Attention Network Test fMRI data for participants with Parkinson's disease and healthy elderly.

Here, we present unprocessed and preprocessed Attention Network Test data from 25 adults with Parkinson's disease and 21 healthy adults, along with the associated defaced structural scans. The preprocessed data has been processed with a provided Analysis of Functional NeuroImages afni_proc.py script and includes structural scans that were skull-stripped before defacing. All acquired demographic and neuropsychological data are included.

Quantitative cerebrovascular pathology in a community-based cohort of older adults.

Cerebrovascular disease, especially small vessel pathology, is the leading comorbidity in degenerative disorders. We applied arterial spin labeling and cerebrovascular reserve (CVR) imaging to quantify small vessel disease and study its effect on cognitive symptoms in nondemented older adults from a community-based cohort. We evaluated baseline cerebral blood flow (CBF) using arterial spin labeling and percent signal change as a marker of CVR using blood-oxygen level-dependent imaging following a breath-hold stimulus. Measurements were performed in and near white matter hyperintensities, which are currently the standard to assess severity of vascular pathology. We show that similar to other studies (1) CBF and CVR are markedly reduced in the hyperintensities as well as in the tissue surrounding them, indicating susceptibility to infarction; (2) low CBF and CVR are significantly correlated with poor cognitive performance; and (3) in addition, compared to a 58.4% reduction in CBF, larger exhaustion (79.3%) of CVR was observed in the hyperintensities with a faster, nonlinear rate of decline. We conclude that CVR may be a more sensitive biomarker of small vessel disease than CBF.

Relationships between Eye Movements during Sentence Reading Comprehension, Word Spelling and Reading, and DTI and fmri Connectivity In Students with and without Dysgraphia or Dyslexia.

While eye movements were recorded and brains scanned, 29 children with and without specific learning disabilities (SLDs) decided if sentences they read (half with only correctly spelled words and half with homonym foils) were meaningful. Significant main effects were found for diagnostic groups (non-SLD control, dysgraphia control, and dyslexia) in total fixation (dwell) time, total number of fixations, and total regressions in during saccades; the dyslexia group had longer and more fixations and made more regressions in during saccades than either control group. The dyslexia group also differed from both control groups in (a) fractional anisotropy in left optic radiation and (b) silent word reading fluency on a task in which surrounding letters can be distracting, consistent with Rayner's selective attention dyslexia model. Different profiles for non-SLD control, dysgraphia, and dyslexia groups were identified in correlations between total fixation time, total number of fixations, regressions in during saccades, magnitude of gray matter connectivity during the fMRI sentence reading comprehension from left occipital temporal cortex seed with right BA44 and from left inferior frontal gyrus with right inferior frontoccipital fasciculus, and normed word-specific spelling and silent word reading fluency measures. The dysgraphia group was more likely than the non-SLD control or dyslexia groups to show negative correlations between eye movement outcomes and sentences containing incorrect homonym foils. Findings are discussed in reference to a systems approach in future sentence reading comprehension research that integrates eye movement, brain, and literacy measures.

Executive attention networks show altered relationship with default mode network in PD.

Attention dysfunction is a common but often undiagnosed cognitive impairment in Parkinson's disease that significantly reduces quality of life. We sought to increase understanding of the mechanisms underlying attention dysfunction using functional neuroimaging. Functional MRI was acquired at two repeated sessions in the resting state and during the Attention Network Test, for 25 non-demented subjects with Parkinson's disease and 21 healthy controls. Behavioral and MRI contrasts were calculated for alerting, orienting, and executive control components of attention. Brain regions showing group differences in attention processing were used as seeds in a functional connectivity analysis of a separate resting state run. Parkinson's disease subjects showed more activation during increased executive challenge in four regions of the dorsal attention and frontoparietal networks, namely right frontal eye field, left and right intraparietal sulcus, and precuneus. In three regions we saw reduced resting state connectivity to the default mode network. Further, whereas higher task activation in the right intraparietal sulcus correlated with reduced resting state connectivity between right intraparietal sulcus and the precuneus in healthy controls, this relationship was absent in Parkinson's disease subjects. Our results suggest that a weakened interaction between the default mode and task positive networks might alter the way in which the executive response is processed in PD.

Relationships between Translation and Transcription Processes during fMRI Connectivity Scanning and Coded Translation and Transcription in Writing Products after Scanning in Children with and without Transcription Disabilities.

Students with transcription disabilities (dysgraphia/impaired handwriting, n = 13 or dyslexia/impaired word spelling, n = 16) or without transcription disabilities (controls) completed transcription and translation (idea generating, planning, and creating) writing tasks during fMRI connectivity scanning and compositions after scanning, which were coded for transcription and translation variables. Compositions in both groups showed diversity in genre beyond usual narrative-expository distinction; groups differed in coded transcription but not translation variables. For the control group specific transcription or translation tasks during scanning correlated with corresponding coded transcription or translation skills in composition, but connectivity during scanning was not correlated with coded handwriting during composing in dysgraphia group and connectivity during translating was not correlated with any coded variable during composing in dyslexia group. Results are discussed in reference to the trend in neuroscience to use connectivity from relevant seed points while performing tasks and trends in education to recognize the generativity (creativity) of composing at both the genre and syntax levels.

Cerebral perfusion and cortical thickness indicate cortical involvement in mild Parkinson's disease.

Cortical dysfunction in Parkinson's disease (PD) may be caused by disruption to ascending systems or by intrinsic cortical neuropathology. We introduce and conduct a joint analysis of metabolism and atrophy capable of identifying whether metabolic disruption occurs in mild PD without cortical atrophy, to determine the extent and spatial pattern of cortical involvement in mild PD. The design was observational, studying 23 cognitively normal participants with mild PD (mean Hoehn & Yahr stage 2) and 21 healthy controls. Cortical thickness (obtained from analysis of structural magnetic resonance imaging [MRI] with FreeSurfer) and cerebral perfusion measures (obtained from arterial spin labeling [ASL]) analyzed independently and then together in a joint multiple factorial analysis to identify spatial patterns of perfusion and cortical thickness. We identify a pattern of changes in perfusion and cortical thickness characterized by symmetric parietal cortical thinning and reduced precuneus perfusion, with relative preservation of thickness and perfusion in the anterior cingulate cortex (ACC), right prefrontal gyrus, and medial frontal gyrus. The expression of this pattern is correlated with motor system symptoms and speed of processing. A spatial pattern of joint parietal cortical thinning and disproportionate reduction in perfusion occurs in our nondemented PD sample. We found no PD-related components of reduced perfusion without cortical thinning. This suggests that PD affects the cortex itself, even when symptoms are relatively mild.

Dynamic connectivity at rest predicts attention task performance.

Consistent spatial patterns of coherent activity, representing large-scale networks, have been reliably identified in multiple populations. Most often, these studies have examined "stationary" connectivity. However, there is a growing recognition that there is a wealth of information in the time-varying dynamics of networks which has neural underpinnings, which changes with age and disease and that supports behavior. Using factor analysis of overlapping sliding windows across 25 participants with Parkinson disease (PD) and 21 controls (ages 41-86), we identify factors describing the covarying correlations of regions (dynamic connectivity) within attention networks and the default mode network, during two baseline resting-state and task runs. Cortical regions that support attention networks are affected early in PD, motivating the potential utility of dynamic connectivity as a sensitive way to characterize physiological disruption to these networks. We show that measures of dynamic connectivity are more reliable than comparable measures of stationary connectivity. Factors in the dorsal attention network (DAN) and fronto-parietal task control network, obtained at rest, are consistently related to the alerting and orienting reaction time effects in the subsequent Attention Network Task. In addition, the same relationship between the same DAN factor and the alerting effect was present during tasks. Although reliable, dynamic connectivity was not invariant, and changes between factor scores across sessions were related to changes in accuracy. In summary, patterns of time-varying correlations among nodes in an intrinsic network have a stability that has functional relevance.

A low-cost, computer-interfaced drawing pad for FMRI studies of dysgraphia and dyslexia.

We have developed a pen and writing tablet for use by subjects during fMRI scanning. The pen consists of two jacketed, multi-mode optical fibers routed to the tip of a hollowed-out ball-point pen. The pen has been further modified by addition of a plastic plate to maintain a perpendicular pen-tablet orientation. The tablet is simply a non-metallic frame holding a paper print of continuously varying color gradients. The optical fibers are routed out of the MRI bore to a light-tight box in an adjacent control room. Within the box, light from a high intensity LED is coupled into one of the fibers, while the other fiber abuts a color sensor. Light from the LED exits the pen tip, illuminating a small spot on the tablet, and the resulting reflected light is routed to the color sensor. Given a lookup table of position for each color on the tablet, the coordinates of the pen on the tablet may be displayed and digitized in real-time. While simple and inexpensive, the system achieves sufficient resolution to grade writing tasks testing dysgraphic and dyslexic phenomena.

Discrimination of left and right leg motor imagery for brain-computer interfaces.

This article reports on a study to identify electroencephalography (EEG) signals with potential to provide new BCI channels through mental motor imagery (MMI). Leg motion was assessed to see if left and right leg MMI could be discriminated in the EEG. The study also explored simultaneous observation of leg movement as a means to enhance MMI evoked EEG signals. The results demonstrate that MMI of the left and right leg produce a contralateral preponderance of EEG alpha band desynchronization, which can be spatially discriminated. This suggests that lower extremity MMI could provide signals for additional BCI channels. The study also shows that movement imitation enhances alpha band desynchronization during MMI, and might provide a useful aid in the identification and training of BCI signals.

Analysis of eyes open, eye closed EEG signals using second-order difference plot.

An assistive technology developed for "hands free" control of electrical devices to be used by severely impaired people within their environment, relies upon using signal processing techniques for analyzing eyes closed (EC) and eyes open (EO) states in the electroencephalography (EEG) signal. Here, we apply a signal processing technique used in continuous chaotic modeling to investigate differences in the EEG time series between EC and EO states. This method is used to detect the degree of variability from a second-order difference plot, and quantifying this using a central tendency measures. The study used EEG time series of EO and EC states from 33 able-bodied and 17 spinal cord injured participants. The results found an increased EEG variability in brain activity during EC compared to EO. This increased EEG variability occurred in the O2 electrode, which overlays the primary visual cortex V1, and could be a result of the replacement of the coherent information obtained during EO by noise. A continuous measure of the variability was then used to demonstrate that this technique has the potential to be used as a switching mechanism for assistive technologies.

Integrating "brain" and "body" measures: correlations between EEG and metabolic changes over the human lifespan.

AIMS: This study investigated the relationship between electroencephalograph (EEG) power and basal metabolic rate (BMR) over the human lifespan, to better understand the mechanisms involved in the decline of neural activity with age. METHODS: Eyes-open EEG power was calculated in standard frequency bands and averaged across recording sites in 1831 healthy subjects aged 6 to 86 years, from the Brain Resource International Database. In a subset of 175 subjects, structural MRI scans were also undertaken to determine the role of grey matter. Cerebral metabolic rate (CMR) was estimated using two models of EEG power, based on: (1) normalization of BMR by total body mass, and (2) scaling by cortical grey matter. RESULTS: Regression analysis revealed a linear relationship between the CMR estimates and EEG power under both models. In the full sample, CMR explained 65% of the variance in delta power, and 53% of the variance in theta power over the age span. DISCUSSION: The results demonstrate that the large EEG signals in early childhood are associated with a higher BMR during that age. INTEGRATIVE SIGNIFICANCE: The use of cross-modal measurements in this study highlights the utility of capturing data in an integrative framework to reveal fundamental physiological relationships.

A controlled investigation into the psychological determinants of fatigue.

Driver fatigue is associated with risks of road accidents that result in injury and death. Research has been limited by several issues such as confusion over definitions, how best to measure fatigue, and the contribution of psychological factors to fatigue. This study addressed these limitations by investigating the relationship between psychological factors and fatigue. Participants were assessed and were required to perform a monotonous task till they tired. Results found few psychological factors to be related to physiological and performance decrement fatigue outcome measures. However, psychological factors were found to correlate consistently with self-reported fatigue. The results suggest that fatigue is associated with a predisposition to be anxious, depressive, less self-assured, more conscientious (rule bound), less socially bold, less adaptable and low vigour. The results indicate that future research should employ a range of fatigue outcome measures in order to best understand what factors contribute to fatigue.

Personality traits and its association with resting regional brain activity.

The association between personality and resting brain activity was investigated. Personality was assessed using the NEO-Five-factor Inventory (NEO-FFI) and resting brain activity was indexed by eyes closed EEG spectral magnitude from four frequency bands over the entire cortex. Results suggest that there are differences between males and females in the NEO-FFI personality traits. The NEO FFI traits were associated with lower frequency brain activity in both males and females. Mild significant and consistent associations were found between delta and theta activity across all cortical regions with Extraversion and Conscientiousness. There were few associations between personality traits and alpha and beta activity, this was shown in males only. Fewer associations between personality and faster frequency bands such as alpha may be due to the methodological problem of using fixed alpha bands. Multiple regression analyses showed that individual alpha frequencies had a greater contribution to personality traits than fixed band alpha waves.

The efficacy and benefits of environmental control systems for the severely disabled.

BACKGROUND: People living with a severe disability suffer substantial personal and social consequences that reduce quality of life (QOL). One potential negative impact on the QOL of a disabled person is the loss of the ability to control devices in their immediate environment (such as the television, computer, telephones, lights, doors, etc.). Consequently, research and development has been conducted on technology designed to restore independence by providing some means of control over these devices. Technology that allows a severely disabled person to gain this type of control has been called an environmental control system (ECS). The aim of this review was to evaluate critically the status and efficacy of ECS technology for the severely disabled. MATERIALS/METHODS: To achieve this, a comprehensive database search was conducted for relevant material on technical and clinical aspects of ECS control. RESULTS: The review demonstrated that there is an abundance of work conducted on ECS technology, resulting in a number of creative control systems that are designed to be used by the severely disabled. These include switching systems that utilize voice, muscle, brain activity, head motion, eye blink, breath, chin, and so on. However, the review also established that rarely has the efficacy of these systems been scientifically established. CONCLUSIONS: Severely disabled persons need access to ECS technology that has been shown to be efficacious. While the severely disabled gain benefits from using ECS technology, challenges still exist before ECS technology for the severely disabled can provide highly reliable and user-friendly device control.

Brain-Computer Interface-FES Integration: Towards a Hands-free Neuroprosthesis Command System.

This paper presents a critical review of brain-computer interfaces (BCIs) and their potential for neuroprosthetic applications. Summaries are provided for the command interface requirements of hand grasp, multijoint, and lower extremity neuroprostheses, and the characteristics of various BCIs are discussed in relation to these requirements. The review highlights the current limitations of BCIs and areas of research that need to be addressed to enhance BCI-FES integration.

Development of an algorithm for an EEG-based driver fatigue countermeasure.

PROBLEM: Fatigue affects a driver's ability to proceed safely. Driver-related fatigue and/or sleepiness are a significant cause of traffic accidents, which makes this an area of great socioeconomic concern. Monitoring physiological signals while driving provides the possibility of detecting and warning of fatigue. The aim of this paper is to describe an EEG-based fatigue countermeasure algorithm and to report its reliability. METHOD: Changes in all major EEG bands during fatigue were used to develop the algorithm for detecting different levels of fatigue. RESULTS: The software was shown to be capable of detecting fatigue accurately in 10 subjects tested. The percentage of time the subjects were detected to be in a fatigue state was significantly different than the alert phase (P<.01). DISCUSSION: This is the first countermeasure software described that has shown to detect fatigue based on EEG changes in all frequency bands. Field research is required to evaluate the fatigue software in order to produce a robust and reliable fatigue countermeasure system. IMPACT ON INDUSTRY: The development of the fatigue countermeasure algorithm forms the basis of a future fatigue countermeasure device. Implementation of electronic devices for fatigue detection is crucial for reducing fatigue-related road accidents and their associated costs.