A Bayesian Double Fusion Model for Resting State Brain Connectivity Using Joint Functional and Structural Data.
Brain Connect. 2017 Mar 19;:
Authors: Kang H, Ombao H, Fonnesbeck C, Ding Z, Morgan VL
Current approaches separately analyze concurrently acquired diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) data. The primary limitation of these approaches is that they do not take advantage of the information from DTI that could potentially enhance estimation of resting state functional connectivity (FC) between brain regions. To overcome this limitation, we develop a Bayesian hierarchical spatio-temporal model that incorporates structural connectivity into estimating FC. In our proposed approach, structural connectivity (SC) based on DTI data is used to construct an informative prior for functional connectivity based on resting state fMRI data via the Cholesky decomposition. Simulation studies showed that incorporating the two data produced significantly reduced mean squared errors compared to the standard approach of separately analyzing the two data from different modalities. We applied our model to analyze the resting state DTI and fMRI data collected to estimate FC between the brain regions that were hypothetically important in the origination and spread of temporal lobe epilepsy seizures. Our analysis concludes that the proposed model achieves smaller false positive rates and is much robust to data decimation compared to the conventional approach.
PMID: 28316255 [PubMed - as supplied by publisher]
Assessing the Impact of Post Traumatic Stress Symptoms on Resting State Function Networks in a Military Chronic Mild Traumatic Brain Injury Sample.
Brain Connect. 2017 Mar 19;:
Authors: Nathan DE, Bellgowan JF, French LM, Wolf JP, Oakes T, Mielke JB, Sham EB, Liu W, Riedy G
The relationship between post traumatic stress disorder (PTSD) and chronic symptoms of mild traumatic brain injury (mTBI) is difficult to discern and poorly understood. An accurate differential diagnosis, assessment and treatment of mTBI and PTSD is challenging due to significant symptom overlap and the absence of clearly established biomarkers. The objective of this work is to examine how post traumatic stress influences task-free brain networks in chronic mTBI subjects. Control subjects (N=44) were compared with chronic mTBI subjects with low (N=58, PCLC total<30), medium (N=124, PCLC total = 31-49) and high (N=105, PCLC total ≥ 60) post traumatic stress symptoms (PTSS). The results indicate significant differences in Brodmann area 10 for all mTBI subject groups, indicating potential mTBI related disruptions with regulation of emotions and decision-making. The effects of PTSS were observed in the anterior cingulate, and parahippocampus suggesting possible disruptions pertaining to memory regulation, encoding and retrieval. The overall results indicate the presence of aberrant connectivity patterns between controls and chronic mTBI subjects with low, medium and high PTSS. Furthermore, the findings suggest a disruption in attention relating to a network of brain regions involved with emotional regulation and memory coding, rather than a fear related response. Taken together, the results suggest these regions form a network that could be a target for future research pertaining to PTSD and chronic mTBI. Furthermore, the use of clinical measures, task based imaging studies or multimodal imaging could help further elucidate specific neural correlates of PTSS and mTBI.
PMID: 28316248 [PubMed - as supplied by publisher]
Single or Multi-Frequency Generators in on-going brain activity: a mechanistic whole-brain model of empirical MEG data.
Neuroimage. 2017 Mar 14;:
Authors: Deco G, Cabral J, Woolrich MW, Stevner AB, van Hartevelt TJ, Kringelbach ML
During rest, envelopes of band-limited on-going MEG signals co-vary across the brain in consistent patterns, which have been related to resting-state networks measured with fMRI. To investigate the genesis of such envelope correlations, we consider a whole-brain network model assuming two distinct fundamental scenarios: one where each brain area generates oscillations in a single frequency, and a novel one where each brain area can generate oscillations in multiple frequency bands. The models share, as a common generator of damped oscillations, the normal form of a supercritical Hopf bifurcation operating at the critical border between the steady state and the oscillatory regime. The envelopes of the simulated signals are compared with empirical MEG data using new methods to analyse the envelope dynamics in terms of their phase coherence and stability across the spectrum of carrier frequencies. Considering the whole-brain model with a single frequency generator in each brain area, we obtain the best fit with the empirical MEG data when the fundamental frequency is tuned at 12Hz. However, when multiple frequency generators are placed at each local brain area, we obtain an improved fit of the spatio-temporal structure of on-going MEG data across all frequency bands. Our results indicate that the brain is likely to operate on multiple frequency channels during rest, introducing a novel dimension for future models of large-scale brain activity.
PMID: 28315461 [PubMed - as supplied by publisher]
Dynamic reorganization of intrinsic functional networks in the mouse brain.
Neuroimage. 2017 Mar 14;:
Authors: Grandjean J, Giulia Preti M, Bolton TA, Buerge M, Seifritz E, Pryce CR, Van De Ville D, Rudin M
Functional connectivity (FC) derived from resting-state functional magnetic resonance imaging (rs-fMRI) allows for the integrative study of neuronal processes at a macroscopic level. The majority of studies to date have assumed stationary interactions between brain regions, without considering the dynamic aspects of network organization. Only recently has the latter received increased attention, predominantly in human studies. Applying dynamic FC (dFC) analysis to mice is attractive given the relative simplicity of the mouse brain and the possibility to explore mechanisms underlying network dynamics using pharmacological, environmental or genetic interventions. Therefore, we have evaluated the feasibility and research potential of mouse dFC using the interventions of social stress or anesthesia duration as two case-study examples. By combining a sliding-window correlation approach with dictionary learning, several dynamic functional states (dFS) with a complex organization were identified, exhibiting highly dynamic inter- and intra-modular interactions. Each dFS displayed a high degree of reproducibility upon changes in analytical parameters and across datasets. They fluctuated at different degrees as a function of anesthetic depth, and were sensitive indicators of pathology as shown for the chronic psychosocial stress mouse model of depression. Dynamic functional states are proposed to make a major contribution to information integration and processing in the healthy and diseased brain.
PMID: 28315459 [PubMed - as supplied by publisher]
7,8-dihydroxyflavone facilitates the action exercise to restore plasticity and functionality: Implications for early brain trauma recovery.
Biochim Biophys Acta. 2017 Mar 14;:
Authors: Krishna G, Agrawal R, Zhuang Y, Ying Z, Paydar A, Harris NG, Royes LF, Gomez-Pinilla F
Metabolic dysfunction accompanying traumatic brain injury (TBI) severely impairs the ability of injured neurons to comply with functional demands. This limits the success of rehabilitative strategies by compromising brain plasticity and function, and highlights the need for early interventions to promote energy homeostasis. We sought to examine whether the TrkB agonist, 7,8-dihydroxyflavone (7,8-DHF) normalizes brain energy deficits and restablishes more normal patterns of functional connectivity, while enhancing the effects of exercise during post-TBI period. Moderate fluid percussion injury (FPI) was performed and 7,8-DHF (5mg/kg, i.p.) was administered in animals subjected to FPI that either had access to voluntary wheel running for 7days after injury or were sedentary. Compared to sham-injured controls, TBI resulted in reduced hippocampal activation of the BDNF receptor TrkB and associated CREB, reduced levels of plasticity markers GAP-43 and Syn I, as well as impaired memory as indicated by the Barnes maze task. While 7,8-DHF treatment and exercise individually mitigated TBI-induced effects, administration of 7,8-DHF concurrently with exercise facilitated memory performance and augmented levels of markers of cell energy metabolism viz., PGC-1α, COII and AMPK. In parallel to these findings, resting-state functional MRI (fMRI) acquired at 2weeks after injury showed that 7,8-DHF with exercise enhanced hippocampal functional connectivity, and suggests 7,8-DHF and exercise to promote increases in functional connectivity. Together, these findings indicate that post-injury 7,8-DHF treatment promotes enhanced levels of cell metabolism, synaptic plasticity in combination with exercise increases in brain circuit function that facilitates greater physical rehabilitation after TBI.
PMID: 28315455 [PubMed - as supplied by publisher]
Amygdala functional connectivity is associated with locus of control in the context of cognitive aging.
Neuropsychologia. 2017 Mar 14;:
Authors: Ren P, Anthony M, Chapman BP, Heffner K, Lin F
Locus of control (LOC) measures the extent to which individuals perceive control over their lives. Those with a more "internal" LOC feel self-sufficient and able to determine important aspects of their own future, while those with a more "external" LOC feel that their lives are governed by events beyond their control. Reduced internal LOC and increased external LOC have been found in cognitive disorders, but the neural substrates of these control perceptions are yet unknown. In the present study, we explored the relationship between amygdala functional connectivity and LOC in 18 amnestic mild cognitive impairment (MCI) and age-, sex-, and education-matched, 22 cognitively healthy controls (HC). Participants completed cognitive challenge tasks (Stroop Word Color task and Dual 1-back) for 20minutes, and underwent resting-state functional magnetic resonance imaging immediately before and after the tasks. We found significantly lower internal LOC and higher external LOC in the MCI group than the HC group. Compared to HC, MCI group showed significantly stronger positive associations between internal LOC and baseline right amygdala connections (including right middle frontal gyrus and anterior cingulate cortex), and stronger negative associations between internal LOC and change of these right amygdala connections. Across all participants, external LOC explained the relationships between associations of another set of right amygdala connections (including middle cingulate cortex and right superior frontal gyrus), both at baseline and for change, and performance in the cognitive challenge tasks. Our findings indicate that the right amygdala networks might be critical in understanding the neural mechanisms underlying LOC's role in cognitive aging.
PMID: 28315366 [PubMed - as supplied by publisher]
tDCS-induced Modulation of GABA Levels and Resting-State Functional Connectivity in Older Adults.
J Neurosci. 2017 Mar 17;:
Authors: Antonenko D, Schubert F, Bohm F, Ittermann B, Aydin S, Hayek D, Grittner U, Flöel A
Transcranial direct current stimulation (tDCS) modulates human behavior, neuronal patterns and metabolite concentrations, with exciting potential for neurorehabilitation. However, the understanding of tDCS-induced alterations on the neuronal level is incomplete and conclusions from young adults, in whom the majority of studies have been conducted, cannot be easily transferred to older populations. Here, we investigated tDCS-induced effects in older adults (N=48, age range 50-79 years) using magnetic resonance spectroscopy to quantify gamma-aminobutyric acid (GABA) levels as well as resting-state functional magnetic resonance imaging to assess sensorimotor network strength and inter-hemispheric connectivity. In a randomized, counterbalanced, cross-over design, we applied anodal (atDCS), cathodal (ctDCS) and sham (stDCS) stimulation over the left sensorimotor region. We observed a significant reduction of GABA levels after atDCS compared to stDCS, reflecting preserved neuromodulatory effect of atDCS in older adults. Moreover, resting-state functional coupling was decreased during atDCS compared to stDCS, most likely indicating augmented efficiency in brain network functioning. Increased levels of inter-hemispheric connectivity with age were diminished by atDCS, suggesting stimulation-induced functional decoupling. Further, the magnitude of atDCS-induced local plasticity was related to baseline functional network strength. Our findings provide novel insight into the neuronal correlates underlying tDCS-induced neuronal plasticity in older adults, and thus might help to develop tDCS interventions tailored to the aging brain.SIGNIFICANCE STATEMENTTranscranial direct current stimulation (tDCS) modulates human behavior, neuronal patterns and metabolite concentrations, with exciting potential for neurorehabilitation. However, the understanding of tDCS-induced alterations on the neuronal level is incomplete and conclusions from young adults cannot be easily transferred to older populations. We used a systematic multimodal imaging approach in order to investigate the neurophysiological effects of tDCS in older adults and found stimulation-induced effects on gamma-aminobutyric acid levels, reflecting augmented local plasticity, and functional connectivity, suggesting modulation of network efficiency. Our findings may help to reconcile some of the recent reports on the variability of tDCS-induced effects, not only implicating age as a crucial modulating factor, but detailing its specific impact on functionality of neural networks.
PMID: 28314813 [PubMed - as supplied by publisher]
(31) P magnetization transfer magnetic resonance spectroscopy: Assessing the activation induced change in cerebral ATP metabolic rates at 3 T.
Magn Reson Med. 2017 Mar 16;:
Authors: Chen C, Stephenson MC, Peters A, Morris PG, Francis ST, Gowland PA
PURPOSE: In vivo (31) P magnetic resonance spectroscopy (MRS) magnetization transfer (MT) provides a direct measure of neuronal activity at the metabolic level. This work aims to use functional (31) P MRS-MT to investigate the change in cerebral adenosine triphosphate (ATP) metabolic rates in healthy adults upon repeated visual stimuli.
METHODS: A magnetization saturation transfer sequence with narrowband selective saturation of γ-ATP was developed for (31) P MT experiments at 3 T.
RESULTS: Using progressive saturation of γ-ATP, the intrinsic T1 relaxation times of phosphocreatine (PCr) and inorganic phosphate (Pi) at 3 T were measured to be 5.1 ± 0.8 s and 3.0 ± 1.4 s, respectively. Using steady-state saturation of γ-ATP, a significant 24% ± 14% and 11% ± 7% increase in the forward creatine kinase (CK) pseudo-first-order reaction rate constant, k1 , was observed upon visual stimulation in the first and second cycles, respectively, of a paradigm consisting of 10-minute rest followed by 10-minute stimulation, with the measured baseline k1 being 0.35 ± 0.04 s(-1) . No significant changes in forward ATP synthase reaction rate, PCr/γ-ATP, Pi/γ-ATP, and nicotinamide adenine dinucleotide/γ-ATP ratios, or intracellular pH were detected upon stimulation.
CONCLUSION: This work demonstrates the potential of studying cerebral bioenergetics using functional (31) P MRS-MT to determine the change in the forward CK reaction rate at 3 T. Magn Reson Med, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
PMID: 28303591 [PubMed - as supplied by publisher]
Abnormal Spontaneous Brain Activity in Acute Low-Back Pain Revealed by Resting-State Functional MRI.
Am J Phys Med Rehabil. 2017 Apr;96(4):253-259
Authors: Zhang SS, Wu W, Yang JM, Wang CH
OBJECTIVE: Neuroimaging studies have revealed that low-back pain (LBP) alters spatiotemporal dynamics of the blood oxygen level-dependent signal in response to persistent noxious stimulus. This study aimed to investigate changes in spontaneous neural activity of various brain regions in acute LBP using resting-state functional magnetic resonance imaging and amplitude of low-frequency fluctuation (ALFF).
DESIGN: Twelve healthy subjects underwent two separate resting-state functional magnetic resonance imaging scans at health status as baseline and after intramuscular injection of hypertonic saline (0.5 mL, 5%) into the back muscles to induce acute LBP.
RESULTS: Compared with baseline, acute LBP showed decreased ALFF in the right posterior cingulate cortex/precuneus and left primary somatosensory cortex (S1) but increased ALFF in the right medial prefrontal cortex, right middle temporal gyrus, bilateral inferior temporal gyrus, bilateral insula, right anterior cingulate cortex, and left cerebellum. In addition, significant negative correlations were observed between visual analog scale scores and ALFF of the bilateral medial prefrontal cortex, left inferior frontal gyrus, left S1, right anterior cingulate cortex, and left middle temporal gyrus.
CONCLUSIONS: These findings suggest that abnormally spontaneous neural activity involving some brain regions are responsible for sensory, affective, and cognitive functions, which may be implicated in the underlying pathophysiology of acute LBP.
PMID: 28301866 [PubMed - in process]
Sensorimotor Cortical Neuroplasticity in the Early Stage of Bell's Palsy.
Neural Plast. 2017;2017:8796239
Authors: Song W, Dai M, Xuan L, Cao Z, Zhou S, Lang C, Lv K, Xu M, Kong J
Neuroplasticity is a common phenomenon in the human brain following nerve injury. It is defined as the brain's ability to reorganize by creating new neural pathways in order to adapt to change. Here, we use task-related and resting-state fMRI to investigate neuroplasticity in the primary sensory (S1) and motor cortex (M1) in patients with acute Bell's palsy (BP). We found that the period directly following the onset of BP (less than 14 days) is associated with significant decreases in regional homogeneity (ReHo), fractional amplitude of low frequency fluctuations (fALFF), and intrinsic connectivity contrast (ICC) values in the contralateral S1/M1 and in ReHo and ICC values in the ipsilateral S1/M1, compared to healthy controls. The regions with decreased ReHo, fALFF, and ICC values were in both the face and hand region of S1/M1 as indicated by resting-state fMRI but not task-related fMRI. Our results suggest that the early stages of BP are associated with functional neuroplasticity in both the face and hand regions of S1/M1 and that resting-state functional fMRI may be a sensitive tool to detect these early stages of plasticity in patient populations.
PMID: 28299208 [PubMed - in process]
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Network Optimization of Functional Connectivity within Default Mode Network Regions to Detect Cognitive Decline.
IEEE Trans Neural Syst Rehabil Eng. 2017 Mar 07;:
Authors: Chaovalitwongse WA, Won D, Seref O, Borghesani P, Askren MK, Willis S, Grabowski T
The rapid aging of the world's population is causing an increase in the prevalence of cognitive decline and degenerative brain disease in the elderly. Current diagnoses of amnestic and nonamnestic Mild Cognitive Impairment (MCI), which may represent early stage Alzheimer's disease or related degenerative conditions, are based on clinical grounds. The recent emergence of advanced network analyses of functional Magnetic Resonance Imaging (fMRI) data taken at cognitive rest has provided insight that declining functional connectivity of the default mode network (DMN) may be correlated with neurological disorders, and particularly prodromal Alzheimer's disease. The goal of this paper is to develop a network analysis technique using fMRI data to characterize transition stages from healthy brain aging to cognitive decline. Previous studies primarily focused on internodal connectivity of the DMN and often assume functional homogeneity within each DMN region. In this paper, we develop a technique that focuses on identifying critical intra-nodal DMN connectivity by incorporating sparsity into connectivity modeling of the k-cardinality tree (KCT) problem. Most biological networks are efficient and formed by sparse connections, and the KCT can potentially reveal sparse connectivity patterns that are biologically informative. The KCT problem is NP-hard, and existing solution approaches are mostly heuristic. Mathematical formulations of the KCT problem in the literature are not compact and do not provide good solution bounds. This paper presents new KCT formulations and a fast heuristic approach to efficiently solve the KCT models for large DMN regions. The results in this study demonstrate that traditional fMRI group analysis on DMN regions cannot detect any statistically significant connectivity differences between normal aging and cognitively impaired subjects in DMN regions, and the proposed KCT approaches are more sensitive than the state-of-the-art regional homogeneity approach in detecting significant differences in both left and right medial temporal regions of the DMN.
PMID: 28287976 [PubMed - as supplied by publisher]
Similarities and differences of functional connectivity in drug-naïve, first-episode adolescent and young adult with major depressive disorder and schizophrenia.
Sci Rep. 2017 Mar 13;7:44316
Authors: Wei S, Womer F, Geng H, Jiang X, Zhou Q, Chang M, Zhou Y, Tang Y, Wang F
Major depressive disorder (MDD) and schizophrenia (SZ) are considered two distinct psychiatric disorders. Yet, they have considerable overlap in symptomatology and clinical features, particularly in the initial phases of illness. The amygdala and prefrontal cortex (PFC) appear to have critical roles in these disorders; however, abnormalities appear to manifest differently. In our study forty-nine drug-naïve, first-episode MDD, 45 drug-naïve, first-episode SZ, and 50 healthy control (HC) participants from 13 to 30 years old underwent resting-state functional magnetic resonance imaging. Functional connectivity (FC) between the amygdala and PFC was compared among the three groups. Significant differences in FC were observed between the amygdala and ventral PFC (VPFC), dorsolateral PFC (DLPFC), and dorsal anterior cingulated cortex (dACC) among the three groups. Further analyses demonstrated that MDD showed decreased amygdala-VPFC FC and SZ had reductions in amygdala-dACC FC. Both the diagnostic groups had significantly decreased amygdala-DLPFC FC. These indicate abnormalities in amygdala-PFC FC and further support the importance of the interaction between the amygdala and PFC in adolescents and young adults with these disorders. Additionally, the alterations in amygdala-PFC FC may underlie the initial similarities observed between MDD and SZ and suggest potential markers of differentiation between the disorders at first onset.
PMID: 28287187 [PubMed - in process]
Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM.
J Neurosci Methods. 2017 Mar 09;:
Authors: Hojjati SH, Ebrahimzadeh A, Khazaee A, Babajani-Feremi A
BACKGROUND: We investigated identifying patients with mild cognitive impairment (MCI) who progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do not progress to AD, MCI non-converter (MCI-NC), based on resting-state fMRI (rs-fMRI).
NEW METHOD: Graph theory and machine learning approach were utilized to predict progress of patients with MCI to AD using rs-fMRI. Eighteen MCI converts (average age 73.6 years; 11 male) and 62 age-matched MCI non-converters (average age 73.0 years, 28 male) were included in this study. We trained and tested a support vector machine (SVM) to classify MCI-C from MCI-NC using features constructed based on the local and global graph measures. A novel feature selection algorithm was developed and utilized to select an optimal subset of features.
RESULTS: Using subset of optimal features in SVM, we classified MCI-C from MCI-NC with an accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve of 91.4%, 83.24%, 90.1%, and 0.95, respectively. Furthermore, results of our statistical analyses were used to identify the affected brain regions in AD.
COMPARISON WITH EXISTING METHOD(S): To the best of our knowledge, this is the first study that combines the graph measures (constructed based on rs-fMRI) with machine learning approach and accurately classify MCI-C from MCI-NC.
CONCLUSION: Results of this study demonstrate potential of the proposed approach for early AD diagnosis and demonstrate capability of rs-fMRI to predict conversion from MCI to AD by identifying affected brain regions underlying this conversion.
PMID: 28286064 [PubMed - as supplied by publisher]
Development of rostral inferior parietal lobule area functional connectivity from late childhood to early adulthood.
Int J Dev Neurosci. 2017 Mar 07;:
Authors: Wang M, Zhang J, Dong G, Zhang H, Lu H, Du X
Although the mirror neuron system (MNS) has been extensively studied in monkeys and adult humans, very little is known about its development. Previous studies suggest that the MNS is present by infancy and that the brain and MNS-related cognitive abilities (such as language, empathy, and imitation learning) continue to develop after childhood. In humans, the PFt area of the inferior parietal lobule (IPL) seems to particularly correlate with the functional properties of the PF area in primates, which contains mirror neurons. However, little is known about the functional connectivity (FC) of the PFt area with other brain areas and whether these networks change over time. Here, we investigated the FC development of the PFt area-based network in 61 healthy subjects aged 7-26 years at resting-state to study brain development from late childhood through adolescence to early adulthood. The bilateral PFt showed similar core FC networks, which included the frontal lobe, the cingulate gyri, the insula, the somatosensory cortex, the precuneus, the superior and inferior parietal lobules, the temporal lobe, and the cerebellum posterior lobes. Furthermore, the FC between the left PFt and the left IPL exhibited a significantly positive correlation with age, and the FC between the left PFt and the right postcentral gyrus exhibited a significantly negative correlation with age. In addition, the FC between the right PFt and the right putamen exhibited a significantly negative correlation with age. Our findings suggest that the PFt area-based network develops and is reorganized with age.
PMID: 28285946 [PubMed - as supplied by publisher]
Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies.
Neurosci Bull. 2017 Mar 10;:
Authors: Li D, Karnath HO, Xu X
Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation, connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and large-scale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.
PMID: 28283808 [PubMed - as supplied by publisher]
Use of resting-state fMRI in planning epilepsy surgery.
Neurol India. 2017;65(Supplement):S25-S33
Authors: Chiang S, Haneef Z, Stern JM, Engel J
Epileptic seizures result from abnormal neuronal excitability and synchronization, affecting 0.5-1% of the population worldwide. Although anti-seizure drugs are often effective, a significant number of patients with epilepsy continue to experience refractory seizures and are candidates for surgical resection. Whereas standard presurgical evaluation has relied on intracranial electroencephalography (icEEG) and direct cortical stimulation to identify epileptogenic tissue and areas of cortex for which resection would produce clinical deficits, the invasive nature and limited spatial extent of icEEG has led to the investigation of less invasive imaging modalities as adjunctive tools in the presurgical workup. In the past few decades, functional connectivity MRI has emerged as a promising approach for presurgical mapping, leading to a surge in the number of proposed methods and biomarkers for identifying epileptogenic tissue. This review focuses on recent advances in the use of functional connectivity MRI toward its application for presurgical planning, including epilepsy localization and eloquent cortex mapping.
PMID: 28281493 [PubMed - in process]
At risk of being risky: The relationship between "brain age" under emotional states and risk preference.
Dev Cogn Neurosci. 2017 Feb 01;24:93-106
Authors: Rudolph MD, Miranda-Domínguez O, Cohen AO, Breiner K, Steinberg L, Bonnie RJ, Scott ES, Taylor-Thompson K, Chein J, Fettich KC, Richeson JA, Dellarco DV, Galván A, Casey BJ, Fair DA
Developmental differences regarding decision making are often reported in the absence of emotional stimuli and without context, failing to explain why some individuals are more likely to have a greater inclination toward risk. The current study (N=212; 10-25y) examined the influence of emotional context on underlying functional brain connectivity over development and its impact on risk preference. Using functional imaging data in a neutral brain-state we first identify the "brain age" of a given individual then validate it with an independent measure of cortical thickness. We then show, on average, that "brain age" across the group during the teen years has the propensity to look younger in emotional contexts. Further, we show this phenotype (i.e. a younger brain age in emotional contexts) relates to a group mean difference in risk perception - a pattern exemplified greatest in young-adults (ages 18-21). The results are suggestive of a specified functional brain phenotype that relates to being at "risk to be risky."
PMID: 28279917 [PubMed - as supplied by publisher]
Mnemonic Training Reshapes Brain Networks to Support Superior Memory.
Neuron. 2017 Mar 08;93(5):1227-1235.e6
Authors: Dresler M, Shirer WR, Konrad BN, Müller NC, Wagner IC, Fernández G, Czisch M, Greicius MD
Memory skills strongly differ across the general population; however, little is known about the brain characteristics supporting superior memory performance. Here we assess functional brain network organization of 23 of the world's most successful memory athletes and matched controls with fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that, in a group of naive controls, functional connectivity changes induced by 6 weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain's functional network organization to enable superior memory performance.
PMID: 28279356 [PubMed - in process]
Parallel group independent component analysis for massive fMRI data sets.
PLoS One. 2017;12(3):e0173496
Authors: Chen S, Huang L, Qiu H, Nebel MB, Mostofsky SH, Pekar JJ, Lindquist MA, Eloyan A, Caffo BS
Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.
PMID: 28278208 [PubMed - in process]