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  1. Here, we combine network neuroscience and machine learning to reveal connections between the brain’s network structure and the emerging network structure of an artificial neural network. Specifically, we train...

    Authors: James M. Shine, Mike Li, Oluwasanmi Koyejo, Ben Fulcher and Joseph T. Lizier

    Citation: Brain Informatics 2021 8:26

    Content type: Research

    Published on:

  2. Magnetoencephalography (MEG) has been combined with machine learning techniques, to recognize the Alzheimer’s disease (AD), one of the most common forms of dementia. However, most of the previous studies are ...

    Authors: Su Yang, Jose Miguel Sanchez Bornot, Ricardo Bruña Fernandez, Farzin Deravi, KongFatt Wong-Lin and Girijesh Prasad

    Citation: Brain Informatics 2021 8:24

    Content type: Research

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  3. Alzheimer’s disease (AD) is a neurodegenerative brain pathology formed due to piling up of amyloid proteins, development of plaques and disappearance of neurons. Another common subtype of dementia like AD, Par...

    Authors: Ahsan Bin Tufail, Yong-Kui Ma, Qiu-Na Zhang, Adil Khan, Lei Zhao, Qiang Yang, Muhammad Adeel, Rahim Khan and Inam Ullah

    Citation: Brain Informatics 2021 8:23

    Content type: Brief Report

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  4. The ability to characterize muscle activities or skilled movements controlled by signals from neurons in the motor cortex of the brain has many useful implications, ranging from biomedical perspectives to brai...

    Authors: Tuan D. Pham

    Citation: Brain Informatics 2021 8:22

    Content type: Research

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  5. Interest in the studying of functional connections in the brain has grown considerably in the last decades, as many studies have pointed out that alterations in the interaction among brain areas can play a rol...

    Authors: Pierfrancesco Ambrosi, Mauro Costagli, Ercan E. Kuruoğlu, Laura Biagi, Guido Buonincontri and Michela Tosetti

    Citation: Brain Informatics 2021 8:19

    Content type: Research

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  6. The literature regarding the use of diffusion-tensor imaging-derived metrics in the evaluation of Parkinson’s disease (PD) is controversial. This study attempted to assess the feasibility of a deep-learning-ba...

    Authors: Junyan Sun, Ruike Chen, Qiqi Tong, Jinghong Ma, Linlin Gao, Jiliang Fang, Dongling Zhang, Piu Chan, Hongjian He and Tao Wu

    Citation: Brain Informatics 2021 8:18

    Content type: Research

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  7. Brain-inspired high-dimensional (HD) computing represents and manipulates data using very long, random vectors with dimensionality in the thousands. This representation provides great robustness for various cl...

    Authors: Michael Hersche, Stefan Lippuner, Matthias Korb, Luca Benini and Abbas Rahimi

    Citation: Brain Informatics 2021 8:16

    Content type: Research

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  8. Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different struc...

    Authors: Marcos Fabietti, Mufti Mahmud, Ahmad Lotfi, M. Shamim Kaiser, Alberto Averna, David J. Guggenmos, Randolph J. Nudo, Michela Chiappalone and Jianhui Chen

    Citation: Brain Informatics 2021 8:14

    Content type: Research

    Published on:

  9. Mental stress is a major individual and societal burden and one of the main contributing factors that lead to pathologies such as depression, anxiety disorders, heart attacks, and strokes. Given that anxiety d...

    Authors: Avirath Sundaresan, Brian Penchina, Sean Cheong, Victoria Grace, Antoni Valero-Cabré and Adrien Martel

    Citation: Brain Informatics 2021 8:13

    Content type: Research

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  10. Annually, over three million people in North America suffer concussions. Every age group is susceptible to concussion, but youth involved in sporting activities are particularly vulnerable, with about 6% of al...

    Authors: Kayvan Tirdad, Alex Dela Cruz, Alireza Sadeghian and Michael Cusimano

    Citation: Brain Informatics 2021 8:12

    Content type: Research

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  11. Memory, the process of encoding, storing, and maintaining information over time to influence future actions, is very important in our lives. Losing it, it comes with a great cost. Deciphering the biophysical m...

    Authors: Nikolaos Andreakos, Shigang Yue and Vassilis Cutsuridis

    Citation: Brain Informatics 2021 8:9

    Content type: Research

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  12. Multivariate prediction of human behavior from resting state data is gaining increasing popularity in the neuroimaging community, with far-reaching translational implications in neurology and psychiatry. Howev...

    Authors: Federico Calesella, Alberto Testolin, Michele De Filippo De Grazia and Marco Zorzi

    Citation: Brain Informatics 2021 8:8

    Content type: Research

    Published on:

  13. In this study, the relationship of orienting of attention, motor control and the Stimulus- (SDN) and Goal-Driven Networks (GDN) was explored through an innovative method for fMRI analysis considering all voxel...

    Authors: Carlos A. Mugruza-Vassallo, Douglas D. Potter, Stamatina Tsiora, Jennifer A. Macfarlane and Adele Maxwell

    Citation: Brain Informatics 2021 8:5

    Content type: Research

    Published on:

  14. The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A system...

    Authors: Frederic Alexandre

    Citation: Brain Informatics 2021 8:3

    Content type: Research

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  15. Seizure is an abnormal electrical activity of the brain. Neurologists can diagnose the seizure using several methods such as neurological examination, blood tests, computerized tomography (CT), magnetic resona...

    Authors: Athar A. Ein Shoka, Monagi H. Alkinani, A. S. El-Sherbeny, Ayman El-Sayed and Mohamed M. Dessouky

    Citation: Brain Informatics 2021 8:1

    Content type: Research

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  16. Cognitive regulation of emotion has been proven to be effective to take control the emotional responses. Some cognitive models have also been proposed to explain the neural mechanism that underlies this proces...

    Authors: Yang Yang, Xiaofei Zhang, Yue Peng, Jie Bai and Xiuya Lei

    Citation: Brain Informatics 2020 7:20

    Content type: Research

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  17. Various machine-learning classification techniques have been employed previously to classify brain states in healthy and disease populations using functional magnetic resonance imaging (fMRI). These methods ge...

    Authors: D. Rangaprakash, Toluwanimi Odemuyiwa, D. Narayana Dutt and Gopikrishna Deshpande

    Citation: Brain Informatics 2020 7:19

    Content type: Research

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  18. Since manual tracing is time consuming and the performance of automatic tracing is unstable, it is still a challenging task to generate accurate neuron reconstruction efficiently and effectively. One strategy ...

    Authors: Jian Yang, Yishan He and Xuefeng Liu

    Citation: Brain Informatics 2020 7:14

    Content type: Research

    Published on:

  19. By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovat...

    Authors: Rasoul Hekmati, Robert Azencott, Wei Zhang, Zili D. Chu and Michael J. Paldino

    Citation: Brain Informatics 2020 7:13

    Content type: Research

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  20. With the growing number of the aged population, the number of Parkinson’s disease (PD) affected people is also mounting. Unfortunately, due to insufficient resources and awareness in underdeveloped countries, ...

    Authors: Md. Sakibur Rahman Sajal, Md. Tanvir Ehsan, Ravi Vaidyanathan, Shouyan Wang, Tipu Aziz and Khondaker Abdullah Al Mamun

    Citation: Brain Informatics 2020 7:12

    Content type: Research

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  21. Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge M...

    Authors: Manan Binth Taj Noor, Nusrat Zerin Zenia, M Shamim Kaiser, Shamim Al Mamun and Mufti Mahmud

    Citation: Brain Informatics 2020 7:11

    Content type: Review

    Published on:

  22. Neuromarketing has become an academic and commercial area of interest, as the advancements in neural recording techniques and interpreting algorithms have made it an effective tool for recognizing the unspoken...

    Authors: Ferdousi Sabera Rawnaque, Khandoker Mahmudur Rahman, Syed Ferhat Anwar, Ravi Vaidyanathan, Tom Chau, Farhana Sarker and Khondaker Abdullah Al Mamun

    Citation: Brain Informatics 2020 7:10

    Content type: Review

    Published on:

  23. Interpretation of brain activity responses using motor imagery (MI) paradigms is vital for medical diagnosis and monitoring. Assessed by machine learning techniques, identification of imagined actions is hinde...

    Authors: D. F. Collazos-Huertas, A. M. Álvarez-Meza, C. D. Acosta-Medina, G. A. Castaño-Duque and G. Castellanos-Dominguez

    Citation: Brain Informatics 2020 7:8

    Content type: Research

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  24. This paper proposes a novel feature selection method utilizing Rényi min-entropy-based algorithm for achieving a highly efficient brain–computer interface (BCI). Usually, wavelet packet transformation (WPT) is...

    Authors: Md. Asadur Rahman, Farzana Khanam, Mohiuddin Ahmad and Mohammad Shorif Uddin

    Citation: Brain Informatics 2020 7:7

    Content type: Research

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  25. Epilepsy and psychogenic non-epileptic seizures (PNES) often show over-lap in symptoms, especially at an early disease stage. During a PNES, the electrical activity of the brain remains normal but in case of a...

    Authors: Negar Ahmadi, Yulong Pei, Evelien Carrette, Albert P. Aldenkamp and Mykola Pechenizkiy

    Citation: Brain Informatics 2020 7:6

    Content type: Research

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  26. In recent days, deep learning technologies have achieved tremendous success in computer vision-related tasks with the help of large-scale annotated dataset. Obtaining such dataset for medical image analysis is...

    Authors: Jyoti Islam and Yanqing Zhang

    Citation: Brain Informatics 2020 7:3

    Content type: Research

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  27. Research advancements in neuroscience entail the production of a substantial amount of data requiring interpretation, analysis, and integration. The complexity and diversity of neuroscience data necessitate th...

    Authors: Kayvan Bijari, Masood A. Akram and Giorgio A. Ascoli

    Citation: Brain Informatics 2020 7:2

    Content type: Research

    Published on:

  28. To improve the efficiency of the structural optimization design in truss calculation, an improved fruit fly optimization algorithm was proposed for truss structure optimization. The fruit fly optimization algo...

    Authors: Yancang Li and Muxuan Han

    Citation: Brain Informatics 2020 7:1

    Content type: Research

    Published on:

  29. It is important to identify brain-based biomarkers that progressively deteriorate from healthy to mild cognitive impairment (MCI) to Alzheimer’s disease (AD). Cortical thickness, amyloid-ß deposition, and grap...

    Authors: Sinan Zhao, D. Rangaprakash, Peipeng Liang and Gopikrishna Deshpande

    Citation: Brain Informatics 2019 6:8

    Content type: Research

    Published on:

  30. Alzheimer’s disease is the most common neurodegenerative disease and is characterized by the accumulation of amyloid-beta peptides leading to the formation of plaques and tau protein tangles in brain. These n...

    Authors: Samuel Iddi, Dan Li, Paul S. Aisen, Michael S. Rafii, Wesley K. Thompson and Michael C. Donohue

    Citation: Brain Informatics 2019 6:6

    Content type: Research

    Published on:

  31. While it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification...

    Authors: Christopher R. Madan

    Citation: Brain Informatics 2019 6:5

    Content type: Research

    Published on:

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Related books

15148

Brain Informatics and Health (Editors-in-Chief: Zhong, Ning, Kikinis, Ron; Series Editors: Cai, W., Müller, H., Onoe, H., Pujol, S., Yu, P.S.)