Hsi Tiana Wei

Schizophrenia disrupts both how people perceive the world and how they express and act on their thoughts, yet these symptoms are usually studied separately. Using magnetoencephalography during multisensory and motor tasks, we tested whether reduced event-related beta-band (15 to 30 hertz) modulation, a signal implicated in predictive control, provides a candidate neural marker across these domains. Compared to healthy individuals, patients showed diminished beta changes during sensory processing and movement completion, suggesting reduced flexibility in updating internal models. This neural pattern covaried with audiovisual simultaneity-judgment behavior, disorganized natural speech, and greater clinical severity. These findings suggest that distributed beta modulation may serve as a candidate cross-domain marker associated with perceptual, motor, and language disturbances in schizophrenia, motivating future studies that directly test predictive updating mechanisms.

Background: Thought disorder in schizophrenia reflects disrupted internal model maintenance in predictive processing. Beta oscillations have been proposed to index top-down predictive signalling, but prior resting-state studies have focused on spectral power, overlooking transient burst dynamics that enable the stabilization and reinstatement of internal representations, especially in the default mode network (DMN). Methods: Resting-state MEG was acquired from 25 patients (7 females) with schizophrenia and 25 matched controls (8 females) between May 2024 and October 2025. Beta bursts (15-30 Hz) were extracted from source-localized cortical time series, and burst rate, duration, power, and inter-regional synchrony were quantified. Associations with computationally-derived semantic and syntactic speech features were assessed using principal-component regression within patients. Results: Conventional beta power did not differ between groups after correction. In contrast, beta-burst dynamics showed significant group-by-anterior-posterior-position interactions for burst rate (p = 0.018), power (p = 0.0014) and duration (p < 0.001). Within the DMN, patients showed shorter inferior parietal burst duration (t(46.0) = -2.74, FDR-p = 0.0343) and increased burst synchrony within left prefrontal cortex (t(31.0) = 2.81, FDR-p = 0.0343) and between prefrontal cortices (t(29.8) = 2.73, FDR-p = 0.0423). Within patients, burst components predicted speech organization (R-squared = 0.47, F(3,19) = 5.66, p = 0.006), driven by the inferior parietal burst-duration component (β = -0.55, p = 0.0036), but did not predict overall clinical severity. Limitations: The modest patient sample, short resting-state recording, cross-sectional design, and lack of laminar specificity limit causal and mechanistic inference; burst-speech associations require replication. Conclusion: Schizophrenia was associated with dissociable anterior and posterior beta-burst abnormalities that tracked objective speech markers of thought disorder. These findings suggest impaired hierarchical coordination of predictive beta signalling as a candidate mechanism linking intrinsic network dysfunction to disorganized thought.

Schizophrenia, major depressive disorder (MDD), and bipolar disorder (Severe Mental Illnesses: SMIs), share genetic risk and brain structure, but their neural mechanisms remain unclear. Magnetoencephalography (MEG), with millisecond precision, enables direct examination of shared and disorder-specific disturbances in neural timing. We reviewed resting-state MEG evidence on spectral power, connectivity, information-theoretic complexity, and brain dynamics across SMIs.A comprehensive search yielded 62 studies. Three reviewers screened, retrieved, and extracted data on MEG-related variables across regional activity (power), coordination of activity (connectivity, coherence, synchrony), regularity of activity (complexity, entropy), and overall dynamics.Three principal findings emerged. Beta oscillations emerge as the most consistently replicated transdiagnostic signal across separate disorder-specific studies, with increased power across all three disorders and correlating with hallucinations, sleep disturbances, and cognitive deficits, consistent with disrupted predictive processing. Preliminary evidence emerges that complexity–age dissociation may partition SMIs into neuroprogressive and state-dependent trajectories: neural complexity declines with age in schizophrenia and bipolar disorder (opposite to healthy aging), while depression preserves the normative trajectory. Slow-wave activity diverges sharply: schizophrenia shows a widespread increase characteristic of cortical ‘idling,’ while mood disorders show a decrease characteristic of ‘restlessness.’We propose a temporal disorganisation spectrum from excessive fragmentation (schizophrenia) to pathological rigidity (depression), with bipolar disorder occupying an intermediate position. This framework offers biomarker-type utility for stratifying illness severity, tracking neuroprogression, and identifying transdiagnostic therapeutic targets, particularly beta-modulatory neuromodulation interventions applicable across SMIs.

Schizophrenia is characterized by disturbances in both perception and expression that profoundly impair social functioning, yet these domains are typically studied in isolation. Predictive processing theories suggest that such symptoms may arise from abnormal updating of internal models, but the neural mechanisms linking perceptual and expressive dysfunction remain unclear. Using magnetoencephalography during multisensory perception and motor tasks, we tested whether beta-band activity (15-30 Hz), a neural signal implicated in predictive control, provides a shared substrate across domains. Compared to healthy individuals, patients with schizophrenia showed attenuated event-related modulation of beta activity, including weaker beta suppression during sensory processing and delayed or reduced post-movement beta rebound. These abnormalities were associated with a widened audiovisual temporal binding window, indicating atypical multisensory integration. Multivariate analyses further revealed that reduced beta modulation across sensory and motor systems covaried with impoverished semantic diversity, simplified syntactic structure in natural speech, and greater clinical symptom burden. Notably, beta abnormalities emerged as distributed latent patterns spanning sensory, motor, and frontotemporal regions. Together, these findings identify diminished event-related beta modulation as a common neural signature linking disrupted multisensory integration, action monitoring, and language organization in schizophrenia. We situate perceptual and expressive impairments within a unified framework of predictive dysfunction and advance a mechanistically grounded account that highlights beta dynamics as a promising target for future mechanistic and translational studies in psychosis. Significance Statement: Schizophrenia disrupts both how people perceive the world and how they express their thoughts, yet these symptoms are usually studied separately. Using magnetoencephalography during multisensory and motor tasks, we identify a shared neural mechanism linking these domains: reduced event-related modulation of beta-band (15–30 Hz) activity, a signal implicated in predictive control. Compared to healthy individuals, patients showed diminished beta changes during sensory processing and movement completion, suggesting reduced flexibility in updating internal models. Importantly, this neural pattern covaried with abnormal audiovisual binding, disorganized natural speech, and greater clinical severity. These findings reveal distributed beta modulation as a cross-domain neural marker of predictive dysfunction, offering a unified framework for understanding perceptual and expressive disturbances in schizophrenia.

Background: Thought disorder in schizophrenia likely reflects disrupted maintenance of internal models during predictive processing. Beta oscillations have been proposed to index top-down predictive signalling, but prior resting-state studies have focused on spectral power, overlooking transient burst dynamics that potentially stabilize and reinstate internal representations, especially in the default mode network (DMN). Methods: Resting-state magnetoencephalography was acquired from 25 patients (7 females) with schizophrenia and 25 matched controls (8 females) between May 2024 and October 2025. Beta bursts (15–30 Hz) were extracted from source-localized cortical time series, and burst rate, duration, power, and inter-regional synchrony were quantified. Associations with computationally derived semantic and syntactic speech features reflecting thought disorder were assessed using principal-component regression in the patient group. Results: Conventional beta power did not differ between groups after correction. In contrast, beta-burst dynamics showed significant group-by-anterior–posterior-position interactions for burst rate ( p = 0.018), power ( p = 0.0014), and duration ( p < 0.001). Within the DMN, patients showed shorter inferior parietal burst duration ( t(46.0) = −2.74, FDR-adjusted p = 0.0343) and increased burst synchrony within left prefrontal cortex ( t(31.0) = 2.81, FDR-adjusted p = 0.0343) and between prefrontal cortices ( t(29.8) = 2.73, FDR-adjusted p = 0.0423). Within the patient group, burst components were associated with speech organization ( R ² = 0.47, F(3,19) = 5.66, p = 0.006), driven by the inferior parietal burst-duration component (β = −0.55, p = 0.0036), but did not relate to overall clinical severity. Limitations: The modest patient sample, short resting-state recording, cross-sectional design, and lack of laminar specificity limit causal and mechanistic inference; burst-speech associations require replication. Conclusion: Schizophrenia is associated with dissociable anterior and posterior beta-burst abnormalities that track objective speech markers of thought disorder. These findings suggest impaired hierarchical coordination of predictive beta signalling as a candidate neurophysiological account linking intrinsic network dysfunction to disorganized thought.

Purpose: Automated analysis of naturalistic speech has emerged as an effective tool for detecting cognitive decline in dementia but has seldom been used to examine the ordinary cognitive decline occurring in normal aging. Executive function (EF) declines throughout the adult lifespan but is difficult to track longitudinally due to practice effects, making speech-based assessments particularly attractive. This study examined relationships between EF and speech characteristics. Method: We collected two audio picture descriptions from participants in two experiments that also included EF assessments, with 67 healthy older adults (aged 65–75 years) in Study 1 and 174 healthy adults (aged 18–90 years) in Study 2. Language composite scores were computed by aggregating relevant speech features indexing aspects of speech that have been reported to show changes in pathological aging. Principal components reflecting common covariation in speech features were extracted from a large training data set to compute speech domain scores. The relationships between language composites/speech principal components and EF were assessed while controlling for age, gender, and education. Results: In Study 1, older adults' word-finding difficulties, measured as speech disfluencies, showed significant associations with EF. Study 2 confirms that speech disfluencies can explain individual differences in EF not only for adults above the age of 65 years but also across the adult lifespan. Information units and coherence in speech showed weaker associations with EF and Montreal Cognitive Assessment scores that were not significant after correction for multiple comparisons. Conclusion: The findings revealed associations between word-finding ability in natural speech and general EF across the adult lifespan, supporting natural speech analysis as a convenient and sensitive assessment of general cognitive ability.

Background: Predictive processing abnormalities offer a unifying account of perceptual and expressive disturbances in psychosis, yet classical predictive coding frameworks remain difficult to translate due to limited neurophysiological grounding. Emerging evidence positions beta-band oscillations and their transient burst dynamics as a biologically plausible mechanism for implementing top-down predictions that stabilize internal models. Study Design: This narrative review synthesizes evidence from electrophysiology, laminar physiology, computational modelling, language research, and clinical neuroimaging to evaluate beta oscillations as a mechanistic target for predictive processing deficits in psychosis. We integrate data from modified predictive routing frameworks and dendritic computation models to clarify how beta rhythms prepare cortical pathways for predicted inputs. Study Results: Across sensory, motor, cognitive, and language domains, schizophrenia features impaired generation, timing, and contextual deployment of beta activity. These include attenuated post-movement beta rebound, reduced or mistimed beta bursts during working memory and inhibition, abnormal beta-gamma interactions during perception, and weakened beta-mediated contextual guidance during language comprehension. Laminar and computational findings indicate that beta bursts arise from the integration of apical (contextual) and basal (sensory) dendritic inputs in layer 5 pyramidal neurons, providing a mechanistic substrate for top-down predictions. Beta disruptions, therefore, offer a parsimonious account of disorganization, psychomotor slowing, and failures of contextual maintenance. Early neuromodulation, pharmacologic, and neurofeedback studies suggest that beta dynamics are modifiable. Conclusions: Beta oscillations provide a tractable and mechanistically grounded target for predictive processing deficits in psychosis. Standardizing burst metrics and developing individualized, closed-loop approaches will be critical for advancing beta-based interventions.

Word-finding difficulty (WFD) is a common cognitive complaint in aging, manifesting both in natural speech and in controlled laboratory tests. Various theories of cognitive aging have addressed WFD, and understanding its underlying mechanisms can help to clarify whether it has diagnostic value for neurodegenerative disease. Two influential "information-universal" theories attribute it to rather broad changes in cognition. The processing speed theory posits a general slowdown of all cognitive processes, while the inhibitory deficit hypothesis (IDH) predicts a specific problem in suppressing irrelevant information. One "information specific" theory of language production, the transmission deficit hypothesis (TDH), posits a breakdown in retrieval of phonological word forms from a corresponding lemma. To adjudicate between these accounts, we administered an online gamified covert naming task featuring picture-word interference (PWI), previously validated to elicit similar semantic interference and phonological facilitation effects as overt naming tasks. 125 healthy adults aged 18 to 85 completed the task, along with a battery of executive function tasks and a naturalistic speech sample to quantify WFD in connected speech. PWI effects provided strong support for the TDH but limited support for IDH, in that semantic interference increased and phonological facilitation decreased across the lifespan. However, neither of these effects on single-word retrieval associated with WFD measured in connected speech. Rather, overall reaction time for word retrieval (controlling for psychomotor slowing) was the best predictor of spontaneous WFD and executive function decline, suggesting processing speed as the key factor, and that verbal reaction time may be an important clinical measure.

The picture-word interference (PWI) paradigm has been used to investigate the time course of processes involved in word retrieval, but is challenging to implement online due to dependence on measurements of vocal reaction time. We performed a series of four experiments to examine picture-word interference and facilitation effects in a form of covert picture naming, with and without gamification. A target picture was accompanied by an audio word distractor that was either unrelated, phonologically-related, associatively-related, or categorically-related to the picture. Participants were instructed to judge whether the name of the target picture ended in the phoneme assigned to the block by pressing corresponding keys as quickly and accurately as possible. Experiments 1 and 2 successfully replicated categorical interference and phonological facilitation effects at different optimal stimulus-onset-asynchronies (SOAs) between words and pictures. Experiment 3 demonstrated that a key gamification feature (collecting coins) motivated faster speed at the expense of accuracy in the gamified vs. experimental format of the task. Experiment 4 adopted the optimal SOAs and verified that the gamification reveals expected interference and facilitation effects despite the speed-accuracy tradeoff. These studies confirmed that categorical interference occurs earlier than phonological facilitation, while both processes are independent from articulation and inherent to word retrieval itself. The covert PWI paradigm and its gamification have methodological value for neuroimaging studies in which articulatory artifacts obscure word retrieval processes, and may be developed into potential online word-finding assessments that can reveal word retrieval difficulties with greater sensitivity.