The Nature of Overinclusive Thinking in Schizophrenia

Cutting, John; David, Anthony S.; Murphy, Declan

doi:10.1159/000284501

Cited by 14 publications

(5 citation statements)

References 8 publications

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“…The young age of onset of clinical symptoms and lack of psychosis in ASD were later recognized as the main features that separated SZ from ASD. While they are now recognized as distinct disorders, their shared cognitive symptoms include impairments in social interaction and communication, deficits in processing emotion ( Wallace et al, 2011 ; Brune, 2003 ; Morrison et al, 1998 ), theory of mind abilities ( Pilowsky et al, 2000 ), language skills ( Magaud et al, 2010 ) and learning ( Titone et al, 2004 ), and the inability to suppress irrelevant information ( Bird et al, 2006 ; Cutting et al, 1987 ). There are currently no medical tests available for either disorder.…”

Section: Introductionmentioning

confidence: 99%

Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia

Mastrovito

Hanson

2018

NeuroImage: Clinical

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Autism and schizophrenia share overlapping genetic etiology, common changes in brain structure and common cognitive deficits. A number of studies using resting state fMRI have shown that machine learning algorithms can distinguish between healthy controls and individuals diagnosed with either autism spectrum disorder or schizophrenia. However, it has not yet been determined whether machine learning algorithms can be used to distinguish between the two disorders. Using a linear support vector machine, we identify features that are most diagnostic for each disorder and successfully use them to classify an independent cohort of subjects. We find both common and divergent connectivity differences largely in the default mode network as well as in salience, and motor networks. Using divergent connectivity differences, we are able to distinguish autistic subjects from those with schizophrenia. Understanding the common and divergent connectivity changes associated with these disorders may provide a framework for understanding their shared cognitive deficits.

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Section: Introductionmentioning

confidence: 99%

Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia

Mastrovito

Hanson

2018

NeuroImage: Clinical

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“…Since Bleuler [86], cognitive impairment in SCZ has been focused on associative disturbance. Later, difficulties in abstract attitude and overinclusive thinking were added to the core features for SCZ [87]. Currently, a huge amount of evidences has found deficits in speed of processing, attention/vigilance, working memory, verbal/visual learning, problem solving, and social cognition [88]).…”

Section: Clinical Featuresmentioning

confidence: 99%

A Neurodevelopment Approach for a Transitional Model of Early Onset Schizophrenia

Berardis

Filippis²,

Masi

et al. 2021

Brain Sciences

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In the last decades, the conceptualization of schizophrenia has dramatically changed, moving from a neurodegenerative process occurring in early adult life to a neurodevelopmental disorder starting be-fore birth, showing a variety of premorbid and prodromal symptoms and, in relatively few cases, evolving in the full-blown psychotic syndrome. High rates of co-occurring different neurodevelopmental disorders such as Autism spectrum disorder and ADHD, predating the onset of SCZ, and neurobio-logical underpinning with significant similarities, support the notion of a pan-developmental disturbance consisting of impairments in neuromotor, receptive language, social and cognitive development. Con-sidering that many SCZ risk factors may be similar to symptoms of other neurodevelopmental psychi-atric disorders, transition processes from child & adolescent to adult systems of care should include both high risk people as well as subject with other neurodevelopmental psychiatric disorders with different levels of severity. This descriptive mini-review discuss the need of innovative clinical approaches, re-considering specific diagnostic categories, stimulating a careful analysis of risk factors and promoting the appropriate use of new and safer medications.

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“…Cameron has suggested that the core feature of thought disorders in schizophrenia was overinclusive thinking, a vagueness of boundaries between concepts making them overextensive and able to accommodate logical contradictions (Cameron, 1939). Subsequent studies have provided support for this notion (Chen et al, 1994;Cutting et al, 1987;Payne, 1973). The study by Chen and colleagues used a task that required subjects to verify words as members or non-members of a conceptual category.…”

Section: Semantic Memorymentioning

confidence: 99%

The Neuropsychology of Schizophrenia

David¹,

Cutting²

2019

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The Nature of Overinclusive Thinking in Schizophrenia

Cited by 14 publications

References 8 publications

Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia

Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia

A Neurodevelopment Approach for a Transitional Model of Early Onset Schizophrenia

The Neuropsychology of Schizophrenia

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