Richard A.P. Roche

Dissociable Executive Functions in the Dynamic Control of Behavior: Inhibition, Error Detection, and Correction

The present study employed event-related fMRI and EEG to investigate the biological basis of the cognitive control of behavior. Using a GO/NOGO task optimized to produce response inhibitions, frequent commission errors, and the opportunity for subsequent behavioral correction, we identified distinct cortical areas associated with each of these specific executive processes. Two cortical systems, one involving right prefrontal and parietal areas and the second regions of the cingulate, underlay inhibitory control. The involvement of these two systems was predicated upon the difficulty or urgency of the inhibition and each was employed to different extents by high- and low-absent-minded subjects. Errors were associated with medial activation incorporating the anterior cingulate and pre-SMA while behavioral alteration subsequent to errors was associated with both the anterior cingulate and the left prefrontal cortex. Furthermore, the EEG data demonstrated that successful response inhibition depended upon the timely activation of cortical areas as predicted by race models of response selection. The results highlight how higher cognitive functions responsible for behavioral control can result from the dynamic interplay of distinct cortical systems.

Individual differences discriminate event-related potentials but not performance during response inhibition

Event-related brain potentials (ERPs) were recorded from 20 normal participants while they completed a Go/NoGo response inhibition task. Previous ERP studies have implicated the N2 and P3 waveforms as the main indices of processing in this task, and functional brain imaging has shown parietal, prefrontal and anterior cingulate cortices to be involved in response inhibition. 32-channel ERP analysis revealed amplitude differences in the N2/P3 components when stimuli that required a button-press (Go stimuli) were compared with stimuli for which the response had to be withheld (No-Go stimuli), and in N2 and P3 latencies when successful withholds to No-Go stimuli were compared with unsuccessful attempts to inhibit. Further differences in the N2/P3 complex emerged when participants were grouped in terms of a measure of absentmindedness (the Cognitive Failures Questionnaire, CFQ); larger and earlier components were found for high CFQ respondents. We conclude that the latencies of the N2 and P3 may be the critical indicators of active inhibitory processes for this task, suggesting that a pattern of sequential activation rather than altered activity level in key structures may mediate success on the task. In addition, highly absentminded participants exhibited larger components for errors than did less absentminded participants when performing at the same level, which implies that the absentminded may require greater activity in the neural substrates of response inhibition in order to accomplish this task at a comparable level of performance to less absentminded participants.

EEG alpha power changes reflect response inhibition deficits after traumatic brain injury (TBI) in humans

Brain damage due to traumatic brain injury (TBI) has been associated with deficits in executive functions and the dynamic control of behaviour. Event-related brain potentials and spectral power data were recorded from eight TBI participants and eight matched controls while they completed a Go/NoGo response inhibition task. The TBI group was found to be significantly impaired at the task compared to controls, and exhibited abnormal N2 and P3 waveform components in response to NoGo stimuli relative to controls. Significant correlations were also found between alpha power, Go-trial RT and errors. We conclude that abnormal activity in the structures damaged in this group may render such patients less capable of maintaining a state of alpha desynchronisation compared to controls, resulting in poorer performance on the task.

Electrophysiological and information processing variability predicts memory decrements associated with normal age-related cognitive decline and Alzheimer's disease (AD).

Recent theoretical models of cognitive aging have implicated increased intra-individual variability as a critical marker of decline. The current study examined electrophysiological and information processing variability and memory performance in normal younger and older controls, and older adults with Alzheimers disease (AD). It was hypothesized that higher levels of variability would be indicative of age-related and disease-related memory deficits. Results indicated both implicit and explicit memory deficits associated with AD. Consistent with previous research, behavioral speed and variability emerged as sensitive to age- and disease-related change. Amplitude variability of P3 event-related potentials was a unique component of electrophysiological activity and accounted for significant variance in reaction time (RT) mean and RT standard deviation, which in turn accounted for significant variance in memory function. Results are discussed in light of theoretical and applied issues in the field of cognitive aging.

Facial emotion recognition in adolescents with psychotic-like experiences: a school-based sample from the general population.

BACKGROUND Psychotic symptoms, also termed psychotic-like experiences (PLEs) in the absence of psychotic disorder, are common in adolescents and are associated with increased risk of schizophrenia-spectrum illness in adulthood. At the same time, schizophrenia is associated with deficits in social cognition, with deficits particularly documented in facial emotion recognition (FER). However, little is known about the relationship between PLEs and FER abilities, with only one previous prospective study examining the association between these abilities in childhood and reported PLEs in adolescence. The current study was a cross-sectional investigation of the association between PLEs and FER in a sample of Irish adolescents. METHOD The Adolescent Psychotic-Like Symptom Screener (APSS), a self-report measure of PLEs, and the Penn Emotion Recognition-40 Test (Penn ER-40), a measure of facial emotion recognition, were completed by 793 children aged 10-13 years. RESULTS Children who reported PLEs performed significantly more poorly on FER (β=-0.03, p=0.035). Recognition of sad faces was the major driver of effects, with children performing particularly poorly when identifying this expression (β=-0.08, p=0.032). CONCLUSIONS The current findings show that PLEs are associated with poorer FER. Further work is needed to elucidate causal relationships with implications for the design of future interventions for those at risk of developing psychosis.

Pedestrian navigation using the sense of touch

Abstract Haptics is a feedback technology that takes advantage of the human sense of touch by applying forces, vibrations, and/or motions to a haptic-enabled user device such as a mobile phone. Historically, human–computer interaction has been visual, data, or images on a screen. Haptic feedback can be an important modality in Mobile Location-Based Services like – knowledge discovery, pedestrian navigation and notification systems. In this paper we describe a methodology for the implementation of haptics in four distinct prototypes for pedestrian navigation. Prototypes are classified based on the user’s navigation guidance requirements, the user type (based on spatial skills), and overall system complexity. Here haptics is used to convey location, orientation, and distance information to users using pedestrian navigation applications. Initial user trials have elicited positive responses from the users who see benefit in being provided with a “heads up” approach to mobile navigation. We also tested the spatial ability of the user to navigate using haptics and landmark images based navigation. This was followed by a test of memory recall about the area. Users were able to successfully navigate from a given origin to a Destination Point without the use of a visual interface like a map. Results show the users of haptic feedback for navigation prepared better maps (better memory recall) of the region as compared to the users of landmark images based navigation.

An exploration of EEG features during recovery following stroke – implications for BCI-mediated neurorehabilitation therapy

BackgroundBrain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control in a limb following stroke. BCIs are typically used by subjects with no damage to the brain therefore relatively little is known about the technical requirements for the design of a rehabilitative BCI for stroke.Methods32-channel electroencephalogram (EEG) was recorded during a finger-tapping task from 10 healthy subjects for one session and 5 stroke patients for two sessions approximately 6 months apart. An off-line BCI design based on Filter Bank Common Spatial Patterns (FBCSP) was implemented to test and compare the efficacy and accuracy of training a rehabilitative BCI with both stroke-affected and healthy data.ResultsStroke-affected EEG datasets have lower 10-fold cross validation results than healthy EEG datasets. When training a BCI with healthy EEG, average classification accuracy of stroke-affected EEG is lower than the average for healthy EEG. Classification accuracy of the late session stroke EEG is improved by training the BCI on the corresponding early stroke EEG dataset.ConclusionsThis exploratory study illustrates that stroke and the accompanying neuroplastic changes associated with the recovery process can cause significant inter-subject changes in the EEG features suitable for mapping as part of a neurofeedback therapy, even when individuals have scored largely similar with conventional behavioural measures. It appears such measures can mask this individual variability in cortical reorganization. Consequently we believe motor retraining BCI should initially be tailored to individual patients.

Dual-task and electrophysiological markers of executive cognitive processing in older adult gait and fall-risk

The role of cognition is becoming increasingly central to our understanding of the complexity of walking gait. In particular, higher-level executive functions are suggested to play a key role in gait and fall-risk, but the specific underlying neurocognitive processes remain unclear. Here, we report two experiments which investigated the cognitive and neural processes underlying older adult gait and falls. Experiment 1 employed a dual-task (DT) paradigm in young and older adults, to assess the relative effects of higher-level executive function tasks (n-Back, Serial Subtraction and visuo-spatial Clock task) in comparison to non-executive distracter tasks (motor response task and alphabet recitation) on gait. All DTs elicited changes in gait for both young and older adults, relative to baseline walking. Significantly greater DT costs were observed for the executive tasks in the older adult group. Experiment 2 compared normal walking gait, seated cognitive performances and concurrent event-related brain potentials (ERPs) in healthy young and older adults, to older adult fallers. No significant differences in cognitive performances were found between fallers and non-fallers. However, an initial late-positivity, considered a potential early P3a, was evident on the Stroop task for older non-fallers, which was notably absent in older fallers. We argue that executive control functions play a prominent role in walking and gait, but the use of neurocognitive processes as a predictor of fall-risk needs further investigation.

Concurrent task performance enhances low-level visuomotor learning

Visuomotor association learning involves learning to make a motor response to an arbitrary visual stimulus. This learning is essential for visual search and discrimination performance and is reliant upon a well-defined neural circuit in the brain that includes the prefrontal cortex and the hippocampal formation. In the present study, we investigated the possible role of attentional processes during such learning using dual-task interference. A motor, verbal, or perceptual concurrent task was performed during the learning/training block of a simple visual discrimination task. Contrary to expectation, the dual-task groups showed improved learning and learning-dependent performance compared with untrained control and non-dual-task trained groups. A second experiment revealed that this effect did not appear to be due to increased arousal level; the inclusion of alerting tones during learning did not result in facilitation. These findings suggest that the engagement of attention, but not arousal, during the acquisition of a visuomotor association can facilitate this learning and its expression.

Behavioural and electrophysiological correlates of visuomotor learning during a visual search task

Visuomotor association learning involves learning specific motor responses to arbitrary cues, and is dependent on a distributed and highly flexible network in the brain. We investigated the behavioural and electrophysiological correlates of arbitrary visuomotor learning in 20 normal participants. An experimental group learned an arbitrary association between a visual stimulus and a motor response during a training block. Their performance was compared with that of untrained controls on a subsequent visual discrimination task in which the learned association was a crucial element. Event-related brain potentials (ERPs) were recorded from the scalp of each participant during learning and discrimination blocks. Reaction times to stimuli in the discrimination task were significantly faster in the trained group compared to controls. There was a corresponding difference in the ERP waveforms recorded during the task, with larger P3b amplitude for the trained group over midline and centroparietal scalp areas. A latency difference in P3b was also observed for trained targets compared to distractors. RTs during the training block decreased in a manner consistent with learning effects. We conclude that training of a visuomotor association facilitates subsequent performance on a related task, and that the waveform correlates found here may reflect the involvement of parts of the network underlying arbitrary association mapping.