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SyNAPSE Phase 2: Large-Scale Model HRL Labs, Malibu, CA February 17, 2010 HRL0011-09-C-001 The Entorhinal-Hippocampal-Subicular-Prefrontal Loop Multiple-Decision.

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Presentation on theme: "SyNAPSE Phase 2: Large-Scale Model HRL Labs, Malibu, CA February 17, 2010 HRL0011-09-C-001 The Entorhinal-Hippocampal-Subicular-Prefrontal Loop Multiple-Decision."— Presentation transcript:

1 SyNAPSE Phase 2: Large-Scale Model HRL Labs, Malibu, CA February 17, 2010 HRL0011-09-C-001 The Entorhinal-Hippocampal-Subicular-Prefrontal Loop Multiple-Decision Navigation based on Short-Term Memory Corey Thibeault Brain Computation Lab Department of Biomedical Engineering Department of Computer Science & Engineering University of Nevada, Reno

2 SyNAPSE Phase 2: Contributors Computer Science & EngineeringComputational Neuroscientists: Dr. Frederick C. Harris, Jr.Dr. Phil H. Goodman Corey M. Thibeault Dr. Laurence C. Jayet Bray Corey M. Thibeault CS Undergraduate Students: Kevin Cassiday CS Graduate Students: Nicholas Ceglia Joshua Hegie Bryce Prescott Gareth Ferneyhough Rashid Makhmudov

3 Phase 1 and 2 DARPA Simulation Components To simulate a system of up to 10 6 neurons and demonstrate core functions and properties including: (a) Dynamic neural activity, (b) network stability, (c) synaptic plasticity and (d) self-organization in response to (e) sensory stimulation and (f) system-level modulation/reinforcement

4 Outline 1. Relevance of Hippocampal-Prefrontal Loop 2. Biology of Short-Term Memory for Navigation 3. 4. Model Assumptions 5. 6. Phase 1 Model and Results 7. Phase 2 Model and Results 8. DARPA Targets 9. Future Goals

5 Relevance PATHOPHYSIOLOGY Alzheimer’s, Parkison’s, Mad Cow, other degenerative dementia Stroke & Traumatic brain injury Schizophrenia Drug addiction Epilepsy TECHNOLOGY Mobile robotic navigation & search Neuromorphic STM for on-line AI in dynamic environments Human-computer interface for improved STM in the field

6 Memory

7 Biology: Neocortical-Hippocampal STM

8 Biology: Prefrontal Cortex

9 Biology: HP & EC in vivo

10 Biology: SUBICULUM in vivo

11 Biology: Ongoing Activity

12 Paradigm & Model Assumptions

13 Phase 1: STM Navigational Loop

14 Hippocampal-Prefrontal Microcircuit

15

16 RAIN Activity

17 ON/OFF Properties of RAIN

18 Hippocampal-Prefrontal Microcircuit

19 Weak Coupling Yields THETA Oscillation

20 Hippocampal-Prefrontal Microcircuit

21 Early Summer Results: EC-HP Pathway Place Cell Dynamics

22 New Brain Slice Experiments Motivated by the Model 1.Mouse brain removal2.Orientation to get EC-HP loop3.400 µm slicing 5.10x magnification6.80x Patching (slide from EPFL) EC HF EC HF 4.DIC Video Microscope

23 Hippocampal-Prefrontal Microcircuit

24 Late Summer Results: Subiculum Dynamics

25 Late Summer Results: Subiculum Dynamics

26 Late Summer Results: Subiculum Dynamics

27 Late Summer Results: Prefrontal Dynamics

28 Late Summer Results: Premotor Dynamics

29 Phase 2: 1 million neuron STM Navigational Loop

30 Hippocampal-Prefrontal Microcircuit

31

32 RAIN Activity

33 Hippocampal-Prefrontal Microcircuit

34 Weak Coupling Yields THETA Oscillation

35 Hippocampal-Prefrontal Microcircuit

36 Now: EC-HP Pathway Place Cell Dynamics

37 Hippocampal-Prefrontal Microcircuit

38 Now: Subiculum Dynamics

39 Now: Prefrontal Dynamics

40 Now: Prefrontal Dynamics

41 Now: Prefrontal Dynamics

42 Now: Premotor Dynamics

43 Phase 1 and 2 DARPA Simulation Components “ To simulate a system of up to 106 neurons and demonstrate core functions and properties including: (a) dynamic neural activity, (b) network stability, (c) synaptic plasticity and (d) self-organization in response to (e) sensory stimulation and (f) system-level modulation/reinforcement” The proposed Hippocampal-Prefrontal cortex model includes aspects of all 6 target components above: (a) Dynamic neural activity: → RAIN, place fields, short-term memory, sequential decision making (b) Network stability: → Effects of lesions and perturbations (c) Synaptic plasticity: → STDP (in both excitatory and inhibitory) (d) Self-organization: → Place field formation and stabilization (e) Sensory stimulation: → Visual landmark representation (no structural VC per se) (f) Modulation/reinforcement: → Reinforcement learning of correct sequence of decisions

44 Future Goals The Hippocampal-Prefrontal cortex model will further include the following aspects: (a) Sensory stimulation: → Structural visual cortex (b) Auto-stimulating neural activity → Self-activating RAIN (c) Structural entorhinal cortex → Grid cells, PPA interneurons (d) Theta coherence → Hippocampal and prefrontal (e) Virtual environment interface → Human robot walking in a street

45 Virtual environment interface: NCS-CASTLE

46 The Quad at UNR

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