Neural correlates of the difference between working memory speed and simple sensorimotor speed: an fMRI study

The difference between the speed of simple cognitive processes and the speed of complex cognitive processes has various psychological correlates. However, the neural correlates of this difference have not yet been investigated. In this study, we focused on working memory (WM) for typical complex cognitive processes. Functional magnetic resonance imaging data were acquired during the performance of an N-back task, which is a measure of WM for typical complex cognitive processes. In our N-back task, task speed and memory load were varied to identify the neural correlates responsible for the difference between the speed of simple cognitive processes (estimated from the 0-back task) and the speed of WM. Our findings showed that this difference was characterized by the increased activation in the right dorsolateral prefrontal cortex (DLPFC) and the increased functional interaction between the right DLPFC and right superior parietal lobe. Furthermore, the local gray matter volume of the right DLPFC was correlated with participants' accuracy during fast WM tasks, which in turn correlated with a psychometric measure of participants' intelligence. Our findings indicate that the right DLPFC and its related network are responsible for the execution of the fast cognitive processes involved in WM. Identified neural bases may underlie the psychometric differences between the speed with which subjects perform simple cognitive tasks and the speed with which subjects perform more complex cognitive tasks, and explain the previous traditional psychological findings.     

Cerebral blood flow during rest associates with general intelligence and creativity

Recently, much scientific attention has been focused on resting brain activity and its investigation through such methods as the analysis of functional connectivity during rest (the temporal correlation of brain activities in different regions). However, investigation of the magnitude of brain activity during rest has focused on the relative decrease of brain activity during a task, rather than on the absolute resting brain activity. It is thus necessary to investigate the association between cognitive factors and measures of absolute resting brain activity, such as cerebral blood flow (CBF), during rest (rest-CBF). In this study, we examined this association using multiple regression analyses. Rest-CBF was the dependent variable and the independent variables included two essential components of cognitive functions, psychometric general intelligence and creativity. CBF was measured using arterial spin labeling and there were three analyses for rest-CBF; namely mean gray matter rest-CBF, mean white matter rest-CBF, and regional rest-CBF. The results showed that mean gray and white matter rest-CBF were significantly and positively correlated with individual psychometric intelligence. Furthermore, mean white matter rest-CBF was significantly and positively correlated with creativity. After correcting the effect of mean gray matter rest-CBF the significant and positive correlation between regional rest-CBF in the perisylvian anatomical cluster that includes the left superior temporal gyrus and insula and individual psychometric intelligence was found. Also, regional rest-CBF in the precuneus was significantly and negatively correlated with individual creativity. Significance of these results of regional rest-CBF did not change when the effect of regional gray matter density was corrected. The findings showed mean and regional rest-CBF in healthy young subjects to be correlated with cognitive functions. The findings also suggest that, even in young cognitively intact subjects, resting brain activity (possibly underlain by default cognitive activity or metabolic demand from developed brain structures) is associated with cognitive functions.     

Imaging-Based Biomarkers of Cognitive Performance in Older Adults Constructed via High-Dimensional Pattern Regression Applied to MRI and PET

In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.     

Investigating structural brain changes of dehydration using voxel-based morphometry

Dehydration can affect the volume of brain structures, which might imply a confound in volumetric and morphometric studies of normal or diseased brain. Six young, healthy volunteers were repeatedly investigated using three-dimensional T(1)-weighted magnetic resonance imaging during states of normal hydration, hyperhydration, and dehydration to assess volume changes in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). The datasets were analyzed using voxel-based morphometry (VBM), a widely used voxel-wise statistical analysis tool, FreeSurfer, a fully automated volumetric segmentation measure, and SIENAr a longitudinal brain-change detection algorithm. A significant decrease of GM and WM volume associated with dehydration was found in various brain regions, most prominently, in temporal and sub-gyral parietal areas, in the left inferior orbito-frontal region, and in the extra-nuclear region. Moreover, we found consistent increases in CSF, that is, an expansion of the ventricular system affecting both lateral ventricles, the third, and the fourth ventricle. Similar degrees of shrinkage in WM volume and increase of the ventricular system have been reported in studies of mild cognitive impairment or Alzheime [Formula: see text]s disease during disease progression. Based on these findings, a potential confound in GM and WM or ventricular volume studies due to the subjects' hydration state cannot be excluded and should be appropriately addressed in morphometric studies of the brain.     

Grey matter lesions in MS

Although multiple sclerosis (MS) is a chronic inflammatory-demyelinating disease of the white matter (WM) of the central nervous system, several pathological and magnetic resonance imaging (MRI) studies have shown that a large amount of lesions are located in the cortical and deep gray matter. The histopathological and immunological characteristics of cortical lesions differ significantly from those located in the WM, which suggests a location-dependent expression of the MS immunopathological process. More recently, the availability of not-conventional MRI sequences having higher sensitivity for the gray matter has allowed to depict in vivo a portion of such lesions. The available MRI data obtained on large cohorts of patients, having different clinical forms of the disease, indicate that cortical lesions can be detected early in the disease course, sometimes even before the appearance of WM lesions, and correlate with the severity of physical disability and cognitive impairment, and with the evolution of the disease toward the secondary progressive phase. This review provides a summary of the main histopathological and MRI findings of cortical lesions in MS and discusses their possible clinical implications.     

White matter integrity and vulnerability to Alzheimer's disease: Preliminary findings and future directions

Neuroimaging biomarkers that precede cognitive decline have the potential to aid early diagnosis of Alzheimer's disease (AD). A body of diffusion tensor imaging (DTI) work has demonstrated declines in white matter (WM) microstructure in AD and its typical prodromal state, amnestic mild cognitive impairment. The present review summarizes recent evidence suggesting that WM integrity declines are present in individuals at high AD-risk, prior to cognitive decline. The available data suggest that AD-risk is associated with WM integrity declines in a subset of tracts showing decline in symptomatic AD. Specifically, AD-risk has been associated with WM integrity declines in tracts that connect gray matter structures associated with memory function. These tracts include parahippocampal WM, the cingulum, the inferior fronto-occipital fasciculus, and the splenium of the corpus callosum. Preliminary evidence suggests that some AD-risk declines are characterized by increases of radial diffusivity, raising the possibility that a myelin-related pathology may contribute to AD onset. These findings justify future research aimed at a more complete understanding of the neurobiological bases of DTI-based declines in AD. With continued refinement of imaging methods, DTI holds promise as a method to aid identification of presymptomatic AD. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.     

White matter integrity and vulnerability to Alzheimer's disease: preliminary findings and future directions

Neuroimaging biomarkers that precede cognitive decline have the potential to aid early diagnosis of Alzheimer's disease (AD). A body of diffusion tensor imaging (DTI) work has demonstrated declines in white matter (WM) microstructure in AD and its typical prodromal state, amnestic mild cognitive impairment. The present review summarizes recent evidence suggesting that WM integrity declines are present in individuals at high AD-risk, prior to cognitive decline. The available data suggest that AD-risk is associated with WM integrity declines in a subset of tracts showing decline in symptomatic AD. Specifically, AD-risk has been associated with WM integrity declines in tracts that connect gray matter structures associated with memory function. These tracts include parahippocampal WM, the cingulum, the inferior fronto-occipital fasciculus, and the splenium of the corpus callosum. Preliminary evidence suggests that some AD-risk declines are characterized by increases of radial diffusivity, raising the possibility that a myelin-related pathology may contribute to AD onset. These findings justify future research aimed at a more complete understanding of the neurobiological bases of DTI-based declines in AD. With continued refinement of imaging methods, DTI holds promise as a method to aid identification of presymptomatic AD. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.     

White Matter Integrity Supports BOLD Signal Variability and Cognitive Performance in the Aging Human Brain

Decline in cognitive performance in old age is linked to both suboptimal neural processing in grey matter (GM) and reduced integrity of white matter (WM), but the whole-brain structure-function-cognition associations remain poorly understood. Here we apply a novel measure of GM processing–moment-to-moment variability in the blood oxygenation level-dependent signal (SD_BOLD)—to study the associations between GM function during resting state, performance on four main cognitive domains (i.e., fluid intelligence, perceptual speed, episodic memory, vocabulary), and WM microstructural integrity in 91 healthy older adults (aged 60-80 years). We modeled the relations between whole-GM SD_BOLD with cognitive performance using multivariate partial least squares analysis. We found that greater SD_BOLD was associated with better fluid abilities and memory. Most of regions showing behaviorally relevant SD_BOLD (e.g., precuneus and insula) were localized to inter- or intra-network “hubs” that connect and integrate segregated functional domains in the brain. Our results suggest that optimal dynamic range of neural processing in hub regions may support cognitive operations that specifically rely on the most flexible neural processing and complex cross-talk between different brain networks. Finally, we demonstrated that older adults with greater WM integrity in all major WM tracts had also greater SD_BOLD and better performance on tests of memory and fluid abilities. We conclude that SD_BOLD is a promising functional neural correlate of individual differences in cognition in healthy older adults and is supported by overall WM integrity.     

Longitudinal Neurostimulation in Older Adults Improves Working Memory

An increasing concern affecting a growing aging population is working memory (WM) decline. Consequently, there is great interest in improving or stabilizing WM, which drives expanded use of brain training exercises. Such regimens generally result in temporary WM benefits to the trained tasks but minimal transfer of benefit to untrained tasks. Pairing training with neurostimulation may stabilize or improve WM performance by enhancing plasticity and strengthening WM-related cortical networks. We tested this possibility in healthy older adults. Participants received 10 sessions of sham (control) or active (anodal, 1.5 mA) tDCS to the right prefrontal, parietal, or prefrontal/parietal (alternating) cortices. After ten minutes of sham or active tDCS, participants performed verbal and visual WM training tasks. On the first, tenth, and follow-up sessions, participants performed transfer WM tasks including the spatial 2-back, Stroop, and digit span tasks. The results demonstrated that all groups benefited from WM training, as expected. However, at follow-up 1-month after training ended, only the participants in the active tDCS groups maintained significant improvement. Importantly, this pattern was observed for both trained and transfer tasks. These results demonstrate that tDCS-linked WM training can provide long-term benefits in maintaining cognitive training benefits and extending them to untrained tasks.     

Capacity-speed relationships in prefrontal cortex

Working memory (WM) capacity and WM processing speed are simple cognitive measures that underlie human performance in complex processes such as reasoning and language comprehension. These cognitive measures have shown to be interrelated in behavioral studies, yet the neural mechanism behind this interdependence has not been elucidated. We have carried out two functional MRI studies to separately identify brain regions involved in capacity and speed. Experiment 1, using a block-design WM verbal task, identified increased WM capacity with increased activity in right prefrontal regions, and Experiment 2, using a single-trial WM verbal task, identified increased WM processing speed with increased activity in similar regions. Our results suggest that right prefrontal areas may be a common region interlinking these two cognitive measures. Moreover, an overlap analysis with regions associated with binding or chunking suggest that this strategic memory consolidation process may be the mechanism interlinking WM capacity and WM speed.     

Colorization and automated segmentation of human T2 MR brain images for characterization of soft tissues

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described.     

Relating Inter-Individual Differences in Verbal Creative Thinking to Cerebral Structures: An Optimal Voxel-Based Morphometry Study

Creativity can be defined the capacity of an individual to produce something original and useful. An important measurable component of creativity is divergent thinking. Despite existing studies on creativity-related cerebral structural basis, no study has used a large sample to investigate the relationship between individual verbal creativity and regional gray matter volumes (GMVs) and white matter volumes (WMVs). In the present work, optimal voxel-based morphometry (VBM) was employed to identify the structure that correlates verbal creativity (measured by the verbal form of Torrance Tests of Creative Thinking) across the brain in young healthy subjects. Verbal creativity was found to be significantly positively correlated with regional GMV in the left inferior frontal gyrus (IFG), which is believed to be responsible for language production and comprehension, new semantic representation, and memory retrieval, and in the right IFG, which may involve inhibitory control and attention switching. A relationship between verbal creativity and regional WMV in the left and right IFG was also observed. Overall, a highly verbal creative individual with superior verbal skills may demonstrate a greater computational efficiency in the brain areas involved in high-level cognitive processes including language production, semantic representation and cognitive control.     

Integration of Diffusion Magnetic Resonance Tractography into tomotherapy radiation treatment planning for high-grade gliomas

IntroductionFractionated radiotherapy in brain tumors is commonly associated with several detrimental effects, largely related to the higher radiosensitivity of the white matter (WM) with respect to gray matter. However, no dose constraints are applied to preserve WM structures at present. Magnetic Resonance (MR) Tractography is the only technique that allows to visualize in vivo the course of WM eloquent tracts in the brain. In this study, the feasibility of integrating MR Tractography in tomotherapy treatment planning has been investigated, with the aim to spare eloquent WM regions from the dose delivered during treatment.MethodsNineteen high grade glioma patients treated with fractionated radiotherapy were enrolled. All the patients underwent pre-treatment MR imaging protocol including Diffusion Tensor Imaging (DTI) acquisitions for MR Tractography analysis. Bilateral tracts involved in several motor, language, cognitive functions were reconstructed and these fiber bundles were integrated into the Tomotherapy Treatment planning system. The original plans without tracts were compared with the optimized plans incorporating the fibers, to evaluate doses to WM structures in the two differently optimized plans.ResultsNo significant differences were found between plans in terms of planning target volume (PTV) coverage between the original plans and the optimized plans incorporating fiber tracts. Comparing the mean as well as the maximal dose (Dmean and Dmax), a significant dose reduction was found for most of the tracts. The dose sparing was more relevant for contralateral tracts (P < 0.0001).ConclusionThe integration of MR Tractography into radiotherapy planning is feasible and beneficial to preserve important WM structures without reducing the clinical goal of radiation treatment.     

Suppressing the Encoding of New Information in Memory: A Behavioral Study Derived from Principles of Hippocampal Function

Cognitive processes do not occur in isolation. Interactions between cognitive processes can be observed as a cost in performance following a switch between tasks, a cost that is greatest when the cognitive requirements of the sequential tasks compete. Interestingly, the long-term mnemonic goals associated with specific cognitive tasks can also directly compete. For example, encoding the sequential order in which stimuli are presented in the commonly-utilised 2-Back working memory (WM) tasks is counter-productive to task performance, as this task requires the continual updating of the contents of one''s current mental set. Performance of this task consistently results in reduced activity within the medial temporal lobe (MTL), and this response is believed to reflect the inhibitory mnemonic component of the task. Conversely, there are numerous cognitive paradigms in which participants are explicitly instructed to encode incoming information and performance of these tasks reliably increases MTL activity. Here, we explore the behavioural cost of sequentially performing two tasks with conflicting long-term mnemonic goals and contrasting neural profiles within the MTL. We hypothesised that performing the 2-Back WM prior to a hippocampal-dependent memory task would impair performance on the latter task. We found that participants who performed the 2-Back WM task, prior to the encoding of novel verbal/face-name stimuli, recollected significantly fewer of these stimuli, compared to those who had performed a 0-Back control task. Memory processes believed to be independent of the MTL were unaffected. Our results suggest that the inhibition of MTL-dependent mnemonic function persists beyond the cessation of the 2-Back WM task and can alter performance on entirely separate and subsequently performed memory tasks. Furthermore, they indicate that performance of such tasks may induce a temporarily-sustained, virtual lesion of the hippocampus, which could be used as a probe to explore cognitive processes in the absence of hippocampal involvement.     

Multi-parametric neuroimaging evaluation of cerebrotendinous xanthomatosis and its correlation with neuropsychological presentations

Background

Cerebrotendinous xanthomatosis (CTX) is a rare genetic disorder. Recent studies show that brain damage in CTX patients extends beyond the abnormalities observed on conventional magnetic resonance imaging (MRI). We studied the MRI and ^{99 m}Tc-ethyl cysteinate dimer single photon emission computed tomography (SPECT) findings of CTX patients and made a correlation with the neuropsychological presentations.

Methods

Diffusion tensor imaging (DTI) and 3D T1-weighted images of five CTX patients were compared with 15 age-matched controls. Voxel-based morphometry (VBM) was use to delineate gray matter (GM) and white matter (WM) volume loss. Fractional anisotropy (FA), mean diffusivity (MD), and eigenvalues derived from DTI were used to detect WM changes and correlate with neuropsychological results. SPECT functional studies were used to correlate with GM changes.

Results

Cognitive results showed that aside from moderate mental retardation, the patient group performed worse in all cognitive domains. Despite the extensive GM atrophy pattern, the cerebellum, peri-Sylvian regions and parietal-occipital regions were correlated with SPECT results. WM atrophy located in the peri-dentate and left cerebral peduncle areas corresponded with changes in diffusion measures, while axial and radial diffusivity suggested both demyelinating and axonal changes. Changes in FA and MD were preceded by VBM in the corpus callosum and corona radiata. Cognitive results correlated with FA changes.

Conclusion

In CTX, GM atrophy affected the perfusion patterns. Changes in WM included atrophy, and axonal changes with demyelination. Disconnection of major fiber tracts among different cortical regions may contribute to cognitive impairment.

     

Long-Term Occupational Stress Is Associated with Regional Reductions in Brain Tissue Volumes

There are increasing reports of cognitive and psychological declines related to occupational stress in subjects without psychiatric premorbidity or major life trauma. The underlying neurobiology is unknown, and many question the notion that the described disabilities represent a medical condition. Using PET we recently found that persons suffering from chronic occupational stress had limbic reductions in the 5-HT1A receptor binding potential. Here we examine whether chronic work-related stress is also associated with changes in brain structure. We performed MRI-based voxel-based morphometry and structural volumetry in stressed subjects and unstressed controls focusing on gray (GM) and white matter (WM) volumes, and the volumes of hippocampus, caudate, and putamen – structures known to be susceptible to neurotoxic changes. Stressed subjects exhibited significant reductions in the GM volumes of the anterior cingulate cortex and the dorsolateral prefrontal cortex. Furthermore, their caudate and putamen volumes were reduced, and the volumes correlated inversely to the degree of perceived stress. Our results add to previous data on chronic psychosocial stress, and indicate a morphological involvement of the frontostriatal circuits. The present findings of morphological changes in these regions confirm our previous conclusion that symptoms from occupational stress merit careful investigations and targeted treatment.     

Political orientations are correlated with brain structure in young adults

Substantial differences exist in the cognitive styles of liberals and conservatives on psychological measures. Variability in political attitudes reflects genetic influences and their interaction with environmental factors. Recent work has shown a correlation between liberalism and conflict-related activity measured by event-related potentials originating in the anterior cingulate cortex. Here we show that this functional correlate of political attitudes has a counterpart in brain structure. In a large sample of young adults, we related self-reported political attitudes to gray matter volume using structural MRI. We found that greater liberalism was associated with increased gray matter volume in the anterior cingulate cortex, whereas greater conservatism was associated with increased volume of the right amygdala. These results were replicated in an independent sample of additional participants. Our findings extend previous observations that political attitudes reflect differences in self-regulatory conflict monitoring and recognition of emotional faces by showing that such attitudes are reflected in human brain structure. Although our data do not determine whether these regions play a causal role in the formation of political attitudes, they converge with previous work to suggest a possible link between brain structure and psychological mechanisms that mediate political attitudes.     

Age-related white matter microstructural differences partly mediate age-related decline in processing speed but not cognition

Aging is associated with declining cognitive performance as well as structural changes in brain gray and white matter (WM). The WM deterioration contributes to a disconnection among distributed brain networks and may thus mediate age-related cognitive decline. The present diffusion tensor imaging (DTI) study investigated age-related differences in WM microstructure and their relation to cognition (episodic memory, visuospatial processing, fluency, and speed) in a large group of healthy subjects (n = 287) covering 6 decades of the human life span. Age related decreases in fractional anisotropy (FA) and increases in mean diffusivity (MD) were observed across the entire WM skeleton as well as in specific WM tracts, supporting the WM degeneration hypothesis. The anterior section of the corpus callosum was more susceptible to aging compared to the posterior section, lending support to the anterior-posterior gradient of WM integrity in the corpus callosum. Finally, and of critical interest, WM integrity differences were found to mediate age-related reductions in processing speed but no significant mediation was found for episodic memory, visuospatial ability, or fluency. These findings suggest that compromised WM integrity is not a major contributing factor to declining cognitive performance in normal aging. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.     

Bayesian estimation of probabilistic atlas for tissue segmentation

Automatic anatomical brain image segmentation is still a challenge. In particular, algorithms have to address the partial volume effect (PVE) as well as the variability of the gray level of internal brain structures which may appear closer to gray matter (GM) than white matter (WM). Atlas based segmentation is one solution as it brings prior information. For such tasks, probabilistic atlases are very useful as they take account of the PVE information. In this paper, we provide a detailed analysis of a generative statistical model based on dense deformable templates that represents several tissue types observed in medical images. The inputs are gray level data whereas our atlas is composed of both an estimation of the deformation metric and probability maps of each tissue (called class). This atlas is used to guide the tissue segmentation of new images. Experiments are shown on brain T1 MRI datasets. This method only requires approximate pre-registration, as the latter is done jointly with the segmentation. Note however that an approximate registration is a reasonable pre-requisite given the application.     

BOLD Correlates of Trial-by-Trial Reaction Time Variability in Gray and White Matter: A Multi-Study fMRI Analysis

Background

Reaction time (RT) is one of the most widely used measures of performance in experimental psychology, yet relatively few fMRI studies have included trial-by-trial differences in RT as a predictor variable in their analyses. Using a multi-study approach, we investigated whether there are brain regions that show a general relationship between trial-by-trial RT variability and activation across a range of cognitive tasks.

Methodology/Principal Findings

The relation between trial-by-trial differences in RT and brain activation was modeled in five different fMRI datasets spanning a range of experimental tasks and stimulus modalities. Three main findings were identified. First, in a widely distributed set of gray and white matter regions, activation was delayed on trials with long RTs relative to short RTs, suggesting delayed initiation of underlying physiological processes. Second, in lateral and medial frontal regions, activation showed a “time-on-task” effect, increasing linearly as a function of RT. Finally, RT variability reliably modulated the BOLD signal not only in gray matter but also in diffuse regions of white matter.

Conclusions/Significance

The results highlight the importance of modeling trial-by-trial RT in fMRI analyses and raise the possibility that RT variability may provide a powerful probe for investigating the previously elusive white matter BOLD signal.