Prosody and lexical accuracy in flat affect schizophrenia

The contribution of prosody to machine classification of schizophrenia

We show how acoustic prosodic features, such as pitch and gaps, can be used computationally for detecting symptoms of schizophrenia from a single spoken response. We compare the individual contributions of acoustic and previously-employed text modalities to the algorithmic determination whether the speaker has schizophrenia. Our classification results clearly show that we can extract relevant acoustic features better than those textual ones. We find that, when combined with those acoustic features, textual features improve classification only slightly.

Prosody and schizophrenia. Objective acoustic measurements of monotonous and flat intonation in young Danish people with a schizophrenia diagnosis. A pilot study

PURPOSE

Patients with schizophrenia have a flat and monotonous intonation. The purpose of the study was to find the variables of flat speech that differed in patients from those in healthy controls in Danish.

MATERIALS AND METHODS

We compared drug-naïve schizophrenic patients 5 men, 13 women and 18 controls, aged 18-35 years, which had all grown up in Copenhagen speaking modern Danish standard (rigsdansk). We used two different tasks that lay different demands on the speaker to elicit spontaneous speech: a retelling of a film clip and telling a story from pictures in a book. A linguist used the computer program Praat to extract the phonetic linguistic parameters.

RESULTS

We found different results for the two elicitation tasks (Task 1: a retelling of a film clip, task 2: telling a story from pictures in a book). There was higher intensity variation in task one in controls and higher pitch variation in task two in controls. We found a difference in intensity with higher intensity variation in the stresses in the controls in task one and fewer syllables between each stress in the controls. We also found higher F1 variation in task one and two in the patient group and higher F2 variation in the control group in both tasks.

CONCLUSIONS

The results varied between patients and controls, but the demands also made a difference. Further research is needed to elucidate the possibilities of acoustic measures in diagnostics or linguistic treatment related to schizophrenia.

Markers of schizophrenia at the prosody/pragmatics interface. Evidence from corpora of spontaneous speech interactions

The speech of individuals with schizophrenia exhibits atypical prosody and pragmatic dysfunctions, producing monotony. The paper presents the outcomes of corpus-based research on the prosodic features of the pathology as they manifest in real-life spontaneous interactions. The research relies on a corpus of schizophrenic speech recorded during psychiatric interviews (CIPPS) compared to a sampling of non-pathological speech derived from the LABLITA corpus of spoken Italian, which has been selected according to comparability requirements. Corpora has been intensively analyzed in the Language into Act Theory (L-AcT) frame, which links prosodic cues and pragmatic values. A cluster of linguistic parameters marked by prosody has been considered: utterance boundaries, information structure, speech disfluency, and prosodic prominence. The speech flow of patients turns out to be organized into small chunks of information that are shorter and scarcely structured, with an atypical proportion of post-nuclear information units (Appendix). It is pervasively scattered with silences, especially with long pauses between utterances and long silences at turn-taking. Fluency is hindered by retracing phenomena that characterize complex information structures. The acoustic parameters that give rise to prosodic prominence (f0 mean, f0 standard deviation, spectral emphasis, and intensity variation) have been measured considering the pragmatic roles of the prosodic units, distinguishing prominences within the illocutionary units (Comment) from those characterizing Topic units. Patients show a flattening of the Comment-prominence, reflecting impairments in performing the illocutionary activity. Reduced values of spectral emphasis and intensity variation also suggest a lack of engagement in communication. Conversely, Topic-prominence shows higher values for f0 standard deviation and spectral emphasis, suggesting effort when defining the domain of relevance of the illocutionary force. When comparing Topic and Comment-prominences of patients, the former consistently exhibit higher values across all parameters. In contrast, the non-pathological group displays the opposite pattern.

Exploring the ability of vocal biomarkers in distinguishing depression from bipolar disorder, schizophrenia, and healthy controls

Background

Vocal features have been exploited to distinguish depression from healthy controls. While there have been some claims for success, the degree to which changes in vocal features are specific to depression has not been systematically studied. Hence, we examined the performances of vocal features in differentiating depression from bipolar disorder (BD), schizophrenia and healthy controls, as well as pairwise classifications for the three disorders.

Methods

We sampled 32 bipolar disorder patients, 106 depression patients, 114 healthy controls, and 20 schizophrenia patients. We extracted i-vectors from Mel-frequency cepstrum coefficients (MFCCs), and built logistic regression models with ridge regularization and 5-fold cross-validation on the training set, then applied models to the test set. There were seven classification tasks: any disorder versus healthy controls; depression versus healthy controls; BD versus healthy controls; schizophrenia versus healthy controls; depression versus BD; depression versus schizophrenia; BD versus schizophrenia.

Results

The area under curve (AUC) score for classifying depression and bipolar disorder was 0.5 (F-score = 0.44). For other comparisons, the AUC scores ranged from 0.75 to 0.92, and the F-scores ranged from 0.73 to 0.91. The model performance (AUC) of classifying depression and bipolar disorder was significantly worse than that of classifying bipolar disorder and schizophrenia (corrected p < 0.05). While there were no significant differences in the remaining pairwise comparisons of the 7 classification tasks.

Conclusion

Vocal features showed discriminatory potential in classifying depression and the healthy controls, as well as between depression and other mental disorders. Future research should systematically examine the mechanisms of voice features in distinguishing depression with other mental disorders and develop more sophisticated machine learning models so that voice can assist clinical diagnosis better.

A Narrative Review of Speech and EEG Features for Schizophrenia Detection: Progress and Challenges

Schizophrenia is a mental illness that affects an estimated 21 million people worldwide. The literature establishes that electroencephalography (EEG) is a well-implemented means of studying and diagnosing mental disorders. However, it is known that speech and language provide unique and essential information about human thought. Semantic and emotional content, semantic coherence, syntactic structure, and complexity can thus be combined in a machine learning process to detect schizophrenia. Several studies show that early identification is crucial to prevent the onset of illness or mitigate possible complications. Therefore, it is necessary to identify disease-specific biomarkers for an early diagnosis support system. This work contributes to improving our knowledge about schizophrenia and the features that can identify this mental illness via speech and EEG. The emotional state is a specific characteristic of schizophrenia that can be identified with speech emotion analysis. The most used features of speech found in the literature review are fundamental frequency (F0), intensity/loudness (I), frequency formants (F1, F2, and F3), Mel-frequency cepstral coefficients (MFCC's), the duration of pauses and sentences (SD), and the duration of silence between words. Combining at least two feature categories achieved high accuracy in the schizophrenia classification. Prosodic and spectral or temporal features achieved the highest accuracy. The work with higher accuracy used the prosodic and spectral features QEVA, SDVV, and SSDL, which were derived from the F0 and spectrogram. The emotional state can be identified with most of the features previously mentioned (F0, I, F1, F2, F3, MFCCs, and SD), linear prediction cepstral coefficients (LPCC), linear spectral features (LSF), and the pause rate. Using the event-related potentials (ERP), the most promissory features found in the literature are mismatch negativity (MMN), P2, P3, P50, N1, and N2. The EEG features with higher accuracy in schizophrenia classification subjects are the nonlinear features, such as Cx, HFD, and Lya.

Initial evidence of vowel space reduction in a subset of individuals with schizophrenia

OBJECTIVE

Acoustic phonetic measures have been found to correlate with negative symptoms of schizophrenia, thus offering a path toward quantitative measurement of such symptoms. These acoustic properties include F1 and F2 measurements (affected by tongue height and tongue forward/back position, respectively), which determine a general "vowel space." Among patients and controls, we consider two phonetic measures of vowel space: average Euclidean distance from a participant's mean F1 and mean F2, and density of vowels around one standard deviation of mean F1 and of F2.

METHODS

Structured and spontaneous speech of 148 participants (70 patients and 78 controls) was recorded and measured acoustically. We examined correlations between the phonetic measures of vowel space and ratings of aprosody obtained using two clinical research measures, the Scale for the Assessment of Negative Symptoms (SANS) and the Clinical Assessment Interview for Negative Symptoms (CAINS).

RESULTS

Vowel space measurements were significantly associated with patient/control status, attributed to a cluster of 13 patients whose phonetic values correspond to reduced vowel space as assessed by both phoenetic measures. No correlation was found between phonetic measures and relevant items and averages of ratings on the SANS and CAINS. Reduced vowel space appears to affect only a subset of patients with schizophrenia, potentially those on higher antipsychotic dosages.

CONCLUSIONS

Acoustic phonetic measures may be more sensitive measures of constricted vowel space than clinical research rating scales of aprosody or monotone speech. Replications are needed before further interpretation of this novel finding, including potential medication effects.

Vocal acoustic features may be objective biomarkers of negative symptoms in schizophrenia: A cross-sectional study

BACKGROUND

There are currently no objective biomarkers that allow the quantification of negative symptoms of schizophrenia. This study therefore explored the use of acoustic features in identifying the severity of negative symptoms in patients with schizophrenia.

METHODS

We recruited 79 inpatients who were diagnosed with schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (the schizophrenia group) at the Huilongguan Hospital in Beijing, China, and 79 healthy controls from the surrounding community (the control group). We assessed the clinical symptoms of the patients with schizophrenia using the Positive and Negative Syndrome Scale (PANSS) and the Brief Negative Symptom Scale (BNSS) and recorded the voice of each participant as they read emotionally positive, neutral, and negative texts. The Praat software was used to analyse and extract acoustic characteristics from the recordings, such as jitter, shimmer, and pitch. The acoustic differences between the two groups of participants and the relationship between acoustic characteristics and clinical symptoms in the patient group were analysed.

RESULTS

There were significant differences between the schizophrenia and control groups in pitch, voice breaks, jitter, shimmer, and the mean harmonics-to-noise ratio (p < 0.05). Jitter was negatively correlated with the blunted affect and alogia subscale scores of the BNSS, both in the positive and neutral emotion conditions, but the correlation disappeared in the negative emotion condition. However, shimmer exhibited a stable negative correlation with the blunted affect and alogia subscale scores of the BNSS in all three emotion conditions. A linear regression analysis showed that pitch, jitter, shimmer, and age were statistically significant predictors of BNSS subscale scores.

CONCLUSIONS

Acoustic emotional expression differs between patients with schizophrenia and healthy controls. Some acoustic characteristics are related to the severity of negative symptoms, regardless of semantic emotions, and may therefore be objective biomarkers of negative symptoms. A systematic method for assessing vocal acoustic characteristics could provide an accurate and feasible means of assessing negative symptoms in schizophrenia.

TWEET

Acoustic emotional expression differs between patients with schizophrenia and healthy controls. A systematic method for assessing vocal acoustics could provide an accurate and feasible means of assessing negative symptoms in schizophrenia.

Pleasant and unpleasant odor identification ability is associated with distinct dimensions of negative symptoms transdiagnostically in psychotic disorders

Negative symptoms are among the greatest sources of functional impairment for individuals with schizophrenia, yet their mechanisms remain poorly understood. Olfactory impairment is associated with negative symptoms. The processing of pleasant olfactory stimuli is subserved by reward-related neural circuitry while unpleasant olfactory processing is subserved by emotion-related neural circuitry, suggesting that these two odor dimensions may offer a window into differential mechanisms of negative symptoms. We examined whether pleasant and unpleasant odor identification bears differential relationships with avolition and inexpressivity dimensions of negative symptoms, whether these relationships are transdiagnostic, and whether pleasant and unpleasant odor processing also relate differently to other domains of functioning in a sample of individuals diagnosed with schizophrenia (N = 54), other psychotic disorders (N = 65), and never-psychotic adults (N = 160). Hierarchical regressions showed that pleasant odor identification was uniquely associated with avolition, while unpleasant odor identification was uniquely associated with inexpressivity. These relationships were largely transdiagnostic across groups. Additionally, pleasant and unpleasant odor identification displayed signs of specificity with other functional and cognitive measures. These results align with past work suggesting dissociable pathomechanisms of negative symptoms and provide a potential avenue for future work using valence-specific olfactory dysfunction as a semi-objective and low-cost marker for understanding and predicting the severity of specific negative symptom profiles.

Conversational metrics, psychopathological dimensions and self-disturbances in patients with schizophrenia

Difficulties in interpersonal communication, including conversational skill impairments, are core features of schizophrenia. However, very few studies have performed conversation analyses in a clinical population of schizophrenia patients. Here we investigate the conversational patterns of dialogues in schizophrenia patients to assess possible associations with symptom dimensions, subjective self-disturbances and social functioning. Thirty-five schizophrenia patients were administered the Positive and Negative Syndrome Scale (PANSS), the Clinical Language Disorder Rating Scale (CLANG), the Scale for the Assessment of Thought, Language and Communication (TLC), the Examination of Anomalous Self-Experience Scale (EASE), and the Social and Occupational Functioning Assessment Scale (SOFAS). Moreover, participants underwent a recorded semi-structured interview, to extract conversational variables. Conversational data were associated with negative symptoms and social functioning, but not with positive or disorganization symptoms. A significant positive correlation was found between "pause duration" and the EASE item "Spatialization of thought". The present study suggests an association between conversational patterns and negative symptom dimension of schizophrenia. Moreover, our findings evoke a relationship between the natural fluidity of conversation and of the natural unraveling of thoughts.

Schizophrenia identification for phonetic coherence using SVM and blur approaches

The diagnosis cycle of schizophrenia is long, there is no objective diagnostic basis. The over-energy entropy product of the speech fluency rectangular parameter is designed in the paper, the fuzzy clustering is used to double locate speech pause areas and to assist in the diagnosis of schizophrenia. The pause area of speech is located based on the low speech fluency and flat energy in schizophrenia patients, an extraction algorithm is given for speech fluency quantification parameters, support vector machine (SVM) classifier is used in the approach. The fluency acoustic features of speech are taken from 28 schizophrenia patients and 28 normal controls, these are used to verify the effect of the method in schizophrenia recognition, there is a correct rate of over 85% . The automatic schizophrenia identification based on energy entropy product and fuzzy clustering can provide objective, effective and non-invasive auxiliary for clinical diagnosis of schizophrenia.

Sch-net: a deep learning architecture for automatic detection of schizophrenia

BACKGROUND

Schizophrenia is a chronic and severe mental disease, which largely influences the daily life and work of patients. Clinically, schizophrenia with negative symptoms is usually misdiagnosed. The diagnosis is also dependent on the experience of clinicians. It is urgent to develop an objective and effective method to diagnose schizophrenia with negative symptoms. Recent studies had shown that impaired speech could be considered as an indicator to diagnose schizophrenia. The literature about schizophrenic speech detection was mainly based on feature engineering, in which effective feature extraction is difficult because of the variability of speech signals.

METHODS

This work designs a novel Sch-net neural network based on a convolutional neural network, which is the first work for end-to-end schizophrenic speech detection using deep learning techniques. The Sch-net adds two components, skip connections and convolutional block attention module (CBAM), to the convolutional backbone architecture. The skip connections enrich the information used for the classification by emerging low- and high-level features. The CBAM highlights the effective features by giving learnable weights. The proposed Sch-net combines the advantages of the two components, which can avoid the procedure of manual feature extraction and selection.

RESULTS

We validate our Sch-net through ablation experiments on a schizophrenic speech data set that contains 28 patients with schizophrenia and 28 healthy controls. The comparisons with the models based on feature engineering and deep neural networks are also conducted. The experimental results show that the Sch-net has a great performance on the schizophrenic speech detection task, which can achieve 97.68% accuracy on the schizophrenic speech data set. To further verify the generalization of our model, the Sch-net is tested on open access LANNA children speech database for specific language impairment detection. The results show that our model achieves 99.52% accuracy in classifying patients with SLI and healthy controls. Our code will be available at https://github.com/Scu-sen/Sch-net .

CONCLUSIONS

Extensive experiments show that the proposed Sch-net can provide aided information for the diagnosis of schizophrenia and specific language impairment.

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.

Using machine learning of computerized vocal expression to measure blunted vocal affect and alogia

Negative symptoms are a transdiagnostic feature of serious mental illness (SMI) that can be potentially “digitally phenotyped” using objective vocal analysis. In prior studies, vocal measures show low convergence with clinical ratings, potentially because analysis has used small, constrained acoustic feature sets. We sought to evaluate (1) whether clinically rated blunted vocal affect (BvA)/alogia could be accurately modelled using machine learning (ML) with a large feature set from two separate tasks (i.e., a 20-s “picture” and a 60-s “free-recall” task), (2) whether “Predicted” BvA/alogia (computed from the ML model) are associated with demographics, diagnosis, psychiatric symptoms, and cognitive/social functioning, and (3) which key vocal features are central to BvA/Alogia ratings. Accuracy was high (>90%) and was improved when computed separately by speaking task. ML scores were associated with poor cognitive performance and social functioning and were higher in patients with schizophrenia versus depression or mania diagnoses. However, the features identified as most predictive of BvA/Alogia were generally not considered critical to their operational definitions. Implications for validating and implementing digital phenotyping to reduce SMI burden are discussed.

Voice patterns in schizophrenia: A systematic review and Bayesian meta-analysis

Voice atypicalities have been a characteristic feature of schizophrenia since its first definitions. They are often associated with core negative symptoms such as flat affect and alogia, and with the social impairments seen in the disorder. This suggests that voice atypicalities may represent a marker of clinical features and social functioning in schizophrenia. We systematically reviewed and meta-analyzed the evidence for distinctive acoustic patterns in schizophrenia, as well as their relation to clinical features. We identified 46 articles, including 55 studies with a total of 1254 patients with schizophrenia and 699 healthy controls. Summary effect sizes (Hedges'g and Pearson's r) estimates were calculated using multilevel Bayesian modeling. We identified weak atypicalities in pitch variability (g = -0.55) related to flat affect, and stronger atypicalities in proportion of spoken time, speech rate, and pauses (g's between -0.75 and -1.89) related to alogia and flat affect. However, the effects were mostly modest (with the important exception of pause duration) compared to perceptual and clinical judgments, and characterized by large heterogeneity between studies. Moderator analyses revealed that tasks with a more demanding cognitive and social component showed larger effects both in contrasting patients and controls and in assessing symptomatology. In conclusion, studies of acoustic patterns are a promising but, yet unsystematic avenue for establishing markers of schizophrenia. We outline recommendations towards more cumulative, open, and theory-driven research.

Lexical analysis of emotional responses to "real-world" experiences in individuals with schizophrenia

Abnormalities in emotion perception, expression, and experience are considered a core component of schizophrenia. Previous laboratory studies have demonstrated that while individuals with schizophrenia report levels of positive emotions comparable to healthy individuals in response to positive stimuli, they also report co-occurring negative emotions in response to such stimuli. However, it is unknown whether this response pattern extends to "real world" naturalistic environments. To examine this question, we employed an experience sampling method (ESM) approach using mobile electronic devices to collect information up to 10 times/day over a two-day period from 53 individuals with schizophrenia and 19 non-clinical controls. As part of each experience sample, participants completed brief open-ended responses and answered questions about their emotional responses to three recent events (neutral, positive, and negative). Additionally, participants completed diagnostic and clinical measures. Lexical analyses were used to analyze ESM-based word production and characterize emotion word use. Compared to non-clinical controls, individuals with schizophrenia reported similar levels of positive emotion, but significantly higher negative emotion, which was associated with increased negative symptoms. The schizophrenia group used more anxiety words in response to negative and neutral events, and more anger words in response to positive events. Increased use of anger words was linked with elevations in positive symptoms as well as symptoms of depression, while use of sadness words was linked with anhedonia. Our findings support the co-activation of negative emotion hypothesis documented in laboratory settings and provide evidence of its ecological validity. Implications for functioning and future directions are discussed.

Speech Prosody as a Bridge Between Psychopathology and Linguistics: The Case of the Schizophrenia Spectrum

Patients with schizophrenia spectrum disorders experience severe difficulties in interpersonal communication, as described by traditional psychopathology and current research on social cognition. From a linguistic perspective, pragmatic abilities are crucial for successful communication. Empirical studies have shown that these abilities are significantly impaired in this group of patients. Prosody, the tone of voice with which words and sentences are pronounced, is one of the most important carriers of pragmatic meaning and can serve a range of functions from linguistic to emotional ones. Most of the existing literature on prosody of patients with schizophrenia spectrum disorders focuses on the expression of emotion, generally showing significant impairments. By contrast, the use of non-emotional prosody in these patients is scarcely investigated. In this paper, we first present a linguistic model to classify prosodic functions. Second, we discuss existing studies on the use of non-emotional prosody in these patients, providing an overview of the state of the art. Third, we delineate possible future lines of research in this field, also taking into account some classical psychopathological assumptions, for both diagnostic and therapeutic purposes.

Non-verbal speech cues as objective measures for negative symptoms in patients with schizophrenia

Negative symptoms in schizophrenia are associated with significant burden and possess little to no robust treatments in clinical practice today. One key obstacle impeding the development of better treatment methods is the lack of an objective measure. Since negative symptoms almost always adversely affect speech production in patients, speech dysfunction have been considered as a viable objective measure. However, researchers have mostly focused on the verbal aspects of speech, with scant attention to the non-verbal cues in speech. In this paper, we have explored non-verbal speech cues as objective measures of negative symptoms of schizophrenia. We collected an interview corpus of 54 subjects with schizophrenia and 26 healthy controls. In order to validate the non-verbal speech cues, we computed the correlation between these cues and the NSA-16 ratings assigned by expert clinicians. Significant correlations were obtained between these non-verbal speech cues and certain NSA indicators. For instance, the correlation between Turn Duration and Restricted Speech is -0.5, Response time and NSA Communication is 0.4, therefore indicating that poor communication is reflected in the objective measures, thus validating our claims. Moreover, certain NSA indices can be classified into observable and non-observable classes from the non-verbal speech cues by means of supervised classification methods. In particular the accuracy for Restricted speech quantity and Prolonged response time are 80% and 70% respectively. We were also able to classify healthy and patients using non-verbal speech features with 81.3% accuracy.

The aprosody of schizophrenia: Computationally derived acoustic phonetic underpinnings of monotone speech

OBJECTIVE

Acoustic phonetic methods are useful in examining some symptoms of schizophrenia; we used such methods to understand the underpinnings of aprosody. We hypothesized that, compared to controls and patients without clinically rated aprosody, patients with aprosody would exhibit reduced variability in: pitch (F0), jaw/mouth opening and tongue height (formant F1), tongue front/back position and/or lip rounding (formant F2), and intensity/loudness.

METHODS

Audiorecorded speech was obtained from 98 patients (including 25 with clinically rated aprosody and 29 without) and 102 unaffected controls using five tasks: one describing a drawing, two based on spontaneous speech elicited through a question (Tasks 2 and 3), and two based on reading prose excerpts (Tasks 4 and 5). We compared groups on variation in pitch (F0), formant F1 and F2, and intensity/loudness.

RESULTS

Regarding pitch variation, patients with aprosody differed significantly from controls in Task 5 in both unadjusted tests and those adjusted for sociodemographics. For the standard deviation (SD) of F1, no significant differences were found in adjusted tests. Regarding SD of F2, patients with aprosody had lower values than controls in Task 3, 4, and 5. For variation in intensity/loudness, patients with aprosody had lower values than patients without aprosody and controls across the five tasks.

CONCLUSIONS

Findings could represent a step toward developing new methods for measuring and tracking the severity of this specific negative symptom using acoustic phonetic parameters; such work is relevant to other psychiatric and neurological disorders.

Individual negative symptoms and domains - Relevance for assessment, pathomechanisms and treatment

The negative symptoms of schizophrenia can be divided into two domains. Avolition/apathy includes the individual symptoms of avolition, asociality and anhedonia. Diminished expression includes blunted affect and alogia. Until now, causes and treatment of negative symptoms have remained a major challenge, which is partially related to the focus on negative symptoms as a broad entity. Here, we propose that negative symptoms may become more tractable when the different domains and individual symptoms are taken into account. There is now increasing evidence that the relationship with clinical variables - in particular outcome - differs between the domains of avolition/apathy and diminished expression. Regarding models of negative symptom formation, those relevant to avolition/apathy are now converging on processes underlying goal-directed behavior and dysfunctions of the reward system. In contrast, models of the diminished expression domains are only beginning to emerge. The aim of this article is to review the specific clinical, behavioral and neural correlates of individual symptoms and domains as a better understanding of these areas may facilitate specific treatment approaches.

The current conceptualization of negative symptoms in schizophrenia

Negative symptoms have long been conceptualized as a core aspect of schizophrenia. They play a key role in the functional outcome of the disorder, and their management represents a significant unmet need. Improvements in definition, characterization, assessment instruments and experimental models are needed in order to foster research aimed at developing effective interventions. A consensus has recently been reached on the following aspects: a) five constructs should be considered as negative symptoms, i.e. blunted affect, alogia, anhedonia, asociality and avolition; b) for each construct, symptoms due to identifiable factors, such as medication effects, psychotic symptoms or depression, should be distinguished from those regarded as primary; c) the five constructs cluster in two factors, one including blunted affect and alogia and the other consisting of anhedonia, avolition and asociality. In this paper, for each construct, we report the current definition; highlight differences among the main assessment instruments; illustrate quantitative measures, if available, and their relationship with the evaluations based on rating scales; and describe correlates as well as experimental models. We conclude that: a) the assessment of the negative symptom dimension has recently improved, but even current expert consensus-based instruments diverge on several aspects; b) the use of objective measures might contribute to overcome uncertainties about the reliability of rating scales, but these measures require further investigation and validation; c) the boundaries with other illness components, in particular neurocognition and social cognition, are not well defined; and d) without further reducing the heterogeneity within the negative symptom dimension, attempts to develop successful interventions are likely to lead to great efforts paid back by small rewards.

The current conceptualization of negative symptoms in schizophrenia

Negative symptoms have long been conceptualized as a core aspect of schizophrenia. They play a key role in the functional outcome of the disorder, and their management represents a significant unmet need. Improvements in definition, characterization, assessment instruments and experimental models are needed in order to foster research aimed at developing effective interventions. A consensus has recently been reached on the following aspects: a) five constructs should be considered as negative symptoms, i.e. blunted affect, alogia, anhedonia, asociality and avolition; b) for each construct, symptoms due to identifiable factors, such as medication effects, psychotic symptoms or depression, should be distinguished from those regarded as primary; c) the five constructs cluster in two factors, one including blunted affect and alogia and the other consisting of anhedonia, avolition and asociality. In this paper, for each construct, we report the current definition; highlight differences among the main assessment instruments; illustrate quantitative measures, if available, and their relationship with the evaluations based on rating scales; and describe correlates as well as experimental models. We conclude that: a) the assessment of the negative symptom dimension has recently improved, but even current expert consensus-based instruments diverge on several aspects; b) the use of objective measures might contribute to overcome uncertainties about the reliability of rating scales, but these measures require further investigation and validation; c) the boundaries with other illness components, in particular neurocognition and social cognition, are not well defined; and d) without further reducing the heterogeneity within the negative symptom dimension, attempts to develop successful interventions are likely to lead to great efforts paid back by small rewards.

Can the Acoustic Analysis of Expressive Prosody Discriminate Schizophrenia?

Emotional states, attitudes and intentions are often conveyed by modulations in the tone of voice. Impaired recognition of emotions from a tone of voice (receptive prosody) has been described as characteristic symptoms of schizophrenia. However, the ability to express non-verbal information in speech (expressive prosody) has been understudied. This paper describes a useful technique for quantifying the degree of expressive prosody deficits in schizophrenia, using a semi-automatic method, and evaluates this method's ability to discriminate between patient and control groups. Forty-five medicated patients with a diagnosis of schizophrenia were matched with thirty-five healthy comparison subjects. Production of expressive prosodic speech was analyzed using variation in fundamental frequency (F0) measures on an emotionally neutral reading task. Results revealed that patients with schizophrenia exhibited significantly more pauses (p < .001), were slower (p < .001), and showed less pitch variability in speech (p < .05) and fewer variations in syllable timing (p < .001) than control subjects. These features have been associated with «flat» speech prosody. Signal processing algorithms applied to speech were shown to be capable of discriminating between patients and controls with an accuracy of 93.8%. These speech parameters may have a diagnostic and prognosis value and therefore could be used as a dependent measure in clinical trials.

Subtypes of anhedonia and facial electromyography response to negative affective pictures in non-psychiatric adults

INTRODUCTION

Flat/constricted affect and anhedonia are symptoms found in several psychiatric disorders such as depression and schizophrenia. However, there are very few studies on the relationships between specific anhedonia subtypes and objectively assessed flat affect, and it appears that none of the existing studies examined potential moderation by sex.

METHODS

Forty-seven undergraduate students (60% male) completed self-report questionnaires assessing three subtypes of anhedonia - non-social consummatory (CON) and anticipatory (ANT) anhedonia, and overall social anhedonia. Participants viewed 15 pictures (5 neutral and 10 negative) from the International Affective Picture System, whereas facial muscle reaction was recorded using electromyography (EMG).

RESULTS

Male participants reporting a greater level of overall social or non-social CON anhedonia showed a greater EMG activity increase in the corrugator supercilii muscle to negative (vs. neutral) pictures. In females, the relationship was only found with social anhedonia and was opposite in direction, as increased social anhedonia related to less EMG activity change in the corrugator muscle.

CONCLUSIONS

The relationship between anhedonia and flat affect varied as a function of sex and anhedonia subtype. These findings may help explain discrepancies in the sparse existing literature examining this relationship in psychiatric populations and have implications for assessment and treatment of these symptoms across psychiatric disorders.

Dissecting negative symptoms in schizophrenia: opportunities for translation into new treatments

Among the constellation of symptoms that characterize schizophrenia, negative symptoms have emerged as a critical feature linked to the functional impairment experienced by affected individuals. Despite advances in our understanding of the role of negative symptoms in the illness, effective treatments for these debilitating symptoms have remained elusive. In this review we explore the contemporary conceptualization of negative symptoms in schizophrenia, including the identification of two key subdomains of diminished expression and amotivation, and clarifications around hedonic capacity. We then explore strategies for clinical assessments of negative symptoms, followed by findings using objective paradigms for evaluating discrete aspects of these negative symptoms in clinical populations and animal models, both for symptoms of diminished expression and within the multifaceted motivation system. We conclude with a consideration of current strategies for drug development for these negative symptoms, the role of heterogeneity in the clinical presentation of symptoms in schizophrenia and opportunities for personalized assessment and treatment approaches, as well as a commentary on current clinical drug trial design and the role of environmental opportunities for novel treatments to effect change and improve outcomes for affected individuals.

What do we really know about blunted vocal affect and alogia? A meta-analysis of objective assessments

Deficits in nonverbal vocal expression (e.g., blunted vocal affect, alogia) are a hallmark of schizophrenia and are a focus of the Research Domain Criteria initiative from the National Institute of Mental Health. Results from studies using symptom rating scales suggest that these deficits are profound; on the order of four to six standard deviations. To complement this endeavor, we conducted a meta-analysis of studies employing objective analysis of natural speech in patients with schizophrenia and nonpsychiatric controls. Thirteen studies, collectively including 480 patients with schizophrenia and 326 nonpsychiatric controls, were identified. There was considerable variability across studies in which aspects of vocal communication were examined and in the magnitudes of deficit. Overall, speech production (reflecting alogia) was impaired at a large effects size level (d=-.80; k=13), whereas speech variability (reflecting blunted affect) was much more modest (d=-.36; k=2). Regarding the former, this was largely driven by measures of pause behavior, as opposed to other aspects of speech (e.g., number of words/utterances). On the other hand, ratings of negative symptoms across these studies suggested profound group differences (d=3.54; k=4). These data suggest that only certain aspects of vocal expression are affected in schizophrenia, and highlight major discrepancies between symptom rating and objective-based measures. The discussion centers on advancing objective analysis for understanding vocal expression in schizophrenia and for identifying and defining more homogenous patient subsets for study.

Stress reactivity of emotional and verbal speech content in schizophrenia

Speech fundamental frequencies (SFFs) are nonverbal sound frequencies that convey emotion in speech. The degree of SFF long-term averaged spectra (LTAS) convergence between conversants reflects aspects of conversant-reported quality of the interaction (e.g., emotional synchrony). This study investigated whether SFF LTAS convergence between inpatients diagnosed with schizophrenia (n = 20) and an interviewer was associated with severity of illness (SOI), formal speech disturbance (FSD), and stress reactivity of FSD. Participants provided speech samples describing stressful and nonstressful life experiences. In the stress condition, SFF LTAS was negatively correlated with SOI and FSD. Moreover, patients exhibiting stress reactivity of FSD also evidenced stress reactivity of SFF LTAS. These findings suggest that the emotional and verbal contents of speech are disrupted by stress in schizophrenia, and SOI is associated with FSD and reduced emotional communication during stressful conditions. The interaction between stress reactivity of FSD and SFF LTAS supports the construct validity of a reactivity dimension in schizophrenia.

Prosodic abnormalities in schizotypal personality disorder

OBJECTIVE

Patients with schizophrenia speak with blunted vocal affect but little is known regarding the prosody of persons with schizotypal personality disorder (SPD). This work examined expressive prosody in SPD, its relationship to brain structure, and outlined a framework for measuring elements of prosody in clinical populations.

METHODS

Twenty-eight antipsychotic-naïve SPD subjects were matched with 27 healthy comparison (HC) subjects. Subjects read aloud short sentences and responded to probes to record both predetermined and self-generated speech samples. Samples were analyzed acoustically (pause proportion, duration, attack, and pitch variability) and subjectively by raters (amount of pauses, degree of emotion portrayed, and how much they wanted to hear more from the subjects) on paragraph, sentence, word, word-fragment, and syllable levels. Alexithymia and ability to self-monitor behavior were compared between groups. The pars opercularis was manually traced on structural MRI data.

RESULTS

SPD subjects' speech had significantly more pauses, was slower, had less pitch variability, and expressed less emotion than HC subjects. Pitch variability correlated with socio-economic status achievement. There was no difference between groups in left or right pars opercularis volumes. A statistically significant correlation suggested that smaller left pars opercularis volumes in SPD subjects correlated with more pauses and less emotion. SPD subjects reported more alexithymia and difficulty self-monitoring their behavior compared with controls. In SPD subjects the high alexithymia correlated with raters not wanting to hear more from them and SPD subjects' inability to modulate their social behavior correlated with their having fewer friends. Thus, the SPD subjects exhibited insight.

CONCLUSIONS

SPD subjects displayed significant prosodic deficits that were measurable in speech samples as brief as a word-fragment. The determinants of these deficits are not known although these may include a dysfunctional pars opercularis. These data add to the nascent literature describing social cognition deficits in SPD.

Phonetic measures of reduced tongue movement correlate with negative symptom severity in hospitalized patients with first-episode schizophrenia-spectrum disorders

BACKGROUND

Aprosody, or flattened speech intonation, is a recognized negative symptom of schizophrenia, though it has rarely been studied from a linguistic/phonological perspective. To bring the latest advances in computational linguistics to the phenomenology of schizophrenia and related psychotic disorders, a clinical first-episode psychosis research team joined with a phonetics/computational linguistics team to conduct a preliminary, proof-of-concept study.

METHODS

Video recordings from a semi-structured clinical research interview were available from 47 first-episode psychosis patients. Audio tracks of the video recordings were extracted, and after review of quality, 25 recordings were available for phonetic analysis. These files were de-noised and a trained phonologist extracted a 1-minute sample of each patient's speech. WaveSurfer 1.8.5 was used to create, from each speech sample, a file of formant values (F0, F1, F2, where F0 is the fundamental frequency and F1 and F2 are resonance bands indicating the moment-by-moment shape of the oral cavity). Variability in these phonetic indices was correlated with severity of Positive and Negative Syndrome Scale negative symptom scores using Pearson correlations.

RESULTS

A measure of variability of tongue front-to-back position-the standard deviation of F2-was statistically significantly correlated with the severity of negative symptoms (r=-0.446, p=0.03).

CONCLUSION

This study demonstrates a statistically significant and meaningful correlation between negative symptom severity and phonetically measured reductions in tongue movements during speech in a sample of first-episode patients just initiating treatment. Further studies of negative symptoms, applying computational linguistics methods, are warranted.

Translating mouse vocalizations: prosody and frequency modulation

Mental illness can include impaired abilities to express emotions or respond to the emotions of others. Speech provides a mechanism for expressing emotions, by both what words are spoken and by the melody or intonation of speech (prosody). Through the perception of variations in prosody, an individual can detect changes in another's emotional state. Prosodic features of mouse ultrasonic vocalizations (USVs), indicated by changes in frequency and amplitude, also convey information. Dams retrieve pups that emit separation calls, females approach males emitting solicitous calls, and mice can become fearful of a cue associated with the vocalizations of a distressed conspecific. Because acoustic features of mouse USVs respond to drugs and genetic manipulations that influence reward circuits, USV analysis can be employed to examine how genes influence social motivation, affect regulation, and communication. The purpose of this review is to discuss how genetic and developmental factors influence aspects of the mouse vocal repertoire and how mice respond to the vocalizations of their conspecifics. To generate falsifiable hypotheses about the emotional content of particular calls, this review addresses USV analysis within the framework of affective neuroscience (e.g. measures of motivated behavior such as conditioned place preference tests, brain activity and systemic physiology). Suggested future studies include employment of an expanded array of physiological and statistical approaches to identify the salient acoustic features of mouse vocalizations. We are particularly interested in rearing environments that incorporate sufficient spatial and temporal complexity to familiarize developing mice with a broader array of affective states.

Acoustic and temporal analysis of speech: A potential biomarker for schizophrenia

Currently, there are no established objective biomarkers for the diagnosis or monitoring of schizophrenia. It has been previously reported that there are notable qualitative differences in the speech of schizophrenics. The objective of this study was to determine whether a quantitative acoustic and temporal analysis of speech may be a potential biomarker for schizophrenia. In this study, 39 schizophrenic patients and 18 controls were digitally recorded reading aloud an emotionally neutral text passage from a children's story. Temporal, energy and vocal pitch features were automatically extracted from the recordings. A classifier based on linear discriminant analysis was employed to differentiate between controls and schizophrenic subjects. Processing the recordings with the algorithm developed demonstrated that it is possible to differentiate schizophrenic patients and controls with a classification accuracy of 79.4% (specificity=83.6%, sensitivity=75.2%) based on speech pause related parameters extracted from recordings carried out in standard office (non-studio) environments. Acoustic and temporal analysis of speech may represent a potential tool for the objective analysis in schizophrenia.

Gender differences in speech temporal patterns detected using lagged co-occurrence text-analysis of personal narratives

This paper describes a novel methodology for the detection of speech patterns. Lagged co-occurrence analysis (LCA) utilizes the likelihood that a target word will be uttered in a certain position after a trigger word. Using this methodology, it is possible to uncover a statistically significant repetitive temporal patterns of word use, compared to a random choice of words. To demonstrate this new tool on autobiographical narratives, 200 subjects related each a 5-min story, and these stories were transcribed and subjected to LCA, using software written by the author. This study focuses on establishing the usefulness of LCA in psychological research by examining its associations with gender. The application of LCA to the corpus of personal narratives revealed significant differences in the temporal patterns of using the word "I" between male and female speakers. This finding is particularly demonstrative of the potential for studying speech temporal patterns using LCA, as men and women tend to utter the pronoun "I" in comparable frequencies. Specifically, LCA of the personal narratives showed that, on average, men tended to have shorter interval between their use of the pronoun, while women speak longer between two subsequent utterances of the pronoun. The results of this study are discussed in light of psycholinguistic factors governing male and female speech communities.

Emotional response deficits in schizophrenia: insights from affective science

Our understanding of the emotional features of schizophrenia has benefited greatly from the adoption of methods and theory from the field of affective science. This article covers basic concepts and methods from affective science on the psychological and neural mechanisms contributing to emotions and reviews the ways in which this research has advanced our understanding of emotional response deficits in schizophrenia. We review naturalistic studies and elicitation studies that evoke emotion responses among participants, including emotion expression, experience, and autonomic physiology. We also consider how these emotion response measures correspond to schizophrenia symptoms, and we focus particular attention on the issue of sex differences in emotional responding and how this may influence our understanding emotional functioning among individuals with schizophrenia.

Computerized measurement of negative symptoms in schizophrenia

Accurate measurement of negative symptoms is crucial for understanding and treating schizophrenia. However, current measurement strategies are reliant on subjective symptom rating scales, which often have psychometric and practical limitations. Computerized analysis of patients' speech offers a sophisticated and objective means of evaluating negative symptoms. The present study examined the feasibility and validity of using widely-available acoustic and lexical-analytic software to measure flat affect, alogia and anhedonia (via positive emotion). These measures were examined in their relationships to clinically-rated negative symptoms and social functioning. Natural speech samples were collected and analyzed for 14 patients with clinically-rated flat affect, 46 patients without flat affect and 19 healthy controls. The computer-based inflection and speech rate measures significantly discriminated patients with flat affect from controls, and the computer-based measure of alogia and negative emotion significantly discriminated the flat and nonflat patients. Both the computer and clinical measures of positive emotion/anhedonia corresponded to functioning impairments. The computerized method of assessing negative symptoms offered a number of advantages over the symptom scale-based approach.

Emotion word use in the conversational speech of schizophrenia patients

INTRODUCTION

Many recent studies have found that, although schizophrenia patients tend to display diminished facial expressions of emotion, they report levels of emotional experiences that are similar to those of controls. Although these findings are very informative, it is unknown whether such dissociation exits for other modalities such as verbal expression of emotion. The purpose of this study was to investigate the association between the use of emotion words during a free speech task and subjective experience of emotion in schizophrenia patients and controls.

METHODS

Speech samples of 48 schizophrenia patients and 48 nonpsychiatric control individuals were compared on the type and amount of emotional words used, as well as on the level of self-reported stress experienced while providing descriptions of themselves.

RESULTS

Groups did not differ in the amount or type of emotion words uttered during the free speech task. Patients, however, found the task more stressful than controls. Emotion word use and subjective emotional experience were not related in either group.

CONCLUSIONS

Results do not fully support prior findings, but are consistent with the notion of a lack of correspondence between the expression and experience of emotion.

Vocal responses to unanticipated perturbations in voice loudness feedback: an automatic mechanism for stabilizing voice amplitude

The present study tested whether subjects respond to unanticipated short perturbations in voice loudness feedback with compensatory responses in voice amplitude. The role of stimulus magnitude (+/- 1,3 vs 6 dB SPL), stimulus direction (up vs down), and the ongoing voice amplitude level (normal vs soft) were compared across compensations. Subjects responded to perturbations in voice loudness feedback with a compensatory change in voice amplitude 76% of the time. Mean latency of amplitude compensation was 157 ms. Mean response magnitudes were smallest for 1-dB stimulus perturbations (0.75 dB) and greatest for 6-dB conditions (0.98 dB). However, expressed as gain, responses for 1-dB perturbations were largest and almost approached 1.0. Response magnitudes were larger for the soft voice amplitude condition compared to the normal voice amplitude condition. A mathematical model of the audio-vocal system captured the main features of the compensations. Previous research has demonstrated that subjects can respond to an unanticipated perturbation in voice pitch feedback with an automatic compensatory response in voice fundamental frequency. Data from the present study suggest that voice loudness feedback can be used in a similar manner to monitor and stabilize voice amplitude around a desired loudness level.

Bradyphrenia and bradykinesia both contribute to altered speech in schizophrenia: a quantitative acoustic study

OBJECTIVE

To evaluate the relative contributions of motor and cognitive symptoms on speech output in persons with schizophrenia (SZ).

BACKGROUND

Studies of speech production in SZ suggest that atypical prosody (eg, pause) is related to clinical symptoms manifest in flat affect and alogia. Others have suggested that a more general motor slowing, bradykinesia, leads to measurable speech changes.

METHOD

Thirteen participants with SZ and age-matched control subjects were included for between-group and by-task comparisons. Two levels of task complexity were analyzed acoustically to determine distinct and overlapping features of speech pause.

RESULTS

For the free-speech task, group differences were found on measures of average pause duration, pause variability, percent pause, and cumulative pause time. Conversely, for the rote-speech task, group differences were found only on measures of average pause duration and pause variability.

CONCLUSIONS

In persons with SZ, differences in the average and variability of pause duration may be reflected in speech motor slowing, whereas more global measures (eg, percentage pause) may better reflect a paucity of thought and idea generation related to the cognitive-linguistic aspects of free speech. These findings corroborate and extend the paucity of thought hypothesis in SZ to include an influence of motor slowing on speech production.

Remote capture of human voice acoustical data by telephone: a methods study

In this pilot study we sought to determine the reliability and validity of collecting speech and voice acoustical data via telephone transmission for possible future use in large clinical trials. Simultaneous recordings of each participant's speech and voice were made at the point of participation, the local recording (LR), and over a telephone line using a dedicated in-line computerized interactive voice recording system, the remote recording (RR). All voice recordings were made from our laboratory telephone located in Groton, Connecticut to the RR system located in Madison, Wisconsin. All data points were compared on a measure-by-measure basis between the LR and RR recordings. The results suggest that both measures of frequency excursion and of speech motor timing are reliably captured over the telephone. Results are discussed in terms of specific acoustic measures that may be useful and accurately measured via telephone transmission, for examining disease severity and pharmacological intervention for use in a large-scale clinical trial.

Brain activity during emotionally negative pictures in schizophrenia with and without flat affect: an fMRI study

The aim of this functional magnetic resonance imaging (fMRI) study was to compare regional brain activity in schizophrenia subjects with (FA+) and without (FA-) flat affect during the viewing of emotionally negative pictures. Thirteen FA+ subjects and 11 FA- subjects were scanned while being presented with a series of emotionally negative and neutral pictures. Experientially, the viewing of the negative pictures induced a negative emotional state whose intensity was significantly greater in the FA- group than in the FA+ group. Neurally, the Negative minus Neutral contrast revealed, in the FA- group, significant loci of activation in the midbrain, pons, anterior cingulate cortex, insula, ventrolateral orbitofrontal cortex, anterior temporal pole, amygdala, medial prefrontal cortex, and extrastriate visual cortex. In the FA+ group, this contrast produced significant loci of activation in the midbrain, pons, anterior temporal pole, and extrastriate visual cortex. When the brain activity measured in the FA+ group was subtracted from that measured in the FA- group, only the lingual gyrus was significantly activated. Perhaps in FA+ subjects an amygdaloid malfunction rendered the amygdala unable to correctly evaluate the emotional meaning of the pictures presented, thus preventing effective connectivity linking the amygdala to the brain regions implicated in the physiological and experiential dimensions of emotion. Alternatively, a disturbance of effective connectivity in the neural networks linking the midbrain and the medial prefrontal system may have been responsible for the quasi absence of emotional reaction in FA+ subjects, and the abnormal functioning of the medial prefrontal cortex and anterior cingulate cortex in the FA+ group.

Sensory contributions to impaired prosodic processing in schizophrenia

BACKGROUND

Deficits in affect recognition are prominent features of schizophrenia. Within the auditory domain, patients show difficulty in interpreting vocal emotional cues based on intonation (prosody). The relationship of these symptoms to deficits in basic sensory processing has not been previously evaluated.

METHODS

Forty-three patients and 34 healthy comparison subjects were tested on two affective prosody measures: voice emotion identification and voice emotion discrimination. Basic auditory sensory processing was measured using a tone-matching paradigm and the Distorted Tunes Test (DTT). A subset of subjects was also tested on facial affect identification and discrimination tasks.

RESULTS

Patients showed significantly impaired performance on all emotion processing tasks. Within the patient group, a principal components analysis demonstrated significant intercorrelations between basic pitch perception and affective prosodic performance. In contrast, facial affect recognition deficits represented a distinct second component. Prosodic affect measures correlated significantly with severity of negative symptoms and impaired global outcome.

CONCLUSIONS

These results demonstrate significant relationships between basic auditory processing deficits and impaired receptive prosody in schizophrenia. The separate loading of auditory and visual affective recognition measures suggests that within-modality factors may be more significant than cross-modality factors in the etiology of affect recognition deficits in schizophrenia.

Peeling the onion: NMDA dysfunction as a unifying model in schizophrenia

N-methyl-d-aspartate receptor (NMDAR) dysfunction plays a crucial role in schizophrenia, leading to impairments in cognitive coordination. NMDAR agonists (e.g., glycine) ameliorate negative and cognitive symptoms, consistent with NMDAR models. However, not all types of cognitive coordination use NMDAR. Further, not all aspects of cognitive coordination are impaired in schizophrenia, suggesting the need for specificity in applying the cognitive coordination construct.

High-frequency synchronisation in schizophrenia: Too much or too little?

Phillips & Silverstein's focus on schizophrenia as a failure of “cognitive coordination” is welcome. They note that a simple hypothesis of reduced Gamma synchronisation subserving impaired coordination does not fully account for recent observations. We suggest that schizophrenia reflects a dynamic compensation to a core deficit of coordination, expressed either as hyper- or hyposynchronisation, with neurotransmitter systems and arousal as modulatory mechanisms.

No blind schizophrenics: Are NMDA-receptor dynamics involved?

Numerous searches have failed to identify a single co-occurrence of total blindness and schizophrenia. Evidence that blindness causes loss of certain NMDA-receptor functions is balanced by reports of compensatory gains. Connections between visual and anterior cingulate NMDA-receptor systems may help to explain how blindness could protect against schizophrenia.

Setting domain boundaries for convergence of biological and psychological perspectives on cognitive coordination in schizophrenia

The claim that the disorganized subtype of schizophrenia results from glutamate hypofunction is enhanced by consideration of current subtypology of schizophrenia, symptom definition, interdependence of neurotransmitters, and the nature of the data needed to support the hypothesis. Careful specification clarifies the clinical reality of disorganization as a feature of schizophrenia and increases the utility of the subtype.

Schizophrenia: Putting context in context

Although context-processing deficits may be core features of schizophrenia, context remains a poorly defined concept. To test Phillips & Silverstein's model, we need to operationalize context more precisely. We offer several useful ways of framing context and discuss enhancing or facilitating schizophrenic patients' performance under different contextual situations. Furthermore, creativity may be a byproduct of cognitive uncoordination.

Phenomenology, context, and self-experience in schizophrenia

Impairments in cognitive coordination in schizophrenia are supported by phenomenological data that suggest deficits in the processing of visual context. Although the target article is sympathetic to such a phenomenological perspective, we argue that the relevance of phenomenological data for a wider understanding of consciousness in schizophrenia is not sufficiently addressed by the authors.