Category fluency, latent semantic analysis and schizophrenia: a candidate gene approach

Genome-Wide Epistatic Network Analyses of Semantic Fluency in Older Adults

Semantic fluency impairment has been attributed to a wide range of neurocognitive and psychiatric conditions, especially in the older population. Moderate heritability estimates on semantic fluency were obtained from both twin and family-based studies suggesting genetic contributions to the observed variation across individuals. Currently, effort in identifying the genetic variants underlying the heritability estimates for this complex trait remains scarce. Using the semantic fluency scale and genome-wide SNP genotype data from the Long Life Family Study (LLFS), we performed a genome-wide association study (GWAS) and epistasis network analysis on semantic fluency in 2289 individuals aged over 60 years from the American LLFS cohorts and replicated the findings in 1129 individuals aged over 50 years from the Danish LLFS cohort. In the GWAS, two SNPs with genome-wide significance (rs3749683, p = 2.52 × 10-8; rs880179, p = 4.83 × 10-8) mapped to the CMYAS gene on chromosome 5 were detected. The epistasis network analysis identified five modules as significant (4.16 × 10-5 < p < 7.35 × 10-3), of which two were replicated (p < 3.10 × 10-3). These two modules revealed significant enrichment of tissue-specific gene expression in brain tissues and high enrichment of GWAS catalog traits, e.g., obesity-related traits, blood pressure, chronotype, sleep duration, and brain structure, that have been reported to associate with verbal performance in epidemiological studies. Our results suggest high tissue specificity of genetic regulation of gene expression in brain tissues with epistatic SNP networks functioning jointly in modifying individual verbal ability and cognitive performance.

SpEx: a German-language dataset of speech and executive function performance

This work presents data from 148 German native speakers (20-55 years of age), who completed several speaking tasks, ranging from formal tests such as word production tests to more ecologically valid spontaneous tasks that were designed to mimic natural speech. This speech data is supplemented by performance measures on several standardised, computer-based executive functioning (EF) tests covering domains of working-memory, cognitive flexibility, inhibition, and attention. The speech and EF data are further complemented by a rich collection of demographic data that documents education level, family status, and physical and psychological well-being. Additionally, the dataset includes information of the participants' hormone levels (cortisol, progesterone, oestradiol, and testosterone) at the time of testing. This dataset is thus a carefully curated, expansive collection of data that spans over different EF domains and includes both formal speaking tests as well as spontaneous speaking tasks, supplemented by valuable phenotypical information. This will thus provide the unique opportunity to perform a variety of analyses in the context of speech, EF, and inter-individual differences, and to our knowledge is the first of its kind in the German language. We refer to this dataset as SpEx since it combines speech and executive functioning data. Researchers interested in conducting exploratory or hypothesis-driven analyses in the field of individual differences in language and executive functioning, are encouraged to request access to this resource. Applicants will then be provided with an encrypted version of the data which can be downloaded.

Reflections on the nature of measurement in language-based automated assessments of patients' mental state and cognitive function

Modern advances in computational language processing methods have enabled new approaches to the measurement of mental processes. However, the field has primarily focused on model accuracy in predicting performance on a task or a diagnostic category. Instead the field should be more focused on determining which computational analyses align best with the targeted neurocognitive/psychological functions that we want to assess. In this paper we reflect on two decades of experience with the application of language-based assessment to patients' mental state and cognitive function by addressing the questions of what we are measuring, how it should be measured and why we are measuring the phenomena. We address the questions by advocating for a principled framework for aligning computational models to the constructs being assessed and the tasks being used, as well as defining how those constructs relate to patient clinical states. We further examine the assumptions that go into the computational models and the effects that model design decisions may have on the accuracy, bias and generalizability of models for assessing clinical states. Finally, we describe how this principled approach can further the goal of transitioning language-based computational assessments to part of clinical practice while gaining the trust of critical stakeholders.

Using big data to understand bilingual performance in semantic fluency: Findings from the Canadian Longitudinal Study on Aging

OBJECTIVES

This study aimed to characterize verbal fluency performance in monolinguals and bilinguals using data from the Canadian Longitudinal Study on Aging (CLSA).

METHODS

A large sample of adults aged 45-85 (n = 12,875) completed a one-minute animal fluency task in English. Participants were English-speaking monolinguals (n = 9,759), bilinguals who spoke English as their first language (L1 bilinguals, n = 1,836), and bilinguals who spoke English as their second language (L2 bilinguals, n = 1,280). Using a distributional modeling approach to quantify the semantic similarity of words, we examined the impact of word frequency and pairwise semantic similarity on performance on this task.

RESULTS

Overall, L1 bilinguals outperformed monolinguals on the verbal fluency task: they produced more items, and these items were of lower average frequency and semantic similarity. Monolinguals in turn outperformed L2 bilinguals on these measures. The results held across different age groups, educational, and income levels.

DISCUSSION

These results demonstrate an advantage for bilinguals compared to monolinguals on a category fluency task, when performed in the first language, indicating that, at least in the CLSA sample, bilinguals have superior semantic search capabilities in their first language compared to monolingual speakers of that language.

Dispositional and ideological factor correlate of conspiracy thinking and beliefs

This study explored how the Big Five personality traits, as well as measures of personality disorders, are related to two different measures of conspiracy theories (CTs)The two measures correlated r = .58 and were applied to examine generalisability of findings. We also measured participants (N = 397) general knowledge levels and ideology in the form of religious and political beliefs. Results show that the Big Five and ideology are related to CTs but these relationships are generally wiped out by the stronger effects of the personality disorder scales. Two personality disorder clusters (A and B) were significant correlates of both CT measures, in both cases accounting for similar amounts of variance (20%). The personality disorders most predictive of conspiracy theories were related to the A cluster, characterized by schizotypal symptoms such as oddities of thinking and loose associations. These findings were corroborated by an additional analysis using Latent Semantic Analysis (LSA). LSA demonstrated that the items measuring schizotypal and related symptoms are cognitively related to both our measures of CTs. The implications for the studying of CTs is discussed, and limitations are acknowledged.

Multivariate genome-wide association study of depression, cognition, and memory phenotypes and validation analysis identify 12 cross-ethnic variants

To date, little is known about the pleiotropic genetic variants among depression, cognition, and memory. The current research aimed to identify the potential pleiotropic single nucleotide polymorphisms (SNPs), genes, and pathways of the three phenotypes by conducting a multivariate genome-wide association study and an additional pleiotropy analysis among Chinese individuals and further validate the top variants in the UK Biobank (UKB). In the discovery phase, the participants were 139 pairs of dizygotic twins from the Qingdao Twins Registry. The genome-wide efficient mixed-model analysis identified 164 SNPs reaching suggestive significance (P < 1 × 10-5). Among them, rs3967317 (P = 1.21 × 10-8) exceeded the genome-wide significance level (P < 5 × 10-8) and was also demonstrated to be associated with depression and memory in pleiotropy analysis, followed by rs9863698, rs3967316, and rs9261381 (P = 7.80 × 10-8-5.68 × 10-7), which were associated with all three phenotypes. After imputation, a total of 457 SNPs reached suggestive significance. The top SNP chr6:24597173 was located in the KIAA0319 gene, which had biased expression in brain tissues. Genes and pathways related to metabolism, immunity, and neuronal systems demonstrated nominal significance (P < 0.05) in gene-based and pathway enrichment analyses. In the validation phase, 12 of the abovementioned SNPs reached the nominal significance level (P < 0.05) in the UKB. Among them, three SNPs were located in the KIAA0319 gene, and four SNPs were identified as significant expression quantitative trait loci in brain tissues. These findings may provide evidence for pleiotropic variants among depression, cognition, and memory and clues for further exploring the shared genetic pathogenesis of depression with Alzheimer's disease.

Genetic analysis of the ZNF804A gene in Mexican patients with schizophrenia, schizoaffective disorder and bipolar disorder

BACKGROUND

Evidence suggests that schizophrenia (SCZ), schizoaffective disorder (SAD) and bipolar disorder (BPD) share genetic risk variants. ZNF804A gene has been associated with these disorders in different populations. GWAS and candidate gene studies have reported association between the rs1344706 A allele with SCZ, SAD and BPD in European and Asian populations. In Mexican patients, no studies have specifically analyzed ZNF804A gene variants with these disorders. The aim of the study was to analyze the rs1344706 and identify common and rare variants in a targeted region of the ZNF804A gene in Mexican patients with SCZ, BPD and SAD compared with a control group.

METHODS

We genotyped the rs1344706 in 228 Mexican patients diagnosed with SCZ, SAD and BPD, and 295 controls. Also, an additional sample of 167 patients with these disorders and 170 controls was analyzed to identify rare and common variants using the Sanger-sequence analysis of a targeted region of ZNF804A gene.

RESULTS

Association analysis of rs1344706 observed a higher frequency of A allele in the patients compared with the control group; however, did not show statistical differences after Bonferronís correction (χ2 = 5.3, p = 0.0208). In the sequence analysis, we did not identify rare variants; however, we identified three common variants: rs3046266, rs1366842 and rs12477430. A comparison of the three identified variants between patients and controls did not show statistical differences (p > 0.0125). Finally, haplotype analysis did not show statistical differences between SCZ, SAD and BPD and controls.

CONCLUSIONS

Our findings did not support the evidence suggesting that ZNF804A gene participates in the etiology of SCZ, SAD and BPD. Future studies are needed in a larger sample size to identify the effect of this gene in psychiatric disorders.

Quantified language connectedness in schizophrenia-spectrum disorders

Language abnormalities are a core symptom of schizophrenia-spectrum disorders and could serve as a potential diagnostic marker. Natural language processing enables quantification of language connectedness, which may be lower in schizophrenia-spectrum disorders. Here, we investigated connectedness of spontaneous speech in schizophrenia-spectrum patients and controls and determine its accuracy in classification. Using a semi-structured interview, speech of 50 patients with a schizophrenia-spectrum disorder and 50 controls was recorded. Language connectedness in a semantic word2vec model was calculated using consecutive word similarity in moving windows of increasing sizes (2-20 words). Mean, minimal and variance of similarity were calculated per window size and used in a random forest classifier to distinguish patients and healthy controls. Classification based on connectedness reached 85% cross-validated accuracy, with 84% specificity and 86% sensitivity. Features that best discriminated patients from controls were variance of similarity at window sizes between 5 and 10. We show impaired connectedness in spontaneous speech of patients with schizophrenia-spectrum disorders even in patients with low ratings of positive symptoms. Effects were most prominent at the level of sentence connectedness. The high sensitivity, specificity and tolerability of this method show that language analysis is an accurate and feasible digital assistant in diagnosing schizophrenia-spectrum disorders.

Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia

Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.

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

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

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

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

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.

Acceptability of collecting speech samples from the elderly via the telephone

OBJECTIVE

There is a critical need to develop rapid, inexpensive and easily accessible screening tools for mild cognitive impairment (MCI) and Alzheimer's disease (AD). We report on the efficacy of collecting speech via the telephone to subsequently develop sensitive metrics that may be used as potential biomarkers by leveraging natural language processing methods.

METHODS

Ninety-one older individuals who were cognitively unimpaired or diagnosed with MCI or AD participated from home in an audio-recorded telephone interview, which included a standard cognitive screening tool, and the collection of speech samples. In this paper we address six questions of interest: (1) Will elderly people agree to participate in a recorded telephone interview? (2) Will they complete it? (3) Will they judge it an acceptable approach? (4) Will the speech that is collected over the telephone be of a good quality? (5) Will the speech be intelligible to human raters? (6) Will transcriptions produced by automated speech recognition accurately reflect the speech produced?

RESULTS

Participants readily agreed to participate in the telephone interview, completed it in its entirety, and rated the approach as acceptable. Good quality speech was produced for further analyses to be applied, and almost all recorded words were intelligible for human transcription. Not surprisingly, human transcription outperformed off the shelf automated speech recognition software, but further investigation into automated speech recognition shows promise for its usability in future work.

CONCLUSION

Our findings demonstrate that collecting speech samples from elderly individuals via the telephone is well tolerated, practical, and inexpensive, and produces good quality data for uses such as natural language processing.

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

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

Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation

OBJECTIVE

Obstacles for computational tools in psychiatry include gathering robust evidence and keeping implementation costs reasonable. We report a systematic review of automated speech evaluation for the psychosis spectrum and analyze the value of information for a screening program in a healthcare system with a limited number of psychiatrists (Maputo, Mozambique).

METHODS

Original studies on speech analysis for forecasting of conversion in individuals at clinical high risk (CHR) for psychosis, diagnosis of manifested psychotic disorder, and first-episode psychosis (FEP) were included in this review. Studies addressing non-verbal components of speech (e.g., pitch, tone) were excluded.

RESULTS

Of 168 works identified, 28 original studies were included. Valuable speech features included direct measures (e.g., relative word counting) and mathematical embeddings (e.g.: word-to-vector, graphs). Accuracy estimates reported for schizophrenia diagnosis and CHR conversion ranged from 71 to 100% across studies. Studies used structured interviews, directed tasks, or prompted free speech. Directed-task protocols were faster while seemingly maintaining performance. The expected value of perfect information is USD 9.34 million. Imperfect tests would nevertheless yield high value.

CONCLUSION

Accuracy for screening and diagnosis was high. Larger studies are needed to enhance precision of classificatory estimates. Automated analysis presents itself as a feasible, low-cost method which should be especially useful for regions in which the physician pool is insufficient to meet demand.

Effect of DISC1 Polymorphisms on the Long-term Course of Neurocognitive Deficits in Non-affective Psychosis

Neurocognitive deficits are core symptoms of schizophrenia that determine a poorer outcome. High variability in the progression of neuropsychological deficits in schizophrenia has been described. It is still unknown whether genetic variations can affect the course of cognitive deficits. Variations in the Disrupted in Schizophrenia 1 (DISC1) gene have previously been associated with neurocognitive deficits. This study investigated the association between 3 DISC1 polymorphisms (rs6675281 (Leu607Phe), rs1000731, and rs821616 (Ser704Cys)) and long-term (3 years) cognitive performance. One-hundred-thirty-three Caucasian drug-naive patients experiencing a first episode of non-affective psychosis were genotyped. Cognitive function was assessed at baseline and after 3 years of initiating treatment. Other clinical and socio-demographic variables were recorded to eliminate potential confounding effects. Patients carrying the A allele of rs1000731 exhibited a significant improvement in Working Memory and Attention domains, and the homozygosity of the A allele of rs821616 showed a significant improvement in Motor Dexterity performance over 3 years of follow-up. In conclusion, DISC1 gene variations may affect the course of cognitive deficits found in patients suffering from the first episode of non-affective psychosis.

The link between formal thought disorder and social functioning in schizophrenia: A meta-analysis

Background.

Formal thought disorder (FTD) and social functioning impairments are core symptoms of schizophrenia. Although both have been observed for over a century, the strength of the relationship between FTD and social functioning remains unclear. Furthermore, a variety of methodological approaches have been used to assess these constructs—which may contribute to inconsistency in reported associations. This meta-analysis aimed to: (a) systematically test the relationship between FTD and social functioning and (b) determine if the methodology used to assess FTD and/or social functioning moderates this relationship.

Methods.

Following Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guidelines, a targeted literature search was conducted on studies examining the relationship between FTD and social functioning. Correlations were extracted and used to calculate weighted mean effect sizes using a random effects model.

Results.

A total of 1,478 participants across 13 unique studies were included in this meta-analysis. A small-medium inverse association (r = −0.23, p < 0.001) was observed between FTD and social functioning. Although heterogeneity analyses produced a significant Q-statistic (Q = 52.77, p = <0.001), the relationship between FTD and social functioning was not moderated by methodology, study quality, demographic variables, or clinical factors.

Conclusions.

Findings illustrate a negative association between FTD and social functioning. Despite differences in the methodological approach used and type of information assessed, measurement type and clinical factors did not moderate the relationship between FTD and social functioning. Future studies should explore whether other variables, such as cognitive processes (e.g., social cognition), may account for variability in associations between these constructs.

Parvalbumin Interneuron Dysfunction in a Thalamo-Prefrontal Cortical Circuit in Disc1 Locus Impairment Mice

Altered cortical excitation-inhibition (E-I) balance resulting from abnormal parvalbumin interneuron (PV IN) function is a proposed pathophysiological mechanism of schizophrenia and other major psychiatric disorders. Preclinical studies have indicated that disrupted-in-schizophrenia-1 (Disc1) is a useful molecular lead to address the biology of prefrontal cortex (PFC)-dependent cognition and PV IN function. To date, PFC inhibitory circuit function has not been investigated in depth in Disc1 locus impairment (LI) mouse models. Therefore, we used a Disc1 LI mouse model to investigate E-I balance in medial PFC (mPFC) circuits. We found that inhibition onto layer 2/3 excitatory pyramidal neurons in the mPFC was significantly reduced in Disc1 LI mice. This reduced inhibition was accompanied by decreased GABA release from local PV, but not somatostatin (SOM) INs, and by impaired feedforward inhibition (FFI) in the mediodorsal thalamus (MD) to mPFC circuit. Our mechanistic findings of abnormal PV IN function in a Disc1 LI model provide insight into biology that may be relevant to neuropsychiatric disorders including schizophrenia.

Bridging the theoretical gap between semantic representation models without the pressure of a ranking: some lessons learnt from LSA

In recent years, latent semantic analysis (LSA) has reached a level of maturity at which its presence is ubiquitous in technology as well as in simulation of cognitive processes. In spite of this, in recent years there has been a trend of subjecting LSA to some criticisms, usually because it is compared to other models in very specific tasks and conditions and sometimes without having good knowledge of what the semantic representation of LSA means, and without exploiting all the possibilities of which LSA is capable other than the cosine. This paper provides a critical review to clarify some of the misunderstandings regarding LSA and other space models. The historical stability of the predecessors of LSA, the representational structure of word meaning and the multiple topologies that could arise from a semantic space, the computation of similarity, the myth that LSA dimensions have no meaning, the computational and algorithm plausibility to account for meaning acquisition in LSA (in contrast to others models based on online mechanisms), the possibilities of spatial models to substantiate recent proposals, and, in general, the characteristics of classic vector models and their ease and flexibility to simulate some cognitive phenomena will be reviewed. The review highlights the similarity between LSA and other techniques and proposes using long LSA experiences in other models, especially in predicting models such as word2vec. In sum, it emphasizes the lessons that can be learned from comparing LSA-based models to other models, rather than making statements about "the best."

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.

Automatic Scoring of Semantic Fluency

In neuropsychological assessment, semantic fluency is a widely accepted measure of executive function and access to semantic memory. While fluency scores are typically reported as the number of unique words produced, several alternative manual scoring methods have been proposed that provide additional insights into performance, such as clusters of semantically related items. Many automatic scoring methods yield metrics that are difficult to relate to the theories behind manual scoring methods, and most require manually-curated linguistic ontologies or large corpus infrastructure. In this paper, we propose a novel automatic scoring method based on Wikipedia, Backlink-VSM, which is easily adaptable to any of the 61 languages with more than 100k Wikipedia entries, can account for cultural differences in semantic relatedness, and covers a wide range of item categories. Our Backlink-VSM method combines relational knowledge as represented by links between Wikipedia entries (Backlink model) with a semantic proximity metric derived from distributional representations (vector space model; VSM). Backlink-VSM yields measures that approximate manual clustering and switching analyses, providing a straightforward link to the substantial literature that uses these metrics. We illustrate our approach with examples from two languages (English and Korean), and two commonly used categories of items (animals and fruits). For both Korean and English, we show that the measures generated by our automatic scoring procedure correlate well with manual annotations. We also successfully replicate findings that older adults produce significantly fewer switches compared to younger adults. Furthermore, our automatic scoring procedure outperforms the manual scoring method and a WordNet-based model in separating younger and older participants measured by binary classification accuracy for both English and Korean datasets. Our method also generalizes to a different category (fruit), demonstrating its adaptability.

Toward the Language Oscillogenome

Language has been argued to arise, both ontogenetically and phylogenetically, from specific patterns of brain wiring. We argue that it can further be shown that core features of language processing emerge from particular phasal and cross-frequency coupling properties of neural oscillations; what has been referred to as the language ‘oscillome.’ It is expected that basic aspects of the language oscillome result from genetic guidance, what we will here call the language ‘oscillogenome,’ for which we will put forward a list of candidate genes. We have considered genes for altered brain rhythmicity in conditions involving language deficits: autism spectrum disorders, schizophrenia, specific language impairment and dyslexia. These selected genes map on to aspects of brain function, particularly on to neurotransmitter function. We stress that caution should be adopted in the construction of any oscillogenome, given the range of potential roles particular localized frequency bands have in cognition. Our aim is to propose a set of genome-to-language linking hypotheses that, given testing, would grant explanatory power to brain rhythms with respect to language processing and evolution.

Community Resilience Learning Collaborative and Research Network (C-LEARN): Study Protocol with Participatory Planning for a Randomized, Comparative Effectiveness Trial

This manuscript presents the protocol and participatory planning process for implementing the Community Resilience Learning Collaborative and Research Network (C-LEARN) study. C-LEARN is designed to determine how to build a service program and individual client capacity to improve mental health-related quality of life among individuals at risk for depression, with exposure to social risk factors or concerns about environmental hazards in areas of Southern Louisiana at risk for events such as hurricanes and storms. The study uses a Community Partnered Participatory Research (CPPR) framework to incorporate community priorities into study design and implementation. The first phase of C-LEARN is assessment of community priorities, assets, and opportunities for building resilience through key informant interviews and community agency outreach. Findings from this phase will inform the implementation of a two-level (program-level and individual client level) randomized study in up to four South Louisiana communities. Within communities, health and social-community service programs will be randomized to Community Engagement and Planning (CEP) for multi-sector coalition support or Technical Assistance (TA) for individual program support to implement evidence-based and community-prioritized intervention toolkits, including an expanded version of depression collaborative care and resources (referrals, manuals) to address social risk factors such as financial or housing instability and for a community resilience approach to disaster preparedness and response. Within each arm, the study will randomize individual adult clients to one of two mobile applications that provide informational resources on services for depression, social risk factors, and disaster response or also provide psychoeducation on Cognitive Behavioral Therapy to enhance coping with stress and mood. Planned data collection includes baseline, six-month and brief monthly surveys for clients, and baseline and 12-month surveys for administrators and staff.

The impact of psychosis genome-wide associated ZNF804A variation on verbal fluency connectivity

Schizophrenia (SCZ) and bipolar disorder (BD) have high heritability. Genome-wide association studies (GWAS) have identified ZNF804A as a significant risk gene for both illnesses. A validation of this finding at the brain systems-level is imperative as there is still little understanding of how it heightens risk. Based in part on our recent findings of an effect on widespread decreased white matter microstructural fractional anisotropy (putatively a proxy of its integrity), particularly strong in SCZ, we asked whether the risk allele has a detrimental effect on regional brain activation and functional connectivity during a type of cognitive processing which is, together with its neural correlates, impaired in BD and SCZ: verbal fluency. Functional MRI and genotype data was collected from 80 healthy volunteers, and 54 SCZ and 40 BD patients. A standard multifactorial analysis of variance using statistical parametric mapping and significance correction of FWE p < 0.05 was used. We found the GWAS risk allele A was associated with decreased positive functional coupling between the left precentral gyrus/inferior frontal gyrus (i.e. the most highly recruited area for the task) and: 1) the left inferior frontal gyrus, and 2) the left posterior cingulate gyrus, encompassing the precuneus; both as a main effect across controls and psychosis patients. Such association of the risk allele with reduced functional connectivity (with no area where the opposite main effect was detected), converges with findings in other tasks, our previous finding of its widespread impact on brain white matter microstructure, and with the dysconnectivity hypothesis of SCZ.

Cognitive development prior to onset of psychosis

Schizophrenia patients commonly exhibit substantial and diffuse cognitive impairment. Evidence suggests that subtle cognitive deficits are already apparent in childhood and adolescence, many years prior to onset of psychosis. While there is almost unequivocal evidence of some degree of cognitive impairment in individuals who later develop schizophrenia, the literature remains inconclusive regarding the exact nature of this impairment and warrants careful review and interpretation. Meta-analytic findings suggest that individuals who later develop schizophrenia, but not related disorders, such as bipolar disorder, exhibit a premorbid IQ deficit of around 8 points. Several studies have also found evidence for premorbid deficits across most cognitive domains, such as language, processing speed and executive functions. Longitudinal studies, although rare, suggest that individuals who go on to develop schizophrenia may show a course of increasing cognitive impairment prior to onset of psychosis. While evidence regarding the etiology of premorbid deficits is scarce, common and rare genetic variants, as well as environmental factors such as obstetric complications and cannabis use may play an important role and warrant further examination. In this selected review, we give an overview of population-based studies on premorbid cognitive deficits in schizophrenia, with a special focus on evidence regarding the specificity, profile and course of these deficits.

Semantic Memory Organization in Japanese Patients With Schizophrenia Examined With Category Fluency

BACKGROUND

Disorganization of semantic memory in patients with schizophrenia has been studied by referring to their category fluency performance. Recently, data-mining techniques such as singular value decomposition (SVD) analysis have been reported to be effective in elucidating the latent semantic memory structure in patients with schizophrenia. The aim of this study is to investigate semantic memory organization in patients with schizophrenia using a novel method based on data-mining approach.

METHOD

Category fluency data were collected from 181 patients with schizophrenia and 335 healthy controls at the Department of Psychiatry, Osaka University. The 20 most frequently reported animals were chosen for SVD analysis. In the two-dimensional (2D) solution, item vectors (i.e., animal names) were plotted in the 2D space of each group. In the six-dimensional (6D) solution, inter-item similarities (i.e., cosines) were calculated among items. Cosine charts were also created for the six most frequent items to show the similarities to other animal items.

RESULTS

In the 2D spatial representation, the six most frequent items were grouped in the same clusters (i.e., dog, cat as pet cluster, lion, tiger as wild/carnivorous cluster, and elephant, giraffe as wild/herbivorous cluster) for patients and healthy adults. As for 6D spatial cosines, the correlations (Pearson's r) between 17 items commonly generated in the two groups were moderately high. However, cosine charts created for the three pairs from the six most frequent animals (dog-cat, lion-tiger, elephant-giraffe) showed that pair-wise similarities between other animals were less salient in patients with schizophrenia.

DISCUSSION

Semantic memory organization in patients with schizophrenia, revealed by SVD analysis, did not appear to be seriously impaired in the 2D space representation, maintaining a clustering structure similar to that in healthy controls for common animals. However, the coherence of those animals was less salient in 6D space, lacking pair-wise similarities to other members of the animal category. These results suggests subtle but structural differences between the two groups. A data-mining approach by means of SVD analysis seems to be effective in evaluating semantic memory in patients with schizophrenia, providing both a visual representation and an objective measure of the structural alterations.

Semantic coherence in psychometric schizotypy: An investigation using Latent Semantic Analysis

Technological advancements have led to the development of automated methods for assessing semantic coherence in psychiatric populations. Latent Semantic Analysis (LSA) is an automated method that has been used to quantify semantic coherence in schizophrenia-spectrum disorders. The current study examined whether: 1) Semantic coherence reductions extended to psychometrically-defined schizotypy and 2) Greater cognitive load further reduces semantic coherence. LSA was applied to responses generated during category fluency tasks in baseline and cognitive load conditions. Significant differences between schizotypy and non-schizotypy groups were not observed. Findings suggest that semantic coherence may be relatively preserved at this point on the schizophrenia-spectrum.

The effects of adjunctive intranasal oxytocin in patients with schizophrenia

OBJECTIVES

Both human and animal studies have suggested that oxytocin may have therapeutic potential in the treatment of schizophrenia. We evaluated the effects of intranasal oxytocin on cognition and its predictive factors in Japanese patients with schizophrenia.

METHODS

Subjects were 16 chronic schizophrenia patients who underwent intranasal oxytocin treatment for 3 months and were assessed for changes in severity of clinical symptoms and cognitions. Fifteen of the 16 subjects underwent 3-Tesla magnetic resonance imaging.

RESULTS

Oxytocin significantly reduced scores on the positive and negative syndrome scale, especially on the negative symptoms. As for cognition, there was an improvement of the verbal fluency. Furthermore, the change of the negative score in positive and negative syndrome scale showed a negative correlation with the gray matter volumes of the right insula and left cingulate cortex.

CONCLUSIONS

Our results indicate that daily administration of intranasal oxytocin may be effective for ameliorating clinical symptoms and cognitive functions in chronic schizophrenia patients, and this improvement may be related to the gray matter volume of the right insula and left cingulate cortex.

Action (verb) fluency deficits in schizophrenia spectrum disorders: linking language, cognition and interpersonal functioning

Deficits in action (verb) fluency have previously been reported in schizophrenia spectrum disorders. The degree to which this reflects difficulties generating verbs in different semantic categories is unknown. Here, action fluency responses of 46 patients with schizophrenia spectrum disorders and 76 healthy controls were classified as action or mental state verbs, using well-established taxonomies. The word length, frequency, age of acquisition, valence and concreteness of the verbs produced were also examined. Participants also completed measures of cognitive function, and clinical symptoms. Independent inter-rater agreement of semantic categorization was high. The percentage of action verbs produced was significantly lower in patients than controls, whilst the percentage of mental state verbs produced did not differ. Patients' action verbs were: significantly less concrete; positively correlated with memory and intelligence; and negatively correlated with interpersonal symptoms. Impaired action verb, but intact mental state verb generation is consistent with the neural separability of these processes.

Translating advances in the molecular basis of schizophrenia into novel cognitive treatment strategies

The presence and severity of cognitive symptoms, including working memory, executive dysfunction and attentional impairment, contributes materially to functional impairment in schizophrenia. Cognitive symptoms have proved to be resistant to both first- and second-generation antipsychotic drugs. Efforts to develop a consensus set of cognitive domains that are both disrupted in schizophrenia and are amenable to cross-species validation (e.g. the National Institute of Mental Health Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia and Research Domain Criteria initiatives) are an important step towards standardization of outcome measures that can be used in preclinical testing of new drugs. While causative genetic mutations have not been identified, new technologies have identified novel genes as well as hitherto candidate genes previously implicated in the pathophysiology of schizophrenia and/or mechanisms of antipsychotic efficacy. This review comprises a selective summary of these developments, particularly phenotypic data arising from preclinical genetic models for cognitive dysfunction in schizophrenia, with the aim of indicating potential new directions for pro-cognitive therapeutics. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc.

Can RDoC Help Find Order in Thought Disorder?

Thought disorder is a pernicious and nonspecific aspect of numerous serious mental illnesses (SMIs) and related conditions. Despite decades of empirical research on thought disorder, our present understanding of it is poor, our clinical assessments focus on a limited set of extreme behaviors, and treatments are palliative at best. Applying a Research Domain Criteria (RDoC) framework to thought disorder research offers advantages to explicate its phenotype; isolate its mechanisms; and develop more effective assessments, treatments, and potential cures. In this commentary, we discuss ways in which thought disorder can be understood within the RDoC framework. We propose operationalizing thought disorder within the RDoC construct of language using psycholinguistic sciences, to help objectify and quantify language within individuals; technologically sophisticated paradigms, to allow naturalistic behavioral sampling techniques with unprecedented ecological validity; and computational modeling, to account for a network of interconnected and dynamic linguistic, cognitive, affective, and social functions. We also highlight challenges for understanding thought disorder within an RDoC framework. Thought disorder likely does not occur as an isomorphic dysfunction in a single RDoC construct, but rather, as multiple potential dysfunctions in a network of RDoC constructs. Moreover, thought disorder is dynamic over time and context within individuals. In sum, RDoC is a useful framework to integrate multidisciplinary research efforts aimed at operationalizing, understanding, and ameliorating thought disorder.

Deictic and Propositional Meaning-New Perspectives on Language in Schizophrenia

Emerging linguistic evidence points at disordered language behavior as a defining characteristic of schizophrenia. In this article, we review this literature and demonstrate how a framework focusing on two core functions of language-reference and propositional meaning-can conceptualize schizophrenic symptoms, identify important variables for risk assessment, diagnosis, and treatment, and inform cognitive behavioral therapy and other remedial approaches. We introduce the linguistic phenomena of deictic anchoring and propositional complexity, explain how they relate to schizophrenic symptoms, and show how they can be tracked in language behavior.

Computerized Analysis of Verbal Fluency: Normative Data and the Effects of Repeated Testing, Simulated Malingering, and Traumatic Brain Injury

In verbal fluency (VF) tests, subjects articulate words in a specified category during a short test period (typically 60 s). Verbal fluency tests are widely used to study language development and to evaluate memory retrieval in neuropsychiatric disorders. Performance is usually measured as the total number of correct words retrieved. Here, we describe the properties of a computerized VF (C-VF) test that tallies correct words and repetitions while providing additional lexical measures of word frequency, syllable count, and typicality. In addition, the C-VF permits (1) the analysis of the rate of responding over time, and (2) the analysis of the semantic relationships between words using a new method, Explicit Semantic Analysis (ESA), as well as the established semantic clustering and switching measures developed by Troyer et al. (1997). In Experiment 1, we gathered normative data from 180 subjects ranging in age from 18 to 82 years in semantic ("animals") and phonemic (letter "F") conditions. The number of words retrieved in 90 s correlated with education and daily hours of computer-use. The rate of word production declined sharply over time during both tests. In semantic conditions, correct-word scores correlated strongly with the number of ESA and Troyer-defined semantic switches as well as with an ESA-defined semantic organization index (SOI). In phonemic conditions, ESA revealed significant semantic influences in the sequence of words retrieved. In Experiment 2, we examined the test-retest reliability of different measures across three weekly tests in 40 young subjects. Different categories were used for each semantic ("animals", "parts of the body", and "foods") and phonemic (letters "F", "A", and "S") condition. After regressing out the influences of education and computer-use, we found that correct-word z-scores in the first session did not differ from those of the subjects in Experiment 1. Word production was uniformly greater in semantic than phonemic conditions. Intraclass correlation coefficients (ICCs) of correct-word z-scores were higher for phonemic (0.91) than semantic (0.77) tests. In semantic conditions, good reliability was also seen for the SOI (ICC = 0.68) and ESA-defined switches in semantic categories (ICC = 0.62). In Experiment 3, we examined the performance of subjects from Experiment 2 when instructed to malinger: 38% showed abnormal (p< 0.05) performance in semantic conditions. Simulated malingerers with abnormal scores could be distinguished with 80% sensitivity and 89% specificity from subjects with abnormal scores in Experiment 1 using lexical, temporal, and semantic measures. In Experiment 4, we tested patients with mild and severe traumatic brain injury (mTBI and sTBI). Patients with mTBI performed within the normal range, while patients with sTBI showed significant impairments in correct-word z-scores and category shifts. The lexical, temporal, and semantic measures of the C-VF provide an automated and comprehensive description of verbal fluency performance.

An examination of the language construct in NIMH's research domain criteria: Time for reconceptualization!

The National Institute of Mental Health's Research Domain Criteria (RDoC) Initiative "calls for the development of new ways of classifying psychopathology based on dimensions of observable behavior." As a result of this ambitious initiative, language has been identified as an independent construct in the RDoC matrix. In this article, we frame language within an evolutionary and neuropsychological context and discuss some of the limitations to the current measurements of language. Findings from genomics and the neuroimaging of performance during language tasks are discussed in relation to serious mental illness and within the context of caveats regarding measuring language. Indeed, the data collection and analysis methods employed to assay language have been both aided and constrained by the available technologies, methodologies, and conceptual definitions. Consequently, different fields of language research show inconsistent definitions of language that have become increasingly broad over time. Individually, they have also shown significant improvements in conceptual resolution, as well as in experimental and analytic techniques. More recently, language research has embraced collaborations across disciplines, notably neuroscience, cognitive science, and computational linguistics and has ultimately re-defined classical ideas of language. As we move forward, the new models of language with their remarkably multifaceted constructs force a re-examination of the NIMH RDoC conceptualization of language and thus the neuroscience and genetics underlying this concept. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Bridging the Gap between Genes and Language Deficits in Schizophrenia: An Oscillopathic Approach

Schizophrenia is characterized by marked language deficits, but it is not clear how these deficits arise from the alteration of genes related to the disease. The goal of this paper is to aid the bridging of the gap between genes and schizophrenia and, ultimately, give support to the view that the abnormal presentation of language in this condition is heavily rooted in the evolutionary processes that brought about modern language. To that end we will focus on how the schizophrenic brain processes language and, particularly, on its distinctive oscillatory profile during language processing. Additionally, we will show that candidate genes for schizophrenia are overrepresented among the set of genes that are believed to be important for the evolution of the human faculty of language. These genes crucially include (and are related to) genes involved in brain rhythmicity. We will claim that this translational effort and the links we uncover may help develop an understanding of language evolution, along with the etiology of schizophrenia, its clinical/linguistic profile, and its high prevalence among modern populations.

Language deficits in schizophrenia and autism as related oscillatory connectomopathies: An evolutionary account

Schizophrenia (SZ) and autism spectrum disorders (ASD) are characterised by marked language deficits, but it is not clear how these arise from gene mutations associated with the disorders. Our goal is to narrow the gap between SZ and ASD and, ultimately, give support to the view that they represent abnormal (but related) ontogenetic itineraries for the human faculty of language. We will focus on the distinctive oscillatory profiles of the SZ and ASD brains, in turn using these insights to refine our understanding of how the brain implements linguistic computations by exploring a novel model of linguistic feature-set composition. We will argue that brain rhythms constitute the best route to interpreting language deficits in both conditions and mapping them to neural dysfunction and risk alleles of the genes. Importantly, candidate genes for SZ and ASD are overrepresented among the gene sets believed to be important for language evolution. This translational effort may help develop an understanding of the aetiology of SZ and ASD and their high prevalence among modern populations.

[The association between the GRIN2B gene and verbal fluency and impairment of abstract thinking in schizophrenia]

OBJECTIVE

To search for the association between the GRIN2B gene and signs of thought and speech disorders which may be the result of decreased accessibility to the mental lexicon.

MATERIAL AND METHODS

The association between the GRIN2B polymorphism rs7301328 with semantic verbal fluency and five symptoms of thought and speech disorders, as assessed with the PANSS, was studied in 552 patients with schizophrenia-spectrum disorders.

RESULTS AND CONCLUSION

There was the association of the GRIN2B gene with verbal fluency and the PANSS item «Difficulty in Abstract Thinking». The association was not modified by verbal fluency. The results suggest that the GRIN2B gene may modify the linguistic processes involved in the retrieval of information from the mental lexicon on the basis of semantic traits and, moreover, contribute to the variability of clinical symptoms of impairment of abstract thinking in patients with schizophrenia. The heterozygous genotype may be protective against the development of thought and speech disorders.

Risperidone and NAP protect cognition and normalize gene expression in a schizophrenia mouse model

Mutated disrupted in schizophrenia 1 (DISC1), a microtubule regulating protein, leads to schizophrenia and other psychiatric illnesses. It is hypothesized that microtubule stabilization may provide neuroprotection in schizophrenia. The NAP (NAPVSIPQ) sequence of activity-dependent neuroprotective protein (ADNP) contains the SxIP motif, microtubule end binding (EB) protein target, which is critical for microtubule dynamics leading to synaptic plasticity and neuroprotection. Bioinformatics prediction for FDA approved drugs mimicking SxIP-like motif which displace NAP-EB binding identified Risperidone. Risperidone or NAP effectively ameliorated object recognition deficits in the mutated DISC1 mouse model. NAP but not Risperidone, reduced anxiety in the mutated mice. Doxycycline, which blocked the expression of the mutated DISC1, did not reverse the phenotype. Transcripts of Forkhead-BOX P2 (Foxp2), a gene regulating DISC1 and associated with human ability to acquire a spoken language, were increased in the hippocampus of the DISC1 mutated mice and were significantly lowered after treatment with NAP, Risperidone, or the combination of both. Thus, the combination of NAP and standard of care Risperidone in humans may protect against language disturbances associated with negative and cognitive impairments in schizophrenia.

Collective unconscious: how gut microbes shape human behavior

The human gut harbors a dynamic and complex microbial ecosystem, consisting of approximately 1 kg of bacteria in the average adult, approximately the weight of the human brain. The evolutionary formation of a complex gut microbiota in mammals has played an important role in enabling brain development and perhaps sophisticated social interaction. Genes within the human gut microbiota, termed the microbiome, significantly outnumber human genes in the body, and are capable of producing a myriad of neuroactive compounds. Gut microbes are part of the unconscious system regulating behavior. Recent investigations indicate that these microbes majorly impact on cognitive function and fundamental behavior patterns, such as social interaction and stress management. In the absence of microbes, underlying neurochemistry is profoundly altered. Studies of gut microbes may play an important role in advancing understanding of disorders of cognitive functioning and social interaction, such as autism.

Neuropsychological characteristics of verbal and non-verbal fluency in schizophrenia patients

This review paper provides analyses confirming correlation between various brain regions activity, particularly its prefrontal portions, and schizophrenia patients' performance in verbal fluency tests. Various factors modifying patients' performance in the aforementioned tasks were singled out and discussed. Systematically we have reviewed the results of non-verbal fluency tests conducted in the schizophrenic patients. The authors also summarizes findings of earlier studies stressing the role of semantic fluency as a predictor of first-episode psychosis. Verbal and non-verbal fluency tests engage complex cognitive processes and executive functions in patients. As a result, the interpretation of their results is often complicated and requires special competences. The tests are popular neuropsychological tools used for assessment of verbal memory, executive functions, visual-spatial abilities and psychomotor speed in patients with mental and neurological disorders. The aim of this paper is to discuss diagnostic tools used for measuring both types of fluency (verbal and non-verbal), test interpretation methods, as well as their usefulness in clinical diagnostics and scientific research.

Inborn and experience-dependent models of categorical brain organization. A position paper

The present review aims to summarize the debate in contemporary neuroscience between inborn and experience-dependent models of conceptual representations that goes back to the description of category-specific semantic disorders for biological and artifact categories. Experience-dependent models suggest that categorical disorders are the by-product of the differential weighting of different sources of knowledge in the representation of biological and artifact categories. These models maintain that semantic disorders are not really category-specific, because they do not respect the boundaries between different categories. They also argue that the brain structures which are disrupted in a given type of category-specific semantic disorder should correspond to the areas of convergence of the sensory-motor information which play a major role in the construction of that category. Furthermore, they provide a simple interpretation of gender-related categorical effects and are supported by studies assessing the importance of prior experience in the cortical representation of objects On the other hand, inborn models maintain that category-specific semantic disorders reflect the disruption of innate brain networks, which are shaped by natural selection to allow rapid identification of objects that are very relevant for survival. From the empirical point of view, these models are mainly supported by observations of blind subjects, which suggest that visual experience is not necessary for the emergence of category-specificity in the ventral stream of visual processing. The weight of the data supporting experience-dependent and inborn models is thoroughly discussed, stressing the fact observations made in blind subjects are still the subject of intense debate. It is concluded that at the present state of knowledge it is not possible to choose between experience-dependent and inborn models of conceptual representations.

Sex differences in TGFB-β signaling with respect to age of onset and cognitive functioning in schizophrenia

There are studies showing that gene polymorphisms within the transforming growth factor-β (TGF-β) signaling constitute schizophrenia risk variants. However, the association between TGFB1 gene polymorphisms (+869T/C and +915G/C), TGF-β level with schizophrenia course, and its symptomatology together with cognitive functioning has not been investigated so far. We included 151 patients with schizophrenia and 279 healthy controls. Cognitive functioning was assessed using Rey Auditory Verbal Learning Test, Trail Making Test (TMT)-A and TMT-B, Verbal Fluency task, Stroop test, as well as selected subtests from the Wechsler Adults Intelligence Scale - Revised, Polish adaptation (WAIS-R-Pl): Digit Symbol Coding, Digit Span Forward and Backward, and Similarities. Additionally, serum TGF-β levels were measured in 88 schizophrenia patients and 88 healthy controls. Serum TGF-β level was significantly higher among patients with schizophrenia in comparison with healthy controls; however, the studied polymorphisms were not associated with TGF-β level in schizophrenia patients. Subjects carrying the +869T allele performed significantly worse in comparison with +869CC homozygotes on Stroop task, Verbal Fluency task and Digit Symbol Coding task. There was a significant difference in age of psychosis onset in female schizophrenia patients with respect to the TGFB1 +869T/C polymorphism. Additionally, adjustment for possible confounders revealed that there was a significant difference in cognitive performance on Digit Symbol Coding task with respect to the TGFB1 +869T/C polymorphism among female schizophrenia patients. Our results suggest that TGF-β signaling might be a valid link contributing to observed differences in age of onset and the level of cognitive decline between male and female schizophrenia patients.