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A principled multivariate intersubject analysis of Generalized Partial Directed Coherence with Dirichlet Regression: application to healthy aging in areas exhibiting cortical thinning.

Wed, 11/07/2018 - 14:09
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A principled multivariate intersubject analysis of Generalized Partial Directed Coherence with Dirichlet Regression: application to healthy aging in areas exhibiting cortical thinning.

J Neurosci Methods. 2018 Oct 27;:

Authors: Vieira BH, Garrido Salmon CE

Abstract
BACKGROUND: Generalized Partial Directed Coherence (GPDC) is a multivariate measure of predictability between functional timeseries defined in the frequency domain. However, analysis has often been constrained by its compositional nature. Specifically, the squared GPDC from a node region to all nodes in any given frequency must sum to one.
NEW METHOD: When analyzing GPDC spectra, it is imperative to consider that squared GPDC from a source timeseries sums to one over its target timeseries. Dirichlet Regression allows the modeling of compositional data and, therefore, becomes a principled choice for the multivariate analysis of GPDC on arbitrary subject-level variables.
RESULTS: Eleven resting-state fMRI connections underwent age-related alterations, with two decreases in squared GPDC from a region to itself in two frequencies, signaling increased integration with the rest, and nine increases in squared GPDC, one involving different regions. All frequencies had at least one alteration due to age.
COMPARISON WITH EXISTING METHOD(S): Our methodology identifies alterations in GPDC in more connections than a naïve approach based on linear regression and centered log-ratio analysis. We also studied alternative connectivity indices between the same ROIs, uncovering no effect of age on the time-domain predictive-causality metrics for any connection, while for Pearson correlation five connections displayed significant effects of age, with parallels to the results pertaining to GPDC.
CONCLUSIONS: Dirichlet Regression allows the study of continuous or discrete variables as predictors for the analysis of GPDC, enabling a wider adoption of this measure of connectivity.

PMID: 30392951 [PubMed - as supplied by publisher]

Functional connectivity in ASD: Atypical pathways in brain networks supporting action observation and joint attention.

Wed, 11/07/2018 - 14:09
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Functional connectivity in ASD: Atypical pathways in brain networks supporting action observation and joint attention.

Brain Res. 2018 Oct 27;:

Authors: Delbruck E, Yang M, Yassine A, Grossman ED

Abstract
Autism Spectrum Disorder (ASD) is a developmental disorder characterized by impaired social communication, including attending to and interpreting social cues, initiating and responding to joint attention, and engaging in abstract social cognitive reasoning. Current studies emphasize a underconnectivity in ASD, particularly for brain systems that support abstract social reasoning and introspective thought. Here, we evaluate intrinsic connectivity in children with ASD, targeting brain systems that support the developmental precursors to social reasoning, namely perception of social cues and joint attention. Using resting state fMRI made available through the Autism Brain Imaging Data Exchange (ABIDE), we compute functional connectivity within and between nodes in the action observation, attention and social cognitive networks in children and adolescents with ASD. We also compare connectivity strength to observational assessments that explicitly evaluate severity of ASD on two distinct subdomains using the ADOS-Revised schedule: social affective (SA) and restricted, repetitive behaviors (RRB). Compared to age-matched controls, children with ASD have decreased functional connectivity in a number of connections in the action observation network, particularly in the lateral occipital cortex (LOTC) and fusiform gyrus (FG). Distinct patterns of connections were also correlated with symptom severity on the two subdomains of the ADOS. ADOS-SA severity most strongly correlated with connectivity to the left TPJ, while ADOS-RRB severity correlated with connectivity to the dMPFC. We conclude that atypical connectivity in the action observation system may underlie some of the more complex deficits in social cognitive systems in ASD.

PMID: 30392771 [PubMed - as supplied by publisher]

Associations between children's family environment, spontaneous brain oscillations, and emotional and behavioral problems.

Wed, 11/07/2018 - 14:09
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Associations between children's family environment, spontaneous brain oscillations, and emotional and behavioral problems.

Eur Child Adolesc Psychiatry. 2018 Nov 03;:

Authors: Sato JR, Biazoli CE, Salum GA, Gadelha A, Crossley N, Vieira G, Zugman A, Picon FA, Pan PM, Hoexter MQ, Amaro E, Anés M, Moura LM, Del'Aquilla MAG, Mcguire P, Rohde LA, Miguel EC, Bressan RA, Jackowski AP

Abstract
The family environment in childhood has a strong effect on mental health outcomes throughout life. This effect is thought to depend at least in part on modifications of neurodevelopment trajectories. In this exploratory study, we sought to investigate whether a feasible resting-state fMRI metric of local spontaneous oscillatory neural activity, the fractional amplitude of low-frequency fluctuations (fALFF), is associated with the levels of children's family coherence and conflict. Moreover, we sought to further explore whether spontaneous activity in the brain areas influenced by family environment would also be associated with a mental health outcome, namely the incidence of behavioral and emotional problems. Resting-state fMRI data from 655 children and adolescents (6-15 years old) were examined. The quality of the family environment was found to be positively correlated with fALFF in the left temporal pole and negatively correlated with fALFF in the right orbitofrontal cortex. Remarkably, increased fALFF in the temporal pole was associated with a lower incidence of behavioral and emotional problems, whereas increased fALFF in the orbitofrontal cortex was correlated with a higher incidence.

PMID: 30392120 [PubMed - as supplied by publisher]

Changes in resting-state functional brain activity are associated with waning cognitive functions in HIV-infected children.

Wed, 11/07/2018 - 14:09
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Changes in resting-state functional brain activity are associated with waning cognitive functions in HIV-infected children.

Neuroimage Clin. 2018 Oct 29;20:1204-1210

Authors: Yadav SK, Gupta RK, Hashem S, Bhat AA, Garg RK, Venkatesh V, Gupta PK, Singh AK, Chaturvedi S, Ahmed SN, Azeem MW, Haris M

Abstract
Delayed brain development in perinatally HIV-infected children may affect the functional brain activity and subsequently cognitive function. The current study evaluated the functional brain activity in HIV-infected children by quantifying the amplitude of low frequency fluctuations (ALFF) and functional connectivity (FC). Additionally, correlation of ALFF and FC with cognitive measures was performed. Twenty-six HIV-infected children and 20 control children underwent neuropsychological (NP) assessment and resting-state functional magnetic resonance imaging (rs-fMRI). ALFF and FC maps were generated and group differences were analyzed using two-sample t-test. Furthermore, ALFF and FC showing significant group differences were correlated with NP scores using Pearson's correlation. Significantly lower ALFF in the left middle temporal gyrus, precentral and post central gyrus was observed in HIV-infected children compared to controls. FC was significantly reduced in the right inferior parietal, vermis, middle temporal and left postcentral regions, and significantly increased in the right precuneus, superior parietal and left middle frontal regions in HIV-infected children as compared to control. HIV-infected children showed significantly lower NP scores in various domains including closure, exclusion, memory, verbal meaning, quantity and hidden figure than controls. These waning cognitive functions were significantly associated with changes in ALFF and FC in HIV-infected children. The findings suggest that abnormal ALFF and FC may responsible for cognitive deficits in HIV-infected children. ALFF and FC in association with cognitive evaluation may provide a clinical biomarker to evaluate functional brain activity and to plan neurocognitive intervention in HIV-infected children undergoing standard treatment.

PMID: 30391858 [PubMed - as supplied by publisher]

Reward and executive control network resting-state functional connectivity is associated with impulsivity during reward-based decision making for cocaine users.

Wed, 11/07/2018 - 14:09
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Reward and executive control network resting-state functional connectivity is associated with impulsivity during reward-based decision making for cocaine users.

Drug Alcohol Depend. 2018 Oct 24;194:32-39

Authors: Hobkirk AL, Bell RP, Utevsky AV, Huettel S, Meade CS

Abstract
BACKGROUND: Cocaine addiction is related to impulsive decision making that is mediated by brain circuitry involved in reward processing and executive functions, such as cognitive control and attentional salience. Resting-state functional connectivity between reward and executive control circuitry is altered among cocaine users, with concomitant deficits in impulsivity and learning. Prior research has examined how select brain regions interact to influence impulsive decision making for drug users; however, research examining interactions between large-scale brain networks and impulsive behavior is limited.
METHODS: The current study compared reward and executive control network resting-state functional connectivity and its relationship to impulsive decision making between cocaine users (n = 37) and non-cocaine using control participants (n = 35). Participants completed computerized decision-making tasks and a separate resting-state functional magnetic resonance imaging scan. Data underwent independent component, dual regression, and linear regression moderation analyses.
RESULTS: Higher impulsivity on the Balloon Analogue Risk Task (BART) was associated with inverse resting-state connectivity between the left cognitive control and subgenual anterior cingulate extended reward networks for cocaine users, while the opposite was found for controls. Less impulsivity on the monetary choice questionnaire was associated with stronger positive resting-state connectivity between the attentional salience and striatal core reward networks for controls, while cocaine users showed no association between impulsivity and resting-state connectivity of these networks.
CONCLUSIONS: Cocaine users show aberrant associations between reward-executive control resting-state network coupling and impulsive decision making. The findings support the conclusion that an imbalance between reward and executive control circuitry contributes to impulsivity in drug use.

PMID: 30391836 [PubMed - as supplied by publisher]

Optimizing fMRI experimental design for MVPA-based BCI control: Combining the strengths of block and event-related designs.

Wed, 11/07/2018 - 14:09
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Optimizing fMRI experimental design for MVPA-based BCI control: Combining the strengths of block and event-related designs.

Neuroimage. 2018 Oct 31;:

Authors: Valente G, Kaas A, Formisano E, Goebel R

Abstract
Functional Magnetic Resonance Imaging (fMRI) has been successfully used for Brain Computer Interfacing (BCI) to classify (imagined) movements of different limbs. However, reliable classification of more subtle signals originating from co-localized neural networks in the sensorimotor cortex, e.g. individual movements of fingers of the same hand, has proved to be more challenging, especially when taking into account the requirement for high single trial reliability in the BCI context. In recent years, Multi Voxel Pattern Analysis (MVPA) has gained momentum as a suitable method to disclose such weak, distributed activation patterns. Much attention has been devoted to developing and validating data analysis strategies, but relatively little guidance is available on the choice of experimental design, even less so in the context of BCI-MVPA. When applicable, block designs are considered the safest choice, but the expectations, strategies and adaptation induced by blocking of similar trials can make it a sub-optimal strategy. Fast event-related designs, in contrast, require a more complicated analysis and show stronger dependence on linearity assumptions but allow for randomly alternating trials. However, they lack resting intervals that enable the BCI participant to process feedback. In this proof-of-concept paper a hybrid blocked fast-event related design is introduced that is novel in the context of MVPA and BCI experiments, and that might overcome these issues by combining the rest periods of the block design with the shorter and randomly alternating trial characteristics of a rapid event-related design. A well-established button-press experiment was used to perform a within-subject comparison of the proposed design with a block and a slow event-related design. The proposed hybrid blocked fast-event related design showed a decoding accuracy that was close to that of the block design, which showed highest accuracy. It allowed for across-design decoding, i.e. reliable prediction of examples obtained with another design. Finally, it also showed the most stable incremental decoding results, obtaining good performance with relatively few blocks. Our findings suggest that the blocked fast event-related design could be a viable alternative to block designs in the context of BCI-MVPA, when expectations, strategies and adaptation make blocking of trials of the same type a sub-optimal strategy. Additionally, the blocked fast event-related design is also suitable for applications in which fast incremental decoding is desired, and enables the use of a slow or block design during the test phase.

PMID: 30391345 [PubMed - as supplied by publisher]

Preoperative localization of the sensorimotor cortex and measurement of tumor perfusion in a single acquisition using ASL technique.

Wed, 11/07/2018 - 14:09
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Preoperative localization of the sensorimotor cortex and measurement of tumor perfusion in a single acquisition using ASL technique.

J Clin Neurosci. 2018 Oct 31;:

Authors: Kim JH, Choi DS, Park SE, Choi HC, Koh EH, Kim SH

Abstract
Resting state fMRI (rs-fMRI) using arterial spin labelling (ASL) technique was performed for the preoperative localization of the sensorimotor cortex in a patient with lymphoma and the results were compared to those of task-based (tb) and rs-fMRI studies using blood oxygenation level-dependent (BOLD) sequence. Rs-fMRI using ASL showed similar results in the regions of the sensorimotor network to those of tb- and rs-fMRI fMRI using BOLD. ASL technique has a potential in clinical practice because all of brain perfusion imaging, cerebral blood flow measurement, and rs-fMRI study can be performed at a single acquisition.

PMID: 30391311 [PubMed - as supplied by publisher]

Intersubject similarity of personality is associated with intersubject similarity of brain connectivity patterns.

Wed, 11/07/2018 - 14:09
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Intersubject similarity of personality is associated with intersubject similarity of brain connectivity patterns.

Neuroimage. 2018 Oct 30;:

Authors: Liu W, Kohn N, Fernández G

Abstract
Personality is a central high-level psychological concept that defines individual human beings and has been associated with a variety of real-world outcomes (e.g., mental health and academic performance). Using 2 h, high resolution, functional magnetic resonance imaging (fMRI) resting state data of 984 (primary dataset N = 801, hold-out dataset N = 183) participants from the Human Connectome Project (HCP), we investigated the relationship between personality (five-factor model, FFM) and intrinsic whole-brain functional connectome. We found a pattern of functional brain connectivity ("global personality network") related to personality traits. Consistent with the heritability of personality traits, the connectivity strength of this global personality network is also heritable (more similar between monozygotic twin pairs compared to the dizygotic twin pairs). Validated by both the repeated family-based 10-fold cross-validation and hold-out dataset, our intersubject network similarity analysis allowed us to identify participants' pairs with similar personality profiles. Across all the identified pairs of participants, we found a positive correlation between the network similarity and personality similarity, supporting our "similar brain, similar personality" hypothesis. Furthermore, the global personality network can be used to predict the individual subject's responses in the personality questionnaire on an item level. In sum, based on individual brain connectivity pattern, we could predict different facets of personality, and this prediction is not based on localized regions, but rather relies on the individual connectivity pattern in large-scale brain networks.

PMID: 30389630 [PubMed - as supplied by publisher]

Decreased subregional specificity of the putamen in Parkinson's Disease revealed by dynamic connectivity-derived parcellation.

Sun, 11/04/2018 - 10:24

Decreased subregional specificity of the putamen in Parkinson's Disease revealed by dynamic connectivity-derived parcellation.

Neuroimage Clin. 2018 Oct 23;20:1163-1175

Authors: Liu A, Lin SJ, Mi T, Chen X, Chan P, Wang ZJ, McKeown MJ

Abstract
Parkinson's Disease (PD) is associated with decreased ability to perform habitual tasks, relying instead on goal-directed behaviour subserved by different cortical/subcortical circuits, including parts of the putamen. We explored the functional subunits in the putamen in PD using novel dynamic connectivity features derived from resting state fMRI recorded from thirty PD subjects and twenty-eight age-matched healthy controls (HC). Dynamic functional segmentation of the putamina was obtained by determining the correlation between each voxel in each putamen along a moving window and applying a joint temporal clustering algorithm to establish cluster membership of each voxel at each window. Contiguous voxels that had consistent cluster membership across all windows were then considered to be part of a homogeneous functional subunit. As PD subjects robustly had two homogenous clusters in the putamina, we also segmented the putamina in HC into two dynamic clusters for a fair comparison. We then estimated the dynamic connectivity using sliding windowed correlation between the mean signal from the identified homogenous subunits and 56 other predefined cortical and subcortical ROIs. Specifically, the mean dynamic connectivity strength and connectivity deviation were then compared to evaluate subregional differences. HC subjects had significant differences in mean dynamic connectivity and connectivity deviation between the two putaminal subunits. The posterior subunit connected strongly to sensorimotor areas, the cerebellum, as well as the middle frontal gyrus. The anterior subunit had strong mean dynamic connectivity to the nucleus accumbens, hippocampus, amygdala, caudate and cingulate. In contrast, PD subjects had fewer differences in mean dynamic connectivity between subunits, indicating a degradation of subregional specificity. Overall UPDRS III and MoCA scores could be predicted using mean dynamic connectivity strength and connectivity deviation. Side of onset of the disease was also jointly related with functional connectivity features. Our results suggest a robust loss of specificity of mean dynamic connectivity and connectivity deviation in putaminal subunits in PD that is sensitive to disease severity. In addition, altered mean dynamic connectivity and connectivity deviation features in PD suggest that looking at connectivity dynamics offers an additional dimension for assessment of neurodegenerative disorders.

PMID: 30388599 [PubMed - as supplied by publisher]

Altered resting-state functional connectivity in children and adolescents born very preterm short title.

Sun, 11/04/2018 - 10:24

Altered resting-state functional connectivity in children and adolescents born very preterm short title.

Neuroimage Clin. 2018 Oct 03;20:1148-1156

Authors: Wehrle FM, Michels L, Guggenberger R, Huber R, Latal B, O'Gorman RL, Hagmann CF

Abstract
The formation of resting-state functional networks in infancy has been reported to be strongly impacted by very preterm birth. Studies in childhood and adolescence have largely focused on language processing networks and identified both decreased and increased functional connectivity. It is unclear, however, whether functional connectivity strength is altered globally in children and adolescents born very preterm and whether these alterations are related to the frequently occurring cognitive deficits. Here, resting-state functional MRI was assessed in a group of 32 school-aged children and adolescents born very preterm with normal intellectual and motor abilities and 39 healthy term-born peers. Functional connectivity within and between a comprehensive set of well-established resting-state networks was compared between the groups. IQ and executive function abilities were tested with standardized tasks and potential associations with connectivity strength were explored. Functional connectivity was weaker in the very preterm compared to the term-born group between the sensorimotor network and the visual and dorsal attention network, within the sensorimotor network and within the central executive network. In contrast, functional connectivity was stronger in the very preterm group between the sensorimotor network and parts of the salience and the central executive network. Little evidence was found that these alterations underlie lower IQ or poorer executive function abilities. This study provides evidence for a long-lasting impact of very preterm birth on the organization of resting-state networks. The potential consequence of these alterations for other neurodevelopmental domains than the ones investigated in the current study warrants further investigation.

PMID: 30388598 [PubMed - as supplied by publisher]

Interaction of Developmental Venous Anomalies with Resting-State Functional MRI Measures.

Sun, 11/04/2018 - 10:24
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Interaction of Developmental Venous Anomalies with Resting-State Functional MRI Measures.

AJNR Am J Neuroradiol. 2018 Nov 01;:

Authors: Sundermann B, Pfleiderer B, Minnerup H, Berger K, Douaud G

Abstract
BACKGROUND AND PURPOSE: Functional MR imaging of the brain, used for both clinical and neuroscientific applications, relies on measuring fluctuations in blood oxygenation. Such measurements are susceptible to noise of vascular origin. The purpose of this study was to assess whether developmental venous anomalies, which are frequently observed normal variants, can bias fMRI measures by appearing as true neural signal.
MATERIALS AND METHODS: Large developmental venous anomalies (1 in each of 14 participants) were identified from a large neuroimaging cohort (n = 814). Resting-state fMRI data were decomposed using independent component analysis, a data-driven technique that creates distinct component maps representing aspects of either structured noise or true neural activity. We searched all independent components for maps that exhibited a spatial distribution of their signals following the topography of developmental venous anomalies.
RESULTS: Of the 14 developmental venous anomalies identified, 10 were clearly present in 17 fMRI independent components in total. While 9 (52.9%) of these 17 independent components were dominated by venous contributions and 2 (11.8%) by motion artifacts, 2 independent components (11.8%) showed partial neural signal contributions and 5 independent components (29.4%) unambiguously exhibited typical neural signal patterns.
CONCLUSIONS: Developmental venous anomalies can strongly resemble neural signal as measured by fMRI. They are thus a potential source of bias in fMRI analyses, especially when present in the cortex. This could impede interpretation of local activity in patients, such as in presurgical mapping. In scientific studies with large samples, developmental venous anomaly confounds could be mainly addressed using independent component analysis-based denoising.

PMID: 30385467 [PubMed - as supplied by publisher]

Functional connectivity between the thalamus and the primary somatosensory cortex in major depressive disorder: a resting-state fMRI study.

Mon, 10/22/2018 - 19:21
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Functional connectivity between the thalamus and the primary somatosensory cortex in major depressive disorder: a resting-state fMRI study.

BMC Psychiatry. 2018 Oct 19;18(1):339

Authors: Kang L, Zhang A, Sun N, Liu P, Yang C, Li G, Liu Z, Wang Y, Zhang K

Abstract
BACKGROUND: Studies have confirmed that the thalamus and the primary somatosensory cortex (SI) are associated with cognitive function. These two brain regions are closely related in structure and function. The interactions between SI and the thalamus are of crucial significance for the cognitive process. Patients with major depressive disorder (MDD) have significant cognitive impairment. Based on these observations, we used resting-state functional magnetic resonance imaging (rs-fMRI) to investigate whether there is an abnormality in the SI-thalamic functional connection in MDD. Furthermore, we explored the clinical symptoms related to this abnormality.
METHODS: We included 31 patients with first-episode major depressive disorder and 28 age-, gender-, and education-matched healthy controls (HC). The SI-thalamic functional connectivity was compared between the MDD and HC groups. The correlation analyses were performed between areas with abnormal connectivity and clinical characteristics.
RESULTS: Compared with healthy subjects, the MDD patients had enhanced functional connectivity between the thalamus and SI (p < 0.05, corrected). Brain areas with significantly different levels of connectivity had a negative correlation with the Assessment of Neuropsychological Status total score (r = - 0.383, p = 0.033), delayed memory score (r = - 0.376, p = 0.037) and two-digit continuous operation test score (r = - 0.369, p = 0.041) in MDD patients.
CONCLUSIONS: These results demonstrate that SI-thalamic functional connectivity is abnormal and associated with the core clinical symptoms in MDD. The SI-thalamic functional connectivity functions as a neurobiological feature and potential biomarker for MDD.

PMID: 30340472 [PubMed - in process]

A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas.

Sat, 10/20/2018 - 14:48
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A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas.

PLoS Comput Biol. 2018 Oct;14(10):e1006359

Authors: Schmidt M, Bakker R, Shen K, Bezgin G, Diesmann M, van Albada SJ

Abstract
Cortical activity has distinct features across scales, from the spiking statistics of individual cells to global resting-state networks. We here describe the first full-density multi-area spiking network model of cortex, using macaque visual cortex as a test system. The model represents each area by a microcircuit with area-specific architecture and features layer- and population-resolved connectivity between areas. Simulations reveal a structured asynchronous irregular ground state. In a metastable regime, the network reproduces spiking statistics from electrophysiological recordings and cortico-cortical interaction patterns in fMRI functional connectivity under resting-state conditions. Stable inter-area propagation is supported by cortico-cortical synapses that are moderately strong onto excitatory neurons and stronger onto inhibitory neurons. Causal interactions depend on both cortical structure and the dynamical state of populations. Activity propagates mainly in the feedback direction, similar to experimental results associated with visual imagery and sleep. The model unifies local and large-scale accounts of cortex, and clarifies how the detailed connectivity of cortex shapes its dynamics on multiple scales. Based on our simulations, we hypothesize that in the spontaneous condition the brain operates in a metastable regime where cortico-cortical projections target excitatory and inhibitory populations in a balanced manner that produces substantial inter-area interactions while maintaining global stability.

PMID: 30335761 [PubMed - in process]

Intranetwork and Internetwork Effects of Navigated Transcranial Magnetic Stimulation Using Low- and High-frequency Pulse Application to the Dorsolateral Prefrontal Cortex-A Combined rTMS-fMRI Approach.

Sat, 10/20/2018 - 14:48
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Intranetwork and Internetwork Effects of Navigated Transcranial Magnetic Stimulation Using Low- and High-frequency Pulse Application to the Dorsolateral Prefrontal Cortex-A Combined rTMS-fMRI Approach.

J Clin Neurophysiol. 2018 Oct 17;:

Authors: Zhang H, Sollmann N, Castrillón G, Kurcyus K, Meyer B, Zimmer C, Krieg SM

Abstract
PURPOSE: Although transcranial magnetic stimulation (TMS) is routinely applied in neuroscience and clinical settings, not much is known about its effects on brain networks. Therefore, this pilot study was set up using repetitive navigated transcranial magnetic stimulation (rTMS) combined with resting-state functional MRI (rs-fMRI) to explore frequency-dependent stimulation effects on an intranetwork and internetwork level.
METHODS: Six healthy subjects (median age: 23.5 years) underwent two rTMS sessions (1 and 10 Hz), 7 days apart, and prestimulation and poststimulation rs-fMRI. Repetitive navigated transcranial magnetic stimulation was delivered to the left dorsolateral prefrontal cortex, with the exact stimulation target being determined by independent component analysis. Alterations of functional connectivity strength were evaluated using seed-based correlation analyses within and between the salience network, central executive network, and posterior and anterior default mode network.
RESULTS: Low-frequency rTMS resulted in significant intranetwork alterations only for the anterior default mode network and primarily within the left hemisphere. In contrast, high-frequency rTMS led to changes within all four networks of interest. Moreover, the posterior and anterior default mode network largely showed opposite effects to rTMS, and the anterior default mode network was rather isolated from the other networks, which was especially true for low-frequency rTMS. Changes in functional connectivity strength because of low-frequency rTMS were even detectable 7 days after stimulation.
CONCLUSIONS: This is one of the first studies using neuronavigated TMS with independent component analysis-based target selection to explore frequency-dependent stimulation effects in a combined rTMS-fMRI approach. Future studies including higher subject numbers may define the underlying mechanisms for the different responses to low- and high-frequency rTMS.

PMID: 30335664 [PubMed - as supplied by publisher]

Do Sensory Stimulation Programs Have an Impact on Consciousness Recovery?

Sat, 10/20/2018 - 14:48
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Do Sensory Stimulation Programs Have an Impact on Consciousness Recovery?

Front Neurol. 2018;9:826

Authors: Cheng L, Cortese D, Monti MM, Wang F, Riganello F, Arcuri F, Di H, Schnakers C

Abstract
Objectives: Considering sensory stimulation programs (SSP) as a treatment for disorders of consciousness is still debated today. Previous studies investigating its efficacy were affected by various biases among which small sample size and spontaneous recovery. In this study, treatment-related changes were assessed using time-series design in patients with disorders of consciousness (i.e., vegetative state-VS and minimally conscious state-MCS). Methods: A withdrawal design (ABAB) was used. During B phases, patients underwent a SSP (3 days a week, including auditory, visual, tactile, olfactory, and gustatory stimulation). The program was not applied during A phases. To assess behavioral changes, the Coma Recovery Scale-Revised (CRS-R) was administered by an independent rater on a weekly basis, across all phases. Each phase lasted 4 weeks. In a subset of patients, resting state functional magnetic resonance imaging (fMRI) data were collected at the end of each phase. Results: Twenty nine patients (48 ± 19 years old; 15 traumatic; 21 > a year post-injury; 11 VS and 18 MCS) were included in our study. Higher CRS-R total scores (medium effect size) as well as higher arousal and oromotor subscores were observed in the B phases (treatment) as compared to A phases (no treatment), in the MCS group but not in the VS group. In the three patients who underwent fMRI analyses, a modulation of metabolic activity related to treatment was observed in middle frontal gyrus, superior temporal gyrus as well as ventro-anterior thalamic nucleus. Conclusion: Our results suggest that SSP may not be sufficient to restore consciousness. SSP might nevertheless lead to improved behavioral responsiveness in MCS patients. Our results show higher CRS-R total scores when treatment is applied, and more exactly, increased arousal and oromotor functions.

PMID: 30333789 [PubMed]

Effects of stress on behavior and resting-state fMRI in rats and evaluation of Telmisartan therapy in a stress-induced depression model.

Sat, 10/20/2018 - 14:48
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Effects of stress on behavior and resting-state fMRI in rats and evaluation of Telmisartan therapy in a stress-induced depression model.

BMC Psychiatry. 2018 Oct 17;18(1):337

Authors: Li J, Yang R, Xia K, Wang T, Nie B, Gao K, Chen J, Zhao H, Li Y, Wang W

Abstract
BACKGROUND: The etiology of depression and its effective therapeutic treatment have not been clearly identified. Using behavioral phenotyping and resting-state functional magnetic resonance imaging (r-fMRI), we investigated the behavioral impact and cerebral alterations of chronic unpredictable mild stress (CUMS) in the rat. We also evaluated the efficacy of telmisartan therapy in this rodent model of depression.
METHODS: Thirty-two rats were divided into 4 groups: a control group(C group), a stress group(S group), a stress + telmisartan(0.5 mg/kg)group (T-0.5 mg/kg group) and a stress + telmisartan(1 mg/kg) group (T-1 mg/kg group). A behavioral battery, including an open field test (OFT), a sucrose preference test (SPT), and an object recognition test (ORT), as well as r-fMRI were conducted after 4 weeks of CUMS and telmisartan therapy. The r-fMRI data were analyzed using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) approach. The group differences in the behavior and r-fMRI test results as well as the correlations between these 2 approaches were examined.
RESULTS: CUMS reduced the number of rearings and the total moved distance in OFT, the sucrose preference in SPT, and novel object recognition ability in ORT. The telmisartan treatment (1 mg/kg) significantly improved B-A/B + A in the ORT and improved latency scores in the OFT and SPT. The S group exhibited a decreased ReHo in the motor cortex and pons, but increased ReHo in the thalamus, visual cortex, midbrain, cerebellum, hippocampus, hypothalamus, and olfactory cortex compared to the C group. Telmisartan (1 mg/kg)reversed or attenuated the stress-induced changes in the motor cortex, midbrain, thalamus, hippocampus, hypothalamus, visual cortex, and olfactory cortex. A negative correlation was found between OFT rearing and ReHo values in the thalamus. Two positive correlations were found between ORT B-A and the ReHo values in the olfactory cortexand pons.
CONCLUSIONS: Telmisartan may be an effective complementary drug for individuals with depression who also exhibit memory impairments. Stress induced widespread regional alterations in the cerebrum in ReHo measures while telmissartan can reverse part of theses alterations. These data lend support for future research on the pathology of depression and provide a new insight into the effects of telmisartan on brain function in depression.

PMID: 30333002 [PubMed - in process]

On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease.

Thu, 10/18/2018 - 10:07
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On the Extraction and Analysis of Graphs From Resting-State fMRI to Support a Correct and Robust Diagnostic Tool for Alzheimer's Disease.

Front Neurosci. 2018;12:528

Authors: Bachmann C, Jacobs HIL, Porta Mana P, Dillen K, Richter N, von Reutern B, Dronse J, Onur OA, Langen KJ, Fink GR, Kukolja J, Morrison A

Abstract
The diagnosis of Alzheimer's disease (AD), especially in the early stage, is still not very reliable and the development of new diagnosis tools is desirable. A diagnosis based on functional magnetic resonance imaging (fMRI) is a suitable candidate, since fMRI is non-invasive, readily available, and indirectly measures synaptic dysfunction, which can be observed even at the earliest stages of AD. However, the results of previous attempts to analyze graph properties of resting state fMRI data are contradictory, presumably caused by methodological differences in graph construction. This comprises two steps: clustering the voxels of the functional image to define the nodes of the graph, and calculating the graph's edge weights based on a functional connectivity measure of the average cluster activities. A variety of methods are available for each step, but the robustness of results to method choice, and the suitability of the methods to support a diagnostic tool, are largely unknown. To address this issue, we employ a range of commonly and rarely used clustering and edge definition methods and analyze their graph theoretic measures (graph weight, shortest path length, clustering coefficient, and weighted degree distribution and modularity) on a small data set of 26 healthy controls, 16 subjects with mild cognitive impairment (MCI) and 14 with Alzheimer's disease. We examine the results with respect to statistical significance of the mean difference in graph properties, the sensitivity of the results to model and parameter choices, and relative diagnostic power based on both a statistical model and support vector machines. We find that different combinations of graph construction techniques yield contradicting, but statistically significant, relations of graph properties between health conditions, explaining the discrepancy across previous studies, but casting doubt on such analyses as a method to gain insight into disease effects. The production of significant differences in mean graph properties turns out not to be a good predictor of future diagnostic capacity. Highest predictive power, expressed by largest negative surprise values, are achieved for both atlas-driven and data-driven clustering (Ward clustering), as long as graphs are small and clusters large, in combination with edge definitions based on correlations and mutual information transfer.

PMID: 30323734 [PubMed]

Modulation of prefrontal connectivity in postherpetic neuralgia patients with chronic pain: a resting-state functional magnetic resonance-imaging study.

Thu, 10/18/2018 - 10:07
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Modulation of prefrontal connectivity in postherpetic neuralgia patients with chronic pain: a resting-state functional magnetic resonance-imaging study.

J Pain Res. 2018;11:2131-2144

Authors: Li J, Huang X, Sang K, Bodner M, Ma K, Dong XW

Abstract
Background: Although the interaction between pain and cognition has been recognized for decades, the neural substrates underlying their association remain unclear. The prefrontal cortex (PFC) is known as a critical brain area for higher cognitive functions, as well as for pain perception and modulation. The objective of the present study was to explore the role of the PFC in the interaction between chronic pain and cognitive functions by examining the relationship between spontaneous activity in the frontal lobe and pain intensity reported by postherpetic neuralgia (PHN) patients.
Methods: Resting-state functional magnetic resonance imaging data from 16 PHN patients were collected, and regional homogeneity and related functional connectivity were analyzed.
Results: The results showed negative correlations between patients' pain scores and regional homogeneity values in several prefrontal areas, including the left lateral PFC, left medial PFC, and right lateral orbitofrontal cortex (P<0.05, AlphaSim-corrected). Further analysis revealed that the functional connectivity of some of these prefrontal areas with other cortical regions was also modulated by pain intensity. Therefore, functional connections of the left lateral PFC with both the left parietal cortex and the left occipital cortex were correlated with patients' pain ratings (P<0.05, AlphaSim-corrected). Similarly, functional connectivity between the right lateral orbitofrontal cortex and bilateral postcentral/precentral gyri was also correlated with pain intensity in the patients (P<0.05, AlphaSim-corrected).
Conclusion: Our findings indicate that activity in the PFC is modulated by chronic pain in PHN patients. The pain-related modulation of prefrontal activity may serve as the neural basis for interactions between chronic pain and cognitive functions, which may link to cognitive impairments observed in chronic pain patients.

PMID: 30323648 [PubMed]

Alterations in patients with major depressive disorder before and after electroconvulsive therapy measured by fractional amplitude of low-frequency fluctuations (fALFF).

Wed, 10/17/2018 - 18:00

Alterations in patients with major depressive disorder before and after electroconvulsive therapy measured by fractional amplitude of low-frequency fluctuations (fALFF).

J Affect Disord. 2018 Oct 09;244:92-99

Authors: Qiu H, Li X, Luo Q, Li Y, Zhou X, Cao H, Zhong Y, Sun M

Abstract
BACKGROUND: Electroconvulsive therapy (ECT) is an important treatment option for patients with major depressive disorder (MDD). However, the mechanisms of ECT in MDD are still unclear.
METHODS: Twenty-four patients with severe MDD and 14 healthy controls were enrolled in this study. Eight ECT sessions were conducted for MDD patients using brief-pulse square-wave signal at bitemporal locations. To investigate the regional cerebral blood flow in MDD patients before and after ECT treatments by resting-state functional magnetic resonance imaging (rs-fMRI), the patients were scanned twice (before the first ECT and after the eighth ECT) for data acquisition. Afterward, we adopted fractional amplitude of low-frequency fluctuations (fALFF) to assess the alterations of regional brain activity.
RESULTS: Compared with healthy controls, the fALFF in the cerebellum lobe, parahippocampal gyrus, fusiform gyrus, anterior cingulate gyrus, and thalamus in MDD patients before ECT (pre-ECT) was significantly increased. In another comparison, the fALFF in the cerebellum anterior lobe, fusiform gyrus, insula, parahippocampal gyrus, middle frontal gyrus, and inferior frontal gyrus in pre-ECT patients was significantly greater than the post-ECT fALFF.
LIMITATIONS: Only two rs-fMRI scans were conducted at predefined times: before the first and after the eighth ECT treatment. More scans during the ECT sessions would yield more information. In addition, the sample size in this study was limited. The number of control subjects was relatively small. A larger number of subjects would produce more robust findings.
CONCLUSIONS: The fALFF of both healthy controls and post-ECT patients in cerebellum anterior lobe, fusiform gyrus, and parahippocampal gyrus is significantly lower than the fALFF of pre-ECT patients. This finding demonstrates that ECT treatment is effective on these brain areas in MDD patients.

PMID: 30326347 [PubMed - as supplied by publisher]

First-year development of modules and hubs in infant brain functional networks.

Mon, 10/15/2018 - 09:37
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First-year development of modules and hubs in infant brain functional networks.

Neuroimage. 2018 Oct 10;:

Authors: Wen X, Zhang H, Li G, Liu M, Yin W, Lin W, Zhang J, Shen D

Abstract
The human brain develops rapidly in the first postnatal year, in which rewired functional brain networks could shape later behavioral and cognitive performance. Resting-state functional magnetic resonances imaging (rs-fMRI) and complex network analysis have been widely used for characterizing the developmental brain functional connectome. Yet, such studies focusing on the first year of postnatal life are still very limited. Leveraging normally developing longitudinal infant rs-fMRI scans from neonate to one year of age, we investigated how brain functional networks develop at a fine temporal scale (every 3 months). Considering challenges in the infant fMRI-based network analysis, we developed a novel algorithm to construct the robust, temporally consistent and modular structure augmented group-level network based on which functional modules were detected at each age. Our study reveals that the brain functional network is gradually subdivided into an increasing number of functional modules accompanied by the strengthened intra- and inter-modular connectivities. Based on the developing modules, we found connector hubs (the high-centrality regions connecting different modules) emerging and increasing, while provincial hubs (the high-centrality regions connecting regions in the same module) diminishing. Further region-wise longitudinal analysis validates that different hubs have distinct developmental trajectories of the intra- and inter-modular connections suggesting different types of role transitions in network, such as non-hubs to hubs or provincial hubs to connector hubs et al. All findings indicate that functional segregation and integration are both increased in the first year of postnatal life. The module reorganization and hub transition lead to more efficient brain networks, featuring increasingly segregated modular structure and more connector hubs. This study provides the first comprehensive report of the development of functional brain networks at three month intervals throughout the first postnatal year of life, which provides essential information to the future neurodevelopmental and developmental disorder studies.

PMID: 30315911 [PubMed - as supplied by publisher]