PowerPoint Presentation
Computational Modeling of the Auditory Periphery:From Soundfiles
to Spiketrains
Marcos CantuCenter for Computational Neuroscience and Neural
Technology (CompNet)Graduate Program for Neuroscience (GPN)Boston
[email protected]
MCN 2013Figure 11. Circuit model of the DCN that includes all
the effects described above. Shaded neurons are the primarily
auditory neurons described in Fig. 6. The granule cell and
cartwheel cell of the superficial layer and a GABAergic neuron of
unknown identity have been added. The relative size of synaptic
terminals corresponds roughly to the relative synaptic strength
needed to account for the effects described above. (Redrawn from
Davis and Young 2000 with permission.)1Project Aims:- Create Large
Scale Spiking Network with several Cell Types- Model Sensory
Transduction at the Auditory Periphery- Use Natural Ethologically
Relevant Stimuli (i.e. Vocalizations)I want to see how the circuit
reacts to natural sound. 2Basilar Membrane model(Bank of Bandpass
Filters)Meddis Hair Cell ModelAuditory Nerve
FiberSpiketrainsAcoustic StimulusAcoustic StimulusBasilar Membrane
model(Bank of Bandpass Filters)Auditory Nerve
FiberSpiketrainsAuditory Toolboxby Malcolm
SlaneyPatterson-HoldsworthERB Filter Bank Ray Meddis, 1986 and
1990Auditory Toolboxby Malcolm SlaneyMeddis Hair Cell ModelEugene
Izhikevich Spiking Neuron (2003)
Meddis Hair Cell Model Gammatone Filterbank Spiking Izhikevich
Neurons .WAV audiofileFrom Soundfiles to Spiketrains
Getting TO the cochlear nucleus.
Before I get to the cochlear nucleus, I should talk about how I
got to the cochlear nucleus. That is, how I created the input
vector for each timestep of the network.
From sound to spiketrain5
Sound to spiketrain Meddis Hair Cell Model(actually Sound to
Probability)
q = free transmitter pool c = transmitter at synaptic cleft w =
reprocessed transmitter The higher the stimulus, the higher the
permeability (k)output:prob(event) = hc(t) dt
Inner hair cellAuditory nerve fiberK is driven by filter respone
at frequency6Spiking neurons were modeled with the system of
ordinary differential equations developed by Eugene M. Izhikevich :
v = 0.04v2 + 5v + 140 - u + I u = a(bv - u) with the auxiliary
after-spike resetting: if v >= 30 mV then v c and u u + dv
corresponds to the membrane potential of the neuron u represents a
membrane recovery variable
a, b, c and d are dimensionless parameters
a time scale of recovery, b the sensitivity of recovery, c the
after-spike reset value of the membrane potential d the after-spike
reset of the recovery variable. Izhikevich, EM: Simple model of
spiking neurons. IEEE Transactions on Neural Networks 2003,
14(6):1569-1572 (2003)Auditory Nerve Fibers (ANFs)K is driven by
filter respone at frequency7
Meddis Hair Cell Model Gammatone Filterbank Spiking Izhikevich
Neurons .WAV audiofileFrom Soundfiles to Spiketrains
Getting TO the cochlear nucleus.
Before I get to the cochlear nucleus, I should talk about how I
got to the cochlear nucleus. That is, how I created the input
vector for each timestep of the network.
From sound to spiketrain8Spiking Neuron Model of Dorsal Cochlear
Nucleus (DCN): 4 cell types2 excitatory: Auditory Nerve Fiber
(Input to DCN)Type IV cell (Output Cell of DCN)2 inhibitory: Type
II cell (Low to High Frequency Inhibition)WBI cell (Wide Band
Inhibition)the responses to sound of DCN neurons display
substantial inhibitory influencesthe responses to sound of DCN
neurons display substantial inhibitory influences9
ouYoung and Davis 2001Wiring Diagram of Principal Cell Types in
the Dorsal Cochlear Nucleus:All three cell types receive
feedforward input from frequency tuned Auditory Nerve Fibers
(ANFs)This is the circuitry in functional space, not in physical
space.
Output CellFigure 11. Circuit model of the DCN that includes all
the effects described above. Shaded neurons are the primarily
auditory neurons described in Fig. 6. The granule cell and
cartwheel cell of the superficial layer and a GABAergic neuron of
unknown identity have been added. The relative size of synaptic
terminals corresponds roughly to the relative synaptic strength
needed to account for the effects described above. (Redrawn from
Davis and Young 2000 with permission.)
This is the circuitry in functional space, not in physical
space. 10
Figure 11. Circuit model of the DCN that includes all the
effects described above. Shaded neurons are the primarily auditory
neurons described in Fig. 6. The granule cell and cartwheel cell of
the superficial layer and a GABAergic neuron of unknown identity
have been added. The relative size of synaptic terminals
corresponds roughly to the relative synaptic strength needed to
account for the effects described above. (Redrawn from Davis and
Young 2000 with permission.)11
Recovering the Missing Fundamental with a Feedforward
NetworkSpiking Network (1000 frequency tuned neurons in each
layer)12
Spiking Network (1000 frequency tuned neurons in each
layer)Recovering the Missing Fundamental with a Feedforward
Network13
Projection to 1st Population1st 2nd2nd 3rd3rd 4thFeed-Forward
Connectivity Matrices14
Spike Timing Dependent Plasticity (STDP) Connectivity Matrix
(previous work)15
1st 2nd2nd 3rd3rd 4thFeed-Forward Connectivity Matrices
16
Fundamental Frequency (500Hz) Absent in Input Spectrum Larger
Spiking Network (4000 frequency tuned neurons in each layer)17
Fundamental Frequency (500Hz) Present in Input Spectrum Larger
Spiking Network (4000 frequency tuned neurons in each
layer)18Future Directions:Adding Various Forms of Inhibition to
NetworkAdding Plasticity and Training the Network on Natural
SoundAdding Top-Down Recurrent Connectivity19
