Research Database
Curated neuroscience and AI research papers
Showing 20 of 110 papers
A systematic review and meta-analysis of the fMRI investigation of autism spectrum disorders.
Philip, Ruth C M; Dauvermann, Maria R; Whalley, Heather C; Baynham, Katie; Lawrie, Stephen M et al.
Recent years have seen a rapid increase in the investigation of autism spectrum disorders (ASD) through the use of functional magnetic resonance imaging (fMRI). We carried out a systematic review and...
Human neuroimaging: fMRI.
Wall, Matthew B; Carhart-Harris, Robin L
Human neuroimaging with functional Magnetic Resonance Imaging has been a key feature of the current wave of psychedelic research, in both healthy and clinical populations. The available data has...
Pitfalls in FMRI.
Haller, Sven; Bartsch, Andreas J
Several different techniques allow a functional assessment of neuronal activations by magnetic resonance imaging (fMRI). The by far most influential fMRI technique is based on a local T2*-sensitive...
Brain-Computer Interface: Advancement and Challenges.
Mridha, M F; Das, Sujoy Chandra; Kabir, Muhammad Mohsin; Lima, Aklima Akter; Islam, Md Rashedul et al.
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the last decades, several...
Brain-Computer Interface, Neuromodulation, and Neurorehabilitation Strategies for Spinal Cord Injury.
Cajigas, Iahn; Vedantam, Aditya
As neural bypass interfacing, neuromodulation, and neurorehabilitation continue to evolve, there is growing recognition that combination therapies may achieve superior results. This article briefly...
Translational machine learning for psychiatric neuroimaging.
Walter, Martin; Alizadeh, Sarah; Jamalabadi, Hamidreza; Lueken, Ulrike; Dannlowski, Udo et al.
Despite its initial promise, neuroimaging has not been widely translated into clinical psychiatry to assist in the prediction of diagnoses, prognoses, and optimal therapeutic strategies. Machine...
How Machine Learning is Powering Neuroimaging to Improve Brain Health.
Singh, Nalini M; Harrod, Jordan B; Subramanian, Sandya; Robinson, Mitchell; Chang, Ken et al.
This report presents an overview of how machine learning is rapidly advancing clinical translational imaging in ways that will aid in the early detection, prediction, and treatment of diseases that...
Machine Learning With Neuroimaging: Evaluating Its Applications in Psychiatry.
Nielsen, Ashley N; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L; Greene, Deanna J
Psychiatric disorders are complex, involving heterogeneous symptomatology and neurobiology that rarely involves the disruption of single, isolated brain structures. In an attempt to better describe...
Machine learning with neuroimaging biomarkers: Application in the diagnosis and prediction of drug addiction.
Yang, Longtao; Du, Yanyao; Yang, Wenhan; Liu, Jun
Drug abuse is a serious problem worldwide. Owing to intermittent intake of certain substances and the early inconspicuous clinical symptoms, this brings huge challenges for timely diagnosing...
Connectomic mapping of brain-spinal cord neural networks: Future directions in assessing spinal cord injury at rest.
Zhang, Lijian; Wang, Luxuan; Xia, Hechun; Tan, Yanli; Li, Chunhui et al.
Following spinal cord injury (SCI), the central nervous system undergoes significant reconstruction. The dynamic change in the interaction of the brain-spinal cord axis as well as in...
Epilepsy as a disease affecting neural networks: a neurophysiological perspective.
San-Juan, D; Rodríguez-Méndez, D A
The brain is a series of networks of functionally and anatomically connected, bilaterally represented structures; in epilepsy, activity of any part of the brain affects activity in the other parts....
Gumbel-Softmax based Neural Architecture Search for Hierarchical Brain Networks Decomposition.
Pang, Tianji; Zhao, Shijie; Han, Junwei; Zhang, Shu; Guo, Lei et al.
Understanding the brain's functional architecture has been an important topic in the neuroimaging field. A variety of brain network modeling methods have been proposed. Recently, deep neural...
Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy.
Liu, Chia-Chen; Liu, Chia-Chan; Kanekiyo, Takahisa; Xu, Huaxi; Bu, Guojun
Apolipoprotein E (Apo-E) is a major cholesterol carrier that supports lipid transport and injury repair in the brain. APOE polymorphic alleles are the main genetic determinants of Alzheimer disease...
Machine learning with neuroimaging data to identify autism spectrum disorder: a systematic review and meta-analysis.
Song, Da-Yea; Topriceanu, Constantin-Cristian; Ilie-Ablachim, Denis C; Kinali, Maria; Bisdas, Sotirios
Autism Spectrum Disorder (ASD) is diagnosed through observation or interview assessments, which is time-consuming, subjective, and with questionable validity and reliability. Thus, we aimed to...
The evolving landscape of Alzheimer's disease therapy: From Aβ to tau.
Courade, Jean-Philippe; Zetterberg, Henrik; Höglinger, Günter U; Dewachter, Ilse
A marked evolution in Alzheimer's disease (AD) therapy research is ongoing. In this perspective, we highlight emerging outcomes of tau-targeting approaches with disease-modifying potential evidenced...
Emerging Opportunities for Advancing Cognitive Neuroscience.
Hasson, Uri; Nusbaum, Howard C
Cognitive neuroscience can be substantially advanced if structured mechanisms are created to increase its social impact and to develop synergies with some currently more distant disciplines that are...
Decoding Glioblastoma Heterogeneity: Neuroimaging Meets Machine Learning.
Fares, Jawad; Wan, Yizhou; Mayrand, Roxanne; Li, Yonghao; Mair, Richard et al.
Recent advancements in neuroimaging and machine learning have significantly improved our ability to diagnose and categorize isocitrate dehydrogenase (IDH)-wildtype glioblastoma, a disease...
Neuroethics and AI ethics: a proposal for collaboration.
Salles, Arleen; Farisco, Michele
The scientific relationship between neuroscience and artificial intelligence is generally acknowledged, and the role that their long history of collaboration has played in advancing both fields is...
Advances in brain-computer interface controlled functional electrical stimulation for upper limb recovery after stroke.
Zhang, Yidan; Gao, Yuling; Zhou, Jiaqi; Zhang, Zhenni; Feng, Min et al.
Stroke often results in varying degrees of functional impairment, significantly affecting patients' quality of daily life. In recent years, brain-computer interface-controlled functional electrical...
Retracted: Design of Financial Risk Control Model Based on Deep Learning Neural Network.
Neuroscience, Computational Intelligence And
[This retracts the article DOI: 10.1155/2022/5842039.].