ORCID Profile
0000-0002-0391-345X
Current Organisations
University of California, San Diego
,
Karolinska Institute
,
University of California Los Angeles
,
University of Toronto
,
Centre for Addiction and Mental Health
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Publisher: Elsevier BV
Date: 06-2020
Publisher: Cold Spring Harbor Laboratory
Date: 04-02-2019
DOI: 10.1101/539551
Abstract: Recent studies suggest that in idual differences in empathic concern may be mediated by continuous interactions between self-other resonance and cognitive control networks. To test this hypothesis, we used machine learning to examine whether resting fMRI connectivity ( i.e. the degree of synchronous BOLD activity across multiple cortical areas in the absence of task demands) of resonance and control networks could predict trait empathy (n=58). Indeed, resonance and control networks’ interconnectivity predicted empathic concern. Empathic concern was also predicted by connectivity within the somatomotor network. In light of numerous reported sex differences in empathy, we controlled for biological sex and also studied separately what aspect of these features could predict participants’ sex. Sex was best predicted by the interconnectivity of the visual system with the resonance, somatomotor, and cingulo-opercular network, as well as the somatomotor-control network connectivity. These findings confirm that variation in empathic responses to others reflects characteristic network properties detectable regardless of task demands. Furthermore, network properties of the visual system may be a locus of sex differences previously unaccounted for in empathy research. Finally, these findings suggest that it may be possible to assess empathic predispositions in in iduals without needing to perform conventional empathy assessments.
Publisher: Frontiers Media SA
Date: 08-01-2019
Publisher: Elsevier BV
Date: 11-2001
DOI: 10.1016/S0165-1781(01)00296-7
Abstract: GABAergic systems have been implicated in the pathogenesis of anxiety, depression and insomnia. These symptoms are part of the core and comorbid psychiatric disturbances in post-traumatic stress disorder (PTSD). In a s le of Caucasian male PTSD patients, dinucleotide repeat polymorphisms of the GABA(A) receptor beta 3 subunit gene were compared to scores on the General Health Questionnaire-28 (GHQ). As the major allele at this gene locus (GABRB3) was G1, the alleles were ided into G1 and non-G1 groups. On the total score of the GHQ, which comprises the somatic symptoms, anxiety/insomnia, social dysfunction and depression subscales, patients with the G1 non-G1 genotype had a significantly higher score when compared to either the G1G1 genotype (alpha=0.01) or the non-G1 non-G1 genotype (alpha=0.05). No significant difference was found between the G1G1 and non-G1 non-G1 genotypes. When the G1 non-G1 heterozygotes were compared to the combined G1G1 and non-G1 non-G1 homozygotes, a significantly higher total GHQ score was found in the heterozygotes (P=0.002). These observations suggest a heterosis effect. Further analysis of GHQ subscale scores showed that heterozygotes compared to the combined homozygotes had higher scores on the somatic symptoms (P=0.006), anxiety/insomnia (P=0.003), social dysfunction (P=0.054) and depression (P=0.004) subscales. In conclusion, the present study indicates that in a population of PTSD patients, heterozygosity of the GABRB3 major (G1) allele confers higher levels of somatic symptoms, anxiety/insomnia, social dysfunction and depression than found in homozygosity.
Publisher: American Psychiatric Association Publishing
Date: 09-2020
Publisher: Springer Science and Business Media LLC
Date: 08-10-2020
DOI: 10.1038/S41398-020-01013-Y
Abstract: No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete s le with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.
Publisher: Informa UK Limited
Date: 30-06-2016
Publisher: American Psychiatric Association Publishing
Date: 05-2018
Location: United States of America
Location: United States of America
No related grants have been discovered for Jamie Feusner.