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Zoltán Vidnyánszky

Zoltán Vidnyánszky

D-Index & Metrics

Neuroscience

D-Index
31
Citations
3311
World Ranking
9586
National Ranking
58

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Neuroscience
  • Perception

Zoltán Vidnyánszky mainly focuses on Communication, Stimulus, Neuroscience, Cognitive psychology and Visual processing. His Communication research integrates issues from Motion, Color vision, Feature, N2pc and Tactile stimuli. His Stimulus research incorporates themes from Perception, Audiology, Categorization, Visual Physiology and Amygdala.

His Categorization research incorporates elements of Concept learning, Speech recognition, Insular cortex and Superior temporal sulcus. His Central nervous system and Fusiform face area study, which is part of a larger body of work in Neuroscience, is frequently linked to Subcellular localization, Postsynaptic potential and Metabotropic glutamate receptor, bridging the gap between disciplines. His Visual processing study combines topics in areas such as Face perception, Electrophysiology, fMRI adaptation and Brain mapping.

His most cited work include:

  • Electrophysiological Correlates of Visual Adaptation to Faces and Body Parts in Humans (184 citations)
  • Neural mechanisms for voice recognition (116 citations)
  • Neural mechanisms for voice recognition (116 citations)

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

Zoltán Vidnyánszky mostly deals with Neuroscience, Cognitive psychology, Stimulus, Artificial intelligence and Functional magnetic resonance imaging. The study incorporates disciplines such as Perceptual learning, Visual perception, Visual field and Face perception in addition to Cognitive psychology. Zoltán Vidnyánszky has included themes like Perception, Communication, Audiology, Speech recognition and Sensory system in his Stimulus study.

His research in Audiology focuses on subjects like Visual acuity, which are connected to Photic Stimulation. Zoltán Vidnyánszky combines subjects such as Resting state fMRI, Computer vision and Pattern recognition with his study of Artificial intelligence. His work deals with themes such as Neuroplasticity and Neuroimaging, which intersect with Functional magnetic resonance imaging.

He most often published in these fields:

  • Neuroscience (45.10%)
  • Cognitive psychology (39.22%)
  • Stimulus (47.06%)

What were the highlights of his more recent work (between 2014-2021)?

  • Cognitive psychology (39.22%)
  • Artificial intelligence (32.68%)
  • Functional magnetic resonance imaging (31.37%)

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

His primary areas of investigation include Cognitive psychology, Artificial intelligence, Functional magnetic resonance imaging, Resting state fMRI and Pattern recognition. His biological study spans a wide range of topics, including Stimulus, Visual field and Face perception. Zoltán Vidnyánszky has researched Stimulus in several fields, including Surprise and Visual cortex.

The Artificial intelligence study combines topics in areas such as Weighting and Cognition. He studied Functional magnetic resonance imaging and Neuroimaging that intersect with Deep learning. Within one scientific family, he focuses on topics pertaining to Connectome under Resting state fMRI, and may sometimes address concerns connected to Dynamic time warping.

Between 2014 and 2021, his most popular works were:

  • Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture. (46 citations)
  • Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture. (46 citations)
  • Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping (43 citations)

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

  • Artificial intelligence
  • Neuroscience
  • Perception

Zoltán Vidnyánszky spends much of his time researching Functional magnetic resonance imaging, Resting state fMRI, Artificial intelligence, Pattern recognition and Cognitive psychology. His study with Functional magnetic resonance imaging involves better knowledge in Neuroscience. His Cognitive psychology research includes themes of Gaze, Visual processing, Visual perception and Face perception.

His work in the fields of Face perception, such as Fusiform face area, overlaps with other areas such as Identity. His research investigates the connection with Gyrus and areas like Perception which intersect with concerns in Stimulus. His Stimulus study integrates concerns from other disciplines, such as Peripheral, Lateralization of brain function and Visual field.

Best Publications

  • Electrophysiological Correlates of Visual Adaptation to Faces and Body Parts in Humans

    Gyula Kovács;Márta Zimmer;Éva Bankó;Éva Bankó;Irén Harza;Irén Harza

  • Neural mechanisms for voice recognition

    Attila Andics;Attila Andics;James M. McQueen;Karl Magnus Petersson;Viktor Gál;Viktor Gál

  • Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

    Regina J. Meszlényi;Krisztian Buza;Zoltán Vidnyánszky;Zoltán Vidnyánszky

  • Implicit Attentional Selection of Bound Visual Features

    David Melcher;David Melcher;Thomas V. Papathomas;Zoltán Vidnyánszky;Zoltán Vidnyánszky

  • Cellular and subcellular localization of the mGluR5a metabotropic glutamate receptor in rat spinal cord.

    Zoltan Vidnyánszky;József Hamori;Lászlo Négyessy;Doris Rüegg

  • The use of CNN models in the subcortical visual pathway

    T. Roska;J. Hamori;E. Labos;K. Lotz

  • Direct current stimulation over MT+/V5 modulates motion aftereffect in humans.

    Andrea Antal;Edina T. Varga;Michael A. Nitsche;Zoltan Chadaide

  • Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping

    Regina Meszlényi;Regina Meszlényi;Petra Hermann;Krisztián Antal Buza;Viktor Gál

  • Immunocytochemical Visualization of the mG1uR1 a Metabotropic Glutamate Receptor at Synapses of Corticothalamic Terminals Originating from Area 17 of the Rat

    Zoltán Vidnyánszky;Tamás J. Görcs;László Négyessy;Zsolt Borostyánköi

  • Adaptation duration affects the spatial selectivity of facial aftereffects

    Gyula Kovács;Márta Zimmer;Irén Harza;Irén Harza;Zoltán Vidnyánszky;Zoltán Vidnyánszky

  • Position-specific and position-invariant face aftereffects reflect the adaptation of different cortical areas.

    Gyula Kovács;Csaba Cziraki;Csaba Cziraki;Zoltán Vidnyánszky;Zoltán Vidnyánszky;Stefan R. Schweinberger

  • Repetition Probability Does Not Affect fMRI Repetition Suppression for Objects

    Gyula Kovács;Gyula Kovács;Gyula Kovács;Daniel Kaiser;Daniel Kaiser;Dzmitry A. Kaliukhovich;Zoltán Vidnyánszky;Zoltán Vidnyánszky

  • Back-to-front: improved tactile discrimination performance in the space you cannot see.

    István Kóbor;László Füredi;Gyula Kovács;Charles Spence

  • Using diffusion MRI for measuring the temperature of cerebrospinal fluid within the lateral ventricles

    LR Kozak;M Bango;M Szabo;G Rudas

  • Dissociating the effect of noise on sensory processing and overall decision difficulty.

    Éva M. Bankó;Viktor Gál;Judit Körtvélyes;Gyula Kovács

  • Stimulus repetition probability effects on repetition suppression are position invariant for faces.

    Gyula Kovács;Lara Iffland;Zoltán Vidnyánszky;Zoltán Vidnyánszky;Mark W. Greenlee

  • Learning to suppress task-irrelevant visual stimuli with attention.

    Zoltán Vidnyánszky;Wonyeong Sohn

  • Position-specificity of facial adaptation.

    Gyula Kovács;Márta Zimmer;Irén Harza;Irén Harza;Andrea Antal

  • Attention-based perceptual learning increases binocular rivalry suppression of irrelevant visual features.

    Chris L E Paffen;Frans A J Verstraten;Zoltán Vidnyánszky

  • Smelling human sex hormone-like compounds affects face gender judgment of men.

    Gyula Kovács;Balázs Gulyás;Ivanka Savic;David I. Perrett

  • The use of CNN models in the subcortical visual pathway. (Reseach report of the Dual and Neural Computing Systems Laboratory DNS-16-1992)

    Tamás Roska;J. Hámori;E. Lábos;K. Lotz

Frequent Co-Authors

Gyula Kovács
Gyula Kovács Friedrich Schiller University Jena
David Melcher
David Melcher University of Trento
Andrea Antal
Andrea Antal University of Göttingen
Thomas Knöpfel
Thomas Knöpfel Hong Kong Baptist University
John T. Serences
John T. Serences University of California, San Diego
Mark W. Greenlee
Mark W. Greenlee University of Regensburg
Balázs Gulyás
Balázs Gulyás Nanyang Technological University
Karl Magnus Petersson
Karl Magnus Petersson University of Algarve
Frans A. J. Verstraten
Frans A. J. Verstraten University of Sydney
James M. McQueen
James M. McQueen Radboud University

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