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"... Role of the dual entorhinal inputs to hippocampus: a hypothesis based on cue/action (non-self/self) couplets ..."
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Role of the dual entorhinal inputs to hippocampus: a hypothesis based on cue/action (non-self/self) couplets
Review Article Selective Vulnerability of Neurons in Layer II of the Entorhinal Cortex during Aging and Alzheimer’s Disease
"... Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. All neurons are not created equal. Certain cell populations in specific brain regions are more susceptible to age-related changes that initiate regional an ..."
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Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. All neurons are not created equal. Certain cell populations in specific brain regions are more susceptible to age-related changes that initiate regional and system-level dysfunction. In this respect, neurons in layer II of the entorhinal cortex are selectively vulnerable in aging and Alzheimer’s disease (AD). This paper will cover several hypotheses that attempt to account for agerelated alterations among this cell population. We consider whether specific developmental, anatomical, or biochemical features of neurons in layer II of the entorhinal cortex contribute to their particular sensitivity to aging and AD. The entorhinal cortex is a functionally heterogeneous environment, and we will also review data suggesting that, within the entorhinal cortex, there is subregional specificity for molecular alterations that may initiate cognitive decline. Taken together, the existing data point to a regional cascade in which entorhinal cortical alterations directly contribute to downstream changes in its primary afferent region, the hippocampus. 1.
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"... Synaptic conditions for auto-associative memory storage and pattern completion in Jensen et al.’s model of hippocampal area CA3 ..."
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Synaptic conditions for auto-associative memory storage and pattern completion in Jensen et al.’s model of hippocampal area CA3
Controlling Working Memory with Learned Instructions
"... Many neural network models of cognition rely heavily on the modeler for control over aspects of model behavior, such as when to learn and whether an item is judged to be present in memory. Developing neurocomputational methods that allow these cognitive control mechanisms to be performed autonomousl ..."
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Many neural network models of cognition rely heavily on the modeler for control over aspects of model behavior, such as when to learn and whether an item is judged to be present in memory. Developing neurocomputational methods that allow these cognitive control mechanisms to be performed autonomously has proven to be surprisingly difficult. Here we present a general purpose framework called GALIS that we believe is amenable to developing a broad range of cognitive control models. Models built using GALIS consist of a network of interacting “regions” inspired by the organization of primate cerebral cortex. Each region is an attractor network capable of learning temporal sequences, and the individual regions not only exchange task-specific information with each other, but also gate one another’s functions and interactions. As a result, GALIS models can learn both task-specific content and also the necessary cognitive control procedures (instructions) needed to perform a task in the first place. As an initial test of this approach, we use GALIS to implement a model that is trained simultaneously to perform five versions of the n-Back task. Not only does the resulting n-Back model function correctly, determining when to learn or remove items in working memory, but its accuracy and response times correlate strongly with those of human subjects performing the same task. The n-Back model also makes testable predictions about how human accuracy would be affected by intra-trial changes in n’s value. We conclude that GALIS opens a potentially effective pathway towards developing a range of cognitive control models with improved autonomy.
THEORETICAL REVIEW The Hippocampus, Time, and Memory Across Scales
"... A wealth of experimental studies with animals have offered insights about how neural networks within the hippocampus support the temporal organization of memories. These studies have revealed the existence of “time cells ” that encode moments in time, much as the well-known “place cells” map locatio ..."
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A wealth of experimental studies with animals have offered insights about how neural networks within the hippocampus support the temporal organization of memories. These studies have revealed the existence of “time cells ” that encode moments in time, much as the well-known “place cells” map locations in space. Another line of work inspired by human behavioral studies suggests that episodic memories are mediated by a state of temporal context that changes gradually over long time scales, up to at least a few thousand seconds. In this view, the “mental time travel ” hypothesized to support the experience of episodic memory corresponds to a “jump back in time ” in which a previous state of temporal context is recovered. We suggest that these 2 sets of findings could be different facets of a representation of temporal history that maintains a record at the last few thousand seconds of experience. The ability to represent long time scales comes at the cost of discarding precise information about when a stimulus was experienced—this uncertainty becomes greater for events further in the past. We review recent computational work that describes a mechanism that could construct such a scale-invariant representation. Taken as a whole, this suggests the hippocampus plays its role in multiple aspects of cognition by representing events embedded in a general spatiotemporal context. The representation of internal time can be useful across nonhippocampal memory systems.
