Speech Rhythms and Multiplexed Oscillatory Sensory Coding in the Human Brain

By Joachim Gross, Nienke Hoogenboom, Gregor Thut, Philippe G. Schyns, Stefano Panzeri, Pascal Belin, Simon Garrod. PLoS Biology, 2013

594 citations recorded by the source corpus.

A neuroimaging study reveals how coupled brain oscillations at different frequencies align with quasi-rhythmic features of continuous speech such as prosody, syllables, and phonemes.

Subfields: Cognitive Neuroscience, Signal Processing

View Paper: https://www.semanticscholar.org/paper/2686526f4e773584779c8aeec09cd90946ea590f

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Citations in the corpus

Active Inference: A Process Theory (2017, background): “Although this is a little fast for overt exploratory movements in a maze, it corresponds to the intervals between saccadic eye movements in visual exploration (Srihasam, Bullock, & Grossberg, 2009) and the rate at which syllables are articulated in normal speech (Gross et al., 2013).”
Distinct contributions of low- and high-frequency neural oscillations to speech comprehension (2017, methodology): “…Braun, & Poeppel, 2005; Ding & Simon, 2012, 2013a, 2013b; Ding, Melloni, Zhang, Tian, & Poeppel, 2016; Doelling, Arnal, Ghitza, & Poeppel, 2014; Gross et al., 2013; Kayser, Ince, Gross, & Kayser, 2015; Luo & Poeppel, 2012, 2007; Luo, Liu, & Poeppel, 2010; Millman, Johnson, & Prendergast,…”
The Encoding of Speech Sounds in the Superior Temporal Gyrus (2019, background): “Although there is evidence that the human auditory cortex activity entrains to the continuous amplitude envelope (Gross et al., 2013; Peelle and Davis, 2012), there are also data suggesting that encoding is”
The free energy principle made simpler but not too simple (2022, unknown): “Biologically, this may be a description of central pattern generators [110,117] that underwrite rhythmical activity (e.g., walking and talking) that is characteristic of biological systems [118].”
Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions. (2015, unknown): “Second, SO may directly modulate FO to deploy more processing resources (FO power) at the SO phases where the most relevant sensory information occurs (e.g., onset of odors in snif ﬁ ng episodes) and ﬁ lter out irrelevant stimuli arriving out of phase [5,92,93].”
A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula (2016, methodology): “Binned MI measured have already been applied to these sorts of problems [Belitski et al., 2010; Gross et al., 2013; Kayser et al., 2009; Schyns et al., 2011; Szymanski et al., 2011], and a number of other techniques have also been developed [Kempter et al., 2012; Lachaux et al., 1999; Voytek et…”
Neural population coding: combining insights from microscopic and mass signals (2015, background): “Experimental data and network models show that slow brain rhythms entrain to low-frequency variations of natural stimuli such as speech, directly inducing sensory information in the phase of these signals (e.g., [91,92,116,117]).”
Speech and music recruit frequency-specific distributed and overlapping cortical networks (2024, unknown): “Abbreviations according to the Brainnetome Atlas (Fan et al., 2016).”
Periodic and Aperiodic EEG Features as Potential Markers of Developmental Dyslexia (2023, background): “, prosodic) rhythms to achieve meaningful linguistic representations [68].”