A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus : A Computational Approach

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A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus : A Computational Approach. Journal Club 5/16/12. Outline. Review of Dentate Gyrus Model Types Introduction to Pattern Separation Model Setup Model Results / Comparison to Experimental Data. - PowerPoint PPT Presentation

Transcript of A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus : A Computational Approach

A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus: A Computational Approach

Journal Club5/16/12

Outline

• Review of Dentate Gyrus Model Types– Introduction to Pattern Separation

• Model Setup• Model Results / Comparison to Experimental

Data

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

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)

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)

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

Pattern Separation in ModelInput – 98% Overlap Output – 68.4% Overlap

Pattern Separation: Effect on Input Density

• Active Inputs chosen randomly

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)

DG and CA3 Place Cell Changes as Environment is morphed

CA3Dentate Gyrus

Leutgeb Model

Leutgeb

Model

Results

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Effects of Hilar LesionModelRatzliff et al. 2004

Takeaways

• Review of other types of Models• Model Reproduction of Experimental Results• HIPP and Mossy Cell Activity levels can

dynamically regulate pattern separation