Skip to search formSkip to main contentSkip to account menu

Interactive memory systems in the human brain

TLDR
Examination of classification learning using event-related FMRI showed rapid modulation of activity in these regions at the beginning of learning, suggesting that subjects relied upon the medial temporal lobe early in learning, but this dependence rapidly declined with training, as predicted by previous computational models of associative learning.
View on Springer (opens in a new tab)

Probabilistic classification learning in amnesia.

TLDR
Declarative memory does appear to make a contribution to performance when training is extended beyond approximately 50 trials, because with further training control subjects eventually outperformed the amnesic patients.
View on PubMed (opens in a new tab)

From conditioning to category learning: an adaptive network model.

  • M. GluckG. Bower
  • Psychology
    Journal of experimental psychology. General
  • 1 September 1988
TLDR
The adaptive network theory was used to extend the Rescorla-Wagner (1972) least mean squares (LMS) model of associative learning to phenomena of human learning and judgment and the results again support the ResCorla-wagner LMS learning rule as embedded within an adaptive network model.
View on PubMed (opens in a new tab)

Pictures and names: Making the connection

View on Elsevier (opens in a new tab)

How do people solve the "weather prediction" task?: individual variability in strategies for probabilistic category learning.

TLDR
New experimental and theoretical analyses of the weather prediction task indicate that there are at least three different strategies that describe how subjects learn this task, which may have important implications for interpreting how different brain regions are involved in probabilistic category learning.
View on PubMed (opens in a new tab)

Cortico-striatal contributions to feedback-based learning: converging data from neuroimaging and neuropsychology.

TLDR
This study provides direct behavioural evidence from humans that cortico-striatal systems are necessary for feedback-based learning on a cognitive task and link between learning impairments in Parkinson's disease and the physiological and computational evidence for the role of midbrain dopaminergic systems in feedback processing.
View on PubMed (opens in a new tab)

Reward-learning and the novelty-seeking personality: a between- and within-subjects study of the effects of dopamine agonists on young Parkinson's patients.

TLDR
The finding that dopamine agonists administration in young patients with Parkinson's disease resulted in increased novelty seeking, enhanced reward processing, and decreased punishment processing may shed light on the cognitive and personality bases of the impulse control disorders, which arise as side-effects of dopamine agonist therapy in some Parkinson's patients.
View on PubMed (opens in a new tab)

Dissociating Hippocampal versus Basal Ganglia Contributions to Learning and Transfer

TLDR
This is the first time that a single task has been used to demonstrate a double dissociation between the associative learning impairments caused by hippocampal versus basal ganglia damage/dysfunction, and has implications for understanding the distinct contributions of the medial temporal lobe and basal Ganglia to learning and memory.
View on MIT Press (opens in a new tab)

Dopaminergic Drugs Modulate Learning Rates and Perseveration in Parkinson's Patients in a Dynamic Foraging Task

TLDR
It is found that dopaminergic drugs selectively modulate learning from positive outcomes, and a novel dopamine-dependent effect on decision making that is not accounted for by reinforcement learning models is found.
View on Publisher (opens in a new tab)

A Novelty Detection Approach to Classification

TLDR
A particular Novelty Detection approach to classification that uses a Redundancy Compression and Non-Redundancy Differentiation technique based on the hippocampus, a part of the brain critically involved in learning and memory, is presented.
View Paper (opens in a new tab)
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)