information transfer at dynamic synapses: effects of short-term plasticity patrick scott 1 anna...
TRANSCRIPT
Information Transfer at Dynamic Synapses: Effects of
Short-Term Plasticity Patrick Scott1
Anna Cowan1
Andrew Walker1
Christian Stricker1,2
1 Division of Neuroscience, John Curtin School of Medical Research, ANU, Canberra, ACT.
2 ANU Medical School
Background
• Probability of neurotransmitter release changes according to previous activity
• Four major short-term effects:– Release-dependent depression (depletion; RDD)– Release-independent depression (RID)– Facilitation– Frequency-dependent recovery (FDR)
• How do they affect information transfer? Nobody knows… (yet)
ModellingExtended mathematical model of short-term plasticity
• Phenomenological response to AP
• success/failure to release
• changes in probability of subsequent release
• no channels, Ca2+, etc.
• Previously
• RDD+F, deterministic (Fuhrmann et al 2002, J Neurophysiol 87:140)
• RDD+RID+FDR, quasi-stochastic (Fuhrmann et al 2004, J Physiol 557:415)
• Now
• RDD+RID+FDR+F, fully stochastic
• 4 coupled 1st-order ordinary differential equations, with an explicit (iterative) solution
Parameter Estimation
• Fitted models to EPSCs from paired recordings in Layers IV/V of rat somatosensory cortex (N = 11)
• Simultaneous fits to different stimuli, EPSCs/variances
• Defined typical ‘facilitating’ and ‘depressing’ connection parameters
• Reduced 2 values all < 1 (i.e. good fits)
Information Measurement
• Generated 5.4 hours of synthetic data for each parameter combination, as postsynaptic APs with an integrate-and-fire model
• Measured information transfer using information theory; entropy (Strong et al 1998, Phys Rev Lett 80:197)
• Includes extrapolations to infinite data size and window length
• For single vesicle and network configurations => spike timing and rate-coding dominated.
Results – RDD & RID
rec = recovery timescale from RDD U1R = strength of RID
RDD, spike timing RID, spike timing
RDD, rate coding RID, rate coding
Results – Facilitation & FDR
U1F = strength of facilitation 1 = strength of FDR
Facilitation, spike timing FDR, spike timing
Facilitation, rate coding FDR, rate coding
Results - ExampleRDD-dominated, no FDR RID-dominated, with FDR
U0 0.4
U1R 0
U1F 0
0 1 s
1 0.2
fac 0 s
FDR2 s
rec 500 ms
U0 0.4
U1R 0.2
U1F 0
0 1 s
1 0.2
fac 0 s
FDR2 s
rec 5 ms
Spike Timing:11.49 bits/s
Rate Coding: 1.84 bits/s
Spike Timing:27.31 bits/s
Rate Coding: 1.86 bits/s
Outcomes
• Information transfer by spike timing goes with release probability, not so for rate-coded information.–RDD: spike timing ↓, rate unaffected
–RID: spike timing ↓, rate ↓–Facilitation: spike timing ↑, rate ↓–FDR: spike timing ↑, rate ↑ or ↓ with other
parameters
Speculation
• Shows how brain can use alternative coding schemes and different dynamic processes to achieve varying goals at different network levels.
• Possible applications to neural prosthetics, neural electronics and artificial neural networks.