Ben Parrell, PhD – Slide of the Week

Ben Parrell, PhD - Slide of the Week

Title: The brain’s sensitivity to sensory error can be modulated by altering perceived variability

Legend: Figure 1. Experiment design. A. Schematic and examples of perturbations (inward and outward) applied to vowel formants during the exposure phase from a single representative participant. The formant values that the participant produced and heard are indicated by black and colored circles, respectively. The ellipses represent a 95% confidence interval around the data points of the same color. All auditory formant perturbations were applied in mels, a logarithmic measure of frequency. B. Experimental procedure. Each participant completed three sessions, one for each of the three perturbations (inward, outward, control) applied during the exposure phase. Participants performed both a speaking task (“S”) and a listening task (“L”), grouped into blocks of 90 trials. The stimulus words were “ease”, “add” and “odd”, pseudo-randomized within each block. Figure 4. Modulation of Speaking-Induced Supression (SIS) across sessions (control, inward and outward). A. Source-localized auditory cortical time course aligned to sound onset during speaking (solid line) and listening (dotted line), shown separately before (baseline, left column) and after (test, right column) exposure to auditory perturbations. Shaded regions around the MEG traces indicate SEM across participants. B. SIS magnitudes across sessions obtained during baseline recording. C. Normalized SIS changes (%, calculated as 100*(SISbase −SIStest)/SISbase) across sessions. Group means are indicated by transparent colored bars. Connected points represent data from individual subjects. * indicates significance (p < 0.05).

Citation: Tang, D., Parrell, B., Beach, S. D., & Niziolek, C. A. (2023). The brain’s sensitivity to sensory error can be modulated by altering perceived variability (p. 2023.06.26.546615). bioRxiv.

Abstract: When individuals make a movement that produces an unexpected outcome, they learn from the resulting error. This process, essential in both acquiring new motor skills and adapting to changing environments, critically relies on error sensitivity, which governs how much behavioral change results from a given error. Although behavioral and computational evidence suggests error sensitivity can change in response to task demands, neural evidence regarding the flexibility of error sensitivity in the human brain is lacking. Critically, the sensitivity of the nervous system to auditory errors during speech production, a complex and well-practiced motor behavior, has been extensively studied by examining the prediction-driven suppression of auditory cortical activity. Here, we tested whether the nervous system’s sensitivity to errors, as measured by this suppression, can be modulated by altering speakers’ perceived variability. Our results showed that error sensitivity was increased after exposure to an auditory perturbation that increased participants’ perceived variability, consistent with predictions generated from previous behavioral data and state-space modeling. Conversely, we observed no significant changes in error sensitivity when perceived variability was unaltered or artificially reduced. The current study establishes the validity of behaviorally modulating the nervous system’s sensitivity to errors. As sensitivity to sensory errors plays a critical role in sensorimotor adaptation, modifying error sensitivity has the potential to enhance motor learning and rehabilitation in speech and, potentially, more broadly across motor domains.

Ben T. Parrell, PhD
Ben T. Parrell, PhD

Investigator: Ben Parrell, PhD

About the Lab: The Speech Motor Action + Control Lab investigates the human capacity to produce speech using behavioral, computation, and neurological methods. Our current projects focus on the role of the cerebellum in speech motor control and speech disorders associated with cerebellar damage by using computational models to understand the architecture of the speech motor system and investigating how speech motor control is updated and altered through various types of learning.

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