Response to simultaneous long-range inputs and oscillatory inputs in a multiscale model of M1 microcircuits

TitleResponse to simultaneous long-range inputs and oscillatory inputs in a multiscale model of M1 microcircuits
Publication TypeConference Paper
Year of Publication2019
AuthorsDura-Bernal, S.., Neymotin S.. A., Suter B.. A., Kelley C.., Tekin R.., Shepherd G.. M., & Lytton W.. W.
Conference NameSociety for Neuroscience 2019 (SFN '19)
Keywords2019, sfn 2019, Society for Neuroscience

We developed a multiscale model of mouse primary motor cortex (M1) microcircuits. The model simulates a cylindrical volume of cortical tissue with over 10,000 biophysically detailed neurons and 30 million synaptic connections. Neuron densities, classes, morphology and biophysics, and connectivity at the long-range, local and dendritic scale were derived from published experimental data. Our model includes most major long-range inputs, primarily arising from posterior nucleus (PO) and ventrolateral thalamus (VL), and contralateral M1, primary somatosensory (S1), secondary somatosensory (S2), secondary motor (M2), and orbital (OC) cortices. We used the model to study the M1 circuit responses to simultaneous long-range inputs from different regions. We compared responses to short pulses from individual regions to combined pulses from two or more regions at varying time lags to investigate dynamical pathway interactions and information flow within the M1 microcircuit. Preliminary results showed M1 response to S2 and M2 inputs depends strongly on the order of, and interval between inputs, and the level of Ih current in pyramidal-tract corticospinal (PT) neurons (one important effect of neuromodulation by norepinephrine). We also studied oscillatory inputs with a variety of dominant frequencies seen in cortex. We computed frequency preference (resonance) of multiple populations and of different dendritic regions within individual neurons. Preliminary results indicated that IT5A and PT5B response to IT2/3 stimulation depends on frequency, phase and PT Ih level. Our results support the hypothesis that the brain encodes multiple parallel information pathways, multiplexing within and across frequencies, by filtering oscillatory synaptic inputs at the circuit and cellular level.For each of the conditions above, we computed and correlated measures of neural activity responses at multiple spatiotemporal scales: single-neuron voltage traces, single-neuron and population spiking activity, local field potentials (LFP), primary currents contributing to electro- and magnetoencephalogram (EEG/MEG) signals, and information transfer measures. Interactions observed within scale include synchronous firing of neuronal ensembles with LFP phase-amplitude coupling; interactions across scales included dendritic frequency resonance filtering synaptic inputs, and coupling of cell spiking with large-scale LFP/EEG/MEG oscillations. Analyzing correlations within and across scales identified mechanisms of multi-plexed neural signaling, and predicted observables that can be pursued experimentally.