Impact of glutamate levels on neuronal response and cognitive abilities in schizophrenia.
Neuroimage Clin. 2014;4:576-84
Authors: Falkenberg LE, Westerhausen R, Craven AR, Johnsen E, Kroken RA, L Berg EM, Specht K, Hugdahl K
Schizophrenia is characterized by impaired cognitive functioning, and brain regions involved in cognitive control processes show marked glutamatergic abnormalities. However, it is presently unclear whether aberrant neuronal response is directly related to the observed deficits at the metabolite level in schizophrenia. Here, 17 medicated schizophrenia patients and 17 matched healthy participants underwent functional magnetic resonance imaging (fMRI) when performing an auditory cognitive control task, as well as proton magnetic resonance spectroscopy ((1)H-MRS) in order to assess resting-state glutamate in the anterior cingulate cortex. The combined fMRI-(1)H-MRS analysis revealed that glutamate differentially predicted cortical blood-oxygen level-dependent (BOLD) response in patients and controls. While we found a positive correlation between glutamate and BOLD response bilaterally in the inferior parietal lobes in the patients, the corresponding correlation was negative in the healthy control participants. Further, glutamate levels predicted task performance in patients, such that lower glutamate levels were related to impaired cognitive control functioning. This was not seen for the healthy controls. These findings suggest that schizophrenia patients have a glutamate-related dysregulation of the brain network supporting cognitive control functioning. This could be targeted in future research on glutamatergic treatment of cognitive symptoms in schizophrenia.
PMID: 24749064 [PubMed]
A robust classifier to distinguish noise from FMRI independent components.
PLoS One. 2014;9(4):e95493
Authors: Sochat V, Supekar K, Bustillo J, Calhoun V, Turner JA, Rubin DL
Analyzing Functional Magnetic Resonance Imaging (fMRI) of resting brains to determine the spatial location and activity of intrinsic brain networks-a novel and burgeoning research field-is limited by the lack of ground truth and the tendency of analyses to overfit the data. Independent Component Analysis (ICA) is commonly used to separate the data into signal and Gaussian noise components, and then map these components on to spatial networks. Identifying noise from this data, however, is a tedious process that has proven hard to automate, particularly when data from different institutions, subjects, and scanners is used. Here we present an automated method to delineate noisy independent components in ICA using a data-driven infrastructure that queries a database of 246 spatial and temporal features to discover a computational signature of different types of noise. We evaluated the performance of our method to detect noisy components from healthy control fMRI (sensitivity = 0.91, specificity = 0.82, cross validation accuracy (CVA) = 0.87, area under the curve (AUC) = 0.93), and demonstrate its generalizability by showing equivalent performance on (1) an age- and scanner-matched cohort of schizophrenia patients from the same institution (sensitivity = 0.89, specificity = 0.83, CVA = 0.86), (2) an age-matched cohort on an equivalent scanner from a different institution (sensitivity = 0.88, specificity = 0.88, CVA = 0.88), and (3) an age-matched cohort on a different scanner from a different institution (sensitivity = 0.72, specificity = 0.92, CVA = 0.79). We additionally compare our approach with a recently published method . Our results suggest that our method is robust to noise variations due to population as well as scanner differences, thereby making it well suited to the goal of automatically distinguishing noise from functional networks to enable investigation of human brain function.
PMID: 24748378 [PubMed - in process]
Decreased resting functional connectivity after traumatic brain injury in the rat.
PLoS One. 2014;9(4):e95280
Authors: Mishra AM, Bai X, Sanganahalli BG, Waxman SG, Shatillo O, Grohn O, Hyder F, Pitkänen A, Blumenfeld H
Traumatic brain injury (TBI) contributes to about 10% of acquired epilepsy. Even though the mechanisms of post-traumatic epileptogenesis are poorly known, a disruption of neuronal networks predisposing to altered neuronal synchrony remains a viable candidate mechanism. We tested a hypothesis that resting state BOLD-fMRI functional connectivity can reveal network abnormalities in brain regions that are connected to the lesioned cortex, and that these changes associate with functional impairment, particularly epileptogenesis. TBI was induced using lateral fluid-percussion injury in seven adult male Sprague-Dawley rats followed by functional imaging at 9.4T 4 months later. As controls we used six sham-operated animals that underwent all surgical operations but were not injured. Electroencephalogram (EEG)-functional magnetic resonance imaging (fMRI) was performed to measure resting functional connectivity. A week after functional imaging, rats were implanted with bipolar skull electrodes. After recovery, rats underwent pentyleneterazol (PTZ) seizure-susceptibility test under EEG. For image analysis, four pairs of regions of interests were analyzed in each hemisphere: ipsilateral and contralateral frontal and parietal cortex, hippocampus, and thalamus. High-pass and low-pass filters were applied to functional imaging data. Group statistics comparing injured and sham-operated rats and correlations over time between each region were calculated. In the end, rats were perfused for histology. None of the rats had epileptiform discharges during functional imaging. PTZ-test, however revealed increased seizure susceptibility in injured rats as compared to controls. Group statistics revealed decreased connectivity between the ipsilateral and contralateral parietal cortex and between the parietal cortex and hippocampus on the side of injury as compared to sham-operated animals. Injured animals also had abnormal negative connectivity between the ipsilateral and contralateral parietal cortex and other regions. Our data provide the first evidence on abnormal functional connectivity after experimental TBI assessed with resting state BOLD-fMRI.
PMID: 24748279 [PubMed - in process]
Gender differences in brain activity and the relationship between brain activity and differences in prevalence rates between male and female major depressive disorder patients: A resting-state fMRI study.
Clin Neurophysiol. 2014 Mar 15;
Authors: Yao Z, Yan R, Wei M, Tang H, Qin J, Lu Q
OBJECTIVE: We examined the gender-difference effect on abnormal spontaneous neuronal activity of male and female major depressive disorder (MDD) patients using the amplitude of low-frequency fluctuation (ALFF) and the further clarified the relationship between the abnormal ALFF and differences in MDD prevalence rates between male and female patients.
METHODS: Fourteen male MDD patients, 13 female MDD patients and 15 male and 15 female well matched healthy controls (HCs) completed this study. The ALFF approach was used, and Pearson correlation was conducted to observe a possible clinical relevance.
RESULTS: There were widespread differences in ALFF values between female and male MDD patients, including some important parts of the frontoparietal network, auditory network, attention network and cerebellum network. In female MDD patients, there was a positive correlation between average ALFF values of the left postcentral gyrus and the severity of weight loss symptom.
CONCLUSIONS: The gender-difference effect leading to abnormal brain activity is an important underlying pathomechanism for different somatic symptoms in MDD patients of different genders and is likely suggestive of higher MDD prevalence rates in females.
SIGNIFICANCE: The abnormal ALFF resulting from the gender-difference effect might improve our understanding of the differences in prevalence rates between male and female MDD patients from another perspective.
PMID: 24746685 [PubMed - as supplied by publisher]
[Functional connectivity of temporal parietal junction in online game addicts:a resting-state functional magnetic resonance imaging study].
Zhonghua Yi Xue Za Zhi. 2014 Feb 11;94(5):372-5
Authors: Yuan J, Qian R, Lin B, Fu X, Wei X, Weng C, Niu C, Wang Y
OBJECTIVE: To explore the functions of temporal parietal junction (TPJ) as parts of attention networks in the pathogenesis of online game addiction using resting-state functional magnetic resonance imaging (fMRI).
METHODS: A total of 17 online game addicts (OGA) were recruited as OGA group and 17 healthy controls during the same period were recruited as CON group. The neuropsychological tests were performed for all of them to compare the inter-group differences in the results of Internet Addiction Test (IAT) and attention functions. All fMRI data were preprocessed after resting-state fMRI scanning. Then left and right TPJ were selected as regions of interest (ROIs) to calculate the linear correlation between TPJ and entire brain to compare the inter-group differences.
RESULTS: Obvious differences existed between OGA group (71 ± 5 scores) and CON group (19 ± 7 scores) in the IAT results and attention function (P < 0.05). Compared with the controls, right TPJ in online game addicts showed decreased functional connectivity with bilateral ventromedial prefrontal cortex (VMPFC), bilateral hippocampal gyrus and bilateral amygdaloid nucleus, but increased functional connectivity with right cuneus.However, left TPJ demonstrated decreased functional connectivity with bilateral superior frontal gyrus and bilateral middle frontal gyrus, but increased functional connectivity with bilateral cuneus (P < 0.05).
CONCLUSION: Altered functional connectivity of TPJ reflected its dysfunction in online game addicts.It suggests that TPJ is an important component of attention networks participating in the generation of online game addiction.
PMID: 24746086 [PubMed - in process]
Altered spontaneous activity in treatment-naive childhood absence epilepsy revealed by Regional Homogeneity.
J Neurol Sci. 2014 Feb 28;
Authors: Yang T, Fang Z, Ren J, Xiao F, Li Q, Liu L, Lei D, Gong Q, Zhou D
PURPOSE: To explore the differences in regional spontaneous activities throughout the whole brain by the Regional Homogeneity (ReHo) method in untreated childhood absence epilepsy (CAE), in order to understand the neuro-pathophysiological mechanism of function impairments in CAE.
METHODS: The rest-functional MRI was used to measure the ReHo in 16 patients with untreated CAE and 16 age- and sex-matched healthy controls. The correlations between the ReHo at each voxel of the whole brain and duration of epilepsy were analyzed. Results: Compared with healthy controls, we found that ReHo was decreased in bilateral thalamus, caudate, posterior lobe of cerebellum and areas mainly in the default mode network (DMN) (including precuneus and posterior cingulate cortex-PCC, bilateral inferior lateral parietal lobule). The increase of ReHo was found in bilateral insula, left occipital cortex. Moreover, a correlation analysis of the ReHo measurement versus the epilepsy duration was performed, and highly positive correlation was observed in precuneus/PCC and supplementary motor area (SMA).
SIGNIFICANCE: The current findings demonstrated alterations of ReHo in the striato-thalamo-cortical network in drug naïve CAE subjects during interictal resting state. Some regions with decreased ReHo followed the pattern of 'default' state of brain function. In addition, positive correlations between the ReHo values in the precuneus/PCC and SMA and the disease duration were identified. These results indicate that the involvement of these regions may be related to the pathomechanisms of seizure generation and the neurological deficits observed in CAE patients. ReHo has demonstrated the capability to characterize spontaneous brain dysfunction in epilepsy.
PMID: 24746024 [PubMed - as supplied by publisher]
Functional connectivity in the normal and injured brain.
Neuroscientist. 2013 Oct;19(5):509-22
Authors: Gillebert CR, Mantini D
The brain is neither uniform nor composed of similar modules but is rather a mosaic of different and highly interconnected regions. Accordingly, knowledge of functional connectivity between brain regions is crucial to understanding perception, cognition, and behavior. Functional connectivity methods estimate similarities between activity recorded in different regions of the brain. They are often applied to resting state activity, thus providing measures that are by nature task independent. The spatial patterns revealed by functional connectivity are not only shaped by the underlying anatomical structure of the brain but also partially depend on the history of task-driven coactivations. Inter-subject differences in functional connectivity may, at least to some degree, underlie variability observed in task performance across healthy subjects and in behavioral impairments in neurological patients. In this respect, recent studies have demonstrated that behavioral deficits in patients with brain injury are not only due to local tissue damage but also due to altered functional connectivity among structurally intact regions connected to the damaged site. Studies based on functional connectivity have the potential to advance basic understanding of how brain lesions induce neuropsychological syndromes. Furthermore, they may eventually suggest improved rehabilitation strategies for patients with brain injury, through the design of individualized treatment and recovery protocols.
PMID: 23064084 [PubMed - indexed for MEDLINE]
Studying the Spatial Distribution of Physiological Effects on BOLD Signals Using Ultrafast fMRI.
Front Hum Neurosci. 2014;8:196
Authors: Tong Y, Frederick BD
The blood-oxygen-level dependent (BOLD) signal in functional MRI (fMRI) reflects both neuronal activations and global physiological fluctuations. These physiological fluctuations can be attributed to physiological low frequency oscillations (pLFOs), respiration, and cardiac pulsation. With typical TR values, i.e., 2 s or longer, the high frequency physiological signals (i.e., from respiration and cardiac pulsation) are aliased into the low frequency band, making it hard to study the individual effect of these physiological processes on BOLD. Recently developed multiband EPI sequences, which offer full brain coverage with extremely short TR values (400 ms or less) allow these physiological signals to be spectrally separated. In this study, we applied multiband resting state scans on nine healthy participants with TR = 0.4 s. The spatial distribution of each physiological process on BOLD fMRI was explored using their spectral features and independent component analysis (ICA). We found that the spatial distributions of different physiological processes are distinct. First, cardiac pulsation affects mostly the base of the brain, where high density of arteries exists. Second, respiration affects prefrontal and occipital areas, suggesting the motion associated with breathing might contribute to the noise. Finally, and most importantly, we found that the effects of pLFOs dominated many prominent ICA components, which suggests that, contrary to the popular belief that aliased cardiac and respiration signals are the main physiological noise source in BOLD fMRI, pLFOs may be the most influential physiological signals. Understanding and measuring these pLFOs are important for denoising and accurately modeling BOLD signals.
PMID: 24744722 [PubMed]
Resting state functional magnetic resonance imaging in Parkinson's disease.
Curr Neurol Neurosci Rep. 2014 Jun;14(6):448
Authors: Prodoehl J, Burciu RG, Vaillancourt DE
Neuroimaging advances over the past several decades have provided increased understanding of the structural and functional brain changes that occur with Parkinson's disease (PD). Examination of resting state functional magnetic resonance imaging (rs-fMRI) provides a noninvasive method that focuses on low-frequency spontaneous fluctuations in the blood-oxygenation-level-dependent signal that occurs when an individual is at rest. Several analysis methods have been developed and used to explore how PD affects resting state activity and functional connectivity, and the purpose of this review is to highlight the critical advances made thus far. Some discrepancies in the rs-fMRI and PD literature exist, and we make recommendations for consideration in future studies. The rs-fMRI technique holds promise for investigating brain changes associated with the motor and nonmotor symptoms of PD, and for revealing important variations across large-scale networks of the brain in PD.
PMID: 24744021 [PubMed - in process]
Altered hypothalamic functional connectivity with autonomic circuits and the locus coeruleus in migraine.
PLoS One. 2014;9(4):e95508
Authors: Moulton EA, Becerra L, Johnson A, Burstein R, Borsook D
The hypothalamus has been implicated in migraine based on the manifestation of autonomic symptoms with the disease, as well as neuroimaging evidence of hypothalamic activation during attacks. Our objective was to determine functional connectivity (FC) changes between the hypothalamus and the rest of the brain in migraine patients vs. control subjects. This study uses fMRI (functional magnetic resonance imaging) to acquire resting state scans in 12 interictal migraine patients and 12 healthy matched controls. Hypothalamic connectivity seeds were anatomically defined based on high-resolution structural scans, and FC was assessed in the resting state scans. Migraine patients had increased hypothalamic FC with a number of brain regions involved in regulation of autonomic functions, including the locus coeruleus, caudate, parahippocampal gyrus, cerebellum, and the temporal pole. Stronger functional connections between the hypothalamus and brain areas that regulate sympathetic and parasympathetic functions may explain some of the hypothalamic-mediated autonomic symptoms that accompany or precede migraine attacks.
PMID: 24743801 [PubMed - in process]
Alterations in amplitude of low frequency fluctuation in treatment-naïve major depressive disorder measured with resting-state fMRI.
Hum Brain Mapp. 2014 Apr 17;
Authors: Liu J, Ren L, Womer FY, Wang J, Fan G, Jiang W, Blumberg HP, Tang Y, Xu K, Wang F
There are limited resting-state functional magnetic resonance imaging (fMRI) studies in major depressive disorder (MDD). Of these studies, functional connectivity analyses are mostly used. However, a new method based on the magnitude of low frequency fluctuation (LFF) during resting-state fMRI may provide important insight into MDD. In this study, we examined the amplitude of LFF (ALFF) within the whole brain during resting-state fMRI in 30 treatment-naïve MDD subjects and 30 healthy control (HC) subjects. When compared with HC, MDD subjects showed increased ALFF in the frontal cortex (including the bilateral ventral/dorsal anterior cingulate cortex, orbitofrontal cortex, premotor cortex, ventral prefrontal cortex, left dorsal lateral frontal cortex, left superior frontal cortex), basal ganglia (including the right putamen and left caudate nucleus), left insular cortex, right anterior entorhinal cortex and left inferior parietal cortex, together with decreased ALFF in the bilateral occipital cortex, cerebellum hemisphere, and right superior temporal cortex. These findings may relate to characteristics of MDD, such as excessive self-referential processing and deficits in cognitive control of emotional processing, which may contribute to the persistent and recurrent nature of the disorder. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
PMID: 24740815 [PubMed - as supplied by publisher]
Resting state functional connectivity of the basal nucleus of Meynert in humans: in comparison to the ventral striatum and the effects of age.
Neuroimage. 2014 Apr 12;
Authors: Li CS, Ide JS, Zhang S, Hu S, Chao HH, Zaborszky L
The basal nucleus of Meynert (BNM) provides the primary cholinergic inputs to the cerebral cortex. Loss of neurons in the BNM is linked to cognitive deficits in Alzheimer's disease and other degenerative conditions. Numerous animal studies described cholinergic and non-cholinergic neuronal responses in the BNM; however, work in humans has been hampered by the difficulty of defining the BNM anatomically. Here, on the basis of a previous study that delineated the BNM of post-mortem human brains in a standard stereotaxic space, we sought to examine functional connectivity of the BNM, as compared to the nucleus accumbens (or ventral striatum, VS), in a large resting state functional magnetic resonance imaging data set. The BNM and VS shared but also showed a distinct pattern of cortical and subcortical connectivity. Compared to the VS, the BNM showed stronger positive connectivity with the putamen, pallidum, thalamus, amygdala and midbrain, as well as the anterior cingulate cortex, supplementary motor area and pre-supplementary motor area, a network of brain regions that respond to salient stimuli and orchestrate motor behavior. In contrast, compared to the BNM, the VS showed stronger positive connectivity with the ventral caudate and medial orbitofrontal cortex, areas implicated in reward processing and motivated behavior. Furthermore, the BNM and VS each showed extensive negative connectivity with visual and lateral prefrontal cortices. Together, the distinct cerebral functional connectivities support the role of the BNM in arousal, saliency responses and cognitive motor control and the VS in reward related behavior. Considering the importance of BNM in age-related cognitive decline, we explored the effects of age on BNM and VS connectivities. BNM connectivity to the visual and somatomotor cortices decreases while connectivity to subcortical structures including the midbrain, thalamus, and pallidum increases with age. These findings of age-related changes of cerebral functional connectivity of the BNM may facilitate research of the neural bases of cognitive decline in health and illness.
PMID: 24736176 [PubMed - as supplied by publisher]
Brain stimulation and functional imaging with fMRI and PET.
Handb Clin Neurol. 2013;116:77-95
Authors: Ko JH, Tang CC, Eidelberg D
The use of functional brain imaging techniques, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), and functional magnetic resonance imaging (fMRI), has allowed for monitoring neuronal and neurochemical activities in the living human brain and identifying abnormal changes in various neurological and psychiatric diseases. Combining these methods with techniques such as deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS) has greatly advanced our understanding of the effects of such treatment on brain activity at targeted regions as well as specific disease-related networks. Indeed, recent network-level analysis focusing on inter-regional covarying activities in data interpretation has unveiled several key mechanisms underlying the therapeutic effects of brain stimulation. However, non-negligible discrepancies have been reported in the literature, attributable in part to the heterogeneity of both imaging and brain stimulation techniques. This chapter summarizes recent studies that combine brain imaging and brain stimulation, and includes discussion of future direction in these lines of research.
PMID: 24112887 [PubMed - indexed for MEDLINE]
Acupuncture modulates the functional connectivity of the default mode network in stroke patients.
Evid Based Complement Alternat Med. 2014;2014:765413
Authors: Zhang Y, Li K, Ren Y, Cui F, Xie Z, Shin JY, Tan Z, Tang L, Bai L, Zou Y
Abundant evidence from previous fMRI studies on acupuncture has revealed significant modulatory effects at widespread brain regions. However, few reports on the modulation to the default mode network (DMN) of stroke patients have been investigated in the field of acupuncture. To study the modulatory effects of acupuncture on the DMN of stroke patients, eight right hemispheric infarction and stable ischemic stroke patients and ten healthy subjects were recruited to undergo resting state fMRI scanning before and after acupuncture stimulation. Functional connectivity analysis was applied with the bilateral posterior cingulate cortices chosen as the seed regions. The main finding demonstrated that the interregional interactions between the ACC and PCC especially enhanced after acupuncture at GB34 in stroke patients, compared with healthy controls. The results indicated that the possible mechanisms of the modulatory effects of acupuncture on the DMN of stroke patients could be interpreted in terms of cognitive ability and motor function recovery.
PMID: 24734113 [PubMed]
Acupuncture Enhances Effective Connectivity between Cerebellum and Primary Sensorimotor Cortex in Patients with Stable Recovery Stroke.
Evid Based Complement Alternat Med. 2014;2014:603909
Authors: Xie Z, Cui F, Zou Y, Bai L
Recent neuroimaging studies have demonstrated that stimulation of acupuncture at motor-implicated acupoints modulates activities of brain areas relevant to the processing of motor functions. This study aims to investigate acupuncture-induced changes in effective connectivity among motor areas in hemiparetic stroke patients by using the multivariate Granger causal analysis. A total of 9 stable recovery stroke patients and 8 healthy controls were recruited and underwent three runs of fMRI scan: passive finger movements and resting state before and after manual acupuncture stimuli. Stroke patients showed significantly attenuated effective connectivity between cortical and subcortical areas during passive motor task, which indicates inefficient information transmissions between cortical and subcortical motor-related regions. Acupuncture at motor-implicated acupoints showed specific modulations of motor-related network in stroke patients relative to healthy control subjects. This specific modulation enhanced bidirectionally effective connectivity between the cerebellum and primary sensorimotor cortex in stroke patients, which may compensate for the attenuated effective connectivity between cortical and subcortical areas during passive motor task and, consequently, contribute to improvement of movement coordination and motor learning in subacute stroke patients. Our results suggested that further efficacy studies of acupuncture in motor recovery can focus on the improvement of movement coordination and motor learning during motor rehabilitation.
PMID: 24734108 [PubMed]
[Resting-state functional MRI research of the auditory cortex in patients with long-term unilateral hearing loss].
Zhonghua Yi Xue Za Zhi. 2014 Jan 21;94(3):167-70
Authors: Li J, Yang M, Liu B, Zhang G, Qian N
OBJECTIVE: To evaluate functional connectivity in patients with unilateral sensorineural hearing loss(USNHL) using resting-state fMRI.
METHODS: Functional connectivity MRI were employed in 29 patients with SNHL (15 left, 14 right) with averaged hearing level above 70 dB HL for the deaf ear, and matched 15 and 14 normal hearing subjects, respectively, were recruited. Functional connectivity mappings between the SNHL patients and normal hearing subjects were evaluated and the differences were contrasted.
RESULTS: The positive functional connectivity of auditory cortex with whole brain in USNHL patients is weaker than that in normal subjects both in volume and intensity. Using the affected side AIas a seed, left and right Laterality index(LI)of auditory cortex was 30.14, -31.25, respectively. Using the healthy side as a seed, the LI of auditory cortex was 0.1, 19.37, respectively. Compared to normal subjects, increased activation in bilateral precentral gyrus, left middle frontal gyrus, left superior frontal gyrus and posterior cingulate cortex/precuneus were found in left USNHL patients. Contrasted with normal subjects, no significant difference was found between the normal subjects and right SNHL patients, except the right caudate nucleus using left AIas a seed.
CONCLUSION: The reduced functional connectivity among the affected side and healthy side auditory cortex as well as associated auditory cortex may suggest a result of functional reorganization adaptive to the SNHL.
PMID: 24731454 [PubMed - in process]
Intensive virtual reality-based training for upper limb motor function in chronic stroke: a feasibility study using a single case experimental design and fMRI.
Disabil Rehabil Assist Technol. 2014 Apr 14;
Authors: Schuster-Amft C, Henneke A, Hartog-Keisker B, Holper L, Siekierka E, Chevrier E, Pyk P, Kollias S, Kiper D, Eng K
Abstract Purpose: To evaluate feasibility and neurophysiological changes after virtual reality (VR)-based training of upper limb (UL) movements. Method: Single-case A-B-A-design with two male stroke patients (P1:67 y and 50 y, 3.5 and 3 y after onset) with UL motor impairments, 45-min therapy sessions 5×/week over 4 weeks. Patients facing screen, used bimanual data gloves to control virtual arms. Three applications trained bimanual reaching, grasping, hand opening. Assessments during 2-week baseline, weekly during intervention, at 3-month follow-up (FU): Goal Attainment Scale (GAS), Chedoke Arm and Hand Activity Inventory (CAHAI), Chedoke-McMaster Stroke Assessment (CMSA), Extended Barthel Index (EBI), Motor Activity Log (MAL). Functional magnetic resonance imaging scans (FMRI) before, immediately after treatment and at FU. Results: P1 executed 5478 grasps (paretic arm). Improvements in CAHAI (+4) were maintained at FU. GAS changed to +1 post-test and +2 at FU. P2 executed 9835 grasps (paretic arm). CAHAI improvements (+13) were maintained at FU. GAS scores changed to -1 post-test and +1 at FU. MAL scores changed from 3.7 at pre-test to 5.5 post-test and 3.3 at FU. Conclusion: The VR-based intervention was feasible, safe, and intense. Adjustable application settings maintained training challenge and patient motivation. ADL-relevant UL functional improvements persisted at FU and were related to changed cortical activation patterns. Implications for Rehabilitation YouGrabber trains uni- and bimanual upper motor function. Its application is feasible, safe, and intense. The control of the virtual arms can be done in three main ways: (a) normal (b) virtual mirror therapy, or (c) virtual following. The mirroring feature provides an illusion of affected limb movements during the period when the affected upper limb (UL) is resting. The YouGrabber training led to ADL-relevant UL functional improvements that were still assessable 12 weeks after intervention finalization and were related to changed cortical activation patterns.
PMID: 24730659 [PubMed - as supplied by publisher]
Estimation of resting-state functional connectivity using random subspace based partial correlation: a novel method for reducing global artifacts.
Neuroimage. 2013 Nov 15;82:87-100
Authors: Chen T, Ryali S, Qin S, Menon V
Intrinsic functional connectivity analysis using resting-state functional magnetic resonance imaging (rsfMRI) has become a powerful tool for examining brain functional organization. Global artifacts such as physiological noise pose a significant problem in estimation of intrinsic functional connectivity. Here we develop and test a novel random subspace method for functional connectivity (RSMFC) that effectively removes global artifacts in rsfMRI data. RSMFC estimates the partial correlation between a seed region and each target brain voxel using multiple subsets of voxels sampled randomly across the whole brain. We evaluated RSMFC on both simulated and experimental rsfMRI data and compared its performance with standard methods that rely on global mean regression (GSReg) which are widely used to remove global artifacts. Using extensive simulations we demonstrate that RSMFC is effective in removing global artifacts in rsfMRI data. Critically, using a novel simulated dataset we demonstrate that, unlike GSReg, RSMFC does not artificially introduce anti-correlations between inherently uncorrelated networks, a result of paramount importance for reliably estimating functional connectivity. Furthermore, we show that the overall sensitivity, specificity and accuracy of RSMFC are superior to GSReg. Analysis of posterior cingulate cortex connectivity in experimental rsfMRI data from 22 healthy adults revealed strong functional connectivity in the default mode network, including more reliable identification of connectivity with left and right medial temporal lobe regions that were missed by GSReg. Notably, compared to GSReg, negative correlations with lateral fronto-parietal regions were significantly weaker in RSMFC. Our results suggest that RSMFC is an effective method for minimizing the effects of global artifacts and artificial negative correlations, while accurately recovering intrinsic functional brain networks.
PMID: 23747287 [PubMed - indexed for MEDLINE]
The Spectral Diversity of Resting-State Fluctuations in the Human Brain.
PLoS One. 2014;9(4):e93375
Authors: Kalcher K, Boubela RN, Huf W, Bartova L, Kronnerwetter C, Derntl B, Pezawas L, Filzmoser P, Nasel C, Moser E
In order to assess whole-brain resting-state fluctuations at a wide range of frequencies, resting-state fMRI data of 20 healthy subjects were acquired using a multiband EPI sequence with a low TR (354 ms) and compared to 20 resting-state datasets from standard, high-TR (1800 ms) EPI scans. The spatial distribution of fluctuations in various frequency ranges are analyzed along with the spectra of the time-series in voxels from different regions of interest. Functional connectivity specific to different frequency ranges (<0.1 Hz; 0.1-0.25 Hz; 0.25-0.75 Hz; 0.75-1.4 Hz) was computed for both the low-TR and (for the two lower-frequency ranges) the high-TR datasets using bandpass filters. In the low-TR data, cortical regions exhibited highest contribution of low-frequency fluctuations and the most marked low-frequency peak in the spectrum, while the time courses in subcortical grey matter regions as well as the insula were strongly contaminated by high-frequency signals. White matter and CSF regions had highest contribution of high-frequency fluctuations and a mostly flat power spectrum. In the high-TR data, the basic patterns of the low-TR data can be recognized, but the high-frequency proportions of the signal fluctuations are folded into the low frequency range, thus obfuscating the low-frequency dynamics. Regions with higher proportion of high-frequency oscillations in the low-TR data showed flatter power spectra in the high-TR data due to aliasing of the high-frequency signal components, leading to loss of specificity in the signal from these regions in high-TR data. Functional connectivity analyses showed that there are correlations between resting-state signal fluctuations of distant brain regions even at high frequencies, which can be measured using low-TR fMRI. On the other hand, in the high-TR data, loss of specificity of measured fluctuations leads to lower sensitivity in detecting functional connectivity. This underlines the advantages of low-TR EPI sequences for resting-state and potentially also task-related fMRI experiments.
PMID: 24728207 [PubMed - as supplied by publisher]
Connectomics signatures of prenatal cocaine exposure affected adolescent brains.
Hum Brain Mapp. 2013 Oct;34(10):2494-510
Authors: Li K, Zhu D, Guo L, Li Z, Lynch ME, Coles C, Hu X, Liu T
Recent in vivo neuroimaging studies revealed that several brain networks are altered in prenatal cocaine exposure (PCE) affected adolescent brains. However, due to a lack of dense and corresponding cortical landmarks across individuals, the systematical alterations of functional connectivities in large-scale brain networks and the alteration of structural brain architecture in PCE affected brain are largely unknown. In this article, we adopted a newly developed data-driven strategy to build a large set of cortical landmarks that are consistent and corresponding across PCE adolescents and their matched controls. Based on these landmarks, we constructed large-scale functional connectomes and applied the well-established approaches of deriving genomics signatures in genome-wide gene expression studies to discover functional connectomics signatures for the characterization of PCE adolescent brains. Results derived from experimental data demonstrated that 10 structurally disrupted landmarks were identified in PCE, and more importantly, the discovered informative functional connectomics signatures among consistent landmarks distinctively differentiate PCE brains from their matched controls.
PMID: 22461404 [PubMed - indexed for MEDLINE]