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Related Concept Videos

Working Memory01:24

Working Memory

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Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
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The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the...
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Associative Learning01:27

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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
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Related Experiment Video

Updated: Apr 9, 2026

Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
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Integrating Neuroimaging and Genetics via Contrastive Learning for Working Memory.

Pranav Nadigapu Suresh1, Behnam Kazemivash1, Dawn M Jensen2

  • 1Computer Science, Georgia State University, Atlanta, USA.

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|April 8, 2026
PubMed
Summary
This summary is machine-generated.

This study links specific genes (FYN, RPL28, MAPT) and brain regions (cerebellum, striatum) to working memory capacity. Findings offer insights into cognitive function and potential biomarkers for impairment in older adults.

Keywords:
Contrastive learningGenetic variantsNeuroimagingSparse Canonical Correlation AnalysisWorking memory

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Area of Science:

  • Cognitive Neuroscience
  • Genetics
  • Neuroimaging

Background:

  • Understanding working memory is vital for cognitive neuroscience and identifying cognitive impairment biomarkers, especially in aging populations.
  • Existing research often analyzes genetic and neural data separately, limiting comprehensive understanding.

Purpose of the Study:

  • To integrate single nucleotide polymorphism (SNP) and neuroimaging data for improved working memory capacity classification.
  • To identify genetic factors associated with brain structure and function in working memory.

Main Methods:

  • Utilized UK Biobank data, integrating 1060 SNPs from Alzheimer's disease-related protein networks with latent brain gray matter density features extracted by a Convolutional Neural Network (CNN).
  • Employed supervised contrastive learning to enhance genetic-imaging relationships within individuals and working memory groups.
  • Applied sparse canonical correlation analysis to uncover significant genetic variants and brain region associations.

Main Results:

  • The contrastive learning model outperformed baseline methods in classifying high vs. low working memory capacity.
  • Identified significant associations between genetic variants in genes like FYN, RPL28, and MAPT, enriched in dendrite and synapse pathways, and brain regions including the cerebellum and striatum.

Conclusions:

  • The study provides novel insights into the genetic and neural underpinnings of working memory.
  • Findings highlight the role of specific genes and brain structures in cognitive function and may inform future research and therapeutic strategies for cognitive impairments.