Human Single‐Neuron Responses to Multi‐Feature Auditory Deviants: Evidence From Medial Temporal Lobe
Vinícius R. Carvalho, Alejandro Hugo Nasimbera, Silvia Kochen, Anne‐Kristin Solbakk, Alejandro O. BlenkmannABSTRACT
The ability to detect unexpected sounds within regular acoustic patterns is fundamental to adaptive behaviour. This capacity is reflected in the mismatch negativity and has been extensively studied in humans and animal models. Surprisingly, single‐unit recordings during auditory deviance detection in humans remain exceptionally rare. Here, we characterized single and multi‐unit responses to auditory deviants in frequency, location, intensity and timing dimensions, using the Optimum‐1 multi‐feature oddball paradigm during unattended listening. Microwire recordings from 13 patients with drug‐resistant epilepsy yielded units from the amygdala ( n = 48), hippocampus ( n = 46), complemented by case‐level observations from Heschl's gyrus and posterior insula ( n = 2 each). Amygdala showed multi‐phase responses, with timing deviants eliciting the strongest and earliest effects: suppression around 60 ms followed by enhancement around 200 ms. Intensity deviants produced suppression around 300 ms. Hippocampus showed sparse engagement with no apparent feature specificity besides a weak late effect of sound frequency at the ensemble level (350–400 ms). Case‐level Heschl's gyrus recordings revealed functional heterogeneity, with responses ranging from early gap‐specific to late frequency and intensity activity. Case‐level insula units showed intensity‐selective responses and late spatial processing with contralateral enhancement for location deviants. Our results, particularly the amygdala response profile (early suppression and later enhancement), suggest temporally dissociable mechanisms of deviance encoding at the subcortical level, while the sparse hippocampal responses indicate limited engagement in deviance detection during passive listening. Overall, these findings provide the first human single‐unit characterization of multi‐feature auditory deviance processing, establishing a critical baseline for understanding cellular mechanisms of predictive auditory processing.