A Hierarchical Generative Framework of Language Processing: Linking Language Perception, Interpretation, and Production Abnormalities in Schizophrenia

Weaker top-down cognitive control and stronger bottom-up signaling transmission as a pathogenesis of schizophrenia

The clinical symptoms of schizophrenia are highly heterogeneous, with the most striking symptoms being cognitive deficits and perceptual disturbances. Cognitive deficits are typically linked to abnormalities in top-down mechanisms, whereas perceptual disturbances stem from dysfunctions in bottom-up processing. However, it remains unclear whether schizophrenia is primarily driven by top-down control mechanisms, bottom-up perceptual processes, or their interaction. We hypothesized that abnormal top-down and bottom-up interactions constitute the neural mechanisms of schizophrenia. Considering that autoencoders can identify hidden data features and support vector machines are capable of automatically locating the classification hyperplane, we developed an improved stacked autoencoder-support vector machine (ISAE-SVM) model for diagnosing schizophrenia based on resting-state functional magnetic resonance imaging data. A permutation test was used to identify the 213 most discriminative functional connections from the model's output features. Functional connections linking regions of higher cognitive functions and lower perceptual tasks were extracted to further examine their relevance to clinical symptoms. Finally, spectral dynamic causal modeling (sDCM) was used to analyze the dynamic causal interaction between brain regions corresponding to these functional connections. Our results showed that the ISAE-SVM model achieved an average classification accuracy of 82%. Notably, five resting-state functional connections spanning both cognitive and sensory brain areas were significantly correlated with Positive and Negative Syndrome Scale scores. Furthermore, sDCM analysis revealed weakened top-down regulation and enhanced bottom-up signaling in schizophrenia. These findings support our hypothesis that impaired top-down regulation and enhanced bottom-up signaling contribute to the neural mechanisms of schizophrenia.

Entrainment of neural oscillations during language processing in Early-Stage schizophrenia

BACKGROUND

Impairments in language processing in schizophrenia (ScZ) are a central aspect of the disorder but the underlying pathophysiology mechanisms are unclear. In the current study, we tested the hypothesis that neural oscillations are impaired during speech tracking in early-stage ScZ and in participants at clinical high-risk for psychosis (CHR-P).

METHOD

Magnetoencephalography (MEG) was used in combination with source reconstructed time-series to examine delta and theta-band entrainment during continuous speech. Participants were presented with a 5-minute audio recording during which they either attened to the story or word level. MEG-data were obtained from n = 22 CHR-P participants, n = 23 early-stage ScZ-patients, and n = 44 healthy controls (HC). Data were analysed with a Mutual Information (MI) approach to compute statistical dependence between the MEG and auditory signal, thus estimating individual speech-tracking ability. MEG-activity was reconstructed in a language network (bilateral inferior frontal cortex [F3T; Broca's], superior temporal areas [STS3, STS4; Wernicke's areas], and primary auditory cortex [bilateral HES; Heschl's gyrus]). MEG-data were correlated with clinical symptoms.

RESULTS

Theta-band entrainment in left Heschl's gyrus, averaged across groups, was significantly lower in the STORY compared to WORD condition (p = 0.022), and averaged over conditions, significantly lower in CHR-Ps (p = 0.045), but intact in early ScZ patients (p = 0.303), compared to controls. Correlation analyses between MEG data and symptom indicated that lower theta-band tracking in CHR-Ps was linked to the severity of perceptual abnormalities (p = 0.018).

CONCLUSION

Our results show that CHR-P participants involve impairments in theta-band entrainment during speech tracking in left primary auditory cortex while higher-order speech processing areas were intact. Moreover, the severity of aberrant perceptual experiences in CHR-P participants correlated with deficits in theta-band entrainment. Together, these findings highlight the possibility that neural oscillations during language processing could reveal fundamental abnormalities in speech processing which may constitute candidate biomarkers for early detection and diagnosis of ScZ.

Causal role of frontocentral beta oscillation in comprehending linguistic communicative functions

Linguistic communication is often considered as an action serving the function of conveying the speaker's goal to the addressee. Although neuroimaging studies have suggested a role of the motor system in comprehending communicative functions, the underlying mechanism is yet to be specified. Here, by two EEG experiments and a tACS experiment, we demonstrate that the frontocentral beta oscillation, which represents action states, plays a crucial part in linguistic communication understanding. Participants read scripts involving two interlocutors and rated the interlocutors' attitudes. Each script included a critical sentence said by the speaker expressing a context-dependent function of either promise, request, or reply to the addressee's query. These functions were behaviorally discriminated, with higher addressee's will rating for the promise than for the reply and higher speaker's will rating for the request than for the reply. EEG multivariate analyses showed that different communicative functions were represented by different patterns of the frontocentral beta activity but not by patterns of alpha activity. Further tACS results showed that, relative to alpha tACS and sham stimulation, beta tACS improved the predictability of communicative functions of request or reply, as measured by the speaker's will rating. These results convergently suggest a causal role of the frontocentral beta activities in comprehending linguistic communications.

Pre-Stimulus Activity of Left and Right TPJ in Linguistic Predictive Processing: A MEG Study

BACKGROUND

The left and right temporoparietal junctions (TPJs) are two brain areas involved in several brain networks, largely studied for their diverse roles, from attentional orientation to theory of mind and, recently, predictive processing. In predictive processing, one crucial concept is prior precision, that is, the reliability of the predictions of incoming stimuli. This has been linked with modulations of alpha power as measured with electrophysiological techniques, but TPJs have seldom been studied in this framework.

METHODS

The present article investigates, using magnetoencephalography, whether spontaneous oscillations in pre-stimulus alpha power in the left and right TPJs can modulate brain responses during a linguistic task that requires predictive processing in literal and non-literal sentences.

RESULTS

Overall, results show that pre-stimulus alpha power in the rTPJ was associated with post-stimulus responses only in the left superior temporal gyrus, while lTPJ pre-stimulus alpha power was associated with post-stimulus activity in Broca's area, left middle temporal gyrus, and left superior temporal gyrus.

CONCLUSIONS

We conclude that both the right and left TPJs have a role in linguistic prediction, involving a network of core language regions, with differences across brain areas and linguistic conditions that can be parsimoniously explained in the context of predictive processing.

Early auditory processing abnormalities alter individual learning trajectories and sensitivity to computerized cognitive training in schizophrenia

BACKGROUND

Auditory system plasticity is a promising target for neuromodulation, cognitive rehabilitation and therapeutic development in schizophrenia (SZ). Auditory-based targeted cognitive training (TCT) is a 'bottom up' intervention designed to enhance the speed and accuracy of auditory information processing, which has been shown to improve neurocognition in certain SZ patients. However, the dynamics of TCT learning as a function of training exercises and their impact on neurocognitive functioning and therapeutic outcomes are unknown.

METHODS

Forty subjects (SZ, n = 21; healthy subjects (HS), n = 19) underwent comprehensive clinical, cognitive, and auditory assessments, including measurements of auditory processing speed (APS) at baseline and after 1-h of TCT. SZ patients additionally completed 30-hours of TCT and repeated assessments ~10-12 weeks later.

RESULTS

SZ patients were deficient in APS at baseline (d = 0.96, p < 0.005) relative to HS. After 1-h of TCT, analyses revealed significant main effects of diagnosis (d = 1.75, p = 0.002) and time (d = 1.04, p < 0.001), and a diagnosis × time interaction (d = 0.85, p = 0.02) on APS. APS learning effects were robust after 1-h in SZ patients (d = 1.47, p < 0.001) and persisted throughout the 30-h of training. Baseline APS was associated with verbal learning gains after 30-h of TCT (r = 0.51, p = 0.02) in SZ.

CONCLUSIONS

TCT learning metrics may have prognostic utility and aid in the prospective identification of individuals likely to benefit from TCT. Future experimental medicine studies may advance predictive algorithms that enhance TCT-related clinical, cognitive and functional outcomes.

The Costs (and Benefits?) of Effortful Listening for Older Adults: Insights from Simultaneous Electrophysiology, Pupillometry, and Memory

Although the impact of acoustic challenge on speech processing and memory increases as a person ages, older adults may engage in strategies that help them compensate for these demands. In the current preregistered study, older adults (n = 48) listened to sentences-presented in quiet or in noise-that were high constraint with either expected or unexpected endings or were low constraint with unexpected endings. Pupillometry and EEG were simultaneously recorded, and subsequent sentence recognition and word recall were measured. Like young adults in prior work, we found that noise led to increases in pupil size, delayed and reduced ERP responses, and decreased recall for unexpected words. However, in contrast to prior work in young adults where a larger pupillary response predicted a recovery of the N400 at the cost of poorer memory performance in noise, older adults did not show an associated recovery of the N400 despite decreased memory performance. Instead, we found that in quiet, increases in pupil size were associated with delays in N400 onset latencies and increased recognition memory performance. In conclusion, we found that transient variation in pupil-linked arousal predicted trade-offs between real-time lexical processing and memory that emerged at lower levels of task demand in aging. Moreover, with increased acoustic challenge, older adults still exhibited costs associated with transient increases in arousal without the corresponding benefits.

A predictive coding model of the N400

The N400 event-related component has been widely used to investigate the neural mechanisms underlying real-time language comprehension. However, despite decades of research, there is still no unifying theory that can explain both its temporal dynamics and functional properties. In this work, we show that predictive coding - a biologically plausible algorithm for approximating Bayesian inference - offers a promising framework for characterizing the N400. Using an implemented predictive coding computational model, we demonstrate how the N400 can be formalized as the lexico-semantic prediction error produced as the brain infers meaning from the linguistic form of incoming words. We show that the magnitude of lexico-semantic prediction error mirrors the functional sensitivity of the N400 to various lexical variables, priming, contextual effects, as well as their higher-order interactions. We further show that the dynamics of the predictive coding algorithm provides a natural explanation for the temporal dynamics of the N400, and a biologically plausible link to neural activity. Together, these findings directly situate the N400 within the broader context of predictive coding research. More generally, they raise the possibility that the brain may use the same computational mechanism for inference across linguistic and non-linguistic domains.

Neuropsychological dimensions related to alterations of verbal self-monitoring neural networks in schizophrenic language: systematic review

Although schizophrenia has traditionally been interpreted as a disorder of thought, contemporary perspectives suggest that it may be more appropriate to conceptualize it as a disorder of language connectivity. The linguistic anomalies present in schizophrenia possess distinctive characteristics that, despite certain connections, are not comparable to aphasic disorders. It is proposed that these anomalies are the result of dysfunctions in verbal self-monitoring mechanisms, which may influence other neuropsychological dimensions. This study set out to examine the neuropsychological dimensions associated with alterations in the neural networks of verbal self-monitoring in schizophrenic language, based on the scientific evidence published to date. Exhaustive searches were conducted in PubMed, Web of Science, and Scopus to identify magnetic resonance studies that evaluated verbal self-monitoring mechanisms in schizophrenia. Of a total of 133 articles identified, 22 were selected for qualitative analysis. The general findings indicated alterations in frontotemporoparietal networks and in systems such as the insula, amygdala, anterior cingulate cortex, putamen, and hippocampus. Despite the heterogeneity of the data, it is concluded that language plays a fundamental role in schizophrenia and that its alterations are linked with other neuropsychological dimensions, particularly emotional and perceptual ones.

Flexibility Retained: Unimpaired Updating of Expectations in Schizophrenia

Flexibly and actively updating expectations based on feedback is crucial for navigating daily life. Previous research has shown that people with schizophrenia (PSZ) have difficulty adjusting their expectations. However, there are studies suggesting otherwise. To explore this further, we used a novel trial-based expectation updating paradigm called attribute amnesia. In the task, the participants needed to report the location of a target stimulus among distractors in pre-surprise trials. In the surprise trial, they were unexpectedly asked to report the identity of the target before reporting its location. Afterward, control trials were conducted whereby the participants were asked the same questions as in the surprise trial. Notably, the surprise trial and control trials were nearly identical, except that the participants expected to be asked about identity information in the control trials but not in the surprise trial. Thus, an improvement in identity reporting accuracy in the control trials in comparison with the surprise trial indicated active updating of expectations. In the current study, a total of 63 PSZ and 60 healthy control subjects (HCS) were enrolled. We found that both the PSZ and the HCS were unable to report information that they had fully attended to (i.e., identity) in the surprise trial. However, both groups showed a significant improvement in reporting identity information even in the first control trial. Critically, there was no significant difference in the magnitude of improvement between the two groups. The current findings indicate that PSZ have the ability to update their expectations as quickly and flexibly as HCS, at least in the context of the current task. The possible factors that might contribute to the discrepancy regarding expectation updating are discussed.

Linguistic findings in persons with schizophrenia-a review of the current literature

INTRODUCTION

Alterations of verbalized thought occur frequently in psychotic disorders. We characterize linguistic findings in individuals with schizophrenia based on the current literature, including findings relevant for differential and early diagnosis.

METHODS

Review of literature published via PubMed search between January 2010 and May 2022.

RESULTS

A total of 143 articles were included. In persons with schizophrenia, language-related alterations can occur at all linguistic levels. Differentiating from findings in persons with affective disorders, typical symptoms in those with schizophrenia mainly include so-called "poverty of speech," reduced word and sentence production, impaired processing of complex syntax, pragmatic language deficits as well as reduced semantic verbal fluency. At the at-risk state, "poverty of content," pragmatic difficulties and reduced verbal fluency could be of predictive value.

DISCUSSION

The current results support multilevel alterations of the language system in persons with schizophrenia. Creative expressions of psychotic experiences are frequently found but are not in the focus of this review. Clinical examinations of linguistic alterations can support differential diagnostics and early detection. Computational methods (Natural Language Processing) may improve the precision of corresponding diagnostics. The relations between language-related and other symptoms can improve diagnostics.

Theory-Driven Analysis of Natural Language Processing Measures of Thought Disorder Using Generative Language Modeling

BACKGROUND

Natural language processing (NLP) holds promise to transform psychiatric research and practice. A pertinent example is the success of NLP in the automatic detection of speech disorganization in formal thought disorder (FTD). However, we lack an understanding of precisely what common NLP metrics measure and how they relate to theoretical accounts of FTD. We propose tackling these questions by using deep generative language models to simulate FTD-like narratives by perturbing computational parameters instantiating theory-based mechanisms of FTD.

METHODS

We simulated FTD-like narratives using Generative-Pretrained-Transformer-2 by either increasing word selection stochasticity or limiting the model's memory span. We then examined the sensitivity of common NLP measures of derailment (semantic distance between consecutive words or sentences) and tangentiality (how quickly meaning drifts away from the topic) in detecting and dissociating the 2 underlying impairments.

RESULTS

Both parameters led to narratives characterized by greater semantic distance between consecutive sentences. Conversely, semantic distance between words was increased by increasing stochasticity, but decreased by limiting memory span. An NLP measure of tangentiality was uniquely predicted by limited memory span. The effects of limited memory span were nonmonotonic in that forgetting the global context resulted in sentences that were semantically closer to their local, intermediate context. Finally, different methods for encoding the meaning of sentences varied dramatically in performance.

CONCLUSIONS

This work validates a simulation-based approach as a valuable tool for hypothesis generation and mechanistic analysis of NLP markers in psychiatry. To facilitate dissemination of this approach, we accompany the paper with a hands-on Python tutorial.

Clinical and computational speech measures are associated with social cognition in schizophrenia spectrum disorders

In this study, we compared three domains of social cognition (emotion processing, mentalizing, and attribution bias) to clinical and computational language measures in 63 participants with schizophrenia spectrum disorders. Based on the active inference model for discourse, we hypothesized that emotion processing and mentalizing, but not attribution bias, would be related to language disturbances. Clinical ratings for speech disturbance assessed disorganized and underproductive dimensions. Computational features included speech graph metrics, use of modal verbs, use of first-person pronouns, cosine similarity of adjacent utterances, and measures of sentiment; these were represented by four principal components. We found that higher clinical ratings for disorganized speech were predicted by greater impairments in both emotion processing and mentalizing, and that these relationships remained significant when accounting for demographic variables, overall psychosis symptoms, and verbal ability. Similarly, a computational speech component reflecting insular speech was consistently predicted by impairment in emotion processing. There were notable trends for computational speech components reflecting underproductive speech and decreased content-rich speech predicting mentalizing ability. Exploratory longitudinal analyses in a small subset of participants (n = 17) found that improvements in both emotion processing and mentalizing predicted improvements in disorganized speech. Attribution bias did not demonstrate strong relationships with language measures. Altogether, our findings are consistent with the active inference model of discourse and suggest greater emphasis on treatments that target social cognitive and language systems.

Executively-mediated language skills are related to performance-based social functioning in the early psychosis spectrum

Social impairment is a core deficit in psychotic spectrum disorders (PSDs). Prior work shows that language abnormalities can predict psychosis onset and are related to social outcomes in PSDs. Few studies have investigated nuanced relationships between language/verbal abilities and social functioning in the early psychosis spectrum, including at-risk (schizotypy) and first episode of psychosis (FEP) individuals. This study aimed to examine the relationship to between language/verbal performance and performance-based and examiner-rated social functioning. We also aimed to replicate prior models that demonstrate neurocognition is related to social functioning through negative symptoms and social cognition. Low schizotypy (n = 42), high schizotypy (n = 44), and FEP (n = 15) participants completed a battery of language/verbal, social cognition, and social functioning measures. Regression analyses revealed that Proverb Test performance was uniquely and significantly associated with performance-based but not examiner-rated social functioning. Other language/verbal measures were not significantly related to social functioning. In mediational analyses, language/verbal performance was indirectly related to social functioning through negative traits, and also through social cognition. Findings extend support for negative symptom and social cognitive intervention in the early psychosis spectrum, and uniquely suggest that executively-mediated language skills may be an additional target to improve social functioning.

A detailed examination of pitch discrimination deficits associated with auditory verbal hallucinations in schizophrenia

Individuals with schizophrenia spectrum disorders (SSD) and a history of experiencing auditory verbal hallucinations (AVH) exhibit poor pitch discrimination relative to those with an SSD but no AVH history. The present study extended this research, asking if a lifetime history, and the current presence, of AVH exacerbated the pitch discrimination challenges that are seen in SSD. Participants completed a pitch discrimination task, where the tones presented differed in pitch by either 2 %, 5 %, 10 %, 25 % or 50 %. Pitch discrimination accuracy, sensitivity, reaction time (RT) and intra-individual RT variability (IIV) were examined in individuals with SSD and AVHs (AVH+; n = 46), or without AVHs (AVH-; n = 31), and healthy controls (HC; n = 131). Secondary analyses split the AVH+ group into state (i.e., actively experiencing AVH; n = 32) and trait hallucinators (i.e., a history of, but not actively experiencing, AVH; n = 16). Relative to HC, significantly poorer accuracy and sensitivity was detected in individuals with SSD at 2 % and 5 % pitch deviants, and in hallucinators at 10 %; however, no significant differences in accuracy, sensitivity, RT nor IIV were found between AVH+ and AVH- groups. No differences between state and trait hallucinators were observed. A general SSD deficit drove the current findings. The findings may inform future research into the auditory processing capabilities of AVH+ individuals.

Controllability of Functional Brain Networks and Its Clinical Significance in First-Episode Schizophrenia

BACKGROUND AND HYPOTHESIS

Disrupted control of brain state transitions may contribute to the diverse dysfunctions of cognition, emotion, and behavior that are fundamental to schizophrenia. Control theory provides the rationale for evaluating brain state transitions from a controllability perspective, which may help reveal the brain mechanism for clinical features such as cognitive control deficits associated with schizophrenia. We hypothesized that brain controllability would be altered in patients with schizophrenia, and that controllability of brain networks would be related to clinical symptomatology.

STUDY DESIGN

Controllability measurements of functional brain networks, including average controllability and modal controllability, were calculated and compared between 125 first-episode never-treated patients with schizophrenia and 133 healthy controls (HCs). Associations between controllability metrics and clinical symptoms were evaluated using sparse canonical correlation analysis.

STUDY RESULTS

Compared to HCs, patients showed significantly increased average controllability (PFDR = .023) and decreased modal controllability (PFDR = .023) in dorsal anterior cingulate cortex (dACC). General psychopathology symptoms and positive symptoms were positively correlated with average controllability in regions of default mode network and negatively associated with average controllability in regions of sensorimotor, dorsal attention, and frontoparietal networks.

CONCLUSIONS

Our findings suggest that altered controllability of functional activity in dACC may play a critical role in the pathophysiology of schizophrenia, consistent with the importance of this region in cognitive and brain state control operations. The demonstration of associations of functional controllability with psychosis symptoms suggests that the identified alterations in average controllability of brain function may contribute to the severity of acute psychotic illness in schizophrenia.

Language Network Dysfunction and Formal Thought Disorder in Schizophrenia

BACKGROUND

Pathophysiological inquiries into schizophrenia require a consideration of one of its most defining features: disorganization and impoverishment in verbal behavior. This feature, often captured using the term Formal Thought Disorder (FTD), still remains to be one of the most poorly understood and understudied dimensions of schizophrenia. In particular, the large-scale network level dysfunction that contributes to FTD remains obscure to date.

STUDY DESIGN

In this narrative review, we consider the various challenges that need to be addressed for us to move towards mapping FTD (construct) to a brain network level account (circuit).

STUDY RESULTS

The construct-to-circuit mapping goal is now becoming more plausible than it ever was, given the parallel advent of brain stimulation and the tools providing objective readouts of human speech. Notwithstanding this, several challenges remain to be overcome before we can decisively map the neural basis of FTD. We highlight the need for phenotype refinement, robust experimental designs, informed analytical choices, and present plausible targets in and beyond the Language Network for brain stimulation studies in FTD.

CONCLUSIONS

Developing a therapeutically beneficial pathophysiological model of FTD is a challenging endeavor, but holds the promise of improving interpersonal communication and reducing social disability in schizophrenia. Addressing the issues raised in this review will be a decisive step in this direction.

From communication dysfunction to treatment options in serious mental illness

The Commentary covers research focused on language dysfunction in schizophrenia, and more broadly in communication dysfunction in this disorder, which I have examined with a variety of both behavioral and imaging methodologies. It briefly outlines how further progress can be achieved in pursuing the goal of a comprehensive understanding of its underlying causes. Possible therapeutic approaches are also briefly discussed.

N-methyl-D-aspartate receptor antagonism impairs sensory gating in the auditory cortex in response to speech stimuli

Deficits in early auditory sensory processing in schizophrenia have been linked to N-methyl-D-aspartate receptor (NMDAR) hypofunction, but the role of NMDARs in aberrant auditory sensory gating (SG) in this disorder is unclear. This study, conducted in 22 healthy humans, examined the acute effects of a subanesthetic dose of the NMDAR antagonist ketamine on SG as measured electrophysiologically by suppression of the P50 event-related potential (ERP) to the second (S2) relative to the first (S1) of two closely paired (500 ms) identical speech stimuli. Ketamine induced impairment in SG indices at sensor (scalp)-level and at source-level in the auditory cortex (as assessed with eLORETA). Together with preliminary evidence of modest positive associations between impaired gating and dissociative symptoms elicited by ketamine, tentatively support a model of NMDAR hypofunction underlying disturbances in auditory SG in schizophrenia.

Disconnection from prediction: A systematic review on the role of right temporoparietal junction in aberrant predictive processing

The right temporoparietal junction (rTPJ) is a brain area that plays a critical role in a variety of cognitive functions. Although different theoretical proposals tried to explain the ubiquitous role of rTPJ, recent evidence suggests that rTPJ may be a fundamental cortical region involved in different kinds of predictions. This systematic review aims to better investigate the potential role of rTPJ under a predictive processing perspective, providing an overview of cognitive impairments in neurological patients as the consequence of structural or functional disconnections or damage of rTPJ. Results confirm the involvement of rTPJ across several tasks and neurological pathologies. RTPJ, via its connections with other brain networks, would integrate diverse information and update internal models of the world. Against traditional views, which tend to focus on distinct domains, we argue that the role of rTPJ can be parsimoniously interpreted as a key hub involved in domain-general predictions. This alternative account of rTPJ role in aberrant predictive processing opens different perspectives, stimulating new hypotheses in basic research and clinical contexts.

Construct validity for computational linguistic metrics in individuals at clinical risk for psychosis: Associations with clinical ratings

Language deficits are prevalent in psychotic illness, including its risk states, and are related to marked impairment in functioning. It is therefore important to characterize language impairment in the psychosis spectrum in order to develop potential preventive interventions. Natural language processing (NLP) metrics of semantic coherence and syntactic complexity have been used to discriminate schizophrenia patients from healthy controls (HC) and predict psychosis onset in individuals at clinical high-risk (CHR) for psychosis. To date, no studies have yet examined the construct validity of key NLP features with respect to clinical ratings of thought disorder in a CHR cohort. Herein we test the association of key NLP metrics of coherence and complexity with ratings of positive and negative thought disorder, respectively, in 60 CHR individuals, using Andreasen's Scale of Assessment of Thought, Language and Communication (TLC) Scale to measure of positive and negative thought disorder. As hypothesized, in CHR individuals, the NLP metric of semantic coherence was significantly correlated with positive thought disorder severity and the NLP metrics of complexity (sentence length and determiner use) were correlated with negative thought disorder severity. The finding of construct validity supports the premise that NLP analytics, at least in respect to core features of reduction of coherence and complexity, are capturing clinically relevant language disturbances in risk states for psychosis. Further psychometric study is required, in respect to reliability and other forms of validity.

Meta-analysis of human prediction error for incentives, perception, cognition, and action

Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, there is still much to learn. Here, we leverage the wealth of human PE data acquired in the functional neuroimaging setting in service of a deeper understanding, using an MKDA (multi-level kernel-based density) meta-analysis. Studies were identified with Google Scholar, and we included studies with healthy adult participants that reported activation coordinates corresponding to PEs published between 1999-2018. Across 264 PE studies that have focused on reward, punishment, action, cognition, and perception, consistent with domain-general theoretical models of prediction error we found midbrain PE signals during cognitive and reward learning tasks, and an insula PE signal for perceptual, social, cognitive, and reward prediction errors. There was evidence for domain-specific error signals--in the visual hierarchy during visual perception, and the dorsomedial prefrontal cortex during social inference. We assessed bias following prior neuroimaging meta-analyses and used family-wise error correction for multiple comparisons. This organization of computation by region will be invaluable in building and testing mechanistic models of cognitive function and dysfunction in machines, humans, and other animals. Limitations include small sample sizes and ROI masking in some included studies, which we addressed by weighting each study by sample size, and directly comparing whole brain vs. ROI-based results.

We both say tomato: Intact lexical alignment in schizophrenia and bipolar disorder

In people with schizophrenia and related disorders, impairments in communication and social functioning can negatively impact social interactions and quality of life. In the present study, we investigated the cognitive basis of a specific aspect of linguistic communication-lexical alignment-in people with schizophrenia and bipolar disorder. We probed lexical alignment as participants played a collaborative picture-naming game with the experimenter, in which the two players alternated between naming a dual-name picture (e.g., rabbit/bunny) and listening to their partner name a picture. We found evidence of lexical alignment in all three groups, with no differences between the patient groups and the controls. We argue that these typical patterns of lexical alignment in patients were supported by preserved-and in some cases increased-bottom-up mechanisms, which balanced out impairments in top-down perspective-taking.

The neural hierarchy of consciousness

The chief undertaking in the studies of consciousness is that of unravelling "the minimal set of neural processes that are together sufficient for the conscious experience of a particular content - the neural correlates of consciousness". To this day, this crusade remains at an impasse, with a clash of two main theories: consciousness may arise either in a graded and cortically-localised fashion, or in an all-or-none and widespread one. In spite of the long-lasting theoretical debates, neurophysiological theories of consciousness have been mostly dissociated from them. Herein, a theoretical review will be put forth with the aim to change that. In its first half, we will cover the hard available evidence on the neurophysiology of consciousness, whereas in its second half we will weave a series of considerations on both theories and substantiate a novel take on conscious awareness: the levels of processing approach, partitioning the conscious architecture into lower- and higher-order, graded and nonlinear.

Imprecise Predictive Coding Is at the Core of Classical Schizophrenia

Current diagnostic criteria for schizophrenia place emphasis on delusions and hallucinations, whereas the classical descriptions of schizophrenia by Kraepelin and Bleuler emphasized disorganization and impoverishment of mental activity. Despite the availability of antipsychotic medication for treating delusions and hallucinations, many patients continue to experience persisting disability. Improving treatment requires a better understanding of the processes leading to persisting disability. We recently introduced the term classical schizophrenia to describe cases with disorganized and impoverished mental activity, cognitive impairment and predisposition to persisting disability. Recent evidence reveals that a polygenic score indicating risk for schizophrenia predicts severity of the features of classical schizophrenia: disorganization, and to a lesser extent, impoverishment of mental activity and cognitive impairment. Current understanding of brain function attributes a cardinal role to predictive coding: the process of generating models of the world that are successively updated in light of confirmation or contradiction by subsequent sensory information. It has been proposed that abnormalities of these predictive processes account for delusions and hallucinations. Here we examine the evidence provided by electrophysiology and fMRI indicating that imprecise predictive coding is the core pathological process in classical schizophrenia, accounting for disorganization, psychomotor poverty and cognitive impairment. Functional imaging reveals aberrant brain activity at network hubs engaged during encoding of predictions. We discuss the possibility that frequent prediction errors might promote excess release of the neurotransmitter, dopamine, thereby accounting for the occurrence of episodes of florid psychotic symptoms including delusions and hallucinations in classical schizophrenia. While the predictive coding hypotheses partially accounts for the time-course of classical schizophrenia, the overall body of evidence indicates that environmental factors also contribute. We discuss the evidence that chronic inflammation is a mechanism that might link diverse genetic and environmental etiological factors, and contribute to the proposed imprecision of predictive coding.

A data-driven linguistic characterization of hallucinated voices in clinical and non-clinical voice-hearers

BACKGROUND

Auditory verbal hallucinations (AVHs) are heterogeneous regarding phenomenology and etiology. This has led to the proposal of AVHs subtypes. Distinguishing AVHs subtypes can inform AVHs neurocognitive models and also have implications for clinical practice. A scarcely studied source of heterogeneity relates to the AVHs linguistic characteristics. Therefore, in this study we investigate whether linguistic features distinguish AVHs subtypes, and whether linguistic AVH-subtypes are associated with phenomenology and voice-hearers' clinical status.

METHODS

Twenty-one clinical and nineteen non-clinical voice-hearers participated in this study. Participants were instructed to repeat verbatim their AVHs just after experiencing them. AVH-repetitions were audio-recorded and transcribed. AVHs phenomenology was assessed using the Auditory Hallucinations Rating Scale of the Psychotic Symptom Rating Scales. Hierarchical clustering analyses without a priori group dichotomization were performed using quantitative measures of sixteen linguistic features to distinguish sets of AVHs.

RESULTS

A two-AVHs-cluster solution best partitioned the data. AVHs-clusters significantly differed in linguistic features (p < .001); AVHs phenomenology (p < .001); and distribution of clinical voice-hearers (p < .001). The "expanded-AVHs" cluster was characterized by more determiners, more prepositions, longer utterances (all p < .01), and mainly contained non-clinical voice-hearers. The "compact-AVHs" cluster had fewer determiners and prepositions, shorter utterances (all p < .01), more negative content, higher degree of negativity (both p < .05), and predominantly came from clinical voice-hearers.

DISCUSSION

Two voice-speech clusters were recognized, differing in syntactic-grammatical complexity and negative phenomenology. Our results suggest clinical voice-hearers often hear negative, "compact-voices", understandable under Broca's right hemisphere homologue and memory-based mechanisms. Conversely, non-clinical voice-hearers experience "expanded-voices", better accounted by inner speech AVHs models.

Application of evoked response audiometry for specifying aberrant gamma oscillations in schizophrenia

Gamma oscillations probed using auditory steady-state response (ASSR) are promising clinical biomarkers that may give rise to novel therapeutic interventions for schizophrenia. Optimizing clinical settings for these biomarker-driven interventions will require a quick and easy assessment system for gamma oscillations in psychiatry. ASSR has been used in clinical otolaryngology for evoked response audiometry (ERA) in order to judge hearing loss by focusing on the phase-locked response detectability via an automated analysis system. Herein, a standard ERA system with 40- and 46-Hz ASSRs was applied to evaluate the brain pathophysiology of patients with schizophrenia. Both ASSRs in the ERA system showed excellent detectability regarding the phase-locked response in healthy subjects and sharply captured the deficits of the phase-locked response caused by aberrant gamma oscillations in individuals with schizophrenia. These findings demonstrate the capability of the ERA system to specify patients who have aberrant gamma oscillations. The ERA system may have a potential to serve as a real-world clinical medium for upcoming biomarker-driven therapeutics in psychiatry.

The Processing of Semantic Complexity and Cospeech Gestures in Schizophrenia: A Naturalistic, Multimodal fMRI Study

Schizophrenia is marked by aberrant processing of complex speech and gesture, which may contribute functionally to its impaired social communication. To date, extant neuroscientific studies of schizophrenia have largely investigated dysfunctional speech and gesture in isolation, and no prior research has examined how the two communicative channels may interact in more natural contexts. Here, we tested if patients with schizophrenia show aberrant neural processing of semantically complex story segments, and if speech-associated gestures (co-speech gestures) might modulate this effect. In a functional MRI study, we presented to 34 participants (16 patients and 18 matched-controls) an ecologically-valid retelling of a continuous story, performed via speech and spontaneous gestures. We split the entire story into ten-word segments, and measured the semantic complexity for each segment with idea density, a linguistic measure that is commonly used clinically to evaluate aberrant language dysfunction at the semantic level. Per segment, the presence of numbers of gestures varied (n = 0, 1, +2). Our results suggest that, in comparison to controls, patients showed reduced activation for more complex segments in the bilateral middle frontal and inferior parietal regions. Importantly, this neural aberrance was normalized in segments presented with gestures. Thus, for the first time with a naturalistic multimodal stimulation paradigm, we show that gestures reduced group differences when processing a natural story, probably by facilitating the processing of semantically complex segments of the story in schizophrenia.

Semantic priming and neurobiology in schizophrenia: A theoretical review

In this theoretical review we bridge the cognitive and neurobiological sciences to shed light on the neurocognitive foundations of the semantic priming effect in schizophrenia. We review and theoretically evaluate the neurotransmitter systems (dopaminergic, GABAergic and glutamatergic) and neurobiological underpinnings of behavioural and electrophysiological (N400) semantic priming in the pathology, and the main hypotheses on their geneses: a disinhibition of the semantic spread of activation, a disorganised semantic storage or noisy lexical-semantic associations, a psychomotor artefact, an artefact of relatedness proportions, or an inability to mobilise contextual information. We further assess the literature on the endophenotype of Formal Thought Disorder from multiple standpoints, ranging from neurophysiology to cognition: considerations are weaved on neuronal (PV basket cell, SST, VIP) and receptor deficits (DRD1, NMDA), neurotransmitter imbalances (dopamine), cortical and dopaminergic lateralisation, inter alia. In conclusion, we put forth novel postulates on the underlying causes of controlled hypopriming, automatic hyperpriming, N400 reversals (larger amplitudes for close associations), indirect versus direct hyperpriming, and the endophenotype of lexical-semantic disturbances in schizophrenia.

Central auditory processing deficits in schizophrenia: Effects of auditory-based cognitive training

BACKGROUND

Sensory processing abnormalities are common in schizophrenia (SZ) and impact everyday functions, such as speech perception in noisy environments. Auditory-based targeted cognitive training (TCT) is a "bottom up" cognitive remediation intervention designed to enhance the speed and accuracy of low-level auditory information processing. However, the effects of TCT on behavioral measures of central auditory processing (CAP) and the role of CAP function on verbal learning outcomes in SZ are unknown.

METHODS

SZ (n = 42) and healthy subjects (CTL; n = 18) underwent comprehensive clinical, neurocognitive, and auditory assessments, including tests of hearing sensitivity and speech recognition (Words-in-Noise (WIN), Quick Speech-in-Noise (SIN)). SZ patients were randomized to receive either treatment-as-usual (TAU); or 30-h of TCT + TAU using a stratified, parallel design. SZ patients repeated assessments ~10-12 weeks later.

RESULTS

Patients exhibited deficits in both WIN (p < 0.05, d = 0.50) and SIN (p < 0.01, d = 0.63). A treatment × time interaction on WIN (p < 0.05, d = 0.74), but not SIN discriminability, was seen in the TCT group relative to TAU. Specific enhancements in the 4-dB over background range drove gains in WIN performance. Moreover, SZ patients with greater CAP deficits experienced robust gains in verbal learning after 30-h of TCT relative to SZ patients without CAP impairment (p < 0.01, d = 1.28).

CONCLUSION

Findings demonstrate that intensive auditory training enhances the fidelity of auditory processing and perception, such that specific CAP deficits were 'normalized' and were predictive of gains in verbal learning after TCT. It is conceivable that patients with deficiencies in CAP measures may benefit most from TCT and other interventions targeting auditory dysfunction in SZ.

Study of differences between patients with schizophrenia and healthy people in semantic processing

Semantic processing is important in language comprehension and production, and context can facilitate understanding and accelerate processing speed by pre-activating semantically related words. There are many studies suggesting that patients with schizophrenia have inferior language ability. This study was aimed to examine the differences between patients with schizophrenia and healthy people in semantic processing with Chinese classifier-noun pairs rating tasks. Participants were required to finish rating tasks to judge acceptability of classifier-noun pairs. Also, the Positive and Negative Syndrome Scale (PANSS) was conducted in the schizophrenia group. According to results of variance analysis, schizophrenic patients' accuracy of judgment on the acceptability of classifier-noun pairs differed from the control group (F = 4.13, p < .05), and the contextual effect of classifier constraint could be observed in healthy people (F(1, 31) = 5.38, p < .05) but not in patients with schizophrenia (F(1, 25) = 3.55, p = .07), indicating that they failed to use the contextual information to facilitate language comprehension as healthy people. Stepwise linear regression analysis found that hostility, poor impulse control and suspiciousness/persecution and preoccupation in the PANSS may have contributed to the reduced sensitivity in the rating in patients (t = -2.38-3.80, p < .05).

The Imbalanced Plasticity Hypothesis of Schizophrenia-Related Psychosis: A Predictive Perspective

A considerable number of studies have attempted to account for the psychotic aspects of schizophrenia in terms of the influential predictive coding (PC) hypothesis. We argue that the prediction-oriented perspective on schizophrenia-related psychosis may benefit from a mechanistic model that: 1) gives due weight to the extent to which alterations in short- and long-term synaptic plasticity determine the degree and the direction of the functional disruption that occurs in psychosis; and 2) addresses the distinction between the two central syndromes of psychosis in schizophrenia: disorganization and reality-distortion. To accomplish these goals, we propose the Imbalanced Plasticity Hypothesis - IPH, and demonstrate that it: 1) accounts for commonalities and differences between disorganization and reality distortion in terms of excessive (hyper) or insufficient (hypo) neuroplasticity, respectively; 2) provides distinct predictions in the cognitive and electrophysiological domains; and 3) is able to reconcile conflicting PC-oriented accounts of psychosis.

Cognitive-perceptual and disorganized schizotypal traits are nonlinearly related to atypical semantic content on tasks of semantic fluency

Language deficits emerge early in the course of schizophrenia, yet research findings in those at-risk for schizophrenia, such as those with schizotypy, are mixed. The purpose of the present study was to elucidate the relationship of language ability, measured via semantic fluency, to schizotypy, examining both linear and non-linear relations. Semantic fluency data from 295 individuals with varying amounts of schizotypal traits were analyzed utilizing traditional methods (i.e., counting words generated that fit a specific semantic category). The content of semantic fluency responses was also analyzed via a semantic infrequency score (i.e., how infrequent participant responses were relative to all responses generated for the category in the study sample) and a total semantic productivity score (i.e., how many unique words generated overall, including those that did not fit the semantic category). Using traditional methods of scoring, schizotypy was not related to semantic fluency. However, schizotypy was non-linearly related to semantic infrequency and productivity, reflecting atypical semantic activation and processing. In particular, cognitive-perceptual and disorganized, but not interpersonal, traits were related to semantic infrequency and productivity. Valuable content-based information is missed when only analyzing semantic fluency data via the traditional method in the schizophrenia spectrum population. Cognitive-perceptual and disorganized traits, attenuated thought disorder symptoms, evidence the strongest relationship to semantic fluency, further illustrating the link between language and schizophrenia symptoms along the schizophrenia spectrum.

Language Dysfunction in Schizophrenia: Assessing Neural Tracking to Characterize the Underlying Disorder(s)?

Deficits in language production and comprehension are characteristic of schizophrenia. To date, it remains unclear whether these deficits arise from dysfunctional linguistic knowledge, or dysfunctional predictions derived from the linguistic context. Alternatively, the deficits could be a result of dysfunctional neural tracking of auditory information resulting in decreased auditory information fidelity and even distorted information. Here, we discuss possible ways for clinical neuroscientists to employ neural tracking methodology to independently characterize deficiencies on the auditory-sensory and abstract linguistic levels. This might lead to a mechanistic understanding of the deficits underlying language related disorder(s) in schizophrenia. We propose to combine naturalistic stimulation, measures of speech-brain synchronization, and computational modeling of abstract linguistic knowledge and predictions. These independent but likely interacting assessments may be exploited for an objective and differential diagnosis of schizophrenia, as well as a better understanding of the disorder on the functional level-illustrating the potential of neural tracking methodology as translational tool in a range of psychotic populations.

Differences in fractal patterns and characteristic periodicities between word salads and normal sentences: Interference of meaning and sound

Fractal dimensions and characteristic periodicities were evaluated in normal sentences, computer-generated word salads, and word salads from schizophrenia patients, in both Japanese and English, using the random walk patterns of vowels.　In normal sentences, the walking curves were smooth with gentle undulations, whereas computer-generated word salads were rugged with mechanical repetitions, and word salads from patients with schizophrenia were unreasonably winding with meaningless repetitive patterns or even artistic cohesion. These tendencies were similar in both languages. Fractal dimensions between normal sentences and word salads of schizophrenia were significantly different in Japanese [1.19 ± 0.09 (n = 90) and 1.15 ± 0.08 (n = 45), respectively] and English [1.20 ± 0.08 (n = 91), and 1.16 ± 0.08 (n = 42)] (p < 0.05 for both). Differences in long-range (>10) periodicities between normal sentences and word salads from schizophrenia patients were predominantly observed at 25.6 (p < 0.01) in Japanese and 10.7 (p < 0.01) in English. The differences in fractal dimension and characteristic periodicities of relatively long-range (>10) presented here are sensitive to discriminate between schizophrenia and healthy mental state, and could be implemented in social robots to assess the mental state of people in care.

CDP-choline and galantamine, a personalized α7 nicotinic acetylcholine receptor targeted treatment for the modulation of speech MMN indexed deviance detection in healthy volunteers: a pilot study

RATIONALE

The combination of CDP-choline, an α7 nicotinic acetylcholine receptor (α7 nAChR) agonist, with galantamine, a positive allosteric modulator of nAChRs, is believed to counter the fast desensitization rate of the α7 nAChRs and may be of interest for schizophrenia (SCZ) patients. Beyond the positive and negative clinical symptoms, deficits in early auditory prediction-error processes are also observed in SCZ. Regularity violations activate these mechanisms that are indexed by electroencephalography-derived mismatch negativity (MMN) event-related potentials (ERPs) in response to auditory deviance.

OBJECTIVES/METHODS

This pilot study in thirty-three healthy humans assessed the effects of an optimized α7 nAChR strategy combining CDP-choline (500 mg) with galantamine (16 mg) on speech-elicited MMN amplitude and latency measures. The randomized, double-blinded, placebo-controlled, and counterbalanced design with a baseline stratification method allowed for assessment of individual response differences.

RESULTS

Increases in MMN generation mediated by the acute CDP-choline/galantamine treatment in individuals with low baseline MMN amplitude for frequency, intensity, duration, and vowel deviants were revealed.

CONCLUSIONS

These results, observed primarily at temporal recording sites overlying the auditory cortex, implicate α7 nAChRs in the enhancement of speech deviance detection and warrant further examination with respect to dysfunctional auditory deviance processing in individuals with SCZ.

Language as a biomarker for psychosis: A natural language processing approach

Human ratings of conceptual disorganization, poverty of content, referential cohesion and illogical thinking have been shown to predict psychosis onset in prospective clinical high risk (CHR) cohort studies. The potential value of linguistic biomarkers has been significantly magnified, however, by recent advances in natural language processing (NLP) and machine learning (ML). Such methodologies allow for the rapid and objective measurement of language features, many of which are not easily recognized by human raters. Here we review the key findings on language production disturbance in psychosis. We also describe recent advances in the computational methods used to analyze language data, including methods for the automatic measurement of discourse coherence, syntactic complexity, poverty of content, referential coherence, and metaphorical language. Linguistic biomarkers of psychosis risk are now undergoing cross-validation, with attention to harmonization of methods. Future directions in extended CHR networks include studies of sources of variance, and combination with other promising biomarkers of psychosis risk, such as cognitive and sensory processing impairments likely to be related to language. Implications for the broader study of social communication, including reciprocal prosody, face expression and gesture, are discussed.

Impairments in Probabilistic Prediction and Bayesian Learning Can Explain Reduced Neural Semantic Priming in Schizophrenia

It has been proposed that abnormalities in probabilistic prediction and dynamic belief updating explain the multiple features of schizophrenia. Here, we used electroencephalography (EEG) to ask whether these abnormalities can account for the well-established reduction in semantic priming observed in schizophrenia under nonautomatic conditions. We isolated predictive contributions to the neural semantic priming effect by manipulating the prime's predictive validity and minimizing retroactive semantic matching mechanisms. We additionally examined the link between prediction and learning using a Bayesian model that probed dynamic belief updating as participants adapted to the increase in predictive validity. We found that patients were less likely than healthy controls to use the prime to predictively facilitate semantic processing on the target, resulting in a reduced N400 effect. Moreover, the trial-by-trial output of our Bayesian computational model explained between-group differences in trial-by-trial N400 amplitudes as participants transitioned from conditions of lower to higher predictive validity. These findings suggest that, compared with healthy controls, people with schizophrenia are less able to mobilize predictive mechanisms to facilitate processing at the earliest stages of accessing the meanings of incoming words. This deficit may be linked to a failure to adapt to changes in the broader environment. This reciprocal relationship between impairments in probabilistic prediction and Bayesian learning/adaptation may drive a vicious cycle that maintains cognitive disturbances in schizophrenia.

Linguistic alignment and theory of mind impairments in schizophrenia patients' dialogic interactions

BACKGROUND

Impairments of contextual processing and theory of mind (ToM) have both been offered as accounts of the deviant language characterising formal thought disorder (FTD) in schizophrenia. This study investigated these processes in patients' dialogue. We predicted that FTD patients would show a decrement in linguistic alignment, associated with impaired ToM in dialogue.

METHODS

Speech samples were elicited via participation in an interactive computer-based task and a semi-structured interview to assess contextual processing abilities and ToM skills in dialogue, respectively, and from an interactive card-sorting task to measure syntactic alignment. Degree of alignment in dialogue and the syntactic task, and evidence of ToM in (i) dialogue and (ii) a traditional ToM task were compared across schizophrenia patients with FTD (n = 21), non-FTD patients (n = 22) and healthy controls (n = 21).

RESULTS

FTD patients showed less alignment than the other two groups in dialogue, and than healthy controls on the syntactic task. FTD patients showed poorer performance on the ToM task than the other two groups, but only compared to the healthy controls in dialogue. The FTD group's degree of alignment in dialogue was correlated with ToM performance in dialogue but not with the traditional ToM task or with syntactic alignment.

CONCLUSIONS

In dialogue, FTD patients demonstrate an impairment in employing available contextual information to facilitate their own subsequent production, which is associated with a ToM deficit. These findings indicate that a contextual processing deficit impacts on exploiting representations via the production system impoverishing the ability to make predictions about upcoming utterances in dialogue.

Auditory processing disorder may be present in schizophrenia and it is highly correlated with formal thought disorder

The present study investigates the presence of Auditory Processing Disorder (APD) in schizophrenia and its association with symptomatology, especially Formal Thought Disorder (FTD). 50 patients with schizophrenia and 25 matched healthy controls completed a battery of three auditory processing tests. Positive and Negative Syndrome Scale (PANSS) and Thought, Language and Communication (TLC) scale were used to assess clinical symptoms. The patient group was divided into two subgroups, according to FTD severity. Auditory processing performance of the control group and the patient group was evaluated. Correlations between auditory processing scores and TLC scores, as well as auditory processing scores and PANSS scores were examined. Most of the patients, especially those with FTD, had auditory deficits that can be classified as APD. Patients showed impaired performance compared to controls in all tests. Total severity and specific factors of FTD, as well as other clinical symptoms and symptom categories were correlated with auditory processing performance. We provided evidence that APD may be present in schizophrenia and that FTD, as well as other clinical symptoms are associated with auditory processing deficits. There are important clinical implications for non-pharmacological interventions and early diagnosis of schizophrenia.

Linking language features to clinical symptoms and multimodal imaging in individuals at clinical high risk for psychosis

BACKGROUND

Abnormalities in the semantic and syntactic organization of speech have been reported in individuals at clinical high-risk (CHR) for psychosis. The current study seeks to examine whether such abnormalities are associated with changes in brain structure and functional connectivity in CHR individuals.

METHODS

Automated natural language processing analysis was applied to speech samples obtained from 46 CHR and 22 healthy individuals. Brain structural and resting-state functional imaging data were also acquired from all participants. Sparse canonical correlation analysis (sCCA) was used to ascertain patterns of covariation between linguistic features, clinical symptoms, and measures of brain morphometry and functional connectivity related to the language network.

RESULTS

In CHR individuals, we found a significant mode of covariation between linguistic and clinical features (r = 0.73; p = 0.003), with negative symptoms and bizarre thinking covarying mostly with measures of syntactic complexity. In the entire sample, separate sCCAs identified a single mode of covariation linking linguistic features with brain morphometry (r = 0.65; p = 0.05) and resting-state network connectivity (r = 0.63; p = 0.01). In both models, semantic and syntactic features covaried with brain structural and functional connectivity measures of the language network. However, the contribution of diagnosis to both models was negligible.

CONCLUSIONS

Syntactic complexity appeared sensitive to prodromal symptoms in CHR individuals while the patterns of brain-language covariation seemed preserved. Further studies in larger samples are required to establish the reproducibility of these findings.

Using Language Processing and Speech Analysis for the Identification of Psychosis and Other Disorders

Increasingly, data-driven methods have been implemented to understand psychopathology. Language is the main source of information in psychiatry and represents "big data" at the level of the individual. Language and behavior are amenable to computational natural language processing (NLP) analytics, which may help operationalize the mental status examination. In this review, we highlight the application of NLP to schizophrenia and its risk states as an exemplar of its use, operationalizing tangential and concrete speech as reductions in semantic coherence and syntactic complexity, respectively. Other clinical applications are reviewed, including forecasting suicide risk and detecting intoxication. Challenges and future directions are discussed, including biomarker development, harmonization, and application of NLP more broadly to behavior, including intonation/prosody, facial expression and gesture, and the integration of these in dyads and during discourse. Similar NLP analytics can also be applied beyond humans to behavioral motifs across species, important for modeling psychopathology in animal models. Finally, clinical neuroscience can inform the development of artificial intelligence.

Shaping perceptual learning of synthetic speech through feedback

Listeners exposed to accented speech must adjust how they map between acoustic features and lexical representations such as phonetic categories. A robust form of this adaptive perceptual learning is learning to perceive synthetic speech where the connections between acoustic features and phonetic categories must be updated. Both implicit learning through mere exposure and explicit learning through directed feedback have previously been shown to produce this type of adaptive learning. The present study crosses implicit exposure and explicit feedback with the presence or absence of a written identification task. We show that simple exposure produces some learning, but explicit feedback produces substantially stronger learning, whereas requiring written identification did not measurably affect learning. These results suggest that explicit feedback guides learning of new mappings between acoustic patterns and known phonetic categories. We discuss mechanisms that may support learning via implicit exposure.

Negative and disorganized symptoms mediate the relationship between verbal learning and global functioning in adolescents with early-onset psychosis

Neurocognitive deficits are associated with impaired global functioning and psychotic symptoms. However, whether symptoms can mediate the relationship between neurocognition and global functioning in adolescent psychosis is unclear. Here, we investigated if symptoms assessed with the Positive And Negative Syndrome Scale (PANSS), mediated the relationship between neurocognitive performance and global functioning in adolescents with non-affective early-onset psychotic disorders (EOP). Sixty-one adolescent EOP patients (age 12-18 years) from 2 Norwegian clinical cohorts were included. Linear regression models were applied to investigate associations between neurocognitive domains from the MATRICS Consensus Cognitive Battery (MCCB) and global functioning. PANSS symptoms were analyzed using the Wallwork/Fortgang five-factor model. Using the INDIRECT macro for SPSS, mediation effects were tested using bootstrapping with 95% bias corrected confidence intervals. Verbal learning was positively associated with global functioning (P < 0.001) and negatively associated with the disorganized symptom factor (P = 0.002), controlling for age, sex and cohort. Testing of indirect effects, controlling for age, sex and cohort, showed that the Negative (point estimate = 1.56, 95% CI 0.22, 3.47) and Disorganized (point estimate = 1.24, 95% CI 0.05, 3.69) symptom factors significantly mediated the relationship between verbal learning and global functioning. We found that verbal learning, negative and disorganized symptoms influenced global functioning in adolescents with EOP, while reality-distorted positive symptoms did not. These results suggest that assessing these domains in EOP is helpful for planning treatment and rehabilitation programs focusing on functional outcome.

Social Cognition Analyzer Application-A New Method for the Analysis of Social Cognition in Patients Diagnosed With Schizophrenia

Introduction: Because of the importance of the assessment of social cognitive impairments in schizophrenia in clinical settings, a new computer application called SCAN (Social Cognition Analyzer applicatioN) was developed. Our first aim was to examine if patients diagnosed with schizophrenia could be differentiated from healthy individuals based on the results of SCAN, taking into consideration both response rates and response times. Our second aim was to create Scanalizer, as part of SCAN, to produce social cognitive profiles of individual patients. Materials and Methods: 86 patients (SG) and 101 healthy participants (CG) were examined with SCAN. The domains were: ToM, irony, metaphor, emotion perception from prosody and social perception. SCAN displayed the tasks, recorded the answers and the response times. For the differentiation of the two groups a two-dimensional scatter plot was used. For the graphical presentation of the social cognitive profile of patients, the calculation of the distributions of CG's results was made with Kolmogorov-Smirnov Goodness-of-fit Test and with the sum of squared residuals (SSR). Results: We found that the SG's response rates were significantly lower and the SG's response times were significantly slower compared to the CG in every condition. With the two-dimensional comparison of the summary response rates and the summary response times of the participants, the SG could be differentiated from the CG and this differentiation worked irrespective of age and education. For the graphical representation of social cognitive functions of patients, distributions of the results of the CG were calculated. We found normal distributions in the response times of all conditions and in the response rates of the ToM condition. In the low-end tail of the irony condition, and in the metaphor, social perception and emotional prosody conditions, power-law distributions were found. We also found that the summary response rates of the lowest performing 10% of the CG was in the same range as the summary response rates of all examined patients. Discussion: Scanalizer enables clinicians to measure and analyse social cognitive profiles of patients diagnosed with schizophrenia. Moreover, SCAN could also be used to detect social cognitive disabilities of vulnerable individuals.

Blindness, Psychosis, and the Visual Construction of the World

The relationship between visual loss and psychosis is complex: congenital visual loss appears to be protective against the development of a psychotic disorder, particularly schizophrenia. In later life, however, visual deprivation or visual loss can give rise to hallucinosis, disorders of visual insight such as blindsight or Anton syndrome, or, in the context of neurodegenerative disorders, more complex psychotic presentations. We draw on a computational psychiatric approach to consider the foundational role of vision in the construction of representations of the world and the effects of visual loss at different developmental stages. Using a Bayesian prediction error minimization model, we describe how congenital visual loss may be protective against the development of the kind of computational deficits postulated to underlie schizophrenia, by increasing the precision (and consequent stability) of higher-level (including supramodal) priors, focusing on visual loss-induced changes in NMDA receptor structure and function as a possible mechanistic substrate. In simple terms, we argue that when people cannot see from birth, they rely more heavily on the context they extract from the other senses, and the resulting model of the world is more impervious to the false inferences, made in the face of inevitably noisy perceptual input, that characterize schizophrenia. We show how a Bayesian prediction error minimization framework can also explain the relationship between later visual loss and other psychotic symptoms, as well as the effects of visual deprivation and hallucinogenic drugs, and outline experimentally testable hypotheses generated by this approach.

Neural Signal to Violations of Abstract Rules Using Speech-Like Stimuli

As the evidence of predictive processes playing a role in a wide variety of cognitive domains increases, the brain as a predictive machine becomes a central idea in neuroscience. In auditory processing, a considerable amount of progress has been made using variations of the Oddball design, but most of the existing work seems restricted to predictions based on physical features or conditional rules linking successive stimuli. To characterize the predictive capacity of the brain to abstract rules, we present here two experiments that use speech-like stimuli to overcome limitations and avoid common confounds. Pseudowords were presented in isolation, intermixed with infrequent deviants that contained unexpected phoneme sequences. As hypothesized, the occurrence of unexpected sequences of phonemes reliably elicited an early prediction error signal. These prediction error signals do not seemed to be modulated by attentional manipulations due to different task instructions, suggesting that the predictions are deployed even when the task at hand does not volitionally involve error detection. In contrast, the amount of syllables congruent with a standard pseudoword presented before the point of deviance exerted a strong modulation. Prediction error's amplitude doubled when two congruent syllables were presented instead of one, despite keeping local transitional probabilities constant. This suggests that auditory predictions can be built integrating information beyond the immediate past. In sum, the results presented here further contribute to the understanding of the predictive capabilities of the human auditory system when facing complex stimuli and abstract rules.

Combining CDP-choline and galantamine: Effects of a selective α7 nicotinic acetylcholine receptor agonist strategy on P50 sensory gating of speech sounds in healthy volunteers

BACKGROUND

Schizophrenia (SCZ) patients and relatives have deficits in early cortical sensory gating (SG) typically measured by suppression of electroencephalography-derived P50 event-related potentials (ERPs) in a conditioning-testing (S₁-S₂) paradigm. Associated with alpha 7 nicotinic acetylcholine receptor (α7 nAChR) dysfunction and shown to be improved with nicotine and α7 nAChR agonists, SG has recently been shown to be improved in low P50 suppressing SCZ patients following acute CDP-choline treatment.

AIMS

This pilot study in healthy humans assessed the SG effects of an α7 nAChR strategy combining CDP-choline with galantamine, a positive allosteric modulator (PAM) of nAChRs, aimed at increasing and prolonging nicotinic receptor activity.

METHODS

The combined effect of CDP-choline (500 mg) and galantamine (16 mg) on speech P50 gating indices rP50 (S₂/S₁) and dP50 (S₁-S₂) was examined in 30 healthy participants stratified into low and high baseline P50 suppressors in a randomized, double-blind, placebo-controlled and counterbalanced design.

RESULTS

In low suppressors, CDP-choline/galantamine (vs. placebo) improved rP50 and dP50 gating, and reduced S₂P50 amplitudes. No P50 gating effects were observed in high suppressors; however, CDP-choline/galantamine (vs. placebo) increased their S₂P50 amplitudes.

CONCLUSION

Findings from this pilot study with CDP-choline/galantamine in a healthy, SCZ-like surrogate deficient gating sample are consistent with the association of α7 nAChR mechanisms in SG impairment in SCZ and support further research trials with CDP-choline and galantamine targeting sensory processes.