D-Index & Metrics Best Publications
Nicholas B. Turk-Browne

Nicholas B. Turk-Browne

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 45 Citations 10,690 211 World Ranking 3886 National Ranking 1765

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Cognition
  • Neuroscience

The scientist’s investigation covers issues in Neuroscience, Cognition, Cognitive psychology, Perception and Hippocampus. His work on Brain mapping, Neuroimaging and Functional neuroimaging as part of general Neuroscience research is often related to Neurofeedback, thus linking different fields of science. His Cognition research includes themes of Space, Cognitive science and Human brain.

His Cognitive psychology study combines topics from a wide range of disciplines, such as Reconstructive memory, Semantic memory, Episodic memory, Explicit memory and Visual cortex. His Perception research focuses on Visual perception in particular. Nicholas B. Turk-Browne combines subjects such as Hippocampal formation, Structure, Statistical learning and Prefrontal cortex with his study of Hippocampus.

His most cited work include:

  • A taxonomy of external and internal attention. (693 citations)
  • The Automaticity of Visual Statistical Learning (473 citations)
  • Neural evidence of statistical learning: Efficient detection of visual regularities without awareness (333 citations)

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

Nicholas B. Turk-Browne mainly focuses on Cognitive psychology, Neuroscience, Perception, Artificial intelligence and Visual cortex. The concepts of his Cognitive psychology study are interwoven with issues in Context, Statistical learning, Long-term memory and Episodic memory. His study in the fields of Hippocampal formation, Stimulus and Brain mapping under the domain of Neuroscience overlaps with other disciplines such as Neurofeedback.

His work is dedicated to discovering how Perception, Cognition are connected with Functional magnetic resonance imaging and other disciplines. His study looks at the relationship between Artificial intelligence and topics such as Pattern recognition, which overlap with Feature. His biological study spans a wide range of topics, including Space, Cognitive neuroscience of visual object recognition and Visual memory.

He most often published in these fields:

  • Cognitive psychology (41.20%)
  • Neuroscience (29.61%)
  • Perception (28.33%)

What were the highlights of his more recent work (between 2019-2021)?

  • Neuroscience (29.61%)
  • Cognitive psychology (41.20%)
  • Functional magnetic resonance imaging (10.73%)

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

His scientific interests lie mostly in Neuroscience, Cognitive psychology, Functional magnetic resonance imaging, Artificial intelligence and Perception. He has researched Cognitive psychology in several fields, including Cognitive development, Cognition, Cognitive neuroscience, Episodic memory and Motor skill. Nicholas B. Turk-Browne has included themes like Cluster analysis, Representation, Data set and Noise in his Cognition study.

As a part of the same scientific family, Nicholas B. Turk-Browne mostly works in the field of Episodic memory, focusing on Recall and, on occasion, Reminiscence and Neuroimaging. The various areas that Nicholas B. Turk-Browne examines in his Artificial intelligence study include Text mining, Natural language processing and Pattern recognition. His Perception research includes elements of Stimulus, Sensory system, Sensation, Cognitive science and Visual cortex.

Between 2019 and 2021, his most popular works were:

  • BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis (19 citations)
  • Re-imagining fMRI for awake behaving infants. (10 citations)
  • Statistical prediction of the future impairs episodic encoding of the present (8 citations)

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

  • Artificial intelligence
  • Cognition
  • Neuroscience

His main research concerns Neuroscience, Statistical learning, Hippocampus, Cognitive psychology and Encoding. The Hippocampal formation, Frontal regions, Anterior cingulate cortex and Fixation research Nicholas B. Turk-Browne does as part of his general Neuroscience study is frequently linked to other disciplines of science, such as Young infants, therefore creating a link between diverse domains of science. His research ties Cognition and Statistical learning together.

Many of his studies on Hippocampus involve topics that are commonly interrelated, such as Pattern recognition. His Cognitive psychology research incorporates themes from Functional magnetic resonance imaging, Neuroimaging, Episodic memory and Elementary cognitive task. Nicholas B. Turk-Browne interconnects Sequence, Cortex and Sequence learning in the investigation of issues within Encoding.

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

A taxonomy of external and internal attention.

Marvin M. Chun;Julie D. Golomb;Nicholas B. Turk-Browne.
Annual Review of Psychology (2011)

1230 Citations

The Automaticity of Visual Statistical Learning

Nicholas B. Turk-Browne;Justin A. Jungé;Brian J. Scholl.
Journal of Experimental Psychology: General (2005)

794 Citations

Interactions between attention and memory.

Marvin M Chun;Nicholas B Turk-Browne.
Current Opinion in Neurobiology (2007)

614 Citations

Neural evidence of statistical learning: Efficient detection of visual regularities without awareness

Nicholas B. Turk-Browne;Brian J. Scholl;Marvin M. Chun;Marcia K. Johnson.
Journal of Cognitive Neuroscience (2009)

502 Citations

Shaping of Object Representations in the Human Medial Temporal Lobe Based on Temporal Regularities

Anna C. Schapiro;Lauren V. Kustner;Nicholas B. Turk-Browne.
Current Biology (2012)

386 Citations

Implicit Perceptual Anticipation Triggered by Statistical Learning

Nicholas B. Turk-Browne;Brian J. Scholl;Marcia K. Johnson;Marvin M. Chun.
The Journal of Neuroscience (2010)

354 Citations

Neural representations of events arise from temporal community structure

Anna C Schapiro;Timothy T Rogers;Natalia I Cordova;Nicholas B Turk-Browne.
Nature Neuroscience (2013)

351 Citations

Closed-loop training of attention with real-time brain imaging

Megan T. DeBettencourt;Jonathan D. Cohen;Ray F. Lee;Kenneth Andrew Norman.
Nature Neuroscience (2015)

306 Citations

Attention Is Spontaneously Biased Toward Regularities

Jiaying Zhao;Naseem Al-Aidroos;Nicholas B. Turk-Browne.
Psychological Science (2013)

302 Citations

Linking Implicit and Explicit Memory: Common Encoding Factors and Shared Representations

Nicholas B. Turk-Browne;Do Joon Yi;Marvin M. Chun.
Neuron (2006)

284 Citations

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