Neural Correlates of Tactile Detection: A Combined Magnetoencephalography and Biophysically Based Computational Modeling Study

Abstract

Previous reports conflict as to the role of primary somatosensory neocortex (SI) in tactile detection. We addressed this question in normal human subjects using whole-head magnetoencephalography (MEG) recording. We found that the evoked signal (0 -175 ms) showed a prominent equivalent current dipole that localized to the anterior bank of the postcentral gyrus, area 3b of SI. The magnitude and timing of peaks in the SI waveform were stimulus amplitude dependent and predicted perception beginning at ϳ70 ms after stimulus. To make a direct and principled connection between the SI waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. The SI evoked response was successfully reproduced from the intracellular currents in pyramidal neurons driven by a sequence of lamina-specific excitatory input, consisting of output from the granular layer (ϳ25 ms), exogenous input to the supragranular layers (ϳ70 ms), and a second wave of granular output (ϳ135 ms). The model also predicted that SI correlates of perception reflect stronger and shorter-latency supragranular and late granular drive during perceived trials. These findings strongly support the view that signatures of tactile detection are present in human SI and are mediated by local neural dynamics induced by lamina-specific synaptic drive. Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception.

Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice

“…This prediction is not currently represented in our model. Based on estimates on the size of current dipole signals produced by spiking activity in individual PNs (34,35,37), spiking activity in a small population of neurons would not impact our results provided the spiking is sufficiently sparse and desynchronized relative to the size of the network producing the subthreshold oscillation.…”

“…Key to the development of our theory of beta emergence was construction of a computational model of a laminar neocortical circuit uniquely designed to reproduce the primary electrical currents underlying macroscopic MEG/EEG signals accurately (1,(34)(35)(36)(37). The neural origin of the estimated primary currents (J p ) is thought to be the aggregate of postsynaptic longitudinal currents flowing inside the apical dendrites of the large, spatially aligned neocortical PNs (Fig.…”

“…The primary current signals were simulated as the net intracellular current flow in a direction parallel to the long apical dendrites, with units directly comparable to the MEG data (expressed as current (nA) × distance (m), or nanoampere meters, nAm) (1,(34)(35)(36)(37). The PNs were embedded in a laminar model of a neocortical column (100 PNs, 35 interneurons per layer) that received an AMPAergic excitatory postsynaptic drive to the granular and supragranular layers (Fig.…”

“…Further, we found beta events had a consistent temporal profile. To study the cellular and network level mechanisms creating this beta activity, we used a biophysically principled model of a laminar cortical circuit designed specifically to simulate human MEG/EEG-measured primary current source signals (1,(34)(35)(36)(37). In keeping the output of our model in close agreement with our MEG data, we arrived at the prediction that these beta events are not inherited linearly from subcortical structures or generated by the spiking interactions in local neocortical circuits.…”

Modeling Gaba Alterations in Schizophrenia: A Link Between Impaired Inhibition and Altered Gamma and Beta Range Auditory Entrainment

“…For example, we have not considered the impact of cortical cell geometry on signal generation, which has been the subject of recent modeling work (Jones et al 2007). Instead we have based our modeling on the assumption that the MEG data modeled represents collective cell activity localized to the auditory cortex and that summed excitatory synaptic activity in our models is a sufficient approximation of the MEG signal.…”