Sound identification in human auditory cortex: Differential contribution of local field potentials and high gamma power as revealed by direct intracranial recordings

Individual variability in functional connectivity of human auditory cortex

Individual variability in functional connectivity underlies individual differences in cognition and behaviors, yet its association with functional specialization in the auditory cortex remains elusive. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, this study was designed to investigate the spatial distribution of auditory cortex individual variability in its whole-brain functional network architecture. An inherent hierarchical axis of the variability was discerned, which radiates from the medial to lateral orientation, with the left auditory cortex demonstrating more pronounced variations than the right. This variability exhibited a significant correlation with the variations in structural and functional metrics in the auditory cortex. Four auditory cortex subregions, which were identified from a clustering analysis based on this variability, exhibited unique connectional fingerprints and cognitive maps, with certain subregions showing specificity to speech perception functional activation. Moreover, the lateralization of the connectional fingerprint exhibited a U-shaped trajectory across the subregions. These findings emphasize the role of individual variability in functional connectivity in understanding cortical functional organization, as well as in revealing its association with functional specialization from the activation, connectome, and cognition perspectives.

Does Electrophysiological Maturation Shape Language Acquisition?

Infants master temporal patterns of their native language at a developmental trajectory from slow to fast: Shortly after birth, they recognize the slow acoustic modulations specific to their native language before tuning into faster language-specific patterns between 6 and 12 months of age. We propose here that this trajectory is constrained by neuronal maturation-in particular, the gradual emergence of high-frequency neural oscillations in the infant electroencephalogram. Infants' initial focus on slow prosodic modulations is consistent with the prenatal availability of slow electrophysiological activity (i.e., theta- and delta-band oscillations). Our proposal is consistent with the temporal patterns of infant-directed speech, which initially amplifies slow modulations, approaching the faster modulation range of adult-directed speech only as infants' language has advanced sufficiently. Moreover, our proposal agrees with evidence from premature infants showing maturational age is a stronger predictor of language development than ex utero exposure to speech, indicating that premature infants cannot exploit their earlier availability of speech because of electrophysiological constraints. In sum, we provide a new perspective on language acquisition emphasizing neuronal development as a critical driving force of infants' language development.

Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models

Objective.Development of brain-computer interface (BCI) technology is key for enabling communication in individuals who have lost the faculty of speech due to severe motor paralysis. A BCI control strategy that is gaining attention employs speech decoding from neural data. Recent studies have shown that a combination of direct neural recordings and advanced computational models can provide promising results. Understanding which decoding strategies deliver best and directly applicable results is crucial for advancing the field.Approach.In this paper, we optimized and validated a decoding approach based on speech reconstruction directly from high-density electrocorticography recordings from sensorimotor cortex during a speech production task.Main results.We show that (1) dedicated machine learning optimization of reconstruction models is key for achieving the best reconstruction performance; (2) individual word decoding in reconstructed speech achieves 92%-100% accuracy (chance level is 8%); (3) direct reconstruction from sensorimotor brain activity produces intelligible speech.Significance.These results underline the need for model optimization in achieving best speech decoding results and highlight the potential that reconstruction-based speech decoding from sensorimotor cortex can offer for development of next-generation BCI technology for communication.

Decoding the temporal dynamics of spoken word and nonword processing from EEG

The efficiency of spoken word recognition is essential for real-time communication. There is consensus that this efficiency relies on an implicit process of activating multiple word candidates that compete for recognition as the acoustic signal unfolds in real-time. However, few methods capture the neural basis of this dynamic competition on a msec-by-msec basis. This is crucial for understanding the neuroscience of language, and for understanding hearing, language and cognitive disorders in people for whom current behavioral methods are not suitable. We applied machine-learning techniques to standard EEG signals to decode which word was heard on each trial and analyzed the patterns of confusion over time. Results mirrored psycholinguistic findings: Early on, the decoder was equally likely to report the target (e.g., baggage) or a similar sounding competitor (badger), but by around 500 msec, competitors were suppressed. Follow up analyses show that this is robust across EEG systems (gel and saline), with fewer channels, and with fewer trials. Results are robust within individuals and show high reliability. This suggests a powerful and simple paradigm that can assess the neural dynamics of speech decoding, with potential applications for understanding lexical development in a variety of clinical disorders.

Inter-individual variability in dorsal stream dynamics during word production

The current standard model of language production involves a sensorimotor dorsal stream connecting areas in the temporo-parietal junction with those in the inferior frontal gyrus and lateral premotor cortex. These regions have been linked to various aspects of word production such as phonological processing or articulatory programming, primarily through neuropsychological and functional imaging group studies. Most if not all the theoretical descriptions of this model imply that the same network should be identifiable across individual speakers. We tested this hypothesis by quantifying the variability of activation observed across individuals within each dorsal stream anatomical region. This estimate was based on electrical activity recorded directly from the cerebral cortex with millisecond accuracy in awake epileptic patients clinically implanted with intracerebral depth electrodes for pre-surgical diagnosis. Each region's activity was quantified using two different metrics-intra-cerebral evoked related potentials and high gamma activity-at the level of the group, the individual and the recording contact. The two metrics show simultaneous activation of parietal and frontal regions during a picture naming task, in line with models that posit interactive processing during word retrieval. They also reveal different levels of between-patient variability across brain regions, except in core auditory and motor regions. The independence and non-uniformity of cortical activity estimated through the two metrics push the current model towards sub-second and sub-region explorations focused on individualized language speech production. Several hypotheses are considered for this within-region heterogeneity.

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.

Evaluating the Use of Cortical Entrainment to Measure Atypical Speech Processing: A Systematic Review

BACKGROUND

Cortical entrainment has emerged as promising means for measuring continuous speech processing in young, neurotypical adults. However, its utility for capturing atypical speech processing has not been systematically reviewed.

OBJECTIVES

Synthesize evidence regarding the merit of measuring cortical entrainment to capture atypical speech processing and recommend avenues for future research.

METHOD

We systematically reviewed publications investigating entrainment to continuous speech in populations with auditory processing differences.

RESULTS

In the 25 publications reviewed, most studies were conducted on older and/or hearing-impaired adults, for whom slow-wave entrainment to speech was often heightened compared to controls. Research conducted on populations with neurodevelopmental disorders, in whom slow-wave entrainment was often reduced, was less common. Across publications, findings highlighted associations between cortical entrainment and speech processing performance differences.

CONCLUSIONS

Measures of cortical entrainment offer useful means of capturing speech processing differences and future research should leverage them more extensively when studying populations with neurodevelopmental disorders.

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.

Transformation of a temporal speech cue to a spatial neural code in human auditory cortex

In speech, listeners extract continuously-varying spectrotemporal cues from the acoustic signal to perceive discrete phonetic categories. Spectral cues are spatially encoded in the amplitude of responses in phonetically-tuned neural populations in auditory cortex. It remains unknown whether similar neurophysiological mechanisms encode temporal cues like voice-onset time (VOT), which distinguishes sounds like /b/ and/p/. We used direct brain recordings in humans to investigate the neural encoding of temporal speech cues with a VOT continuum from /ba/ to /pa/. We found that distinct neural populations respond preferentially to VOTs from one phonetic category, and are also sensitive to sub-phonetic VOT differences within a population's preferred category. In a simple neural network model, simulated populations tuned to detect either temporal gaps or coincidences between spectral cues captured encoding patterns observed in real neural data. These results demonstrate that a spatial/amplitude neural code underlies the cortical representation of both spectral and temporal speech cues.

The time-course of speech perception revealed by temporally-sensitive neural measures

Recent advances in cognitive neuroscience have provided a detailed picture of the early time-course of speech perception. In this review, we highlight this work, placing it within the broader context of research on the neurobiology of speech processing, and discuss how these data point us toward new models of speech perception and spoken language comprehension. We focus, in particular, on temporally-sensitive measures that allow us to directly measure early perceptual processes. Overall, the data provide support for two key principles: (a) speech perception is based on gradient representations of speech sounds and (b) speech perception is interactive and receives input from higher-level linguistic context at the earliest stages of cortical processing. Implications for models of speech processing and the neurobiology of language more broadly are discussed. This article is categorized under: Psychology > Language Psychology > Perception and Psychophysics Neuroscience > Cognition.

Converging intracortical signatures of two separated processing timescales in human early auditory cortex

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fingerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal microarchitecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.

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.

Visual epidural field potentials possess high functional specificity in single trials

Recordings of epidural field potentials (EFPs) allow neuronal activity to be acquired over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations and possess a higher trial-by-trial variability and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short timescales relevant for many clinical and basic neuroscience purposes. We used the high spatial resolution of primary visual cortex to address these issues and investigated the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one of nine closely adjacent locations and recorded neuronal activity with a high-density epidural multielectrode array in three macaque monkeys. With the use of receiver operating characteristics (ROC) to identify the most informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.NEW & NOTEWORTHY Epidural field potential (EFP) recordings provide a minimally invasive approach to investigate large-scale neural networks, but little is known about whether they possess the required specificity for basic and clinical neuroscience. By making use of the spatial selectivity of primary visual cortex, we show that single-trial information can be decoded with close-to-perfect performance, even without using advanced classifiers and based on very few data. This labels EFPs as a highly attractive and widely usable signal.

Speaker-normalized sound representations in the human auditory cortex

The acoustic dimensions that distinguish speech sounds (like the vowel differences in "boot" and "boat") also differentiate speakers' voices. Therefore, listeners must normalize across speakers without losing linguistic information. Past behavioral work suggests an important role for auditory contrast enhancement in normalization: preceding context affects listeners' perception of subsequent speech sounds. Here, using intracranial electrocorticography in humans, we investigate whether and how such context effects arise in auditory cortex. Participants identified speech sounds that were preceded by phrases from two different speakers whose voices differed along the same acoustic dimension as target words (the lowest resonance of the vocal tract). In every participant, target vowels evoke a speaker-dependent neural response that is consistent with the listener's perception, and which follows from a contrast enhancement model. Auditory cortex processing thus displays a critical feature of normalization, allowing listeners to extract meaningful content from the voices of diverse speakers.

Gamma-Band Oscillations Preferential for Nociception can be Recorded in the Human Insula

Transient nociceptive stimuli elicit robust phase-locked local field potentials (LFPs) in the human insula. However, these responses are not preferential for nociception, as they are also elicited by transient non-nociceptive vibrotactile, auditory, and visual stimuli. Here, we investigated whether another feature of insular activity, namely gamma-band oscillations (GBOs), is preferentially observed in response to nociceptive stimuli. Although nociception-evoked GBOs have never been explored in the insula, previous scalp electroencephalography and magnetoencephalography studies suggest that nociceptive stimuli elicit GBOs in other areas such as the primary somatosensory and prefrontal cortices, and that this activity could be closely related to pain perception. Furthermore, tracing studies showed that the insula is a primary target of spinothalamic input. Using depth electrodes implanted in 9 patients investigated for epilepsy, we acquired insular responses to brief thermonociceptive stimuli and similarly arousing non-nociceptive vibrotactile, auditory, and visual stimuli (59 insular sites). As compared with non-nociceptive stimuli, nociceptive stimuli elicited a markedly stronger enhancement of GBOs (150-300 ms poststimulus) at all insular sites, suggesting that this feature of insular activity is preferential for thermonociception. Although this activity was also present in temporal and frontal regions, its magnitude was significantly greater in the insula as compared with these other regions.

The time-course of cortical responses to speech revealed by fast optical imaging

Recent work has sought to describe the time-course of spoken word recognition, from initial acoustic cue encoding through lexical activation, and identify cortical areas involved in each stage of analysis. However, existing methods are limited in either temporal or spatial resolution, and as a result, have only provided partial answers to the question of how listeners encode acoustic information in speech. We present data from an experiment using a novel neuroimaging method, fast optical imaging, to directly assess the time-course of speech perception, providing non-invasive measurement of speech sound representations, localized to specific cortical areas. We find that listeners encode speech in terms of continuous acoustic cues at early stages of processing (ca. 96 ms post-stimulus onset), and begin activating phonological category representations rapidly (ca. 144 ms post-stimulus). Moreover, cue-based representations are widespread in the brain and overlap in time with graded category-based representations, suggesting that spoken word recognition involves simultaneous activation of both continuous acoustic cues and phonological categories.

The neural oscillations of speech processing and language comprehension: state of the art and emerging mechanisms

Neural oscillations subserve a broad range of functions in speech processing and language comprehension. On the one hand, speech contains-somewhat-repetitive trains of air pressure bursts that occur at three dominant amplitude modulation frequencies, physically marking the linguistically meaningful progressions of phonemes, syllables and intonational phrase boundaries. To these acoustic events, neural oscillations of isomorphous operating frequencies are thought to synchronise, presumably resulting in an implicit temporal alignment of periods of neural excitability to linguistically meaningful spectral information on the three low-level linguistic description levels. On the other hand, speech is a carrier signal that codes for high-level linguistic meaning, such as syntactic structure and semantic information-which cannot be read from stimulus acoustics, but must be acquired during language acquisition and decoded for language comprehension. Neural oscillations subserve the processing of both syntactic structure and semantic information. Here, I synthesise a mapping from each linguistic processing domain to a unique set of subserving oscillatory mechanisms-the mapping is plausible given the role ascribed to different oscillatory mechanisms in different subfunctions of cortical information processing and faithful to the underlying electrophysiology. In sum, the present article provides an accessible and extensive review of the functional mechanisms that neural oscillations subserve in speech processing and language comprehension.

Auditory processing in the human cortex: An intracranial electrophysiology perspective

Objective

Direct electrophysiological recordings in epilepsy patients offer an opportunity to study human auditory cortical processing with unprecedented spatiotemporal resolution. This review highlights recent intracranial studies of human auditory cortex and focuses on its basic response properties as well as modulation of cortical activity during the performance of active behavioral tasks.

Data Sources: Literature review.

Review Methods: A review of the literature was conducted to summarize the functional organization of human auditory and auditory‐related cortex as revealed using intracranial recordings.

Results

The tonotopically organized core auditory cortex within the posteromedial portion of Heschl's gyrus represents spectrotemporal features of sounds with high temporal precision and short response latencies. At this level of processing, high gamma (70–150 Hz) activity is minimally modulated by task demands. Non‐core cortex on the lateral surface of the superior temporal gyrus also maintains representation of stimulus acoustic features and, for speech, subserves transformation of acoustic inputs into phonemic representations. High gamma responses in this region are modulated by task requirements. Prefrontal cortex exhibits complex response patterns, related to stimulus intelligibility and task relevance. At this level of auditory processing, activity is strongly modulated by task requirements and reflects behavioral performance.

Conclusions

Direct recordings from the human brain reveal hierarchical organization of sound processing within auditory and auditory‐related cortex.

Level of Evidence

Level V

Intracerebral evidence of rhythm transform in the human auditory cortex

Musical entrainment is shared by all human cultures and the perception of a periodic beat is a cornerstone of this entrainment behavior. Here, we investigated whether beat perception might have its roots in the earliest stages of auditory cortical processing. Local field potentials were recorded from 8 patients implanted with depth-electrodes in Heschl's gyrus and the planum temporale (55 recording sites in total), usually considered as human primary and secondary auditory cortices. Using a frequency-tagging approach, we show that both low-frequency (<30 Hz) and high-frequency (>30 Hz) neural activities in these structures faithfully track auditory rhythms through frequency-locking to the rhythm envelope. A selective gain in amplitude of the response frequency-locked to the beat frequency was observed for the low-frequency activities but not for the high-frequency activities, and was sharper in the planum temporale, especially for the more challenging syncopated rhythm. Hence, this gain process is not systematic in all activities produced in these areas and depends on the complexity of the rhythmic input. Moreover, this gain was disrupted when the rhythm was presented at fast speed, revealing low-pass response properties which could account for the propensity to perceive a beat only within the musical tempo range. Together, these observations show that, even though part of these neural transforms of rhythms could already take place in subcortical auditory processes, the earliest auditory cortical processes shape the neural representation of rhythmic inputs in favor of the emergence of a periodic beat.

Phonetic detail and lateralization of reading-related inner speech and of auditory and somatosensory feedback processing during overt reading

Phonetic detail and lateralization of inner speech during covert sentence reading as well as overt reading in 32 right-handed healthy participants undergoing 3T fMRI were investigated. The number of voiceless and voiced consonants in the processed sentences was systematically varied. Participants listened to sentences, read them covertly, silently mouthed them while reading, and read them overtly. Condition comparisons allowed for the study of effects of externally versus self-generated auditory input and of somatosensory feedback related to or independent of voicing. In every condition, increased voicing modulated bilateral voice-selective regions in the superior temporal sulcus without any lateralization. The enhanced temporal modulation and/or higher spectral frequencies of sentences rich in voiceless consonants induced left-lateralized activation of phonological regions in the posterior temporal lobe, regardless of condition. These results provide evidence that inner speech during reading codes detail as fine as consonant voicing. Our findings suggest that the fronto-temporal internal loops underlying inner speech target different temporal regions. These regions differ in their sensitivity to inner or overt acoustic speech features. More slowly varying acoustic parameters are represented more anteriorly and bilaterally in the temporal lobe while quickly changing acoustic features are processed in more posterior left temporal cortices. Furthermore, processing of external auditory feedback during overt sentence reading was sensitive to consonant voicing only in the left superior temporal cortex. Voicing did not modulate left-lateralized processing of somatosensory feedback during articulation or bilateral motor processing. This suggests voicing is primarily monitored in the auditory rather than in the somatosensory feedback channel. Hum Brain Mapp 38:493-508, 2017. © 2016 Wiley Periodicals, Inc.

Electrocorticographic Activation within Human Auditory Cortex during Dialog-Based Language and Cognitive Testing

Current models of cortical speech and language processing include multiple regions within the temporal lobe of both hemispheres. Human communication, by necessity, involves complex interactions between regions subserving speech and language processing with those involved in more general cognitive functions. To assess these interactions, we utilized an ecologically salient conversation-based approach. This approach mandates that we first clarify activity patterns at the earliest stages of cortical speech processing. Therefore, we examined high gamma (70–150 Hz) responses within the electrocorticogram (ECoG) recorded simultaneously from Heschl’s gyrus (HG) and lateral surface of the superior temporal gyrus (STG). Subjects were neurosurgical patients undergoing evaluation for treatment of medically intractable epilepsy. They performed an expanded version of the Mini-mental state examination (MMSE), which included additional spelling, naming, and memory-based tasks. ECoG was recorded from HG and the STG using multicontact depth and subdural electrode arrays, respectively. Differences in high gamma activity during listening to the interviewer and the subject’s self-generated verbal responses were quantified for each recording site and across sites within HG and STG. The expanded MMSE produced widespread activation in auditory cortex of both hemispheres. No significant difference was found between activity during listening to the interviewer’s questions and the subject’s answers in posteromedial HG (auditory core cortex). A different pattern was observed throughout anterolateral HG and posterior and middle portions of lateral STG (non-core auditory cortical areas), where activity was significantly greater during listening compared to speaking. No systematic task-specific differences in the degree of suppression during speaking relative to listening were found in posterior and middle STG. Individual sites could, however, exhibit task-related variability in the degree of suppression during speaking compared to listening. The current study demonstrates that ECoG recordings can be acquired in time-efficient dialog-based paradigms, permitting examination of language and cognition in an ecologically salient manner. The results obtained from auditory cortex serve as a foundation for future studies addressing patterns of activity beyond auditory cortex that subserve human communication.

Can you hear me yet? An intracranial investigation of speech and non-speech audiovisual interactions in human cortex

In everyday conversation, viewing a talker's face can provide information about the timing and content of an upcoming speech signal, resulting in improved intelligibility. Using electrocorticography, we tested whether human auditory cortex in Heschl's gyrus (HG) and on superior temporal gyrus (STG) and motor cortex on precentral gyrus (PreC) were responsive to visual/gestural information prior to the onset of sound and whether early stages of auditory processing were sensitive to the visual content (speech syllable versus non-speech motion). Event-related band power (ERBP) in the high gamma band was content-specific prior to acoustic onset on STG and PreC, and ERBP in the beta band differed in all three areas. Following sound onset, we found with no evidence for content-specificity in HG, evidence for visual specificity in PreC, and specificity for both modalities in STG. These results support models of audio-visual processing in which sensory information is integrated in non-primary cortical areas.

Re-visiting the electrophysiology of language

This editorial accompanies a special issue of Brain and Language re-visiting old themes and new leads in the electrophysiology of language. The event-related potential (ERP) as a series of characteristic deflections ("components") over time and their distribution on the scalp has been exploited by speech and language researchers over decades to find support for diverse psycholinguistic models. Fortunately, methodological and statistical advances have allowed human neuroscience to move beyond some of the limitations imposed when looking at the ERP only. Most importantly, we currently witness a refined and refreshed look at "event-related" (in the literal sense) brain activity that relates itself more closely to the actual neurobiology of speech and language processes. It is this imminent change in handling and interpreting electrophysiological data of speech and language experiments that this special issue intends to capture.