Psychoradiology最新文献

Background: Rumination is a pivotal psychopathological process in major depressive disorder (MDD). The neurotrophic hypothesis suggests that glial cell line-derived neurotrophic factor (GDNF) might play a role in brain dysfunction and clinical symptoms of MDD. However, the relationship remains unclear.

Methods: Thirty-three individuals with MDD and 33 healthy controls (HCs) underwent functional magnetic resonance imaging (fMRI) while performing a rumination state task designed to induce sustained, active rumination. The Ruminative Response Scale (RRS) was administered to assess individual rumination tendency. Brain activity within the default mode network (DMN) subsystems during rumination was characterized using both fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity (FC) analyses. Serum levels of GDNF and inflammatory markers [interleukin (IL)-6, IL-8, and C-reactive protein] were quantified in all participants. We then examined the relationships between regional brain activity (fALFF values), GDNF levels, and rumination severity (RRS scores) in the MDD group.

Results: Compared to HCs, MDD patients exhibited significantly reduced serum levels of both GDNF (t = -3.204, P = 0.002) and IL-8 (t = -3.239, P = 0.002). Significant interaction effects were observed in fALFF within both the dorsal medial prefrontal cortex (DMPFC; F = 25.075, P < 0.001) and medial temporal lobe (MTL; F = 28.753, P < 0.001) subsystems of the DMN. Mediation analysis revealed that the relationship between GDNF levels and brooding rumination in MDD patients was mediated by neural activity within the DMPFC subsystem.

Conclusions: In MDD patients, GDNF levels were associated with neural activity within the DMPFC subsystem of the DMN, which statistically mediated the link to rumination severity.

Background: We aimed to evaluate the relationship between cerebral white matter quantitative anomalies and postoperative clinical outcomes in patients with drug-resistant epilepsies.

Methods: Automatic fiber quantification methodology was used to determine the diffusional anomalies in cerebral white matter tracts, from eight patients with frontal lobe epilepsy (FLE) and 12 with temporal lobe epilepsy (TLE) candidates and/or undergoing epilepsy surgery. We studied the fractional anisotropy (FA), mean diffusivity (MD), volume (Vol), and number of fibers (Fib) of white matter tracts related to the physiopathologic mechanism of these epilepsies. The information was compared with that obtained from 19 healthy controls and between patients with seizure freedom and those with seizure recurrence 1 year after epilepsy surgery.

Results: Significant pre- and postsurgical global and segmental abnormalities were characterized by increased MD and decreased FA, Vol, and Fib in tracts from both hemispheres. TLE patients with postsurgical seizure freedom had preoperative increased global MD of the contralateral inferior longitudinal fasciculus and uncinate fasciculus. Furthermore, drug-resistant epilepsy patients with seizure freedom had a presurgical segmental increased MD in the contralateral thalamic radiation. Additionally, FLE patients with seizure freedom exhibited postsurgical increases in the Fib of the ipsilateral thalamic radiation and contralateral inferior longitudinal fasciculus. Furthermore, temporal lobe epilepsy patients with seizure freedom had a postsurgical lower global MD in the ipsilateral inferior fronto-occipital fasciculus.

Conclusions: Patients with drug-resistant epilepsies have global and segmental quantitative white matter tract anomalies, which suggests cerebral neural involvement in this disease. These abnormalities can vary regarding the postsurgical clinical outcome.

Mobile psychophysiological technologies, such as portable eye tracking, electroencephalography, and functional near-infrared spectroscopy, are advancing ecologically valid findings in cognitive and educational neuroscience research. Staying informed on the field's current status and main themes requires continuous updates. Here, we conducted a bibliometric and text-based content analysis on 135 articles from Web of Science, specifically parsing publication trends, identifying prolific journals, authors, institutions, and countries, along with influential articles, and visualizing the characteristics of cooperation among authors, institutions, and countries. Using a keyword co-occurrence analysis, five clusters of research trends were identified: (i) cognitive and emotional processes, intelligent education, and motor learning; (ii) professional vision and collaborative learning; (iii) face-to-face social learning and real classroom learning; (iv) cognitive load and spatial learning; and (v) virtual reality-based learning, child learning, and technology-assisted special education. These trends illustrate a consistent growth in the use of portable technologies in education over the past 20 years and an emerging shift towards "naturalistic" approaches, with keywords such as "face-to-face" and "real-world" gaining prominence. These observations underscore the need to further generalize the current research to real-world classroom settings and call for interdisciplinary collaboration between researchers and educators. Also, combining multimodal technologies and conducting longitudinal studies will be essential for a comprehensive understanding of teaching and learning processes.

Ex vivo magnetic resonance imaging (MRI) has revolutionized psychoradiological research by enabling detailed structural and pathological assessments of the brain in conditions ranging from psychiatric disorders to neurodegenerative diseases. By providing high-resolution images of postmortem brain tissue, ex vivo MRI overcomes several limitations inherent in in vivo imaging, offering unparalleled insights into the underlying pathophysiology of mental disorders. This review critically summarizes the state-of-the-art ex vivo MRI methodologies for neuroanatomical mapping and pathological characterization in psychoradiology, while also establishing standardized specimen processing protocols. Furthermore, we explore the prospects of application in ex vivo MRI in schizophrenia, major depressive disorder and bipolar disorder, highlighting its role in understanding neuroanatomical alterations, disease progression, and the validation of in vivo neuroimaging biomarkers.

Functional magnetic resonance imaging (fMRI) provides a powerful tool for studying brain function by capturing neural activity in a non-invasive manner. Mapping brain function from fMRI data enables researchers to investigate the spatial and temporal dynamics of neural processes, providing insights into how the brain responds to various tasks and stimuli. In this review, we explore the evolution of deep learning-based methods for brain function mapping using fMRI. We begin by discussing various network architectures such as convolutional neural networks, recurrent neural networks, and transformers. We further examine supervised, unsupervised, and self-supervised learning paradigms for fMRI-based brain function mapping, highlighting the strengths and limitations of each approach. Additionally, we discuss emerging trends such as fMRI embedding, brain foundation models, and brain-inspired artificial intelligence, emphasizing their potential to revolutionize brain function mapping. Finally, we delve into the real-world applications and prospective impact of these advancements, particularly in the diagnosis of neural disorders, neuroscientific research, and brain-computer interfaces for decoding brain activity. This review aims to provide a comprehensive overview of current techniques and future directions in the field of deep learning and fMRI-based brain function mapping.

Background: Emotion control represents a promising intervention target for mental disorders. In a recent study Bramson et al. (2023) demonstrate a functional-anatomical shift from the lateral frontal pole (FPl) to the dorsolateral prefrontal cortex (DLPFC) in anxious individuals during emotional action control. However, findings of neuroimaging experiments are often limited regarding generalizability and reproducibility. The present study examined the robustness of the reported functional shift across samples, cultures and paradigms.

Methods: We capitalized on large-scale task fMRI data (n = 250 participants) using an affective linguistic Go/NoGo paradigm to examine the anxiety-related shift between FPl and DLPFC during emotional action control. Additionally, context-dependent functional connectivity analyses were employed to examine anxiety-related differences and associations on the network level.

Results: Non-anxious individuals engaged the left FPl while highly anxious individuals specifically recruited the DLPFC, but non-significant between-group differences were found (see also Bramson et al.). The secondary analyses revealed moderate evidence for the absence of left FPl activation in the high-anxious as well as for left DLPFC activation in the non-anxious group. Additionally, trait anxiety scores were positively correlated with left DLPFC activity but negatively correlated with left FPl activity across groups. Furthermore, we found a context-specific connectivity shift between the subgenual anterior cingulate cortex (sgACC) with the FPl and DLPFC specifically in highly anxious individuals.

Conclusion: The results partially confirmed the anxiety-related shift as reported by Bramson and colleagues across paradigms and samples. The findings provide further support for the functional shift in anxiety and can inform target-based interventions of persistent emotional control deficits in anxiety disorders.

Background: Major depressive disorder (MDD) is a prevalent psychiatric disorder with disruptions in brain white matter (WM). While much research has focused on WM structure, the dysfunctional organization of WM in MDD remains poorly understood.

Methods: Using resting-state functional magnetic resonance imaging data from 48 MDD patients and 68 healthy controls (HC), we characterized the WM functional connectome gradients across participants and identified both global and regional alterations in MDD. Furthermore, we examined the relationship between gradient properties and depressive symptom severity. External validation and sensitivity analyses were finally conducted to ensure the reliability of results.

Results: The principal WM connectome gradient extended from the forceps major and superior longitudinal fasciculus to the uncinate fasciculus (UF) and anterior thalamic radiation (ATR), exhibiting a superficial-to-deep pattern in both groups. Compared to HC, MDD patients displayed a narrower gradient range and lower spatial variation, indicating a contracted WM hierarchy. At the tract-specific level, MDD patients exhibited lower gradient scores in the forceps minor, left ATR and UF, and bilateral cingulate gyrus and cingulum hippocampus, but higher gradient scores in the forceps major, bilateral inferior longitudinal fasciculus and superior longitudinal fasciculus. WM tract gradient patterns explained 37.2% of the variance in clinical severity, with the strongest contributions from the inferior fronto-occipital fasciculus, cingulum hippocampus, ATR, UF, and corticospinal tract.

Conclusions: These findings highlight altered WM functional connectome gradient in MDD and their association with clinical severity, offering novel insights into the neurobiological mechanisms of the disorder and potential biomarkers for symptom evaluation.

Background: Emotional symptomatology is a hallmark of depression. Antidepressant often fail to effectively target emotional blunting, while acupuncture, by contrast, has emerged as a promising alternative. However, the exact electrophysiologic mechanisms remain unclear. This study aimed to investigate how acupuncture influences emotional reactivity in youth with self-reported depressive symptoms.

Methods: A modified oddball paradigm incorporating a negative emotional valence deviant, combined with event-related potential analysis, was used to measure emotional reactivity before and after intervention. Seventy individuals exhibiting depressive symptoms in the previous 2 weeks, were randomly assigned to either a verum or sham acupuncture group. Electroencephalogram data from 59 participants were analyzed following preprocessing and quality assessment. Occipital P1, N170, frontal N1, N2, and parietal P3 components were extracted. The Positive and Negative Affect Schedule (PANAS) was completed after each oddball session. The Massachusetts General Hospital Acupuncture Sensation Scale (MASS) was completed after each intervention session.

Results: The MASS Index was significantly higher in the verum group. However, significant increases in occipital P1, N170, frontal N1, N2, and parietal P3 amplitudes for high-negative, mild-negative, and neutral pictures were observed after the intervention in both the verum and sham groups, with no significant difference between the groups. Additionally, both groups induced PANAS changes, and positive effect changes were significantly correlated with N170 and P1 (in response to high-negative pictures) changes in the sham group.

Conclusion: Acupuncture altered emotional reactivity in youth with depressive symptoms, highlighting its potential role, albeit possibly non-specific, in depression prevention and treatment.