Speech and music have structured rhythms. Here we discuss a major acoustic correlate of spoken and musical rhythms, the slow (0.25-32Hz) temporal modulations in sound intensity and compare the modulation properties of speech and music. We analyze these modulations using over 25h of speech and over 39h of recordings of Western music. We show that the speech modulation spectrum is highly consistent across 9 languages (including languages with typologically different rhythmic characteristics). A different, but similarly consistent modulation spectrum is observed for music, including classical music played by single instruments of different types, symphonic, jazz, and rock. The temporal modulations of speech and music show broad but well-separated peaks around 5 and 2Hz, respectively. These acoustically dominant time scales may be intrinsic features of speech and music, a possibility which should be investigated using more culturally diverse samples in each domain. Distinct modulation timescales for speech and music could facilitate their perceptual analysis and its neural processing.

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How the brain groups sequential sensory events into chunks is a fundamental question in cognitive neuroscience. This study investigates whether top-down attention or specific tasks are required for the brain to apply lexical knowledge to group syllables into words. Neural responses tracking the syllabic and word rhythms of a rhythmic speech sequence were concurrently monitored using electroencephalography (EEG). The participants performed different tasks, attending to either the rhythmic speech sequence or a distractor, which was another speech stream or a nonlinguistic auditory/visual stimulus. Attention to speech, but not a lexical-meaning-related task, was required for reliable neural tracking of words, even when the distractor was a nonlinguistic stimulus presented cross-modally. Neural tracking of syllables, however, was reliably observed in all tested conditions. These results strongly suggest that neural encoding of individual auditory events (i.e., syllables) is automatic, while knowledge-based construction of temporal chunks (i.e., words) crucially relies on top-down attention.

Schizophrenia is thought as a self-disorder with dysfunctional brain connectivity. This self-disorder is often attributed to high-order cognitive impairment. Yet due to the frequent report of sensorial and perceptual deficits, it has been hypothesized that self-disorder in schizophrenia is dysfunctional communication between sensory and cognitive processes. To further verify this assumption, the present study comprehensively examined dynamic reconfigurations of resting-state functional connectivity (rsFC) in schizophrenia at voxel level, region level, and network levels (102 patients vs. 124 controls). We found patients who show consistently increased rsFC variability in sensory and perceptual system, including visual network, sensorimotor network, attention network, and thalamus at all the three levels. However, decreased variability in high-order networks, such as default mode network and frontal–parietal network were only consistently observed at region and network levels. Taken together, these findings highlighted the rudimentary role of elevated instability of information communication in sensory and perceptual system and attenuated whole-brain integration of high-order network in schizophrenia, which provided novel neural evidence to support the hypothesis of disrupted perceptual and cognitive function in schizophrenia. The foci of effects also highlighted that targeting perceptual deficits can be regarded as the key to enhance our understanding of pathophysiology in schizophrenia and promote new treatment intervention.

Our understanding of cerebellar involvement in brain disorders has evolved from motor processing to high-level cognitive and affective processing. Recent neuroscience progress has highlighted hierarchy as a fundamental principle for the brain organization. Despite substantial research on cerebellar dysfunction in schizophrenia, there is a need to establish a neurobiological framework to better understand the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellum in schizophrenia. To help to establish such a framework, we investigated the abnormalities in the distribution of sensorimotor-supramodal hierarchical processing topography in the cerebellum and cerebellar-cerebral circuits in schizophrenia using a novel gradient-based resting-state functional connectivity (FC) analysis (96 patients with schizophrenia vs 120 healthy controls). We found schizophrenia patients showed a compression of the principal motor-to-supramodal gradient. Specifically, there were increased gradient values in sensorimotor regions and decreased gradient values in supramodal regions, resulting in a shorter distance (compression) between the sensorimotor and supramodal poles of this gradient. This pattern was observed in intra-cerebellar, cerebellar-cerebral, and cerebral-cerebellar FC. Further investigation revealed hyper-connectivity between sensorimotor and cognition areas within cerebellum, between cerebellar sensorimotor and cerebral cognition areas, and between cerebellar cognition and cerebral sensorimotor areas, possibly contributing to the observed compressed pattern. These findings present a novel mechanism that may underlie the co-occurrence and interaction of low- and high-level functional abnormalities of cerebellar and cerebro-cerebellar circuits in schizophrenia. Within this framework of abnormal motor-to-supramodal organization, a cascade of impairments stemming from disrupted low-level sensorimotor system may in part account for high-level cognitive cerebellar dysfunction in schizophrenia.

Benign epilepsy with centrotemporal spikes (BECT) is the most common childhood idiopathic focal epilepsy syndrome, which characterized with white‐matter abnormalities in the rolandic cortex. Although diffusion tensor imaging research could characterize white‐matter structural architecture, it cannot detect neural activity or white‐matter functions. Recent studies demonstrated the functional organization of white‐matter by using functional magnetic resonance imaging (fMRI), suggesting that it is feasible to investigate white‐matter dysfunctions in BECT. Resting‐state fMRI data were collected from 24 new‐onset drug‐naive (unmedicated [NMED]), 21 medicated (MED) BECT patients, and 27 healthy controls (HC). Several white‐matter functional networks were obtained using a clustering analysis on voxel‐by‐voxel correlation profiles. Subsequently, conventional functional connectivity (FC) was calculated in four frequency sub‐bands (Slow‐5:0.01–0.027, Slow‐4:0.027–0.073, Slow‐3:0.073–0.198, and Slow‐2:0.198–0.25 Hz). We also employed a functional covariance connectivity (FCC) to estimate the covariant relationship between two white‐matter networks based on their correlations with multiple gray‐matter regions. Compared with HC, the NMED showed increased FC and/or FCC in rolandic network (RN) and precentral/postcentral network, and decreased FC and/or FCC in dorsal frontal network, while these alterations were not observed in the MED group. Moreover, the changes exhibited frequency‐specific properties. Specifically, only two alterations were shared in at least two frequency bands. Most of these alterations were observed in the frequency bands of Slow‐3 and Slow‐4. This study provided further support on the existence of white‐matter functional networks which exhibited frequency‐specific properties, and extended abnormalities of rolandic area from the perspective of white‐matter dysfunction in BECT.

Background Schizophrenia has been primarily conceptualized as a disorder of high-order cognitive functions with deficits in executive brain regions. Yet due to the increasing reports of early sensory processing deficit, recent models focus more on the developmental effects of impaired sensory process on high-order functions. The present study examined whether this pathological interaction relates to an overarching system-level imbalance, specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Methods We applied a novel combination of connectome gradient and stepwise connectivity analysis to resting-state fMRI to characterize the sensorimotor-to-transmodal cortical hierarchy organization (96 patients v. 122 controls). Results We demonstrated compression of the cortical hierarchy organization in schizophrenia, with a prominent compression from the sensorimotor region and a less prominent compression from the frontal−parietal region, resulting in a diminished separation between sensory and fronto-parietal cognitive systems. Further analyses suggested reduced differentiation related to atypical functional connectome transition from unimodal to transmodal brain areas. Specifically, we found hypo-connectivity within unimodal regions and hyper-connectivity between unimodal regions and fronto-parietal and ventral attention regions along the classical sensation-to-cognition continuum (voxel-level corrected, p < 0.05). Conclusions The compression of cortical hierarchy organization represents a novel and integrative system-level substrate underlying the pathological interaction of early sensory and cognitive function in schizophrenia. This abnormal cortical hierarchy organization suggests cascading impairments from the disruption of the somatosensory−motor system and inefficient integration of bottom-up sensory information with attentional demands and executive control processes partially account for high-level cognitive deficits characteristic of schizophrenia.