Neural Connectivity Evolution during Adaptive Learning with and without Proprioception

Bokadia, Harshit; Cole, Jonathan; Torres, Elizabeth B.

doi:10.1145/3401956.3404232

“…In recent years, we have learned about the central processing of movement-related reafference from a special participant (Ian Waterman, IW) who experienced a viral infection that killed the afferent fibers for light-touch, pressure, and movements. The infection spared the afferent fibers for pain and temperature [ 24 , 25 , 26 ]. IW has remastered motor control in the absence of proprioception and kinesthetic reafferent information, by sensory substituting with vision the senses of touch, pressure, and movement [ 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

“…IW has remastered motor control in the absence of proprioception and kinesthetic reafferent information, by sensory substituting with vision the senses of touch, pressure, and movement [ 27 , 28 ]. Perhaps using information about his central processing of peripheral activity during resting state [ 24 ], could help us develop new models of statistical inference and interpretations for use in other data sets. His case could help us interpret resting-state data from centrally processed sensory information in other patient populations with sensory processing dysfunctions mediated by disruptions in peripheral reafferent flow [ 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity

Ryu

¹

,

Bar-Shalita

²

,

Granovsky

³

et al. 2021

JPM

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The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

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“…In recent years, we have learned about the central processing of movement-related reafference from a special participant (Ian Waterman, IW) who experienced a viral infection that killed the afferent fibers for light-touch, pressure, and movements. The infection spared the afferent fibers for pain and temperature [24][25][26]. IW has remastered motor control in the absence of proprioception and kinesthetic reafferent information, by sensory substituting with vision the senses of touch, pressure, and movement [27,28].…”

Section: Introductionmentioning

confidence: 99%

Personalized Biometrics of Physical Pain Agree with Its Psychological Perception by Participants with Sensory Over Responsivity

Ryu¹,

Bar-Shalita²,

Granovsky³

et al. 2020

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0

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The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

show abstract

Connecting movement and cognition through different modes of learning

Torres

¹

2022

Psychology of Learning and Motivation

0

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Neural Connectivity Evolution during Adaptive Learning with and without Proprioception

Cited by 3 publications

References 17 publications

Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity

Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity

Personalized Biometrics of Physical Pain Agree with Its Psychological Perception by Participants with Sensory Over Responsivity

Connecting movement and cognition through different modes of learning

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