Biology subjects

Kroken, R. A.

Publications and source records attributed to Kroken, R. A..

3 recordsLinked to original sources

bioRxiv2020

Neural activity precedes conscious awareness of being in or out of a transient hallucinatory state

Auditory verbal hallucinations, or "hearing voices", is a remarkable state of the mind, occurring in psychiatric and neurological patients, and in a significant minority of the general population. An unexplained characteristic of this phenomenon is that it transiently fluctuates, with coming and going of episodes with time. We monitored neural activity with BOLD-fMRI second-by-second before and after participants indicated the start and end of a transient hallucinatory episode during the scanning session by pressing a response-button. We show that a region in the ventro-medial frontal cortex is activated in advance of conscious awareness of going in or out of a transient hallucinatory state. There was an increase in activity initiated a few seconds before the button-press for onsets, and a corresponding decrease in activity initiated a few seconds before the button-press for offsets. We identified the time between onset and offset button-presses, extracted the corresponding BOLD time-courses from nominated regions-of-interest, and analyzed changes in the signal from 10 seconds before to 15 seconds after the response-button was pressed, which identified onset and offset events. We suggest that this brain region act as a switch to turn on and off a hallucinatory episode. The results may have implications for new interventions for intractable hallucinations.

neuroscience↗

bioRxiv2019

Positive relation between arcuate fasciculus white matter fiber structure and severity of auditory hallucinations: A DTI tractography study

The arcuate fasciculus (AF) has been implicated in the pathology behind schizophrenia and auditory verbal hallucinations (AVHs). White matter tracts forming the arcuate fasciculus can be quantified and visualized using diffusion tensor imaging (DTI) tractography. Although there have been a number of studies on this topic, the results have been conflicting. Studying the underlying white matter structure of the AF could shed light on functional connectivity between temporal and frontal language areas in AVHs. The participants were 66 patients with a schizophrenia diagnosis, where AVHs were defined from the Positive and Negative Syndrome Scale (PANSS), and compared with a healthy control group. DTI was performed on a 3T MR scanner, and tensor estimation was done using deterministic streamline tractography. Statistical analysis of the data showed significantly longer tracts along the AF in patients with severe and frequent AVHs, as well as an overall significant asymmetry with longer fibers on the left side. In addition, there were significant positive correlations between PANSS scores and tract length, tract volume, and number of streamlines for the posterior AF segment on the left side. It is concluded that the present structural results complement previous functional findings of fronto-temporal connectivity in AVH patients.

neuroscience↗

bioRxiv2019

Brain age prediction reveals aberrant brain white matter in schizophrenia and bipolar disorder: A multi-sample diffusion tensor imaging study

BackgroundSchizophrenia (SZ) and bipolar disorders (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, BD, and healthy controls across 10 cohorts. MethodsWe trained six cross-validated models using different combinations of DTI data from 927 healthy controls (HC, 18-94 years), and applied the models to the test sets including 648 SZ (18-66 years) patients, 185 BD patients (18-64 years), and 990 HC (17-68 years), estimating brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results. Results10-fold cross-validation revealed high accuracy for all models. Compared to controls, the model including all feature sets significantly over-estimated the age of patients with SZ (d=-.29) and BD (d=.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy (FA) based models showed larger group differences than the models based on other DTI-derived metrics. ConclusionsBrain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.

neuroscience↗