Psychoradiology最新文献

Background: The hippocampus has been widely reported to be involved in the neuropathology of major depressive disorder (MDD). All the previous researches adopted group-level hippocampus subregions atlas to investigate abnormal functional connectivities in MDD in absence of capturing individual variability. In addition, the molecular basis of functional impairments of hippocampal subregions in MDD remains elusive.

Objective: We aimed to reveal functional disruptions and recovery of individual hippocampal subregions in MDD patients before and after ECT and linked these functional connectivity differences to transcriptomic profiles to reveal molecular mechanism.

Methods: we used group guided individual functional parcellation approach to define individual subregions of hippocampus for each participant. Resting-state functional connectivity (FC) analysis of individual hippocampal subregions was conducted to investigate functional disruptions and recovery in MDD patients before and after ECT. Spatial association between functional connectivity differences and transcriptomic profiles was employed to reveal molecular mechanism.

Results: MDD patients showed increased FCs of the left tail part of hippocampus with dorsolateral prefrontal cortex and middle temporal gyrus while decreased FC with primary visual cortex. These abnormal FCs in MDD patients were normalized after ECT. In addition, we found that functional disruptions of the left tail part of hippocampus in MDD were mainly related to synaptic signaling and transmission, ion transport, cell-cell signaling and neurogenesis.

Conclusion: Our findings provide initial evidence for functional connectome disruption of individual hippocampal subregions and their molecular basis in MDD.

Brain network control theory (NCT) is a groundbreaking field in neuroscience that employs system engineering and cybernetics principles to elucidate and manipulate brain dynamics. This review examined the development and applications of NCT over the past decade. We highlighted how NCT has been effectively utilized to model brain dynamics, offering new insights into cognitive control, brain development, the pathophysiology of neurological and psychiatric disorders, and neuromodulation. Additionally, we summarized the practical implementation of NCT using the nctpy package. We also presented the doubts and challenges associated with NCT and efforts made to provide better empirical validations and biological underpinnings. Finally, we outlined future directions for NCT, covering its development and applications.

This review examines the methodological challenges and advancements in laminar functional magnetic resonance imaging (fMRI). With the advent of ultra-high-field MRI scanners, laminar fMRI has become pivotal in elucidating the intricate micro-architectures and functionalities of the human brain at a mesoscopic scale. Despite its profound potential, laminar fMRI faces significant challenges such as signal loss at high spatial resolution, limited specificity to laminar signatures, complex layer-specific analysis, the necessity for precise anatomical alignment, and prolonged acquisition times. This review discusses current methodologies, highlights typical challenges in laminar fMRI research, introduces innovative sequence and analysis methods, and outlines potential solutions for overcoming existing technical barriers. It aims to provide a technical overview of the field's current state, emphasizing both the impact of existing hurdles and the advancements that shape future prospects.

Background: The lack of clearly defined neuromodulation targets has contributed to the inconsistent results of real-time fMRI-based neurofeedback (rt-fMRI-NF) for the treatment of chronic pain. Functional neurosurgery (funcSurg) approaches have shown more consistent effects in reducing pain in patients with severe chronic pain.

Objective: This study aims to redefine rt-fMRI-NF targets for chronic pain management informed by funcSurg studies.

Methods: Based on independent systematic reviews, we identified the neuromodulation targets of the rt-fMRI-NF (in acute and chronic pain) and funcSurg (in chronic pain) studies. We then characterized the underlying functional networks using a subsample of the 7 T resting-state fMRI dataset from the Human Connectome Project. Principal component analyses (PCA) were used to identify dominant patterns (accounting for a cumulative explained variance >80%) within the obtained functional maps, and the overlap between these PCA maps and canonical intrinsic brain networks (default, salience, and sensorimotor) was calculated using a null map approach.

Results: The anatomical targets used in rt-fMRI-NF and funcSurg approaches are largely distinct, with the middle cingulate cortex as a common target. Within the investigated canonical rs-fMRI networks, these approaches exhibit both divergent and overlapping functional connectivity patterns. Specifically, rt-fMRI-NF approaches primarily target the default mode network (P value range 0.001-0.002) and the salience network (P = 0.002), whereas funcSurg approaches predominantly target the salience network (P = 0.001) and the sensorimotor network (P value range 0.001-0.023).

Conclusion: Key hubs of the salience and sensorimotor networks may represent promising targets for the therapeutic application of rt-fMRI-NF in chronic pain.

The prefrontal cortex (PFC) is a critical non-invasive brain stimulation (NIBS) target for treating depression. However, the alterations of brain activations post-intervention remain inconsistent and the clinical moderators that could improve symptomatic effectiveness are unclear. The study aim was to systematically review the effectiveness of NIBS on depressive symptoms targeting PFC in functional magnetic resonance imaging (fMRI) studies. In our study, we delivered a combined activation likelihood estimation (ALE) meta-analysis and meta-regression. Until November 2020, three databases (PubMed, Web of Science, EMBASE) were searched and 14 studies with a total sample size of 584 were included in the ALE meta-analysis; after NIBS, four clusters in left cerebrum revealed significant activation while two clusters in right cerebrum revealed significant deactivation (P < 0.001, cluster size >150 mm³). Eleven studies were statistically reanalyzed for depressive symptoms pre-post active-NIBS and the pooled effect size was very large [(d = 1.82, 95%CI (1.23, 2.40)]; significant moderators causing substantial heterogeneity (Chi squared = 75.25, P < 0.01; I ² = 87%) were detected through subgroup analysis and univariate meta-regression. Multivariate meta-regression was then conducted accordingly and the model suggested good fitness (Q = 42.32, P < 0.01). In all, NIBS targeting PFC balanced three core depressive-related neurocognitive networks (the salience network, the default mode network, and the central executive network); the striatum played a central role and might serve as a candidate treatment biomarker; gender difference, treatment-resistant condition, comorbidity, treatment duration, and localization all contributed to moderating depressive symptoms during NIBS. More high-quality, multi-center randomized controlled trails delivering personalized NIBS are needed for clinical practice in the future.

From July 20 to 22, 2024, the ISMRM Endorsed Workshop on MR for Psychiatry was held in Chengdu City, China. This prestigious event attracted numerous academic elites worldwide, and Professor Benjamin Becker from the University of Hong Kong was invited. On the morning of July 20, during the "Advances in MR Technology" session, Professor Becker delivered an engaging lecture entitled "Novel approaches to precision MRI-imaging of human emotion." His presentation was met with great enthusiasm and sparked lively discussions among the participants. Following the conference, the Psychoradiology journal interviewed Professor Becker. In the interview, Benjamin emphasized the significant role of interdisciplinary collaboration, spanning various fields including psychology, neuroscience, clinical medicine, biomedical engineering, and computer science. Professor Becker firmly believed that such collaboration was crucial for a deeper understanding of the brain and psychiatric disorders. Additionally, he highly valued the importance of international cooperation, especially in addressing global mental health issues and challenges related to psychiatric disorders.

Background: We reported a case of cervical invasive vagus nerve stimulation (iVNS) treatment for avoidant/restrictive food intake disorder (ARFID) in a patient with severe anxiety and depression. This patient was even given a critical illness notice during his hospitalization and all treatment efforts were failed.

Objective: We aimed to verfiy the effectiveness of iVNS in a patient with ARFID.

Methods: We first attempted to perform cervical iVNS in this case and then observed the changes in clinical scores. We also analyzed the alterations in brain magnetic resonance imaging characteristics before and after iVNS using multi-modal neuroimagings.

Results: After 18 days of iVNS (from 1 to 19 July 2023), the patient's clinical symptoms improved significantly and he rapidly gained 5 kg in weight. The brain functional characteristics of this patient tended toward those of the normal group. Functional connectivities of the medial of orbitalis prefrontal cortex returned to the normal range after iVNS.

Conclusion: This is a precedent for performing cervical iVNS in an ARFID patient. Brain neural activity can be modulated through iVNS. The observed improvements in clinical scores and positive changes in brain function validated the effectiveness of iVNS. This case study provides evidence that this intervention technique could be used to reduce the burden on more similar ARFID patients.

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are common stress-related psychiatric disorders. Genetic and neurobiology research has supported the viewpoint that PTSD and MDD may possess common and disorder-specific underlying mechanisms. In this systematic review, we summarize evidence for the similarities and differences in brain functional and structural features of MDD, PTSD, and their comorbidity, as well as the effects of extensively used therapies in patients with comorbid PTSD and MDD (PTSD + MDD). These functional magnetic resonance imaging (MRI) studies highlight the (i) shared hypoactivation in the prefrontal cortex during cognitive and emotional processing in MDD and PTSD; (ii) higher activation in fear processing regions including amygdala, hippocampus, and insula in PTSD compared to MDD; and (iii) distinct functional deficits in brain regions involved in fear and reward processing in patients with PTSD + MDD relative to those with PTSD alone. These structural MRI studies suggested that PTSD and MDD share features of reduced volume in focal frontal areas. The treatment effects in patients with PTSD + MDD may correlate with the normalization trend of structural alterations. Neuroimaging predictors of repetitive transcranial magnetic stimulation response in patients with PTSD + MDD may differ from the mono-diagnostic groups. In summary, neuroimaging studies to date have provided limited information about the shared and disorder-specific features in MDD and PTSD. Further research is essential to pave the way for developing improved diagnostic markers and eventually targeted treatment approaches for the shared and distinct brain alterations presented in patients with MDD and PTSD.

Background: Naturalistic stimuli, such as videos, can elicit complex brain activations. However, the intricate nature of these stimuli makes it challenging to attribute specific brain functions to the resulting activations, particularly for higher-level processes such as social interactions.

Objective: We hypothesized that activations in different layers of a convolutional neural network (VGG-16) would correspond to varying levels of brain activation, reflecting the brain's visual processing hierarchy. Additionally, we aimed to explore which brain regions would be linked to the deeper layers of the network.

Methods: This study analyzed functional MRI data from participants watching a cartoon video. Using a pre-trained VGG-16 convolutional neural network, we mapped hierarchical features of the video to different levels of brain activation. Activation maps from various kernels and layers were extracted from video frames, and the time series of average activation patterns for each kernel were used in a voxel-wise model to examine brain responses.

Results: Lower layers of the network were primarily associated with activations in lower visual regions, although some kernels also unexpectedly showed associations with the posterior cingulate cortex. Deeper layers were linked to more anterior and lateral regions of the visual cortex, as well as the supramarginal gyrus.

Conclusions: This analysis demonstrated both the potential and limitations of using convolutional neural networks to connect video content with brain functions, providing valuable insights into how different brain regions respond to varying levels of visual processing.