Publications by authors named "Palaniyappan L"

The striatum, a core brain structure relevant for schizophrenia, exhibits heterogeneous volumetric changes in this illness. Due to this heterogeneity, its role in the risk of developing schizophrenia following exposure to environmental stress remains poorly understood. Using the putamen (a subnucleus of the striatum) as an indicator for convergent genetic risk of schizophrenia, 63 unaffected first-degree relatives of patients (22.

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Delusions are a defining feature of psychosis and play an important role in the conceptualization and diagnosis of psychotic disorders; however, the particular role that different delusions play in the prognosis of these disorders is not well understood. This study explored relationships between delusions and other symptoms in 674 first episode psychosis (FEP) individuals by comparing symptom networks between baseline and 12 months after intake to an early intervention service. Specifically, we (1) estimated regularized partial correlation networks at baseline and month 12, (2) identified the most central symptoms in each network, (3) identified clusters of highly connected symptoms, and (4) compared networks to examine changes in structure and connectivity.

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Background: Working memory deficit, a key feature of schizophrenia, is a heritable trait shared with unaffected siblings. It can be attributed to dysregulation in transitions from one brain state to another.

Aims: Using network control theory, we evaluate if defective brain state transitions underlie working memory deficits in schizophrenia.

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Background: Major psychiatric disorders (MPDs) are delineated by distinct clinical features. However, overlapping symptoms and transdiagnostic effectiveness of medications have challenged the traditional diagnostic categorisation. We investigate if there are shared and illness-specific disruptions in the regional functional efficiency (RFE) of the brain across these disorders.

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  • The study investigates glutamate levels in different stages of schizophrenia, focusing on individuals at genetic high risk (GHR), clinical high risk (CHR), and first-episode schizophrenia (FES) compared to healthy controls.
  • People with GHR showed lower levels of glutamate in the dorsal anterior cingulate cortex (dACC), while those with CHR had higher levels in the perigenual ACC (pACC) compared to FES individuals.
  • The research suggests that reduced glutamatergic tone may contribute to early symptoms of schizophrenia, with higher levels emerging as symptoms intensify, particularly linking lower glutamate to disorganization in high-risk groups.
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  • Accelerated brain aging is observed in first-episode schizophrenia patients, particularly in those who do not respond well to antipsychotic treatment.
  • Patients treated with risperidone showed pronounced brain age gaps compared to healthy individuals, but this gap did not worsen significantly over the treatment period.
  • Measuring the brain age gap early on can help predict later treatment resistance and inform decisions regarding second-line treatments for schizophrenia.
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Psychosis implicates changes across a broad range of cognitive functions. These functions are cortically organized in the form of a hierarchy ranging from primary sensorimotor (unimodal) to higher-order association cortices, which involve functions such as language (transmodal). Language has long been documented as undergoing structural changes in psychosis.

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Background And Hypothesis: Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness.

Study Design: Diffusion and T1-weighted 7T MR scans were obtained from  = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario.

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Introduction: Frontotemporal dementia (FTD) can be phenotypically divided into behavioral variant FTD (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA). However, the neural underpinnings of this phenotypic heterogeneity remain elusive.

Methods: Cortical morphology, white matter hyperintensities (WMH), diffusion tensor image analysis along the perivascular space (DTI-ALPS), and their interrelationships were assessed in subtypes of FTD.

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Background: Psychosis involves a distortion of thought content, which is partly reflected in anomalous ways in which words are semantically connected into utterances in speech. We sought to explore how these linguistic anomalies are realized through putative circuit-level abnormalities in the brain's semantic network.

Methods: Using a computational large-language model, Bidirectional Encoder Representations from Transformers (BERT), we quantified the contextual expectedness of a given word sequence (perplexity) across 180 samples obtained from descriptions of 3 pictures by patients with first-episode schizophrenia (FES) and controls matched for age, parental social status, and sex, scanned with 7 T ultra-high field functional magnetic resonance imaging (fMRI).

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Article Synopsis
  • This study used machine learning to classify subtypes of schizophrenia by analyzing brain images from over 4,000 patients and healthy individuals through international collaboration.* -
  • Researchers identified two neurostructural subgroups: one with predominant cortical loss and enlarged striatum, and another with significant subcortical loss in areas like the hippocampus and striatum.* -
  • The findings suggest this new imaging-based classification could redefine schizophrenia based on biological similarities, enhancing our understanding and treatment of the disorder.*
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Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca's area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia.

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Working memory (WM) is the ability to maintain and manipulate information 'in mind'. The neural codes underlying WM have been a matter of debate. We simultaneously recorded the activity of hundreds of neurons in the lateral prefrontal cortex of male macaque monkeys during a visuospatial WM task that required navigation in a virtual 3D environment.

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Background: Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups.

Methods: Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992-2011).

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  • Dopamine plays a critical role in addiction, with its functioning disrupted at all stages of the addiction process, potentially indicated by neuromelanin levels in the substantia nigra.
  • A systematic review identified 10 relevant articles examining neuromelanin in substance use disorders, with a meta-analysis showing inconclusive results due to insufficient sample size and power.
  • The analysis underscores the need for more robust replication studies and research on neuromelanin in relation to various substances and associated psychiatric conditions.
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The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial.

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Background And Hypothesis: Speech markers are digitally acquired, computationally derived, quantifiable set of measures that reflect the state of neurocognitive processes relevant for social functioning. "Oddities" in language and communication have historically been seen as a core feature of schizophrenia. The application of natural language processing (NLP) to speech samples can elucidate even the most subtle deviations in language.

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Major depressive, bipolar, or psychotic disorders are preceded by earlier manifestations in behaviours and experiences. We present a synthesis of evidence on associations between person-level antecedents (behaviour, performance, psychopathology) in childhood, adolescence, or early adulthood and later onsets of major depressive disorder, bipolar disorder, or psychotic disorder based on prospective studies published up to September 16, 2022. We screened 11,342 records, identified 460 eligible publications, and extracted 570 risk ratios quantifying the relationships between 52 antecedents and onsets in 198 unique samples with prospective follow-up of 122,766 individuals from a mean age of 12.

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Disrupted language in psychotic disorders, such as schizophrenia, can manifest as false contents and formal deviations, often described as thought disorder. These features play a critical role in the social dysfunction associated with psychosis, but we continue to lack insights regarding how and why these symptoms develop. Natural language generation (NLG) is a field of computer science that focuses on generating human-like language for various applications.

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Article Synopsis
  • Preventing relapse in schizophrenia is essential for better long-term health, as recurrent psychotic episodes hinder recovery and overall wellbeing.
  • Current clinical methods to predict relapses are not precise enough, emphasizing the need for alternative strategies.
  • Recent progress in Natural Language Processing (NLP) shows promise in using speech patterns to forecast relapses 2-4 weeks in advance by identifying linguistic markers associated with thought disorders.
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Background: Environmental modification of genetic information (epigenetics) is often invoked to explain interindividual differences in the phenotype of schizophrenia. In clinical practice, such variability is most prominent in the symptom profile and the treatment response. Epigenetic regulation of immune function is of particular interest, given the therapeutic relevance of this mechanism in schizophrenia.

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Thoughts and moods constituting our mental life incessantly change. When the steady flow of this dynamics diverges in clinical directions, the possible pathways involved are captured through discrete diagnostic labels. Yet a single vulnerable neurocognitive system may be causally involved in psychopathological deviations transdiagnostically.

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Speech in psychosis has long been ascribed as involving 'loosening of associations'. We pursued the aim to elucidate its underlying cognitive mechanisms by analysing picture descriptions from 94 subjects (29 healthy controls, 18 participants at clinical high risk, 29 with first-episode psychosis, and 18 with chronic schizophrenia), using five language models with different computational architectures: FastText, which represents meaning non-contextually/statically; BERT, which represents contextual meaning sensitive to grammar and context; Infersent and SBERT, which provide sentential representations; and CLIP, which evaluates speech relative to a visual stimulus. These models were used to quantify semantic distances crossed between successive tokens/sentences, and semantic perplexity indicating unexpectedness in continuations.

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