D-Index & Metrics Best Publications

D-Index & Metrics

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 35 Citations 6,584 122 World Ranking 4237 National Ranking 1859

Overview

What is he best known for?

The fields of study he is best known for:

  • Neuroscience
  • Artificial intelligence
  • Statistics

Edmund C. Lalor mostly deals with Electroencephalography, Speech recognition, Artificial intelligence, Stimulus and Context. Edmund C. Lalor has researched Electroencephalography in several fields, including Evoked potential and Sensory system. His Speech recognition study integrates concerns from other disciplines, such as Neurophysiology, Speech perception, Perception and Communication.

His Artificial intelligence study combines topics in areas such as Semantic memory and Pattern recognition. Edmund C. Lalor has included themes like Developmental psychology, Electrophysiology, Oscillatory power and Alpha band in his Context study. His work on Brain mapping and Endophenotype is typically connected to Orbitofrontal cortex and Substance abuse as part of general Neuroscience study, connecting several disciplines of science.

His most cited work include:

  • Increases in Alpha Oscillatory Power Reflect an Active Retinotopic Mechanism for Distracter Suppression During Sustained Visuospatial Attention (513 citations)
  • Increases in Alpha Oscillatory Power Reflect an Active Retinotopic Mechanism for Distracter Suppression During Sustained Visuospatial Attention (513 citations)
  • Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG (385 citations)

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

Edmund C. Lalor focuses on Electroencephalography, Speech recognition, Neuroscience, Stimulus and Speech processing. His Electroencephalography research integrates issues from Evoked potential, Audiology, Communication, Cognition and Sensory system. The Evoked potential study which covers Artificial intelligence that intersects with Computer vision.

His Speech recognition research includes themes of Multisensory integration, Perception, Active listening, Auditory cortex and Decoding methods. His Speech processing study incorporates themes from Speech perception, Feature, Speech coding and Information processing. The Electrophysiology study combines topics in areas such as Developmental psychology and Visual field.

He most often published in these fields:

  • Electroencephalography (99.37%)
  • Speech recognition (64.56%)
  • Neuroscience (37.34%)

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

  • Speech recognition (64.56%)
  • Electroencephalography (99.37%)
  • Speech processing (30.38%)

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

Edmund C. Lalor mainly investigates Speech recognition, Electroencephalography, Speech processing, Active listening and Context. His study in Speech recognition is interdisciplinary in nature, drawing from both Sound, Multisensory integration and Auditory cortex. Edmund C. Lalor carries out multidisciplinary research, doing studies in Electroencephalography and Envelope.

His Speech processing research is multidisciplinary, incorporating elements of Feature, Neuroimaging and Magnetoencephalography. His Active listening research focuses on Perception and how it connects with Motor speech, Rule-based machine translation, Sensory system, Encoding and Language model. His Context research incorporates elements of Cognitive psychology, Word order, Natural language processing, Comprehension and Semantic data model.

Between 2019 and 2021, his most popular works were:

  • Where is the cocktail party? Decoding locations of attended and unattended moving sound sources using EEG. (13 citations)
  • Where is the cocktail party? Decoding locations of attended and unattended moving sound sources using EEG. (13 citations)
  • Dissociable electrophysiological measures of natural language processing reveal differences in comprehension strategy in healthy ageing (7 citations)

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

  • Neuroscience
  • Artificial intelligence
  • Statistics

Speech recognition, Electroencephalography, Speech processing, Stimulus and Encoding are his primary areas of study. The study incorporates disciplines such as Modulation and Sound in addition to Speech recognition. His work carried out in the field of Speech processing brings together such families of science as Intelligibility and Cochlea.

His studies in Stimulus integrate themes in fields like Auditory cortex, Speech comprehension, Cocktail party effect, Decoding methods and Headphones. Edmund C. Lalor combines subjects such as Representation, Feature, Speech Acoustics and Focus with his study of 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

Increases in Alpha Oscillatory Power Reflect an Active Retinotopic Mechanism for Distracter Suppression During Sustained Visuospatial Attention

Simon P. Kelly;Edmund C. Lalor;Edmund C. Lalor;Richard B. Reilly;Richard B. Reilly;John J. Foxe.
Journal of Neurophysiology (2006)

621 Citations

Steady-state VEP-based brain-computer interface control in an immersive 3D gaming environment

E. C. Lalor;S. P. Kelly;C. Finucane;R. Burke.
EURASIP Journal on Advances in Signal Processing (2005)

523 Citations

Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG

James A. O'Sullivan;Alan J. Power;Nima Mesgarani;Siddharth Rajaram.
Cerebral Cortex (2015)

455 Citations

Adolescent impulsivity phenotypes characterized by distinct brain networks.

Robert Whelan;Patricia J Conrod;Patricia J Conrod;Jean-Baptiste Poline;Anbarasu Lourdusamy.
Nature Neuroscience (2012)

394 Citations

Low-Frequency Cortical Entrainment to Speech Reflects Phoneme-Level Processing

Giovanni M. Di Liberto;James A. O’Sullivan;Edmund C. Lalor.
Current Biology (2015)

342 Citations

Visual spatial attention tracking using high-density SSVEP data for independent brain-computer communication

S.P. Kelly;E.C. Lalor;R.B. Reilly;J.J. Foxe.
international conference of the ieee engineering in medicine and biology society (2005)

273 Citations

The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli

Michael J. Crosse;Michael J. Crosse;Giovanni M. Di Liberto;Adam Bednar;Adam Bednar;Edmund C. Lalor;Edmund C. Lalor.
Frontiers in Human Neuroscience (2016)

271 Citations

Visual spatial attention control in an independent brain-computer interface

S.P. Kelly;E.C. Lalor;C. Finucane;G. McDarby.
IEEE Transactions on Biomedical Engineering (2005)

228 Citations

Neural responses to uninterrupted natural speech can be extracted with precise temporal resolution.

Edmund C. Lalor;John J. Foxe;John J. Foxe;John J. Foxe.
European Journal of Neuroscience (2010)

206 Citations

Electrophysiological Correlates of Semantic Dissimilarity Reflect the Comprehension of Natural, Narrative Speech

Michael P. Broderick;Andrew J. Anderson;Giovanni M. Di Liberto;Giovanni M. Di Liberto;Giovanni M. Di Liberto;Michael J. Crosse;Michael J. Crosse.
Current Biology (2018)

178 Citations

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John J. Foxe

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Ernst Strüngmann Institute for Neuroscience

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