Literature DB >> 26462573

Chronological age and its impact on associative learning proficiency and brain structure in middle adulthood.

Vaibhav A Diwadkar1, Marcella Bellani2, Rizwan Ahmed3, Nicola Dusi2, Gianluca Rambaldelli2, Cinzia Perlini2, Veronica Marinelli2, Karthik Ramaseshan3, Mirella Ruggeri2, Paolo Bambilla4.   

Abstract

INTRODUCTION: The rate of biological change in middle-adulthood is relatively under-studied. Here, we used behavioral testing in conjunction with structural magnetic resonance imaging to examine the effects of chronological age on associative learning proficiency and on brain regions that previous functional MRI studies have closely related to the domain of associative learning.
METHODS: Participants (n=66) completed a previously established associative learning paradigm, and consented to be scanned using structural magnetic resonance imaging. Age-related effects were investigated both across sub-groups in the sample (younger vs. older) and across the entire sample (using regression approaches).
RESULTS: Chronological age had substantial effects on learning proficiency (independent of IQ and Education Level), with older adults showing a decrement compared to younger adults. In addition, decreases in estimated gray matter volume were observed in multiple brain regions including the hippocampus and the dorsal prefrontal cortex, both of which are strongly implicated in associative learning.
CONCLUSION: The results suggest that middle adulthood may be a more dynamic period of life-span change than previously believed. The conjunctive application of narrowly focused tasks, with conjointly acquired structural MRI data may allow us to enrich the search for, and the interpretation of, age-related changes in cross-sectional samples.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Aging; Associative learning; Brain structure; Hippocampus; Life span changes; Voxel based morphometry

Mesh:

Year:  2015        PMID: 26462573     DOI: 10.1016/j.bbr.2015.10.016

Source DB:  PubMed          Journal:  Behav Brain Res        ISSN: 0166-4328            Impact factor:   3.352


  6 in total

1.  Activations in gray and white matter are modulated by uni-manual responses during within and inter-hemispheric transfer: effects of response hand and right-handedness.

Authors:  Vaibhav A Diwadkar; Marcella Bellani; Asadur Chowdury; Silvia Savazzi; Cinzia Perlini; Veronica Marinelli; Giada Zoccatelli; Franco Alessandrini; Elisa Ciceri; Gianluca Rambaldelli; Mirella Ruggieri; A Carlo Altamura; Carlo A Marzi; Paolo Brambilla
Journal:  Brain Imaging Behav       Date:  2018-08       Impact factor: 3.978

2.  Functional dynamics of hippocampal glutamate during associative learning assessed with in vivo 1H functional magnetic resonance spectroscopy.

Authors:  Jeffrey A Stanley; Ashley Burgess; Dalal Khatib; Karthik Ramaseshan; Muzamil Arshad; Helen Wu; Vaibhav A Diwadkar
Journal:  Neuroimage       Date:  2017-03-29       Impact factor: 6.556

3.  Cortical-hippocampal functional connectivity during covert consolidation sub-serves associative learning: Evidence for an active "rest" state.

Authors:  Mathura Ravishankar; Alexandra Morris; Ashley Burgess; Dalal Khatib; Jeffrey A Stanley; Vaibhav A Diwadkar
Journal:  Brain Cogn       Date:  2017-10-18       Impact factor: 2.310

4.  Ocular measures during associative learning predict recall accuracy.

Authors:  Aakash A Dave; Matthew Lehet; Vaibhav A Diwadkar; Katharine N Thakkar
Journal:  Int J Psychophysiol       Date:  2021-05-27       Impact factor: 2.903

5.  From mathematics to medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data.

Authors:  Andrew Salch; Adam Regalski; Hassan Abdallah; Raviteja Suryadevara; Michael J Catanzaro; Vaibhav A Diwadkar
Journal:  PLoS One       Date:  2021-08-12       Impact factor: 3.752

6.  Disordered directional brain network interactions during learning dynamics in schizophrenia revealed by multivariate autoregressive models.

Authors:  Shahira J Baajour; Asadur Chowdury; Patricia Thomas; Usha Rajan; Dalal Khatib; Caroline Zajac-Benitez; Dimitri Falco; Luay Haddad; Alireza Amirsadri; Steven Bressler; Jeffery A Stanley; Vaibhav A Diwadkar
Journal:  Hum Brain Mapp       Date:  2020-05-21       Impact factor: 5.038

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.