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Related Concept Videos

Correlations02:20

Correlations

Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
Cause and Effect01:53

Cause and Effect

While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
Prediction Intervals01:03

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
The...
Correlation and Regression00:53

Correlation and Regression

In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a negative...
Evolutionary Psychology01:20

Evolutionary Psychology

Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the human psyche...
Associative Learning01:27

Associative Learning

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.
Classical conditioning, also known...

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Related Experiment Video

Updated: Jul 22, 2026

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

The predictive value of changes in effective connectivity for human learning.

C Büchel1, J T Coull, K J Friston

  • 1The Wellcome Department of Cognitive Neurology, Institute of Neurology, 12 Queen Square, London WC1N 3BG, UK. c.buechel@fil.ion.ucl.ac.uk

Science (New York, N.Y.)
|March 5, 1999
PubMed
Summary

Neural responses optimize during learning, showing decreased activation but increased connectivity between brain regions. These plastic changes correlate with learning performance, highlighting brain network interactions in associative learning.

Related Experiment Videos

Last Updated: Jul 22, 2026

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Psychology

Background:

  • Neural responses typically decrease with repeated stimulus exposure, a phenomenon known as repetition suppression.
  • This adaptation is believed to signify optimized neuronal processing during tasks.

Purpose of the Study:

  • To investigate the neural basis of associative learning for visual objects and their locations using functional magnetic resonance imaging (fMRI).
  • To explore the relationship between changes in neural activity, effective connectivity, and learning performance.

Main Methods:

  • Utilized functional magnetic resonance imaging (fMRI) to monitor brain activity during a visual associative learning task.
  • Employed path analysis to examine effective connectivity between distinct cortical processing systems.

Main Results:

  • Observed expected decreases in activation within specialized cortical areas over time.
  • Demonstrated an increase in effective connectivity between spatial and object processing systems.
  • Found a strong correlation between the dynamics of these neural plasticity changes and individual learning performance.

Conclusions:

  • Associative learning involves both adaptation (decreased activation) and increased integration (enhanced connectivity) between brain networks.
  • Interactions between specialized cortical systems are crucial for successful associative learning of visual information.