Brain modifications after acute alcohol consumption analyzed by resting state fMRI.
Magn Reson Imaging. 2013 May 13;
Authors: Spagnolli F, Cerini R, Cardobi N, Barillari M, Manganotti P, Storti S, Mucelli RP
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.
PMID: 23680187 [PubMed - as supplied by publisher]
Reduced functional connectivity and asymmetry of the planum temporale in patients with schizophrenia and first-degree relatives.
Schizophr Res. 2013 May 12;
Authors: Oertel-Knöchel V, Knöchel C, Matura S, Prvulovic D, Linden DE, van de Ven V
The planum temporale (PT) is a highly lateralized brain area associated with auditory and language processing. In schizophrenia, reduced structural and functional laterality of the PT has been suggested, which is of clinical interest because of its potential role in the generation of auditory verbal hallucinations. We investigated whether resting-state functional imaging (fMRI) of the PT reveals aberrant functional connectivity and laterality in patients with schizophrenia (SZ) and unaffected relatives, and examined possible associations between altered intrinsic functional organization of auditory networks and hallucinations. We estimated functional connectivity between bilateral PT and whole-brain in 24 SZ patients, 22 unaffected first-degree relatives and 24 matched healthy controls. The results indicated reduced functional connectivity between PT and temporal, parietal, limbic and subcortical regions in SZ patients and relatives in comparison with controls. Altered functional connectivity correlated with predisposition towards hallucinations (measured with the Revised Hallucination Scale [RHS]) in both patients and relatives. We also observed reduced functional asymmetry of the superior temporal gyrus in patients and relatives, which correlated significantly with acute severity of hallucinations in the patient group. To conclude, SZ patients and relatives showed abnormal asymmetry and aberrant connectivity in the planum temporale during resting-state, which was related to psychopathology. These results are in line with results from auditory processing and symptom-mapping studies that suggest that the PT is a central node in the generation of hallucinations. Our findings support reduced intrinsic functional hemispheric asymmetry of the auditory network as a possible trait marker in schizophrenia.
PMID: 23672819 [PubMed - as supplied by publisher]
Combining Classification with fMRI-Derived Complex Network Measures for Potential Neurodiagnostics.
PLoS One. 2013;8(5):e62867
Authors: Fekete T, Wilf M, Rubin D, Edelman S, Malach R, Mujica-Parodi LR
Complex network analysis (CNA), a subset of graph theory, is an emerging approach to the analysis of functional connectivity in the brain, allowing quantitative assessment of network properties such as functional segregation, integration, resilience, and centrality. Here, we show how a classification framework complements complex network analysis by providing an efficient and objective means of selecting the best network model characterizing given functional connectivity data. We describe a novel kernel-sum learning approach, block diagonal optimization (BDopt), which can be applied to CNA features to single out graph-theoretic characteristics and/or anatomical regions of interest underlying discrimination, while mitigating problems of multiple comparisons. As a proof of concept for the method's applicability to future neurodiagnostics, we apply BDopt classification to two resting state fMRI data sets: a trait (between-subjects) classification of patients with schizophrenia vs. controls, and a state (within-subjects) classification of wake vs. sleep, demonstrating powerful discriminant accuracy for the proposed framework.
PMID: 23671641 [PubMed - in process]
Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients.
Hum Brain Mapp. 2013 May 14;
Authors: Li X, Zhu D, Jiang X, Jin C, Zhang X, Guo L, Zhang J, Hu X, Li L, Liu T
Functional connectomes (FCs) have been recently shown to be powerful in characterizing brain conditions. However, many previous studies assumed temporal stationarity of FCs, while their temporal dynamics are rarely explored. Here, based on the structural connectomes constructed from diffusion tensor imaging data, FCs are derived from resting-state fMRI (R-fMRI) data and are then temporally divided into quasi-stable segments via a sliding time window approach. After integrating and pooling over a large number of those temporally quasi-stable FC segments from 44 post-traumatic stress disorder (PTSD) patients and 51 healthy controls, common FC (CFC) patterns are derived via effective dictionary learning and sparse coding algorithms. It is found that there are 16 CFC patterns that are reproducible across healthy controls, and interestingly, two additional CFC patterns with altered connectivity patterns [termed signature FC (SFC) here] exist dominantly in PTSD subjects. These two SFC patterns alone can successfully differentiate 80% of PTSD subjects from healthy controls with only 2% false positive. Furthermore, the temporal transition dynamics of CFC patterns in PTSD subjects are substantially different from those in healthy controls. These results have been replicated in separate testing datasets, suggesting that dynamic functional connectomics signatures can effectively characterize and differentiate PTSD patients. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.
PMID: 23671011 [PubMed - as supplied by publisher]
Assessing the function of the fronto-parietal attention network: Insights from resting-state fMRI and the attentional network test.
Hum Brain Mapp. 2013 May 14;
Authors: Markett S, Reuter M, Montag C, Voigt G, Lachmann B, Rudorf S, Elger CE, Weber B
In the recent past, various intrinsic connectivity networks (ICN) have been identified in the resting brain. It has been hypothesized that the fronto-parietal ICN is involved in attentional processes. Evidence for this claim stems from task-related activation studies that show a joint activation of the implicated brain regions during tasks that require sustained attention. In this study, we used functional magnetic resonance imaging (fMRI) to demonstrate that functional connectivity within the fronto-parietal network at rest directly relates to attention. We applied graph theory to functional connectivity data from multiple regions of interest and tested for associations with behavioral measures of attention as provided by the attentional network test (ANT), which we acquired in a separate session outside the MRI environment. We found robust statistical associations with centrality measures of global and local connectivity of nodes within the network with the alerting and executive control subfunctions of attention. The results provide further evidence for the functional significance of ICN and the hypothesized role of the fronto-parietal attention network. Hum Brain Mapp , 2013. © 2013 Wiley Periodicals, Inc.
PMID: 23670989 [PubMed - as supplied by publisher]
Selectively and progressively disrupted structural connectivity of functional brain networks in Alzheimer's disease - revealed by a novel framework to analyze edge distributions of networks detecting disruptions with strong statistical evidence.
Neuroimage. 2013 May 10;
Authors: Hahn K, Myers N, Prigarin S, Rodenacker K, Kurz A, Förstl H, Zimmer C, Wohlschläger AM, Sorg C
Alzheimer's disease (AD) disrupts selectively and progressively (increasing with severity) functional connectivity of intrinsic brain networks (IBN), most prominent in the default mode network. Given that IBNs' functional connectivity depends on structural connectivity, we hypothesize for our study selective and progressive changes of IBN based structural connectivity in AD. To achieve strong statistical evidence, we introduce a novel statistical method based on the edge frequency distributions of structural connectivity networks. Such non-Gaussian distributions are compared in a multiple testing scheme, combining a flexible nonparametric test statistic with permutation based strong control of the family wise error rate. We assessed 26 healthy elderly, 23 patients with AD-dementia, and 28 patients with mild cognitive impairment (MCI) by resting-state functional MRI, diffusion tensor imaging, and clinical-neuropsychological testing including annual follow-up assessment. After 3years, 50% of the patients with MCI converted to AD. Tractography of diffusion tensor data identifies structural connectivity networks between regions of IBNs, which are detected by an independent component analysis of resting state fMRI data. We find that IBNs' structural connectivity is selectively and progressively disrupted with primary changes in the default mode network. Correspondent results are found for IBNs' functional connectivity. In addition, structural connectivity across the nodes of all IBNs separated individual MCI patients converting to AD from non-converters. Conclusively, our study provides a new approach to analyze connectivity networks by their non-Gaussian edge frequency distributions and achieves strong statistical evidence by application of the family wise error rate. Data analysis provides selective and progressive disruptions of IBN`s structural connectivity in AD and demonstrates the increased power of our method compared to recent studies.
PMID: 23668966 [PubMed - as supplied by publisher]
[Neuroimaging in epilepsy].
Brain Nerve. 2013 May;65(5):573-81
Authors: Yamao Y, Kunieda T, Kikuchi T, Matsuhashi M, Sawamoto N, Matsumoto R, Okada T, Miyamoto S, Ikeda A
Abstract It is now recommended that magnetic resonance imaging (MRI) or computed tomography (CT) be carried out in all patients with at least partial- and hopefully also generalized epilepsy to help identify intracranial lesions, such as hippocampal sclerosis, focal cortical dysplasia, brain tumor, cavernous malformation, and arteriovenous malformation. In order to identify epileptic focus, other neuroimaging tools, such as positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetoencephalography (MEG), are also useful, because an epileptogenic area is not necessarily located within these intracranial lesions. With regard to epilepsy surgery, neuroimaging is also required for the identification of functionally essential cortices, such as motor and language areas. MEG and functional MRI are noninvasively, and tractography with diffusion-weighted imaging (DWI) is also useful for visualizing relevant white matter tracts. Recently, it has been reported that the cortico-cortical network plays an important role in preservation of brain function. Thus, cortico-cortical evoked potentials (CCEP) and resting state fMRI are candidate methods to help clarify brain network. While good seizure control is an important treatment outcome for patients with intractable partial epilepsy, the preservation of brain function is equally important. For this reason, further development and clinical application of sophisticated imaging technique are required.
PMID: 23667122 [PubMed - in process]
Inferring Group-Wise Consistent Multimodal Brain Networks via Multi-View Spectral Clustering.
IEEE Trans Med Imaging. 2013 May 2;
Authors: Chen H, Li K, Zhu D, Jiang X, Yuan Y, Lv P, Zhang T, Guo L, Shen D, Liu T
Quantitative modeling and analysis of structural and functional brain networks based on diffusion tensor imaging (DTI) and functional MRI (fMRI) data have received extensive interest recently. However, the regularity of these structural and functional brain networks across multiple neuroimaging modalities and also across different individuals is largely unknown. This paper presents a novel approach to inferring group-wise consistent brain sub-networks from multimodal DTI/resting-state fMRI datasets via multi-view spectral clustering of cortical networks, which were constructed upon our recently developed and validated large-scale cortical landmarks - DICCCOL (Dense Individualized and Common Connectivity-based Cortical Landmarks). We applied the algorithms on DTI data of 100 healthy young females and 50 healthy young males, obtained consistent multimodal brain networks within and across multiple groups, and further examined the functional roles of these networks. Our experimental results demonstrated that the derived brain networks have substantially improved inter-modality and inter-subject consistency.
PMID: 23661312 [PubMed - as supplied by publisher]
Independent Sources of Spontaneous BOLD Fluctuation Along the Visual Pathway.
Brain Topogr. 2013 May 10;
Authors: de Zwart JA, van Gelderen P, Liu Z, Duyn JH
In resting-state functional magnetic resonance imaging (fMRI) experiments, correlation analysis can be used to identify clusters of cortical regions that may be functionally connected. Although such functional connectivity is often assumed to reflect cortico-cortical connections, a potential confound is the contribution of subcortical brain regions, many of which have strong anatomical connectivity to cortical regions and may also enable cortico-cortical interactions through trans-thalamic pathways. To investigate this, we performed resting state fMRI of the human visual system, including cortical regions and subcortical nuclei of the pulvinar and lateral geniculate. Regression analysis was used to investigate the dependence of the measured inter-regional correlations upon afferents from specific retinal, thalamic and cortical regions as well as systemic global signal fluctuation. A high level of inter-hemispheric correlation (cc = 0.95) was found in the visual cortex that could not be explained by activity in the subcortical nuclei investigated; in addition a relatively low level of inter-hemispheric correlation (cc = 0.39-0.42) was found in vision-related thalamic nuclei that could not be explained by direct anatomical connections or their cortical inputs. These findings suggest that spontaneous fMRI signal correlations within the human visual system originate from a mixture of independent signal sources that may be transmitted through thalamo-cortical, cortico-thalamic, and cortico-cortical connections either trans-callosal or trans-thalamic in origin. Our findings thus call for more cautious interpretation of resting state functional connectivity in terms of any single type of anatomical connectivity.
PMID: 23660870 [PubMed - as supplied by publisher]
On the origins of signal variance in FMRI of the human midbrain at high field.
PLoS One. 2013;8(4):e62708
Authors: Barry RL, Coaster M, Rogers BP, Newton AT, Moore J, Anderson AW, Zald DH, Gore JC
Functional Magnetic Resonance Imaging (fMRI) in the midbrain at 7 Tesla suffers from unexpectedly low temporal signal to noise ratio (TSNR) compared to other brain regions. Various methodologies were used in this study to quantitatively identify causes of the noise and signal differences in midbrain fMRI data. The influence of physiological noise sources was examined using RETROICOR, phase regression analysis, and power spectral analyses of contributions in the respiratory and cardiac frequency ranges. The impact of between-shot phase shifts in 3-D multi-shot sequences was tested using a one-dimensional (1-D) phase navigator approach. Additionally, the effects of shared noise influences between regions that were temporally, but not functionally, correlated with the midbrain (adjacent white matter and anterior cerebellum) were investigated via analyses with regressors of 'no interest'. These attempts to reduce noise did not improve the overall TSNR in the midbrain. In addition, the steady state signal and noise were measured in the midbrain and the visual cortex for resting state data. We observed comparable steady state signals from both the midbrain and the cortex. However, the noise was 2-3 times higher in the midbrain relative to the cortex, confirming that the low TSNR in the midbrain was not due to low signal but rather a result of large signal variance. These temporal variations did not behave as known physiological or other noise sources, and were not mitigated by conventional strategies. Upon further investigation, resting state functional connectivity analysis in the midbrain showed strong intrinsic fluctuations between homologous midbrain regions. These data suggest that the low TSNR in the midbrain may originate from larger signal fluctuations arising from functional connectivity compared to cortex, rather than simply reflecting physiological noise.
PMID: 23658643 [PubMed - in process]
Mitochondrial functional state impacts spontaneous neocortical activity and resting state FMRI.
PLoS One. 2013;8(5):e63317
Authors: Sanganahalli BG, Herman P, Hyder F, Kannurpatti SS
Mitochondrial Ca(2+) uptake, central to neural metabolism and function, is diminished in aging whereas enhanced after acute/sub-acute traumatic brain injury. To develop relevant translational models for these neuropathologies, we determined the impact of perturbed mitochondrial Ca(2+) uptake capacities on intrinsic brain activity using clinically relevant markers. From a multi-compartment estimate of probable baseline Ca(2+) ranges in the brain, we hypothesized that reduced or enhanced mitochondrial Ca(2+) uptake capacity would decrease or increase spontaneous neuronal activity respectively. As resting state fMRI-BOLD fluctuations and stimulus-evoked BOLD responses have similar physiological origins  and stimulus-evoked neuronal and hemodynamic responses are modulated by mitochondrial Ca(2+) uptake capacity ,  respectively, we tested our hypothesis by measuring hemodynamic fluctuations and spontaneous neuronal activities during normal and altered mitochondrial functional states. Mitochondrial Ca(2+) uptake capacity was perturbed by pharmacologically inhibiting or enhancing the mitochondrial Ca(2+) uniporter (mCU) activity. Neuronal electrical activity and cerebral blood flow (CBF) fluctuations were measured simultaneously and integrated with fMRI-BOLD fluctuations at 11.7T. mCU inhibition reduced spontaneous neuronal activity and the resting state functional connectivity (RSFC), whereas mCU enhancement increased spontaneous neuronal activity but reduced RSFC. We conclude that increased or decreased mitochondrial Ca(2+) uptake capacities lead to diminished resting state modes of brain functional connectivity.
PMID: 23650561 [PubMed - in process]
Task-free functional MRI in cervical dystonia reveals multi-network changes that partially normalize with botulinum toxin.
PLoS One. 2013;8(5):e62877
Authors: Delnooz CC, Pasman JW, Beckmann CF, van de Warrenburg BP
Cervical dystonia is characterized by involuntary, abnormal movements and postures of the head and neck. Current views on its pathophysiology, such as faulty sensorimotor integration and impaired motor planning, are largely based on studies of focal hand dystonia. Using resting state fMRI, we explored whether cervical dystonia patients have altered functional brain connectivity compared to healthy controls, by investigating 10 resting state networks. Scans were repeated immediately before and some weeks after botulinum toxin injections to see whether connectivity abnormalities were restored. We here show that cervical dystonia patients have reduced connectivity in selected regions of the prefrontal cortex, premotor cortex and superior parietal lobule within a distributed network that comprises the premotor cortex, supplementary motor area, primary sensorimotor cortex, and secondary somatosensory cortex (sensorimotor network). With regard to a network originating from the occipital cortex (primary visual network), selected regions in the prefrontal and premotor cortex, superior parietal lobule, and middle temporal gyrus areas have reduced connectivity. In selected regions of the prefrontal, premotor, primary motor and early visual cortex increased connectivity was found within a network that comprises the prefrontal cortex including the anterior cingulate cortex and parietal cortex (executive control network). Botulinum toxin treatment resulted in a partial restoration of connectivity abnormalities in the sensorimotor and primary visual network. These findings demonstrate the involvement of multiple neural networks in cervical dystonia. The reduced connectivity within the sensorimotor and primary visual networks may provide the neural substrate to expect defective motor planning and disturbed spatial cognition. Increased connectivity within the executive control network suggests excessive attentional control and while this may be a primary trait, perhaps contributing to abnormal motor control, this may alternatively serve a compensatory function in order to reduce the consequences of the motor planning defect inflicted by the other network abnormalities.
PMID: 23650536 [PubMed - in process]
Functional Bimodality in the Brain Networks of Preterm and Term Human Newborns.
Cereb Cortex. 2013 May 5;
Authors: Omidvarnia A, Fransson P, Metsäranta M, Vanhatalo S
The spontaneous brain activity exhibits long-range spatial correlations detected using functional magnetic resonance imaging (fMRI) signals in newborns when (1) long neuronal pathways are still developing, and (2) the electrical brain activity consists of developmentally unique, intermittent events believed to guide activity-dependent brain wiring. We studied this spontaneous electrical brain activity using multichannel electroencephalography (EEG) of premature and fullterm babies during sleep to assess the development of spatial integration during last months of gestation. Correlations of frequency-specific amplitudes were found to follow a robust bimodality: During low amplitudes (low mode), brain activity exhibited very weak spatial correlations. In contrast, the developmentally essential high-amplitude events (high mode) showed strong spatial correlations. There were no clear spatial patterns in the early preterm, but clear frontal and parieto-occipital modules at term age. A significant fronto-occipital gradient was also seen in the development of the graph measure clustering coefficient. Strikingly, no bimodality was found in the fMRI recordings of the fullterm babies, suggesting that early EEG activity and fMRI signal reflect different mechanisms of spatial coordination. The results are compatible with the idea that early developing human brain exhibits intermittent long-range spatial connections that likely provide the endogenous guidance for early activity-dependent development of brain networks.
PMID: 23650289 [PubMed - as supplied by publisher]
A Pilot Functional MRI Study of the Effects of Prefrontal rTMS on Pain Perception.
Pain Med. 2013 May 3;
Authors: Martin L, Borckardt JJ, Reeves ST, Frohman H, Beam W, Nahas Z, Johnson K, Younger J, Madan A, Patterson D, George M
OBJECTIVE.: Repetitive transcranial magnetic stimulation (rTMS) has been shown to effectively treat depression, and its potential value in pain management is emphasized by recent studies. Transcranial magnetic stimulation (TMS)-evoked activity in the prefrontal cortex may be associated with corticolimbic inhibitory circuits capable of decreasing pain perception. The present exploratory pilot study used functional magnetic resonance imaging (fMRI) to examine the effects of left prefrontal rTMS on brain activity and pain perception. DESIGN AND INTERVENTION.: Twenty-three healthy adults with no history of depression or chronic pain underwent an 8-minute thermal pain protocol with fMRI before and after a single rTMS session. Participants received 15 minutes of either real (N = 12) or sham (N = 11) 10 Hz rTMS over the left prefrontal cortex (110% of resting motor threshold; 5 seconds on, 10 seconds off). RESULTS.: TMS was associated with a 13.30% decrease in pain ratings, while sham was associated with an 8.61% decrease (P = 0.04). TMS was uniquely associated with increased activity in the posterior cingulate gyrus, precuneous, right superior frontal gyrus, right insula, and bilateral postcentral gyrus. Activity in the right superior prefrontal gyrus was negatively correlated with pain ratings (r = -0.65, P = 0.02) in the real TMS group. CONCLUSIONS.: Findings suggest that prefrontal rTMS may be capable of activating inhibitory circuits involved with pain reduction.
PMID: 23647651 [PubMed - as supplied by publisher]
Tool Selectivity in Left Occipitotemporal Cortex Develops without Vision.
J Cogn Neurosci. 2013 May 6;
Authors: Peelen MV, Bracci S, Lu X, He C, Caramazza A, Bi Y
Previous studies have provided evidence for a tool-selective region in left lateral occipitotemporal cortex (LOTC). This region responds selectively to pictures of tools and to characteristic visual tool motion. The present human fMRI study tested whether visual experience is required for the development of tool-selective responses in left LOTC. Words referring to tools, animals, and nonmanipulable objects were presented auditorily to 14 congenitally blind and 16 sighted participants. Sighted participants additionally viewed pictures of these objects. In whole-brain group analyses, sighted participants showed tool-selective activity in left LOTC in both visual and auditory tasks. Importantly, virtually identical tool-selective LOTC activity was found in the congenitally blind group performing the auditory task. Furthermore, both groups showed equally strong tool-selective activity for auditory stimuli in a tool-selective LOTC region defined by the picture-viewing task in the sighted group. Detailed analyses in individual participants showed significant tool-selective LOTC activity in 13 of 14 blind participants and 14 of 16 sighted participants. The strength and anatomical location of this activity were indistinguishable across groups. Finally, both blind and sighted groups showed significant resting state functional connectivity between left LOTC and a bilateral frontoparietal network. Together, these results indicate that tool-selective activity in left LOTC develops without ever having seen a tool or its motion. This finding puts constraints on the possible role that this region could have in tool processing and, more generally, provides new insights into the principles shaping the functional organization of OTC.
PMID: 23647514 [PubMed - as supplied by publisher]
Functional Connectivity and Brain Activation: A Synergistic Approach.
Cereb Cortex. 2013 May 3;
Authors: Tomasi D, Wang R, Wang GJ, Volkow ND
Traditional functional magnetic resonance imaging (fMRI) studies exploit endogenous brain activity for mapping brain activation during "periodic" cognitive/emotional challenges or brain functional connectivity during the "resting state". Previous studies demonstrated that these approaches provide a limited view of brain function which can be complemented by each other. We hypothesized that graph theory functional connectivity density (FCD) mapping would demonstrate regional FCD decreases between resting-state scan and a continuous "task-state" scan. Forty-five healthy volunteers underwent functional connectivity MRI during resting-state as well as a continuous visual attention task, and standard fMRI with a blocked version of the visual attention task. High-resolution data-driven FCD mapping was used to measure task-related connectivity changes without a priori hypotheses. Results demonstrate that task performance was associated with FCD decreases in brain regions weakly activated/deactivated by the task. Furthermore, a pronounced negative correlation between blood oxygen level-dependent-fMRI activation and task-related FCD decreases emerged across brain regions that also suggest the disconnection of task-irrelevant networks during task performance. The correlation between improved accuracy and stronger FCD decreases further suggests the disconnection of task-irrelevant networks during task performance. Functional connectivity can potentiate traditional fMRI studies and offer a more complete picture of brain function.
PMID: 23645721 [PubMed - as supplied by publisher]
Utility of resting fMRI and connectivity in patients with brain tumor.
Neurol India. 2013 Mar-Apr;61(2):144-51
Authors: Manglore S, Bharath RD, Panda R, George L, Thamodharan A, Gupta AK
Background: Resting state (task independent) Functional Magnetic Resonance Imaging (fMRI) has opened a new avenue in cognitive studies and has found practical clinical applications. Materials and Methods: Resting fMRI analysis was performed in six patients with brain tumor in the motor cortex. For comparison, task-related mapping of the motor cortex was done. Connectivity analysis to study the connections and strength of the connections between the primary motor cortex, premotor cortex, and primary somatosensory cortex on the affected side was also performed and compared with the contralateral normal side and the controls. Results: Resting fMRI in patients with brain tumor in the motor cortex mapped the motor cortex in a task-free state and the results were comparable to the motor task paradigm. Decreased connectivity on the tumor-affected side was observed, as compared to the unaffected side. Conclusion: Resting fMRI and connectivity analysis are useful in the presurgical evaluation of patients with brain tumors and may help in uncooperative or pediatric patients. They can also prognosticate the postoperative outcome. This method also has significant applications due to the ease of image acquisition.
PMID: 23644313 [PubMed - in process]
Spontaneous brain activity in combat related PTSD.
Neurosci Lett. 2013 May 2;
Authors: Yan X, Brown AD, Lazar M, Cressman VL, Henn-Haase C, Neylan TC, Shalev A, Wolkowitz OM, Hamilton SP, Yehuda R, Sodickson DK, Weiner MW, Marmar CR
Posttraumatic stress disorder (PTSD) is a prevalent psychiatric disorder, especially in combat veterans. Existing functional neuroimaging studies have provided important insights into the neural mechanisms of PTSD using various experimental paradigms involving trauma recollection or other forms of emotion provocation. However it is not clear whether the abnormal brain activity is specific to the mental processes related to the experimental tasks or reflects general patterns across different brain states. Thus, studying intrinsic spontaneous brain activity without the influence of external tasks may provide valuable alternative perspectives to further understand the neural characteristics of PTSD. The present study evaluated the magnitudes of spontaneous brain activity of male US veterans with or without PTSD, with the two groups matched on age, gender, and ethnicity. Amplitudes of low frequency fluctuation (ALFF), a data driven analysis method, were calculated on each voxel of the resting state fMRI data to measure the magnitudes of spontaneous brain activity. Results revealed that PTSD subjects showed increased spontaneous activity in the amygdala, ventral anterior cingulate cortex, insula, and orbital frontal cortex, as well as decreased spontaneous activity in the precuneus, dorsal lateral prefrontal cortex and thalamus. Within the PTSD group, larger magnitudes of spontaneous activity in the thalamus, precuneus and dorsal lateral prefrontal cortex were associated with lower re-experiencing symptoms. Comparing our results with previous functional neuroimaging findings, increased activity of the amygdala and anterior insula and decreased activity of the thalamus are consistent patterns across emotion provocation states and the resting state.
PMID: 23643995 [PubMed - as supplied by publisher]
Spatio-temporal Granger causality: A new framework.
Neuroimage. 2013 May 2;
Authors: Luo Q, Lu W, Cheng W, Valdes-Sosa PA, Wen X, Ding M, Feng J
That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data.
PMID: 23643924 [PubMed - as supplied by publisher]
Decreased functional connectivity of the amygdala in Alzheimer's disease revealed by resting-state fMRI.
Eur J Radiol. 2013 May 2;
Authors: Yao H, Liu Y, Zhou B, Zhang Z, An N, Wang P, Wang L, Zhang X, Jiang T
Alzheimer's disease (AD), the most common cause of dementia, is thought to be a progressive neurodegenerative disease that is clinically characterised by a decline of memory and other cognitive functions. Mild cognitive impairment (MCI) is considered to be the prodromal stage of AD. However, the relationship between AD and MCI and the development process remains unclear. The amygdala is one of the most vulnerable structures in the early stages of AD. To our knowledge, this is the first report on the alteration of the functional connectivity of the amygdala in AD and MCI subjects. We hypothesised that the amygdala-cortical loop is impaired in AD and that these alterations relate to the disease severity. In our study, we used resting-state functional MRIs to investigate the altered amygdala connectivity patterns in 35 AD patients, 27 MCI patients and 27 age- and gender-matched normal controls (NC). Compared with the NC, the decreased functional connectivity found in the AD patients was mainly located between the amygdala and the regions that are included in the default mode, context conditioning and extinction networks. Importantly, the decreased functional connectivity between the amygdala and some of the identified regions was positively correlated with MMSE, which indicated that the cognitive function impairment is related to an altered functional connectivity pattern.
PMID: 23643516 [PubMed - as supplied by publisher]