Schizophrenia

Quantum-like behavior without quantum physics II. A quantum-like model of neural network dynamics.

In earlier work, we laid out the foundation for explaining the quantum-like behavior of neural syste...

Machine learning improved classification of psychoses using clinical and biological stratification: Update from the bipolar-schizophrenia network for intermediate phenotypes (B-SNIP).

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

RATIONALE: Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a d...

Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.

BACKGROUND: Early diagnosis of schizophrenia could improve the outcome of the illness. Unlike classi...

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

BACKGROUND: A lack of a sufficiently large sample at single sites causes poor generalizability in au...

Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach.

In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigat...

In Schizophrenia, Depression, Anxiety, and Physiosomatic Symptoms Are Strongly Related to Psychotic Symptoms and Excitation, Impairments in Episodic Memory, and Increased Production of Neurotoxic Tryptophan Catabolites: a Multivariate and Machine Learning Study.

The depression, anxiety and physiosomatic symptoms (DAPS) of schizophrenia are associated with negat...

Music Intervention Leads to Increased Insular Connectivity and Improved Clinical Symptoms in Schizophrenia.

Schizophrenia is a syndrome that is typically accompanied by delusions and hallucinations that might...

The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning.

Machine learning techniques were used to identify highly informative early psychosis self-report ite...

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity.

Despite significant progress in the field, the detection of fMRI signal changes during hallucinatory...

Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

UNLABELLED: Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alt...

Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study.

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) pat...

Automatic schizophrenic discrimination on fNIRS by using complex brain network analysis and SVM.

BACKGROUND: Schizophrenia is a kind of serious mental illness. Due to the lack of an objective physi...

Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI.

Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI ...

A novel fuzzy rough selection of non-linearly extracted features for schizophrenia diagnosis using fMRI.

BACKGROUND AND OBJECTIVES: Schizophrenia is a severe brain disorder primarily diagnosed through exte...

Does this robot have a mind? Schizophrenia patients' mind perception toward humanoid robots.

A Deep-Dream Virtual Reality Platform for Studying Altered Perceptual Phenomenology.

Altered states of consciousness, such as psychotic or pharmacologically-induced hallucinations, prov...

Working Memory and Decision-Making in a Frontoparietal Circuit Model.

Working memory (WM) and decision-making (DM) are fundamental cognitive functions involving a distrib...

Influence of facial feedback during a cooperative human-robot task in schizophrenia.

Rapid progress in the area of humanoid robots offers tremendous possibilities for investigating and ...

Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features.

Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive ...

Improving individual predictions: Machine learning approaches for detecting and attacking heterogeneity in schizophrenia (and other psychiatric diseases).

Psychiatric diseases are very heterogeneous both in clinical manifestation and etiology. With the re...