New resting-state fMRI related studies at PubMed

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Effects of pharmacological and nonpharmacological treatments on brain functional magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment: a critical review.

Wed, 02/21/2018 - 17:40
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Effects of pharmacological and nonpharmacological treatments on brain functional magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment: a critical review.

Alzheimers Res Ther. 2018 Feb 20;10(1):21

Authors: Canu E, Sarasso E, Filippi M, Agosta F

Abstract
BACKGROUND: A growing number of pharmacological and nonpharmacological trials have been performed to test the efficacy of approved or experimental treatments in Alzheimer disease (AD) and mild cognitive impairment (MCI). In this context, functional magnetic resonance imaging (fMRI) may be a good candidate to detect brain changes after a short period of treatment.
MAIN BODY: This critical review aimed to identify and discuss the available studies that have tested the efficacy of pharmacological and nonpharmacological treatments in AD and MCI cases using task-based or resting-state fMRI measures as primary outcomes. A PubMed-based literature search was performed with the use of the three macro-areas: 'disease', 'type of MRI', and 'type of treatment'. Each contribution was individually reviewed according to the Cochrane Collaboration's tool for assessing risk of bias. Study limitations were systematically detected and critically discussed. We selected 34 pharmacological and 13 nonpharmacological articles. According to the Cochrane Collaboration's tool for assessing risk of bias, 40% of these studies were randomized but only a few described clearly the randomization procedure, 36% declared the blindness of participants and personnel, and only 21% reported the blindness of outcome assessment. In addition, 28% of the studies presented more than 20% drop-outs at short- and/or long-term assessments. Additional common shortcomings of the reviewed works were related to study design, patient selection, sample size, choice of outcome measures, management of drop-out cases, and fMRI methods.
CONCLUSION: There is an urgent need to obtain efficient treatments for AD and MCI. fMRI is powerful enough to detect even subtle changes over a short period of treatment; however, the soundness of methods should be improved to enable meaningful data interpretation.

PMID: 29458420 [PubMed - in process]

In need of constraint: Understanding the role of the cingulate cortex in the impulsive mind.

Wed, 02/21/2018 - 17:40
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In need of constraint: Understanding the role of the cingulate cortex in the impulsive mind.

Neuroimage. 2017 Feb 01;146:804-813

Authors: Golchert J, Smallwood J, Jefferies E, Liem F, Huntenburg JM, Falkiewicz M, Lauckner ME, Oligschläger S, Villringer A, Margulies DS

Abstract
Impulsive behavior often occurs without forethought and can be driven by strong emotions or sudden impulses, leading to problems in cognition and behavior across a wide range of situations. Although neuroimaging studies have explored the neurocognitive indicators of impulsivity, the large-scale functional networks that contribute to different aspects of impulsive cognition remain unclear. In particular, we lack a coherent account of why impulsivity is associated with such a broad range of different psychological features. Here, we use resting state functional connectivity, acquired in two independent samples, to investigate the neural substrates underlying different aspects of self-reported impulsivity. Based on the involvement of the anterior cingulate cortex (ACC) in cognitive but also affective processes, five seed regions were placed along the caudal to rostral gradient of the ACC. We found that positive urgency was related to functional connectivity between subgenual ACC and bilateral parietal regions such as retrosplenial cortex potentially highlighting this connection as being important in the modulation of the non-prospective, hastiness - related aspects of impulsivity. Further, two impulsivity dimensions were associated with significant alterations in functional connectivity of the supragenual ACC: (i) lack of perseverance was positively correlated to connectivity with the bilateral dorsolateral prefrontal cortex and right inferior frontal gyrus and (ii) lack of premeditation was inversely associated with functional connectivity with clusters within bilateral occipital cortex. Further analysis revealed that these connectivity patterns overlapped with bilateral dorsolateral prefrontal and bilateral occipital regions of the multiple demand network, a large-scale neural system implicated in the general control of thought and action. Together these results demonstrate that different forms of impulsivity have different neural correlates, which are linked to the functional connectivity of a region of anterior cingulate cortex. This suggests that poor perseveration and premeditation might be linked to dysfunctions in how the rostral zone of the ACC interacts with the multiple demand network that allows cognition to proceed in a controlled way.

PMID: 27989844 [PubMed - indexed for MEDLINE]

Multiparametric imaging of brain hemodynamics and function using gas-inhalation MRI.

Wed, 02/21/2018 - 17:40
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Multiparametric imaging of brain hemodynamics and function using gas-inhalation MRI.

Neuroimage. 2017 Feb 01;146:715-723

Authors: Liu P, Welch BG, Li Y, Gu H, King D, Yang Y, Pinho M, Lu H

Abstract
Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI. The proposed technique uses a single MRI scan to provide simultaneous measurements of baseline venous cerebral blood volume (vCBV), cerebrovascular reactivity (CVR), bolus arrival time (BAT), and resting-state functional connectivity (fcMRI). This was achieved with a novel, concomitant O2 and CO2 gas inhalation paradigm, rapid MRI image acquisition with a 9.3min BOLD sequence, and an advanced algorithm to extract multiple hemodynamic information from the same dataset. In healthy subjects, CVR and vCBV values were 0.23±0.03%/mmHg and 0.0056±0.0006%/mmHg, respectively, with a strong correlation (r=0.96 for CVR and r=0.91 for vCBV) with more conventional, separate acquisitions that take twice the scan time. In patients with Moyamoya syndrome, CVR in the stenosis-affected flow territories (typically anterior-cerebral-artery, ACA, and middle-cerebral-artery, MCA, territories) was significantly lower than that in posterior-cerebral-artery (PCA), which typically has minimal stenosis, flow territories (0.12±0.06%/mmHg vs. 0.21±0.05%/mmHg, p<0.001). BAT of the gas bolus was significantly longer (p=0.008) in ACA/MCA territories, compared to PCA, and the maps were consistent with the conventional contrast-enhanced CT perfusion method. FcMRI networks were robustly identified from the gas-inhalation MRI data after factoring out the influence of CO2 and O2 on the signal time course. The spatial correspondence between the gas-data-derived fcMRI maps and those using a separate, conventional fcMRI scan was excellent, showing a spatial correlation of 0.58±0.17 and 0.64±0.20 for default mode network and primary visual network, respectively. These findings suggest that advanced gas-inhalation MRI provides reliable measurements of multiple hemodynamic parameters within a clinically acceptable imaging time and is suitable for patient examinations.

PMID: 27693197 [PubMed - indexed for MEDLINE]

Convergence of prefrontal and parietal anatomical projections in a connectional hub in the striatum.

Wed, 02/21/2018 - 17:40
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Convergence of prefrontal and parietal anatomical projections in a connectional hub in the striatum.

Neuroimage. 2017 Feb 01;146:821-832

Authors: Choi EY, Tanimura Y, Vage PR, Yates EH, Haber SN

Abstract
Visual attentional bias forms for rewarding and punishing stimuli in the environment. While this attentional bias is adaptive in healthy situations, it is maladaptive in disorders such as drug addiction or PTSD. In both these disorders, the ability to exert control over this attentional bias is associated with drug abstinence rates or reduced PTSD symptoms, indicating the interaction of visual attention, cognitive control, and stimulus association. The inferior parietal lobule (IPL) is central to attention, while the prefrontal cortex (PFC) is critical for reward, cognitive control, and attention. Importantly, regions of the IPL and PFC commonly project to the rostral dorsal caudate (rdCaud) of the striatum. We propose an anatomical network architecture in which IPL projections converge with PFC projections in a connectional hub in the rdCaud, providing an anatomical substrate for the interaction of these projections and their competitive influence on striatal processing. To investigate this, we mapped the dense projections from the caudal IPL and prefrontal (dlPFC, vlPFC, OFC, dACC, and dmPFC) regions that project to the medial rdCaud with anatomical tract-tracing tracer injections in monkeys. These inputs converge in a precise site in the medial rdCaud, rostral to the anterior commissure. Small retrograde tracer injections confirmed these inputs to the medial rdCaud and showed that a proximal ventral striatal location has a very different pattern of cortical inputs. We next used human resting-state functional connectivity MRI (fcMRI) to examine whether a striatal hub exists in the human medial rdCaud. Seed regions in the human medial rdCaud revealed cortical correlation maps similar to the monkey retrograde injection results. A subsequent analysis of these correlated cortical regions showed that their peak correlation within the striatum is in the medial rdCaud, indicating that this is a connectional hub. In contrast, this peak striatal correlation was not found in the ventral striatal location, suggesting that this site is not a connectional hub of cortical regions. Taken together, this work uses the precision of monkey anatomy to identify a connectional hub of IPL and PFC projections in the medial rdCaud. It also translates this anatomical precision to humans, demonstrating that, guided by anatomy, connectional hubs can be identified in humans with fcMRI. These connectional hubs provide more specific treatment targets for drug addiction, PTSD, and other neurological and psychiatric disorders involving the striatum.

PMID: 27646127 [PubMed - indexed for MEDLINE]

The functional connectivity in the motor loop of human basal ganglia.

Wed, 02/21/2018 - 17:40
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The functional connectivity in the motor loop of human basal ganglia.

Brain Imaging Behav. 2017 Apr;11(2):417-429

Authors: Rodriguez-Sabate C, Sabate M, Llanos C, Morales I, Sanchez A, Rodriguez M

Abstract
Basal ganglia interact in a complex way which is still not completely understood. The model generally used to explain basal ganglia interactions is based on experimental data in animals, but its validation in humans has been hampered by methodological restrictions. The time-relationship (partial correlation) of the fluctuations of the blood-oxygen-level-dependent signals recorded in the main basal ganglia was used here (32 healthy volunteers; 18-72 years of age; 16 males and 16 females) to test whether the interaction of the main basal ganglia in humans follows the pattern of functional connectivity in animals. Data showed that most basal ganglia have a functional connectivity which is compatible with that of the established closed-loop model. The strength of the connectivity of some basal ganglia changed with finger motion, suggesting that the functional interactions between basal ganglia are quickly restructured by the motor tasks. The present study with the motor cortico-BG loop centers supports the circling dynamic of the basal ganglia model in humans, showing that motor tasks may change the functional connectivity of these centers.

PMID: 26935555 [PubMed - indexed for MEDLINE]

Influence of orthodontic appliance-derived artifacts on 3-T MRI movies.

Tue, 02/20/2018 - 17:00
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Influence of orthodontic appliance-derived artifacts on 3-T MRI movies.

Prog Orthod. 2018 Feb 19;19(1):7

Authors: Ozawa E, Honda EI, Parakonthun KN, Ohmori H, Shimazaki K, Kurabayashi T, Ono T

Abstract
BACKGROUND: Magnetic resonance imaging (MRI) has been used to study configurations of speech organs in the resting state. However, MRI is sensitive to metals, and numerous types of metallic appliances, most of which have a large magnetic susceptibility, are used in orthodontic treatment and may cause severe artifacts on MRI. We have developed techniques for obtaining MRI movies of the oral region, to evaluate articulatory changes, especially movement of the tongue, palate, and teeth, pre- and post-orthodontic/orthognathic treatment. We evaluated the influence of artifacts caused by orthodontic appliances, including fixed retainers, metal brackets, and wires, on measurements in 3-T MRI movies.
METHODS: Sixteen healthy young adults (nine males, seven females; average age, 27 years) with normal occlusion were recruited. Four types of customized maxillary and mandibular plates were prepared by incorporating one of the following into the plate: (a) nothing, (b) a fixed canine-to-canine retainer, (c) metal brackets for the anterior and molar teeth, or (d) clear brackets for the anterior teeth and metal brackets for molars. A 3-T MRI movie, in segmented cine mode, was generated for each plate condition while participants pronounced a vowel-consonant-vowel syllable (/asa/). The size of the artifact due to the metallic brackets was measured. The face size and orthodontically important anatomical structures, such as the velum, the hard palate, and the laryngeal ventricle, were also measured.
RESULTS: A large artifact was observed over the entire oral region around orthodontic appliances, altering regional visibility. The velopharyngeal height was measured as significantly longer in the presence of metal brackets. The maximum artifact size due to a metallic bracket was > 8 cm. Our results show that even if it is possible to obtain the measurements of palate length, nasion to sella, and nasion to basion in individuals wearing metal brackets for molars, the measurements might be affected due to the presence of artifacts.
CONCLUSIONS: Orthodontic appliances, including metallic materials, sometimes produce significant measurement error in speech evaluation using MRI movies, which often become invisible or distorted by metallic orthodontic appliances. When the distorted image is measured, caution should be exercised, as the measurement may be affected. Based on the study, it is concluded that orthodontists should not necessarily remove all metallic appliances before MRI examination because the influence varies among the appliances and should also know that a significant measurement error in speech evaluation using MRI movie may occur by image distortion caused by metallic artifacts.

PMID: 29457192 [PubMed - in process]

Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan.

Tue, 02/20/2018 - 17:00
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Hurst Exponent Analysis of Resting-State fMRI Signal Complexity across the Adult Lifespan.

Front Neurosci. 2018;12:34

Authors: Dong J, Jing B, Ma X, Liu H, Mo X, Li H

Abstract
Exploring functional information among various brain regions across time enables understanding of healthy aging process and holds great promise for age-related brain disease diagnosis. This paper proposed a method to explore fractal complexity of the resting-state functional magnetic resonance imaging (rs-fMRI) signal in the human brain across the adult lifespan using Hurst exponent (HE). We took advantage of the examined rs-fMRI data from 116 adults 19 to 85 years of age (44.3 ± 19.4 years, 49 females) from NKI/Rockland sample. Region-wise and voxel-wise analyses were performed to investigate the effects of age, gender, and their interaction on complexity. In region-wise analysis, we found that the healthy aging is accompanied by a loss of complexity in frontal and parietal lobe and increased complexity in insula, limbic, and temporal lobe. Meanwhile, differences in HE between genders were found to be significant in parietal lobe (p = 0.04, corrected). However, there was no interaction between gender and age. In voxel-wise analysis, the significant complexity decrease with aging was found in frontal and parietal lobe, and complexity increase was found in insula, limbic lobe, occipital lobe, and temporal lobe with aging. Meanwhile, differences in HE between genders were found to be significant in frontal, parietal, and limbic lobe. Furthermore, we found age and sex interaction in right parahippocampal gyrus (p = 0.04, corrected). Our findings reveal HE variations of the rs-fMRI signal across the human adult lifespan and show that HE may serve as a new parameter to assess healthy aging process.

PMID: 29456489 [PubMed]

Parietal control network activation during memory tasks may be associated with the co-occurrence of externally and internally directed cognition: A cross-function meta-analysis.

Tue, 02/20/2018 - 17:00
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Parietal control network activation during memory tasks may be associated with the co-occurrence of externally and internally directed cognition: A cross-function meta-analysis.

Brain Res. 2018 Mar 15;1683:55-66

Authors: Kim H

Abstract
Functional neuroimaging studies on episodic memory retrieval consistently indicated the activation of the precuneus (PCU), mid-cingulate cortex (MCC), and lateral intraparietal sulcus (latIPS) regions. Although studies typically interpreted these activations in terms of memory retrieval processes, resting-state functional connectivity data indicate that these regions are part of the frontoparietal control network, suggesting a more general, cross-functional role. In this regard, this study proposes a novel hypothesis which suggests that the parietal control network plays a strong role in accommodating the co-occurrence of externally directed cognition (EDC) and internally directed cognition (IDC), which are typically antagonistic to each other. To evaluate how well this dual cognitive processes hypothesis can account for parietal activation patterns during memory tasks, this study provides a cross-function meta-analysis involving 3 different memory paradigms, namely, retrieval success (hit > correct rejection), repetition enhancement (repeated > novel), and subsequent forgetting (forgotten > remembered). Common to these paradigms is that the target condition may involve both EDC (stimulus processing and motor responding) and IDC (intentional remembering, involuntary awareness of previous encounter, or task-unrelated thoughts) strongly, whereas the reference condition may involve EDC to a greater extent, but IDC to a lesser extent. Thus, the dual cognitive processes hypothesis predicts that each of these paradigms will activate similar, overlapping PCU, MCC, and latIPS regions. The results were fully consistent with the prediction, supporting the dual cognitive processes hypothesis. Evidence from relevant prior studies suggests that the dual cognitive processes hypothesis may also apply to non-memory domain tasks.

PMID: 29456134 [PubMed - in process]

Predicting Autism Spectrum Disorder Using Domain-Adaptive Cross-Site Evaluation.

Tue, 02/20/2018 - 17:00
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Predicting Autism Spectrum Disorder Using Domain-Adaptive Cross-Site Evaluation.

Neuroinformatics. 2018 Feb 17;:

Authors: Bhaumik R, Pradhan A, Das S, Bhaumik DK

Abstract
The advances in neuroimaging methods reveal that resting-state functional fMRI (rs-fMRI) connectivity measures can be potential diagnostic biomarkers for autism spectrum disorder (ASD). Recent data sharing projects help us replicating the robustness of these biomarkers in different acquisition conditions or preprocessing steps across larger numbers of individuals or sites. It is necessary to validate the previous results by using data from multiple sites by diminishing the site variations. We investigated partial least square regression (PLS), a domain adaptive method to adjust the effects of multicenter acquisition. A sparse Multivariate Pattern Analysis (MVVPA) framework in a leave one site out cross validation (LOSOCV) setting has been proposed to discriminate ASD from healthy controls using data from six sites in the Autism Brain Imaging Data Exchange (ABIDE). Classification features were obtained using 42 bilateral Brodmann areas without presupposing any prior hypothesis. Our results showed that using PLS, SVM showed poorer accuracies with highest accuracy achieved (62%) than without PLS but not significantly. The regions occurred in two or more informative connections are Dorsolateral Prefrontal Cortex, Somatosensory Association Cortex, Primary Auditory Cortex, Inferior Temporal Gyrus and Temporopolar area. These interrupted regions are involved in executive function, speech, visual perception, sense and language which are associated with ASD. Our findings may support early clinical diagnosis or risk determination by identifying neurobiological markers to distinguish between ASD and healthy controls.

PMID: 29455363 [PubMed - as supplied by publisher]

Dynamic resting state fMRI analysis in mice reveals a set of Quasi-Periodic Patterns and illustrates their relationship with the global signal.

Tue, 02/20/2018 - 17:00
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Dynamic resting state fMRI analysis in mice reveals a set of Quasi-Periodic Patterns and illustrates their relationship with the global signal.

Neuroimage. 2018 Feb 15;:

Authors: Belloy ME, Naeyaert M, Abbas A, Shah D, Vanreusel V, van Audekerke J, Keilholz SD, Keliris GA, Van der Linden A, Verhoye M

Abstract
Time-resolved 'dynamic' over whole-period 'static' analysis of low frequency (LF) blood-oxygen level dependent (BOLD) fluctuations provides many additional insights into the macroscale organization and dynamics of neural activity. Although there has been considerable advancement in the development of mouse resting state fMRI (rsfMRI), very little remains known about its dynamic repertoire. Here, we report for the first time the detection of a set of recurring spatiotemporal Quasi-Periodic Patterns (QPPs) in mice, which show spatial similarity with known resting state networks. Furthermore, we establish a close relationship between several of these patterns and the global signal. We acquired high temporal rsfMRI scans under conditions of low (LA) and high (HA) medetomidine-isoflurane anesthesia. We then employed the algorithm developed by Majeed et al. (2011), previously applied in rats and humans, which detects and averages recurring spatiotemporal patterns in the LF BOLD signal. One type of observed patterns in mice was highly similar to those originally observed in rats, displaying propagation from lateral to medial cortical regions, which suggestively pertain to a mouse Task-Positive like network (TPN) and Default Mode like network (DMN). Other QPPs showed more widespread or striatal involvement and were no longer detected after global signal regression (GSR). This was further supported by diminished detection of subcortical dynamics after GSR, with cortical dynamics predominating. Observed QPPs were both qualitatively and quantitatively determined to be consistent across both anesthesia conditions, with GSR producing the same outcome. Under LA, QPPs were consistently detected at both group and single subject level. Under HA, consistency and pattern occurrence rate decreased, whilst cortical contribution to the patterns diminished. These findings confirm the robustness of QPPs across species and demonstrate a new approach to study mouse LF BOLD spatiotemporal dynamics and mechanisms underlying functional connectivity. The observed impact of GSR on QPPs might help better comprehend its controversial role in conventional resting state studies. Finally, consistent detection of QPPs at single subject level under LA promises a step forward towards more reliable mouse rsfMRI and further confirms the importance of selecting an optimal anesthesia regime.

PMID: 29454935 [PubMed - as supplied by publisher]

Time scale properties of task and resting-state functional connectivity: Detrended partial cross correlation analysis.

Tue, 02/20/2018 - 17:00
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Time scale properties of task and resting-state functional connectivity: Detrended partial cross correlation analysis.

Neuroimage. 2018 Feb 15;:

Authors: Ide JS, Li CR

Abstract
Functional connectivity analysis is an essential tool for understanding brain function. Previous studies showed that brain regions are functionally connected through low-frequency signals both within the default mode network (DMN) and task networks. However, no studies have directly compared the time scale (frequency) properties of network connectivity during task versus rest, or examined how they relate to task performance. Here, using fMRI data collected from sixty-eight subjects at rest and during a stop signal task, we addressed this issue with a novel functional connectivity measure based on detrended partial cross-correlation analysis (DPCCA). DPCCA has the advantage of quantifying correlations between two variables in different time scales while controlling for the influence of other variables. The results showed that the time scales of within-network connectivity of the DMN and task networks are modulated in opposite directions across rest and task, with the time scale increased during rest vs. task in the DMN and vice versa in task networks. In regions of interest analysis, the within-network connectivity time scale of the pre-supplementary motor area - a medial prefrontal cortical structure of the task network critical to proactive inhibitory control - correlated inversely with Barratt impulsivity and stop signal reaction time. Together, these findings demonstrate that time scale properties of brain networks may vary across mental states and provide evidence in support of a role of low frequency fluctuations of BOLD signals in behavioral control.

PMID: 29454934 [PubMed - as supplied by publisher]

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

Tue, 02/20/2018 - 17:00
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Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

Neuroimage. 2018 Feb 15;:

Authors: Li Z, Vidorreta M, Katchmar N, Alsop DC, Wolf DH, Detre JA

Abstract
Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition.

PMID: 29454933 [PubMed - as supplied by publisher]

Resting state functional connectivity of the amygdala and problem drinking in non-dependent alcohol drinkers.

Tue, 02/20/2018 - 17:00
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Resting state functional connectivity of the amygdala and problem drinking in non-dependent alcohol drinkers.

Drug Alcohol Depend. 2018 Feb 07;185:173-180

Authors: Hu S, Ide JS, Chao HH, Zhornitsky S, Fischer KA, Wang W, Zhang S, Li CR

Abstract
Alcohol misuse is associated with dysfunction of the amygdala-prefrontal cortical circuit. The amygdala and its cortical targets show decreased activity during a variety of task challenges in individuals engaged in problem drinking. On the other hand, it is less clear how amygdala resting state functional connectivity (rsFC) may be altered in association with alcohol misuse and whether such changes are restricted to prefrontal cortical structures. Further, the influences of comorbid substance use and depression and potential sex differences have not been assessed in earlier work. Here, with fMRI data from a Nathan Kline Institute/Rockland sample of 83 non-dependent alcohol drinkers (26 men), we addressed changes in whole brain rsFC of the amygdala in association with problem drinking as indexed by an alcohol involvement score. Imaging data were processed with Statistical Parametric Mapping following standard routines and all results were examined at voxel p < 0.001 uncorrected in combination with cluster p < 0.05 corrected for false discovery rate. Alcohol misuse was correlated with decreased amygdala connectivity with the dorsal anterior cingulate cortex (dACC) irrespective of depression and other substance use. Changes in amygdala-dACC connectivity manifested in the latero-basal subdivision of the amygdala. Further, men as compared to women showed a significantly stronger relationship in decreased amygdala-dACC connectivity and problem drinking, although it should be noted that men also showed a trend toward higher alcohol involvement score than women. The findings add to a growing literature documenting disrupted amygdala-prefrontal cortical functions in relation to alcohol misuse.

PMID: 29454928 [PubMed - as supplied by publisher]

Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior.

Tue, 02/20/2018 - 17:00
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Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior.

Neuroimage. 2017 Feb 01;146:561-574

Authors: Senden M, Reuter N, van den Heuvel MP, Goebel R, Deco G

Abstract
Cognition is hypothesized to require the globally coordinated, functionally relevant integration of otherwise segregated information processing carried out by specialized brain regions. Studies of the macroscopic connectome as well as recent neuroimaging and neuromodeling research have suggested a densely connected collective of cortical hubs, termed the rich club, to provide a central workspace for such integration. In order for rich club regions to fulfill this role they must dispose of a dynamic mechanism by which they can actively shape networks of brain regions whose information processing needs to be integrated. A potential candidate for such a mechanism comes in the form of oscillations which might be employed to establish communication channels among relevant brain regions. We explore this possibility using an integrative approach combining whole-brain computational modeling with neuroimaging, wherein we investigate the local dynamics model brain regions need to exhibit in order to fit (dynamic) network behavior empirically observed for resting as well as a range of task states. We find that rich club regions largely exhibit oscillations during task performance but not during rest. Furthermore, oscillations exhibited by rich club regions can harmonize a set of asynchronous brain regions thus supporting functional coupling among them. These findings are in line with the hypothesis that the rich club can actively shape integration using oscillations.

PMID: 27989843 [PubMed - indexed for MEDLINE]

Targeted transcranial theta-burst stimulation alters fronto-insular network and prefrontal GABA.

Tue, 02/20/2018 - 17:00
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Targeted transcranial theta-burst stimulation alters fronto-insular network and prefrontal GABA.

Neuroimage. 2017 Feb 01;146:395-403

Authors: Iwabuchi SJ, Raschke F, Auer DP, Liddle PF, Lankappa ST, Palaniyappan L

Abstract
Repetitive transcranial magnetic stimulation (rTMS) has been used worldwide to treat depression. However, the exact physiological effects are not well understood. Pathophysiology of depression involves crucial limbic structures (e.g. insula), and it is still not clear if these structures can be modulated through neurostimulation of surface regions (e.g. dorsolateral prefrontal cortex, DLPFC), and whether rTMS-induced excitatory/inhibitory transmission alterations relate to fronto-limbic connectivity changes. Therefore, we sought proof-of-concept for neuromodulation of insula via prefrontal intermittent theta-burst stimulation (iTBS), and how these effects relate to GABAergic and glutamatergic systems. In 27 healthy controls, we employed a single-blind crossover randomised-controlled trial comparing placebo and real iTBS using resting-state functional MRI and magnetic resonance spectroscopy. Granger causal analysis was seeded from right anterior insula (rAI) to locate individualized left DLPFC rTMS targets. Effective connectivity coefficients within rAI and DLPFC were calculated, and levels of GABA/Glx, GABA/Cr and Glx/Cr in DLPFC and anterior cingulate voxels were also measured. ITBS significantly dampened fronto-insular connectivity and reduced GABA/Glx in both voxels. GABA/Glx had a significant mediating effect on iTBS-induced changes in DLPFC-to-rAI connectivity. We demonstrate modulation of the rAI using targeted iTBS through alterations of excitatory/inhibitory interactions, which may underlie therapeutic effects of rTMS, offering promise for rTMS treatment optimization.

PMID: 27651067 [PubMed - indexed for MEDLINE]

Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

Sun, 02/18/2018 - 14:20
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Functional brain connectivity is predictable from anatomic network's Laplacian eigen-structure.

Neuroimage. 2018 Feb 14;:

Authors: Abdelnour F, Dayan M, Devinsky O, Thesen T, Raj A

Abstract
How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses.

PMID: 29454104 [PubMed - as supplied by publisher]

Indices of repetitive behaviour are correlated with patterns of intrinsic functional connectivity in youth with autism spectrum disorder.

Sun, 02/18/2018 - 14:20
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Indices of repetitive behaviour are correlated with patterns of intrinsic functional connectivity in youth with autism spectrum disorder.

Brain Res. 2018 Feb 14;:

Authors: Traynor JM, Doyle-Thomas KAR, Hanford LC, Foster NE, Tryfon A, Hyde KL, Anagnostou E, Evans AC, Zwaigenbaum L, Hall GBC, Asd Imaging Group N

Abstract
The purpose of the current study was to examine how repetitive behaviour in Autism Spectrum Disorder (ASD) is related to intrinsic functional connectivity patterns in a number of large-scale, neural networks. Resting-state fMRI scans from thirty subjects with ASD and thirty-two age-matched, typically developing control subjects were analysed. Seed-to-voxel and ROI-to-ROI functional connectivity analyses were used to examine resting-state connectivity in a number of cortical and subcortical neural networks. Bivariate correlation analysis was performed to examine the relationship between repetitive behaviour scores from the Repetitive Behaviour Scale - Revised and intrinsic functional connectivity in ASD subjects. Compared to control subjects, ASD subjects displayed marked over-connectivity of the thalamus with several cortical sensory processing areas, as well as over-connectivity of the basal ganglia with somatosensory and motor cortices. Within the ASD group, significant correlations were found between functional connectivity patterns and total RBS-R scores as well as one principal component analysis-derived score from the RBS-R. These results suggest that thalamocortical resting-state connectivity is altered in individuals with ASD, and that resting-state functional connectivity is associated with ASD symptomatology.

PMID: 29453959 [PubMed - as supplied by publisher]

Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

Sun, 02/18/2018 - 14:20
Related Articles

Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

Brain Struct Funct. 2018 Feb 16;:

Authors: Patel KR, Tobyne S, Porter D, Bireley JD, Smith V, Klawiter E

Abstract
Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.

PMID: 29453522 [PubMed - as supplied by publisher]

Randomized EEG functional brain networks in major depressive disorders with greater resilience and lower rich-club coefficient.

Sun, 02/18/2018 - 14:20
Related Articles

Randomized EEG functional brain networks in major depressive disorders with greater resilience and lower rich-club coefficient.

Clin Neurophysiol. 2018 Jan 31;129(4):743-758

Authors: Zhang M, Zhou H, Liu L, Feng L, Yang J, Wang G, Zhong N

Abstract
OBJECTIVE: Some studies have shown that the functional electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) networks in those with major depressive disorders (MDDs) have an abnormal random topology. In this study we aimed to further investigate the characteristics of the randomized functional brain networks in MDDs by examining resting-state scalp-EEG data.
METHODS: Based on the methods of independent component analysis (ICA) and graph theoretic analysis, the abnormalities in the power spectral density (PSD) functional brain networks were compared between 13 MDDs and 13 matched healthy controls (HCs). Nonparametric permutation tests were performed to explore the between-group differences in multiple network metrics. The Pearson correlation coefficients were calculated to measure the linear relationships between the clinical symptom and network metrics.
RESULTS: Compared with the HCs, the MDDs showed significant randomization of global network metrics, characterized by greater global efficiency, but lower clustering coefficient, characteristic path length, and local efficiency. This randomization was also reflected in the less heterogeneous and less fat-tailed degree distributions in the MDDs. More importantly, the randomized brain networks in MDDs had greater network resilience to both random failure and targeted attack, which might be a protective mechanism to avoid fast deterioration of the integrity of MDDs' brain networks under pathological attack. In addition, the randomized brain networks in MDDs had a lower level of rich-club coefficient, suggesting that the density of connections among rich-club hubs became sparser. Furthermore, some of the network metrics explored in this study were significantly associated with the severity of depression in all participants.
CONCLUSIONS: A replicable randomization of the brain network is found in MDDs. The randomization is further characterized by more homogeneous degree distribution, greater resilience and lower rich-club coefficient, reflecting the reconfiguration of the brain network caused by the reduction of hub nodes in MDD.
SIGNIFICANCE: Our results may provide new biomarkers of brain network organization in MDD.

PMID: 29453169 [PubMed - as supplied by publisher]

Characterizing the modulation of resting-state fMRI metrics by baseline physiology.

Sat, 02/17/2018 - 12:20

Characterizing the modulation of resting-state fMRI metrics by baseline physiology.

Neuroimage. 2018 Feb 13;:

Authors: Chu PPW, Golestani AM, Kwinta JB, Khatamian YB, Chen JJ

Abstract
The blood-oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal is commonly used to assess functional connectivity across brain regions, particularly in the resting state (rs-fMRI). However, the BOLD fMRI signal is not merely a representation of neural activity, but a combination of neural activity and vascular response. These aspects of the BOLD signal are easily influenced by systemic physiology, potentially biasing BOLD-based functional connectivity measurements. In this work, we focus on the following physiological modulators of the BOLD signal: cerebral blood flow (CBF), venous blood oxygenation, and cerebrovascular reactivity (CVR). We use simulations and experiments to examine the relationship between the physiological parameters and rs-fMRI functional connectivity measurements in three resting-state networks: default mode network, somatosensory network and visual network. By using the general linear model, we demonstrate that physiological modulators significantly impact functional connectivity measurements in these regions, but in a manner that depends on the interplay between signal- and noise-driven correlations. Moreover, we find that the physiological effects vary by brain region and depend on the range of physiological conditions probed; the associations are more complex than previously reported. The results confirm that it is important to account for the effect of physiological modulators when comparing resting-state fMRI metrics. We note that such modulatory effects may be amplified by disease conditions, which will warrant future investigations.

PMID: 29452265 [PubMed - as supplied by publisher]

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