Functional geometry of auditory cortical resting state networks derived from intracranial electrophysiology.

Understanding central auditory processing critically depends on defining underlying auditory cortical networks and their relationship to the rest of the brain. We addressed these questions using resting state functional connectivity derived from human intracranial electroencephalography. Mapping recording sites into a low-dimensional space where proximity represents functional similarity revealed a hierarchical organization. At a fine scale, a group of auditory cortical regions excluded several higher-order auditory areas and segregated maximally from the prefrontal cortex. On mesoscale, the proximity of limbic structures to the auditory cortex suggested a limbic stream that parallels the classically described ventral and dorsal auditory processing streams. Identities of global hubs in anterior temporal and cingulate cortex depended on frequency band, consistent with diverse roles in semantic and cognitive processing. On a macroscale, observed hemispheric asymmetries were not specific for speech and language networks. This approach can be applied to multivariate brain data with respect to development, behavior, and disorders.

Analogous cortical reorganization accompanies entry into states of reduced consciousness during anesthesia and sleep.

Theories of consciousness suggest that brain mechanisms underlying transitions into and out of unconsciousness are conserved no matter the context or precipitating conditions. We compared signatures of these mechanisms using intracranial electroencephalography in neurosurgical patients during propofol anesthesia and overnight sleep and found strikingly similar reorganization of human cortical networks. We computed the "effective dimensionality" of the normalized resting state functional connectivity matrix to quantify network complexity. Effective dimensionality decreased during stages of reduced consciousness (anesthesia unresponsiveness, N2 and N3 sleep). These changes were not region-specific, suggesting global network reorganization. When connectivity data were embedded into a low-dimensional space in which proximity represents functional similarity, we observed greater distances between brain regions during stages of reduced consciousness, and individual recording sites became closer to their nearest neighbors. These changes corresponded to decreased differentiation and functional integration and correlated with decreases in effective dimensionality. This network reorganization constitutes a neural signature of states of reduced consciousness that is common to anesthesia and sleep. These results establish a framework for understanding the neural correlates of consciousness and for practical evaluation of loss and recovery of consciousness.

Learning nonnative speech sounds changes local encoding in the adult human cortex.

Adults can learn to identify nonnative speech sounds with training, albeit with substantial variability in learning behavior. Increases in behavioral accuracy are associated with increased separability for sound representations in cortical speech areas. However, it remains unclear whether individual auditory neural populations all show the same types of changes with learning, or whether there are heterogeneous encoding patterns. Here, we used high-resolution direct neural recordings to examine local population response patterns, while native English listeners learned to recognize unfamiliar vocal pitch patterns in Mandarin Chinese tones. We found a distributed set of neural populations in bilateral superior temporal gyrus and ventrolateral frontal cortex, where the encoding of Mandarin tones changed throughout training as a function of trial-by-trial accuracy ("learning effect"), including both increases and decreases in the separability of tones. These populations were distinct from populations that showed changes as a function of exposure to the stimuli regardless of trial-by-trial accuracy. These learning effects were driven in part by more variable neural responses to repeated presentations of acoustically identical stimuli. Finally, learning effects could be predicted from speech-evoked activity even before training, suggesting that intrinsic properties of these populations make them amenable to behavior-related changes. Together, these results demonstrate that nonnative speech sound learning involves a wide array of changes in neural representations across a distributed set of brain regions.

Gamma Activation and Alpha Suppression within Human Auditory Cortex during a Speech Classification Task.

The dynamics of information flow within the auditory cortical hierarchy associated with speech processing and the emergence of hemispheric specialization remain incompletely understood. To study these questions with high spatiotemporal resolution, intracranial recordings in 29 human neurosurgical patients of both sexes were obtained while subjects performed a semantic classification task. Neural activity was recorded from posteromedial portion of Heschl's gyrus (HGPM) and anterolateral portion of Heschl's gyrus (HGAL), planum temporale (PT), planum polare, insula, and superior temporal gyrus (STG). Responses to monosyllabic words exhibited early gamma power increases and a later suppression of alpha power, envisioned to represent feedforward activity and decreased feedback signaling, respectively. Gamma activation and alpha suppression had distinct magnitude and latency profiles. HGPM and PT had the strongest gamma responses with shortest onset latencies, indicating that they are the earliest auditory cortical processing stages. The origin of attenuated top-down influences in auditory cortex, as indexed by alpha suppression, was in STG and HGAL. Gamma responses and alpha suppression were typically larger to nontarget words than tones. Alpha suppression was uniformly greater to target versus nontarget stimuli. Hemispheric bias for words versus tones and for target versus nontarget words, when present, was left lateralized. Better task performance was associated with increased gamma activity in the left PT and greater alpha suppression in HGPM and HGAL bilaterally. The prominence of alpha suppression during semantic classification and its accessibility for noninvasive electrophysiologic studies suggests that this measure is a promising index of auditory cortical speech processing.SIGNIFICANCE STATEMENT Understanding the dynamics of cortical speech processing requires the use of active tasks. This is the first comprehensive intracranial electroencephalography study to examine cortical activity within the superior temporal plane, lateral superior temporal gyrus, and the insula during a semantic classification task. Distinct gamma activation and alpha suppression profiles clarify the functional organization of feedforward and feedback processing within the auditory cortical hierarchy. Asymmetries in cortical speech processing emerge at early processing stages. Relationships between cortical activity and task performance are interpreted in the context of current models of speech processing. Results lay the groundwork for iEEG studies using connectivity measures of the bidirectional information flow within the auditory processing hierarchy.

High-dimensional multivariate autoregressive model estimation of human electrophysiological data using fMRI priors.

Multivariate autoregressive (MVAR) model estimation enables assessment of causal interactions in brain networks. However, accurately estimating MVAR models for high-dimensional electrophysiological recordings is challenging due to the extensive data requirements. Hence, the applicability of MVAR models for study of brain behavior over hundreds of recording sites has been very limited. Prior work has focused on different strategies for selecting a subset of important MVAR coefficients in the model to reduce the data requirements of conventional least-squares estimation algorithms. Here we propose incorporating prior information, such as resting state functional connectivity derived from functional magnetic resonance imaging, into MVAR model estimation using a weighted group least absolute shrinkage and selection operator (LASSO) regularization strategy. The proposed approach is shown to reduce data requirements by a factor of two relative to the recently proposed group LASSO method of Endemann et al (Neuroimage 254:119057, 2022) while resulting in models that are both more parsimonious and more accurate. The effectiveness of the method is demonstrated using simulation studies of physiologically realistic MVAR models derived from intracranial electroencephalography (iEEG) data. The robustness of the approach to deviations between the conditions under which the prior information and iEEG data is obtained is illustrated using models from data collected in different sleep stages. This approach allows accurate effective connectivity analyses over short time scales, facilitating investigations of causal interactions in the brain underlying perception and cognition during rapid transitions in behavioral state.

Multivariate autoregressive model estimation for high-dimensional intracranial electrophysiological data.

Fundamental to elucidating the functional organization of the brain is the assessment of causal interactions between different brain regions. Multivariate autoregressive (MVAR) modeling techniques applied to multisite electrophysiological recordings are a promising avenue for identifying such causal links. They estimate the degree to which past activity in one or more brain regions is predictive of another region's present activity, while simultaneously accounting for the mediating effects of other regions. Including as many mediating variables as possible in the model has the benefit of drastically reducing the odds of detecting spurious causal connectivity. However, effective bounds on the number of MVAR model coefficients that can be estimated reliably from limited data make exploiting the potential of MVAR models challenging for even modest numbers of recording sites. Here, we utilize well-established dimensionality-reduction techniques to fit MVAR models to human intracranial data from ∼100 - 200 recording sites spanning dozens of anatomically and functionally distinct cortical regions. First, we show that high-dimensional MVAR models can be successfully estimated from long segments of data and yield plausible connectivity profiles. Next, we use these models to generate synthetic data with known ground-truth connectivity to explore the utility of applying principal component analysis and group least absolute shrinkage and selection operator (gLASSO) to reduce the number of parameters (connections) during model fitting to shorter data segments. We show that gLASSO is highly effective for recovering ground-truth connectivity in the limited data regime, capturing important features of connectivity for high-dimensional models with as little as 10 seconds of data. The methods presented here have broad applicability to the analysis of high-dimensional time series data in neuroscience, facilitating the elucidation of the neural basis of sensation, cognition, and arousal.

Cortical Responses to Vowel Sequences in Awake and Anesthetized States: A Human Intracranial Electrophysiology Study.

Elucidating neural signatures of sensory processing across consciousness states is a major focus in neuroscience. Noninvasive human studies using the general anesthetic propofol reveal differential effects on auditory cortical activity, with a greater impact on nonprimary and auditory-related areas than primary auditory cortex. This study used intracranial electroencephalography to examine cortical responses to vowel sequences during induction of general anesthesia with propofol. Subjects were adult neurosurgical patients with intracranial electrodes placed to identify epileptic foci. Data were collected before electrode removal surgery. Stimuli were vowel sequences presented in a target detection task during awake, sedated, and unresponsive states. Averaged evoked potentials (AEPs) and high gamma (70-150 Hz) power were measured in auditory, auditory-related, and prefrontal cortex. In the awake state, AEPs were found throughout studied brain areas; high gamma activity was limited to canonical auditory cortex. Sedation led to a decrease in AEP magnitude. Upon LOC, there was a decrease in the superior temporal gyrus and adjacent auditory-related cortex and a further decrease in AEP magnitude in core auditory cortex, changes in the temporal structure and increased trial-to-trial variability of responses. The findings identify putative biomarkers of LOC and serve as a foundation for future investigations of altered sensory processing.

Electrophysiology of the Human Superior Temporal Sulcus during Speech Processing.

The superior temporal sulcus (STS) is a crucial hub for speech perception and can be studied with high spatiotemporal resolution using electrodes targeting mesial temporal structures in epilepsy patients. Goals of the current study were to clarify functional distinctions between the upper (STSU) and the lower (STSL) bank, hemispheric asymmetries, and activity during self-initiated speech. Electrophysiologic properties were characterized using semantic categorization and dialog-based tasks. Gamma-band activity and alpha-band suppression were used as complementary measures of STS activation. Gamma responses to auditory stimuli were weaker in STSL compared with STSU and had longer onset latencies. Activity in anterior STS was larger during speaking than listening; the opposite pattern was observed more posteriorly. Opposite hemispheric asymmetries were found for alpha suppression in STSU and STSL. Alpha suppression in the STS emerged earlier than in core auditory cortex, suggesting feedback signaling within the auditory cortical hierarchy. STSL was the only region where gamma responses to words presented in the semantic categorization tasks were larger in subjects with superior task performance. More pronounced alpha suppression was associated with better task performance in Heschl's gyrus, superior temporal gyrus, and STS. Functional differences between STSU and STSL warrant their separate assessment in future studies.

Neural Signatures of Auditory Perceptual Bistability Revealed by Large-Scale Human Intracranial Recordings.

A key challenge in neuroscience is understanding how sensory stimuli give rise to perception, especially when the process is supported by neural activity from an extended network of brain areas. Perception is inherently subjective, so interrogating its neural signatures requires, ideally, a combination of three factors: (1) behavioral tasks that separate stimulus-driven activity from perception per se; (2) human subjects who self-report their percepts while performing those tasks; and (3) concurrent neural recordings acquired at high spatial and temporal resolution. In this study, we analyzed human electrocorticographic recordings obtained during an auditory task which supported mutually exclusive perceptual interpretations. Eight neurosurgical patients (5 male; 3 female) listened to sequences of repeated triplets where tones were separated in frequency by several semitones. Subjects reported spontaneous alternations between two auditory perceptual states, 1-stream and 2-stream, by pressing a button. We compared averaged auditory evoked potentials (AEPs) associated with 1-stream and 2-stream percepts and identified significant differences between them in primary and nonprimary auditory cortex, surrounding auditory-related temporoparietal cortex, and frontal areas. We developed classifiers to identify spatial maps of percept-related differences in the AEP, corroborating findings from statistical analysis. We used one-dimensional embedding spaces to perform the group-level analysis. Our data illustrate exemplar high temporal resolution AEP waveforms in auditory core region; explain inconsistencies in perceptual effects within auditory cortex, reported across noninvasive studies of streaming of triplets; show percept-related changes in frontoparietal areas previously highlighted by studies that focused on perceptual transitions; and demonstrate that auditory cortex encodes maintenance of percepts and switches between them.SIGNIFICANCE STATEMENT The human brain has the remarkable ability to discern complex and ambiguous stimuli from the external world by parsing mixed inputs into interpretable segments. However, one's perception can deviate from objective reality. But how do perceptual discrepancies occur? What are their anatomical substrates? To address these questions, we performed intracranial recordings in neurosurgical patients as they reported their perception of sounds associated with two mutually exclusive interpretations. We identified signatures of subjective percepts as distinct from sound-driven brain activity in core and non-core auditory cortex and frontoparietal cortex. These findings were compared with previous studies of auditory bistable perception and suggested that perceptual transitions and maintenance of perceptual states were supported by common neural substrates.

A Sound-Sensitive Source of Alpha Oscillations in Human Non-Primary Auditory Cortex.

The functional organization of human auditory cortex can be probed by characterizing responses to various classes of sound at different anatomical locations. Along with histological studies this approach has revealed a primary field in posteromedial Heschl's gyrus (HG) with pronounced induced high-frequency (70-150 Hz) activity and short-latency responses that phase-lock to rapid transient sounds. Low-frequency neural oscillations are also relevant to stimulus processing and information flow, however, their distribution within auditory cortex has not been established. Alpha activity (7-14 Hz) in particular has been associated with processes that may differentially engage earlier versus later levels of the cortical hierarchy, including functional inhibition and the communication of sensory predictions. These theories derive largely from the study of occipitoparietal sources readily detectable in scalp electroencephalography. To characterize the anatomical basis and functional significance of less accessible temporal-lobe alpha activity we analyzed responses to sentences in seven human adults (4 female) with epilepsy who had been implanted with electrodes in superior temporal cortex. In contrast to primary cortex in posteromedial HG, a non-primary field in anterolateral HG was characterized by high spontaneous alpha activity that was strongly suppressed during auditory stimulation. Alpha-power suppression decreased with distance from anterolateral HG throughout superior temporal cortex, and was more pronounced for clear compared to degraded speech. This suppression could not be accounted for solely by a change in the slope of the power spectrum. The differential manifestation and stimulus-sensitivity of alpha oscillations across auditory fields should be accounted for in theories of their generation and function.SIGNIFICANCE STATEMENT To understand how auditory cortex is organized in support of perception, we recorded from patients implanted with electrodes for clinical reasons. This allowed measurement of activity in brain regions at different levels of sensory processing. Oscillations in the alpha range (7-14 Hz) have been associated with functions including sensory prediction and inhibition of regions handling irrelevant information, but their distribution within auditory cortex is not known. A key finding was that these oscillations dominated in one particular non-primary field, anterolateral Heschl's gyrus, and were suppressed when subjects listened to sentences. These results build on our knowledge of the functional organization of auditory cortex and provide anatomical constraints on theories of the generation and function of alpha oscillations.

Cortical functional connectivity indexes arousal state during sleep and anesthesia.

Disruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained conscious experience (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced conscious experience (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will exhibit clear changes when transitioning into states of reduced consciousness, and (2) these changes will be similar for arousal states of comparable levels of consciousness during sleep and anesthesia. Using intracranial recordings from five adult neurosurgical patients, we compared resting state cortical functional connectivity (as measured by weighted phase lag index, wPLI) in the same subjects across arousal states during natural sleep [wake (WS), N1, N2, N3, REM] and propofol anesthesia [pre-drug wake (WA), sedated/responsive (S), and unresponsive (U)]. Analysis of alpha-band connectivity indicated a transition boundary distinguishing states of maintained and reduced conscious experience in both sleep and anesthesia. In wake states WS and WA, alpha-band wPLI within the temporal lobe was dominant. This pattern was largely unchanged in N1, REM, and S. Transitions into states of reduced consciousness N2, N3, and U were characterized by dramatic changes in connectivity, with dominant connections shifting to prefrontal cortex. Secondary analyses indicated similarities in reorganization of cortical connectivity in sleep and anesthesia. Shifts from temporal to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.

Sequence learning modulates neural responses and oscillatory coupling in human and monkey auditory cortex.

Learning complex ordering relationships between sensory events in a sequence is fundamental for animal perception and human communication. While it is known that rhythmic sensory events can entrain brain oscillations at different frequencies, how learning and prior experience with sequencing relationships affect neocortical oscillations and neuronal responses is poorly understood. We used an implicit sequence learning paradigm (an "artificial grammar") in which humans and monkeys were exposed to sequences of nonsense words with regularities in the ordering relationships between the words. We then recorded neural responses directly from the auditory cortex in both species in response to novel legal sequences or ones violating specific ordering relationships. Neural oscillations in both monkeys and humans in response to the nonsense word sequences show strikingly similar hierarchically nested low-frequency phase and high-gamma amplitude coupling, establishing this form of oscillatory coupling-previously associated with speech processing in the human auditory cortex-as an evolutionarily conserved biological process. Moreover, learned ordering relationships modulate the observed form of neural oscillatory coupling in both species, with temporally distinct neural oscillatory effects that appear to coordinate neuronal responses in the monkeys. This study identifies the conserved auditory cortical neural signatures involved in monitoring learned sequencing operations, evident as modulations of transient coupling and neuronal responses to temporally structured sensory input.

Auditory Predictive Coding across Awareness States under Anesthesia: An Intracranial Electrophysiology Study.

The systems-level mechanisms underlying loss of consciousness (LOC) under anesthesia remain unclear. General anesthetics suppress sensory responses within higher-order cortex and feedback connections, both critical elements of predictive coding hypotheses of conscious perception. Responses to auditory novelty may offer promise as biomarkers for consciousness. This study examined anesthesia-induced changes in auditory novelty responses over short (local deviant [LD]) and long (global deviant [GD]) time scales, envisioned to engage preattentive and conscious levels of processing, respectively. Electrocorticographic recordings were obtained in human neurosurgical patients (3 male, 3 female) from four hierarchical processing levels: core auditory cortex, non-core auditory cortex, auditory-related, and PFC. Stimuli were vowel patterns incorporating deviants within and across stimuli (LD and GD). Subjects were presented with stimuli while awake, and during sedation (responsive) and following LOC (unresponsive) under propofol anesthesia. LD and GD effects were assayed as the averaged evoked potential and high gamma (70-150 Hz) activity. In the awake state, LD and GD effects were present in all recorded regions, with averaged evoked potential effects more broadly distributed than high gamma activity. Under sedation, LD effects were preserved in all regions, except PFC. LOC was accompanied by loss of LD effects outside of auditory cortex. By contrast, GD effects were markedly suppressed under sedation in all regions and were absent following LOC. Thus, although the presence of GD effects is indicative of being awake, its absence is not indicative of LOC. Loss of LD effects in higher-order cortical areas may constitute an alternative biomarker of LOC.SIGNIFICANCE STATEMENT Development of a biomarker that indexes changes in the brain upon loss of consciousness (LOC) under general anesthesia has broad implications for elucidating the neural basis of awareness and clinical relevance to mechanisms of sleep, coma, and disorders of consciousness. Using intracranial recordings from neurosurgery patients, we investigated changes in the activation of cortical networks involved in auditory novelty detection over short (local deviance) and long (global deviance) time scales associated with sedation and LOC under propofol anesthesia. Our results indicate that, whereas the presence of global deviance effects can index awareness, their loss cannot serve as a biomarker for LOC. The dramatic reduction of local deviance effects in areas beyond auditory cortex may constitute an alternative biomarker of LOC.

Direct electrophysiological mapping of human pitch-related processing in auditory cortex.

This work sought correlates of pitch perception, defined by neural activity above the lower limit of pitch (LLP), in auditory cortical neural ensembles, and examined their topographical distribution. Local field potentials (LFPs) were recorded in eight patients undergoing invasive recordings for pharmaco-resistant epilepsy. Stimuli consisted of bursts of broadband noise followed by regular interval noise (RIN). RIN was presented at rates below and above the LLP to distinguish responses related to the regularity of the stimulus and the presence of pitch itself. LFPs were recorded from human cortical homologues of auditory core, belt, and parabelt regions using multicontact depth electrodes implanted in Heschl's gyrus (HG) and Planum Temporale (PT), and subdural grid electrodes implanted over lateral superior temporal gyrus (STG). Evoked responses corresponding to the temporal regularity of the stimulus were assessed using autocorrelation of the evoked responses, and occurred for stimuli below and above the LLP. Induced responses throughout the high gamma range (60-200 Hz) were present for pitch values above the LLP, with onset latencies of approximately 70 ms. Mapping of the induced responses onto a common brain space demonstrated variability in the topographical distribution of high gamma responses across subjects. Induced responses were present throughout the length of HG and on PT, which is consistent with previous functional neuroimaging studies. Moreover, in each subject, a region within lateral STG showed robust induced responses at pitch-evoking stimulus rates. This work suggests a distributed representation of pitch processing in neural ensembles in human homologues of core and non-core auditory cortex.

Processing of auditory novelty across the cortical hierarchy: An intracranial electrophysiology study.

Under the predictive coding hypothesis, specific spatiotemporal patterns of cortical activation are postulated to occur during sensory processing as expectations generate feedback predictions and prediction errors generate feedforward signals. Establishing experimental evidence for this information flow within cortical hierarchy has been difficult, especially in humans, due to spatial and temporal limitations of non-invasive measures of cortical activity. This study investigated cortical responses to auditory novelty using the local/global deviant paradigm, which engages the hierarchical network underlying auditory predictive coding over short ('local deviance'; LD) and long ('global deviance'; GD) time scales. Electrocorticographic responses to auditory stimuli were obtained in neurosurgical patients from regions of interest (ROIs) including auditory, auditory-related and prefrontal cortex. LD and GD effects were assayed in averaged evoked potential (AEP) and high gamma (70-150 Hz) signals, the former likely dominated by local synaptic currents and the latter largely reflecting local spiking activity. AEP LD effects were distributed across all ROIs, with greatest percentage of significant sites in core and non-core auditory cortex. High gamma LD effects were localized primarily to auditory cortex in the superior temporal plane and on the lateral surface of the superior temporal gyrus (STG). LD effects exhibited progressively longer latencies in core, non-core, auditory-related and prefrontal cortices, consistent with feedforward signaling. The spatial distribution of AEP GD effects overlapped that of LD effects, but high gamma GD effects were more restricted to non-core areas. High gamma GD effects had shortest latencies in STG and preceded AEP GD effects in most ROIs. This latency profile, along with the paucity of high gamma GD effects in the superior temporal plane, suggest that the STG plays a prominent role in initiating novelty detection signals over long time scales. Thus, the data demonstrate distinct patterns of information flow in human cortex associated with auditory novelty detection over multiple time scales.

Neural phase locking predicts BOLD response in human auditory cortex.

Natural environments elicit both phase-locked and non-phase-locked neural responses to the stimulus in the brain. The interpretation of the BOLD signal to date has been based on an association of the non-phase-locked power of high-frequency local field potentials (LFPs), or the related spiking activity in single neurons or groups of neurons. Previous studies have not examined the prediction of the BOLD signal by phase-locked responses. We examined the relationship between the BOLD response and LFPs in the same nine human subjects from multiple corresponding points in the auditory cortex, using amplitude modulated pure tone stimuli of a duration to allow an analysis of phase locking of the sustained time period without contamination from the onset response. The results demonstrate that both phase locking at the modulation frequency and its harmonics, and the oscillatory power in gamma/high-gamma bands are required to predict the BOLD response. Biophysical models of BOLD signal generation in auditory cortex therefore require revision and the incorporation of both phase locking to rhythmic sensory stimuli and power changes in the ensemble neural activity.

Neural Correlates of Vocal Production and Motor Control in Human Heschl's Gyrus.

The present study investigated how pitch frequency, a perceptually relevant aspect of periodicity in natural human vocalizations, is encoded in Heschl's gyrus (HG), and how this information may be used to influence vocal pitch motor control. We recorded local field potentials from multicontact depth electrodes implanted in HG of 14 neurosurgical epilepsy patients as they vocalized vowel sounds and received brief (200 ms) pitch perturbations at 100 Cents in their auditory feedback. Event-related band power responses to vocalizations showed sustained frequency following responses that tracked voice fundamental frequency (F0) and were significantly enhanced in posteromedial HG during speaking compared with when subjects listened to the playback of their own voice. In addition to frequency following responses, a transient response component within the high gamma frequency band (75-150 Hz) was identified. When this response followed the onset of vocalization, the magnitude of the response was the same for the speaking and playback conditions. In contrast, when this response followed a pitch shift, its magnitude was significantly enhanced during speaking compared with playback. We also observed that, in anterolateral HG, the power of high gamma responses to pitch shifts correlated with the magnitude of compensatory vocal responses. These findings demonstrate a functional parcellation of HG with neural activity that encodes pitch in natural human voice, distinguishes between self-generated and passively heard vocalizations, detects discrepancies between the intended and heard vocalization, and contains information about the resulting behavioral vocal compensations in response to auditory feedback pitch perturbations. SIGNIFICANCE STATEMENT: The present study is a significant contribution to our understanding of sensor-motor mechanisms of vocal production and motor control. The findings demonstrate distinct functional parcellation of core and noncore areas within human auditory cortex on Heschl's gyrus that process natural human vocalizations and pitch perturbations in the auditory feedback. In addition, our data provide evidence for distinct roles of high gamma neural oscillations and frequency following responses for processing periodicity in human vocalizations during vocal production and motor control.

Electrocorticographic delineation of human auditory cortical fields based on effects of propofol anesthesia.

The functional organization of human auditory cortex remains incompletely characterized. While the posteromedial two thirds of Heschl's gyrus (HG) is generally considered to be part of core auditory cortex, additional subdivisions of HG remain speculative. To further delineate the hierarchical organization of human auditory cortex, we investigated regional heterogeneity in the modulation of auditory cortical responses under varying depths of anesthesia induced by propofol. Non-invasive studies have shown that propofol differentially affects auditory cortical activity, with a greater impact on non-core areas. Subjects were neurosurgical patients undergoing removal of intracranial electrodes placed to identify epileptic foci. Stimuli were 50Hz click trains, presented continuously during an awake baseline period, and subsequently, while propofol infusion was incrementally titrated to induce general anesthesia. Electrocorticographic recordings were made with depth electrodes implanted in HG and subdural grid electrodes implanted over superior temporal gyrus (STG). Depth of anesthesia was monitored using spectral entropy. Averaged evoked potentials (AEPs), frequency-following responses (FFRs) and high gamma (70-150Hz) event-related band power were used to characterize auditory cortical activity. Based on the changes in AEPs and FFRs during the induction of anesthesia, posteromedial HG could be divided into two subdivisions. In the most posteromedial aspect of the gyrus, the earliest AEP deflections were preserved and FFRs increased during induction. In contrast, the remainder of the posteromedial HG exhibited attenuation of both the AEP and the FFR. The anterolateral HG exhibited weaker activation characterized by broad, low-voltage AEPs and the absence of FFRs. Lateral STG exhibited limited activation by click trains, and FFRs there diminished during induction. Sustained high gamma activity was attenuated in the most posteromedial portion of HG, and was absent in all other regions. These differential patterns of auditory cortical activity during the induction of anesthesia may serve as useful physiological markers for field delineation. In this study, the posteromedial HG could be parcellated into at least two subdivisions. Preservation of the earliest AEP deflections and FFRs in the posteromedial HG likely reflects the persistence of feedforward synaptic activity generated by inputs from subcortical auditory pathways, including the medial geniculate nucleus.

Direct physiologic evidence of a heteromodal convergence region for proper naming in human left anterior temporal lobe.

Retrieving the names of friends, loved ones, and famous people is a fundamental human ability. This ability depends on the left anterior temporal lobe (ATL), where lesions can be associated with impaired naming of people regardless of modality (e.g., picture or voice). This finding has led to the idea that the left ATL is a modality-independent convergence region for proper naming. Hypotheses for how proper-name dispositions are organized within the left ATL include both a single modality-independent (heteromodal) convergence region and spatially discrete modality-dependent (unimodal) regions. Here we show direct electrophysiologic evidence that the left ATL is heteromodal for proper-name retrieval. Using intracranial recordings placed directly on the surface of the left ATL in human subjects, we demonstrate nearly identical responses to picture and voice stimuli of famous U.S. politicians during a naming task. Our results demonstrate convergent and robust large-scale neurophysiologic responses to picture and voice naming in the human left ATL. This finding supports the idea of heteromodal (i.e., transmodal) dispositions for proper naming in the left ATL.

Beta modulation reflects name retrieval in the human anterior temporal lobe: an intracranial recording study.

Naming people, places, and things is a fundamental human ability that is often impaired in patients with language-dominant anterior temporal lobe (ATL) dysfunction or ATL resection as part of epilepsy treatment. Convergent lines of evidence point to the importance of the ATL in name retrieval. The physiologic mechanisms that mediate name retrieval in the ATL, however, are not well understood. The purpose of this study was to characterize the electrophysiologic responses of the human ATL during overt cued naming of famous people and objects. Eight neurosurgical patients with suspected temporal lobe epilepsy who underwent implantation of intracranial electrodes for seizure focus localization were the subjects of this study. Specialized coverage of the ATL was achieved in each subject. The subjects named pictures of U.S. presidents and images of common hand-held tools. Event-related band power was measured for each ATL recording site. Both the left and right ATL demonstrated robust and focal increases in beta-band (14-30 Hz) power during person and tool naming. The onset of this response typically occurred at 400 ms but sometimes as early as 200 ms. Visual naming of famous people and tools is associated with robust and localized modulation of the beta band in both the left and right ATL. Measurement of visual naming responses may provide the groundwork for future mapping modalities to localize eloquent cortex in the ATL.