Processing Speed Research Articles

Enhancing Big Data Processing Efficiency in AI-Based Healthcare Systems: A Comparative Analysis of Random Forest and Deep

This research focuses on optimizing the speed of Big Data processing using Artificial Intelligence (AI) in healthcare applications. The study integrates Random Forest (RF) and Deep Learning (DL) algorithms with cloud-based computing systems to improve data processing efficiency. The dataset includes both structured data, such as Electronic Health Records (EHR), and unstructured data, like medical images. The results show that RF performs better with structured data, achieving a lower Mean Squared Error (MSE) and higher R-squared (R²) than traditional methods. Meanwhile, DL achieves superior accuracy and Area Under the Curve (AUC) in processing unstructured data. By utilizing the distributed computing power of Spark on a cloud platform, the processing speed was significantly enhanced, as demonstrated by a statistically significant reduction in processing time (p < 0.05) observed through a t-test analysis comparing Spark-based computing with traditional methods. Despite these improvements, challenges such as data privacy and infrastructure costs remain. Despite these improvements, challenges such as data privacy and infrastructure costs remain. This research provides a robust framework for real-time healthcare data analysis, highlighting its potential to improve decision-making processes and patient outcomes in medical services.

Effects of increasing fitness through exercise training on language comprehension in monolingual and bilingual older adults: a randomized controlled trial

ABSTRACT Exercise training has been proposed to counteract age-related cognitive decline through improvements in cardiorespiratory fitness (CRF hypothesis). Research has focused on cognitive domains like attention and processing speed, and one cross-sectional study reported a positive relationship between CRF and language production in older adults. In a randomized controlled trial, we investigated whether these benefits could extend to language comprehension in healthy older adults, and whether bilinguals, for whom language processing is more costly, would exhibit greater benefits than monolinguals. Eighty older English monolinguals and 80 older Norwegian-English bilinguals were randomized into either a 6-month exercise training group or into a passive control group. We assessed CRF (VO2peak) and language comprehension (reaction times to spoken word monitoring) in first (L1, all participants) and second language (L2, bilinguals only), before and after the intervention. We found that monolinguals in the exercise group (compared to the control group) were faster in comprehension following the intervention. Moreover, this effect was mediated by exercise-induced increases in VO2peak, supporting the CRF hypothesis. This extends previous cross-sectional research and establishes a causal link between exercise training and speeded comprehension in older monolinguals. However, despite inducing increased VO2peak, exercise training did not affect bilingual (L1 or L2) comprehension, and bilinguals in both groups were slower after the intervention period. Exploratory analyses suggested that this slowing may be driven by participants with low L2 proficiency, but further research is needed to examine whether bilingual language processing is in fact unaffected by exercise training and its consequent improvements in CRF.

Interaction between serum inflammatory cytokines and brain-derived neurotrophic factor in cognitive function among first-episode schizophrenia patients

BACKGROUND The pathogenesis of cognitive impairment in schizophrenia (SCZ) remains unclear. Accumulating studies showed that inflammatory-immune dysregulation and altered brain derived neurotrophic factor (BDNF) levels play a crucial role in the psychopathology of SCZ. However, their association with cognitive dysfunction in first-episode SCZ patients has not been thoroughly investigated. AIM To explore the interaction effects between cognitive function and inflammatory cytokines and BDNF in first-episode SCZ. METHODS The current study is a cross-sectional case-control investigation that recruited 84 patients with first-episode SCZ (SCZ group) and 80 healthy controls (HCs group) at the Huzhou Third Municipal Hospital between August 2021 and September 2023. ELISA was employed to measure the serum levels of interleukin (IL)-1β, IL-4, IL-6, IL-10, and BDNF. The Chinese brief cognitive test (C-BCT) and the positive and negative syndrome scales were measured the severity of cognitive impairment and psychiatric symptoms. RESULTS Compared to the HC group, the SCZ group exhibited elevated IL-1β and IL-6 levels, decreased BDNF levels, and reduced C-BCT scores (all P < 0.001). In SCZ, BDNF was negatively correlated with IL-6 (r = -0.324, P < 0.05). Information processing speed was negatively correlated with IL-6 (r = -0.315, P < 0.05) and positively with BDNF (r = 0.290, P < 0.05); attention, working memory, comprehensive ability, and executive function were negatively correlated with IL-1β and IL-6 (all P < 0.05) and positively with BDNF (all P < 0.05). Multiple regression analysis showed IL-6 influenced C-BCT dimensions (β = -0.218 to -0.327, all P < 0.05); attention and executive ability were influenced by IL-1β (β = -0.199 to -0.261, all P < 0.05) ; comprehensive executive ability was influenced by BDNF (β = 0.209, P < 0.05) . CONCLUSION Our findings suggested that interrelationships between immune dysfunction and neurotrophic deficiency might underlie the pathological mechanisms of cognitive impairments in first-episode SCZ patients.

The effects of adrenal insufficiency and its treatment on cognition in an athlete with post-concussion syndrome

ABSTRACT Post-concussion Syndrome (PCS) describes persistent nonspecific neurological, cognitive and emotional symptoms following concussion. A young male presented to a sports concussion clinic with persistent symptoms post-injury. Neurocognitive testing found unexpected severe memory impairment. Blood tests for pituitary function returned low cortisol levels secondary to adrenal insufficiency (AI), which was immediately treated. Post-treatment and improvement of cortisol levels, repeat neuropsychology testing demonstrated reliable improvement in memory and processing speed test scores, commensurate with premorbid expectations. This case highlights the importance of a broad diagnostic approach to formulating unexpected persistent PCS symptoms, screening for AI in PCS cases, and completing neurocognitive testing.

Lifestyle, Cognition, and Disability Outcomes in Multiple Sclerosis: A Comprehensive Cohort Study

Background/Objectives: People with multiple sclerosis (MS) often experience sensory, psychomotor, and cognitive impairment, sphincter disturbances, and fatigue, which can affect their ability to perform work-related tasks, self-care, and daily activities. This study aimed to analyze the lifestyle changes, cognitive function, and disability outcomes over a seven-year follow-up period, exploring potential associations with predictive markers. Methods: At the end of the seven-year follow-up period, 32 participants returned for cognitive and clinical reassessment with the Twenty-Five-Foot Walk Test, Nine-Hole Peg Test, and Brief Repeatable Neuropsychological Battery. Lifestyle data were acquired via interviews regarding sleep quality, reading habits, technology use, physical activity levels, household responsibilities, and participation in leisure and cultural activities. Results: The occupational profile did not demonstrate significant changes, but 11 (34%) participants showed disability accumulation, and the number of relapses increased (p = 0.001). Over time, improvement was observed in verbal episodic memory and worsening in psychomotor speed. Better cognitive performance in mental agility was associated with higher levels of physical activity (p = 0.021) and technology use (p = 0.039). In addition, better cognition (verbal memory p = 0.038 and processing speed 0.015) and psychomotor speed (upper limbs p = 0.017 and lower limbs p = 0.003) and lower functional disability (p = 0.022) were associated with maintenance of household activities. Conclusions: The changes in verbal memory and psychomotor speed were more prominent over time, and verbal memory, psychomotor and processing speed, and mental agility were associated with good lifestyle habits, mainly household activities. The treatment strategies should include lifestyle changes and pharmacological interventions.

Do executive functions and processing speed mediate the relationship between socioeconomic status and educational achievement? Analysis of an observational birth cohort study

BackgroundThere are large and persistent social inequalities in children’s educational attainment, with children from more socioeconomically disadvantaged families consistently having lower attainment. Despite this being widely reported, the mechanisms underlying the association between socioeconomic disadvantage and educational attainment are not well understood. It is important to understand the potential mechanisms by which socioeconomic disadvantage may impede on educational outcomes, as this knowledge could then be used to help target possible interventions to improve educational outcomes for socioeconomically disadvantaged children. Children’s executive functions (including working memory and inhibition) and processing speed abilities may underlie these inequalities, however, the previous literature regarding this is limited. This study examined longitudinal mediating mechanisms between socioeconomic status (SES) and educational achievement, using a socioeconomically deprived and ethnically diverse cohort.MethodsData from the Born in Bradford longitudinal cohort study was analysed using Structural Equation Modelling (n = 4201; 28% White British, 56% Pakistani heritage, 16% Other; 54% Female). SES was measured before birth, executive functions and processing speed were measured in middle childhood (Mage=8.45 years), and educational achievement was obtained through educational records (Mage=10.85 years). All models adjusted for child gender, age, language ability, ethnicity, and mother immigration status.ResultsExecutive functions significantly mediated the association between SES and educational achievement (B = 0.109), whilst processing speed did not. Examination of executive function components revealed that working memory significantly mediated the associated between SES and educational achievement (B = 0.100), whilst inhibition did not. Working memory appeared to account for a large proportion (39%) of the total effect of SES on educational achievement.ConclusionsThese results, and the theoretical mechanisms linking working memory to educational achievement, both indicate the importance of finding ways to support children with working memory difficulties in the classroom. This is an important avenue for future research and may be useful for closing the socioeconomic gap in educational achievement.

Association between cognitive function, antioxidants, and clinical variables in Chinese patients with schizophrenia

ObjectiveCognitive dysfunction is a prevalent and intricate manifestation of schizophrenia (SCZ) that may be associated with distinct clinical factors and the presence of antioxidants, which relationship is unclear. The study aimed to investigate cognitive function and its influencing factors in Chinese patients with SCZ.MethodsA group of 133 patients with SCZ and 120 healthy controls (HCs) were recruited. The MATRICS Consensus Cognitive Battery (MCCB) was utilized to evaluate cognitive ability, and the Positive and Negative Syndrome Scale (PANSS) was used to assess clinical symptoms. Levels of plasma superoxide dismutase (SOD), serum albumin (ALB) and uric acid (UA) were assessed.ResultsCompared with HCs, patients with SCZ exhibited lower cognitive performance as indicated by MCCB scores, including the dimensions of speed of processing, attention/vigilance, working memory, verbal learning, and visual learning. In the SCZ group, total PANSS scores were negatively associated with all MCCB dimensions (all p < 0.05), except for the attention/vigilance score. The PANSS-negative and PANSS-cognitive subscores were negatively associated with speed of processing, verbal learning, and visual learning scores (all p < 0.05). The PANSS-excited subscores showed a negative correlation with working memory and visual learning scores (all p < 0.05). ALB levels significantly decreased, and their UA and SOD levels were notably elevated compared to HCs (all p < 0.05). ALB levels and PANSS-negative factors were correlated with to speed of processing, working memory, and visual learning dimensions. SOD levels were independent contributors to the attention/vigilance dimension.ConclusionThe cognitive function was decreased in SCZ. The degree of cognitive impairment was closely related to ALB, SOD levels and negative clinical symptoms.

Examining the Discrepancy between Subjective Cognitive Complaints and Processing Speed Performance in Military Personnel with Traumatic Brain Injury.

To examine correlates of the discrepancy between subjective cognitive complaints and processing speed performance in a sample of military personnel with and without traumatic brain injury (TBI). About 235U.S. military service members (31 noninjured controls [NIC], 69 injured controls [IC], 70 uncomplicated mild TBI [mTBI], and 65 complicated mild/moderate/severe TBI [sTBI]) prospectively enrolled in a longitudinal TBI study completed neuropsychological testing, performance validity tests, and self-report measures of cognitive complaints and psychological symptoms. Service members were categorized as "Accurate Estimators," "Underestimators," and "Overestimators" based on discrepancies between their subjective cognition and processing speed performance. The NIC group was less likely to underestimate their cognitive abilities than the mTBI group (p < .05). Discrepancy groups significantly differed in processing speed scores (p < .001), with underestimators demonstrating the best objective cognitive performance. Spearman correlations revealed significant positive correlations between unadjusted discrepancy scores and psychological symptoms in the NIC, IC, and sTBI groups (ps < 0.05) but not the mTBI group (ps > 0.05). In contrast, discrepancy scores adjusted for premorbid intelligence were consistently and positively correlated with psychological symptoms across all injury groups (ps < 0.05). Findings suggest that mTBI injuries may increase the likelihood of a patient underestimating their cognitive performance. Further, premorbid cognitive functioning is an important factor in evaluating discrepancies in self-reported cognitive complaints and processing speed performance.

Functional and structural cerebellar-behavior relationships in aging.

Healthy aging is associated with deficits in cognitive performance and brain changes, including in the cerebellum. Cerebellar communication with the cortex via closed-loop circuits through the thalamus have been established and these circuits are closely related to the functional topography of the cerebellum. In this study, we sought to elucidate relationships between cerebellar structure and function with cognition in healthy aging. We explored this relationship in 138 healthy adults (aged 35-86, 53% female) using resting-state functional connectivity MRI (fcMRI), cerebellar volume, and cognitive and motor assessments. Behavioral tasks assessed attention, processing speed, working memory, episodic memory, and motor abilities. We expected to find negative relationships between lobular volume with age, and positive relationships between specific lobular volumes with motor and cognitive behavior, respectively. We predicted lower cerebello-cortical fcMRI with increased age. Behaviorally, we expected higher cerebello-frontal and cerebello-association area fcMRI cerebellar connectivity to correlate with better behavioral performance. Correlations were conducted between cerebellar lobules I-IV, V, Crus I, Crus II, vermis VI and behavioral measures. We found lower volumes with increased age as well as both higher and lower cerebellar connectivity relationships with increased age, consistent with literature on functional connectivity and network segregation in aging. Further, we revealed unique associations between cerebellar structure and connectivity with comprehensive behavioral measures in a healthy aging population. Our findings further highlight the role of the cerebellum in aging.

Efficacy and safety of a non-immersive virtual reality-based neuropsychological intervention for cognitive stimulation and relaxation in patients with critical illness: study protocol of a randomized clinical trial (RGS-ICU)

BackgroundExperiencing a critical illness may be a stressful life event that is also associated with cognitive dysfunction during and after the intensive care unit (ICU) stay. A deep-tech solution based on non-immersive virtual reality, gamification and motion capture called Rehabilitation Gaming System for Intensive Care Units (RGS-ICU) has been developed that includes both cognitive stimulation and relaxation protocols specifically designed for patients with critical illness. This study aims to evaluate whether the cognitive and relaxation protocols of the RGS-ICU platform are 1) effective in improving neuropsychological outcomes during and after ICU stay and 2) safe for patients with critical illness.MethodsThis is a study protocol for a multicenter longitudinal randomized clinical trial. At least 80 patients with critical illness will be included: 40 experimental subjects and 40 control subjects. Patients in the experimental group will receive daily 20-min sessions of cognitive stimulation and relaxation with the RGS-ICU platform adjuvant to standard ICU care in their own rooms during the ICU stay and until discharge from the ICU or up to a maximum of 28 days after randomization, provided they are alert and calm. Patients in the experimental group will be constantly monitored as part of standard ICU care to ensure the safety of the intervention and that no avoidable adverse events occur. Patients in the control group will receive standard ICU care. The primary outcome is objective cognition 12 months after ICU discharge, assessed with a composite index including measures of attention, working memory, learning/memory, executive function and processing speed. The secondary outcome is the safety of the intervention, assessed by considering the number of sessions terminated early due to unsafe events in physiological parameters. Other outcomes are comfort experienced during the ICU stay, and subjective cognition, mental health (anxiety, depression and post-traumatic stress disorder), functionality and health-related quality of life 12 months after ICU discharge.DiscussionThe expected results are 1) better neuropsychological outcomes during and after the ICU stay in patients in the experimental group compared to patients in the control group and 2) that the cognitive and relaxation protocols of the RGS-ICU platform are safe for patients with critical illness.Trial registrationClinicaltrials.gov NCT06267911. Registered on February 20, 2024.

Heart sound recognition using hybrid joint transform correlator

Abstract This work introduces an innovative method for heart sound recognition using hybrid joint transform correlator (JTC). The existing techniques such as convolutional neural networks and machine learning models, often suffer from computational complexity and latency difficulties, resulting in slower processing speeds. The proposed method addresses these challenges by utilizing an optical correlator, capable of operating at significantly accelerated speeds. The heart sound signals are first converted into spectrograms, which are then correlated using hybrid JTC operation for recognition and decision. To enhance the accuracy and robustness of the scheme, distortion-invariant filter fabrication has been incorporated with the JTC. The proposed approach not only enhances the speed of heart sound analysis but also maintains high precision and reliability. The effectiveness of the method has been confirmed through both simulation and experimental results.&amp;#xD;

Seeing fast and slow: the influence of music-induced affective states and individual sensory sensitivity on visual processing speed

ABSTRACT There is a speed-accuracy trade-off in perception. The ability to quickly extract sensory information is critical for survival, while extended processing can improve our accuracy. It has been suggested that emotions can change our style of processing, but their influence on processing speed is not yet clear. In three experiments, combining online and laboratory studies with different emotion induction procedures, we investigated the influence of both affective states, manipulated with music, and individual traits in sensory-processing sensitivity on the ability to rapidly segregate two visual flashes. Across studies, the musical manipulations pushed participants towards either rapid or slow processing. Individual variations in sensory-processing sensitivity modulated these effects. Our findings demonstrate that affective states, influenced by music, can shift the balance between fast and slow visual processing, altering our perceptual experience. These results also emphasise the interaction of individual traits in sensory processing and affective states.

From "invisible" to "audible": Features extracted during simple speech tasks classify patient-reported fatigue in multiple sclerosis.

Fatigue is a major "invisible" symptom in people with multiple sclerosis (PwMS), which may affect speech. Automated speech analysis is an objective, rapid tool to capture digital speech biomarkers linked to functional outcomes. To use automated speech analysis to assess multiple sclerosis (MS) fatigue metrics. Eighty-four PwMS completed scripted and spontaneous speech tasks; fatigue was assessed with Modified Fatigue Impact Scale (MFIS). Speech was processed using an automated speech analysis pipeline (ki elements: SIGMA speech processing library) to transcribe speech and extract features. Regression models assessed associations between speech features and fatigue and validated in a separate set of 30 participants. Cohort characteristics were as follows: mean age 49.8 (standard deviation (SD) = 13.6), 71.4% female, 85% relapsing-onset, median Expanded Disability Status Scale (EDSS) 2.5 (range: 0-6.5), mean MFIS 27.6 (SD = 19.4), and 30% with MFIS > 38. MFIS moderately correlated with pitch (R = 0.32, p = 0.005), pause duration (R = 0.33, p = 0.007), and utterance duration (R = 0.31, p = 0.0111). A logistic model using speech features from multiple tasks accurately classified MFIS in training (area under the curve (AUC) = 0.95, R2 = 0.59, p < 0.001) and test sets (AUC = 0.93, R2 = 0.54, p = 0.0222). Adjusting for EDSS, processing speed, and depression in sensitivity analyses did not impact model accuracy. Fatigue may be assessed using simple, low-burden speech tasks that correlate with gold-standard subjective fatigue measures.

Enhancing Big Data Processing Efficiency in AI-Based Healthcare Systems: A Comparative Analysis of Random Forest and Deep

This research focuses on optimizing the speed of Big Data processing using Artificial Intelligence (AI) in healthcare applications. The study integrates Random Forest (RF) and Deep Learning (DL) algorithms with cloud-based computing systems to improve data processing efficiency. The dataset includes both structured data, such as Electronic Health Records (EHR), and unstructured data, like medical images. The results show that RF performs better with structured data, achieving a lower Mean Squared Error (MSE) and higher R-squared (R²) compared to traditional methods. Meanwhile, DL achieves superior accuracy and Area Under the Curve (AUC) in processing unstructured data. By utilizing the distributed computing power of Spark on a cloud platform, the processing speed was significantly enhanced, as demonstrated by a statistically significant reduction in processing time (p &lt; 0.05) observed through a t-test analysis comparing Spark-based computing with traditional methods. Despite these improvements, challenges such as data privacy and infrastructure costs remain. Despite these improvements, challenges such as data privacy and infrastructure costs remain. This research provides a robust framework for real-time healthcare data analysis, highlighting its potential to improve decision-making processes and patient outcomes in medical services.

Hardware-Assisted Low-Latency NPU Virtualization Method for Multi-Sensor AI Systems

Recently, AI systems such as autonomous driving and smart homes have become integral to daily life. Intelligent multi-sensors, once limited to single data types, now process complex text and image data, demanding faster and more accurate processing. While integrating NPUs and sensors has improved processing speed and accuracy, challenges like low resource utilization and long memory latency remain. This study proposes a method to reduce processing time and improve resource utilization by virtualizing NPUs to simultaneously handle multiple deep-learning models, leveraging a hardware scheduler and data prefetching techniques. Experiments with 30,000 SA resources showed that the hardware scheduler reduced memory cycles by over 10% across all models, with reductions of 30% for NCF and 70% for DLRM. The hardware scheduler effectively minimized memory latency and idle NPU resources in resource-constrained environments with frequent context switching. This approach is particularly valuable for real-time applications like autonomous driving, enabling smooth transitions between tasks such as object detection and route planning. It also enhances multitasking in smart homes by reducing latency when managing diverse data streams. The proposed system is well suited for resource-constrained environments that demand efficient multitasking and low-latency processing.

Associations of accelerometer-measured physical activity, sedentary behaviour, and sleep with next-day cognitive performance in older adults: a micro-longitudinal study

BackgroundPrevious studies suggest short-term cognitive benefits of physical activity occurring minutes to hours after exercise. Whether these benefits persist the following day and the role of sleep is unclear. We examined associations of accelerometer-assessed physical activity, sedentary behaviour, and sleep with next-day cognitive performance in older adults.MethodsBritish adults aged 50-83 years (N = 76) without evidence of cognitive impairment or dementia wore accelerometers for eight days, and took daily cognitive tests of attention, memory, psychomotor speed, executive function, and processing speed. Physical behaviour (time spent in moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], and sedentary behaviour [SB]) and sleep characteristics (overnight sleep duration, time spent in rapid eye movement [REM] sleep and slow wave sleep [SWS]) were extracted from accelerometers, with sleep stages derived using a novel polysomnography-validated machine learning algorithm. We used linear mixed models to examine associations of physical activity and sleep with next-day cognitive performance, after accounting for habitual physical activity and sleep patterns during the study period and other temporal and contextual factors.ResultsAn additional 30 min of MVPA on the previous day was associated with episodic memory scores 0.15 standard deviations (SD; 95% confidence interval = 0.01 to 0.29; p = 0.03) higher and working memory scores 0.16 SD (0.03 to 0.28; p = 0.01) higher. Each 30-min increase in SB was associated with working memory scores 0.05 SD (0.00 to 0.09) lower (p = 0.03); adjustment for sleep characteristics on the previous night did not substantively change these results. Independent of MVPA on the previous day, sleep duration ≥ 6 h (compared with < 6 h) on the previous night was associated with episodic memory scores 0.60 SD (0.16 to 1.03) higher (p = 0.008) and psychomotor speed 0.34 SD (0.04 to 0.65) faster (p = 0.03). Each 30-min increase in REM sleep on the previous night was associated with 0.13 SD (0.00 to 0.25) higher attention scores (p = 0.04); a 30-min increase in SWS was associated with 0.17 SD (0.05 to 0.29) higher episodic memory scores (p = 0.008).ConclusionsMemory benefits of MVPA may persist for 24 h; longer sleep duration, particularly more time spent in SWS, could independently contribute to these benefits.

A multi-stage feature selection method to improve classification of potential super-agers and cognitive decliners using structural brain MRI data-a UK biobank study.

Cognitive aging is described as the age-related decline in areas such as memory, executive function, reasoning, and processing speed. Super-Agers, adults over 80 years old, have cognitive function performance comparable to middle-aged adults. To improve cognitive reserve and potentially decrease Alzheimer's disease (AD) risk, it is essential to contrast changes in regional brain volumes between "Positive-Agers" who have superior cognitive performance compared to their age peers but are not 80 years old yet and aging adults who show cognitive decline (i.e., "Cognitive Decliners"). Using longitudinal cognitive tests over 7-9 years in UK Biobank, principal component analysis (PCA) was first applied to four cognitive domains to create a general cognition (GC) composite score. The GC score was then used to identify latent cognitive groups. Given cognitive groups as the target variable and structural magnetic resonance imaging (sMRI) data and demographics as predictors, we developed a multi-stage feature selection algorithm to identify the most important features. We then trained a Random Forest (RF) classifier on the final set of 54 selected sMRI and covariate predictors to distinguish between Positive-Agers and Cognitive Decliners. The RF model achieved an AUC of 73%. The top 6 features were age, education, brain total surface area, the area of pars orbitalis, mean intensity of the thalamus, and superior frontal gyrus surface area. Prediction of cognitive trajectory types using sMRI may improve our understanding of successful cognitive aging.

The mediating role of processing speed on the relationship between executive functions and social cognition in relapsing-remitting multiple sclerosis patients.

This study examined the mediating role of processing speed between executive functions and social cognition in 67 relapsing-remitting multiple sclerosis (RRMS) patients. Executive functions were assessed using the Trail Making Test-Part B (TMT-B) and the Stroop Neuropsychological Screening Test (SNST); social cognition with the Reading the Mind in the Eyes Test (RMET); and processing speed with the Symbol Digit Modalities Test (SDMT). Mediated effects were explored using a series of regression analyses and were further confirmed through bootstrapping procedures. Results revealed that processing speed partially mediated the relationship between cognitive shifting (TMT-B) and social cognition (RMET), and fully mediated the relationship between inhibitory control (SNST) and social cognition (RMET). These findings highlight the importance of processing speed in the socio-cognitive impairments observed in RRMS patients, thus suggesting that comprehensive assessments and targeted interventions in this clinical group.

Driving after Concussion: Symptom Clusters and Neurocognition Uniquely Relate to Post-Concussion Driving Performance.

To identify clinical concussion assessment outcomes that uniquely capture simulated driving performance among acutely concussed individuals, relative to controls. Cross-sectional design. Twenty-eight college students within 72-hours of concussion and 46 non-concussed controls participated in the study. We collected the following clinical concussion assessment outcomes: 4 concussion symptom clusters, 7 computerized neurocognitive domain scores, Standardized Assessment of Concussion (SAC) total score, Balance Error Scoring System total score, and tandem gait completion time. The following simulated driving outcomes were included (count): total collisions, speed exceedances, centerline crossings, and road edge excursions. We used separate generalized linear mixed regression models fit using a Poisson distribution with group, assessment, and interaction effects. Higher migrainous symptoms (p < 0.001), cognitive-fatigue symptoms (p = 0.041), poorer visual memory (p = 0.015), and slower reaction time (p = 0.023) in concussion group were associated with higher risk of committing speed exceedances, relative to controls. Conversely, better performance on the continuous performance test (p = 0.046) and SAC (p = 0.045) in concussion group were associated with higher risk of committing speed exceedances relative to controls. Poorer performance on psychomotor speed (p = 0.001), reaction time (p = 0.031), cognitive flexibility (p = 0.004), and executive function (p = 0.003) were associated with higher risk of committing centerline crossings in concussion group, relative to controls. Conversely, better performance on the continuous performance test (p = 0.035) and higher affective symptoms (p = 0.013) were associated with higher risk of committing centerline crossings and road edge excursions, respectively. relative to controls. Our results highlight key symptom clusters and computerized neurocognitive outcomes that uniquely inform poorer simulated driving performance in acutely concussed individuals. Symptom clusters and computerized neurocognitive function might be helpful when discussing with patients about return to driving decisions post-concussion.

Understanding the complex network of objectively assessed cognition and self-reported psychological symptoms in people with multiple sclerosis.

Literature on the intricate relationship between self-reported and objectively assessed cognitive functioning suggests a discrepancy between self-reported cognitive complaints (SCC) and actual test performance. To investigate the interplay between patient-reported outcome measures (PROMs) and objective cognitive functioning using network analysis in people with multiple sclerosis (PwMS). We collected PROMs on anxiety, depression, fatigue and SCC, and cognitive functioning across six domains (n = 703 PwMS; 71% female, mean age = 46.3 ± 11.2 years). We constructed cognitive symptom networks using Gaussian Graphical Models, in which the aforementioned variables were presented as nodes linked by regularized partial correlations. We compared global network strength between relevant subgroups. The networks primarily showed clustering of PROMs and cognitive domains into two separate modules, with weaker links connecting both modules. Global network strength was lower for PwMS with impaired information processing speed (IPS; indicating lower symptom interrelatedness) compared to those with preserved IPS (3.57 versus 4.51, p = 0.001), but not when comparing SCC subgroups (p = 0.140). Cognitive symptom networks deepen our understanding of the discrepancy between self-reported and objectively assessed cognitive functioning. Lower symptom interrelatedness in PwMS with impaired IPS might suggest a nonlinear relation between PROMs and cognitive domains, which depends on the cognitive status.