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A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo ActivityAn Approximation to the Adaptive Exponential Integrate-and-Fire Neuron Model Allows Fast and Predictive Fitting to Physiological DataMethod for stationarity-segmentation of spike train data with application to the Pearson cross-correlation.Neurocomputational models of time perception.A computational model of prefrontal cortex based on physiologically derived cellular parameter distributions.A neurocomputational model of temporal processing: evidence from sequence experiments.The neural representation of time: an information-theoretic perspective.A neurocomputational model for optimal temporal processing.Flexible resonance in prefrontal networks with strong feedback inhibition
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description
researcher ORCID ID = 0000-0001-6802-7718
@en
wetenschapper
@nl
name
Joachim Hass
@ast
Joachim Hass
@en
Joachim Hass
@es
Joachim Hass
@nl
type
label
Joachim Hass
@ast
Joachim Hass
@en
Joachim Hass
@es
Joachim Hass
@nl
prefLabel
Joachim Hass
@ast
Joachim Hass
@en
Joachim Hass
@es
Joachim Hass
@nl
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15026123000
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P496
0000-0001-6802-7718