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The hippocampus as a cognitive map: From grid cells to navigation
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The classic book of O’Keefe and Nadel (1978) has inspired a vibrant research program about animal and human navigation to the present day. But is the hippocampus technically a “map” and in what sense is it “cognitive”? Many results about place cells in the hippocampus have recently been clarified by the breakthrough discovery of g rid cells and their remarkable hexagonal activity patterns in the entorhinal cortex (Hafting et al., 2005). This talk will summarize recent modeling results concerning how both grid and place cell maps may be learned in a hierarchy of self-organizing maps as an animal navigates through space. The model clarifies why both types of cells are needed, how top-down cognitive mechanisms may modulate this map, how various observed oscillations may emerge from these learning mechanisms, and how What and Where spatial representations and adaptively-timed object representations may both arise from variations of a shared hippocampal circuit design. In particular, top-down matching and attentional mechanisms may help to stabilize and reset cell properties in this mapping hierarchy and regulate the occurrence of beta and gamma oscillations. The talk will also discuss how optic-flow based navigation and tracking may be achieved in response to natural environments through interactions of visual cortical regions, and how spatial and object attention may interact to learn to recognize and search objects and scenes as part of the information acquisition process during navigation, including roles for perirhinal and parahippocampal cortex in learning object and spatial contextual information.
Supported in part by CELEST, an NSF Science of Learning Center (SBE-0354378), and the SyNAPSE program of DARPA (HR0011-09-C-0001).
References (see http://cns.bu.edu/~steve)
Browning, A., Grossberg, S., and Mingolla, M. (2009). A neural model of how the brain computes heading from optic flow in realistic scenes. Cognitive Psychology, 59, 320-356.
Browning, A., Grossberg, S., and Mingolla, E. (2009). Cortical dynamics of navigation and steering in natural scenes: Motion-based object segmentation, heading, and obstacle avoidance. Neural Networks, 22, 1383-1398.
Fazl, A., Grossberg, S., and Mingolla, E. (2009). View-invariant object category learning, recognition, and search: How spatial and object attention are coordinated using surface- based attentional shrouds. Cognitive Psychology, 58, 1-48.
Gorchetchnikov, A., and Grossberg, S. (2007). Space, time, and learning in the hippocampus: How fine spatial and temporal scales are expanded into population codes for behavioral control. Neural Networks, 20, 182-193.
Grossberg, S. (2009). Beta oscillations and hippocampal place cell learning during exploration of novel environments. Hippocampus, 19, 881-885.
Huang, T.-R., and Grossberg, S. (2010). Cortical dynamics of contextually-cued visual learning and search: Spatial and object evidence accumulation. Psychological Review, in press.
Mhatre, H., Gorchetchnikov, A., and Grossberg, S. (2010). Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex. Hippocampus, in press.