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Alpha oscillations in the auditory cortex have been associated with attention and the suppression of irrelevant information. However, their anatomical organization and interaction with other neural processes remain unclear. Do alpha oscillations function as a local mechanism within most neural sources to regulate their internal excitation/inhibition balance, or do they belong to separated inhibitory sources gating information across the auditory network? To address this question, we acquired intracerebral electrophysiological recordings from epilepsy patients during rest and tones listening. Thanks to independent component analysis, we disentangled the different neural sources and labeled them as “oscillatory” if they presented strong alpha oscillations at rest, and/or “evoked” if they displayed a significant evoked response to the stimulation. Our results show that 1) sources are condition-specific and segregated in the auditory cortex, 2) both sources have a high-gamma response followed by an induced alpha suppression, 3) only oscillatory sources present a sustained alpha suppression during all the stimulation period. We hypothesize that there are two different alpha oscillations in the auditory cortex: an induced bottom-up response indicating a selective engagement of the primary cortex to process the stimuli, and a sustained suppression reflecting a general disinhibited state of the network to process sensory information.
Alpha oscillations in the auditory cortex have been associated with attention and the suppression of irrelevant information. However, their anatomical organization and interaction with other neural processes remain unclear. Do alpha oscillations function as a local mechanism within most neural sources to regulate their internal excitation/inhibition balance, or do they belong to separated inhibitory sources gating information across the auditory network? To address this question, we acquired intracerebral electrophysiological recordings from epilepsy patients during rest and tones listening. Thanks to independent component analysis, we disentangled the different neural sources and labeled them as “oscillatory” if they presented strong alpha oscillations at rest, and/or “evoked” if they displayed a significant evoked response to the stimulation. Our results show that 1) sources are condition-specific and segregated in the auditory cortex, 2) both sources have a high-gamma response followed by an induced alpha suppression, 3) only oscillatory sources present a sustained alpha suppression during all the stimulation period. We hypothesize that there are two different alpha oscillations in the auditory cortex: an induced bottom-up response indicating a selective engagement of the primary cortex to process the stimuli, and a sustained suppression reflecting a general disinhibited state of the network to process sensory information.
Language comprehension involves the grouping of words into larger multiword chunks. This is required to recode information into sparser representations to mitigate memory limitations and counteract forgetting. It has been suggested that electrophysiological processing time windows constrain the formation of these units. Specifically, the period of rhythmic neural activity (i.e., slow-frequency neural oscillations) may set an upper limit of 2–3 sec. Here, we assess whether learning of new multiword chunks is also affected by this neural limit. We applied an auditory statistical learning paradigm of an artificial language while manipulating the duration of to-be-learnt chunks. Participants listened to isochronous sequences of disyllabic pseudowords from which they could learn hidden three-word chunks based on transitional probabilities. We presented chunks of 1.95, 2.55, and 3.15 sec that were created by varying the pause interval between pseudowords. In a first behavioral experiment, we tested learning using an implicit target detection task. We found better learning for chunks of 2.55 sec as compared to longer durations in line with an upper limit of the proposed time constraint. In a second experiment, we recorded participants' electroencephalogram during the exposure phase to use frequency tagging as a neural index of statistical learning. Extending the behavioral findings, results show a significant decline in neural tracking for chunks exceeding 3 sec as compared to both shorter durations. Overall, we suggest that language learning is constrained by endogenous time constraints, possibly reflecting electrophysiological processing windows.
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