Advance Preparation in Task-Switching: Converging Evidence from Behavioral, Brain Activation, and Model-Based Approaches

Recent research has taken advantage of the temporal and spatial resolution of event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI) to identify the time course and neural circuitry of preparatory processes required to switch between different tasks. Here we overview some key findings contributing to understanding strategic processes in advance preparation. Findings from these methodologies are compatible with advance preparation conceptualized as a set of processes activated for both switch and repeat trials, but with substantial variability as a function of individual differences and task requirements. We then highlight new approaches that attempt to capitalize on this variability to link behavior and brain activation patterns. One approach examines correlations among behavioral, ERP and fMRI measures. A second “model-based” approach accounts for differences in preparatory processes by estimating quantitative model parameters that reflect latent psychological processes. We argue that integration of behavioral and neuroscientific methodologies is key to understanding the complex nature of advance preparation in task-switching

Facial Emotion and Identity Processing Development in 5- to 15-Year-Old Children

Most developmental studies of emotional face processing to date have focused on infants and very young children. Additionally, studies that examine emotional face processing in older children do not distinguish development in emotion and identity face processing from more generic age-related cognitive improvement. In this study, we developed a paradigm that measures processing of facial expression in comparison to facial identity and complex visual stimuli. The three matching tasks were developed (i.e., facial emotion matching, facial identity matching, and butterfly wing matching) to include stimuli of similar level of discriminability and to be equated for task difficulty in earlier samples of young adults. Ninety-two children aged 5–15 years and a new group of 24 young adults completed these three matching tasks. Young children were highly adept at the butterfly wing task relative to their performance on both face-related tasks. More importantly, in older children, development of facial emotion discrimination ability lagged behind that of facial identity discrimination

Adaptiveness in proactive control engagement in children and adults

Age-related progress in cognitive control reflects more frequent engagement of proactive control during childhood. As proactive preparation for an upcoming task is adaptive only when the task can be reliably predicted, progress in proactive control engagement may rely on more efficient use of contextual cue reliability. Developmental progress may also reflect increasing efficiency in how proactive control is engaged, making this control mode more advantageous with age. To address these possibilities, 6-year-olds, 9-year-olds, and adults completed three versions of a cued task-switching paradigm in which contextual cue reliability was manipulated. When contextual cues were reliable (but not unreliable or uninformative), all age groups showed greater pupil dilation and a more pronounced (pre)cue-locked posterior positivity associated with faster response times, suggesting adaptive engagement of proactive task selection. However, adults additionally showed a larger contingent negative variation (CNV) predicting a further reduction in response times with reliable cues, suggesting motor preparation in adults but not children. Thus, early developing use of contextual cue reliability promotes adaptiveness in proactive control engagement from early childhood; yet, less efficient motor preparation in children makes this control mode overall less advantageous in childhood than adulthood

Cognition in Stroke Rehabilitation and Recovery Research: Consensus-Based Core Recommendations From the Second Stroke Recovery and Rehabilitation Roundtable

Cognitive impairment is an important target for rehabilitation as it is common following stroke, is associated with reduced quality of life and interferes with motor and other types of recovery interventions. Cognitive function following stroke was identified as an important, but relatively neglected area during the first Stroke Recovery and Rehabilitation Roundtable (SRRR I), leading to a Cognition Working Group being convened as part of SRRR II. There is currently insufficient evidence to build consensus on specific approaches to cognitive rehabilitation. However, we present recommendations on the integration of cognitive assessments into stroke recovery studies generally and define priorities for ongoing and future research for stroke recovery and rehabilitation. A number of promising interventions are ready to be taken forward to trials to tackle the gap in evidence for cognitive rehabilitation. However, to accelerate progress requires that we coordinate efforts to tackle multiple gaps along the whole translational pathway

Cognition in stroke rehabilitation and recovery research: Consensus-based core recommendations from the second Stroke Recovery and Rehabilitation Roundtable

Cognitive impairment is an important target for rehabilitation as it is common following stroke, is associated with reduced quality of life and interferes with motor and other types of recovery interventions. Cognitive function following stroke was identified as an important, but relatively neglected area during the first Stroke Recovery and Rehabilitation Roundtable (SRRR I), leading to a Cognition Working Group being convened as part of SRRR II. There is currently insufficient evidence to build consensus on specific approaches to cognitive rehabilitation. However, we present recommendations on the integration of cognitive assessments into stroke recovery studies generally and define priorities for ongoing and future research for stroke recovery and rehabilitation. A number of promising interventions are ready to be taken forward to trials to tackle the gap in evidence for cognitive rehabilitation. However, to accelerate progress requires that we coordinate efforts to tackle multiple gaps along the whole translational pathway

Twenty-four-hour time-use composition and cognitive function in older adults: cross-sectional findings of the ACTIVate study

IntroductionPhysical activity, sedentary behaviour and sleep are associated with cognitive function in older adults. However, these behaviours are not independent, but instead make up exclusive and exhaustive components of the 24-h day. Few studies have investigated associations between 24-h time-use composition and cognitive function in older adults. Of these, none have considered how the quality of sleep, or the context of physical activity and sedentary behaviour may impact these relationships. This study aims to understand how 24-h time-use composition is associated with cognitive function across a range of domains in healthy older adults, and whether the level of recreational physical activity, amount of television (TV) watching, or the quality of sleep impact these potential associations.Methods384 healthy older adults (age 65.5 ± 3.0 years, 68% female, 63% non-smokers, mean education = 16.5 ± 3.2 years) participated in this study across two Australian sites (Adelaide, n = 207; Newcastle, n = 177). Twenty-four-hour time-use composition was captured using triaxial accelerometry, measured continuously across 7 days. Total time spent watching TV per day was used to capture the context of sedentary behaviours, whilst total time spent in recreational physical activity was used to capture the context of physical activity (i.e., recreational accumulation of physical activity vs. other contexts). Sleep quality was measured using a single item extracted from the Pittsburgh Sleep Quality Index. Cognitive function was measured using a global cognition index (Addenbrooke’s Cognitive Examination III) and four cognitive domain composite scores (derived from five tests of the Cambridge Neuropsychological Test Automated Battery: Paired Associates Learning; One Touch Stockings of Cambridge; Multitasking; Reaction Time; Verbal Recognition Memory). Pairwise correlations were used to describe independent relationships between time use variables and cognitive outcomes. Then, compositional data analysis regression methods were used to quantify associations between cognition and 24-h time-use composition.ResultsAfter adjusting for covariates and false discovery rate there were no significant associations between time-use composition and global cognition, long-term memory, short-term memory, executive function, or processing speed outcomes, and no significant interactions between TV watching time, recreational physical activity engagement or sleep quality and time-use composition for any cognitive outcomes.DiscussionThe findings highlight the importance of considering all activities across the 24-h day against cognitive function in older adults. Future studies should consider investigating these relationships longitudinally to uncover temporal effects

The Influence of Feedback on Task-Switching Performance:A Drift Diffusion Modeling Account

Task-switching is an important cognitive skill that facilitates our ability to choose appropriate behavior in a varied and changing environment. Task-switching training studies have sought to improve this ability by practicing switching between multiple tasks. However, an efficacious training paradigm has been difficult to develop in part due to findings that small differences in task parameters influence switching behavior in a non-trivial manner. Here, for the first time we employ the Drift Diffusion Model (DDM) to understand the influence of feedback on task-switching and investigate how drift diffusion parameters change over the course of task switch training. We trained 316 participants on a simple task where they alternated sorting stimuli by color or by shape. Feedback differed in six different ways between subjects groups, ranging from No Feedback (NFB) to a variety of manipulations addressing trial-wise vs. Block Feedback (BFB), rewards vs. punishments, payment bonuses and different payouts depending upon the trial type (switch/non-switch). While overall performance was found to be affected by feedback, no effect of feedback was found on task-switching learning. Drift Diffusion Modeling revealed that the reductions in reaction time (RT) switch cost over the course of training were driven by a continually decreasing decision boundary. Furthermore, feedback effects on RT switch cost were also driven by differences in decision boundary, but not in drift rate. These results reveal that participants systematically modified their task-switching performance without yielding an overall gain in performance

Microstructural white matter changes mediated age- related cognitive decline in the Montreal Cognitive Assessment (MoCA)

Although the relationship between aging and cognitive decline is well established, there is substantial individual variability in the degree of cognitive decline in older adults. The present study investigates whether variability in cognitive performance in community-dwelling older adults is related to the presence of whole brain or tract-specific changes in white matter microstructure. Specifically, we examine whether age-related decline in performance on the Montreal Cognitive Assessment (MoCA), a cognitive screening tool, is mediated by the white matter microstructural decline. We also examine if this relationship is driven by the presence of cardiovascular risk factors or variability in cerebral arterial pulsatility, an index of cardiovascular risk. Sixty-nine participants (aged 43–87) completed behavioral and MRI testing including T1 structural, T2-weighted FLAIR, and diffusion-weighted imaging (DWI) sequences. Measures of white matter microstructure were calculated using diffusion tensor imaging analyses on the DWI sequence. Multiple linear regression revealed that MoCA scores were predicted by radial diffusivity (RaD) of white matter beyond age or other cerebral measures. While increasing age and arterial pulsatility were associated with increasing RaD, these factors did not mediate the relationship between total white matter RaD and MoCA. Further, the relationship between MoCA and RaD was specific to participants who reported at least one cardiovascular risk factor. These findings highlight the importance of cardiovascular risk factors in the presentation of cognitive decline in old age. Further work is needed to establish whether medical or lifestyle management of these risk factors can prevent or reverse cognitive decline in old age