Brain-inspired Approaches for De Bruijns model of associative memory Femke Jansen 0741948

Contents Overview of the model Brain-inspired approaches Conclusions Lower & upper layer A simple scenario Brain-inspired approaches Ideas Issues & resolutions Conclusions / Computer Science & Engineering 23-5-2019

Overview of the model Lower layer: single cells “Bowl” of soup: chemical compounds Chemical reactions via signals Storage: A + B → C Retrieval: A + C → B Associative memory Soup “knows” about (p, q) Only recalls when p? / Computer Science & Engineering 23-5-2019

Overview of the model (2) Upper layer: brain + set of cells Distributes work over cells Roaming random set Cells connected to the brain: communication Bidirectional communication Connect & disconnect at random / Computer Science & Engineering 23-5-2019

Overview of the model (3) Limitations of individual cells Decay period: not stored indefinitely Capacity: store maximal X pairs Unreliability: fail to reply to p?, although it stores a pair containing p Then how can this work? Redundancy! / Computer Science & Engineering 23-5-2019

A simple scenario for the upper layer Small example 3 brain cells in roaming random set Initially, no compounds present For simplicity, no deterioration of compounds / Computer Science & Engineering 23-5-2019

Brain-inspired Approaches - ideas Slowing down dementia Idea: stimulate patients with signals - help them remember How it works: stimulate brain of patients to broadcast signals more often broadcasted  more cells contain the signals mental activity  “fitter” brain How it helps people: remain longer self-reliant / Computer Science & Engineering 23-5-2019

A BiA- ideas (2) Helping people with dyslexia Idea: stimulate patients with signals as (letter, looks like) or (letter, sounds like). How it works: similar to dementia: broadcasted often  more cells contain the signals perhaps easier/faster then learning process How it helps people: dyslexia is treated better at an early age A / Computer Science & Engineering 23-5-2019

BiA- ideas (3) Processing traumas Idea: traumas can be “hidden”; stimulating patients with signals to let traumas arise How it works: use signals (i.e., memories) from the past connected cells involved will reply with a part  trauma unfolds itself How it helps people: dealing with a trauma requires recalling it / Computer Science & Engineering 23-5-2019

BiA- ideas (4) Example to illustrate trauma recall For simplicity, only second half of pairs shown: pairs that contain a fragment of a trauma / Computer Science & Engineering 23-5-2019

BiA- issues & resolutions How to stimulate patients? Invasive: implant, directly in contact with cells Non-invasive: helmet, no direct contact What kind of signals correspond to features (i.e., memories)? Difficult: varies from person to person requires knowledge from many fields: biology, chemistry, physiology … / Computer Science & Engineering 23-5-2019

BiA- issues & resolutions (2) The next step: understanding relations between pairs in vitro experiments - brain cells / small neural networks provide input, observe output (electrical / light) not as complex as the (human) brain in vivo experiments - smaller animals (mice) influence from cooperation of areas in the brain age as a limiting factor (mice: lifespan of 2 years) eventually, test on humans / Computer Science & Engineering 23-5-2019

Questions? Conclusions Main ideas model: cells store signals of pairs and can reply to a query  associative memory distributing work over cells: different pairs stored Brain-inspired approaches may exploit these features Still: difficult, because of chemical & biological aspects Once aspects fully understood, conduct experiments: in vitro for initial idea in vivo for interaction of different brain areas Questions? / Computer Science & Engineering 23-5-2019