Whilst the concept of a general mental factor known as 'g' has been of longstanding interest, for... more Whilst the concept of a general mental factor known as 'g' has been of longstanding interest, for unknown reasons, it has never been interrogated in epilepsy despite the 100+ year empirical history of the neuropsychology of epilepsy. This investigation seeks to identify g within a comprehensive neuropsychological data set and compare participants with temporal lobe epilepsy to controls, characterize the discriminatory power of g compared with domain-specific cognitive metrics, explore the association of g with clinical epilepsy and sociodemographic variables and identify the structural and network properties associated with g in epilepsy. Participants included 110 temporal lobe epilepsy patients and 79 healthy controls between the ages of 19 and 60. Participants underwent neuropsychological assessment, clinical interview and structural and functional imaging. Cognitive data were subjected to factor analysis to identify g and compare the group of patients with control participants. The relative power of g compared with domain-specific tests was interrogated, clinical and sociodemographic variables were examined for their relationship with g, and structural and functional images were assessed using traditional regional volumetrics, cortical surface features and network analytics. Findings indicate (i) significantly (P < 0.005) lower g in patients compared with controls; (ii) g is at least as powerful as individual cognitive domain-specific metrics and other analytic approaches to discriminating patients from control participants; (iii) lower g was associated with earlier age of onset and medication use, greater number of antiseizure medications and longer epilepsy duration (Ps < 0.04); and lower parental and personal education and greater neighbourhood deprivation (Ps < 0.012); and (iv) amongst patients, lower g was linked to decreased total intracranial volume (P = 0.019), age and intracranial volume adjusted total tissue volume (P = 0.019) and age and intracranial volume adjusted total corpus callosum volume (P = 0.012)-particularly posterior, mid-posterior and anterior (Ps < 0.022) regions. Cortical vertex analyses showed lower g to be associated specifically with decreased gyrification in bilateral medial orbitofrontal regions. Network analysis of resting-state data with focus on the participation coefficient showed g to be associated with the superior parietal network. Spearman's g is reduced in patients, has considerable discriminatory power compared with domain-specific metrics and is linked to a multiplex of factors related to brain (size, connectivity and frontoparietal networks), environment (familial and personal education and neighbourhood disadvantage) and disease (epilepsy onset, treatment and duration). Greater attention to contemporary models of human cognition is warranted in order to advance the neuropsychology of epilepsy.
The recent revision of the classification of the epilepsies released by the ILAE Commission on Cl... more The recent revision of the classification of the epilepsies released by the ILAE Commission on Classification and Terminology (2005-2009) has been a major development in the field. Papers in this section of the special issue were charged with examining the relevance of other techniques and approaches to examining, categorizing and classifying cognitive and behavioral comorbidities. In that light, we investigate the applicability of graph theory to understand the impact of epilepsy on cognition compared to controls, and then the patterns of cognitive development in normally developing children which would set the stage for prospective comparisons of children with epilepsy and controls. The overall goal is to examine the potential utility of other analytic tools and approaches to conceptualize the cognitive comorbidities in epilepsy. Given that the major cognitive domains representing cognitive function are interdependent, the associations between the neuropsychological abilities underlying these domains can be referred to as a cognitive network. Therefore, the architecture of this cognitive network can be quantified and assessed using graph theory methods, rendering a novel approach to the characterization of cognitive status. In this article we provide fundamental information about graph theory procedures, followed by application of these techniques to cross-sectional analysis of neuropsychological data in children with epilepsy compared to controls, finalizing with prospective analysis of neuropsychological development in younger and older healthy controls.
The recent revision of the classification of the epilepsies released by the ILAE Commission on Cl... more The recent revision of the classification of the epilepsies released by the ILAE Commission on Classification and Terminology (2005-2009) has been a major development in the field. Papers in this section of the special issue were charged with examining the relevance of other techniques and approaches to examining, categorizing and classifying cognitive and behavioral comorbidities. In that light, we investigate the applicability of graph theory to understand the impact of epilepsy on cognition compared to controls, and then the patterns of cognitive development in normally developing children which would set the stage for prospective comparisons of children with epilepsy and controls. The overall goal is to examine the potential utility of other analytic tools and approaches to conceptualize the cognitive comorbidities in epilepsy. Given that the major cognitive domains representing cognitive function are interdependent, the associations between the neuropsychological abilities underlying these domains can be referred to as a cognitive network. Therefore, the architecture of this cognitive network can be quantified and assessed using graph theory methods, rendering a novel approach to the characterization of cognitive status. In this article we provide fundamental information about graph theory procedures, followed by application of these techniques to cross-sectional analysis of neuropsychological data in children with epilepsy compared to controls, finalizing with prospective analysis of neuropsychological development in younger and older healthy controls.
Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a n... more Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE. SVM was able to predict group membership (mean accuracy = 0.70, area under the curve (AUC) = 0.747, Brier score (BS) = 0.264) using 10-fold cross-validation. In addition, k-means clustering identified 2 TLE clusters: 1 similar to controls, and 1 dissimilar. Clusters were significantly different in their distribution of cognitive phenotypes, with the Dissimilar cluster containing the majority of TLE with cognitive impairment (χ 2 = 6.641, P = 0.036). In addition, cluster membership showed significant correlations between GT measures and clinical variables. Given that SVM classification seemed driven by the Dissimilar cluster, SVM analysis was repeated to classify Dissimilar versus Similar + Controls with a mean accuracy of 0.91 (AUC = 0.957, BS = 0.189). Altogether, the pattern of results shows that GT measures based on connectome DWI could be significant factors in the search for clinical and neurobehavioral biomarkers in TLE.
Ischemic stroke is a worldwide problem, with 15 million people experiencing a stroke annually. MR... more Ischemic stroke is a worldwide problem, with 15 million people experiencing a stroke annually. MR imaging is a valuable tool for understanding and assessing brain changes after stroke and predicting recovery. Of particular interest is the use of diffusion MR imaging in the nonacute stage 1-30 days poststroke. Thousands of articles have been published on the use of diffusion MR imaging in stroke, including several recent articles reviewing the use of DTI for stroke. The goal of this work was to survey and put into context the recent use of diffusion MR imaging methods beyond DTI, including diffusional kurtosis, generalized fractional anisotropy, spherical harmonics methods, and neurite orientation and dispersion models, in patients poststroke. Early studies report that these types of beyond-DTI methods outperform DTI metrics either in being more sensitive to poststroke changes or by better predicting outcome motor scores. More and larger studies are needed to confirm the improved prediction of stroke recovery with the beyond-DTI methods.
Background: There has been increasing recognition for the decline of motor function in Alzheimer&... more Background: There has been increasing recognition for the decline of motor function in Alzheimer&#39;s disease (AD) progression and its substantial role in disease morbidity. However, less is known about regional pathology burden-including amyloid-β and tau protein deposition and cortical trophy-and its relationship to motor performance. Here investigate this relationship using standardized motor function assessment tools.
Resting state functional connectivity (rFC) is used to identify functionally related brain areas ... more Resting state functional connectivity (rFC) is used to identify functionally related brain areas without requiring subjects to perform specific tasks. Previous work suggests that prior brain state, as determined by the activity engaged in immediately prior to collection of resting state data, can influence the networks recovered by rFC analyses. We determined the prevalence and network specificity of rFC changes induced by manipulations of prior state (including an unstructured (unconstrained) state, and language and motor tasks). Three blocks of rest data (one after each of the specified prior states) were acquired on each of 25 subjects. We hypothesised that prior state induced changes in rFC would be greatest within the networks most actively recruited by that prior state. Changes in rFC were greatest following the motor task and, contrary to our hypothesis, were not network specific. This was demonstrated by comparing (1) the timecourses within a set of ROIs selected on the basis of task-related de/activation, and (2) seed-based whole brain voxel-wise connectivity maps, seeded from local maxima in the task-related de/activation maps. Changes in connectivity strength tended to manifest as increases in rFC relative to that in the unstructured rest state, with change maps resembling partially complete maps of the primary sensory cortices and the cognitive control network. The majority of rFC changes occurred in areas moderately (but not weakly) connected to the seeds. Constrained prior states were associated with lower across-participant variance in rFC. This systematic investigation of the effect of prior brain state on rFC indicates that the rFC changes induced by prior brain state occur both in brain networks related to that brain activity and in networks nominally unrelated to that brain activity.
Objective: Stroke can have important effects on widespread brain regions resulting in network dis... more Objective: Stroke can have important effects on widespread brain regions resulting in network disruption. This study investigates the changes in spontaneous activity in the brain after stroke using resting-state functional connectivity(FC) MRI. Methods: Acute ischemic stroke patients (N=22, 11 cortical, mean age=60, 10F) were recruited within 7 days of stroke onset(timepoint 1, V1). Eleven of these patients were also scanned at timepoint 2(V2), approximately 3 months later. Age-matched healthy controls (N=17, mean age = 56, 7F) and 7 patients with risk factors for stroke (mean age=67, 1F) were also recruited in the study. Ten minute eyes-closed resting-state fMRI scans were collected along with a high resolution anatomical scan. We examined FC in the language network consisting of ten regions extracted based on functional activations on a phonemic fluency task performed during a separate scan. We also examined the correlation of brain FC with behavioral performance on the task outside the scanner. Results: We examined correlation between every seed region and every other region in the network(45 seed region-pairs). Compared to age-matched controls, acute strokes showed significantly reduced inter-hemispheric connectivity, specifically between inferior frontal and temporal regions(p<.001 corrected). This difference however was not significant in the sub-acute stage(Figure 1 left panel). Additionally, although both acute and sub-acute patients showed significant differences in performance compared to normals on phonemic fluency(Fig 1 right), there were no significant correlations between brain FC measures and behavior and no differences in the correlation between brain FC and behavior among the groups.
12-16 min. Consequently, new techniques that improve reliability across sessions will be importan... more 12-16 min. Consequently, new techniques that improve reliability across sessions will be important for the 40 interpretation of longitudinal fMRI studies.
Background: There has been increasing recognition for the decline of motor function in Alzheimer'... more Background: There has been increasing recognition for the decline of motor function in Alzheimer's disease (AD) progression and its substantial role in disease morbidity. However, less is known about regional pathology burden-including amyloid-β and tau protein deposition and cortical trophy-and its relationship to motor performance. Here investigate this relationship using standardized motor function assessment tools.
12-16 min. Consequently, new techniques that improve reliability across sessions will be importan... more 12-16 min. Consequently, new techniques that improve reliability across sessions will be important for the 40 interpretation of longitudinal fMRI studies.
Background: Brain myelin is known to play an important role in maintaining optimal neuronal funct... more Background: Brain myelin is known to play an important role in maintaining optimal neuronal function, with deficits in myelin leading to worse performance on cognitive tests. The extent to which cortex-specific myelin is associated with other cognitive domains, or is impacted by disease processes such as Alzheimer&#39;s disease (AD), is unknown. Here we leverage MPnRAGE-derived quantitative R1 (Kecskemeti et al., 2016; 2018), a metric sensitive to brain myelin, to assess the role of intracortical myelin in performance on tests of executive function (exec_func), working memory (work-ing_mem), and processing speed (process_speed) in older adults who ranged from cognitively unimpaired to those with dementia. Method: 143 older adults (N=75 cognitively unimpaired, N=44 mild cognitive impairment, N=24 dementia) enrolled in the Alzheimer&#39;s Disease Connectome Project underwent T1-weighted (T1w) MPnRAGE MRI with motion-correction and testing via the NIH Toolbox Cognitive Battery. Inherently registered quantitative R1 maps and T1w images were reconstructed at 1mm isotropic resolution. The image processing pipeline and composite regions of interest (ROIs) used for analysis can be viewed in Figure 1. Uncorrected standard scores were computed by the NIH Toolbox for each measure of exec_func (dimensional change card sort), working_mem (list sorting), and process_speed (pattern comparison). Multiple linear regression models were employed in R with test scores as the dependent variable, regional R1 as the predictor of interest, and age, sex, and education as covariates. Result: Higher R1 was associated with worse exec_func in regions that are affected in AD, including posterior cingulate (ß =-62.47, t(1,138) =-2.42, p = 0.017) and temporal cortices(ß =-123.05, t(1,138) =-2.77, p = 0.0064) ROIs. Additionally, higher R1 in temporal cortices was associated with worse working_mem (ß =-158.16, t(1,133) =-2.84, p = 0.0053) (Figure 2). There were no significant associations between process_speed and regional cortical R1. Conclusion: Unexpectedly, higher regional cortical myelin (as indexed by R1) was associated with worse exec_func and working_mem, suggesting higher R1 may be
PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral mu... more PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
Rs-fMRI has been shown to be a valuable neuroimaging modality to study the pathophysiological mec... more Rs-fMRI has been shown to be a valuable neuroimaging modality to study the pathophysiological mechanisms and effects of Alzheimer’s Disease. However, most existing brain network modeling frameworks for rs-fMRI often do not account for the combined statistical and temporal dependencies underlying dynamic functional connectivity (dFC) in a statistically robust manner, which may be limiting our understanding of altered brain organization in disease. To address these issues, we demonstrate an application of a new framework that characterizes dFC as covariance trajectories on the Riemannian manifold and employs scan statistics as a means to jointly incorporate first- and second-order statistics to localize subsets of features that contribute to group differences. Experimental results demonstrate that our approach is capable of identifying differential effects in large-scale functional networks altered in Alzheimer’s Disease in a way that overcomes statistical challenges common with many neuroimaging studies.
Introduction: Brain-computer interface (BCI) is an emerging technology for stroke rehabilitation,... more Introduction: Brain-computer interface (BCI) is an emerging technology for stroke rehabilitation, but little is known about brain changes associated with its use. We examine changes in laterality index (LI) and functional connectivity (FC) during hand movements associated with BCI interventional therapy. Methods: We collected anatomical and functional MRI of 8 stroke patients with upper extremity motor impairment before, during, and after up to 6 weeks of therapy using a BCI system with tongue and functional electrical stimulations. We acquired functional images during imagined (MI) and executed (ME) tapping and squeezing of each hand; not all subjects performed all tasks. Two subjects’ scans were flipped so that as a group the lesion was left (L) and the impaired limb right (R). We computed LI using 3 mask sets: whole brain, motor network, and motor cortex. Group-level analyses examined FC changes to motor network seeds using AFNI and Matlab NBS toolbox. Results: BCI intervention l...
Autosomal dominant Alzheimer’s disease (AD) is caused by known genetic mutations which results in... more Autosomal dominant Alzheimer’s disease (AD) is caused by known genetic mutations which results in the biochemical consequences that underlie the pathological basis of the disease, and a disease process driven by amyloid accumulation. Mutation carriage is characterized by substantial amyloid accumulation, and dementia onset at or around the age of parental dementia onset. Dementia onset is likely due to neurodegeneration, including loss of neuronal networks, although changes to structural connectivity remain incompletely characterized. Here, we report preliminary connection‐wise analysis of neuronal networks based on mutation and cognitive status, as well as estimated years to symptom onset (EYO), in autosomal dominant AD.
Whilst the concept of a general mental factor known as 'g' has been of longstanding interest, for... more Whilst the concept of a general mental factor known as 'g' has been of longstanding interest, for unknown reasons, it has never been interrogated in epilepsy despite the 100+ year empirical history of the neuropsychology of epilepsy. This investigation seeks to identify g within a comprehensive neuropsychological data set and compare participants with temporal lobe epilepsy to controls, characterize the discriminatory power of g compared with domain-specific cognitive metrics, explore the association of g with clinical epilepsy and sociodemographic variables and identify the structural and network properties associated with g in epilepsy. Participants included 110 temporal lobe epilepsy patients and 79 healthy controls between the ages of 19 and 60. Participants underwent neuropsychological assessment, clinical interview and structural and functional imaging. Cognitive data were subjected to factor analysis to identify g and compare the group of patients with control participants. The relative power of g compared with domain-specific tests was interrogated, clinical and sociodemographic variables were examined for their relationship with g, and structural and functional images were assessed using traditional regional volumetrics, cortical surface features and network analytics. Findings indicate (i) significantly (P < 0.005) lower g in patients compared with controls; (ii) g is at least as powerful as individual cognitive domain-specific metrics and other analytic approaches to discriminating patients from control participants; (iii) lower g was associated with earlier age of onset and medication use, greater number of antiseizure medications and longer epilepsy duration (Ps < 0.04); and lower parental and personal education and greater neighbourhood deprivation (Ps < 0.012); and (iv) amongst patients, lower g was linked to decreased total intracranial volume (P = 0.019), age and intracranial volume adjusted total tissue volume (P = 0.019) and age and intracranial volume adjusted total corpus callosum volume (P = 0.012)-particularly posterior, mid-posterior and anterior (Ps < 0.022) regions. Cortical vertex analyses showed lower g to be associated specifically with decreased gyrification in bilateral medial orbitofrontal regions. Network analysis of resting-state data with focus on the participation coefficient showed g to be associated with the superior parietal network. Spearman's g is reduced in patients, has considerable discriminatory power compared with domain-specific metrics and is linked to a multiplex of factors related to brain (size, connectivity and frontoparietal networks), environment (familial and personal education and neighbourhood disadvantage) and disease (epilepsy onset, treatment and duration). Greater attention to contemporary models of human cognition is warranted in order to advance the neuropsychology of epilepsy.
The recent revision of the classification of the epilepsies released by the ILAE Commission on Cl... more The recent revision of the classification of the epilepsies released by the ILAE Commission on Classification and Terminology (2005-2009) has been a major development in the field. Papers in this section of the special issue were charged with examining the relevance of other techniques and approaches to examining, categorizing and classifying cognitive and behavioral comorbidities. In that light, we investigate the applicability of graph theory to understand the impact of epilepsy on cognition compared to controls, and then the patterns of cognitive development in normally developing children which would set the stage for prospective comparisons of children with epilepsy and controls. The overall goal is to examine the potential utility of other analytic tools and approaches to conceptualize the cognitive comorbidities in epilepsy. Given that the major cognitive domains representing cognitive function are interdependent, the associations between the neuropsychological abilities underlying these domains can be referred to as a cognitive network. Therefore, the architecture of this cognitive network can be quantified and assessed using graph theory methods, rendering a novel approach to the characterization of cognitive status. In this article we provide fundamental information about graph theory procedures, followed by application of these techniques to cross-sectional analysis of neuropsychological data in children with epilepsy compared to controls, finalizing with prospective analysis of neuropsychological development in younger and older healthy controls.
The recent revision of the classification of the epilepsies released by the ILAE Commission on Cl... more The recent revision of the classification of the epilepsies released by the ILAE Commission on Classification and Terminology (2005-2009) has been a major development in the field. Papers in this section of the special issue were charged with examining the relevance of other techniques and approaches to examining, categorizing and classifying cognitive and behavioral comorbidities. In that light, we investigate the applicability of graph theory to understand the impact of epilepsy on cognition compared to controls, and then the patterns of cognitive development in normally developing children which would set the stage for prospective comparisons of children with epilepsy and controls. The overall goal is to examine the potential utility of other analytic tools and approaches to conceptualize the cognitive comorbidities in epilepsy. Given that the major cognitive domains representing cognitive function are interdependent, the associations between the neuropsychological abilities underlying these domains can be referred to as a cognitive network. Therefore, the architecture of this cognitive network can be quantified and assessed using graph theory methods, rendering a novel approach to the characterization of cognitive status. In this article we provide fundamental information about graph theory procedures, followed by application of these techniques to cross-sectional analysis of neuropsychological data in children with epilepsy compared to controls, finalizing with prospective analysis of neuropsychological development in younger and older healthy controls.
Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a n... more Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE. SVM was able to predict group membership (mean accuracy = 0.70, area under the curve (AUC) = 0.747, Brier score (BS) = 0.264) using 10-fold cross-validation. In addition, k-means clustering identified 2 TLE clusters: 1 similar to controls, and 1 dissimilar. Clusters were significantly different in their distribution of cognitive phenotypes, with the Dissimilar cluster containing the majority of TLE with cognitive impairment (χ 2 = 6.641, P = 0.036). In addition, cluster membership showed significant correlations between GT measures and clinical variables. Given that SVM classification seemed driven by the Dissimilar cluster, SVM analysis was repeated to classify Dissimilar versus Similar + Controls with a mean accuracy of 0.91 (AUC = 0.957, BS = 0.189). Altogether, the pattern of results shows that GT measures based on connectome DWI could be significant factors in the search for clinical and neurobehavioral biomarkers in TLE.
Ischemic stroke is a worldwide problem, with 15 million people experiencing a stroke annually. MR... more Ischemic stroke is a worldwide problem, with 15 million people experiencing a stroke annually. MR imaging is a valuable tool for understanding and assessing brain changes after stroke and predicting recovery. Of particular interest is the use of diffusion MR imaging in the nonacute stage 1-30 days poststroke. Thousands of articles have been published on the use of diffusion MR imaging in stroke, including several recent articles reviewing the use of DTI for stroke. The goal of this work was to survey and put into context the recent use of diffusion MR imaging methods beyond DTI, including diffusional kurtosis, generalized fractional anisotropy, spherical harmonics methods, and neurite orientation and dispersion models, in patients poststroke. Early studies report that these types of beyond-DTI methods outperform DTI metrics either in being more sensitive to poststroke changes or by better predicting outcome motor scores. More and larger studies are needed to confirm the improved prediction of stroke recovery with the beyond-DTI methods.
Background: There has been increasing recognition for the decline of motor function in Alzheimer&... more Background: There has been increasing recognition for the decline of motor function in Alzheimer&#39;s disease (AD) progression and its substantial role in disease morbidity. However, less is known about regional pathology burden-including amyloid-β and tau protein deposition and cortical trophy-and its relationship to motor performance. Here investigate this relationship using standardized motor function assessment tools.
Resting state functional connectivity (rFC) is used to identify functionally related brain areas ... more Resting state functional connectivity (rFC) is used to identify functionally related brain areas without requiring subjects to perform specific tasks. Previous work suggests that prior brain state, as determined by the activity engaged in immediately prior to collection of resting state data, can influence the networks recovered by rFC analyses. We determined the prevalence and network specificity of rFC changes induced by manipulations of prior state (including an unstructured (unconstrained) state, and language and motor tasks). Three blocks of rest data (one after each of the specified prior states) were acquired on each of 25 subjects. We hypothesised that prior state induced changes in rFC would be greatest within the networks most actively recruited by that prior state. Changes in rFC were greatest following the motor task and, contrary to our hypothesis, were not network specific. This was demonstrated by comparing (1) the timecourses within a set of ROIs selected on the basis of task-related de/activation, and (2) seed-based whole brain voxel-wise connectivity maps, seeded from local maxima in the task-related de/activation maps. Changes in connectivity strength tended to manifest as increases in rFC relative to that in the unstructured rest state, with change maps resembling partially complete maps of the primary sensory cortices and the cognitive control network. The majority of rFC changes occurred in areas moderately (but not weakly) connected to the seeds. Constrained prior states were associated with lower across-participant variance in rFC. This systematic investigation of the effect of prior brain state on rFC indicates that the rFC changes induced by prior brain state occur both in brain networks related to that brain activity and in networks nominally unrelated to that brain activity.
Objective: Stroke can have important effects on widespread brain regions resulting in network dis... more Objective: Stroke can have important effects on widespread brain regions resulting in network disruption. This study investigates the changes in spontaneous activity in the brain after stroke using resting-state functional connectivity(FC) MRI. Methods: Acute ischemic stroke patients (N=22, 11 cortical, mean age=60, 10F) were recruited within 7 days of stroke onset(timepoint 1, V1). Eleven of these patients were also scanned at timepoint 2(V2), approximately 3 months later. Age-matched healthy controls (N=17, mean age = 56, 7F) and 7 patients with risk factors for stroke (mean age=67, 1F) were also recruited in the study. Ten minute eyes-closed resting-state fMRI scans were collected along with a high resolution anatomical scan. We examined FC in the language network consisting of ten regions extracted based on functional activations on a phonemic fluency task performed during a separate scan. We also examined the correlation of brain FC with behavioral performance on the task outside the scanner. Results: We examined correlation between every seed region and every other region in the network(45 seed region-pairs). Compared to age-matched controls, acute strokes showed significantly reduced inter-hemispheric connectivity, specifically between inferior frontal and temporal regions(p<.001 corrected). This difference however was not significant in the sub-acute stage(Figure 1 left panel). Additionally, although both acute and sub-acute patients showed significant differences in performance compared to normals on phonemic fluency(Fig 1 right), there were no significant correlations between brain FC measures and behavior and no differences in the correlation between brain FC and behavior among the groups.
12-16 min. Consequently, new techniques that improve reliability across sessions will be importan... more 12-16 min. Consequently, new techniques that improve reliability across sessions will be important for the 40 interpretation of longitudinal fMRI studies.
Background: There has been increasing recognition for the decline of motor function in Alzheimer'... more Background: There has been increasing recognition for the decline of motor function in Alzheimer's disease (AD) progression and its substantial role in disease morbidity. However, less is known about regional pathology burden-including amyloid-β and tau protein deposition and cortical trophy-and its relationship to motor performance. Here investigate this relationship using standardized motor function assessment tools.
12-16 min. Consequently, new techniques that improve reliability across sessions will be importan... more 12-16 min. Consequently, new techniques that improve reliability across sessions will be important for the 40 interpretation of longitudinal fMRI studies.
Background: Brain myelin is known to play an important role in maintaining optimal neuronal funct... more Background: Brain myelin is known to play an important role in maintaining optimal neuronal function, with deficits in myelin leading to worse performance on cognitive tests. The extent to which cortex-specific myelin is associated with other cognitive domains, or is impacted by disease processes such as Alzheimer&#39;s disease (AD), is unknown. Here we leverage MPnRAGE-derived quantitative R1 (Kecskemeti et al., 2016; 2018), a metric sensitive to brain myelin, to assess the role of intracortical myelin in performance on tests of executive function (exec_func), working memory (work-ing_mem), and processing speed (process_speed) in older adults who ranged from cognitively unimpaired to those with dementia. Method: 143 older adults (N=75 cognitively unimpaired, N=44 mild cognitive impairment, N=24 dementia) enrolled in the Alzheimer&#39;s Disease Connectome Project underwent T1-weighted (T1w) MPnRAGE MRI with motion-correction and testing via the NIH Toolbox Cognitive Battery. Inherently registered quantitative R1 maps and T1w images were reconstructed at 1mm isotropic resolution. The image processing pipeline and composite regions of interest (ROIs) used for analysis can be viewed in Figure 1. Uncorrected standard scores were computed by the NIH Toolbox for each measure of exec_func (dimensional change card sort), working_mem (list sorting), and process_speed (pattern comparison). Multiple linear regression models were employed in R with test scores as the dependent variable, regional R1 as the predictor of interest, and age, sex, and education as covariates. Result: Higher R1 was associated with worse exec_func in regions that are affected in AD, including posterior cingulate (ß =-62.47, t(1,138) =-2.42, p = 0.017) and temporal cortices(ß =-123.05, t(1,138) =-2.77, p = 0.0064) ROIs. Additionally, higher R1 in temporal cortices was associated with worse working_mem (ß =-158.16, t(1,133) =-2.84, p = 0.0053) (Figure 2). There were no significant associations between process_speed and regional cortical R1. Conclusion: Unexpectedly, higher regional cortical myelin (as indexed by R1) was associated with worse exec_func and working_mem, suggesting higher R1 may be
PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral mu... more PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)
Rs-fMRI has been shown to be a valuable neuroimaging modality to study the pathophysiological mec... more Rs-fMRI has been shown to be a valuable neuroimaging modality to study the pathophysiological mechanisms and effects of Alzheimer’s Disease. However, most existing brain network modeling frameworks for rs-fMRI often do not account for the combined statistical and temporal dependencies underlying dynamic functional connectivity (dFC) in a statistically robust manner, which may be limiting our understanding of altered brain organization in disease. To address these issues, we demonstrate an application of a new framework that characterizes dFC as covariance trajectories on the Riemannian manifold and employs scan statistics as a means to jointly incorporate first- and second-order statistics to localize subsets of features that contribute to group differences. Experimental results demonstrate that our approach is capable of identifying differential effects in large-scale functional networks altered in Alzheimer’s Disease in a way that overcomes statistical challenges common with many neuroimaging studies.
Introduction: Brain-computer interface (BCI) is an emerging technology for stroke rehabilitation,... more Introduction: Brain-computer interface (BCI) is an emerging technology for stroke rehabilitation, but little is known about brain changes associated with its use. We examine changes in laterality index (LI) and functional connectivity (FC) during hand movements associated with BCI interventional therapy. Methods: We collected anatomical and functional MRI of 8 stroke patients with upper extremity motor impairment before, during, and after up to 6 weeks of therapy using a BCI system with tongue and functional electrical stimulations. We acquired functional images during imagined (MI) and executed (ME) tapping and squeezing of each hand; not all subjects performed all tasks. Two subjects’ scans were flipped so that as a group the lesion was left (L) and the impaired limb right (R). We computed LI using 3 mask sets: whole brain, motor network, and motor cortex. Group-level analyses examined FC changes to motor network seeds using AFNI and Matlab NBS toolbox. Results: BCI intervention l...
Autosomal dominant Alzheimer’s disease (AD) is caused by known genetic mutations which results in... more Autosomal dominant Alzheimer’s disease (AD) is caused by known genetic mutations which results in the biochemical consequences that underlie the pathological basis of the disease, and a disease process driven by amyloid accumulation. Mutation carriage is characterized by substantial amyloid accumulation, and dementia onset at or around the age of parental dementia onset. Dementia onset is likely due to neurodegeneration, including loss of neuronal networks, although changes to structural connectivity remain incompletely characterized. Here, we report preliminary connection‐wise analysis of neuronal networks based on mutation and cognitive status, as well as estimated years to symptom onset (EYO), in autosomal dominant AD.
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