Yaryna Bitkovska

New publication out in Biological Psychiatry CNNI!

Our new publication on “Characterizing thalamocortical (dys)connectivity following d-amphetamine, LSD, and MDMA administration” (Avram et al., 2022) in Biological Psychiatry CNNI shows that prototypical psychostimulants, empathogens, and psychedelics evoke thalamocortical-hyperconnectivity with sensorimotor areas, similar to findings in patients with psychosis, but differentially influence thalamocortical-connectivity with prefrontal-limbic cortices. Check out the publication here: Avram, M., Müller, […]

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Convolutional neural network propagation on electroencephalographic scalograms for detection of schizophrenia

In our recent study, scalograms of EEG signals were used to identify potential biomarkers in schizophrenia heritability. This study presented evidence for the validation of a Convolutional Neural Network (CNN) model using transfer learning for scalp EEGs of patients and controls during the performance of a speeded sensorimotor task and a working memory task. It

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Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions

Non-segmented MRI brain images are used for the identification of new Magnetic Resonance Imaging (MRI) biomarkers able to differentiate between schizophrenic patients (SCZ), major depressive patients (MD) and healthy controls (HC). Brain texture measures such as entropy and contrast, capturing the neighboring variation of MRI voxel intensities, were computed and fed into deep learning technique

Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions Read More »

Pattern classification as decision support tool in antipsychotic treatment algorithms

Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment

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Recognition of blinks activity patterns during stress conditions using CNN and Markovian analysis

This paper investigates eye behaviour through blinks activity during stress conditions. Although eye blinking is a semi-voluntary action, it is considered to be affected by one’s emotional states such as arousal or stress. The blinking rate provides information towards this direction, however, the analysis on the entire eye aperture timeseries and the corresponding blinking patterns

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