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1. Facilitation and depression in cortical neurons
How does it work and what is it good for?
2. Facilitation and working memory
3. Facilitation and decision making
Sequential decision making
Parallel decision making
4. Outlook
Lunch
Neurophysiological mechanism
Facilitation:APs arriving in the presynaptic terminal cause the accumulation of calcium ions. increase of released vesicles/AP
From: Wang Y et al. 2006
Idea: - docked pool of vesicles containing neurotransmitter - each released vesicle is replaced with a time constant τd.- intracellular calcium responsible for release probability of vesicles
Synaptic depression:The neuron fires more rapidly than vesicles can be replaced. Vesicle depletion
Possible benefits of facilitation and depression
Synaptic Filter (low-, high- or band-pass) Decorrelation Burst detection
Stabilize against noise (Gain Control)
Persistent activity:Depression:
Persistent activity can be maintained with relatively low firing rates (e.g. 15 Hz).
Facilitation: May increase the strength of connections above a critical threshold necessary for the stability of persistent firing.
Brief periods of synaptic activity may transiently shift connected cortical neurons into a state in which recurrent excitation is sufficiently strong to support persistent activity.
Mostly depression in the cortex?
Special properties of PFC:
Heterogeneity of synaptic dynamics (40-50% facilitation dominant).
Facilitation is often masked by high initial probability of release.
Augmentation with time constants of several seconds.
Short-term synaptic depression between pyramidal neurons has been observed in all cortical areas that have been examined (mainly V1, sensory areas).
From: Wang Y et al. 2006
Why in PFC? – Working memory!
Synaptic Theory of Working MemoryMongillo et al. (2008) Science 319, 1543
Memory is maintained by short-term synaptic facilitation. (mediated by increased residual calcium levels at the presynaptic terminals)
x: available resources (vesicles)
u: fraction of resources used by each spike (residual calcium level)
τF = 1.5 s >> τD = 0.2 s
…Object Working memory dominated by recurrent inhibitionBrunel and Wang (2001) J Comp Neurosci 11, 63-85
Working memory based on persistent activity maintained through recurrent NMDA synapses with long time constants.
(Synapses are permanently enhanced by previous long-term potentiation)
F-D spiking network
• integrate-and-fire neurons
(inhibitory and excitatory)
• structured network
(p selective populations each encoding one memory item)
• E-E connections weights are multiplied by u(t)·x(t) (0 > ux > 1)
From: Mongillo et al. 2008
Different regimes of working memory depending on background input
F-D spiking network
From: Mongillo et al. 2008
Memory maintained synaptically
Memory maintained by persistent firing
Temporary vs. permanent synaptic enhancement
Advantages of strengthening synapses temporarily:
• metabolically more efficient (conserve synaptic resources during periods of baseline activity)
• greater flexibility and control (synaptic facilitation is activity dependent and can vary in a graded
fashion)
• regulation of persistent activity by altering presynaptic release probability through neuromodulators (e.g. dopamine)
• Quiescent memory decoupling from other brain areas
Facilitation and sequential decision making
Task: Comparison of two vibrotactile stimuli applied sequentially
Experimental findings: “partially differential neurons” in VPCrespond to f1, show no persistent activity, but ramp up at the end of the
delay period and are influenced by f2 during the decision period
Problem: Model of Wang 2002 (attractor network of two competing populations) does not work in sequential decision making
Deco et al. in preparation
f1 > f2
f1 < f2
Facilitation and sequential decision making
Deco et al. in preparation
f1f2
delay
Specific input
Global attention signal
Facilitation and sequential decision making
During application of f2, the level of activity will depend on the synaptic history (u·f1) and on f2.
f2 f1
f2 f1
network model experiment
spik
es/s
Deco et al. in preparation
Together with the neurons that encode just f2, a decision of f1 < f2 or f1 > f2 can be reached with a standard attractor model of decision making.
f1 > f2
f1 < f2
Facilitation and parallel decision making
Albantakis & Deco 2009
Task: Gather evidence (dot motion) and decide between multiple targets
Facilitation:
Network performance and decision dynamics are mainly preserved.
But: greater flexibility in weights!
Outlook
Idea: Use facilitation (or combination of facilitation and depression) for experimental findings that are currently not completely accounted for by the multiple choice model without facilitation:
Log Odds (coherence-dependent difference between in and out choice)
Extend the multiple choice model to more than 4 choices
…
Thanks…
… … to my supervisor to my supervisor Prof.Gustavo DecoProf.Gustavo Deco
… … Consolider Consolider
andand
… … to everybody for listening!to everybody for listening!