D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Neuroscience D-index 57 Citations 10,808 300 World Ranking 2620 National Ranking 26

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Neuroscience

His scientific interests lie mostly in Neuroscience, Resting state fMRI, Artificial intelligence, Cognition and Functional magnetic resonance imaging. As part of his studies on Neuroscience, he frequently links adjacent subjects like Artificial neural network. His study in Resting state fMRI is interdisciplinary in nature, drawing from both Hippocampus and Middle temporal gyrus.

The Artificial intelligence study combines topics in areas such as Set and Pattern recognition. Jianfeng Feng interconnects Temporal lobe, Epilepsy, Sensory system, Brain asymmetry and Mechanism in the investigation of issues within Cognition. His studies in Functional magnetic resonance imaging integrate themes in fields like Young adult, Schizophrenia, Prefrontal cortex and Clinical psychology.

His most cited work include:

  • Analyzing multiple nonlinear time series with extended Granger causality (285 citations)
  • Precision Measurement of the $\left({e}^{+}+{e}^{-} ight)$ Flux in Primary Cosmic Rays from 0.5 GeV to 1 TeV with the Alpha Magnetic Spectrometer on the International Space Station (243 citations)
  • Precision Measurement of the Boron to Carbon Flux Ratio in Cosmic Rays from 1.9 GV to 2.6 TV with the Alpha Magnetic Spectrometer on the International Space Station. (217 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Neuroscience, Artificial intelligence, Artificial neural network, Algorithm and Resting state fMRI. Many of his studies on Neuroscience involve topics that are commonly interrelated, such as Schizophrenia. His Artificial intelligence research includes elements of Machine learning and Pattern recognition.

The various areas that Jianfeng Feng examines in his Artificial neural network study include Inhibitory postsynaptic potential and Applied mathematics. His Orbitofrontal cortex research incorporates elements of Anterior cingulate cortex and Inferior frontal gyrus.

He most often published in these fields:

  • Neuroscience (47.49%)
  • Artificial intelligence (24.52%)
  • Artificial neural network (18.53%)

What were the highlights of his more recent work (between 2018-2021)?

  • Neuroscience (47.49%)
  • Orbitofrontal cortex (10.62%)
  • Schizophrenia (12.93%)

In recent papers he was focusing on the following fields of study:

Neuroscience, Orbitofrontal cortex, Schizophrenia, Artificial intelligence and Cognition are his primary areas of study. Anterior cingulate cortex, Resting state fMRI, Temporal cortex, Ventromedial prefrontal cortex and Cerebral cortex are the primary areas of interest in his Neuroscience study. His Resting state fMRI study combines topics from a wide range of disciplines, such as Functional magnetic resonance imaging and Functional connectivity.

The concepts of his Orbitofrontal cortex study are interwoven with issues in Inferior frontal gyrus, Cingulate cortex, Nucleus accumbens, Impulsivity and Precuneus. His Schizophrenia study incorporates themes from First episode, Neurocognitive, Cortex and Human Connectome Project. His work on Pattern recognition expands to the thematically related Artificial intelligence.

Between 2018 and 2021, his most popular works were:

  • COMPUTATIONAL NEUROSCIENCE: A COMPREHENSIVE APPROACH (163 citations)
  • Automated anatomical labelling atlas 3. (80 citations)
  • GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition (78 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Quantum mechanics

Jianfeng Feng mainly focuses on Neuroscience, Orbitofrontal cortex, Inferior frontal gyrus, Precuneus and Anterior cingulate cortex. His Neuroscience research includes themes of Computational model, Models of neural computation and Spike train. His research integrates issues of Temporal lobe and Cingulate cortex in his study of Orbitofrontal cortex.

Jianfeng Feng interconnects Longitudinal study, Resting state fMRI, Ventromedial prefrontal cortex and Insula in the investigation of issues within Inferior frontal gyrus. His studies deal with areas such as Functional magnetic resonance imaging, Default mode network and Impulsivity as well as Resting state fMRI. His research in Precuneus intersects with topics in Parahippocampal gyrus, Temporal cortex and Posterior cingulate.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Analyzing multiple nonlinear time series with extended Granger causality

Yonghong Chen;Yonghong Chen;Govindan Rangarajan;Govindan Rangarajan;Jianfeng Feng;Mingzhou Ding.
Physics Letters A (2004)

439 Citations

Precision Measurement of the $\left({e}^{+}+{e}^{-} ight)$ Flux in Primary Cosmic Rays from 0.5 GeV to 1 TeV with the Alpha Magnetic Spectrometer on the International Space Station

M. Aguilar;A. Piluso;A. Lebedev;U. Becker.
Physical Review Letters (2014)

399 Citations

Precision Measurement of the Boron to Carbon Flux Ratio in Cosmic Rays from 1.9 GV to 2.6 TV with the Alpha Magnetic Spectrometer on the International Space Station.

M. Aguilar;L. Ali Cavasonza;G. Ambrosi;L. Arruda.
Physical Review Letters (2016)

325 Citations

COMPUTATIONAL NEUROSCIENCE: A COMPREHENSIVE APPROACH

Jianfeng Feng.
(2020)

258 Citations

Partial Granger causality—Eliminating exogenous inputs and latent variables

Shuixia Guo;Anil K. Seth;Keith M. Kendrick;Cong Zhou.
Journal of Neuroscience Methods (2008)

244 Citations

Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders

Jie Zhang;Jie Zhang;Wei Cheng;Zhaowen Liu;Zhaowen Liu;Kai Zhang.
Brain (2016)

239 Citations

Depression Uncouples Brain Hate Circuit

H. Tao;Shuixia Guo;Tian Ge;Keith M. Kendrick.
Molecular Psychiatry (2013)

231 Citations

Autism: reduced connectivity between cortical areas involved in face expression, theory of mind, and the sense of self.

Wei Cheng;Edmund T. Rolls;Huaguang Gu;Jie Zhang.
Brain (2015)

220 Citations

Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression

Wei Cheng;Edmund T. Rolls;Jiang Qiu;Jiang Qiu;Wei Liu;Wei Liu.
Brain (2016)

203 Citations

Granger causality vs. dynamic Bayesian network inference: a comparative study

Cunlu Zou;Jianfeng Feng;Jianfeng Feng.
BMC Bioinformatics (2009)

182 Citations

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