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Human tactile FA1 neurons (Hay and Pruszynski 2020)
 
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Model Information
Model File
Accession:
266798
"... we show that synaptic integration across the complex signals from the first-order neuronal population could underlie human ability to accurately (< 3°) and rapidly process the orientation of edges moving across the fingertip. We first derive spiking models of human first-order tactile neurons that fit and predict responses to moving edges with high accuracy. We then use the model neurons in simulating the peripheral neuronal population that innervates a fingertip. We train classifiers performing synaptic integration across the neuronal population activity, and show that synaptic integration across first-order neurons can process edge orientations with high acuity and speed. ... our models suggest that integration of fast-decaying (AMPA-like) synaptic inputs within short timescales is critical for discriminating fine orientations, whereas integration of slow-decaying (NMDA-like) synaptic inputs supports discrimination of coarser orientations and maintains robustness over longer timescales"
Reference:
1 .
Hay E, Pruszynski JA (2020) Orientation processing by synaptic integration across first-order tactile neurons.
PLoS Comput Biol
16
:e1008303
[
PubMed
]
Citations
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Model Information
(Click on a link to find other models with that property)
Model Type:
Neuron or other electrically excitable cell;
Axon;
Realistic Network;
Brain Region(s)/Organism:
Human;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
AMPA;
NMDA;
Gene(s):
Transmitter(s):
Simulation Environment:
MATLAB;
Model Concept(s):
Sensory coding;
Synaptic Integration;
Receptive field;
Implementer(s):
Search NeuronDB
for information about:
AMPA
;
NMDA
;
Download the displayed file
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Hay2020
data
models
readme.txt
add_noise_stim.m
align_times.m
calc_err.m
calc_performance.m
cell_response.m
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F3_t_win.m
F4_network_weights_AMPA20.m
F5_network_weights_NMDA20.m
F6_RF_KeyCells.m
F7_simple_population.m
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get_innervation.m
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Hay2020.zip
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mean_exp_response.m
model_rotation.m
model_variation.m
model2w.m
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mutate_model.m
new_models.m
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plot_skin_patch.m
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select_model.m
sim_edge_response.m
st2epsp.m
test_model.m
tile_patch.m
w2img.m
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