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

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% Overlap Output – 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 Leutgeb Model Results Dentate Gyrus CA3 1 2 3 4 5 6 7 Leutgeb Model

11. Effects of Hilar Lesion Ratzliff et al. 2004 Model

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