Local and Global Gating of Synaptic Plasticity

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Information about Local and Global Gating of Synaptic Plasticity
Technology

Published on September 23, 2008

Author: cijat

Source: slideshare.net

Description

A Seminar talk on the paper by Sanches-Montanes

Local and Global Gating of Synaptic Plasticity Manuel A. Sanchez-Montañes Hannes Schulz University of Osnabrück, Department of Cognitive Science Action and Cognition II / May 2nd 2005

Learning on Global vs. Local Scale Mechanisms for learning in neuronal nets: Local Global Hebb’s Rule & modifications Signals to the whole network Forms representations on Modifies local learning cortex

Learning Goals Local Learning: Global Learning: Representation of all Influence size of stimuli representation Possibility to add new (→ experimental stimuli later on evidence on basal forebrain) Independence from presentation frequency ◮ How to connect both?

The Neuronal Model Experimental Results Discussion Outline 1 The Neuronal Model The Cell The Network The Inputs 2 Experimental Results 3 Discussion Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Outline 1 The Neuronal Model The Cell The Network The Inputs 2 Experimental Results 3 Discussion Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs The Cell Model integrate-and-fire delayed transmission refractory period Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Network Topology Input Cells Excitatory Cells Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Network Topology Input Cells Excitatory Cells Inhibitory Cells Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Network Topology Input Cells Excitatory Cells Inhibitory Cells Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Network Topology Input Cells Excitatory Cells Inhibitory Cells Nucleus Basalis Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Network Topology Input Cells Excitatory Cells Inhibitory Cells Nucleus Basalis Layers 1&2, 3&2 fully connected Random weight initialization Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Network Topology Input Cells Excitatory Cells Inhibitory Cells Nucleus Basalis Layers 1&2, 3&2 fully connected Random weight initialization Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Retrograde Signal Inhibition Retrograde Signal Inhibitory Signal Dendrit ◮ Retrograde signal of firing cell Firing blocked by inhibitory inputs Cell Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Heterosynaptic Long Term Depression Presynaptic Cell Postsynaptic Cell “Normal” Condition Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Heterosynaptic Long Term Depression Presynaptic Cell Postsynaptic Cell Heterosynaptic LTD: postsynaptic cell active presynaptic cell “Normal” Condition inactive in time window ◮ Synaptic efficacy decrease LTD Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Relative Timing in Hebb Learning Sample interpretations of “Synchronous activity”: Symmetric coincidence window. Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Relative Timing in Hebb Learning Sample interpretations of “Synchronous activity”: Symmetric coincidence window. Asymmetric coincidence window. Used in this study. Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Input Trial I Ten different stimuli pseudorandom order 500 examples shown to network Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Input Trial I Trial II Ten different stimuli 9+1 different stimuli pseudorandom order pseudorandom order 500 examples shown to 500 examples shown to network network One stimulus paired with stimulus in basal-neuron Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Cell The Network The Inputs Input Trial I Trial II Ten different stimuli 9+1 different stimuli pseudorandom order pseudorandom order 500 examples shown to 500 examples shown to network network One stimulus paired with stimulus in basal-neuron Both run 40 times with random start parameters Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Outline 1 The Neuronal Model The Cell The Network The Inputs 2 Experimental Results 3 Discussion Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Formed Representations – Trial I Neuron Specificity Stimuli shown more often 44.8% unspecific to network not better 50.5% specific to 1 stimulus represented 4.7% intermediate Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Formed Representations – Trial II Number of neurons representing paired stimulus increases Number of neurons representing other stimuli stay the same Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Role of the Global Mechanism 1 Basal ganglion neuron fires 2 Inhibitory neurons have a prolonged refractory period 3 Inhibitory neurons do not fire 4 Excitatory neurons can fire and shorten refractory period again Network Topology Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Role of the Global Mechanism ◮ Unchanged mean activity of inhibitory neurons ◮ Delay of inhibitory activity relative to excitatory activity ◮ Retrograde APs invade dendritic tree Network Topology Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion The Same, in Graphs Delay of inhibitory Number of neurons activity relative to representing paired excitatory activity stimulus increases Number of neurons representing other stimuli stay the same Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Outline 1 The Neuronal Model The Cell The Network The Inputs 2 Experimental Results 3 Discussion Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Comparison of Results to Goals New stimuli can be trained w/o loss Optimally activated neurons inhibit others Unspecific neurons are result Frequency invariance, variable representation size Invariance due to mechanism described above Stimulus representation enhanced by global mechanism Hannes Schulz Local and Global Gating of Synaptic Plasticity

The Neuronal Model Experimental Results Discussion Predictions for Experimentors During basal forbrain stimulation: Delayed inhibitory activity Invasion of dendritic tree by more retrograde APs Hannes Schulz Local and Global Gating of Synaptic Plasticity

The End

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