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A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus: A Computational Approach Journal Club 5/16/12.

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Presentation on theme: "A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus: A Computational Approach Journal Club 5/16/12."— Presentation transcript:

1 A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus: A Computational Approach Journal Club 5/16/12

2 Outline Review of Dentate Gyrus Model Types – Introduction to Pattern Separation Model Setup Model Results / Comparison to Experimental Data

3 1. Functional Models with Simplified Physiology CA3 – Pattern Completion and Pattern Storage Storage Capacity of CA3 is highest if inputs do not overlap Increase storage capacity by decreasing overlap of input patterns Pattern Separation – Definition: “ability to transform a set of similar input patterns into a less- similar set of output patterns” – Methods Fewer elements are active in each pattern Those that are active can be orthogonalized Dentate Gyrus inherent pattern separation properties – (decrease probability that two separate entorhinal input activate the same subset of CA3 neurons) – Low firing probability of dentate gyrus cells – Low contact probability of dentate granule cells axons to CA3 pyramidal cells Variations – Plasticity – Neurogenesis

4 2. Physiologically Detailed Models Include detailed cells of many types – Mossy fiber sprouting can lead to granule cell hyperexcitability – Nonrandom connections between granule cells could produce hyperexcitable, seizure-prone circuits – Did not directly address pattern separation (authors include Santhakumar, Morgan and Soltez)

5 3. Sequence Learning Models Excitatory granule cell–mossy cell–granule cell loops could form circuits with variable delays Allows dentate gyrus to recover temporal structure originally present in entorhinal inputs. (authors include Lisman, Buzsaki)

6 Myers and Scharfman Model Model Components – Perforant Path Inputs – Granule Cells – Interneurons – Mossy Cells glutamatergic – HIPP Cells GABAergic Conclusions – Reproduction of Experimental Results – Pattern separation can be dynamically regulated by HIPP and Mossy Cells

7 Pattern Separation in Model Input – 98% OverlapOutput – 68.4% Overlap

8 Pattern Separation: Effect on Input Density Active Inputs chosen randomly

9 Experimental Pattern Separation Results Examples Lesioning dentate gyrus in rats Human functional neuroimaging study Recording place cells in rat DG and CA3 when environment is morphed (Leutgeb)

10 DG and CA3 Place Cell Changes as Environment is morphed CA3 Dentate Gyrus LeutgebModel Leutgeb Model Results 12345671234567

11 Effects of Hilar Lesion Model Ratzliff et al. 2004

12 Takeaways Review of other types of Models Model Reproduction of Experimental Results HIPP and Mossy Cell Activity levels can dynamically regulate pattern separation


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