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Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory.
The account presented here suggests that memories are first stored via synaptic changes in the hippocampal system, that these changes support reinstatement of recent memories in the neocortex, that neocortical synapses change a little on each reinstatement, and that remote memory is based on accumulated neocorticals changes.
By Carrot or by Stick: Cognitive Reinforcement Learning in Parkinsonism
It is shown, using two cognitive procedural learning tasks, that Parkinson's patients off medication are better at learning to avoid choices that lead to negative outcomes than they are at learning from positive outcomes.
Modeling hippocampal and neocortical contributions to recognition memory: a complementary-learning-systems approach.
A computational neural-network model is presented of how the hippocampus and medial temporal lobe cortex contribute to recognition memory and the stochastic relationship between recall and familiarity and the effects of partial versus complete hippocampal lesions on recognition.
Making Working Memory Work: A Computational Model of Learning in the Prefrontal Cortex and Basal Ganglia
This article presents an attempt to deconstruct this homunculus through powerful learning mechanisms that allow a computational model of the prefrontal cortex to control both itself and other brain areas in a strategic, task-appropriate manner.
Interactions between frontal cortex and basal ganglia in working memory: A computational model
- Michael J. Frank, B. Loughry, R. O’Reilly
- Biology, PsychologyCognitive, Affective, & Behavioral Neuroscience
- 1 June 2001
In this model, the frontal cortex exhibits robust active maintenance, whereas the basal ganglia contribute a selective, dynamic gating function that enables frontal memory representations to be rapidly updated in a task-relevant manner.
A mechanistic account of striatal dopamine function in human cognition: psychopharmacological studies with cabergoline and haloperidol.
The authors test a neurocomputational model of dopamine function in cognition by administering to healthy participants low doses of D2 agents cabergoline and haloperidol. The model suggests that DA…
Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain
This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field of computational cognitive neuroscience.
Hippocampal conjunctive encoding, storage, and recall: Avoiding a trade‐off
This analysis is focused on the feedforward pathways from the entorhinal cortex to the dentate gyrus (DG) and region CA3 and finds that Hebbian synaptic modification facilitates completion but reduces separation, unless the strengths of synapses from inactive presynaptic units to active postsynaptic units are reduced (LTD).
Conjunctive representations in learning and memory: principles of cortical and hippocampal function.
This framework suggests that tasks involving rapid, incidental conjunctive learning are better tests of hippocampal function, and is implemented in a computational neural network model that can account for a wide range of data in animal learning.