Dual Regression Approach Research Articles

TCM psychological pathomechanism of RBD

Introduction: Resting-state functional MRI (rs-fMRI) has been shown by our group as a promising tool for the diagnosis of early Parkinson’s disease (PD). As REM sleep behavior disorder (RBD) is strongly associated with alpha-synucleinopathy, we aimed to investigate potential resting-state connectivity and structural changes in this promising prodromal group. Materials and methods: Twenty-six patients with polysomnography-proven idiopathic RBD and 22 age and sexmatched healthy controls were recruited from the Oxford Parkinson’s Disease Centre (OPDC) patient cohort. All subjects underwent a structural MRI protocol, including T1weighted and diffusion imaging. Blood-oxygen level dependent (BOLD) sequences were acquired during resting conditions, with the subject awake and their eyes open. Resting-state analysis was performed using probabilistic independent component analysis (ICA) as implemented in the Multivariate Exploratory Linear Optimized Decomposition into Independent Component FSL tool (MELODIC). A previously developed template of resting-sate networks typical for healthy elderly participants was used. Based on a priori hypotheses, three networks of interest (the basal ganglia network (BGN), the sensorimotor network (SMN) and the default mode network (DMN)), and one control network (the primary visual network (PVN)) were chosen for further analyses. The dual regression approach was then used to identify individual temporal dynamics and the associated spatial maps. Statistical comparisons between RBD and healthy controls were performed using permutation-based non-parametric inference. Results were corrected for age, sex and voxelwise gray matter volume, and defined as significant at p < 0.05 after FWE correction. Results: One of the RBD patients had significant cortical atrophy on their T1-weighted structural scan, and was excluded from further analyses. Patients with RBD performed marginally worse on the UPDRS part III (0.7 (1.1) vs. 3.0 (3.4), p = 0.005) and had lower cognitive scores (MMSE 29.3 (1.0) vs. 27.4 (1.7), p < 0.001). The two groups performed comparatively on the Purdue Pegboard Test (p = 0.5). At the time of the MRI investigation, none of the subjects fulfilled the UK Parkinson’s Disease Society Brain bank criteria for the diagnosis of idiopathic Parkinson’s disease and there was no clinical suspicion of any other neurological condition. There were no significant volumetric differences between patients with RBD and healthy controls. Voxel-based morphometry analysis did not yield any significant graymatter differences between the two groups. Similarly, no significant differences of fractional anisotropy were found using white matter tract analysis. Rs-fMRI revealed decreased coactivation within the BGN (involving the caudate, putamen, globus pallidus and the dorsolateral prefrontal cortex) and the SMN (precentral gyrus) of patients with RBD. No increased coactivation within these networks was seen in the RBD group, and no between-group differences were seen in the DMN and PVN. Conclusion: Rs-fMRI demonstrates significantly reduced coactivation within the BGN and SMN of patients with RBD. These results are similar to those found in early PD and are likely to represent pre-clinical basal ganglia dysfunction. This approach shows great promise as a potential biomarker for prodromal alpha-synucleinopathy. Acknowledgements: This studywas funded by theMonument Trust Discovery Award from Parkinson’s UK and supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. The authors report no conflict of interest in relation to this work.

Investigating distinct and common abnormalities of resting-state functional connectivity in depression, anxiety, and their comorbid states

Depression and anxiety disorders are highly comorbid and share neurobiological characteristics. However, this is usually not explicitly addressed in studies on intrinsic brain functioning in these disorders. Contrary to previous resting-state reports on small, monodiagnostic subsets of the current sample, we investigated resting-state functional connectivity (RSFC) in medication-free patients with depression, anxiety, comorbid depression and anxiety, and a healthy control group. RSFC was investigated in 140 medication-free subjects: 37 major depressive disorder patients (MDD), 30 patients with one or more anxiety disorders (ANX), 25 patients with MDD and one or more anxiety disorders (COM), and 48 healthy controls (HC). RSFC networks were calculated using a probabilistic independent component analysis. Using a dual regression approach, individuals׳ timecourses were extracted and regressed to obtain subjects-specific spatial maps, which were used for group comparisons in four networks of interest (limbic, default mode, salience and sensory–motor networks). When compared to HC, the COM group showed increased RSFC of the limbic network with a cluster containing the bilateral precuneus, intracalcarine cortex, lingual gyrus, and posterior cingulate, and with a cluster including the right precentral gyrus, inferior frontal gyrus, and middle frontal gyrus. This effect was specific for comorbid depression and anxiety. No abnormal RSFC of other networks or in the MDD and ANX groups was observed. No association was found between strength of RSFC and symptom severity. These results indicate that altered RSFC of cortical regions with a limbic network could be specific for comorbid depression and anxiety.

Functional Connectivity of Insula, Basal Ganglia, and Prefrontal Executive Control Networks during Hypoglycemia in Type 1 Diabetes.

The major factor limiting improved glucose control in type 1 diabetes is the significant increase in hypoglycemia associated with insulin treatment. Repeated exposure to hypoglycemia alters patients' ability to recognize the autonomic and neuroglycopenic symptoms associated with low plasma glucose levels. We examined brain resting state networks during the induction of hypoglycemia in diabetic and control subjects and found differences in networks involved in sensorimotor function, cognition, and interoceptive awareness that were related to chronic levels of glycemic control. These findings identify brain regions that are sensitive to variations in plasma glucose levels and may also provide a basis for understanding the mechanisms underlying the increased incidence of cognitive impairment and affective disorders seen in patients with diabetes.

Aberrant functional connectivity of resting state networks associated with trait anxiety

Trait anxiety, a personality dimension, has been characterized by functional consequences such as increased distractibility, attentional bias in favor of threat-related information and hyper-responsive amygdala. However, literature on the association between resting state brain functional connectivity, as studied using resting state functional magnetic resonance imaging (rs-fMRI), and reported anxiety levels in the sub-clinical population is limited. In the present study, we employed rs-fMRI to investigate the possible alterations in the functional integrity of Resting State Networks (RSNs) associated with trait anxiety of the healthy subjects (15 high anxious and 14 low anxious). The rs-fMRI data was analyzed using independent component analysis and a dual regression approach that was applied on 12 RSNs that were identified using FSL. High anxious subjects showed significantly reduced functional connectivity in regions of the default mode network (posterior cingulate gyrus, middle and superior temporal gyrus, planum polare, supramarginal gyrus, temporal pole, angular gyrus and lateral occipital gyrus) which has been suggested to be involved in episodic memory, theory of mind, self-evaluation, and introspection, and perceptual systems including medial visual network, auditory network and another network involving temporal, parieto-occipital and frontal regions. Reduction in resting state connectivity in regions of the perceptual networks might underlie the perceptual, attentional and working memory deficits associated with trait anxiety. To our knowledge, this is the first study to relate trait anxiety to resting state connectivity using independent component analysis.

Alterations of Functional Connectivity Among Resting-State Networks in Hypothyroidism.

Hypothyroidism affects brain functioning as suggested by various neuroimaging studies. The primary focus of the present study was to examine whether hypothyroidism would impact connectivity among resting-state networks (RSNs) using resting-state functional magnetic resonance imaging (rsfMRI). Twenty-two patients with hypothyroidism and 22 healthy controls were recruited and scanned using rsfMRI. The data were analysed using independent component analysis and a dual regression approach that was applied on five RSNs that were identified using fsl software (http://fsl.fmrib.ox.ac.uk). Hypothyroid patients showed significantly decreased functional connectivity in the regions of the right frontoparietal network (frontal pole), the medial visual network (lateral occipital gyrus, precuneus cortex and cuneus) and the motor network (precentral gyrus, postcentral gyrus, precuneus cortex, paracingulate gyrus, cingulate gyrus and supramarginal gyrus) compared to healthy controls. The reduced functional connectivity in the right frontoparietal network, the medial visual network and the motor network suggests neurocognitive alterations in hypothyroid patients in the corresponding functions. However, the study would be further continued to investigate the effects of thyroxine treatment and correlation with neurocognitive scores. The findings of the present study provide further interesting insights into our understanding of the action of thyroid hormone on the adult human brain.

Vascular risk factor burden correlates with cerebrovascular reactivity but not resting state coactivation in the default mode network.

White matter hyperintensities (WMH) are prevalent among older adults and are often associated with cognitive decline and increased risk of stroke and dementia. Vascular risk factors (VRFs) are linked to WMH, yet the impact of multiple VRFs on gray matter function is still unclear. The goal of this study was to test for associations between the number of VRFs and cerebrovascular reactivity (CVR) and resting state (RS) coactivation among individuals with WMH. Twenty-nine participants with suspected WMH were grouped based on the number of VRFs (subgroups: 0, 1, or ≥2). CVR and RS coactivation were measured with blood oxygenation level-dependent (BOLD) imaging on a 3T magnetic resonance imaging (MRI) system during hypercapnia and rest, respectively. Default-mode (DMN), sensory-motor, and medial-visual networks, generated using independent component analysis of RS-BOLD, were selected as networks of interest (NOIs). CVR-BOLD was analyzed using two methods: 1) a model-based approach using CO2 traces, and 2) a dual-regression (DR) approach using NOIs as spatial inputs. Average CVR and RS coactivations within NOIs were compared between VRF subgroups. A secondary analysis investigated the correlation between CVR and RS coactivation. VRF subgroup differences were detected using DR-based CVR in the DMN (F20,2 = 5.17, P = 0.015) but not the model-based CVR nor RS coactivation. DR-based CVR was correlated with RS coactivation in the DMN (r(2) = 0.28, P = 0.006) but not the sensory-motor nor medial-visual NOIs. In individuals with WMH, CVR in the DMN was inversely associated with the number of VRFs and correlated with RS coactivation.

Age-related changes in resting-state networks of a large sample size of healthy elderly.

Population aging is burdening the society globally, and the evaluation of functional networks is the key toward understanding cognitive changes in normal aging. However, the effect of age on default mode subnetworks has not been documented well, and age-related changes in many resting-state networks remain debatable. The purpose of this study was to propose more precise results for these issues using a large sample size. We used group-level meta-ICA analysis and dual regression approach for identifying resting-state networks from functional magnetic resonance imaging data of 430 healthy elderly participants. Partial correlation was used to observe age-related correlations within and between resting-state networks. In the default mode network, only the ventral subnetwork negatively correlated with age. Age-related decrease in functional connectivity was also noted in the auditory, right frontoparietal, sensorimotor, and visual medial networks. Further, some age-related increases and decreases were observed for between-network correlations. The results of this study suggest that only the ventral default mode subnetwork had age-related decline in functional connectivity and several reverse patterns of resting-state networks for network development. Understanding age-related network changes may provide solutions for the impact of population aging and diagnosis of neurodegenerative diseases.

Increased functional connectivity in the resting-state basal ganglia network after acute heroin substitution.

Reinforcement signals in the striatum are known to be crucial for mediating the subjective rewarding effects of acute drug intake. It is proposed that these effects may be more involved in early phases of drug addiction, whereas negative reinforcement effects may occur more in later stages of the illness. This study used resting-state functional magnetic resonance imaging to explore whether acute heroin substitution also induced positive reinforcement effects in striatal brain regions of protracted heroin-maintained patients. Using independent component analysis and a dual regression approach, we compared resting-state functional connectivity (rsFC) strengths within the basal ganglia/limbic network across a group of heroin-dependent patients receiving both an acute infusion of heroin and placebo and 20 healthy subjects who received placebo only. Subsequent correlation analyses were performed to test whether the rsFC strength under heroin exposure correlated with the subjective rewarding effect and with plasma concentrations of heroin and its main metabolites morphine. Relative to the placebo treatment in patients, heroin significantly increased rsFC of the left putamen within the basal ganglia/limbic network, the extent of which correlated positively with patients' feelings of rush and with the plasma level of morphine. Furthermore, healthy controls revealed increased rsFC of the posterior cingulate cortex/precuneus in this network relative to the placebo treatment in patients. Our results indicate that acute heroin substitution induces a subjective rewarding effect via increased striatal connectivity in heroin-dependent patients, suggesting that positive reinforcement effects in the striatum still occur after protracted maintenance therapy.

Impairment of functional integration of the default mode network correlates with cognitive outcome at three months after stroke.

Resting‐state studies conducted with stroke patients are scarce. The study of brain activity and connectivity at rest provides a unique opportunity for the investigation of brain rewiring after stroke and plasticity changes. This study sought to identify dynamic changes in the functional organization of the default mode network (DMN) of stroke patients at three months after stroke. Eleven patients (eight male and three female; age range: 48–72) with right cortical and subcortical ischemic infarctions and 17 controls (eleven males and six females; age range: 57–69) were assessed by neurological and neuropsychological examinations and scanned with resting‐state functional magnetic ressonance imaging. First, we explored group differences in functional activity within the DMN by means of probabilistic independent component analysis followed by a dual regression approach. Second, we estimated functional connectivity between 11 DMN nodes both locally by means of seed‐based connectivity analysis, as well as globally by means of graph‐computation analysis. We found that patients had greater DMN activity in the left precuneus and the left anterior cingulate gyrus when compared with healthy controls (P < 0.05 family‐wise error corrected). Seed‐based connectivity analysis showed that stroke patients had significant impairment (P = 0.014; threshold = 2.00) in the connectivity between the following five DMN nodes: left superior frontal gyrus (lSFG) and posterior cingulate cortex (t = 2.01); left parahippocampal gyrus and right superior frontal gyrus (t = 2.11); left parahippocampal gyrus and lSFG (t = 2.39); right parietal and lSFG (t = 2.29). Finally, mean path length obtained from graph‐computation analysis showed positive correlations with semantic fluency test (r s = 0.454; P = 0.023), phonetic fluency test (r s = 0.523; P = 0.007) and the mini mental state examination (r s = 0.528; P = 0.007). In conclusion, the ability to regulate activity of the DMN appears to be a central part of normal brain function in stroke patients. Our study expands the understanding of the changes occurring in the brain after stroke providing a new avenue for investigating lesion‐induced network plasticity. Hum Brain Mapp 36:577–590, 2015. © 2014 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Cognitive impairment and resting-state network connectivity in Parkinson's disease.

The purpose of this work was to evaluate changes in the connectivity patterns of a set of cognitively relevant, dynamically interrelated brain networks in association with cognitive deficits in Parkinson's disease (PD) using resting-state functional MRI. Sixty-five nondemented PD patients and 36 matched healthy controls were included. Thirty-four percent of PD patients were classified as having mild cognitive impairment (MCI) based on performance in attention/executive, visuospatial/visuoperceptual (VS/VP) and memory functions. A data-driven approach using independent component analysis (ICA) was used to identify the default-mode network (DMN), the dorsal attention network (DAN) and the bilateral frontoparietal networks (FPN), which were compared between groups using a dual-regression approach controlling for gray matter atrophy. Additional seed-based analyses using a priori defined regions of interest were used to characterize local changes in intranetwork and internetwork connectivity. Structural group comparisons through voxel-based morphometry and cortical thickness were additionally performed to assess associated gray matter atrophy. ICA results revealed reduced connectivity between the DAN and right frontoinsular regions in MCI patients, associated with worse performance in attention/executive functions. The DMN displayed increased connectivity with medial and lateral occipito-parietal regions in MCI patients, associated with worse VS/VP performance, and with occipital reductions in cortical thickness. In line with data-driven results, seed-based analyses mainly revealed reduced within-DAN, within-DMN and DAN-FPN connectivity, as well as loss of normal DAN-DMN anticorrelation in MCI patients. Our findings demonstrate differential connectivity changes affecting the networks evaluated, which we hypothesize to be related to the pathophysiological bases of different types of cognitive impairment in PD.

A study of structural and functional connectivity in early Alzheimer's disease using rest fMRI and diffusion tensor imaging.

Alzheimer's disease (AD) is a progressive neurodegenerative condition where in early diagnosis and interventions are key policy priorities in dementia services and research. We studied the functional and structural connectivity in mild AD to determine the nature of connectivity changes that coexist with neurocognitive deficits in the early stages of AD. Fifteen mild AD subjects and 15 cognitively healthy controls (CHc) matched for age and gender, underwent detailed neurocognitive assessment and magnetic resonance imaging (MRI) of resting state functional MRI (rs-fMRI) and diffusion tensor imaging (DTI). Rest fMRI was analyzed using dual regression approach and DTI by voxel wise statistics. Patients with mild AD had significantly lower functional connectivity (FC) within the default mode network and increased FC within the executive network. The mild AD group scored significantly lower in all domains of cognition compared with CHc. But fractional anisotropy did not significantly (p < 0.05) differ between the groups. Resting state functional connectivity alterations are noted during initial stages of cognitive decline in AD, even when there are no significant white matter microstructural changes.

Altered resting‐state connectivity in Huntington's Disease

Huntington's disease (HD) is an autosomal dominantly inherited neurodegenerative disorder characterized by motor, cognitive, and psychiatric symptoms. Using resting-state fMRI (rs-fMRI) we investigated the functional integrity of resting-state networks (RSN) in HD. 17 HD and 19 matched control participants were examined at a 3 Tesla MR scanner. After controlling for structural degeneration by means of voxel-based morphometry, task-free rs-fMRI data were analyzed using Independent Component Analysis (ICA) and a dual-regression approach in the context of genetic and clinical parameters. Further, we evaluated HD-related differences in interregional connectivity between networks. RSN analysis showed a significant increase in intrinsic functional connectivity in the HD sample compared with controls, including the thalamus, striatum, prefrontal, premotor, and parietal maps. A subset of the Default Mode Network (DMN) was also affected. In the HD cohort, motor impairment correlated with higher network connectivity in mainly motor and parietal cortices. Deteriorating total functional capacity was additionally associated with higher connectivity in the striatum, thalamus, insular and frontal areas. This pattern of increased activity in intrinsic functional networks might suggest a reduced ability of intra-network differentiation with clinical disease progression in HD. Finally, results showed reduced long-range connectivity between parietal ICA components in HD compared to controls, indicating impaired functional coupling between interregional networks in HD. Our data demonstrates that functional connectivity is profoundly altered in HD, both within and between RSN. Rs-fMRI analysis may provide additional valuable insights into neuronal dysfunctions beyond HD-related structural degeneration and disruptions of functional circuits in HD.

Resting-State Functional Magnetic Resonance Imaging Activity and Connectivity and Cognitive Outcome in Traumatic Brain Injury

The study of brain activity and connectivity at rest provides a unique opportunity for the investigation of the brain substrates of cognitive outcome after traumatic axonal injury. This knowledge may contribute to improve clinical management and rehabilitation programs. To study functional magnetic resonance imaging abnormalities in signal amplitude and brain connectivity at rest and their relationship to cognitive outcome in patients with chronic and severe traumatic axonal injury. Observational study. University of Barcelona and Hospital Clinic de Barcelona, Barcelona, and Institut Guttmann-Neurorehabilitation Hospital, Badalona, Spain. Twenty patients with traumatic brain injury (TBI) were studied, along with 17 matched healthy volunteers. Resting-state functional magnetic resonance imaging and diffusion tensor imaging data were acquired. After exploring group differences in amplitude of low-frequency fluctuations (ALFF), we studied functional connectivity within the default mode network (DMN) by means of independent component analysis, followed by a dual regression approach and seed-based connectivity analyses. Finally, we performed probabilistic tractography between the frontal and posterior nodes of the DMN. Signal amplitude and functional connectivity during the resting state, tractography related to DMN, and the association between signal amplitudes and cognitive outcome. Patients had greater ALFF in frontal regions, which was correlated with cognitive performance. Within the DMN, patients showed increased connectivity in the frontal lobes. Seed-based connectivity analyses revealed augmented connectivity within surrounding areas of the frontal and left parietal nodes of the DMN. Fractional anisotropy of the cingulate tract was correlated with increased connectivity of the frontal node of the DMN in patients with TBI. Increased ALFF is related to better cognitive performance in chronic TBI. The loss of structural connectivity produced by damage to the cingulum tract explained the compensatory increases in functional connectivity within the frontal node of the DMN.

Brain modifications after acute alcohol consumption analyzed by resting state fMRI

Resting-state functional magnetic resonance imaging (fMRI) is a recent breakthrough in neuroimaging research able to describe “in vivo” the spontaneous baseline neuronal activity characterized by blood oxygen level dependent (BOLD) signal fluctuations at slow frequency (0.01–0.1Hz) that, in the absence of any task, forms spatially distributed functional connectivity networks, called resting state networks (RSNs). The aim of this study was to investigate, in the young and healthy population, the changing of the RSNs after acute ingestion of an alcohol dose able to determine a blood concentration (0.5g/L) that barely exceeds the legal limits for driving in the majority of European Countries. Fifteen healthy volunteers underwent two fMRI sessions using a 1.5T MR scanner before and after alcohol oral consumption. The main sequence acquired was EPI 2D BOLD, one per each session. To prevent the excessive alcohol consumption the subjects underwent the estimation of blood rate by breath test and after the stabilization of blood alcohol level (BAL) at 0.5g/L the subjects underwent the second fMRI session. Functional data elaboration was carried out using the probabilistic independent component analysis (PICA). Spatial maps so obtained were further organized, with MELODIC multisession temporal concatenation FSL option, in a cluster representing the group of pre-alcohol sessions and the group of post-alcohol sessions, followed by the dual regression approach in order to evaluate the increase or decrease in terms of connectivity in the RSNs between the two sessions at group level.The results we obtained reveal that acute consumption of alcohol reduces in a significant way the BOLD signal fluctuations in the resting brain selectively in the sub-callosal cortex (SCC), in left temporal fusiform cortex (TFC) and left inferior temporal gyrus (ITG), which are cognitive regions known to be part of the reward brain network and the ventral visual system.

Whole-brain functional connectivity during emotional word classification in medication-free Major Depressive Disorder: Abnormal salience circuitry and relations to positive emotionality

Major Depressive Disorder (MDD) has been associated with biased processing and abnormal regulation of negative and positive information, which may result from compromised coordinated activity of prefrontal and subcortical brain regions involved in evaluating emotional information. We tested whether patients with MDD show distributed changes in functional connectivity with a set of independently derived brain networks that have shown high correspondence with different task demands, including stimulus salience and emotional processing. We further explored if connectivity during emotional word processing related to the tendency to engage in positive or negative emotional states. In this study, 25 medication-free MDD patients without current or past comorbidity and matched controls (n = 25) performed an emotional word-evaluation task during functional MRI. Using a dual regression approach, individual spatial connectivity maps representing each subject's connectivity with each standard network were used to evaluate between-group differences and effects of positive and negative emotionality (extraversion and neuroticism, respectively, as measured with the NEO-FFI). Results showed decreased functional connectivity of the medial prefrontal cortex, ventrolateral prefrontal cortex, and ventral striatum with the fronto-opercular salience network in MDD patients compared to controls. In patients, abnormal connectivity was related to extraversion, but not neuroticism. These results confirm the hypothesis of a relative (para)limbic–cortical decoupling that may explain dysregulated affect in MDD. As connectivity of these regions with the salience network was related to extraversion, but not to general depression severity or negative emotionality, dysfunction of this network may be responsible for the failure to sustain engagement in rewarding behavior.

Default mode network in young people with familial risk for psychosis — The Oulu Brain and Mind Study

ObjectiveThe default mode network (DMN) is active in the brain at rest and de-activated during cognitive tasks. Abnormal function in the DMN has been reported in people with schizophrenia but it is not known whether this applies also to people with a familial risk for psychosis (FR). We compared the activity of the DMN between FR participants and controls. MethodsWe conducted a resting state functional MRI (R-fMRI) in 72 young adults without psychosis and with a history of psychosis in one or both parents (FR group) and 72 age matched controls without parental psychosis, and without current psychosis or a current prodromal syndrome. Both groups were drawn from the Northern Finland Birth Cohort 1986 (Oulu Brain and Mind study). Parental psychosis was established using the Finnish hospital discharge register. We pre-processed R-fMRI data using independent component analysis followed by a dual regression approach to assess differences between the groups. The FR vs. Control group differences were assessed using non-parametric permutation tests utilizing threshold-free cluster enhancement and correcting for multiple comparisons (p<0.05). ResultsFR participants demonstrated significantly lower activity compared with controls in the posterior cingulate cortex, the central node of the DMN. The size of the region was 41mm3. ConclusionThe activity of the DMN differed between FR and control groups. This suggests that familial risk for psychotic disorders may be mediated through genetic effects on connectivity in the posterior cingulate cortex.

Iterative approach of dual regression with a sparse prior enhances the performance of independent component analysis for group functional magnetic resonance imaging (fMRI) data

This study proposes an iterative dual-regression (DR) approach with sparse prior regularization to better estimate an individual's neuronal activation using the results of an independent component analysis (ICA) method applied to a temporally concatenated group of functional magnetic resonance imaging (fMRI) data (i.e., Tc-GICA method). An ordinary DR approach estimates the spatial patterns (SPs) of neuronal activation and corresponding time courses (TCs) specific to each individual's fMRI data with two steps involving least-squares (LS) solutions. Our proposed approach employs iterative LS solutions to refine both the individual SPs and TCs with an additional a priori assumption of sparseness in the SPs (i.e., minimally overlapping SPs) based on L(1)-norm minimization. To quantitatively evaluate the performance of this approach, semi-artificial fMRI data were created from resting-state fMRI data with the following considerations: (1) an artificially designed spatial layout of neuronal activation patterns with varying overlap sizes across subjects and (2) a BOLD time series (TS) with variable parameters such as onset time, duration, and maximum BOLD levels. To systematically control the spatial layout variability of neuronal activation patterns across the "subjects" (n=12), the degree of spatial overlap across all subjects was varied from a minimum of 1 voxel (i.e., 0.5-voxel cubic radius) to a maximum of 81 voxels (i.e., 2.5-voxel radius) across the task-related SPs with a size of 100 voxels for both the block-based and event-related task paradigms. In addition, several levels of maximum percentage BOLD intensity (i.e., 0.5, 1.0, 2.0, and 3.0%) were used for each degree of spatial overlap size. From the results, the estimated individual SPs of neuronal activation obtained from the proposed iterative DR approach with a sparse prior showed an enhanced true positive rate and reduced false positive rate compared to the ordinary DR approach. The estimated TCs of the task-related SPs from our proposed approach showed greater temporal correlation coefficients with a reference hemodynamic response function than those of the ordinary DR approach. Moreover, the efficacy of the proposed DR approach was also successfully demonstrated by the results of real fMRI data acquired from left-/right-hand clenching tasks in both block-based and event-related task paradigms.

Changes in resting‐state functionally connected parietofrontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Group inference of default-mode networks from functional magnetic resonance imaging data: comparison of random- and mixed-effects group statistics

Default-mode network (DMN) activity measured with functional magnetic resonance imaging (fMRI) represents dominant intrinsic neuronal activations of the human brain during rest as opposed to task periods. Previous studies have demonstrated the utility of DMNs in identifying characteristic traits such as hyperactivation and hypoactivation from group-level fMRI data. However, these group-level spatial patterns (SPs) were mostly based on random-effect (RFX) statistics determined using only the intersubject variability. To reduce the potentially significant level of variability in group-level SPs in RFX due to intrasubject variability, we were motivated to adopt a mixed-effects (MFX) statistics that is using both intrasubject and intersubject variability. Publicly available group fMRI database during resting state was analyzed using a temporal concatenation-based group independent component (IC) analysis, and DMN-related ICs at the group-level were automatically selected. The individual-level SPs of these DMN-related ICs were subsequently estimated using a dual-regression approach. Using these individual-level SPs, we evaluated the reproducibility and potential variability of the DMNs from the RFX and MFX statistics using performance measures including (1) neuronal activation levels, (2) percentages of overlap, (3) Pearson's spatial correlation coefficients, and (4) the distances between center-of-clusters. The resulting SPs from the MFX-based group inference showed a significantly greater level of reproducibility than those from the RFX-based group inference as tested in a bootstrapping framework Family-wise error (FWE)-corrected p < 10−10, one-way analysis of variance (ANOVA)). The reported findings may provide a valuable supplemental option for investigating the neuropsychiatric group- or condition-dependent characteristic traits implicated in DMNs. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 121–131, 2012 © 2012 Wiley Periodicals, Inc.

Prefrontal and limbic resting state brain network functional connectivity differs between nicotine-dependent smokers and non-smoking controls

BackgroundBrain dysfunction in prefrontal cortex (PFC) and dorsal striatum (DS) contributes to habitual drug use. These regions are constituents of brain networks thought to be involved in drug addiction. To investigate whether networks containing these regions differ between nicotine dependent female smokers and age-matched female non-smokers, we employed functional MRI (fMRI) at rest. MethodsData were processed with independent component analysis (ICA) to identify resting state networks (RSNs). We identified a subcortical limbic network and three discrete PFC networks: a medial prefrontal cortex (mPFC) network and right and left lateralized fronto-parietal networks common to all subjects. We then compared these RSNs between smokers and non-smokers using a dual regression approach. ResultsSmokers had greater coupling versus non-smokers between left fronto-parietal and mPFC networks. Smokers with the greatest mPFC–left fronto-parietal coupling had the most DS smoking cue reactivity as measured during an fMRI smoking cue reactivity paradigm. This may be important because the DS plays a critical role in maintaining drug-cue associations. Furthermore, subcortical limbic network amplitude was greater in smokers. ConclusionsOur results suggest that prefrontal brain networks are more strongly coupled in smokers, which could facilitate drug-cue responding. Our data also are the first to document greater reward-related network fMRI amplitude in smokers. Our findings suggest that resting state PFC network interactions and limbic network amplitude can differentiate nicotine-dependent smokers from controls, and may serve as biomarkers for nicotine dependence severity and treatment efficacy.