of memory and aging, additional focus has turned to applied methods for improving memory across the adult life span. Considerable attention has been given to intervention techniques (i.e., cognitive training, lifestyle adjustments) to boost cognitive function and delay the onset of memory decline. We note, however, that the field of cognitive training is still very young, and continued rigorous scientific studies are needed to determine the reliability, breadth, and duration of training effects.

One of the earliest and most influential intervention studies was an offshoot of the Seattle Longitudinal Study, when Sherry Willis imbedded a cognitive training program within the fifth cycle (see Schaie & Willis, 2010 ). This work provided the foundation for later training efforts, including the ACTIVE trial, which reported improvements in speed, reasoning, and memory after 10 sessions of targeted cognitive training ( Ball et al., 2002 ). Additional intervention studies were founded upon models of cognitive reserve, which posit that certain lifestyle and health factors can influence current cognition and longitudinal cognitive change (e.g., Reuter-Lorenz & Park, 2014 ; Tucker & Stern, 2011 ). As such, some interventions have been developed to determine whether increasing protective factors can heighten memory. Work from our own lab documented increases in episodic memory in older adults who learned complex new skills, such as digital photography or how to use an iPad ( Chan, Haber, Drew, & Park, 2014 ; Park et al., 2014 ). We envision that cognitive aging researchers will maintain their interest in training studies and that additional experimental work will help characterize the conditions under which neural plasticity can be exploited to improve memory.

Related to cognitive reserve is the concept of brain maintenance. Nyberg, Lovden, Riklund, Lindenberger, and Bäckman (2012) propose that successful agers maintain brains that are similar to those of young adults. Whereas cognitive reserve theories center more on characteristics that enable people to retain cognitive function in the face of neuropathological changes, brain maintenance considers what factors reduce functional, anatomical, and neurochemical brain changes in the first place. Future research will undoubtedly consider predictors of brain maintenance and how they relate to preservation of memory with age.

Neurostimulation has also garnered recent interest as a possible method to enhance memory. Researchers have begun examining the influence of transcranial direct current stimulation (tDCS), a noninvasive technique involving the passage of a small electrical current (i.e., 1–2 mA) through the brain, traveling between two electrodes placed on the surface of the head. Thus far, several studies have documented memorial benefits of tDCS in young adults and at least one older adult sample (see Coffman, Clark, & Parasuraman, 2014 ). Moreover, one study noted improved verbal recognition memory in Alzheimer’s patients following tDCS ( Ferrucci et al., 2008 ). If these findings prove to be replicable and reliable, it is conceivable that such brain stimulation may become popular. Needless to say, further research is needed to determine whether this is a viable technique to abate memory decline in older adults and whether the anatomical loci of these effects will help inform theories of memory and aging.

Finally, we predict that future research will place greater emphasis on genetic risk factors and epigenetic environmental triggers that predispose individuals for memory disturbances. At present, the field has identified certain genes with influences on cognition, such as APOE, BDNF, COMT, and KIBRA (e.g., Laukka et al., 2013 ), and evidence suggests that the effects of disadvantageous genes are amplified in old age (see Papenberg, Salami, Persson, Lindenberger, & Bäckman, 2015 ). Additional research will further elucidate these relationships, tracking genetic impacts on memory and cognition throughout the life span.

Conclusions

This brief review highlights major theoretical issues in the study of memory and aging and how they changed over time. No doubt this review is selective and somewhat subjective, but it offers organizing principles for how memory and aging research unfolded. One broad theme evident in the article is that, as research developed, a multitude of variables were recognized to contribute to age-related memory deficits. The shift from early single-mechanism views to involved multifactorial models is striking, and these intricate cognitive models mirror the vast complexity of the aging brain. Advances in neuroimaging clearly delineate that there are age differences in neural structure and function that contribute to memory performance, and contemporary theorists are becoming increasingly interested in using both neural and behavioral measures to differentiate between pathological and normal age-related decline in memory. Additionally, an increased focus has been placed on identifying practical techniques to maintain memory function for life. This research on memory preservation has relied heavily on the rich depth of information generated in earlier research about basic memory function. The investment in memory and aging research over the last 50 years has provided the knowledge base needed to develop increasingly effective interventions and to identify early markers of pathological aging. Continued and sustained investment in this critically important research domain is likely to yield advances that have the potential to enhance the quality of life of both sufferers of age-related memory disorders and their families.

Preparation of this manuscript was supported by the National Institutes of Health Grant 5R37AG-006265-29 to D. C. Park. S. B. Festini is supported by the Aging Mind Foundation.

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Mild COVID-19 can cause long-term cognitive losses, finds study

by Maria Fernanda Ziegler, FAPESP

Memory loss and attention deficit are frequent complaints of people who have survived severe COVID-19, but these and other cognitive impairments have also been observed in mild cases more than 18 months after the start of the infection, according to a study by researchers at the University of São Paulo (USP) in Brazil.

The study is published in the journal BMC Psychology . The findings highlight the need for more comprehensive rehabilitation to address the enduring cognitive impacts of long COVID, the authors write.

Data collected from 302 volunteers pointed to cognitive impairment in 11.7% of mild patients, 39.2% of moderate patients and 48.9% of severe patients.

"Although the damage done by the disease in terms of memory loss , attention deficit and slow processing increases in proportion to its severity, the same problems affect a far from negligible number of people—around 100 in our study—who had mild or moderate COVID," said Antônio de Pádua Serafim, first author of the article and a professor at the Institute of Psychology (IP-USP).

The results of the study evidence the potential impact of neuroinflammation due to infection by SARS-CoV-2.

"Memory loss and attention deficit are known to be associated with post- intensive care syndrome due to intubation under deep anesthesia. Some of the data analyzed in the study, however, was from patients who didn't require intensive care or didn't even have sufficient symptoms to be hospitalized and nevertheless exhibited memory loss and attention deficit. The findings therefore opened our eyes to the question of neuroinflammation due to COVID-19," Serafim said.

Memory and attention are important cognitive functions that affect people's day-to-day lives. Reflecting this, participants in the study with poor memory and attention test scores reported difficulties with recalling words or performing routine activities, such as forgetting pots on the stove or failing to pick children up from school.

"Hierarchically speaking, attention is the primary function in all mental activity , and this explains why attention deficit has such a huge impact on people's daily lives. High-quality attention is required to think and act in various ways at the same time. Impairment of attention in turn affects memory.

"In some cases, attentional activity is so dispersed that each new stimulus [or impending activity] dissolves, so that the person can't remember what they were doing. This also affects processing activity, which involves rapid decision-making based on information," he said.

Cognitive rehabilitation

According to Serafim, all the evidence has shown for some time that SARS-CoV-2 can affect the central nervous system as well as the lungs, kidneys, heart and muscles, but the extent of the damage it may cause is poorly understood.

"We don't know if cognitive impairment due to COVID-19 is permanent, and we're currently evaluating ways to intervene in this process," he said.

In partnership with other researchers at USP, Serafim is developing programs to try to mitigate the cognitive losses caused by COVID-19. The aim is to find out whether techniques such as neurostimulation and neurofeedback can attenuate or reserve memory loss and attention deficit.

"Both are non-invasive techniques that aim to improve brain functions by means of neuromodulation, which can stimulate the connections among neurons in the brain [synapses]. We have only case studies so far. For example, in the case of a physician who was in the intensive care unit for 34 days, we conducted a neurofeedback protocol often used to study patients with attention deficit disorder, and he made a good recovery. But that was an isolated case," he said.

"Based on the knowledge we've acquired so far regarding cognitive stimulation and rehabilitation techniques, I believe it may be possible to obtain an improvement in neural connectivity by means of brain training to stimulate overall cognitive ability. The severe phase of the pandemic is over, but the sequelae persist. So it's not a closed case.

"Many people were infected, and many have sequelae of this kind. However, we don't have an effective program to intervene not only in the emotional aspects but also in the cognitive difficulties resulting from COVID-19."

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July 19, 2024

What to Know about Project 2025’s Dangers to Science

Project 2025 would jeopardize federal scientists’ independence and undermine their influence

By Ben Guarino , Andrea Thompson , Tanya Lewis & Lauren J. Young

Brendan Smialowski/AFP via Getty Images

Project 2025, the sweeping right-wing blueprint for a new kind of U.S. presidency, would sabotage science-based policies that address climate change, the environment, abortion, health care access, technology and education. It would impose religious and conservative ideology on the federal civil service to such an extent that Republican presidential candidate Donald Trump has, dubiously, tried to distance himself from the plan. But in 2022 Trump said the Heritage Foundation—the think tank that authored Project 2025—would “ lay the groundwork and detail plans for exactly what our movement will do.” The project’s main document, a lengthy policy agenda, was published the following year.

Although Trump is not among its 34 authors, more than half are appointees and staff from his time as president; the words “Trump” and “Trump Administration” appear 300 times in its pages. At least 140 former Trump officials are involved in Project 2025, according to a CNN tally . It’s reasonable to expect that a second Trump presidency would follow many of the project’s recommendations.

Project 2025 presents a long-standing conservative vision of a smaller government and describes specific, detailed steps to achieve this goal. It would shrink some federal departments and agencies while eliminating others—dividing the Centers for Disease Control and Prevention into two weaker entities, for instance, and abolishing the Department of Education (ED) entirely.

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What is even more unusual, and also mapped out in detail, is a plan to exert more presidential control over traditionally nonpartisan governmental workers—those Trump might describe as members of the “deep state,” or regulatory bureaucracy. For example, Project 2025 claims that the the National Oceanic and Atmospheric Administration and other scientific institutions are “vulnerable to obstructionism” unless appointees at these agencies are “wholly in sync” with presidential policy. To that end, it would reclassify tens of thousands of civil service jobs as political positions that answer to the president.

“The independence of science is being attacked across the board in this document,” says Rachel Cleetus, policy director of the Climate and Energy program at the nonpartisan Union of Concerned Scientists. “The importance of this science is that’s how we can ensure people’s health and the environment are being safeguarded.” (Cleetus notes that her comments address the policy agenda’s contents, not the upcoming presidential election.)

Career scientists who are now employed by the federal government are “terrified and polishing up their résumés,” says Jacqueline Simon, policy director of the American Federation of Government Employees, or AFGE, a union that represents workers at the National Institutes of Health, the Environmental Protection Agency, the CDC and other agencies. If Project 2025 becomes reality, she says, “the very idea of scientific integrity will be flushed down the toilet.” The Heritage Foundation did not respond to Scientific American ’s request for comment.

The policy handbook is not a light read. It is at turns wonkish, militant and sneering (and sometimes all three at once, such as when it calls for transforming federal institutions into “hard targets” for “woke culture warriors”). It tears down policies to curb climate change, even though a majority of Americans endorse climate action . And although there is broad support in the U.S. for laws that protect the relationships and rights of LGBTQ+ people, Project 2025 advocates for “a biblically based, social science-reinforced definition of marriage.” The Department of Health and Human Services (HHS) would become a “Department of Life” that would explicitly reject abortion and promote the heterosexual nuclear family structure as “ideal.” Below is a nonexhaustive list—Project 2025 is 922 pages long—of ways the agenda would warp scientific policies and processes that have long been integral to the country’s functioning.

Project 2025 insists abortion should not be considered health care. It seeks to undo access to medication abortion, falsely stating that the involved drugs have complication rates four times higher than that of surgical abortion. In reality, studies have shown that mifepristone, one of two drugs used in almost all medication abortions in the U.S., is extremely safe and effective . Project 2025 argues that the Food and Drug Administration should “reverse its approval of chemical abortion drugs because the politicized approval process was illegal from the start.” But earlier this year the Supreme Court ruled unanimously to dismiss a case that challenged the FDA’s approval of mifepristone on these grounds (though the conservative-majority Court did leave the door open to future challenges ). The Heritage Foundation’s plan seeks to have the FDA “stop promoting or approving mail-order abortions in violation of long-standing federal laws ,” citing laws enacted as part of the Comstock Act , despite the fact that the U.S. Department of Justice has said such legislation does not apply to drugs that can be used to lawfully produce abortions.

Project 2025 also calls for the HHS to pressure each state to submit detailed reports of every abortion that is carried out within that state. And it would require the CDC to monitor and report abortion complications. That would include children being “born alive after an abortion”—a misleading phrase because the vast majority of abortions take place long before a fetus becomes viable and doctors are required by law to provide care once an infant is born.

Agriculture

The Department of Agriculture’s current functions are as diverse and wide-reaching as providing loans for rural development and defending U.S. livestock from flesh-eating worms . The department has a crucial role in national nutrition: the USDA has overseen the country’s largest food assistance initiative, the Supplemental Nutrition Assistance Program (SNAP), in its various forms since its World War II–era beginnings and reintroduction in 1961 . Project 2025 would cut eligibility for SNAP benefits while moving the program to the HHS. And even though free school lunches have consistently been found to improve academic performance , the Heritage Foundation’s plan would restrict school meals provided through the USDA and repeal the dietary guidelines that those meals are based on.

Under Project 2025, the USDA’s scope would narrow to the efficient production of food, undoing the department’s current strategy to promote renewable energy and protect national forests and agricultural land from the climate crisis.

Climate Change

Across multiple departments and agencies, including the EPA, the Department of Energy and NOAA, the project would jettison much of the federal government’s climate science apparatus; it dismissively refers to such programs as “climate alarmism.” This move would significantly hinder researchers’ ability to understand climate change’s many impacts on our daily lives. It would stifle information on how to adapt society and infrastructure to threats such as increased flooding and more frequent and extreme heat waves, all of which have been conclusively linked to rising global temperatures. Cutting DOE research into renewable energy, battery storage and other technology—while increasing fossil fuel extraction on federal lands—would make reining in greenhouse gas emissions enough to meet the goals of the Paris climate accord all but impossible.

“Any attempt to reverse policies, any attempt to slow down this transition to clean energy, is putting us at greater risk” from climate change’s severe impacts, Cleetus says. She notes that the 2025 scheme targets the EPA’s 2009 endangerment finding —a bedrock of climate policy that identifies heat-trapping pollutants as a public health threat. But distorting or burying science does not change the reality of the climate crisis. “Science will not bend to political will,” Cleetus adds, “but what will happen is that people will suffer.”

To oversee and reform research at the EPA, Project 2025 would install a “science adviser” who would report directly to the presidential administration, as well as multiple new senior political appointees. “It’s pretty alarming, and it would be completely new for us,” says Joyce Howell, a Philadelphia-based EPA attorney speaking in her capacity as executive vice president of AFGE Council 238, a union of employees of the agency.

The plan would eliminate the National Weather Service’s role as a forecaster, relegating the agency to only collecting data—which private companies could use to create their own forecasts. This has been a goal in some conservative circles for many years; in 2005 then senator Rick Santorum of Pennsylvania introduced a bill to codify such a change into law. John Morales, a former NWS meteorologist who now works as a consultant, expressed his “alarm” at such proposals. “The U.S. economy grows as a result of our robust research, innovation, forecasts and warnings” from the NWS and NOAA, he says. These proposals “just make absolutely no sense.”

A key function of the NWS is to provide ample warnings about tornadoes, floods, heat waves and other hazardous weather—notifications that, Morales notes, protect lives and property. As a result, under Project 2025, this single, authoritative warning system would likely be replaced with a patchwork of alerts from weather stations and private apps.

In addition to dismantling the ED, Project 2025 would end student loan forgiveness. It would narrow Title IX protections, which prohibit discrimination in education, by focusing only on “biological sex recognized at birth” and removing considerations for gender identity and sexual orientation.

Project 2025 could also make it harder for U.S. schools to attract international students and for employers to hire them after their education. Visa holders make up a significant portion of master’s and Ph.D. students in the country’s engineering, health and science programs: among first-time, full-time master’s students, for instance, scholars on temporary visas exceeded U.S. citizens and permanent residents in 2022, according to National Science Foundation data . After graduation, many foreign students remain in the U.S. to work with an H-1B visa. But Project 2025 would eliminate the lowest qualifying wage levels for H-1B workers set by the Department of Labor—levels that are commonly applied to these individuals’ first jobs. This would effectively mean “excluding most foreign-born graduates from these job opportunities,” according to an assessment released by the Niskanen Center , a pro-immigration think tank.

Environment

The EPA’s role beyond climate-change-related programs would be stymied, too. Project 2025 would increase the extent to which environmental policymakers have to consider costs to industry. It also argues for lessening the consideration of “co-benefits”—instances when, for example, regulating one pollutant coincidentally reduces emissions of another. This calculus flies in the face of the intent behind the Clean Air Act of 1970 ; the authors of that law, who wanted to spur industrial innovation, emphasized that human health was more important than company profits. The Project 2025 recommendations would also limit what is considered a pollutant or a hazardous chemical—in particular, they make the call to “revisit the designation” of perfluoroalkyl and polyfluoroalkyl substances (PFASs) as hazardous chemicals. “If anything should be listed as a hazardous chemical, it should be PFAS,” says Maria Doa, senior director for chemicals policy at the Environmental Defense Fund and a former EPA employee, who worked at the agency during the Trump administration. These compounds, found in many products from firefighting foam to cosmetics, are prevalent in U.S. drinking water and soils. They can take hundreds, even thousands, of years to break down in the environment, earning them the common name “forever chemicals.” And PFASs have been linked to numerous ailments, including various cancers, hypertension and immune dysfunction.

“Across the board, [the authors of the project are] looking at undermining things,” Doa says, especially “the expertise to properly characterize the risk presented by chemicals.” Project 2025 would cease funding for the Integrated Risk Information System (IRIS), a database of chemical health hazards that is considered a gold standard: in addition to the EPA, state governments use it to set regulations. The plan also seeks to undermine the agency’s ability to assess people’s cumulative exposure to chemicals under the Toxic Substances Control Act (TSCA). For example, under Project 2025, if a given chemical was regulated under the Clean Water Act , its route of exposure couldn’t also be considered under TSCA—meaning the latter program would have an incomplete measure of the chemical’s cumulative impact. PFASs are “a perfect example” of where this becomes a problem, Doa says, because people are exposed to multiple types of these substances through water, soil and consumer products. Overall, the project is “trying to give the industry preeminence in this rather than looking at all of us,” she adds.

Health Care

The project’s restrictions to the Affordable Care Act (ACA) would roll back Medicaid expansions, potentially leaving millions of people without medical coverage. The ACA currently expands Medicaid eligibility to adults with incomes at or below 138 percent of the federal poverty line, and it helps states offset the costs through a matching rate program. But Project 2025 would cap federal grants and leave primary oversight to states. Experts predict that with less federal funding as an incentive, certain states may choose to roll back Medicaid and restrict eligibility criteria . And with fewer people qualifying for Medicaid, gaps in health care access would grow—as has already been seen in states that have not adopted expanded Medicaid .

Project 2025 aggressively attacks the federal programs and funding that increase health care access to LGBTQ+ families and single-parent households. It criticizes President Joe Biden’s administration for focusing on “LGBTQ+ equity” and, without evidence, claims these policies are “subsidizing single-motherhood, disincentivizing work, and penalizing marriage.” The project would also undo the antidiscrimination rules that are now applied to all federal health care programs, including the ACA and the Children’s Health Insurance Program. Removing those protections would greatly restrict access to gender-affirming care for transgender people of all ages.

Much of Project 2025 is concerned with eliminations or reductions, such as cutting federal support for automakers that produce electric vehicles. But there is at least one thing its authors would like to see enlarged: the U.S. thermonuclear arsenal. This would be, as nuclear policy analyst Joe Cirincione wrote recently in the Bulletin of the Atomic Scientists, “the most dramatic build up of nuclear weapons since the start of the Reagan administration.”

Project 2025 advocates for a “readiness to test” nuclear weapons at the Nevada National Security Site, even though detonating an underground nuke would violate the Comprehensive Nuclear-Test-Ban Treaty , which the U.S. signed in 1996. Physicists in the U.S. still have ways to study nuclear weapons, however: they do it virtually through supercomputer simulations that remove the risks to experimenters’ health and the environment—and avoid inflaming geopolitical tensions.

One Type of Fiber Could Have Weight Loss Benefits Similar to Ozempic

Research on the gut microbiome has triggered a ' revolution ' in nutritional science, and in the last few years, dietary fiber has become the " new protein " – added to foods in abundance to feed our gut and boost our health.

A recent study on mice, however, suggests not all fiber supplements are equally beneficial.

A form that is readily found in oats and barley, called beta-glucan , can control blood sugar and assist in weight loss among mice fed a high-fat diet.

Researchers at the University of Arizona (UA) and the University of Vienna say it is the only type of fiber supplement they tested that decreased a mouse's fat content and body weight within 18 weeks.

The other fibers considered, including wheat dextrin, pectin, resistant starch, and cellulose, had no such effect, despite shifting the makeup of the mouse microbiome significantly compared to mice fed no fiber supplements.

"We know that fiber is important and beneficial; the problem is that there are so many different types of fiber," explains biomedical scientist Frank Duca from UA.

"We wanted to know what kind of fiber would be most beneficial for weight loss and improvements in glucose homeostasis so that we can inform the community, the consumer, and then also inform the agricultural industry."

Dietary fibers are the main source of energy for bacteria living in our guts, and yet less than 5 percent of people in the US consume the recommended 25–30 grams (0.9–1 ounce) of fiber a day.

To make up for this, fiber supplements and 'invisible fiber'-infused foods are growing in popularity . But fibers are extremely diverse, so which do we choose?

Some fibers, like oat beta-glucans and wheat dextrin, are water- soluble , meaning they are easily fermented by gut bacteria. Others, like cellulose and resistant starch, are less soluble or insoluble, meaning they stick to other materials to form stool .

Until now, writes biomedical scientist Elizabeth Howard from UA and her colleagues, "there is no study that has investigated the role of various fibers in one cohort."

To make up for this, the current study tested several forms of fiber in one cohort of mice. Only beta-glucan was found to increase the number of Ileibacterium found in the mouse intestine. Other studies on mice have linked this bacterium to weight loss.

Sure enough, long before the 10-week marker, mice fed beta-glucan showed reduced body weight and body fat content compared to mice fed other forms of fiber.

The findings align with another recent study by Duca, which fed barley flour, rich in beta-glucan, to rodents. Even though the rats continued eating just as much of their high-fat diet as before, their energy expenditure increased and they lost weight anyway.

A similar outcome was observed in mice fed beta-glucan in the new study. These animals also showed increased concentrations of butyrate in their guts, which is a metabolite made when microbes break down fiber.

Butyrate induces the release of glucagon-like peptide-1 (GLP-1), which is the natural protein that synthetic drugs like Ozempic mimic to stimulate insulin release.

"Part of the benefits of consuming dietary fiber is through the release of GLP-1 and other gut peptides that regulate appetite and body weight," explains Duca.

"However, we don't think that's all of the effect. We think that there are other beneficial things that butyrate could be doing that are not gut peptide related, such as improving gut barrier health and targeting peripheral organs like the liver."

Far more research is needed before these results can be extended to humans, but the findings suggest that some fibers may be better suited to weight loss and insulin control than others.

The study was published in the Journal of Nutrition .

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12 June 2024

Sleep deprivation disrupts memory: here’s why

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A crucial brain signal linked to long-term memory falters in rats when they are deprived of sleep — which might help to explain why poor sleep disrupts memory formation 1 . Even a night of normal slumber after a poor night’s sleep isn’t enough to fix the brain signal .

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