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Neurophysiology of mismatch negativity generation: a biophysical modeling study

Fernandez Pujol, C.; Bruce, J.; Thorpe, R. V.; Jones, S. R.; Dykstra, A. R.

2025-11-09 neuroscience
10.1101/2025.11.08.687373 bioRxiv
Show abstract

The mismatch negativity, or MMN, is a ubiquitous evoked brain response elicited by any discriminable change of an otherwise regular stimulus sequence. Despite its potential clinical relevance - the MMN is known to be affected by brain state, lesions, and neurologic/psychiatric disorders - and a growing body of animal work, the underlying neurophysiology of the MMN is not well understood. This hinders translation of circuit-level animal findings and mitigates the utility of the MMN as a neurologic/psychiatric biomarker. Here, we used biophysical modeling to examine the neurophysiological basis of the MMN as measured in a canonical auditory oddball paradigm with frequency deviants (i.e., tones whose frequency was shifted slightly with respect to standard tones). The response to standards was successfully modeled by a typical feedforward-followed-by-feedback input sequence. The response to deviants required additional, prolonged input to supragranular layers, consistent with input from the non-lemniscal thalamus. This additional input resulted in downward-going pyramidal-neuron currents in both layer 2/3 (via indirect somatic inhibition) and, critically, layer 5 (via direct apical excitation), which together generated the MMN. The results suggest that current circuit-level models of MMN generation derived from animal models are incomplete, and that further work is required to characterize the underlying neurophysiology of the MMN. SIGNIFICANCE STATEMENTThe mismatch negativity, or MMN, is a change-related brain response and one of the most widely studied brain responses in neuroscience. However, despite its prevalence and potential utility as a biomarker for neurological and psychiatric disorders, its underlying neurophysiology is not well understood. We combined MEG with biophysical modeling to better understand the cells, circuits, and cortical laminae that contribute to deviance processing and the MMN in humans.

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