Neuroscientist最新文献

Social anxiety disorder (SAD) is characterized by social anxiety/fear, self-attention, and interoception. Functional magnetic resonance imaging studies demonstrate increased activity during symptom-sensitive tasks in regions of the default-mode network (DMN), amygdala (AMG), and salience network (SN). What is the source of this task-unspecific symptom-sensitive hyperactivity in DMN? We address this question by probing SAD resting state (rs) changes in DMN including their relation to other regions as possible source of task-unspecific hyperactivity in the same regions. Our findings show the following: (1) rs-hypoconnectivity within-DMN regions; (2) rs-hyperconnectivity between DMN and AMG/SN; (3) task-evoked hyperactivity in the abnormal rs-regions of DMN and AMG/SN during different symptom-sensitive tasks; (4) negative relationship of rest and task changes in especially anterior DMN regions as their rs-hypoconnectivity is accompanied by task-unspecific hyperactivity; (5) abnormal top-down/bottom-up modulation between anterior DMN regions and AMG during rest and task. Findings demonstrate that rs-hypoconnectivity among DMN regions is negatively related to task-unspecific hyperactivity in DMN and AMG/SN. We propose a model of "Topography of the Anxious Self" in SAD (TAS-SAD). Abnormal DMN-AMG/SN topography during rest, as trait feature of an "unstable social self", is abnormally aggravated during SAD-sensitive situations resulting in task-related hyperactivity in the same regions with an "anxious self" as state feature.

Pliny the Elder was a prolific Roman author, naturalist, and military leader. Yet, his impact on modern-day neuroscience, psychiatry, and neurology has been little explored. Here, we aimed to trace the origins of our current understanding of the brain in ancient Rome through Pliny and his work, Natural History. As his magnum opus, this 37-book tome catalogs the facts and observations of natural life collected by Pliny, reflecting the knowledge of his time. Following the cephalocentric school of thought, Pliny places the brain as an agent for consciousness and details its diseases. Further, we explore Pliny's methods, which allow him to build a thorough collection of clinical descriptions and remedies. This body of work serves as an important lesson for future neuroscientists on the power of observation, the role of the humanities, and the necessity of understanding the origin of modern scientific thinking.

Multiple types of neural progenitor cells (NPCs) contribute to the development of the neocortex, a brain region responsible for our higher cognitive abilities. Proliferative capacity of NPCs varies among NPC types, developmental stages, and species. The higher proliferative capacity of NPCs in the developing human neocortex is thought to be a major contributing factor why humans have the most expanded neocortex within primates. Recent studies have shed light on the importance of cell metabolism in the neocortical NPC proliferative capacity. Specifically, glutaminolysis, a metabolic pathway that converts glutamine to glutamate and then to α-ketoglutarate, has been shown to play a critical role in human NPCs, both in apical and basal progenitors. In this review, we summarize our current knowledge of NPC metabolism, focusing especially on glutaminolysis, and discuss the role of NPC metabolism in neocortical development, evolution, and neurodevelopmental disorders, providing a broader perspective on a newly emerging research field.

Once strictly the domain of medical and graduate education, neuroscience has made its way into the undergraduate curriculum with over 230 colleges and universities now offering a bachelor's degree in neuroscience. The disciplinary focus on the brain teaches students to apply science to the understanding of human behavior, human interactions, sensation, emotions, and decision making. In this article, we encourage new and existing undergraduate neuroscience programs to envision neuroscience as a broad discipline with the potential to develop competencies suitable for a variety of careers that reach well beyond research and medicine. This article describes our philosophy and illustrates a broad-based undergraduate degree in neuroscience implemented at a major state university, Virginia Tech. We highlight the fact that the research-centered Experimental Neuroscience major is least popular of our four distinct majors, which underscores our philosophy that undergraduate neuroscience can cater to a different audience than traditionally thought.

Targeted optical neural stimulation comprises infrared neural stimulation and optogenetics, which affect the nervous system through induced thermal transients and activation of light-sensitive proteins, respectively. The main advantage of this pair of optical tools is high functional selectivity, which conventional electrical stimulation lacks. Over the past 15 years, the mechanism, safety, and feasibility of optical stimulation techniques have undergone continuous investigation and development. When combined with other methods like optical imaging and high-field functional magnetic resonance imaging, the translation of optical stimulation to clinical practice adds high value. We review the theoretical foundations and current state of optical stimulation, with a particular focus on infrared neural stimulation as a potential bridge linking optical stimulation to personalized medicine.

Background: Pancreatic cystic lesions (PCLs) are frequent and underreported incidental findings on computed tomography (CT) scans and can evolve to pancreatic cancer-the most lethal cancer, with less than 5 months of life expectancy.

Objective: The aim of this study was to develop and validate an artificial deep neural network (attention gate U-Net, also named "AGNet") for automated detection of PCLs. This kind of technology can help radiologists to cope with an increasing demand of cross-sectional imaging tests and increase the number of PCLs incidentally detected, thus increasing the early detection of pancreatic cancer.

Methods: We adapted and evaluated an algorithm based on an attention gate U-Net architecture for automated detection of PCL on CTs. A total of 335 abdominal CTs with PCLs and control cases were manually segmented in 3D by 2 radiologists with over 10 years of experience in consensus with a board-certified radiologist specialized in abdominal radiology. This information was used to train a neural network for segmentation followed by a postprocessing pipeline that filtered the results of the network and applied some physical constraints, such as the expected position of the pancreas, to minimize the number of false positives.

Results: Of 335 studies included in this study, 297 had a PCL, including serous cystadenoma, intraductal pseudopapillary mucinous neoplasia, mucinous cystic neoplasm, and pseudocysts . The Shannon Index of the chosen data set was 0.991 with an evenness of 0.902. The mean sensitivity obtained in the detection of these lesions was 93.1% (SD 0.1%), and the specificity was 81.8% (SD 0.1%).

Conclusions: This study shows a good performance of an automated artificial deep neural network in the detection of PCL on both noncontrast- and contrast-enhanced abdominal CT scans.