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The study of brain networks, including derived from functional neuroimaging data, attracts broad interest and represents a rapidly growing interdisciplinary field. Comparing networks of healthy volunteers with those of patients can…

神经元与认知 · 定量生物学 2018-06-05 Emma K. Towlson , Petra E. Vértes , Ulrich Müller , Sebastian E. Ahnert

Modularity plays an important role in brain networks' architecture and influences its dynamics and the ability to integrate and segregate different modules of cerebral regions. Alterations in community structure are associated with several…

神经元与认知 · 定量生物学 2018-05-14 M. Cinelli , I. Echegoyen , M. Oliveira , S. Orellana , T. Gili

Network neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of…

Empirical studies over the past two decades have supported the hypothesis that schizophrenia is characterized by altered connectivity patterns in functional brain networks. These alterations have been proposed as genetically-mediated…

神经元与认知 · 定量生物学 2013-06-28 Felix Siebenhuhner , Shennan A. Weiss , Richard Coppola , Daniel R. Weinberger , Danielle S. Bassett

Accelerated brain aging has been consistently reported in patients with schizophrenia. Over the past decade, these findings have been replicated using the Brain Age paradigm, which applies machine learning techniques to estimate brain age…

Background: The choice of efficient antipsychotic therapy for schizophrenia relies on a time-consuming trial-and-error approach, whereas the social and economic burdens of the disease call for faster alternatives. Material \& methods: In a…

The human brain has a complex, intricate functional architecture. While many studies primarily emphasize pairwise interactions, delving into high-order associations is crucial for a comprehensive understanding of how functional brain…

神经元与认知 · 定量生物学 2023-10-30 Qiang Li , Vince D. Calhoun , Adithya Ram Ballem , Shujian Yu , Jesus Malo , Armin Iraji

Brain connectivity with functional Magnetic Resonance Imaging (fMRI) is a popular approach for detecting differences between healthy and clinical populations. Before creating a functional brain network, the fMRI time series must undergo…

神经元与认知 · 定量生物学 2020-02-20 A. M. Triana , E. Glerean , J. Saramäki , O. Korhonen

This paper reports nano-CT analysis of brain tissues of schizophrenia and control cases. The analysis revealed that: (1) neuronal structures vary between individuals, (2) the mean curvature of distal neurites of the schizophrenia cases was…

Social capital may help individuals maintain their mental health. Most empirical work based on small-scale surveys finds that bonding social capital and cohesive social networks are critical for mental well-being, while bridging social…

物理与社会 · 物理学 2023-11-27 Balazs Lengyel , Gergo Toth , Nicholas A. Christakis , Aniko Biro

Human mentality develops with age and is altered in psychiatric disorders, though their underlying mechanism is unknown. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of the anterior cingulate…

We have reported nanometer-scale three-dimensional studies of brain networks of schizophrenia cases and found that their neurites are thin and tortuous compared to healthy controls. This suggests that connections between distal neurons are…

图像与视频处理 · 电气工程与系统科学 2022-04-04 Ryuta Mizutani , Senta Noguchi , Rino Saiga , Yuichi Yamashita , Mitsuhiro Miyashita , Makoto Arai , Masanari Itokawa

Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and…

图像与视频处理 · 电气工程与系统科学 2022-07-08 Junhao Zhang , Vishwanatha M. Rao , Ye Tian , Yanting Yang , Nicolas Acosta , Zihan Wan , Pin-Yu Lee , Chloe Zhang , Lawrence S. Kegeles , Scott A. Small , Jia Guo

Schizophrenia and bipolar disorder are debilitating psychiatric illnesses that can be challenging to diagnose accurately. The similarities between the diseases make it difficult to differentiate between them using traditional diagnostic…

This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep network architectures. We analyzed and compared the most representative symptoms…

神经元与认知 · 定量生物学 2019-11-22 Pablo Lanillos , Daniel Oliva , Anja Philippsen , Yuichi Yamashita , Yukie Nagai , Gordon Cheng

Schizophrenia is a debilitating, chronic mental disorder that significantly impacts an individual's cognitive abilities, behavior, and social interactions. It is characterized by subtle morphological changes in the brain, particularly in…

计算机视觉与模式识别 · 计算机科学 2024-09-04 Nagur Shareef Shaik , Teja Krishna Cherukuri , Vince Calhoun , Dong Hye Ye

Most humans have the good fortune to live their lives embedded in richly structured social groups. Yet, it remains unclear how humans acquire knowledge about these social structures to successfully navigate social relationships. Here we…

神经元与认知 · 定量生物学 2019-04-23 Steven H. Tompson , Ari E. Kahn , Emily B. Falk , Jean M. Vettel , Danielle S. Bassett

Modeling dose-response relationships of drugs is essential to understanding their effect on patient outcomes under realistic circumstances. While intention-to-treat analyses of clinical trials provide the effect of assignment to a…

应用统计 · 统计学 2018-02-15 Jacob Spertus , Marcela Horvitz-Lennon , Sharon-Lise Normand

The cerebral cortex is composed of multiple cortical areas that exert a wide variety of brain functions. Although human brain neurons are genetically and areally mosaic, the three-dimensional structural differences between neurons in…

Objective: To identify if whole-brain structural network alterations in patients with temporal lobe epilepsy (TLE) and focal to bilateral tonic-clonic seizures (FBTCS) differ from alterations in patients without FBTCS. Methods: We…

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