Yet Another Connectionist Memory Model

1. Yet Another Connectionist Memory Model Robert Turetsky rjt72@columbia.edu BMEN 6480

2. Memory: Computational Demands • Associative and Content addressable • Memories are encoded, not stored veridically • Memory is subject to distortion • Gist Learning • Capacity • Noise • Encoding and retrieval must be flexible • Memories “consolidate” over time

3. The Connectionist View • Model: Simple processing units and plastic weights between them • Memories stored in weights • Weight training: • Interleaved • Sequential (aka Focused) • Structure is found by emergent similarities in connections

4. Interleaved vs. Sequential • Sequential: • Fast: Train each vector as it arrives • Causes catastrophic interference • Interleaved: • Slow: Must iterate through entire corpus • Can form arbitrary relationships • Problem: Sequential learning is unstable, interleaved learning is too slow for survival

5. Example: The Exception Principle • Birds can fly • Birds can fly unless they are penguins or ostriches • Birds can fly, unless they are penguins or ostriches, or if they happen to be dead, or have broken wings, or are confined to cages, or have their feet stuck in cement, or have undergone experiences so dreadful as to render them psychologically incapable of flight

6. So how do we deal? • At least 2 memory locations: • Hippocampus: • Short term • Sequential Learning • Neocortex • Long term • Interleaved Learning? • Consolidation: Transferring data from Hippocampus to Neocortex

7. The Hippocampus and why we like it

8. Role of the Hippocampus • Rapid storage of new memories • Explicit: Episodic, semantic, encyclopedic, spatial • Not Implicit: Motor skills, repetition priming • Model salient features of tasks/episodes • Place Cells: cognitive map? • Eichenbaum’s Odor Discrimination Test

9. HS: High Level Architecture • Located in Medial Temporal Lobe • 2 parts to Hippocampal System (HS) • Hippocampal Formation (HF) • Entorhinal Complex (EC) • 3 parts to HF: • Dentate Gyrus (DG) • Ammon’s Horn (CA1, CA3) • Subicular Complex

10. Hippocampus: Connections

11. LTP + LTD: Hebb in the Head • 2 requirements: • Presence of glutamate • Depolarization of post-synaptic membrane • If two afferent neurons are active at (about) the same time, one can lead to glutamate release, while the other will lead to depolarization. Then the “complex” chain reaction with Ca+ leads to LTP • Eventually committed cells emerge

12. Place Cells: A Retrospective • Place cells fire when test subject is in/near a specific location • Distances from subjects may be encoded by phase within theta cycle • Place fields shrink with experience in a particular domain • Most studied feature of Hippocampus

13. Place Cells: Not enough? • With only place cells: • Reaching a goal means searching a graph • It is difficult to find new shortcuts • Alternative: Path integration? • Besides, there is much more to hippocampus then place cells • Is the cognitive map treated differently or is it just another form of semantic knowledge?

14. Towards a connectionistmodel of memory

15. Phenomenon to investigate • Temporally graded retrograde amnesia • No new memories, but old ones are preserved • Time delay of up to 15 years for how long “old” is • Older memories are preserved better then newer • Cannot form new memories without excessive repetition • Only refers to explicit memories, implicit memories have little retrograde amnesia at all • Fundamental Questions: • Why do we need the hippocampus? • Why does learning in neocortex take so long?

16. Memory: A Connectionist Model(McClelland, 1994) • Neocortical memory is distributed • Recollection of a memory means activating many different areas • Memories are content-addressable • Ultimately, all knowledge ends up in the neocortical system as synaptic weights • During information processing, the weights get changed, but only slowly

17. Connectionist Model Cont’d • Small changes add up over time add up • Short episodes impact both the hippocampus and neocortex, but in neocortex it is so minimal it basically has no effect • Bidirectional Attractor-based reinstatement • Hippocampus ==> neocortex teacher • This system is capable of explaining temporally graded retrograde amnesia

18. YACMM: My Memory Model

19. Memory Model: Simulation • Model hippocampus as attractor-based associative memory (Hopfield Network) • Sequential learning • Model neocortex as MLP network • Backpropagation is interleaved learning • MLP structure based on Rumelhart 1990, connectionist update on semantic networks • Bidirectional communication: • Hippocampus trains neocortex • Neocortex can cue hippocampus (like cache mem)

20. The Model Neocortex • From Rumelhart 1990

21. Learning Structure • Relationships emerge from interleaved learning

22. Catastrophic Interference • Focused learning will allow you to remember new facts fast, but can ruin relationships you’ve already built

23. Hippocampus as Hopfield Net

24. Conclusion: Together at last! Teaches during downtime Perceptual Input Recalls as needed Fast, Sequential Hippocampus (Hopfield Net) Slow, Interleaved Neocortex (Pseudo-semantic Net)