The unique profile of strong and weak cognitive traits characterizing each individual is of a fundamental significance, yet their neurophysiological underpinnings remain elusive. Here, we present intracranial electroencephalogram (iEEG) measurements in humans pointing to resting-state cortical "noise" as a possible neurophysiological trait that limits visual recognition capacity. We show that amplitudes of slow (<1 Hz) spontaneous fluctuations in high-frequency power measured during rest were predictive of the patients' performance in a visual recognition 1-back task (26 patients, total of 1,389 bipolar contacts pairs). Importantly, the effect was selective only to task-related cortical sites. The prediction was significant even across long (mean distance 4.6 ± 2.8 days) lags. These findings highlight the level of the individuals' internal "noise" as a trait that limits performance in externally oriented demanding tasks.
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http://dx.doi.org/10.1016/j.celrep.2019.11.081 | DOI Listing |
Sensors (Basel)
January 2025
Department of Mechanical Engineering, College of Engineering, Imam Mohammad Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia.
Enhancing motor disability assessment and its imagery classification is a significant concern in contemporary medical practice, necessitating reliable solutions to improve patient outcomes. One promising avenue is the use of brain-computer interfaces (BCIs), which establish a direct communication pathway between users and machines. This technology holds the potential to revolutionize human-machine interaction, especially for individuals diagnosed with motor disabilities.
View Article and Find Full Text PDFBrain Sci
January 2025
Department of Computer Science, Georgia State University, Atlanta, GA 30302, USA.
Objective: Functional magnetic resonance imaging data pose significant challenges due to their inherently noisy and complex nature, making traditional statistical models less effective in capturing predictive features. While deep learning models offer superior performance through their non-linear capabilities, they often lack transparency, reducing trust in their predictions. This study introduces the Time Reversal (TR) pretraining method to address these challenges.
View Article and Find Full Text PDFPLoS Biol
January 2025
Carney Institute for Brain Science, Department of Cognitive & Psychological Sciences, Brown University, Providence, Rhode Island, United States of America.
The basal ganglia (BG) play a key role in decision-making, preventing impulsive actions in some contexts while facilitating fast adaptations in others. The specific contributions of different BG structures to this nuanced behavior remain unclear, particularly under varying situations of noisy and conflicting information that necessitate ongoing adjustments in the balance between speed and accuracy. Theoretical accounts suggest that dynamic regulation of the amount of evidence required to commit to a decision (a dynamic "decision boundary") may be necessary to meet these competing demands.
View Article and Find Full Text PDFInt J Audiol
January 2025
Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, Leiden, Netherlands.
Objective: Measuring listening effort using pupillometry is challenging in cochlear implant (CI) users. We assess three validated speech tests (Matrix, LIST, and DIN) to identify the optimal speech material for measuring peak-pupil-dilation (PPD) in CI users as a function of signal-to-noise ratio (SNR).
Design: Speech tests were administered in quiet and two noisy conditions, namely at the speech recognition threshold (0 dB re SRT), i.
J Exp Child Psychol
January 2025
Callier Center for Communication Disorders, University of Texas at Dallas, Richardson, TX 75080, USA; Center for Children and Families, University of Texas at Dallas, Richardson, TX 75080, USA.
It has been proposed that a childhood in a noisy household might lead to poor language skills and slow development of language areas of the brain. Notably, a direct link between noisy households and language development has not been confirmed. Households might have high levels of noise for a range of reasons, including situational (near a large road intersection or airport), family (large families), and cultural (differences in beliefs surrounding noise in the home, including media use).
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