Spontaneous Fluctuations in Sensory Processing Predict Within-Subject Reaction Time Variability

Introducing the Intra-Individual Variability Hypothesis in Explaining Individual Differences in Language Development

PURPOSE

Response times (RTs) are commonly used in studying language acquisition. However, previous research utilizing RT in the context of language has largely overlooked the intra-individual variability (IIV) of RTs, which could hold significant information about the processes underlying language acquisition.

METHOD

We explored the association between language abilities and RT variability in visuomotor tasks using two data sets from previously published studies. The participants were 7- to 10-year-old children (n = 77).

RESULTS

Our results suggest that increased variability in RTs is associated with weaker language abilities. Specifically, this within-participant variability in visuomotor RTs, especially the proportion of unusually slow responses, predicted language abilities better than mean RTs, a factor often linked to language skills in past research.

CONCLUSIONS

Based on our findings, we introduce the IIV hypothesis in explaining individual differences in language development. According to our hypothesis, inconsistency in the timing of cognitive processes, reflected by increased IIV in RTs, degrades learning different aspects of language, and results in individual differences in language abilities. Future studies should further examine the relationship between IIV and language abilities, and test the extent to which the possible relationship is causal.

Establishing the relationship between subjective perception and neural responses: Insights from correlation analysis and representational similarity analysis

Exploring the relationship between sensory perception and brain responses holds important theoretical and clinical implications. However, commonly used methodologies like correlation analysis performed either intra- or inter- individually often yield inconsistent results across studies, limiting their generalizability. Representational similarity analysis (RSA), a method that assesses the perception-response relationship by calculating the correlation between behavioral and neural patterns, may offer a fresh perspective to reveal novel findings. Here, we delivered a series of graded sensory stimuli of four modalities (i.e., nociceptive somatosensory, non-nociceptive somatosensory, visual, and auditory) to/near the left or right hand of 107 healthy subjects and collected their single-trial perceptual ratings and electroencephalographic (EEG) responses. We examined the relationship between sensory perception and brain responses using within- and between-subject correlation analysis and RSA, and assessed their stability across different numbers of subjects and trials. We found that within-subject and between-subject correlations yielded distinct results: within-subject correlation revealed strong and reliable correlations between perceptual ratings and most brain responses, while between-subject correlation showed weak correlations that were vulnerable to the change of subject number. In addition to verifying the correlation results, RSA revealed some novel findings, i.e., correlations between behavioral and neural patterns were observed in some additional neural responses, such as "γ-ERS" in the visual modality. RSA results were sensitive to the trial number, but not to the subject number, suggesting that consistent results could be obtained for studies with relatively small sample sizes. In conclusion, our study provides a novel perspective on establishing the relationship between behavior and brain activity, emphasizing that RSA holds promise as a method for exploring this pattern relationship in future research.

Motor-induced oscillations in choice response performance

Recently, numerous studies have revealed 4-12 Hz fluctuations of behavioral performance in a multitude of tasks. The majority has utilized stimuli near detection threshold and observed related fluctuations in hit-rates, attributing these to perceptual or attentional processes. As neural oscillations in the 8-20 Hz range also feature prominently in cortical motor areas, they might cause fluctuations in the ability to induce responses, independent of attentional capabilities. Additionally, different effectors (e.g., the left versus right hand) might be cyclically prioritized in an alternating fashion, similar to the attentional sampling of distinct locations, objects, or memory templates. Here, we investigated these questions via a behavioral dense-sampling approach. Twenty-six participants performed a simple visual discrimination task using highly salient stimuli. We varied the interval between each motor response and the subsequent target from 330 to 1040 ms, and analyzed performance as a function of this interval. Our data show significant fluctuations of both RTs and sensitivity between 12.5 and 25 Hz, but no evidence for an alternating prioritization of left- versus right-hand responses. While our results suggest an impact of motor-related signals on performance oscillations, they might additionally be influenced by perceptual processes earlier in the processing hierarchy. In summary, we demonstrate that behavioral oscillations generalize to situations involving highly salient stimuli, closer to everyday life. Moreover, our work adds to the literature by showing fluctuations at a high speed, which might be a consequence of both low task difficulty and the involvement of sensorimotor rhythms.

Enhancing touch sensibility by sensory retraining in a sensory discrimination task via haptic rendering

Stroke survivors are commonly affected by somatosensory impairment, hampering their ability to interpret somatosensory information. Somatosensory information has been shown to critically support movement execution in healthy individuals and stroke survivors. Despite the detrimental effect of somatosensory impairments on performing activities of daily living, somatosensory training—in stark contrast to motor training—does not represent standard care in neurorehabilitation. Reasons for the neglected somatosensory treatment are the lack of high-quality research demonstrating the benefits of somatosensory interventions on stroke recovery, the unavailability of reliable quantitative assessments of sensorimotor deficits, and the labor-intensive nature of somatosensory training that relies on therapists guiding the hands of patients with motor impairments. To address this clinical need, we developed a virtual reality-based robotic texture discrimination task to assess and train touch sensibility. Our system incorporates the possibility to robotically guide the participants' hands during texture exploration (i.e., passive touch) and no-guided free texture exploration (i.e., active touch). We ran a 3-day experiment with thirty-six healthy participants who were asked to discriminate the odd texture among three visually identical textures –haptically rendered with the robotic device– following the method of constant stimuli. All participants trained with the passive and active conditions in randomized order on different days. We investigated the reliability of our system using the Intraclass Correlation Coefficient (ICC). We also evaluated the enhancement of participants' touch sensibility via somatosensory retraining and compared whether this enhancement differed between training with active vs. passive conditions. Our results showed that participants significantly improved their task performance after training. Moreover, we found that training effects were not significantly different between active and passive conditions, yet, passive exploration seemed to increase participants' perceived competence. The reliability of our system ranged from poor (in active condition) to moderate and good (in passive condition), probably due to the dependence of the ICC on the between-subject variability, which in a healthy population is usually small. Together, our virtual reality-based robotic haptic system may be a key asset for evaluating and retraining sensory loss with minimal supervision, especially for brain-injured patients who require guidance to move their hands.

Slow fluctuations in ongoing brain activity decrease in amplitude with ageing yet their impact on task-related evoked responses is dissociable from behavior

In humans, ageing is characterized by decreased brain signal variability and increased behavioral variability. To understand how reduced brain variability segregates with increased behavioral variability, we investigated the association between reaction time variability, evoked brain responses and ongoing brain signal dynamics, in young (N=36) and older adults (N=39). We studied the electroencephalogram (EEG) and pupil size fluctuations to characterize the cortical and arousal responses elicited by a cued go/no-go task. Evoked responses were strongly modulated by slow (<2 Hz) fluctuations of the ongoing signals, which presented reduced power in the older participants. Although variability of the evoked responses was lower in the older participants, once we adjusted for the effect of the ongoing signal fluctuations, evoked responses were equally variable in both groups. Moreover, the modulation of the evoked responses caused by the ongoing signal fluctuations had no impact on reaction time, thereby explaining why although ongoing brain signal variability is decreased in older individuals, behavioral variability is not. Finally, we showed that adjusting for the effect of the ongoing signal was critical to unmask the link between neural responses and behavior as well as the link between task-related evoked EEG and pupil responses.

A Dissociation of Attention, Executive Function and Reaction to Difficulty: Development of the MindPulse Test, a Novel Digital Neuropsychological Test for Precise Quantification of Perceptual-Motor Decision-Making Processes

Traditionally, neuropsychological testing has assessed processing speed and precision, closely related to the ability to perform high-order cognitive tasks. An individual making a decision under time pressure must constantly rebalance its speed to action in order to account for possible errors. A deficit in processing speed appears to be afrequent disorder caused by cerebral damage — but it can be hard to pinpoint the exact cause of the slowdown. It is therefore important to separate the perceptual-motor component of processing speed from the decision-time component. We present a technique to isolate Reaction Times (RTs): a short digital test to assess the decision-making abilities of individuals by gauging their ability to balance between speed and precision. Our hypothesis is that some subjects willaccelerate, and others slow down in the face of the difficulty. This pilot study, conducted on 83 neurotypical adult volunteers, used images stimuli. The test was designed to measure RTs and correctness. After learning release gesture, the subjects were presented with three tasks: a simple Reaction Time task, a Go/No-Go, and a complex Go/No-Go with 2 simultaneous Choices. All three tasks have in common a perceptual component and a motor response. By measuring the 3 reference points requiring attentional and executive processing, while progressively increasing the conceptual complexity of the task, we were able to compare the processing times for different tasks — thus calculating the deceleration specific to the reaction time linked to difficulty. We defined the difficulty coefficient of a task as being the ratio of the group average time of this task minus the base time/average time of the unit task minus the base time. We found that RTs can be broken down into three elementary, uncorrelated components: Reaction Time, Executive Speed, and Reaction to Difficulty (RD). We hypothesized that RD reflects how the subject reacts to difficulty by accelerating (RD < 0) or decelerating (RD > 0). Thus we provide here a first proof of concept: the ability to measure four axes of the speed-precision trade-off inherent in a subject’s fundamental decision making: perceptual-motor speed, executive speed, subject accuracy, and reaction to difficulty.

Understanding the unexplained: The magnitude and correlates of individual differences in residual variance

Behavioral and physiological ecologists have long been interested in explaining the causes and consequences of trait variation, with a focus on individual differences in mean values. However, the majority of phenotypic variation typically occurs within individuals, rather than among individuals (as indicated by average repeatability being less than 0.5). Recent studies have further shown that individuals can also differ in the magnitude of variation that is unexplained by individual variation or environmental factors (i.e., residual variation). The significance of residual variation, or why individuals differ, is largely unexplained, but is important from evolutionary, methodological, and statistical perspectives. Here, we broadly reviewed literature on individual variation in behavior and physiology, and located 39 datasets with sufficient repeated measures to evaluate individual differences in residual variance. We then analyzed these datasets using methods that permit direct comparisons of parameters across studies. This revealed substantial and widespread individual differences in residual variance. The magnitude of individual variation appeared larger in behavioral traits than in physiological traits, and heterogeneity was greater in more controlled situations. We discuss potential ecological and evolutionary implications of individual differences in residual variance and suggest productive future research directions.

Description and psychometric properties of a prototype to test tactile acuity in the neck

BACKGROUND

Clinical tools assessing tactile acuity in people with persistent pain have limitations. Therefore, a novel and semi-automated tool was developed: The Imprint Tactile Acuity Device (iTAD).

AIM

To describe the iTAD prototype and present the psychometric properties of its tactile acuity assessments: the localisation test, the orientation test and the overall score (mean of both tests).

METHOD

A test-retest design with fifty healthy participants was used to assess intra-rater reliability (ICC_(2.1)), internal consistency (ICC_(2.4)) and measurement error (SEM) of the three assessments (0-100% accuracy scores each) performed at the neck. Using a known-group comparison design, balanced by age and sex, scores of thirty individuals with persistent neck pain were compared to thirty healthy controls to determine construct validity.

RESULTS

The ICC_(2,1) and ICC_(2,4) were 0.60 and 0.78 for the localisation test, 0.66 and 0.77 for the orientation test, and 0.73 and 0.84 for the overall score. The SEMs were 9.0%, 8.1% and 6.0%, respectively. No fixed or proportional bias, or signs of heteroscedasticity were observed. Overall, no between group differences were observed (p = 0.49). In the male subgroup, however, the overall score was lower for people with neck pain than for healthy participants (mean difference (SE); 7.6% (2.5); p = 0.008).

DISCUSSION

The tactile acuity assessments of the iTAD demonstrate moderate reliability and good internal consistency. Measurement errors appear comparable to currently preferred methods. Clear construct validity was not established, but results may be biased by design issues of the prototype. Taken together, the iTAD shows promise but further fine-tuning is needed.

Subcortical Ischemic Vascular Cognitive Impairment: Insights from Reaction Time Measures

In this study, reaction time (RT), intraindividual variability (IIV), and errors, and the effects of practice and processing load upon such function, were compared in patients with subcortical ischemic vascular cognitive impairment (SIVCI) [n = 27] and cognitively healthy older adults (CH) [n = 26]. Compared to CH aging, SIVCI was characterized by a profile of significantly slowed RT, raised IIV, and higher error levels, particularly in the presence of distracting stimuli, indicating that the integrity and/or accessibility of the additional functions required to support high processing load, serial search strategies, are reduced in SIVCI. Furthermore, although practice speeded RT in SIVCI, unlike CH, practice did not lead to an improvement in IIV. This indicates that improvement in RT in SIVCI can in fact mask an abnormally high degree of IIV. Because IIV appears more related to disease, function, and health than RT, its status and potential for change may represent a particularly meaningful, and relevant, disease characteristic of SIVCI. Finally, a high level of within-group variation in the above measures was another characteristic of SIVCI, with such processing heterogeneity in patients with ostensibly the same diagnosis, possibly related to individual variation in pathological load. Detailed measurement of RT, IIV, errors, and practice effects therefore reveal a degree of functional impairment in brain processing not apparent by measuring RT in isolation.

Characterizing the brain's dynamical response from scalp-level neural electrical signals: a review of methodology development

The brain displays dynamical system behaviors at various levels that are functionally and cognitively relevant. Ample researches have examined how the dynamical properties of brain activity reflect the neural cognitive working mechanisms. A prevalent approach in this field is to extract the trial-averaged brain electrophysiological signals as a representation of the dynamical response of the complex neural system to external stimuli. However, the responses are intrinsically variable in latency from trial to trial. The variability compromises the accuracy of the detected dynamical response pattern based on trial-averaged approach, which may mislead subsequent modelling works. More accurate characterization of the brain's dynamical response incorporating single trial variability information is of profound significance in deepening our understanding of neural cognitive dynamics and brain's working principles. Various methods have been attempted to address the trial-to-trial asynchrony issue in order to achieve an improved representation of the dynamical response. We review the latest development of methodology in this area and the contribution of latency variability-based decomposition and reconstruction of dynamical response to neural cognitive researches.

Wearable Biomonitoring Platform for the Assessment of Stress and its Impact on Cognitive Performance of Firefighters: An Experimental Study

BACKGROUND

Stress is a complex process with an impact on health and performance. The use of wearable sensor-based monitoring systems offers interesting opportunities for advanced health care solutions for stress analysis. Considering the stressful nature of firefighting and its importance for the community's safety, this study was conducted for firefighters.

OBJECTIVES

A biomonitoring platform was designed, integrating different biomedical systems to enable the acquisition of real time Electrocardiogram (ECG), computation of linear Heart Rate Variability (HRV) features and collection of perceived stress levels. This platform was tested using an experimental protocol, designed to understand the effect of stress on firefighter's cognitive performance, and whether this effect is related to the autonomic response to stress.

METHOD

The Trier Social Stress Test (TSST) was used as a testing platform along with a 2-Choice Reaction Time Task. Linear HRV features from the participants were acquired using an wearable ECG. Self-reports were used to assess perceived stress levels.

RESULTS

The TSST produced significant changes in some HRV parameters (AVNN, SDNN and LF/HF) and subjective measures of stress, which recovered after the stress task. Although these short-term changes in HRV showed a tendency to normalize, an impairment on cognitive performance was found after performing the stress event.

CONCLUSION

Current findings suggested that stress compromised cognitive performance and caused a measurable change in autonomic balance. Our wearable biomonitoring platform proved to be a useful tool for stress assessment and quantification. Future studies will implement this biomonitoring platform for the analysis of stress in ecological settings.

Is reaction time an index of white matter connectivity during training?

Voelker et al. (this issue) discuss the idea of linking white matter (WM) plasticity to improved reaction time (RT) during training. While compelling, this argument has important confounds and should be taken with cautions. RT is constrained not only by the speed of signal transmission in WM, but also by the properties of synaptic and neural processing in cortical gray matter. It is still unclear to what extent RT variability could be explained by WM plasticity and cortical plasticity. Future studies should examine both WM plasticity and cortical plasticity in relation to RT changes, to fully understand the brain mechanisms underlying RT improvement during training.