| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Neuroscience | 278 | 19 | 21 | 11 |
Brain Informatics tackles a plethora of topics, such as Artificial intelligence, Pattern recognition, Machine learning, Electroencephalography and Cognition. The studies on Artificial intelligence discussed can also contribute to research in the domains of Brain activity and meditation and Computer vision. It facilitates discussions on Pattern recognition that incorporate concepts from other fields like Functional magnetic resonance imaging and Motor imagery.
The Machine learning works featured in it incorporate elements from Voxel and Neuroimaging. The concepts on Electroencephalography presented in Brain Informatics can also apply to other research fields, including Speech recognition and Epilepsy. It holds forums on Cognition that merges themes from other disciplines such as Cognitive psychology and Cognitive science.
Discussions in the journal are anchored in the subject of Cognitive psychology and the similar topic of Social psychology.
The journal publications cover a variety of subjects, including Artificial intelligence, Electroencephalography, Pattern recognition, Machine learning and Speech recognition. The journal publications facilitate discussions on Artificial intelligence that incorporate concepts from other fields like Magnetic resonance imaging, Disease and Computer vision. The most cited publications explore topics in Electroencephalography which can be helpful for research in disciplines like Valence (psychology) and Support vector machine.
The scientific interests tackled in Brain Informatics are Artificial intelligence, Pattern recognition, Electroencephalography, Neuroscience and Brain–computer interface. The featured works in Deep learning, F1 score and Recall rate, which all belong in the domain if Artificial intelligence, also overlaps with concepts under Tracing and Multiple species. Feature extraction are all disciplines of Pattern recognition that connect with topics in Smith–Waterman algorithm.
Some problems in Electroencephalography that were presented in it overlapped with concepts under Psychological intervention, Biometrics, Speech recognition, Support vector machine and Feature vector. In the journal, Context (language use), Disease and Behavioural genetics are investigated in conjunction with one another to address concerns in Neuroscience research. The research on Brain–computer interface featured in the journal combines topics in other fields like Physical medicine and rehabilitation, Neurotypical, Autism, Autism spectrum disorder and Anxiety.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Brain Informatics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Brain Informatics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 27.27% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 13.64% of all publications and 59.09% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
While most of the people associated with 'Brain Informatics' are researchers, there are also other career opportunities available in related fields. Some professionals opt to become speech therapists, which involves using cognitive techniques to improve the communications skills of their patients. This is highly relevant for individuals with brain-related disorders as their conditions typically impact their speech and language abilities.
For those interested in this field, there are specific academic and practical steps towards becoming a speech therapist. It should be noted that each state in the U.S. has its own requirements, for instance, the process to become a speech therapist in Illinois would differ from the process in other states. Therefore, individuals should carefully research the relevant requirements that apply to their situation.
However, in general, becoming speech therapist requires a master's degree in Speech-Language Pathology. In addition to their academic studies, students must also gain supervised clinical experience. After their program is completed, they must pass a national exam before receiving their state license and becoming a fully qualified speech therapist.
By choosing this career pathway, professionals can apply cutting-edge research from 'Brain Informatics' to address real-world problems and assist those with speech and language impairments. Such contributions are invaluable to the healthcare sector and to improving the overall quality of life for their patients.
Thus, 'Brain Informatics' is not only a field for abstract research, but it also holds pragmatic career opportunities and allows professionals to make a tangible impact in their communities.
Negar Ahmadi;Yulong Pei;Evelien Carrette;Albert P. Aldenkamp
(2020)Sakibur Rahman Sajal;Tanvir Ehsan;Ravi Vaidyanathan;Shouyan Wang
(2020)Avirath Sundaresan;Brian Penchina;Sean Cheong;Victoria Grace;Victoria Grace
(2021)Kayvan Bijari;Masood A. Akram;Giorgio A. Ascoli
(2020)Marcos Fabietti;Mufti Mahmud;Ahmad Lotfi;M. Shamim Kaiser
(2021)D. Rangaprakash;D. Rangaprakash;Toluwanimi Odemuyiwa;D. Narayana Dutt;Gopikrishna Deshpande
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