Biology subjects

Chandresekaran, B.

Publications and source records attributed to Chandresekaran, B..

3 recordsLinked to original sources

bioRxiv2021

Linear superposition of responses evoked by individual glottal pulses explain over 80% of the frequency following response to human speech in the macaque monkey

The frequency-following response (FFR) is a scalp-recorded electrophysiological potential that closely follows the periodicity of complex sounds such as speech. It has been suggested that FFRs reflect the linear superposition of responses that are triggered by the glottal pulse in each cycle of the fundamental frequency (F0 responses) and sequentially propagate through auditory processing stages in brainstem, midbrain, and cortex. However, this conceptualization of the FFR is debated, and it remains unclear if and how well a simple linear superposition can capture the spectro-temporal complexity of FFRs that are generated within the highly recurrent and non-linear auditory system. To address this question, we used a deconvolution approach to compute the hypothetical F0 responses that best explain the FFRs in rhesus monkeys to human speech and click trains with time-varying pitch patterns. The linear superposition of F0 responses explained well over 90% of the variance of click train steady state FFRs and well over 80% of mandarin tone steady state FFRs. The F0 responses could be measured with high signal-to-noise ratio and featured several spectro-temporally and topographically distinct components that likely reflect the activation of brainstem (<5ms; 200-1000 Hz), midbrain (5-15 ms; 100-250 Hz) and cortex (15-35 ms; ~90 Hz). In summary, our results in the monkey support the notion that FFRs arise as the superposition of F0 responses by showing for the first time that they can capture the bulk of the variance and spectro-temporal complexity of FFRs to human speech with time-varying pitch. These findings identify F0 responses as a potential diagnostic tool that may be useful to reliably link altered FFRs in speech and language disorders to altered F0 responses and thus to specific latencies, frequency bands and ultimately processing stages.

neuroscience↗

bioRxiv2021

Deconstructing the Cortical Sources of Frequency Following Responses to Speech: A Cross-species Approach

Time-varying pitch is a vital cue for human speech perception. Neural processing of time-varying pitch has been extensively assayed using scalp-recorded frequency-following responses (FFRs), an electrophysiological signal thought to reflect integrated phase-locked neural ensemble activity from subcortical auditory areas. Emerging evidence increasingly points to a putative contribution of auditory cortical ensembles to the scalp-recorded FFRs. However, the properties of cortical FFRs and precise characterization of laminar sources are still unclear. Here we used direct human intracortical recordings as well as extra- and intracranial recordings from macaques and guinea pigs to characterize the properties of cortical sources of FFRs to time-varying pitch patterns. We found robust FFRs in the auditory cortex across all species. We leveraged representational similarity analysis as a translational bridge to characterize similarities between the human and animal models. Laminar recordings in animal models showed FFRs emerging primarily from the thalamorecepient layers of the auditory cortex. FFRs arising from these cortical sources significantly contributed to the scalp-recorded FFRs via volume conduction. Our research paves the way for a wide array of studies to investigate the role of cortical FFRs in auditory perception and plasticity. Significance StatementFrequency following responses (FFRs) to speech are scalp-recorded neural signals that inform the fidelity of sound encoding in the auditory system. FFRs, long believed to arise from brainstem and midbrain, have shaped our understanding of sub-cortical auditory processing and plasticity. Non-invasive studies have shown cortical contributions to the FFRs, however, this is still actively debated. Here we employed direct cortical recordings to trace the cortical contribution to the FFRs and characterize the properties of these cortical FFRs. With extra-cranial and intra-cranial recordings within the same subjects we show that cortical FFRs indeed contribute to the scalp-recorded FFRs, and their response properties differ from the sub-cortical FFRs. The findings provide strong evidence to revisit and reframe the FFR driven theories and models of sub-cortical auditory processing and plasticity with careful characterization of cortical and sub-cortical components in the scalp-recorded FFRs.

neuroscience↗

bioRxiv2021

Separate neural dynamics underlying the acquisition of different auditory category structures

Current models of auditory category learning argue for a rigid specialization of hierarchically organized regions that are fine-tuned to extracting and mapping acoustic dimensions to categories. We test a competing hypothesis: the neural dynamics of emerging auditory representations are driven by category structures and learning strategies. We designed a category learning experiment where two groups of learners learned novel auditory categories with identical dimensions but differing category structures: rule-based (RB) and information-integration (II) based categories. Despite similar learning accuracies, strategies and cortico-striatal systems processing feedback differed across structures. Emergent neural representations of category information within an auditory frontotemporal pathway exclusively for the II learning task. In contrast, the RB task yielded neural representations within distributed regions involved in cognitive control that emerged at different time-points of learning. Our results demonstrate that learners neural systems are flexible and show distinct spatiotemporal patterns that are not dimension-specific but reflect underlying category structures. SignificanceWhether it is an alarm signifying danger or the characteristics of background noise, humans are capable of rapid auditory learning. Extant models posit that novel auditory representations emerge in the superior temporal gyrus, a region specialized for extracting behaviorally relevant auditory dimensions and transformed onto decisions via the dorsal auditory stream. Using a computational cognitive neuroscience approach, we offer an alternative viewpoint: emergent auditory representations are highly flexible, showing distinct spatial and temporal trajectories that reflect different category structures.

bioinformatics↗