Human Cortex Research Articles

Morphology of Cortical Microglia in the Hyperacute Phase of Subarachnoid Hemorrhage

Hemorrhagic stroke is the deadliest type of stroke. Cellular and molecular biomarkers are important for understanding the pathophysiology of stroke. Microglia are among the most promising biological markers. However, the morphological and physiological characteristics of microglia, as well as the structural and functional aspects of their interactions with neurons and other cells, are largely unknown. Due to the large number of different morphological phenotypes and very limited information on microglial changes in subarachnoid hemorrhage (SAH), we performed this study aimed at identifying the features of the distribution of various microglial phenotypes in the layers of the cerebral cortex in the hyperacute phase of non-traumatic SAH. We studied the distribution of various microglial phenotypes in the layers of the cerebral cortex of SAH non-survivors with a control group (coronary heart disease and sudden cardiac death were the underlying causes of death). An immunohistochemical study using antibodies to iba-1 (a marker of microglia) revealed changes in the morphological phenotypes of microglia in the cerebral cortex after subarachnoid hemorrhage. Significant differences between the groups indicate a rapid microglial response to injury. The findings indicate that there are quantitative and phenotypic changes in microglia in the cerebral cortex during early SAH in the human cortex.

TMET-19. REWIRING OF CORTICAL GLUCOSE METABOLISM FUELS HUMAN BRAIN CANCER GROWTH

Abstract The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), lose aspects of normal biology and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to fuel these processes is poorly understood. Here we perform infusions of 13C-labeled glucose into patients and mice with brain cancer to define the metabolic fates of glucose-derived carbon in tumor and cortex. By combining these measurements with quantitative metabolic flux analysis, we find that human cortex funnels glucose-derived carbons towards physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. In contrast, brain cancers downregulate these physiologic processes, scavenge alternative carbon sources from the environment, and instead use glucose-derived carbons to produce molecules needed for proliferation and invasion. In particular, we find that cortical tissue produces its own glucose-derived serine, whereas gliomas predominantly consume serine from the environment. Targeting this metabolic rewiring in mice through dietary modulation selectively alters GBM metabolism and slows tumor growth. Combining dietary serine restriction with chemoradiation reduces brain tumor growth in mice, suggesting that such a dietary intervention could improve outcomes for patients with high grade glioma.

CNSC-22. GLIOBLASTOMA CELLS EXHIBIT NEURON-LIKE EXCITABILITY IN BOTH ACUTE AND ORGANOTYPIC HUMAN BRAIN SLICES

Abstract Glioblastomas (GBM) are known for their significant intratumor heterogeneity, featuring a variety of plastic cell types that make effective treatment challenging. Recent studies have shown that neuronal-progenitor-like transcriptomic cell states at the leading edge of the tumor receive synaptic input from nearby neurons, which drives disease proliferation. However, the excitability of GBM cells remains controversial, with observations ranging from non-excitable to neuron-like excitability, complicating our understanding of their pathophysiology. In this study, we developed a novel experimental approach to study glioblastoma cells in both acute and cultured brain slices infiltrated with cancer from GBM patients. Using an adeno-associated virus for gene delivery, we selectively expressed fluorescent proteins in specific cell types. Fluorescence-guided whole-cell patch-clamp recordings were then used to analyze the electrophysiological properties of GBM cells and neurons within the tumor microenvironment. Our findings show that GBM cells have distinct electrophysiological properties, including a depolarized resting membrane potential (-31.95 ± 2.18 mV, n = 55 cells) and high membrane resistance (1.27 ± 0.19 GΩ, n = 62 cells). Approximately 56% of GBM cells at the tumor’s leading edge exhibited neuron-like excitability, generating aberrant action potentials (aAPs) upon depolarization. Collectively, our study provides direct evidence of the intrinsic excitability of GBM cells and a detailed characterization of their electrophysiological properties in the cancer-infiltrated human cortex. These insights shed new light on tumor heterogeneity and cell-cell interactions in glioblastoma, potentially guiding the development of targeted therapies.

An eccentricity gradient reversal across high-level visual cortex.

Human visual cortex contains regions selectively involved in perceiving and recognizing ecologically important visual stimuli such as people and places. Located in the ventral temporal lobe, these regions are organized consistently relative to cortical folding, a phenomenon thought to be inherited from how centrally or peripherally these stimuli are viewed with the retina. While this eccentricity theory of visual cortex has been one of the best descriptions of its functional organization, whether or not it accurately describes visual processing in all category-selective regions is not yet clear. Through a combination of behavioral and functional MRI measurements in 27 participants (17 females), we demonstrate that a limb-selective region neighboring well-studied face-selective regions shows tuning for the visual periphery in a cortical region originally thought to be centrally-biased. We demonstrate that the spatial computations performed by the limb-selective region are consistent with visual experience, and in doing so, make the novel observation that there may in fact be two eccentricity gradients, forming an eccentricity reversal across high-level visual cortex. These data expand the current theory of cortical organization to provide a unifying principle that explains the broad functional features of many visual regions, showing that viewing experience interacts with innate wiring principles to drive the location of cortical specialization.Significance Statement What is the organizing principle of high-level visual cortex? Visual stimuli experienced extensively during childhood, like faces or scenes, give rise to specialized regions in visual cortex. These regions emerge in consistent locations across individuals, thought to result from the retinotopic input of earlier visual cortex. The field has quantified this input as a medial-lateral gradient of retinotopic eccentricity in ventrotemporal cortex that has not yet been mapped beyond the fusiform gyrus. By performing receptive field mapping in limb-selective cortex for the first time we uncover a u-shaped eccentricity gradient which reverses near the lateral Fusiform. These findings produce a parsimonious model of cortical organization incorporating previously uncharacterized regions, offering a new organizing principle of high-level vision.

Fluoxetine does not influence response to continuous theta burst stimulation in human motor cortex.

Selective serotonin reuptake inhibitors are thought to exert a clinical effect through various mechanisms, including through alteration in synaptic plasticity. Repetitive transcranial magnetic stimulation can induce temporary changes in synaptic excitability in cerebral cortex that resemble long-term potentiation and long-term depression that serve as a measure of synaptic plasticity invivo. A version of repetitive transcranial magnetic stimulation called continuous theta burst stimulation can induce inhibition of cortical excitability that can be measured through a motor evoked potential. Previous work has suggested that this response can be modulated by administration of selective serotonin reuptake inhibitors. Thirty-one healthy volunteers received both fluoxetine 20 mg and placebo in randomly ordered sessions, followed by spaced continuous theta burst stimulation to motor cortex. Changes in Motor Evoked Potentials were then recorded over 60 min. The response to spaced continuous theta burst stimulation did not differ significantly between fluoxetine and placebo sessions. Spaced continuous theta burst stimulation produced a paradoxical excitatory response in an unexpected number of participants. A single dose of fluoxetine 20 mg does not influence the response to continuous theta burst stimulation. Previous results suggesting an effect of selective serotonin reuptake inhibitors on inhibitory non-invasive brain stimulation protocols may be due to insufficiently large sample sizes.

Molecular Lineages and Spatial Distributions of Subplate Neurons in the Human Fetal Cerebral Cortex.

The expansion of neural progenitors and production of distinct neurons are crucial for architectural assembly and formation of connectivity in human brains. Subplate neurons (SPNs) are among the firstborn neurons in the human fetal cerebral cortex, and play a critical role in establishing intra- and extracortical connections. However, little is known about SPN origin and developmental lineages. In this study, spatial landscapes and molecular trajectories of SPNs in the human fetal cortices from gestational weeks (GW) 10 to 25 are created by performing spatial transcriptomics and single-cell RNA sequencing. Genes known to be evolutionarily human-specific and genes associated with extracellular matrices (ECMs) are found to maintain stable proportions of subplate neurons among other neuronal types. Enriched ECM gene expression in SPNs varies in distinct cortical regions, with the highest level in the frontal lobe of human fetal brains. This study reveals molecular origin and lineage specification of subplate neurons in the human fetal cerebral cortices, and highlights underpinnings of SPNs to cortical neurogenesis and early structural folding.

Stimulus-induced rotary saturation imaging of visually evoked response: A pilot study.

Spin-lock (SL) pulses have been proposed to directly detect neuronal activity otherwise inaccessible through standard functional magnetic resonance imaging. However, the practical limits of this technique remain unexplored. Key challenges in SL-based detection include ultra-weak signal variations, sensitivity to magnetic field inhomogeneities, and potential contamination from blood oxygen level-dependent effects, all of which hinder the reliable isolation of neuronal signals. This pilot study evaluates the performance of the stimulus-induced rotary saturation (SIRS) technique to map visual stimulation response in the human cortex. A rotary echo spin-lock (RESL) preparation followed by a 2D echo planar imaging readout was used to investigate 12 healthy subjects at rest and during continuous exposure to 8Hz flickering light. The SL amplitude was fixed to the target neuroelectric oscillations at that frequency. The signal variance was used as contrast metric, and two alternative post-processing pipelines (regression-filtering-rectification and normalized subtraction) were statistically evaluated. Higher variance in the SL signal was detected in four of the 12 subjects. Although group-level analysis indicated activation in the occipital pole, analysis of variance revealed that this difference was not statistically significant, highlighting the need for comparable control measures and more robust preparations. Further optimization in sensitivity and robustness is required to noninvasively detect physiological neuroelectric activity in the human brain.

Color and Spatial Frequency Provide Functional Signatures of Retinotopic Visual Areas.

Primate vision relies on retinotopically organized cortical parcels defined by representations of hemifield (upper versus lower visual field), eccentricity (fovea versus periphery), and area (V1, V2, V3, V4). Here we test for functional signatures of these organizing principles. We used fMRI to measure responses to gratings varying in spatial frequency, color, and saturation across retinotopically defined parcels in two macaque monkeys, and we developed a Sparse Supervised Embedding (SSE) analysis to identify stimulus features that best distinguish cortical parcels from each other. Constraining the SSE model to distinguish just eccentricity representations of the voxels revealed the expected variation of spatial frequency and S-cone modulation with eccentricity. Constraining the model according to the dorsal-ventral location and retinotopic area of each voxel provided unexpected functional signatures, which we investigated further with standard univariate analyses. Posterior parcels (V1) were distinguished from anterior parcels (V4) by differential responses to chromatic and luminance contrast, especially of low spatial frequency gratings. Meanwhile, ventral parcels were distinguished from dorsal parcels by differential responses to chromatic and luminance contrast, especially of colors that modulate all three cone types. The dorsal-ventral asymmetry not only resembled differences between candidate dorsal and ventral subdivisions of human V4, but also extended to include all retinotopic visual areas, starting in V1 and increasing from V1 to V4. The results provide insight into the functional roles of different retinotopic areas and demonstrate the utility of Sparse Supervised Embedding as a data-driven tool for generating hypotheses about cortical function and behavior.Significance Statement This study demonstrates a new analysis, Sparse Supervised Embedding (SSE), which promises to be useful for visualizing and understanding complex neuroimaging datasets. The paper uses SSE to explore the functional roles of retinotopic visual areas (V1, V2, V3, V4, V3a, MT). The results show that retinotopic areas parcellated by representations for eccentricity and upper/lower visual hemifield have functional signatures, which are defined by unique combinations of responses to color, spatial frequency, and contrast. The functional signatures provide hypotheses for the different roles that the parcels play in vision and help resolve apparent differences between human and macaque visual cortex organization.

Altered immune response is associated with sex difference in vulnerability to Alzheimer's disease in human prefrontal cortex.

Alzheimer's disease (AD) is a neurodegenerative disorder with a higher risk incidence in females than in males, and there are also differences in AD pathophysiology between sexes. The role of sex in the pathogenesis of AD may be crucial, yet the cellular and molecular basis remains unclear. Here, we performed a comprehensive analysis using four public transcriptome datasets of AD patients and age-matched control individuals in prefrontal cortex, including bulk transcriptome (295 females and 402 males) and single-nucleus RNA sequencing (snRNA-seq) data (224 females and 219 males). We found that the transcriptomic profile in female control was similar to those in AD. To characterize the key features associated with both the pathogenesis of AD and sex difference, we identified a co-expressed gene module that positively correlated with AD, sex, and aging, and was also enriched with immune-associated pathways. Using snRNA-seq datasets, we found that microglia (MG), a resident immune cell in the brain, demonstrated substantial differences in several aspects between sexes, such as an elevated proportion of activated MG, altered transcriptomic profile and cell-cell interaction between MG and other brain cell types in female control. Additionally, genes upregulated in female MG, such as TLR2, MERTK, SPP1, SLA, ACSL1, and FKBP5, had high confidence to be identified as biomarkers to distinguish AD status, and these genes also interacted with some approved drugs for treatment of AD. These findings underscore the altered immune response in female is associated with sex difference in susceptibility to AD, and the necessity of considering sex factors when developing AD biomarkers and therapeutic strategies, providing a scientific basis for further in-depth studies on sex differences in AD.

Melody transposition tolerance in the human cortex: An fMRI adaptation and MVPA investigation

Abstract Melody perception involves constant relational representations, enabling most people to recognize the melodies after being transposed. This invariant property of melody transposition has been supported in many previous behavioral studies, and we hypothesize that there are brain regions showing tolerance toward melody transposition when processing melodies. To test the hypothesis, we adopted an event-related adaptation approach and a multivariate pattern cross-classification (MVCC) analysis approach. Consistent with our prediction, we discovered clusters in the right superior temporal gyrus (STG) and the left middle temporal gyrus (MTG) that exhibited adaptation when participants listened to both the same and transposed-same melodies after the original ones. An ROI and searchlight-based cross-classification analysis also revealed that BOLD pattern in the bilateral precentral gyrus (PreCG), the left inferior frontal gyrus (IFG), the left inferior parietal lobule (IPL), the right angular gyrus (AG), and the right superior temporal gyrus (STG) showed tolerance to melody transposition. These findings suggest that tolerance to melody transposition exists throughout the music processing pathway from auditory to motor cortices.

Functional architecture of cerebral cortex during naturalistic movie watching.

Characterizing the functional organization of cerebral cortex is a fundamental step in understanding how different kinds of information are processed in the brain. However, it is still unclear how these areas are organized during naturalistic visual and auditory stimulation. Here, we used high-resolution functional MRI data from 176 human subjects to map the macro-architecture of the entire cerebral cortex based on responses to a 60-min audiovisual movie stimulus. A data-driven clustering approach revealed a map of 24 functional areas/networks, each explicitly linked to a specific aspect of sensory or cognitive processing. Novel features of this map included an extended scene-selective network in the lateral prefrontal cortex, separate clusters responsive to human-object and human-human interaction, and a push-pull interaction between three executive control (domain-general) networks and domain-specific regions of the visual, auditory, and language cortex. Our cortical parcellation provides a comprehensive and unified map of functionally defined areas in the human cerebral cortex.

A subset of brain regions within adult functional connectivity networks demonstrates high reliability across early development.

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized into functional networks. These networks show stronger internal and weaker external functional connectivity (FC), with FC profiles more similar within the same network. Previous studies have shown these networks develop from nascent forms before birth to their mature, adult-like structures in childhood. However, these analyses often rely on adult functional network definitions. This study assesses the potential misidentification of infant functional networks when using adult models and explores the consequences and possible solutions to this problem. Our findings suggest that although adult networks only marginally describe infant FC organization better than chance, misidentification is primarily driven by specific areas. Restricting functional networks to areas with adult-like network clustering revealed consistent within-network FC across scans and throughout development. These areas are also near locations with low network identity variability. Our results highlight the implications of using adult networks for infants and offer guidance for selecting and utilizing functional network models based on research questions and scenarios.

SpaInGNN: Enhanced clustering and integration of spatial transcriptomics based on refined graph neural networks

Recent developments in spatial transcriptomics (ST) technology have markedly enhanced the proposed capacity to comprehensively characterize gene expression patterns within tissue microenvironments while crucially preserving spatial context. However, the identification of spatial domains at the single-cell level remains a significant challenge in elucidating biological processes. To address this, SpaInGNN was developed, a sophisticated graph neural network (GNN) framework that accurately delineates spatial domains by integrating spatial location data, histological information, and gene expression profiles into low-dimensional latent embeddings. Additionally, to fully leverage spatial coordinate data, spatial integration using graph neural network (SpaInGNN) refines the graph constructed for spatial locations by incorporating both tissue image distance and Euclidean distance, following a pre-clustering of gene expression profiles. This refined graph is then embedded using a self-supervised GNN, which minimizes self-reconfiguration loss. By applying SpaInGNN to refined graphs across multiple consecutive tissue slices, this study mitigates the impact of batch effects in data analysis. The proposed method demonstrates substantial improvements in the accuracy of spatial domain recognition, providing a more faithful representation of the tissue organization in both mouse olfactory bulb and human lateral prefrontal cortex samples

MVCLST: A spatial transcriptome data analysis pipeline for cell type classification based on multi-view comparative learning

Recent advancements in spatial transcriptomics sequencing technologies can not only provide gene expression within individual cells or cell clusters (spots) in a tissue but also pinpoint the exact location of this expression and generate detailed images of stained tissue sections, which offers invaluable insights into cell type identification and cell function exploration. However, effectively integratingthegene expression data, spatial location information, and tissue images from spatial transcriptomics data presents a significant challenge for computational methodsin cell classification. In this work, we propose MVCLST, a multi-view comparative learningmethod to analyze spatial transcriptomicsdata for accurate cell type classification. MVCLSTconstructs two views based on gene expression profiles, cell coordinates and image features. The multi-view method we proposed can significantly enhance the effectiveness of feature extraction while avoiding the impact of erroneous information in organizing image or gene expression data. The model employs four separate encoders to capture shared and unique features within each view. To ensure consistency and facilitate information exchange between the two views, MVCLST incorporates a contrastive learning loss function. The extracted shared and private features from both views are fused using corresponding decoders. Finally, the model utilizes the Leiden algorithm to clusterthe learned featuresfor cell type identification. Additionally, we establish a framework called MVCLST-CCFS for spatial transcriptomicsdata analysis based on MVCLST and consistent clustering. Our method achieves excellent results in clustering on human dorsolateral prefrontal cortex data and the mouse brain tissue data. Italso outperforms state-of-the-art techniques in the subsequent search for highly variable genes across cell types on the mouse olfactory bulbdata.

PM2.5 Induces Developmental Neurotoxicity in Cortical Organoids

There is mounting evidence implicating the potential neurotoxic effects of PM2.5 during brain development, as it has been observed to traverse both the placental barrier and the fetal blood-brain barrier. However, the current utilization of 2D cell culture and animal models falls short in providing an accurate representation of human brain development. Consequently, the precise mechanisms underlying PM2.5-induced developmental neurotoxicity in humans remain obscure. To address this research gap, we constructed three-dimensional (3D) cortical organoids that faithfully recapitulate the initial stages of human cerebral cortex development. Our goal is to investigate the mechanisms of PM2.5-induced neurotoxicity using 3D brain organoids that express cortical layer proteins. Our findings demonstrate that exposure to PM2.5 concentrations of 5 μg/mL and 50 μg/mL induces neuronal apoptosis and disrupts normal neural differentiation, thereby suggesting a detrimental impact on neurodevelopment. Furthermore, transcriptomic analysis revealed PM2.5 exposure induced aberrations in mitochondrial complex I functionality, which is reminiscent of Parkinson's syndrome, potentially mediated by misguided axon guidance and compromised synaptic maintenance. This study is a pioneering assessment of the neurotoxicity of PM2.5 pollution on human brain tissues based on 3D cortical organoids, and the results are of great significance in guiding the formulation of the next air pollution prevention and control policies in China to achieve the sustainable improvement of air quality and to formulate pollution abatement strategies that can maximize the benefits to public health.

Evidence for convergence of distributed cortical processing in band-like functional zones in human entorhinal cortex.

The wide array of cognitive functions associated with the hippocampus is supported through interactions with the cerebral cortex. However, most of the direct cortical input to the hippocampus originates in the entorhinal cortex, forming the hippocampal-entorhinal system. In humans, the role of the entorhinal cortex in mediating hippocampal-cortical interactions remains unknown. In this study, we used precision neuroimaging to examine the distributed cortical anatomy associated with the human hippocampal-entorhinal system. Consistent with animal anatomy, our results associate different subregions of the entorhinal cortex with different parts of the hippocampus long axis. Furthermore, we find that the entorhinal cortex comprises three band-like zones that are associated with functionally distinct cortical networks. Importantly, the entorhinal cortex bands traverse the proposed human homologs of rodent lateral and medial entorhinal cortices. Finally, we show that the entorhinal cortex is a major convergence area of distributed cortical processing and that the topography of cortical networks associated with the anterior medial temporal lobe mirrors the macroscale structure of high-order cortical processing.

Synaptic and extrasynaptic distribution of NMDA receptors in the cortex of Alzheimer's disease patients.

Synaptic and extrasynaptic distribution of N-methyl-D-aspartate receptors (NMDARs) has not been addressed in the brain from Alzheimer´s disease (AD) subjects, despite theircontribution to neurodegeneration. We have developed a protocol to isolate synaptic and extrasynaptic membranes from controls and AD frontal cortex. We characterized the distribution of the NMDAR subunits GluN2B, GluN2A, GluN1, and GluN3A, as well aspost-translational modifications, such as phosphorylation and glycosylation. Lower levels of synaptic GluN2B and GluN2A were found in AD fractions, while extrasynaptic GluN2B and GluN1 levels were significantly higher; GluN3A distribution remained unaffected in AD. We also identified different glycoforms of GluN2B and GluN2A in extrasynaptic membranes. Synaptic Tyr1472 GluN2B phosphorylation was significantly lower in AD fractions. Reduction of synaptic NMDAR subunits, particularly for GluN2B, is likely to contribute to synaptic transmission failure in AD. Additionally, the increment of extrasynaptic NMDAR subunits could favor the activation of excitotoxicity in AD. New protocol to isolate synaptic and extrasynaptic membranes from the human cortex. Low GluN2B and GluN2A levels in Alzheimer´s disease (AD) synaptic membranes. High GluN2B and GluN1 levels in AD extrasynaptic membranes. Specific glycoforms of extrasynaptic GluN2B and GluN2A. Low phosphorylation at Tyr1472 in synaptic GluN2B in AD.

Transposable element small and long RNAs in aging brains and implications in Huntington's and Parkinson's disease.

Transposable Elements (TEs) are implicated in aging and neurodegenerative disorders, but the impact of brain TE RNA dynamics on these phenomena is not fully understood. Therefore, we quantified TE RNA changes in aging post-mortem human and mouse brains and in the neurodegenerative disorders Huntington's Disease (HD) and Parkinson's Disease (PD). We tracked TE small RNAs (smRNAs) expression landscape to assess the relationship to the active processing from TE long RNAs (lnRNAs). Human brain transcriptomes from the BrainSpan Atlas displayed a significant shift of TE smRNA patterns at age 20 years, whereas aging mouse brains lacked any such marked change, despite clear shift in aging-associated mRNA levels. Human frontal cortex displayed pronounced sense TE smRNAs during aging with a negative relationship between the TE smRNAs and lnRNAs indicative of age associated regulatory effects. Our analysis revealed TE smRNAs dysregulation in HD, while PD showed a stronger impact on TE lnRNAs, potentially correlating with the early average age of death for HD relative to PD. Furthermore, TE-silencing factor TRIM28 was down-regulated only in aging human brains, possibly explaining the lack of substantial TE RNA changes in aging mouse brains. Our study suggests brain TE RNAs may serve as novel biomarkers of human brain aging and neurodegenerative disorders.

Spatiotemporal mapping of auditory onsets during speech production.

The human auditory cortex is organized according to the timing and spectral characteristics of speech sounds during speech perception. During listening, the posterior superior temporal gyrus is organized according to onset responses, which segment acoustic boundaries in speech, and sustained responses, which further process phonological content. When we speak, the auditory system is actively processing the sound of our own voice to detect and correct speech errors in real time. This manifests in neural recordings as suppression of auditory responses during speech production compared to perception, but whether this differentially affects onset and sustained temporal profiles is not known. Here we investigated this question using intracranial EEG recorded from seventeen pediatric, adolescent, and adult patients with medication-resistant epilepsy while they performed a reading/listening task. We identified onset and sustained responses to speech in bilateral auditory cortex and observed a selective suppression of onset responses during speech production. We conclude that onset responses provide a temporal landmark during speech perception that is redundant with forward prediction during speech production and are therefore suppressed. Phonological feature tuning in these "onset suppression" electrodes remained stable between perception and production. Notably, auditory onset responses and phonological feature tuning were present in the posterior insula during both speech perception and production, suggesting an anatomically and functionally separate auditory processing zone that we believe to be involved in multisensory integration during speech perception and feedback control.Significance Statement Specific neural populations in the auditory cortex preferentially respond to the onset of speech sounds. These "onset responses" aid in perceiving boundaries in continuous speech. We recorded neural responses from patients with intracranial electrodes during a speaking and listening task to investigate the role of onset responses in speech production. Onset responses were present in the auditory cortex during listening, but absent during speaking. On the other hand, onset responses were observed in the insula during both conditions, suggesting a different functional role for the insula in auditory feedback processing. These findings extend our knowledge of how different parts of the brain involved in feedback control operate during speech production by identifying two functionally and anatomically distinct patterns of activity.

Segmentation window of speech information processing in the human auditory cortex

Humans perceive continuous speech signals as discrete sequences. To clarify the temporal segmentation window of speech information processing in the human auditory cortex, the relationship between speech perception and cortical responses was investigated using auditory evoked magnetic fields (AEFs). AEFs were measured while participants heard synthetic Japanese words /atataka/. There were eight types of /atataka/ with different speech rates. The durations of the words ranged from 75 to 600 ms. The results revealed a clear correlation between the AEFs and syllables. Specifically, when the durations of the words were between 375 and 600 ms, the evoked responses exhibited four clear responses from the superior temporal area, M100, that corresponded not only to the onset of speech but also to each group of consonant/vowel syllable units. The number of evoked M100 responses was correlated to the duration of the stimulus as well as the number of perceived syllables. The approximate range of the temporal segmentation window limit of speech perception was considered to be between 75 and 94 ms. This finding may contribute to optimizing the temporal performance of high-speed synthesized speech generation systems.