Role of functional imaging in the development and refinement of invasive neuromodulation for psychiatric disorders

Deep brain stimulation(DBS) is emerging as a pow-erful tool for the alleviation of targeted symptoms in treatment-resistant neuropsychiatric disorders. Despite the expanding use of neuropsychiatric DBS, the mecha-nisms responsible for its effects are only starting to be elucidated. Several modalities such as quantitative elec-troencephalography as well a intraoperative recordings have been utilized to attempt to understand the under-pinnings of this new treatment modality, but functional imaging appears to offer several unique advantages. Functional imaging techniques like positron emission tomography, single photon emission computed tomog-raphy and functional magnetic resonance imaging have been used to examine the effects of focal DBS on activ-ity in a distributed neural network. These investigations are critical for advancing the field of invasive neuro-modulation in a safe and effective manner, particularly in terms of defining the neuroanatomical targets and refining the stimulation protocols. The purpose of this review is to summarize the current functional neuroim-aging findings from neuropsychiatric DBS implantation for three disorders: treatment-resistant depression, obsessive-compulsive disorder, and Tourette syndrome. All of the major targets will be discussed(Nucleus ac-cumbens, anterior limb of internal capsule, subcallosal cingulate, Subthalamic nucleus, Centromedial nucleus of the thalamus-Parafasicular complex, frontal pole, and dorsolateral prefrontal cortex). We will also address some apparent inconsistencies within this literature, and suggest potential future directions for this promis-ing area.

IN VIVO MAPPING BRAIN MICROCIRCULATION BY LASER SPECKLE CONTRAST IMAGING:A MAGNETIC RESONANCE PERSPECTIVE OF THEORETICAL FRAMEWORK

The fundamental limitations of most vascular-based functional neuroimaging techniques are placed by the fact how fine the brain regulates the blood supply system.In vivo mapping of the cerebral microcirculation with high resolution and sensitivity hence becomes unprecedentedly compelling.This paper reviews the theoretical background of the laser speckle contrast imaging(LSCI)technique and attempts to present a complete framework stemming from a simple biophysical model.Through the sensitivity analysis,more insights into the tool optimization are attained for in vivo applications.Open questions of the technical aspects are discussed within this unified framework.Finally,it concludes with a brief perspective of future research in a way analogous to the magnetic resonance imaging(MRI)technique.Such exploration could catalyze their development and initiate a technological fusion for precise assessment of blood flow across various spatial scales.

Modulatory effects of acupuncture on brain networks in mild cognitive impairment patients

Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.

通过深度神经网络与皮层网络的多级整合增强自然感知的神经编码模型

Cognitive neuroscience aims to develop computational models that can accurately predict and explain neural responses to sensory inputs in the cortex. Recent studies attempt to leverage the representation power of deep neural networks(DNNs) to predict the brain response and suggest a correspondence between artificial and biological neural networks in their feature representations. However, typical voxel-wise encoding models tend to rely on specific networks designed for computer vision tasks, leading to suboptimal brain-wide correspondence during cognitive tasks. To address this challenge, this work proposes a novel approach that upgrades voxel-wise encoding models through multi-level integration of features from DNNs and information from brain networks. Our approach combines DNN feature-level ensemble learning and brain atlas-level model integration, resulting in significant improvements in predicting whole-brain neural activity during naturalistic video perception. Furthermore, this multi-level integration framework enables a deeper understanding of the brain's neural representation mechanism, accurately predicting the neural response to complex visual concepts. We demonstrate that neural encoding models can be optimized by leveraging a framework that integrates both data-driven approaches and theoretical insights into the functional structure of the cortical networks.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research ？eld of Autism Spectrum Disorder（ASD）. Magnetic resonance imaging（MRI） provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation,connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and largescale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.