ReviewFrontiers in neuroscience2021
Linear Modeling of Neurophysiological Responses to Speech and Other Continuous Stimuli: Methodological Considerations for Applied Research.
Review in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
74 citing papers in PubMed.
- Linguistic information may compensate for age-related decline in attentional filtering.Communications biology · 2026Article
- Article
- Infant Cortical Tracking of Speech Shows Emerging Spatial Release from Masking in the First Year of Life.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Articulatory timing and form support distinct neural benefits during audiovisual speech.bioRxiv : the preprint server for biology · 2026Article
- Quantifying the Influence of Lexical Surprisal on Acoustic Speech Encoding While Controlling for Within-Speaker Variability.The European journal of neuroscience · 2026Article
- Magnetoencephalography in human neuroscience research: planning, piloting, implementation and quality assurance.Nature protocols · 2026Review
- Enhanced Time-Locked Decoding for Spoken Words but Not Environmental Sounds in Natural-Like Auditory Conditions.The European journal of neuroscience · 2026Article
- The Effect of Task Demand on EEG Responses to Irrelevant Sound and Speech in Simulated Surgical Environments.Psychophysiology · 2026Article
- Speech Neurophysiology in Realistic Contexts: Big Hype or Big Leap?The European journal of neuroscience · 2026Review
- Infant cortical tracking of speech shows emerging spatial release from masking in the first year of life.bioRxiv : the preprint server for biology · 2026Article
- Cortical speech envelope tracking reflects lesion-symptom profiles in post-stroke aphasia.Brain communications · 2026Article
- MEG-SCANS - A comprehensive magnetoencephalography speech dataset with Stories, Chirps and Noisy Sentences.Scientific data · 2025Article
- Attentional Engagement with Target and Distractor Streams Predicts Speech Comprehension in Multitalker Environments.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Linear modeling of brain activity during selective attention to continuous speech: the critical role of the N1 effect in event-related potentials to acoustic edges.Cognitive neurodynamics · 2025Article
- Neural Response Attenuates with Decreasing Inter-Onset Intervals Between Sounds in a Natural Soundscape.eNeuro · 2025Article
- Auditory and Semantic Processing of Speech-in-Noise in Autism: A Behavioral and EEG Study.Autism research : official journal of the International Society for Autism Research · 2025Article
- Personalized mapping of inhibitory spinal cord circuits in humans via noninvasive neural decoding and in silico modeling.Science advances · 2025Article
- Application of machine learning and temporal response function modeling of EEG data for differential diagnosis in primary progressive aphasia.Scientific reports · 2025Article
- Test-Retest Reliability of TRF-Derived Measures of Cortical Tracking of the Speech Envelope.eNeuro · 2025Article
- Attention, musicality, and familiarity shape cortical speech tracking at the musical cocktail party.Brain and language · 2025Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Cognitive neuroscience, in particular research on speech and language, has seen an increase in the use of linear modeling techniques for studying the processing of natural, environmental stimuli. The availability of such computational tools has prompted similar investigations in many clinical domains, facilitating the study of cognitive and sensory deficits under more naturalistic conditions. However, studying clinical (and often highly heterogeneous) cohorts introduces an added layer of complexity to such modeling procedures, potentially leading to instability of such techniques and, as a result, inconsistent findings. Here, we outline some key methodological considerations for applied research, referring to a hypothetical clinical experiment involving speech processing and worked examples of simulated electrophysiological (EEG) data. In particular, we focus on experimental design, data preprocessing, stimulus feature extraction, model design, model training and evaluation, and interpretation of model weights. Throughout the paper, we demonstrate the implementation of each step in MATLAB using the mTRF-Toolbox and discuss how to address issues that could arise in applied research. In doing so, we hope to provide better intuition on these more technical points and provide a resource for applied and clinical researchers investigating sensory and cognitive processing using ecologically rich stimuli.
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