Altered resting-state functional connectivity in a thalamo-cortico-cerebellar network in patients with schizophrenia.

The diagnosis of schizophrenia is associated with a complex psychopathology related to disrupted brain circuitry causing a failure in coordinating information across brain sites with no consensus regarding the mechanisms. Although schizophrenia is well-studied, the great majority of studies investigated pre-selected ROIs or Seed-based connectivity. Whole brain ROI-wise studies that consider all ROIs available simultaneously are lacking.

Low-Level Visual Features of Window Views Contribute to Perceived Naturalness and Mental Health Outcomes.

Previous studies have shown that natural window views are beneficial for mental health, but it is still unclear which specific features constitute a 'natural' window view. On the other hand, studies on image analysis found that (LLVFs) are associated with perceived naturalness, but mainly conducted experiments with brief stimulus presentations. In this study, research on the effects of window views on mental health was combined with the detailed analysis of LLVFs.

Linking Cognitive Integrity to Working Memory Dynamics in the Aging Human Brain.

Aging is accompanied by a decline of working memory, an important cognitive capacity that involves stimulus-selective neural activity that persists after stimulus presentation. Here, we unraveled working memory dynamics in older human adults (male and female) including those diagnosed with mild cognitive impairment (MCI) using a combination of behavioral modeling, neuropsychological assessment, and MEG recordings of brain activity. Younger adults (male and female) were studied with behavioral modeling only.

Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity.

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R and R, proton density PD, and magnetization transfer saturation MT) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g.

The Thought From the Machine: Neural Basis of Thoughts With a Coherent and Diminished Sense of Authorship.

Patients with schizophrenia who experience inserted thoughts report a diminished sense of thought authorship. Based on its elusive neural basis, this functional neuroimaging study used a novel setup to convince healthy participants that a technical device triggers thoughts in their stream of consciousness. Self-reports indicate that participants experienced their thoughts as self-generated when they believed the (fake) device was deactivated, and attributed their thoughts externally when they believed the device was activated-an experience usually only reported by patients diagnosed with schizophrenia.

Reduced Resting-State Connectivity in the Precuneus is correlated with Apathy in Patients with Schizophrenia.

A diagnosis of schizophrenia is associated with a heterogeneous psychopathology including positive and negative symptoms. The disconnection hypothesis, an early pathophysiological framework conceptualizes the diversity of symptoms as a result of disconnections in neural networks. In line with this hypothesis, previous neuroimaging studies of patients with schizophrenia reported alterations within the default mode network (DMN), the most prominent network at rest.

New Graph-Theoretical-Multimodal Approach Using Temporal and Structural Correlations Reveals Disruption in the Thalamo-Cortical Network in Patients with Schizophrenia.

Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive, and behavioral symptoms in this disorder. When building brain networks, functional and structural networks are typically modeled independently: Functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks.