The language profile of formal thought disorder

Deciphering language disturbances in schizophrenia: A study using fine-tuned language models

This research presents two stable language metrics, namely Successful Prediction Rate (SPR) and Disfluency (DF), to objectively quantify the linguistic disturbances associated with schizophrenia. These novel language metrics can capture both off-topic responses and incoherence in patients' speech by modeling speech information and fine-tuning techniques. Additionally, these metrics exhibit cultural sensitivity while providing a more comprehensive evaluation of linguistic abnormalities in schizophrenia. This research fine-tuned the ELECTRA Pretrained Language Model on a 750 MB text corpus obtained from major Chinese mental health forums. The effectiveness of the fine-tuned language model is verified on a group comprising 38 individuals diagnosed with schizophrenia and 25 meticulously matched healthy controls. The study explores the association between the fine-tuned language model and the Positive and Negative Syndrome Scale (PANSS) items. The results demonstrate that SPR is higher in healthy controls, indicating better language understanding by the pre-trained language model. Conversely, DF is higher in individuals with schizophrenia, indicating more inconsistent language structure. The relationship between linguistic features and P2 (conceptual disorganization) reveals that patients with positive P2 exhibit lower SPR and higher DF. Binary logistic regression using the combined SPR and DF features achieves 84.5 % accuracy in classifying P2, exceeding the performance of traditional features by 20.5 %. Moreover, the proposed linguistic features outperform traditional linguistic features in discriminating FTD (formal thought disorder), as demonstrated by multivariate linear regression analysis.

A Methodological Approach to Quantifying Silent Pauses, Speech Rate, and Articulation Rate across Distinct Narrative Tasks: Introducing the Connected Speech Analysis Protocol (CSAP)

The examination of connected speech may serve as a valuable tool for exploring speech output in both healthy speakers and individuals with language disorders. Numerous studies incorporate various fluency and silence measures into their analyses to investigate speech output patterns in different populations, along with the underlying cognitive processes that occur while speaking. However, methodological inconsistencies across existing studies pose challenges in comparing their results. In the current study, we introduce CSAP (Connected Speech Analysis Protocol), which is a specific methodological approach to investigate fluency metrics, such as articulation rate and speech rate, as well as silence measures, including silent pauses' frequency and duration. We emphasize the importance of employing a comprehensive set of measures within a specific methodological framework to better understand speech output patterns. Additionally, we advocate for the use of distinct narrative tasks for a thorough investigation of speech output in different conditions. We provide an example of data on which we implement CSAP to showcase the proposed pipeline. In conclusion, CSAP offers a comprehensive framework for investigating speech output patterns, incorporating fluency metrics and silence measures in distinct narrative tasks, thus allowing a detailed quantification of connected speech in both healthy and clinical populations. We emphasize the significance of adopting a unified methodological approach in connected speech studies, enabling the integration of results for more robust and generalizable conclusions.

A new schizophrenia screening instrument based on evaluating the patient's writing

Formal Thought Disorder (FTD) is a defining feature of schizophrenia, which is often assessed through patients' speech. Meanwhile, the written language is less studied. The aim of the present study is to establish and validate a comprehensive clinical screening scale, capturing the full variety of empirical characteristics of writing in patients with schizophrenia. The 16-item Screening Instrument for Schizophrenic Features in Writing (SISFiW) is derived from detailed literature review and a "brainstorming" discussion on 30 samples written by patients with schizophrenia. One hundred and fifty-seven participants (114 patients with an ICD-10 diagnoses of schizophrenia; 43 healthy control subjects) were interviewed and symptoms assessed with the Positive and Negative Syndrome Scale (PANSS) and the Scale for the Assessment of Thought, Language, and Communication (TLC). Article samples written by each participant were rated with the SISFiW. Results demonstrated significant difference of the SISFiW-total between the patient group and healthy controls [(3.61 ± 1.72) vs. (0.49 ± 0.63), t = 16.64, p<0.001]. The inter-rater reliability (weighted kappa = 0.72) and the internal consistency (Cronbach's alpha coefficient = 0.613) were acceptable, but correlations with the criterion (PANSS and TLC) were unremarkable. The ROC analysis indicated a cutoff point at 2 with the maximal sensitivity (93.0 %)/specificity (93.0 %). Discriminant analysis of the SISFiW items yielded 8 classifiers that discriminated between the diagnostic groups at a perfect overall performance (with 90.4 % of original and 88.5 % cross-validated grouped cases classified correctly). This instrument appears to be practicable and reliable, with relatively robust discriminatory power, and may serve as a complementary tool to existing FTD rating scales.

Navigating the semantic space: Unraveling the structure of meaning in psychosis using different computational language models

Speech in psychosis has long been ascribed as involving 'loosening of associations'. We pursued the aim to elucidate its underlying cognitive mechanisms by analysing picture descriptions from 94 subjects (29 healthy controls, 18 participants at clinical high risk, 29 with first-episode psychosis, and 18 with chronic schizophrenia), using five language models with different computational architectures: FastText, which represents meaning non-contextually/statically; BERT, which represents contextual meaning sensitive to grammar and context; Infersent and SBERT, which provide sentential representations; and CLIP, which evaluates speech relative to a visual stimulus. These models were used to quantify semantic distances crossed between successive tokens/sentences, and semantic perplexity indicating unexpectedness in continuations. Results showed that, among patients, semantic similarity increased when measured with FastText, Infersent, and SBERT, while it decreased with CLIP and BERT. Higher perplexity was observed in first-episode psychosis. Static semantic measures were associated with clinically measured impoverishment of thought and referential semantic measures with disorganization. These patterns indicate a shrinking conceptual semantic space as represented by static language models, which co-occurs with a widening in the referential semantic space as represented by contextual models. This duality underlines the need to separate these two forms of meaning for understanding mechanisms involved in semantic change in psychosis.

Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study

BACKGROUND

Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level.

METHODS

Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up.

RESULTS

Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%.

CONCLUSIONS

We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

Trajectories through semantic spaces in schizophrenia and the relationship to ripple bursts

Human cognition is underpinned by structured internal representations that encode relationships between entities in the world (cognitive maps). Clinical features of schizophrenia-from thought disorder to delusions-are proposed to reflect disorganization in such conceptual representations. Schizophrenia is also linked to abnormalities in neural processes that support cognitive map representations, including hippocampal replay and high-frequency ripple oscillations. Here, we report a computational assay of semantically guided conceptual sampling and exploit this to test a hypothesis that people with schizophrenia (PScz) exhibit abnormalities in semantically guided cognition that relate to hippocampal replay and ripples. Fifty-two participants [26 PScz (13 unmedicated) and 26 age-, gender-, and intelligence quotient (IQ)-matched nonclinical controls] completed a category- and letter-verbal fluency task, followed by a magnetoencephalography (MEG) scan involving a separate sequence-learning task. We used a pretrained word embedding model of semantic similarity, coupled to a computational model of word selection, to quantify the degree to which each participant's verbal behavior was guided by semantic similarity. Using MEG, we indexed neural replay and ripple power in a post-task rest session. Across all participants, word selection was strongly influenced by semantic similarity. The strength of this influence showed sensitivity to task demands (category > letter fluency) and predicted performance. In line with our hypothesis, the influence of semantic similarity on behavior was reduced in schizophrenia relative to controls, predicted negative psychotic symptoms, and correlated with an MEG signature of hippocampal ripple power (but not replay). The findings bridge a gap between phenomenological and neurocomputational accounts of schizophrenia.

Grammatical impairment in schizophrenia: An exploratory study of the pronominal and sentential domains

Schizophrenia (SZ) is a severe mental disorder associated with a variety of linguistic deficits, and recently it has been suggested that these deficits are caused by an underlying impairment in the ability to build complex syntactic structures and complex semantic relations. Aiming at contributing to determining the specific linguistic profile of SZ, we investigated the usage of pronominal subjects and sentence types in two corpora of oral dream and waking reports produced by speakers with SZ and participants without SZ (NSZ), both native speakers of Brazilian Portuguese. Narratives of 40 adult participants (20 SZ, and 20 NSZ-sample 1), and narratives of 31 teenage participants (11 SZ undergoing first psychotic episode, and 20 NSZ-sample 2) were annotated and statistically analyzed. Overall, narratives of speakers with SZ presented significantly higher rates of matrix sentences, null pronouns-particularly null 3Person referential pronouns-and lower rates of non-anomalous truncated sentences. The high rate of matrix sentences correlated significantly with the total PANSS scores, suggesting an association between the overuse of simple sentences and SZ symptoms in general. In contrast, the high rate of null pronouns correlated significantly with positive PANSS scores, suggesting an association between the overuse of null pronominal forms and the positive symptoms of SZ. Finally, a cross-group analysis between samples 1 and 2 indicated a higher degree of grammatical impairment in speakers with multiple psychotic episodes. Altogether, the results strengthen the notion that deficits at the pronominal and sentential levels constitute a cross-cultural linguistic marker of SZ.

Referential noun phrases distribute differently in Turkish speakers with schizophrenia

In all human languages, noun phrases (NPs) (e.g., 'a field', 'the woman with a book') are used to identify entities in discourse. Previous evidence has shown that the spontaneous speech of patients with schizophrenia (Sz) shows differences in the distribution of grammatically different types of NPs, which are in part specific to patients with formal thought disorder (FTD). Here we sought to provide the first evidence of related grammatical effects in a non-Indo-European language. Results from a picture description task in a sample of 16 Turkish speakers with FTD (+FTD), 15 without FTD (-FTD), and 27 controls revealed that relative to controls, people with Sz over-produced NPs that are 'bare' (in the sense of lacking any grammatical items such as the or a in English). The +FTD group generally showed stronger effects than -FTD, and used more pronouns and less NPs co-referring with previously mentioned NPs. In addition, the dynamic distribution of NP types over narrative time showed an effect of increased mean distance between definite NPs in -FTD relative to controls. In +FTD but no other group there was an unexpected random distribution of indefinite DPs. Incidence rates of referential anomalies increased from controls to the -FTD and +FTD groups. These findings further confirm that Sz is manifest through specific linguistic effects in the referential structure of meaning as mediated by grammar. They provide a linguistic baseline for neurocognitive models of FTD and help to define appropriate targets for the automatic extraction of linguistic features to classify psychotic speech.

Syntactic complexity and diversity of spontaneous speech production in schizophrenia spectrum and major depressive disorders

Syntax, the grammatical structure of sentences, is a fundamental aspect of language. It remains debated whether reduced syntactic complexity is unique to schizophrenia spectrum disorder (SSD) or whether it is also present in major depressive disorder (MDD). Furthermore, the association of syntax (including syntactic complexity and diversity) with language-related neuropsychology and psychopathological symptoms across disorders remains unclear. Thirty-four SSD patients and thirty-eight MDD patients diagnosed according to DSM-IV-TR as well as forty healthy controls (HC) were included and tasked with describing four pictures from the Thematic Apperception Test. We analyzed the produced speech regarding its syntax delineating measures for syntactic complexity (the total number of main clauses embedding subordinate clauses) and diversity (number of different types of complex sentences). We performed cluster analysis to identify clusters based on syntax and investigated associations of syntactic, to language-related neuropsychological (verbal fluency and verbal episodic memory), and psychopathological measures (positive and negative formal thought disorder) using network analyses. Syntax in SSD was significantly reduced in comparison to MDD and HC, whereas the comparison of HC and MDD revealed no significant differences. No associations were present between speech measures and current medication, duration and severity of illness, age or sex; the single association accounted for was education. A cluster analysis resulted in four clusters with different degrees of syntax across diagnoses. Subjects with less syntax exhibited pronounced positive and negative symptoms and displayed poorer performance in executive functioning, global functioning, and verbal episodic memory. All cluster-based networks indicated varying degrees of domain-specific and cross-domain connections. Measures of syntactic complexity were closely related while syntactic diversity appeared to be a separate node outside of the syntactic network. Cross-domain associations were more salient in more complex syntactic production.

Linguistic markers of psychosis in Mandarin Chinese: Relations to theory of mind

Disorganized and impoverished language is a key feature of schizophrenia (Sz), but whether and which linguistic changes previously observed in Indo-European languages generalize to other languages remains unclear. Targeting Mandarin Chinese, we aimed to profile aspects of grammatical complexity that we hypothesized would be reduced in schizophrenia in a task of verbalizing social events. 51 individuals with Sz and 39 controls participated in the animated triangles task, a standardized measure of theory of mind (ToM), in which participants describe triangles moving in either a random or an 'intentional' condition. Results revealed that clauses embedded as arguments in other clauses were reduced in Sz, and that both groups produced such clauses and grammatical aspect more frequently in the intentional condition. ToM scores specifically correlated with production of embedded argument clauses. These results document grammatical impoverishment in Sz in Chinese across several structural domains, which in some of its specific aspects relate to mentalizing performance.

Coreference Delays in Psychotic Discourse: Widening the Temporal Window

BACKGROUND AND HYPOTHESIS

Any form of coherent discourse depends on saying different things about the same entities at different times. Such recurrent references to the same entity need to predictably happen within certain temporal windows. We hypothesized that a failure of control over reference in speakers with schizophrenia (Sz) would become manifest through dynamic temporal measures.

STUDY DESIGN

Conversational speech with a mean of 909.2 words (SD: 178.4) from 20 Chilean Spanish speakers with chronic Sz, 20 speakers at clinical high risk (CHR), and 20 controls were collected. Using directed speech graphs with referential noun phrases (NPs) as nodes, we studied deviances in the topology and temporal distribution of such NPs and of the entities they denote over narrative time.

STUDY RESULTS

The Sz group had a larger density of NPs (number of NPs divided by total words) relative to both controls and CHR. This related to topological measures of distance between recurrent entities, which revealed that the Sz group produced more recurrences, as well as greater topological distances between them, relative to controls. A logistic regression using five topological measures showed that Sz and controls can be distinguished with 84.2% accuracy.

CONCLUSIONS

This pattern indicates a widening of the temporal window in which entities are maintained in discourse and co-referenced in it. It substantiates and extends earlier evidence for deficits in the cognitive control over linguistic reference in psychotic discourse and informs both neurocognitive models of language in Sz and machine learning-based linguistic classifiers of psychotic speech.

Language Analytics for Assessment of Mental Health Status and Functional Competency

BACKGROUND AND HYPOTHESIS

Automated language analysis is becoming an increasingly popular tool in clinical research involving individuals with mental health disorders. Previous work has largely focused on using high-dimensional language features to develop diagnostic and prognostic models, but less work has been done to use linguistic output to assess downstream functional outcomes, which is critically important for clinical care. In this work, we study the relationship between automated language composites and clinical variables that characterize mental health status and functional competency using predictive modeling.

STUDY DESIGN

Conversational transcripts were collected from a social skills assessment of individuals with schizophrenia (n = 141), bipolar disorder (n = 140), and healthy controls (n = 22). A set of composite language features based on a theoretical framework of speech production were extracted from each transcript and predictive models were trained. The prediction targets included clinical variables for assessment of mental health status and social and functional competency. All models were validated on a held-out test sample not accessible to the model designer.

STUDY RESULTS

Our models predicted the neurocognitive composite with Pearson correlation PCC = 0.674; PANSS-positive with PCC = 0.509; PANSS-negative with PCC = 0.767; social skills composite with PCC = 0.785; functional competency composite with PCC = 0.616. Language features related to volition, affect, semantic coherence, appropriateness of response, and lexical diversity were useful for prediction of clinical variables.

CONCLUSIONS

Language samples provide useful information for the prediction of a variety of clinical variables that characterize mental health status and functional competency.

Syntactic Network Analysis in Schizophrenia-Spectrum Disorders

BACKGROUND

Language anomalies are a hallmark feature of schizophrenia-spectrum disorders (SSD). Here, we used network analysis to examine possible differences in syntactic relations between patients with SSD and healthy controls. Moreover, we assessed their relationship with sociodemographic factors, psychotic symptoms, and cognitive functioning, and we evaluated whether the quantification of syntactic network measures has diagnostic value.

STUDY DESIGN

Using a semi-structured interview, we collected speech samples from 63 patients with SSD and 63 controls. Per sentence, a syntactic representation (ie, parse tree) was obtained and used as input for network analysis. The resulting syntactic networks were analyzed for 11 local and global network measures, which were compared between groups using multivariate analysis of covariance, considering the effects of age, sex, and education.

RESULTS

Patients with SSD and controls significantly differed on most syntactic network measures. Sex had a significant effect on syntactic measures, and there was a significant interaction between sex and group, as the anomalies in syntactic relations were most pronounced in women with SSD. Syntactic measures were correlated with negative symptoms (Positive and Negative Syndrome Scale) and cognition (Brief Assessment of Cognition in Schizophrenia). A random forest classifier based on the best set of network features distinguished patients from controls with 74% cross-validated accuracy.

CONCLUSIONS

Examining syntactic relations from a network perspective revealed robust differences between patients with SSD and healthy controls, especially in women. Our results support the validity of linguistic network analysis in SSD and have the potential to be used in combination with other automated language measures as a marker for SSD.

Automated measures of speech content and speech organization in schizophrenia: Test-retest reliability and generalizability across demographic variables

Technological advances in artificial intelligence and natural language processing have increased efficiency of assessing speech content and speech organization in schizophrenia. Despite these developments, there has been little focus on the psychometrics of these approaches. Using two common assessments, the current study addressed this gap by: 1) measuring test-retest reliability; and 2) assessing whether speech content and/or speech organization generalize across demographics. To test these aims, we examined psychometric properties of the Linguistic Inquiry Word Count (LIWC), a speech content measure, and the Coh-Metrix, a speech organization measure. Across baseline to six month (n = 101) and baseline to one year (n = 47) narrative speech samples, we generally observed fair reliability for speech content measures and fair to good reliability for speech organization measures. Regarding demographics, multiple speech indices varied by race, income, and education. The lack of excellent reliability scores for speech indices holds important implications for examining speech variables in clinical trials and highlights the dynamic nature of speech. This work illustrates the importance of designing speech content and speech organization measures with external validity across demographic factors. Future studies examining speech in schizophrenia should account for potential biases against demographic groups introduced by linguistic analysis tools.

Semantic coherence markers: The contribution of perplexity metrics

Devising automatic tools to assist specialists in the early detection of mental disturbances and psychotic disorders is to date a challenging scientific problem and a practically relevant activity. In this work we explore how language models (that are probability distributions over text sequences) can be employed to analyze language and discriminate between mentally impaired and healthy subjects. We have preliminarily explored whether perplexity can be considered a reliable metrics to characterize an individual's language. Perplexity was originally conceived as an information-theoretic measure to assess how much a given language model is suited to predict a text sequence or, equivalently, how much a word sequence fits into a specific language model. We carried out an extensive experimentation with healthy subjects, and employed language models as diverse as N-grams - from 2-grams to 5-grams - and GPT-2, a transformer-based language model. Our experiments show that irrespective of the complexity of the employed language model, perplexity scores are stable and sufficiently consistent for analyzing the language of individual subjects, and at the same time sensitive enough to capture differences due to linguistic registers adopted by the same speaker, e.g., in interviews and political rallies. A second array of experiments was designed to investigate whether perplexity scores may be used to discriminate between the transcripts of healthy subjects and subjects suffering from Alzheimer Disease (AD). Our best performing models achieved full accuracy and F-score (1.00 in both precision/specificity and recall/sensitivity) in categorizing subjects from both the AD class, and control subjects. These results suggest that perplexity can be a valuable analytical metrics with potential application to supporting early diagnosis of symptoms of mental disorders.

Agency of Subjects and Eye Movements in Schizophrenia Spectrum Disorders

People with schizophrenia spectrum disorders (SSD) show anomalies in language processing with respect to "who is doing what" in an action. This linguistic behavior is suggestive of an atypical representation of the formal concepts of "Agent" in the lexical representation of a verb, i.e., its thematic grid. To test this hypothesis, we administered a silent-reading task with sentences including a semantic violation of the animacy trait of the grammatical subject to 30 people with SSD and 30 healthy control participants (HCs). When the anomalous grammatical subject was the Agent of the event, a significant increase of Gaze Duration was observed in HCs, but not in SSDs. Conversely, when the anomalous subject was a Theme, SSDs displayed an increased probability of go-back movements, unlike HCs. These results are suggestive of a higher tolerability for anomalous Agents in SSD compared to the normal population. The fact that SSD participants did not show a similar tolerability for anomalous Themes rules out the issue of an attention deficit. We suggest that general communication abilities in SSD might benefit from explicit training on deep linguistic structures.

Thought disorder is correlated with atypical spoken binomial orderings

Thought disorder may be associated with subtle language abnormalities. Binomials are pairs of words of the same grammatical type that are joined by a conjunction that often have a preferred order (for example, “up and down” is more common than “down and up”). We analyzed speech transcripts from patients with first-episode psychosis and found that atypical ordering of binomial pairs was associated with thought disorder but not with other psychosis symptoms. These results illustrate the potential to generate objective, quantifiable measures of disorganized speech.

Processing of linguistic deixis in people with schizophrenia, with and without auditory verbal hallucinations

Auditory verbal hallucinations (AVH) are a key symptom of schizophrenia (SZ) defined by anomalous perception of speech. Anomalies of processing external speech stimuli have also been reported in people with AVH, but it is unexplored which specific dimensions of language are processed differently. Using a speech perception task (passive listening), we here targeted the processing of deixis, a key dimension of language governing the contextual anchoring of speech in interpersonal context. We designed naturalistic speech stimuli that were either non-personal and fact-reporting ('low-deixis' condition), or else involved rich deictic devices such as the grammatical first and second persons, direct questions, and vocatives ('high-deixis'). We asked whether neural correlates of deixis obtained with fMRI would distinguish patients with and without frequent hallucinations (AVH + vs AVH-) from controls and each other. Results showed that high-deixis relative to low-deixis was associated with clusters of increased activation in the bilateral middle temporal gyri extending into the temporal poles and the inferior parietal cortex, in all groups. The AVH + and AVH- groups did not differ. When unifying them, the SZ group as a whole showed altered activity in the precuneus, midline regions and inferior parietal cortex. These results fail to confirm deictic processing anomalies specific to patients with AVH, but reveal such anomalies across SZ. Hypoactivation of this network may relate to a cognitive mechanism for attributing and anchoring thought and referential speech content in context.

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.

The role of white matter abnormality in the left anterior corona radiata: In relation to formal thought disorder in patients with schizophrenia

White matter abnormality has been widely reported in patients with schizophrenia (Sz). However, few studies have focused on the relationship between the white matter deficit and formal thought disorder (FTD). Moreover, the role of genetic high risk in FTD-related white matter deficit remains unclear. The present study recruited 46 Sz patients, 18 unaffected first-degree relatives of Sz patients, and 29 healthy controls. There was a widespread fractional anisotropy (FA) reduction in Sz. In addition, reduced FA in the left anterior corona radiata was related to more severe FTD symptoms in Sz. However, the genetic high-risk group only showed lower mean FA in the left anterior limb of the internal capsule than healthy controls. Our findings suggest that abnormality in the left anterior corona radiata may only occur in Sz but not in the genetic high-risk group. Such an abnormality might be associated with the severity of FTD symptoms. Meanwhile, genetic vulnerability may contribute to the abnormality in the left anterior limb of the internal capsule. Better analytical methods are needed to validate our results.

Investigating the diagnostic utility of speech patterns in schizophrenia and their symptom associations

BACKGROUND

Speech disturbances are a recognised aspect of schizophrenia that may have potential utility as a diagnostic indicator. Recent advances in quantitative speech assessment methods have led to more reproducible and precise metrics making this possible. The current study sought firstly to characterise the speech profile of schizophrenia patients using quantitative speech measures, then examine the diagnostic utility of these measures and explore their relationship to symptoms.

METHODS

Speech recordings from 43 schizophrenia/schizoaffective disorder (SZ) patients and 46 healthy controls (HC) were obtained and transcribed. Cognitive and symptom measures were also administered.

RESULTS

Compared to HCs, SZ patients had higher incidences of aberrance across five types of quantitative speech variables: utterances, single words, time/speaking rate, turns and formulation errors, but not pauses. Based on two machine learning algorithms, 21 speech variables across the same five speech variable types (again not including pauses) were identified as significant classifiers for a schizophrenia diagnosis with 90-100% specificity and 80-90% sensitivity for both models. Selective relationships were also observed between these speech variables and only positive, disorganisation, excitement and formal thought disorder symptoms.

CONCLUSIONS

The findings support pervasive speech impairments in schizophrenia patients relative to HCs, and the potential diagnostic utility of these speech disturbances. Continued work is needed to build the evidence base for quantitative speech assessment as a future objective diagnostic tool for schizophrenia. It holds the promise of improved diagnostic accuracy leading to increased treatment efficacy and better patient outcomes.

Implications for Early Diagnosis and Treatment in Schizophrenia Due to Correlation between Auditory Perceptual Deficits and Cognitive Impairment

It is indicated that auditory perception deficits are present in schizophrenia and related to formal thought disorder. The purpose of the present study was to investigate the association of auditory deficits with cognitive impairment in schizophrenia. An experimental group of 50 schizophrenia patients completed a battery of auditory processing evaluation and a neuropsychological battery of tests. Correlations between neuropsychological battery scores and auditory processing scores were examined. Cognitive impairment was correlated with auditory processing deficits in schizophrenia patients. All neuropsychological test scores were significantly correlated with at least one auditory processing test score. Our findings support the coexistence of auditory processing disorder, severe cognitive impairment, and formal thought disorder in a subgroup of schizophrenia patients. This may have important implications in schizophrenia research, as well as in early diagnosis and nonpharmacological treatment of the disorder.

More than a biomarker: could language be a biosocial marker of psychosis?

Automated extraction of quantitative linguistic features has the potential to predict objectively the onset and progression of psychosis. These linguistic variables are often considered to be biomarkers, with a large emphasis placed on the pathological aberrations in the biological processes that underwrite the faculty of language in psychosis. This perspective offers a reminder that human language is primarily a social device that is biologically implemented. As such, linguistic aberrations in patients with psychosis reflect both social and biological processes affecting an individual. Failure to consider the sociolinguistic aspects of NLP measures will limit their usefulness as digital tools in clinical settings. In the context of psychosis, considering language as a biosocial marker could lead to less biased and more accessible tools for patient-specific predictions in the clinic.

Formal thought disorder in patients with first-episode schizophrenia: Results of a one-year follow-up study

Formal thought disorder (FTD) refers to abnormal speech patterns that can be characterized by deficiencies in thought organization and direction. The present study aimed to assess the factor structure of FTD and to examine its relationship with cognition and clinical features at first admission in patients with first-episode schizophrenia. We also examined the course of FTD during the twelve months after first admission. We assessed FTD using the alogia items of the Scale for the Assessment of Negative Symptoms and FTD items of the Scale for the Assessment of Positive Symptoms in 160 drug-naïve patients. A three-factor structure as a disorganization factor, poverty factor, and verbosity factor were found in principal component analysis. The poverty factor was correlated negatively with executive functions, attention, and global cognition. The poverty factor was also correlated with global functioning. Admission FTD factor scores were not related to global functioning and work/study status at one year. The positive-FTD score decreased from admission to the third month, but no change occurred from the third to the twelfth month. The negative-FTD score did not differ throughout the follow-up. Our findings showed that FTD had three factors. Each factor had a different relationship with cognition and functioning.

Acute conceptual disorganization in untreated first-episode psychosis: a combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum

BACKGROUND

Disorganized thinking is a core feature of acute psychotic episodes that is linked to social and vocational functioning. Several lines of evidence implicate disrupted cognitive control, excitatory overdrive and oxidative stress relating to the anterior cingulate cortex as mechanisms of conceptual disorganization (CD). We examined 3 candidate mechanistic markers related to CD in firstepisode psychosis: glutamate excess, cortical antioxidant (glutathione) status and the integrity of the cingulum bundle that connects regions implicated in cognitive control.

METHODS

We used fractional anisotropy maps from 7 T diffusion-weighted imaging to investigate the bilateral cingulum based on a probabilistic white matter atlas. We compared high CD, low CD and healthy control groups and performed probabilistic fibre tracking from the identified clusters (regions of interest within the cingulum) to the rest of the brain. We quantified glutamate and glutathione using magnetic resonance spectroscopy (MRS) in the dorsal anterior cingulate cortex.

RESULTS

We found a significant fractional anisotropy reduction in a cluster in the left cingulum in the high CD group compared to the low CD group (Cohen's d = 1.39; p < 0.001) and controls (Cohen's d = 0.86; p = 0.009). Glutamate levels did not vary among groups, but glutathione levels were higher in the high CD group than in the low CD group. We also found higher glutathione related to lower fractional anisotropy in the cingulum cluster in the high CD group.

LIMITATIONS

The MRS measures of glutamine were highly uncertain, and MRS was acquired from a single voxel only.

CONCLUSION

Acute CD relates to indicators of oxidative stress, as well as reduced white matter integrity of the cingulum, but not to MRI-based glutamatergic excess. We propose that both oxidative imbalance and structural dysconnectivity underlie acute disorganization.

Facilitative Effects of Transcranial Direct Current Stimulation on Semantic Memory Examined by Text-Mining Analysis in Patients With Schizophrenia

Background: Beneficial effects of transcranial direct current stimulation (tDCS) are relevant to cognition and functional capacity, in addition to psychiatric symptoms in patients with schizophrenia. However, whether tDCS would improve higher-order cognition, e.g., semantic memory organization, has remained unclear. Recently, text-mining analyses have been shown to reveal semantic memory. The purpose of the current study was to determine whether tDCS would improve semantic memory, as evaluated by text-mining analyses of category fluency data, in patients with schizophrenia. Methods: Twenty-eight patients entered the study. Cognitive assessment including the category fluency task was conducted at baseline (before tDCS treatment) and 1 month after t administration of tDCS (2 mA × 20 min, twice per day) for 5 days, according to our previous study. The category fluency data were also obtained from 335 healthy control subjects. The verbal outputs (i.e., animal names) from the category fluency task were submitted to singular valued decomposition (SVD) analysis. Semantic memory structures were estimated by calculating inter-item cosines (i.e., similarities) among animal names frequently produced in the category fluency task. Data were analyzed longitudinally and cross-sectionally to compare the semantic structure within the patient group (i.e., baseline vs. follow-up) and between groups (patients vs. healthy controls). In the former, semantic associations for frequent items were compared in the form of cosine profiles, while in the latter, the difference in the magnitude of the correlations for inter-item cosines between healthy controls and patients (baseline, follow-up) was examined. Results: Cosine profiles in the patient group became more cluster-based (i.e., pet, carnivores, and herbivores) at follow-up compared to those at baseline, yielding higher cosines within subcategories. The correlational coefficient of inter-item cosines between healthy controls and patients was significantly greater at follow-up compared to baseline; semantic associations in patients approached the normality status after multi-session tDCS. Conclusions: To our knowledge, this is the first study to demonstrate the facilitative effect of tDCS on semantic memory organization in patients with schizophrenia. Text-mining analysis was indicated to effectively evaluate semantic memory structures in patients with psychiatric disorders.

Conceptual disorganization and redistribution of resting-state cortical hubs in untreated first-episode psychosis: A 7T study

Network-level dysconnectivity has been studied in positive and negative symptoms of schizophrenia. Conceptual disorganization (CD) is a symptom subtype that predicts impaired real-world functioning in psychosis. Systematic reviews have reported aberrant connectivity in formal thought disorder, a construct related to CD. However, no studies have investigated whole-brain functional correlates of CD in psychosis. We sought to investigate brain regions explaining the severity of CD in patients with first-episode psychosis (FEPs) compared with healthy controls (HCs). We computed whole-brain binarized degree centrality maps of 31 FEPs, 25 HCs, and characterized the patterns of network connectivity in the 2 groups. In FEPs, we related these findings to the severity of CD. We also studied the effect of positive and negative symptoms on altered network connectivity. Compared to HCs, reduced centrality of a right superior temporal gyrus (rSTG) cluster was observed in the FEPs. In patients exhibiting high CD, increased centrality of a medial superior parietal (mSPL) cluster was observed, compared to patients exhibiting low CD. This cluster was strongly correlated with CD scores but not with other symptom scores. Our observations are congruent with previous findings of reduced but not increased centrality. We observed increased centrality of mSPL suggesting that cortical reorganization occurs to provide alternate routes for information transfer. These findings provide insight into the underlying neural processes mediating the presentation of symptoms in untreated FEP. Longitudinal tracking of the symptom course will be useful to assess the mechanisms underlying these compensatory changes.

Small Words That Matter: Linguistic Style and Conceptual Disorganization in Untreated First-Episode Schizophrenia

This study aimed to shed light on the linguistic style affecting the communication discourse in first-episode schizophrenia (FES) by investigating the analytic thinking index in relation to clinical scores of conceptual and thought disorganization (Positive and Negative Syndrome Scale, PANSS-P2 and Thought and Language Index, TLI). Using robust Bayesian modeling, we report three major findings: (1) FES subjects showed reduced analytic thinking, exhibiting a less categorical linguistic style than healthy control (HC) subjects (Bayes factor, BF10 > 1000), despite using the same proportion of function and content words as HCs; (2) the lower the analytic thinking score, the higher the symptoms scores of conceptual disorganization (PANSS-P2, BF = 22.66) and global disorganization of thinking (TLI, BF10 = 112.73); (3) the linguistic style is a better predictor of conceptual disorganization than the cognitive measure of processing speed in schizophrenia (SZ). These findings provide an objectively detectable linguistic style with a focus on Natural Language Processing Analytics of transcribed speech samples of patients with SZ that require no clinical judgment. These findings also offer a crucial insight into the primacy of linguistic structural disruption in clinically ascertained disorganized thinking in SZ. Our work contributes to an emerging body of literature on the psychopathology of SZ using a first-order lexeme-level analysis and a hypothesis-driven approach. At a utilitarian level, this has implications for improving educational and social outcomes in patients with SZ.

Theory of Mind, Executive Functions, and Syntax in Bilingual Children with Autism Spectrum Disorder

Impairments in Theory of Mind (ToM) are a core feature of Autism Spectrum Disorder (ASD). ToM may be enhanced by various factors, including bilingualism, executive functions (EF), and complex syntax. This work investigates the language-cognition interface in ASD by exploring whether ToM can be enhanced by bilingualism, whether such ToM boosts would be due to EF or syntax, and whether routes to mentalizing would differ between bilinguals and monolinguals on the spectrum. Twenty-seven monolingual Greek-speaking and twenty-nine bilingual Albanian-Greek children with ASD were tested on ToM reasoning in verbal and low-verbal ToM tasks, an executive function 2-back task, and a sentence repetition task. Results revealed that bilingual children with ASD performed better than monolinguals with ASD in the low-verbal ToM and the 2-back tasks. In the sentence repetition task, bilinguals scored higher than monolinguals in complex sentences, and specifically in adverbials and relatives. Regarding the relations between ToM, EF, and sentence repetition, the monolingual group’s performance in the verbal ToM tasks was associated with complement syntax, whereas, for the bilingual children with ASD, performance in both verbal and low-verbal ToM tasks was associated with EF and adverbial clause repetition. The overall pattern of results suggests that mentalizing may follow distinct pathways across the two groups.

Language disturbances in schizophrenia: the relation with antipsychotic medication

Language disturbances are key aberrations in schizophrenia. Little is known about the influence of antipsychotic medication on these symptoms. Using computational language methods, this study evaluated the impact of high versus low dopamine D2 receptor (D2R) occupancy antipsychotics on language disturbances in 41 patients with schizophrenia, relative to 40 healthy controls. Patients with high versus low D2R occupancy antipsychotics differed by total number of words and type-token ratio, suggesting medication effects. Both patient groups differed from the healthy controls on percentage of time speaking and clauses per utterance, suggesting illness effects. Overall, more severe negative language disturbances (i.e. slower articulation rate, increased pausing, and shorter utterances) were seen in the patients that used high D2R occupancy antipsychotics, while less prominent disturbances were seen in low D2R occupancy patients. Language analyses successfully predicted drug type (sensitivity = 80.0%, specificity = 76.5%). Several language disturbances were more related to drug type and dose, than to other psychotic symptoms, suggesting that language disturbances may be aggravated by high D2R antipsychotics. This negative impact of high D2R occupancy drugs may have clinical implications, as impaired language production predicts functional outcome and degrades the quality of life.

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.

Quantifying the Uncertainty of Parameters Measured in Spontaneous Speech of Speakers With Dementia

Purpose Corpus analyses of spontaneous language fragments of varying length provide useful insights in the language change caused by brain damage, such as caused by some forms of dementia. Sample size is an important experimental parameter to consider when designing spontaneous language analyses studies. Sample length influences the confidence levels of analyses. Machine learning approaches often favor to use as much language as available, whereas language evaluation in a clinical setting is often based on truncated samples to minimize annotation labor and to limit any discomfort for participants. This article investigates, using Bayesian estimation of machine learned models, what the ideal text length should be to minimize model uncertainty. Method We use the Stanford parser to extract linguistic variables and train a statistic model to distinguish samples by speakers with no brain damage from samples by speakers with probable Alzheimer's disease. We compare the results to previously published models that used CLAN for linguistic analysis. Results The uncertainty around six individual variables and its relation to sample length are reported. The same model with linguistic variables that is used in all three experiments can predict group membership better than a model without them. One variable (concept density) is more informative when measured using the Stanford tools than when measured using CLAN. Conclusion For our corpus of German speech, the optimal sample length is found to be around 700 words long. Longer samples do not provide more information.

Anomalies in language as a biomarker for schizophrenia

PURPOSE OF REVIEW

After more than a century of neuroscience research, reproducible, clinically relevant biomarkers for schizophrenia have not yet been established. This article reviews current advances in evaluating the use of language as a diagnostic or prognostic tool in schizophrenia.

RECENT FINDINGS

The development of computational linguistic tools to quantify language disturbances is rapidly gaining ground in the field of schizophrenia research. Current applications are the use of semantic space models and acoustic analyses focused on phonetic markers. These features are used in machine learning models to distinguish patients with schizophrenia from healthy controls or to predict conversion to psychosis in high-risk groups, reaching accuracy scores (generally ranging from 80 to 90%) that exceed clinical raters. Other potential applications for a language biomarker in schizophrenia are monitoring of side effects, differential diagnostics and relapse prevention.

SUMMARY

Language disturbances are a key feature of schizophrenia. Although in its early stages, the emerging field of research focused on computational linguistics suggests an important role for language analyses in the diagnosis and prognosis of schizophrenia. Spoken language as a biomarker for schizophrenia has important advantages because it can be objectively and reproducibly quantified. Furthermore, language analyses are low-cost, time efficient and noninvasive in nature.

Language in schizophrenia and aphasia: the relationship with non-verbal cognition and thought disorder

Objective: To determine the relationship between language abnormalities and broader cognitive impairment and thought disorder by examining language and cognition in schizophrenia and aphasia (a primary language disorder).Methods: Cognitive and linguistic profiles were measured with a battery of standardised tests, and compared in a clinical population of n = 50 (n = 30 with schizophrenia and n = 20 with aphasia) and n = 61 non-clinical comparisons (n = 45 healthy controls and n = 16 non-affected first-degree relatives of patients with schizophrenia).Results: Both clinical groups showed linguistic deficits. Verbal impairment was more severe in participants with aphasia, whereas non-verbal performance was more affected in participants with schizophrenia. In schizophrenia, but not in aphasia, verbal and non-verbal performance were associated. Formal thought disorder was associated with impairment in executive function and in grammatical, but not naming, tasks.Conclusion: While patients with schizophrenia and aphasia showed language impairments, the nature and cognitive basis of these impairments may be different; language performance disassociates from broader cognitive functioning in aphasia but may be an intrinsic expression of a broader cognitive impairment in schizophrenia. Thought disorder may represent a core malfunction of grammatical processing. Results suggests that communicative ability may be a valid target in cognitive remediation strategies in schizophrenia.

Non-literal understanding and psychosis: Metaphor comprehension in individuals with a diagnosis of schizophrenia

Previous studies suggest that understanding of non-literal expressions, and in particular metaphors, can be impaired in people with schizophrenia; although it is not clear why. We explored metaphor comprehension capacity using a novel picture selection paradigm; we compared task performance between people with schizophrenia and healthy comparator subjects and we further examined the relationships between the ability to interpret figurative expressions non-literally and performance on a number of other cognitive tasks. Eye-tracking was used to examine task strategy. We showed that even when IQ, years of education, and capacities for theory of mind and associative learning are factored in as covariates, patients are significantly more likely to interpret metaphorical expressions literally, despite eye-tracking findings suggesting that patients are following the same interpretation strategy as healthy controls. Inhibitory control deficits are likely to be one of multiple factors contributing to the poorer performance of our schizophrenia group on the metaphor trials of the picture selection task.

A machine learning approach to predicting psychosis using semantic density and latent content analysis

Subtle features in people’s everyday language may harbor the signs of future mental illness. Machine learning offers an approach for the rapid and accurate extraction of these signs. Here we investigate two potential linguistic indicators of psychosis in 40 participants of the North American Prodrome Longitudinal Study. We demonstrate how the linguistic marker of semantic density can be obtained using the mathematical method of vector unpacking, a technique that decomposes the meaning of a sentence into its core ideas. We also demonstrate how the latent semantic content of an individual’s speech can be extracted by contrasting it with the contents of conversations generated on social media, here 30,000 contributors to Reddit. The results revealed that conversion to psychosis is signaled by low semantic density and talk about voices and sounds. When combined, these two variables were able to predict the conversion with 93% accuracy in the training and 90% accuracy in the holdout datasets. The results point to a larger project in which automated analyses of language are used to forecast a broad range of mental disorders well in advance of their emergence.

Disturbing the rhythm of thought: Speech pausing patterns in schizophrenia, with and without formal thought disorder

Everyday speech is produced with an intricate timing pattern and rhythm. Speech units follow each other with short interleaving pauses, which can be either bridged by fillers (erm, ah) or empty. Through their syntactic positions, pauses connect to the thoughts expressed. We investigated whether disturbances of thought in schizophrenia are manifest in patterns at this level of linguistic organization, whether these are seen in first degree relatives (FDR) and how specific they are to formal thought disorder (FTD). Spontaneous speech from 15 participants without FTD (SZ-FTD), 15 with FTD (SZ+FTD), 15 FDRs and 15 neurotypical controls (NC) was obtained from a comic strip retelling task and rated for pauses subclassified by syntactic position and duration. SZ-FTD produced significantly more unfilled pauses than NC in utterance-initial positions and before embedded clauses. Unfilled pauses occurring within clausal units did not distinguish any groups. SZ-FTD also differed from SZ+FTD in producing significantly more pauses before embedded clauses. SZ+FTD differed from NC and FDR only in producing longer utterance-initial pauses. FDRs produced significantly fewer fillers than NC. Results reveal that the temporal organization of speech is an important window on disturbances of the thought process and how these relate to language.

Comprehension of Embedded Clauses in Schizophrenia With and Without Formal Thought Disorder

Formal thought disorder (FTD) in schizophrenia (SZ) is clinically manifested primarily through language production, where linguistic studies have reported numerous anomalies including lesser use of embedded clauses. Here, we explored whether problems of language may extend to comprehension and clause embedding in particular. A sentence-picture matching task was designed with two conditions in which embedded clauses were presupposed as either true (factive) or not. Performance across these two conditions was compared in people with SZ and moderate-to-severe FTD (SZ + FTD), SZ with minimal FTD (SZ-FTD), first-degree relatives of people with SZ, and neurotypical controls. The SZ + FTD group performed significantly worse than all others in both conditions, and worse in the nonfactive than in the factive one. These results demonstrate language dysfunction in comprehension specific to FTD is a critical aspect of grammatical complexity and its associated meaning, which has been independently known to be cognitively significant as well.

The maturation of speech structure in psychosis is resistant to formal education

Discourse varies widely with age, level of education, and psychiatric state. Word graphs have been recently shown to provide behavioral markers of formal thought disorders in psychosis (e.g., disorganized flow of ideas) and to track literacy acquisition in children with typical development. Here we report that a graph-theoretical computational analysis of verbal reports from subjects spanning 6 decades of age and 2 decades of education reveals asymptotic changes over time that depend more on education than age. In typical subjects, short-range recurrence and lexical diversity stabilize after elementary school, whereas graph size and long-range recurrence only steady after high school. Short-range recurrence decreases towards random levels, while lexical diversity, long-range recurrence, and graph size increase away from near-randomness towards a plateau in educated adults. Subjects with psychosis do not show similar dynamics, presenting at adulthood a children-like discourse structure. Typical subjects increase the range of word recurrence over school years, but the same feature in subjects with psychosis resists education.