Modulation of Dopamine for Adaptive Learning: a Neurocomputational Model
- Biology, Computer ScienceComputational brain & behavior
A biologically detailed computational model is proposed that implements adaptive learning rates by modulating the gain on the dopamine response to reward prediction errors, and activity within this circuit is model activity at the level of spiking neurons.
Computational Neuroscientific Models of Categorization
- Psychology, Biology
This chapter reviews a number of new theories that have been proposed that can account for the traditional cognitive results as well as for these newer neuroscience results.
A neurocomputational theory of how rule-guided behaviors become automatic.
- Psychology, BiologyPsychological review
A biologically detailed computational model of how rule-guided behaviors become automatic, implemented as a biologically detailed neural network constructed from spiking neurons and displaying a biologically plausible form of Hebbian learning.
The metamemory expectancy illusion in source monitoring affects metamemory control and memory
True contextuality in a psychophysical experiment
- PsychologyJournal of Mathematical Psychology