Neuroscience 2004 Abstract
| Presentation Number: | 330.4 |
|---|---|
| Abstract Title: | Computational significance of differentiating CA1 from CA3. |
| Authors: |
Papp, G.*1
; Roudi, Y.1
; Leutgeb, S.2
; Leutgeb, J. K.2
; Moser, M.2
; Moser, E. I.2
; Treves, A.1,2
1Cognitive Neurosci., SISSA, Trieste, Italy 2Norway, via Beirut 4, I-34014, |
| Primary Theme and Topics |
Cognition and Behavior - Human and Animal Cognition and Behavior -- Learning & memory: Physiology and imaging |
| Secondary Theme and Topics | Cognition and Behavior<br />- Human and Animal Cognition and Behavior<br />-- Cognitive learning and memory systems |
| Session: |
330. Mapping and Remapping Poster |
| Presentation Time: | Sunday, October 24, 2004 4:00 PM-5:00 PM |
| Location: | San Diego Convention Center - Hall A-H, Board # NN10 |
| Keywords: | recurrent network, orthogonalization, spatial memory, network model |
The CA3 and CA1 fields of the mammalian hippocampus are strikingly different in their network architecture: massively recurrent the former, essentially feed-forward the latter. The functional significance of this structural differentiation is not clear, in that neural activity is qualitatively similar in the two fields, and computational models generally succeed in mimicking hippocampal functions even when equipped with the architecture of CA3 alone. To assess the functional advantage of the differentiation, a simulation approach has been proposed that quantitatively compares the performance of a differentiated with a uniform network model, each comprised of the same number of units and connections (AT, Hippocampus, 2004).
Recent experiments have discovered a striking functional difference between CA3 and CA1 activity patterns: multiple environments with overlapping features are represented by distinct ensembles in CA3, whereas ensembles in CA1 show a correspondingly graded overlap (SL et al, SfN abs, 2003). These rat recordings indicate that CA3 sets up a new, arbitrarily assigned representation to any distinguishable environment, whereas CA1, although able to access the CA3 representation when needed, by default tends to reflect the non-orthogonalized entorhinal inputs.
Given that the necessity of the CA1 stage is logically not apparent, we have extended the simulation approach to again assess the quantitative effect of the differentiation per se, decoupled from the predictable advantage of merely adding more computing resources to an existing CA3 network model. When simulating the learning of a new environment correlated with a familiar one, we find that in the differentiated network CA3 units ‘remap’, or change their spatial response fields, much more frequently than CA1 units.
Recent experiments have discovered a striking functional difference between CA3 and CA1 activity patterns: multiple environments with overlapping features are represented by distinct ensembles in CA3, whereas ensembles in CA1 show a correspondingly graded overlap (SL et al, SfN abs, 2003). These rat recordings indicate that CA3 sets up a new, arbitrarily assigned representation to any distinguishable environment, whereas CA1, although able to access the CA3 representation when needed, by default tends to reflect the non-orthogonalized entorhinal inputs.
Given that the necessity of the CA1 stage is logically not apparent, we have extended the simulation approach to again assess the quantitative effect of the differentiation per se, decoupled from the predictable advantage of merely adding more computing resources to an existing CA3 network model. When simulating the learning of a new environment correlated with a familiar one, we find that in the differentiated network CA3 units ‘remap’, or change their spatial response fields, much more frequently than CA1 units.
Sample Citation:
[Authors]. [Abstract Title]. Program No. XXX.XX. 2004 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2004. Online.
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