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1.  Spatial patterns of genome-wide expression profiles reflect anatomic and fiber connectivity architecture of healthy human brain 
Human brain mapping  2014;35(8):4204-4218.
Unraveling the relationship between molecular signatures in the brain and their functional, architectonic and anatomic correlates is an important neuroscientific goal. It is still not well understood whether the diversity demonstrated by histological studies in the human brain is reflected in the spatial patterning of whole brain transcriptional profiles. Using genome-wide maps of transcriptional distribution of the human brain by the Allen Brain Institute, we test the hypothesis that gene expression profiles are specific to anatomically described brain regions. In this work, we demonstrate that this is indeed the case by showing that gene similarity clusters appear to respect conventional basal-cortical and caudal-rostral gradients. To fully investigate the causes of this observed spatial clustering, we test a connectionist hypothesis that states that the spatial patterning of gene expression in the brain is simply reflective of the fiber tract connectivity between brain regions. We find that although gene expression and structural connectivity are not determined by each other, they do influence each other with a high statistical significance. This implies that spatial diversity of gene expressions is a result of mainly location-specific features, but is influenced by neuronal connectivity, such that like cellular species preferentially connects with like cells.
doi:10.1002/hbm.22471
PMCID: PMC4283562  PMID: 24677576
gene similarity; brain network; spatial clustering; generalized discriminant analysis; white matter connectivity
2.  Enhanced phase regression with Savitzky-Golay filtering for high-resolution BOLD fMRI 
Human brain mapping  2014;35(8):3832-3840.
Phase regression exploits the temporal evolution of phase in individual voxels to suppress blood oxygenation level dependent (BOLD) signal fluctuations caused by larger vessels and draining veins while preserving signal changes from microvascular effects. However, this process does not perform well when phase time series have low signal-to-noise ratios because of high levels of physiological noise. We demonstrate that Savitzky-Golay filters may be used to recover the underlying change in phase and completely restore the efficacy of phase regression. We do not make a priori assumptions regarding phase evolution and perform a data-driven exploration of parameter space to select the Savitzky-Golay filter parameters that minimize temporal variance in each voxel after phase regression. This approach is shown to work well on data acquired with single-shot and multi-shot pulse sequences, and should therefore be useful for both human and animal gradient-echo fMRI at high spatial resolutions at high fields. The ability to improve the spatial specificity of BOLD activation may be especially advantageous for clinical applications of fMRI that rely upon the accuracy of individual subject's activation maps to assist with presurgical planning and clinical decision-making. Enhanced phase regression with Savitzky-Golay filtering may also find other uses in analyses of resting state functional connectivity.
doi:10.1002/hbm.22440
PMCID: PMC4296570  PMID: 24443117
functional magnetic resonance imaging (fMRI); blood oxygenation level dependent (BOLD) contrast; phase regression; 7 Tesla; high resolution imaging; Savitzky-Golay filtering
3.  Repetition Suppression of Face-Selective Evoked and Induced EEG Recorded From Human Cortex 
Human brain mapping  2014;35(8):4155-4162.
In functional MRI studies, repetition suppression refers to the reduction of hemodynamic activation to repeated stimulus presentation. For example, the repeated presentation of a face reduces the hemodynamic response evoked by faces in the fusiform gyrus. The neural events that underlie repetition suppression are not well understood. Indeed, in contrast to the hemodynamic response, the face-specific N200 recorded from subdural electrodes on the ventral occipitotemporal cortex, primarily along the fusiform gyrus, has been reported to be insensitive to face-identity repetition. We have previously described a face-specific broadband gamma (30–100 Hz) response at ventral face-specific N200 sites that is functionally dissociable from the N200. In this study, we investigate whether gamma and other components of the electroencephalogram spectrum are affected by face-identity repetition independently of the N200. Participants viewed sequentially presented identical faces. At sites on and around the fusiform gyrus, we found that face repetition modulated alpha (8–12 Hz), low-gamma (30–60 Hz), and high-gamma (60–100 Hz) synchrony, but not the N200. These findings provide evidence of a spatially co-localized progression of face processing. Whereas the N200 reflects an initial obligatory response that is less sensitive to face-identity repetition, the subsequent spectral fluctuations reflect more elaborative face processing and are thus sensitive to face novelty. It is notable that the observed modulations were different for different frequency bands. We observed repetition suppression of broadband gamma, but repetition enhancement of alpha synchrony. This difference is discussed with regard to an existing model of repetition suppression and behavioral repetition priming.
doi:10.1002/hbm.22467
PMCID: PMC4322774  PMID: 24677530
ECoG; ERP; face; alpha; gamma; vision; repetition suppression
4.  Behavioral and Neural Correlates of Imagined Walking and Walking-While-Talking in the Elderly 
Human brain mapping  2014;35(8):4090-4104.
Cognition is important for locomotion and gait decline increases the risk for morbidity, mortality, cognitive decline, and dementia. Yet, the neural correlates of gait are not well established, because most neuroimaging methods cannot image the brain during locomotion. Imagined gait protocols overcome this limitation. This study examined the behavioral and neural correlates of a new imagined gait protocol that involved imagined walking (iW), imagined talking (iT), and imagined walking-while-talking (iWWT). In Experiment 1, 82 cognitively-healthy older adults (M = 80.45) walked (W), iW, walked while talking (WWT) and iWWT. Real and imagined walking task times were strongly correlated, particularly real and imagined dual-task times (WWT and iWWT). In Experiment 2, 33 cognitively-healthy older adults (M = 73.03) iW, iT, and iWWT during functional Magnetic Resonance Imaging. A multivariate Ordinal Trend (OrT) Covariance analysis identified a pattern of brain regions that: 1) varied as a function of imagery task difficulty (iW, iT and iWWT), 2) involved cerebellar, precuneus, supplementary motor and other prefrontal regions, and 3) were associated with kinesthetic imagery ratings and behavioral performance during actual WWT. This is the first study to compare the behavioral and neural correlates of imagined gait in single and dual-task situations, an issue that is particularly relevant to elderly populations. These initial findings encourage further research and development of this imagined gait protocol as a tool for improving gait and cognition among the elderly.
doi:10.1002/hbm.22461
PMCID: PMC4106989  PMID: 24522972
Gait; Imagery; Dual-task; fMRI; Aging
5.  The relationship between task-related and subsequent memory effects 
Human brain mapping  2014;35(8):3687-3700.
The primary aim of this fMRI study was to assess the proposal that negative subsequent memory effects – greater activity for later forgotten relative to later remembered study items – are localized to regions demonstrating task-negative effects, and hence to potential components of the default mode network. Additionally, we assessed whether positive subsequent memory effects overlapped with regions demonstrating task-positive effects. Eighteen participants were scanned while they made easy or difficult relational judgments on visually presented word pairs. Easy and hard task blocks were interleaved with fixation-only rest periods. In the later unscanned test phase, associative recognition judgments were required on intact word pairs (studied pairs), rearranged pairs (pairs formed from words presented on different study trials) and new pairs. Subsequent memory effects were identified by contrasting the activity elicited by study pairs that went on to be correctly endorsed as intact versus incorrectly endorsed as rearranged. Task effects were identified by contrasting all study items and rest blocks. Both task-negative and task-positive effects were evident in widespread cortical regions and negative and positive subsequent memory effects were generally confined to task-negative and task-positive regions respectively. However, subsequent memory effects could be identified in only a fraction of task-sensitive voxels and, unlike task effects, were insensitive to the difficulty manipulation. The findings for the negative subsequent memory effects are consistent with recent proposals that the default mode network is functionally heterogeneous, and suggest that these effects are not accurately characterized as reflections of the modulation of the network as a whole.
doi:10.1002/hbm.22430
PMCID: PMC4107062  PMID: 24615858
fMRI; memory encoding; episodic memory; associative recognition; default mode network
6.  Cerebellar Networks in Individuals at Ultra High-Risk of Psychosis: Impact on Postural Sway and Symptom Severity 
Human brain mapping  2014;35(8):4064-4078.
Despite known deficits in postural control in patients with schizophrenia, this domain has not been investigated in youth at ultra high-risk (UHR) for psychosis. This is particularly relevant as postural control implicates dysfunction in the cerebellum-a region implicated in cognitive dysmetria conceptions of schizophrenia but poorly understood in the prodrome. Here, we extended our understanding of movement abnormalities in UHR individuals to include postural control, and have linked these deficits to both symptom severity and cerebello-cortical network connectivity. UHR and healthy control participants completed an instrumentally-based balance task to quantify postural control along with a resting state brain imaging scan to investigate cerebellar networks. We also quantified positive and negative symptom severity with structured clinical interviews. The UHR group showed overall increased postural sway and decreased cerebello-cortical resting state connectivity, relative to controls. The decreased cerebello-cortical connectivity was seen across multiple networks. Postural sway was also correlated with cerebellar connectivity in this population and uniquely positively correlated with the severity of negative symptoms. Finally, symptom severity was also associated with cerebellar connectivity. Together, our results point to a potential deficit in sensory integration as an underlying contributor to the increased postural sway, and provide evidence of cerebellar abnormalities in UHR individuals. These results extend our understanding of the motor abnormalities of UHR individuals beyond striatum-based dyskinesias to include postural control and sensory integration deficits, and implicate the cerebellum as a distinct neural substrate preceding the onset of psychosis. Taken together, our results extend the cognitive dysmetria framework to UHR populations.
doi:10.1002/hbm.22458
PMCID: PMC4107098  PMID: 24464473
postural control; ultra high-risk; cerebellum; psychosis; resting state connectivity; symptom severity
7.  Extracting and summarizing white matter hyperintensities using supervised segmentation methods in Alzheimer’s disease risk and aging studies 
Human brain mapping  2014;35(8):4219-4235.
Precise detection and quantification of white matter hyperintensities (WMH) observed in T2–weighted Fluid Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Images (MRI) is of substantial interest in aging, and age related neurological disorders such as Alzheimer’s disease (AD). This is mainly because WMH may reflect comorbid neural injury or cerebral vascular disease burden. WMH in the older population may be small, diffuse and irregular in shape, and sufficiently heterogeneous within and across subjects. Here, we pose hyperintensity detection as a supervised inference problem and adapt two learning models, specifically, Support Vector Machines and Random Forests, for this task. Using texture features engineered by texton filter banks, we provide a suite of effective segmentation methods for this problem. Through extensive evaluations on healthy middle–aged and older adults who vary in AD risk, we show that our methods are reliable and robust in segmenting hyperintense regions. A measure of hyperintensity accumulation, referred to as normalized Effective WMH Volume, is shown to be associated with dementia in older adults and parental family history in cognitively normal subjects. We provide an open source library for hyperintensity detection and accumulation (interfaced with existing neuroimaging tools), that can be adapted for segmentation problems in other neuroimaging studies.
doi:10.1002/hbm.22472
PMCID: PMC4107160  PMID: 24510744
White Matter Hyperintensities; Support Vector Machines; Random Forests; Segmentation
8.  GENETIC INFLUENCE OF APOE4 GENOTYPE ON HIPPOCAMPAL MORPHOMETRY - AN N=725 SURFACE-BASED ADNI STUDY 
Human brain mapping  2014;35(8):3903-3918.
The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer’s disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 non-carriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database – the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling’s T2 test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the entire cohort as well as in the non-demented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.
doi:10.1002/hbm.22447
PMCID: PMC4269525  PMID: 24453132
Alzheimer’s disease; hippocampus; APOE e4; MRI; multivariate tensor-based morphometry (mTBM)
9.  Cognitive Strategies Regulate Fictive, But Not Reward Prediction Error Signals in A Sequential Investment Task 
Human brain mapping  2013;35(8):3738-3749.
Computational models of reward processing suggest that foregone or fictive outcomes serve as important information sources for learning and augment those generated by experienced rewards (e.g. reward prediction errors). An outstanding question is how these learning signals interact with top-down cognitive influences, such as cognitive reappraisal strategies. Using a sequential investment task and functional magnetic resonance imaging, we show that the reappraisal strategy selectively attenuates the influence of fictive, but not reward prediction error signals on investment behavior; such behavioral effect is accompanied by changes in neural activity and connectivity in the anterior insular cortex, a brain region thought to integrate subjective feelings with high-order cognition. Furthermore, individuals differ in the extent to which their behaviors are driven by fictive errors versus reward prediction errors, and the reappraisal strategy interacts with such individual differences; a finding also accompanied by distinct underlying neural mechanisms. These findings suggest that the variable interaction of cognitive strategies with two important classes of computational learning signals (fictive, reward prediction error) represent one contributing substrate for the variable capacity of individuals to control their behavior based on foregone rewards. These findings also expose important possibilities for understanding the lack of control in addiction based on possibly foregone rewarding outcomes.
doi:10.1002/hbm.22433
PMCID: PMC4105325  PMID: 24382784
Decision-making; reward prediction errors; fictive learning; emotion regulation; reappraisal; insula; fMRI
10.  Shape Abnormalities of Subcortical and Ventricular Structures in Mild Cognitive Impairment and Alzheimer’s Disease: Detecting, Quantifying, and Predicting 
Human brain mapping  2014;35(8):3701-3725.
This article assesses the feasibility of using shape information to detect and quantify the subcortical and ventricular structural changes in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. We first demonstrate structural shape abnormalities in MCI and AD as compared with healthy controls (HC). Exploring the development to AD, we then divide the MCI participants into two subgroups based on longitudinal clinical information: (1) MCI patients who remained stable; (2) MCI patients who converted to AD over time. We focus on seven structures (amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricles) in 754 MR scans (210 HC, 369 MCI of which 151 converted to AD over time, and 175 AD). The hippocampus and amygdala were further subsegmented based on high field 0.8 mm isotropic 7.0T scans for finer exploration. For MCI and AD, prominent ventricular expansions were detected and we found that these patients had strongest hippocampal atrophy occurring at CA1 and strongest amygdala atrophy at the basolateral complex. Mild atrophy in basal ganglia structures was also detected in MCI and AD. Stronger atrophy in the amygdala and hippocampus, and greater expansion in ventricles was observed in MCI converters, relative to those MCI who remained stable. Furthermore, we performed principal component analysis on a linear shape space of each structure. A subsequent linear discriminant analysis on the principal component values of hippocampus, amygdala, and ventricle leads to correct classification of 88% HC subjects and 86% AD subjects.
doi:10.1002/hbm.22431
PMCID: PMC4474087  PMID: 24443091
Alzheimer’s disease; mild cognitive impairment; subcortical structures; lateral ventricles; high field; subsegmentations; shape abnormality; large deformation diffeomorphic metric mapping
11.  Neural Bases of Individual Variation in Decision Time 
Human brain mapping  2013;35(6):2531-2542.
People make decisions by evaluating existing evidence against a threshold or level of confidence. Individuals vary widely in response times even when they perform a simple task in the laboratory. We examine the neural bases of this individual variation by combining computational modeling and brain imaging of 64 healthy adults performing a stop signal task. Behavioral performance was modeled by an accumulator model that describes the process of information growth to reach a threshold to respond. In this model, go trial reaction time (goRT) is jointly determined by the information growth rate, threshold, and movement time (MT). In a linear regression of activations in successful go and all stop (Go+Stop) trials against goRT across participants, the insula, supplementary motor area (SMA), pre-SMA, thalamus including the subthalamic nucleus (STN), and caudate head respond to increasing goRT. Among these areas, the insula, SMA, and thalamus including the STN respond to a slower growth rate, the caudate head responds to an elevated threshold, and the pre-SMA responds to a longer MT. In the regression of Go+Stop trials against the stop signal reaction time (SSRT), the pre-SMA shows a negative correlation with SSRT. These results characterize the component processes of decision making and elucidate the neural bases of a critical aspect of inter-subject variation in human behavior. These findings also suggest that the pre-SMA may play a broader role in response selection and cognitive control rather than simply response inhibition in the stop signal task.
doi:10.1002/hbm.22347
PMCID: PMC4511156  PMID: 24027122
accumulator model; threshold; growth rate; pre-SMA; caudate; subthalamic nucleus
12.  Reconstruction of the Human Cerebral Cortex Robust to White Matter Lesions: Method and Validation 
Human brain mapping  2013;35(7):3385-3401.
Cortical atrophy has been reported in a number of diseases, such as multiple sclerosis and Alzheimer’s disease, that are also associated with white matter (WM) lesions. However, most cortical reconstruction techniques do not account for these pathologies, thereby requiring additional processing to correct for the effect of WM lesions. In this work we introduce CRUISE+, an automated process for cortical reconstruction from magnetic resonance brain images with WM lesions. The process extends previously well validated methods to allow for multichannel input images and to accommodate for the presence of WM lesions. We provide new validation data and tools for measuring the accuracy of cortical reconstruction methods on healthy brains as well as brains with multiple sclerosis lesions. Using this data, we validate the accuracy of CRUISE+ and compare it to another state-of-the-art cortical reconstruction tool. Our results demonstrate that CRUISE+ has superior performance in the cortical regions near WM lesions, and similar performance in other regions.
doi:10.1002/hbm.22409
PMCID: PMC4055590  PMID: 24382742
Cortical reconstruction; WM lesions; Multiple sclerosis; Lesion segmentation; cortical thickness
13.  Quantification of Primary Motor Pathways Using Diffusion MRI Tractography and Its Application to Predict Postoperative Motor Deficits in Children With Focal Epilepsy 
Human brain mapping  2013;35(7):3216-3226.
As a new tool to quantify primary motor pathways and predict postoperative motor deficits in children with focal epilepsy, the present study utilized a maximum a posteriori probability (MAP) classification of diffusion weighted imaging (DWI) tractography combined with Kalman filter. DWI was performed in 31 children with intractable focal epilepsy who underwent epilepsy surgery. Three primary motor pathways associated with “finger,” “leg,” and “face” were classified using DWI-MAP classifier and compared with the results of invasive electrical stimulation mapping (ESM) via receiver operating characteristic (ROC) curve analysis. The Kalman filter analysis was performed to generate a model to determine the probability of postoperative motor deficits as a function of the proximity between the resection margin and the finger motor pathway. The ROC curve analysis showed that the DWI-MAP achieves high accuracy up to 89% (finger), 88% (leg), 89% (face), in detecting the three motor areas within 20 mm, compared with ESM. Moreover, postoperative reduction of the fiber count of finger pathway was associated with postoperative motor deficits involving the hand. The prediction model revealed an accuracy of 92% in avoiding postoperative deficits if the distance between the resection margin and the finger motor pathway seen on preoperative DWI tractography was 19.5 mm. This study provides evidence that the DWI-MAP combined with Kalman filter can effectively identify the locations of cortical motor areas even in patients whose motor areas are difficult to identify using ESM, and also can serve as a reliable predictor for motor deficits following epilepsy surgery.
doi:10.1002/hbm.22396
PMCID: PMC4360906  PMID: 24142581
primary motor pathway; corticospinal tract; diffusion weighted image tractography; presurgical planning; epilepsy
14.  Reliability of an fMRI Paradigm for Emotional Processing in a Multisite Longitudinal Study 
Human brain mapping  2015;36(7):2558-2579.
Multisite neuroimaging studies can facilitate the investigation of brain-related changes in many contexts, including patient groups that are relatively rare in the general population. Though multisite studies have characterized the reliability of brain activation during working memory and motor functional magnetic resonance imaging tasks, emotion processing tasks, pertinent to many clinical populations, remain less explored. A traveling participants study was conducted with eight healthy volunteers scanned twice on consecutive days at each of the eight North American Longitudinal Prodrome Study sites. Tests derived from generalizability theory showed excellent reliability in the amygdala (Eρ2=0.82), inferior frontal gyrus (IFG;Eρ2=0.83), anterior cingulate cortex (ACC;Eρ2=0.76), insula (Eρ2=0.85), and fusiform gyrus (Eρ2=0.91) for maximum activation and fair to excellent reliability in the amygdala (Eρ2=0.44), IFG (Eρ2=0.48), ACC (Eρ2=0.55), insula (Eρ2=0.42), and fusiform gyrus (Eρ2=0.83) for mean activation across sites and test days. For the amygdala, habituation (Eρ2=0.71) was more stable than mean activation. In a second investigation, data from 111 healthy individuals across sites were aggregated in a voxelwise, quantitative meta-analysis. When compared with a mixed effects model controlling for site, both approaches identified robust activation in regions consistent with expected results based on prior single-site research. Overall, regions central to emotion processing showed strong reliability in the traveling participants study and robust activation in the aggregation study. These results support the reliability of blood oxygen level-dependent signal in emotion processing areas across different sites and scanners and may inform future efforts to increase efficiency and enhance knowledge of rare conditions in the population through multisite neuroimaging paradigms.
doi:10.1002/hbm.22791
PMCID: PMC4478164  PMID: 25821147
fMRI; reliability; multisite; emotion; meta-analysis; amygdale
15.  Schizophrenia-like topological changes in the structural connectome of individuals with sub-clinical psychotic experiences 
Human brain mapping  2015;36(7):2629-2643.
Schizophrenia is often regarded as a ‘dysconnectivity’ disorder and recent work using graph theory (GT) has been used to better characterise dysconnectivity of the structural connectome in schizophrenia. However, there are still little data on the topology of connectomes in less severe forms of the condition. Such analysis will identify topological markers of less severe disease states and provide potential predictors of further disease development.
Individuals with psychotic experiences (PEs) were identified from a population-based cohort without relying upon participants presenting to clinical services. Such individuals have an increased risk of developing clinically significant psychosis. 123 individuals with PEs and 125 controls were scanned with diffusion-weighted MRI. Whole-brain structural connectomes were derived and a range of global and local GT-metrics were computed.
Global efficiency and density were significantly reduced in individuals with PEs. Local efficiency was reduced in a number of regions, including critical network hubs. Further analysis of functional sub-networks showed differential impairment of the default mode network. An additional analysis of pair-wise connections showed no evidence of differences in individuals with PEs.
These results are consistent with previous findings in schizophrenia. Reduced efficiency in critical core hubs suggests the brains of individuals with PEs may be particularly predisposed to dysfunction. The absence of any detectable effects in pair-wise connections illustrates that, at less severe stages of psychosis, white-matter alterations are subtle and only manifest when examining network topology. This study indicates that topology could be a sensitive biomarker for early stages of psychotic illness.
doi:10.1002/hbm.22796
PMCID: PMC4479544  PMID: 25832856
psychosis; schizophrenia; connectomics; tractography; graph theory; structural connectivity; diffusion MRI; psychotic experiences; network efficiency; ALSPAC; birth cohort; psychosis risk; neuropsychiatry; epidemiology
16.  Sensation-to-Cognition Cortical Streams in Attention-Deficit/Hyperactivity Disorder 
Human brain mapping  2015;36(7):2544-2557.
We sought to determine whether functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits are atypical in attention-deficit/hyperactivity disorder (ADHD). We applied a graph-theory method to the resting-state functional magnetic resonance imaging data of 120 children with ADHD and 120 age-matched typically developing children (TDC). Starting in unimodal primary cortex—visual, auditory, and somatosensory—we used stepwise functional connectivity to calculate functional connectivity paths at discrete numbers of relay stations (or link-step distances). First, we characterized the functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits in TDC and found that systems do not reach the level of integration achieved by adults. Second, we searched for stepwise functional connectivity differences between children with ADHD and TDC. We found that, at the initial steps of sensory functional connectivity streams, patients display significant enhancements of connectivity degree within neighboring areas of primary cortex, while connectivity to attention-regulatory areas is reduced. Third, at subsequent link-step distances from primary sensory cortex, children with ADHD show decreased connectivity to executive processing areas and increased degree of connections to default mode regions. Fourth, in examining medication histories in children with ADHD, we found that children medicated with psychostimulants present functional connectivity streams with higher degree of connectivity to regions subserving attentional and executive processes compared to medication-naïve children. We conclude that predominance of local sensory processing and lesser influx of information to attentional and executive regions may reduce the ability to organize and control the balance between external and internal sources of information in ADHD.
doi:10.1002/hbm.22790
PMCID: PMC4484811  PMID: 25821110
attention-deficit/hyperactivity disorder; resting-state functional magnetic resonance imaging; ventral attention network; default mode network; sensorimotor network
17.  Aging and the Interaction of Sensory Cortical Function and Structure 
Human brain mapping  2009;30(1):228-240.
Even the healthiest older adults experience changes in cognitive and sensory function. Studies show that older adults have reduced neural responses to sensory information. However, it is well known that sensory systems do not act in isolation but function cooperatively to either enhance or suppress neural responses to individual environmental stimuli. Very little research has been dedicated to understanding how aging affects the interactions between sensory systems, especially cross-modal deactivations or the ability of one sensory system (e.g., audition) to suppress the neural responses in another sensory system cortex (e.g., vision). Such cross-modal interactions have been implicated in attentional shifts between sensory modalities and could account for increased distractibility in older adults. To assess age-related changes in cross-modal deactivations, functional MRI studies were performed in 61 adults between 18 and 80 years old during simple auditory and visual discrimination tasks. Results within visual cortex confirmed previous findings of decreased responses to visual stimuli for older adults. Age-related changes in the visual cortical response to auditory stimuli were, however, much more complex and suggested an alteration with age in the functional interactions between the senses. Ventral visual cortical regions exhibited cross-modal deactivations in younger but not older adults, whereas more dorsal aspects of visual cortex were suppressed in older but not younger adults. These differences in deactivation also remained after adjusting for age-related reductions in brain volume of sensory cortex. Thus, functional differences in cortical activity between older and younger adults cannot solely be accounted for by differences in gray matter volume.
doi:10.1002/hbm.20497
PMCID: PMC4485392  PMID: 18072271
functional magnetic resonance imaging; cortical atrophy; vision; auditory; cross-modal
18.  Executive Function and Error Detection: The Effect of Motivation on Cingulate and Ventral Striatum Activity 
Human brain mapping  2010;31(3):458-469.
Reacting appropriately to errors during task performance is fundamental to successful negotiation of our environment. This is especially true when errors will result in a significant penalty for the person performing a given task, be they financial or otherwise. Error responses and monitoring states were manipulated in a GO/NOGO task by introducing a financial punishment for errors. This study employed a mixed block design alternating between punishment and no punishment (neutral) conditions, enabling an assessment of tonic changes associated with cognitive control as well as trial-specific effects. Behavioural results revealed slower responses and fewer commission errors in the punishment condition. The dorsal anterior cingulate cortex (ACC) had equal trial-specific activity for errors in the neutral and punishment conditions but had greater tonic activity throughout the punishment condition. A region of interest analysis revealed different activation patterns between the dorsal and the rostral parts of the ACC with the rostral ACC having only trial-specific activity for errors in the punishment condition, an activity profile similar to one observed in the nucleus accumbens. This study suggests that there is a motivational influence on cognitive processes in the ACC and nucleus accumbens and hints at a dissociation between tonic proactive activity and phasic reactive error-related activity.
doi:10.1002/hbm.20879
PMCID: PMC4485396  PMID: 19718655
inhibitory control; error detection; fMRI; motivation; monetary loss; anterior cingulate; nucleus accumbens
19.  Development of brain systems for nonsymbolic numerosity and the relationship to formal math academic achievement 
Human brain mapping  2014;36(2):804-826.
A central question in cognitive and educational neuroscience is whether brain operations supporting non-linguistic intuitive number sense (numerosity) predict individual acquisition and academic achievement for symbolic or “formal” math knowledge. Here, we conducted a developmental functional MRI study of nonsymbolic numerosity task performance in 44 participants including 14 school age children (6–12 years-old), 14 adolescents (13–17 years-old), and 16 adults and compared a brain activity measure of numerosity precision to scores from the Woodcock-Johnson III Broad Math index of math academic achievement. Accuracy and reaction time from the numerosity task did not reliably predict formal math achievement. We found a significant positive developmental trend for improved numerosity precision in the parietal cortex and intraparietal sulcus (IPS) specifically. Controlling for age and overall cognitive ability, we found a reliable positive relationship between individual math achievement scores and parietal lobe activity only in children. In addition, children showed robust positive relationships between math achievement and numerosity precision within ventral stream processing areas bilaterally. The pattern of results suggests a dynamic developmental trajectory for visual discrimination strategies that predict the acquisition of formal math knowledge. In adults, the efficiency of visual discrimination marked by numerosity acuity in ventral occipital-temporal cortex and hippocampus differentiated individuals with better or worse formal math achievement, respectively. Overall, these results suggest that two different brain systems for nonsymbolic numerosity acuity may contribute to individual differences in math achievement and that the contribution of these systems differs across development.
doi:10.1002/hbm.22666
PMCID: PMC4477628  PMID: 25327879
child development; adolescent development; academic achievement; mathematics; functional magnetic resonance imaging; cognition; behavior; number sense; numerosity
20.  Reduced fMRI activity predicts relapse in patients recovering from stimulant dependence 
Human brain mapping  2012;35(2):414-428.
Relapse presents a major problem for patients recovering from stimulant dependence. Here we examined the hypothesis that patterns of brain function obtained at an early stage of abstinence differentiates patients who later relapse vs. those who remain abstinent. Forty-five recently abstinent stimulant-dependent patients were tested using a randomized event-related functional MRI (ER-fMRI) design that was developed in order to replicate a previous ERP study of relapse using a selective attention task, and were then monitored until 6 months of verified abstinence or stimulant use occurred. SPM revealed smaller absolute BOLD response amplitude in bilateral ventral posterior cingulate and right insular cortex in 23 patients positive for relapse to stimulant use compared with 22 who remained abstinent. ER-fMRI data was compared with psychiatric, neuropsychological, demographic, personal- and family- history of drug use in order to form predictive models, and was found to predict abstinence with higher accuracy than any other single measure obtained in this study. Logistic regression using fMRI amplitude in right posterior cingulate and insular cortex predicted abstinence with 77.8% accuracy, which increased to 89.9% accuracy when history of mania was included. Using 10-fold cross-validation, Bayesian logistic regression and multilayer perceptron algorithms provided the highest accuracy of 84.4%. These results, combined with previous studies, suggest that the functional organization of paralimbic brain regions including ventral anterior and posterior cingulate and right insula are related to patients’ ability to maintain abstinence. Novel therapies designed to target these paralimbic regions identified using ER-fMRI may improve treatment outcome.
doi:10.1002/hbm.22184
PMCID: PMC4470394  PMID: 23015512
Cingulate; insula; cocaine; methamphetamine; drug dependence; attention
21.  Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification 
Human brain mapping  2014;36(2):489-507.
Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis.
doi:10.1002/hbm.22642
PMCID: PMC4470367  PMID: 25277605
manifold regularization; group-sparsity regularizer; multitask learning; feature selection; multimodality classification; Alzheimer’s disease
22.  Dopamine-Agonists and Impulsivity in Parkinson’s Disease: Impulsive Choices vs. Impulsive Actions 
Human brain mapping  2013;35(6):2499-2506.
The control of impulse behavior is a multidimensional concept subdivided into separate subcomponents, which are thought to represent different underlying mechanisms due to either disinhibitory processes or poor decision-making. In patients with Parkinson’s disease (PD), dopamine-agonist (DA) therapy has been associated with increased impulsive behavior. However, the relationship among these different components in the disease and the role of DA is not well understood. In this imaging study, we investigated in PD patients the effects of DA medication on patterns of brain activation during tasks testing impulsive choices and actions. Following overnight withdrawal of antiparkinsonian medication, PD patients were studied with a H2 (15)O PET before and after administration of DA (1 mg of pramipexole), while they were performing the delay discounting task (DDT) and the GoNoGo Task (GNG). We observed that pramipexole augmented impulsivity during DDT, depending on reward magnitude and activated the medial prefrontal cortex and posterior cingulate cortex and deactivated ventral striatum. In contrast, the effect of pramipexole during the GNG task was not significant on behavioral performance and involved different areas (i.e., lateral prefrontal cortex). A voxel-based correlation analysis revealed a significant negative correlation between the discounting value (k) and the activation of medial prefrontal cortex and posterior cingulate suggesting that more impulsive patients had less activation in those cortical areas. Here we report how these different subcomponents of inhibition/impulsivity are differentially sensitive to DA treatment with pramipexole influencing mainly the neural network underlying impulsive choices but not impulsive action.
doi:10.1002/hbm.22344
PMCID: PMC4452224  PMID: 24038587 CAMSID: cams4599
Parkinson’s disease; impulsivity; dopamine agonists
23.  Shared space, separate processes: neural activation patterns for auditory description and visual object naming in healthy adults 
Human brain mapping  2013;35(6):2507-2520.
Historically, both clinicians and cognitive scientists have used visual object naming measures to study naming, and lesion-type studies have implicated the left posterior, temporo-parietal region as a critical component of naming circuitry. However, recent results from behavioral and cortical stimulation studies using auditory description naming as well as visual object naming in left temporal lobe epilepsy patients suggest that discrete sites in anterior temporal cortex are critical for description naming, whereas posterior temporal regions mediate both visual object naming and description naming. To determine whether this task specificity reflects normal cerebral organization and processing, 13 healthy adults performed description naming and visual naming during functional neuroimaging. In addition to standard univariate analysis, multivariate, Ordinal Trend Analysis examined the network character of the regions involved in task-specific naming. Univariate analysis indicated posterior temporal activation for both visual naming and description naming, whereas multivariate analysis revealed broader networks for both tasks, with both overlapping and task-specific regions, as well as task related differences in the way the tasks utilized common regions. Additionally, multivariate analysis revealed unique, task-specific, regionally covarying activation patterns that were strikingly consistent in all 13 subjects for visual naming and 12/13 subjects for description naming. Results suggest a common neural substrate, yet differentiable neural processes underlying visual naming and description naming in neurologically intact individuals. These findings support the use of both types of tasks for clinical assessment, and may have application in the treatment of neurologically based naming deficits.
doi:10.1002/hbm.22345
PMCID: PMC4091775  PMID: 23918095
visual object naming; auditory description naming; fMRI
24.  Stochastic Dynamic Causal Modeling of Working Memory Connections in Cocaine Dependence 
Human brain mapping  2012;35(3):760-778.
Although reduced working memory brain activation has been reported in several brain regions of cocaine dependent subjects compared to controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging (fMRI)-based stochastic dynamic causal model (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes prior to convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in BOLD response caused by disease or drugs. Based on the significant regional activation common to both groups, and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared to the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology.
doi:10.1002/hbm.22212
PMCID: PMC4440319  PMID: 23151990
dynamic causal modeling; stochastic DCM; effective connectivity; working memory; cocaine dependence; addiction
25.  Brain Connectivity during Verbal Working Memory in Children and Adolescents 
Human brain mapping  2012;35(2):698-711.
Working memory (WkM) is a fundamental cognitive process that serves as a building block for higher order cognitive functions. While studies have shown that children and adolescents utilize similar brain regions during verbal WkM, there have been few studies that evaluate the developmental differences in brain connectivity. Our goal was to study the development of brain connectivity related to verbal WkM in typically developing children and adolescents.
Thirty-five healthy children and adolescents, divided into three groups: 9–12 (children), 13–16 (young adolescents) and 17–19 (older adolescents) years, were included in this fMRI study. The verbal WkM task involved a modified Sternberg item recognition paradigm using three different loads. Brain connectivity analysis was performed using independent component analyses and regressing the components with the design matrix to determine task-related networks.
Connectivity analyses resulted in four components associated solely with encoding, four solely with recognition and two with both. Two networks demonstrated age-related differences with respect to load, 1) the left motor area and right cerebellum, and 2) the left prefrontal cortex, left parietal lobe, and right cerebellum. Post hoc analyses revealed that the first network showed significant effects of age between children and the two older groups. There was increasing connectivity with increasing load for adolescents. The second network demonstrated age-related differences between children and older adolescents. Children have higher task-related connectivity at lower loads, but they tend to equalize with the adolescents with higher loads. Finally, a non-load related network involving the orbital frontal and anterior cingulate cortices showed less connectivity in children.
doi:10.1002/hbm.22193
PMCID: PMC4435694  PMID: 23233279
adolescents; brain connectivity; children; development; fMRI; verbal working memory

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