What learning systems do intelligent agents need? Complementary learning systems theory updated
We update complementary learning systems (CLS) theory, which holds that intelligent
agents must possess two learning systems, instantiated in mammalians in neocortex and …
agents must possess two learning systems, instantiated in mammalians in neocortex and …
On the integration of space, time, and memory
H Eichenbaum - Neuron, 2017 - cell.com
The hippocampus is famous for map** locations in spatially organized environments, and
several recent studies have shown that hippocampal networks also map moments in …
several recent studies have shown that hippocampal networks also map moments in …
Expectation in perceptual decision making: neural and computational mechanisms
Sensory signals are highly structured in both space and time. These structural regularities in
visual information allow expectations to form about future stimulation, thereby facilitating …
visual information allow expectations to form about future stimulation, thereby facilitating …
Domain generality versus modality specificity: The paradox of statistical learning
Statistical learning (SL) is typically considered to be a domain-general mechanism by which
cognitive systems discover the underlying distributional properties of the input. However …
cognitive systems discover the underlying distributional properties of the input. However …
Statistical learning research: A critical review and possible new directions.
Statistical learning (SL) is involved in a wide range of basic and higher-order cognitive
functions and is taken to be an important building block of virtually all current theories of …
functions and is taken to be an important building block of virtually all current theories of …
[HTML][HTML] How can hearing loss cause dementia?
Epidemiological studies identify midlife hearing loss as an independent risk factor for
dementia, estimated to account for 9% of cases. We evaluate candidate brain bases for this …
dementia, estimated to account for 9% of cases. We evaluate candidate brain bases for this …
Complementary learning systems within the hippocampus: a neural network modelling approach to reconciling episodic memory with statistical learning
A growing literature suggests that the hippocampus is critical for the rapid extraction of
regularities from the environment. Although this fits with the known role of the hippocampus …
regularities from the environment. Although this fits with the known role of the hippocampus …
The successor representation in human reinforcement learning
Theories of reward learning in neuroscience have focused on two families of algorithms
thought to capture deliberative versus habitual choice.'Model-based'algorithms compute the …
thought to capture deliberative versus habitual choice.'Model-based'algorithms compute the …
How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning
CM Conway - Neuroscience & Biobehavioral Reviews, 2020 - Elsevier
Despite a growing body of research devoted to the study of how humans encode
environmental patterns, there is still no clear consensus about the nature of the …
environmental patterns, there is still no clear consensus about the nature of the …
Human hippocampal and entorhinal neurons encode the temporal structure of experience
Extracting the underlying temporal structure of experience is a fundamental aspect of
learning and memory that allows us to predict what is likely to happen next. Current …
learning and memory that allows us to predict what is likely to happen next. Current …