Selective Memory Generalization by Spatial Patterning of Protein Synthesis

Transcription

1 Selective Memory Generalization by Spatial Patterning of Protein Synthesis Cian O Donnell and Terrence J. Sejnowski Neuron 82, (2014) Referred by Kristjan-Julius Laak

2 Spatial Protein Synthesis in Synaptic Learning Cian O Donnell and Terrence J. Sejnowski Neuron 82, (2014) Referred by Kristjan-Julius Laak

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5 Stimulation

6 Synaptic tagging and capture (STC) model* * Redondo & Morris, 2011

7 Strongly activated synapse Weakly activated synapse on the same dendrite on another dendrite

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9 FLASHBULB MEMORY When you remember every unimportant detail of the moment you experienced some strong stimuli (e.g. 9/11)

10 Goal To investigate the PRP expression in spatial domain.

11 Today we will investigate how: Weak-stimuli-induced plasticity consolidation is dependent on (1)Functional clustering of synapses on dendrites (2)The sparsity and overlap of neural activity patterns at the ciruit level

12 Today we will investigate how: Weak-stimuli-induced plasticity consolidation is dependent on (1)Functional clustering of synapses on dendrites (2)The sparsity and overlap of neural activity patterns at the ciruit level

13 STC Strongly activated synapse Weakly activated synapse on the same dendrite on another dendrite

14 What determines whether the weak stimuli targets the same dendrite targeted by strong stimuli? Strong stimulus that causes LTP and synthesis of PRP c dend = 0 c dend = 1 Dendritic correlation coefficient = Weak stimulus that has access to PRPs only when targets the first dendrite

15 If c dend = 1/2 then p = 2/3 (as d = 3)

16 Mean long-term synaptic strength change Δw for a synapse receiving a weak stimulus: Exponential function describing the temporal window for PRP capture

17 Some weakly activated synapses are consolidated, but not the others.

18 Weak-stimuli-induced plasticity consolidation is dependent on (1)Functional clustering of synapses on dendrites (2)The sparsity and overlap of neural activity patterns at the ciruit level

19 We want to calculate mean consolidated synaptic strength change resulting from a weak activity pattern as a function of its temporal and spatial overlap with a strong activity pattern.

20 A generic model of a two-layer feedforward neural network Weak-only Shared

21 Synapses in a weak pattern

22 Don t have access to PRP Quaranteed to have access to PRP; overwriting process

23 Fraction of synapses in a weak pattern that fall into the connection group:

24 Total mean consolidated synaptic strength change in a weak pattern

25 Changes in overlap between strong and weak patterns increases or decreases the consolidated synaptic strength change

26 Some weakly activated synapses are consolidated, but not the others. Overlap between neural activity patterns determines which weak memories are consolidated

27 What determines the overlap between neural activity patterns in the brain?

28 1. Random and uncorrelated patterns Overlap of the patterns, q, is equal to the sparsity of the strong pattern, f s, i.e. q = f s We explore sparse (f s = 0.1) and dense (f s = 0.5) levels of strong pattern sparsity: 1) sparse-to-sparse 2) dense-to-sparse 3) sparse-to-dense 4) dense-to-dense

29 Memory consolidation is selective, but weak. Memory consolidation is weak and not selective (most of the synapses that have access to PRP are part of the strong pattern)

30 Maximizes the contribution of postsynaptic PRP sharing, selective! Most of the pre- and postsynaptic neurons overlap, a lot of overwriting. Strong consolidation, but not selective

31 Density of the neural representations is a strong determinant of the effectiveness of dendritic protein sharing for selective memory consolidation

32 2. Patterns are arranged

33 2. Patterns are arranged Pre- and postsynaptic populations are organized Synaptic connections are highly stimuli specific

34 1) Distance between the strong and weak stimuli values (ΔΘ) 2) Width of the pre- and postsynaptic tuning curves 3) Width of dendric spatial correlation window between pre- and 4) postsynaptic neurons

35 Conclusion 3 Increasing the width of the presyn. tuning curve decreases the consolidation of weak patterns for all stimulus values.

36 Some weakly activated synapses are consolidated, but not the others (single dendrite level) Overlap between neural activity patterns is important (circuit level) Density of the neural representations is critical (random patterns) Very specific coding conditions must be met for weak pattern consolidation (arranged patterns)

37 Extra reading: Why cats don t bite!

38 Now go grab some pizza!