Wednesday, Jun 26: 11:30 AM - 12:45 PM
Oral Sessions
COEX
Room: Grand Ballroom 101-102
Presentations
Voxel-based morphometry (VBM) [1] has been used extensively to study anatomical differences between people with psychiatric illness and healthy controls. However, the results of these studies have often been difficult to replicate [2]–[6], which may be driven in part by the well-known clinical heterogeneity within psychiatric disorders. Despite this heterogeneity, a fundamental assumption in psychiatric neuroimaging is that each disorder is associated with some core neural phenotype that should be replicable and consistent across different samples and study locations. If such a consistent phenotype cannot be identified, there may be questionable value in ongoing attempts to examine group differences in small, individual studies. Here, we investigated the degree to which five psychiatric disorders––Autism Spectrum Disorder (ASD), Bipolar Disorder (BD), Mood Disorder (MDD), Schizoaffective (SCA), and Schizophrenia (SCZ)––show consistent neuroanatomical phenotypes by examining correlations between disorder- and site-specific maps of grey matter volume alterations.
Presenter
Trang Cao, Monash University Clayton, VIC
Australia
Dysregulated striatal function and executive control deficits are typically characterized in the development and perpetuation of cocaine addiction, as evidenced by animal models and human neuroimaging studies. Recently, connectome gradient-based approaches have emerged as a promising alternative to traditional parcellation-based methods for indicating continuous variations in neural organization across cortical and subcortical systems. These approaches pose huge potential in offering a novel perspective on elucidating dysfunction of striatum in cocaine addiction. Here we systematically examined the abnormalities of intra-striatal and striatal-cerebral cortex functional connectome gradient in cocaine users and revealed the effect of repetitive transcranial magnetic stimulation (rTMS) on striatal function, to facilitate the understanding about functional connectome hierarchy of striatum in cocaine addiction and treatment targets.
Presenter
Ran Zhang, Southwest University Chongqing, China, Chongqing
China
Imaging meta-analyses of addiction have summarized symptom-brain region correspondence patterns, revealing diagnosis-specific and transdiagnostic effects [1]. However, group average differences are not representative of individual cases [2]. There are both clinical and neuroanatomical variabilities at the single-subject level in addiction, complicating it challenging to develop neuroimaging biomarkers to track disease severity, progression, and treatment response. Here we demonstrate through normative model [3] and lesion network mapping [4] techniques that regional gray matter atrophy patterns across patients with addiction are highly heterogeneous, yet these deviations can be embedded in common functional circuits and networks.
Presenter
Min Wang, University of Science and Technology of China
Department of Psychology
Hefei, Anhui
China
Substance use disorders are highly comorbid with other neuropsychiatric disorders and share with them widespread structural brain alterations (Eaton, Rodriguez-Seijas, Carragher, & Krueger, 2015; Mackey et al., 2019; Reich-Erkelenz, Schmitt, & Falkai, 2015). Previous work has shown that structural alterations across neuropsychiatric conditions are organized in a systematic fashion, linked to the intrinsic organization of the human connectome (Hettwer et al., 2022). However, to what extent similar coordinated co-alteration effects extend to substance use disorders remains to be established. Here, we investigated substance use co-alteration networks (pathological structural covariance) to elucidate concordant macroscale principles of illness and substance-use effects across the cortex.
Presenter
Sofie Valk, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig
Germany
Ketamine, an N-methyl-D-aspartate receptor (NMDAR) antagonist, produces rapid antidepressant effects in major depressive disorder (MDD). Recent investigations show that patients with MDD exhibit altered resting brain network dynamics that manifest as increased transitions between the central executive (CEN) and default mode (DMN) networks(Belleau et al., 2022), and increased dwell time in fronto-insular brain networks, which associate with rumination(Kaiser et al., 2019). We thus used Co-Activation Pattern (CAP) analysis(Liu et al., 2013) to determine how ketamine affects the dynamic properties of resting brain networks and the relationships with therapeutic effects in patients with treatment resistant depression (TRD).
Major depressive disorder (MDD) is one of the leading causes of disability worldwide (1) and is still insufficiently treated, with approximately one third of patients being treatment-resistent (2). Despite the societal relevance of depression and a plethora of research over the past decades, the neurobiological underpinnings of the disorder are still poorly understood. Previous neuroimaging studies have yielded highly heterogeneous results, even across large consortia (3–5) and effect sizes appear to be subtle at most (6). In addition, the validity of brain-behavior findings in general have been questioned due to reports of underpowered study samples, overestimated effect sizes and overall low replicability (7). These findings make it highly relevant to systematically investigate the replicability of the neural correlates of psychiatric disorders, such as depression and assess their generalizability to independent cohorts.
Presenter
Janik Goltermann, University of Münster
Institute for Translational Psychiatry
Münster, NRW, Germany
Germany