New resting-state fMRI related studies at PubMed

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Using autoregressive-dynamic conditional correlation model with residual analysis to extract dynamic functional connectivity.

Wed, 05/27/2020 - 13:20
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Using autoregressive-dynamic conditional correlation model with residual analysis to extract dynamic functional connectivity.

J Neural Eng. 2020 May 26;:

Authors: Hakimdavoodi H, Amirmazlaghani M

Abstract
OBJECTIVE: Statistical methods that simultaneously model temporal and spatial variations of fMRI data are promising tools for dynamic functional connectivity (FC) estimation. Although different approaches are available, they need to manually set the parameters, or may disregard some important fMRI features such as the autocorrelation. In addition, no reliable method exists for the validation of dynamic FC analysis models.
APPROACH: In the present study, we have proposed an autoregressive dynamic conditional correlation model to deal with the temporal autocorrelation and non-stationarity in fMRI time-series. This model assumes that the brain time courses follow a multivariate Gaussian distribution, and that the conditional mean, variance and covariances change in an autoregressive form. Also, we proposed a new measurement index for the evaluation of the statistical consistency between the inferred dynamic functional connectivity and the real fMRI data. The performance of our model was tested in both simulated and real fMRI data.
MAIN RESULTS: The model was associated with independent Gaussian residuals, and identified the dynamic connectivity patterns with high precision. Applying the model to the fMRI data from typically developing and Attention deficit hyperactivity disorder (ADHD) subjects, brain connectivities were significantly different between the two groups.
SIGNIFICANCE: Prominent features of our model were the consideration of the fMRI autocorrelation, no need to adjust the window length, and also elimination of the variance changes in each brain time-course from its connectivity changes.

PMID: 32454472 [PubMed - as supplied by publisher]

Psilocybin acutely alters the functional connectivity of the claustrum with brain networks that support perception, memory, and attention.

Wed, 05/27/2020 - 13:20
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Psilocybin acutely alters the functional connectivity of the claustrum with brain networks that support perception, memory, and attention.

Neuroimage. 2020 May 23;:116980

Authors: Barrett FS, Krimmel SR, Griffiths R, Seminowicz DA, Mathur BN

Abstract
Psychedelic drugs, including the serotonin 2a (5-HT2A) receptor partial agonist psilocybin, are receiving renewed attention for their possible efficacy in treating a variety of neuropsychiatric disorders. Psilocybin induces widespread dysregulation of cortical activity, but circuit-level mechanisms underlying this effect are unclear. The claustrum is a subcortical nucleus that highly expresses 5-HT2A receptors and provides glutamatergic inputs to arguably all areas of the cerebral cortex. We therefore tested the hypothesis that psilocybin modulates claustrum function in humans. Fifteen healthy participants (10M, 5F) completed this within-subjects study in which whole-brain resting-state blood-oxygenation level-dependent (BOLD) signal was measured 100 min after blinded oral administration of placebo and 10 mg/70 kg psilocybin. Left and right claustrum signal was isolated using small region confound correction. Psilocybin significantly decreased both the amplitude of low frequency fluctuations as well as the variance of BOLD signal in the left and right claustrum. Psilocybin also significantly decreased functional connectivity of the right claustrum with auditory and default mode networks (DMN), increased right claustrum connectivity with the fronto-parietal task control network (FPTC), and decreased left claustrum connectivity with the FPTC. DMN integrity was associated with right-claustrum connectivity with the DMN, while FPTC integrity and modularity were associated with right claustrum and left claustrum connectivity with the FPTC, respectively. Subjective effects of psilocybin predicted changes in the amplitude of low frequency fluctuations and the variance of BOLD signal in the left and right claustrum. Observed effects were specific to claustrum, compared to flanking regions of interest (the left and right insula and putamen). This study uses a pharmacological intervention to provide the first empirical evidence in any species for a significant role of 5-HT2A receptor signaling in claustrum functioning, and supports a possible role of the claustrum in the subjective and therapeutic effects of psilocybin.

PMID: 32454209 [PubMed - as supplied by publisher]

Imaging Diagnosis of Central Nervous System Damage in Patients with T2DM.

Wed, 05/27/2020 - 13:20
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Imaging Diagnosis of Central Nervous System Damage in Patients with T2DM.

Neurosci Lett. 2020 May 23;:135092

Authors: Zhang W, Zhao W, Wang J, Xu Q, Li S, Yin C

Abstract
This paper uses resting-state functional magnetic resonance imaging (rs-FMRI) to construct a whole-brain binary functional network through a complex brain network analysis theory based on graph theory to explore the functional network of patients with type 2 diabetes (T2DM). Changes in topological properties and their potential relationships with fasting blood glucose (FBG), glycated haemoglobin (HbAlc), and cognitive function scale, and further explore the diagnostic value of rs-FMRI technology for central nervous system damage in T2DM patients, for clinical diagnosis and treatment Provide objective radiological evidence. In the range of sparsity (Sp) of 0.05 to 0.50 and a step size of 0.01, compared with the random network, the resting brain functional networks in the T2DM group and the HC group have larger clustering coefficients and similar shortest paths. Length and small world index greater than 1, that is, both groups of resting brain functional networks have small world characteristics. The MoCA score of the T2DM group was positively correlated with the node degree (r = 0.400, p = 0.043) and the node efficiency (r = 0.452, p = 0.021) of the right straight back. FBG is positively correlated with the node degree of the left occipital gyrus (r = 0.422, p = 0.023); HbAlc is related to the node degree of the left occipital gyrus (r = 0.372, p = 0.043) and the node degree of the left occipital gyrus ( r = 0.382, p = 0.037) was positively correlated with the node intermediary (r = 0.388, p = 0.034) at the back of the right cingulate gyrus. The topological properties of the resting brain function network of T2DM patients with negative MRI findings have changed compared with normal people, indicating that T2DM is an important factor leading to brain function damage, further explaining the rs-fMRI technology and complex brain networks based on graph theory Analysis theory can be used as an effective method to study the changes of brain function in T2DM patients.

PMID: 32454146 [PubMed - as supplied by publisher]

Functional connectome contractions in temporal lobe epilepsy: Microstructural underpinnings and predictors of surgical outcome.

Wed, 05/27/2020 - 13:20
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Functional connectome contractions in temporal lobe epilepsy: Microstructural underpinnings and predictors of surgical outcome.

Epilepsia. 2020 May 26;:

Authors: Larivière S, Weng Y, Vos de Wael R, Royer J, Frauscher B, Wang Z, Bernasconi A, Bernasconi N, Schrader DV, Zhang Z, Bernhardt BC

Abstract
OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Although it is commonly related to hippocampal pathology, increasing evidence suggests structural changes beyond the mesiotemporal lobe. Functional anomalies and their link to underlying structural alterations, however, remain incompletely understood.
METHODS: We studied 30 drug-resistant TLE patients and 57 healthy controls using multimodal magnetic resonance imaging (MRI) analyses. All patients had histologically verified hippocampal sclerosis and underwent postoperative imaging to outline the extent of their surgical resection. Our analysis leveraged a novel resting-state functional MRI framework that parameterizes functional connectivity distance, consolidating topological and physical properties of macroscale brain networks. Functional findings were integrated with morphological and microstructural metrics, and utility for surgical outcome prediction was assessed using machine learning techniques.
RESULTS: Compared to controls, TLE patients showed connectivity distance reductions in temporoinsular and prefrontal networks, indicating topological segregation of functional networks. Testing for morphological and microstructural associations, we observed that functional connectivity contractions occurred independently from TLE-related cortical atrophy but were mediated by microstructural changes in the underlying white matter. Following our imaging study, all patients underwent an anterior temporal lobectomy as a treatment of their seizures, and postsurgical seizure outcome was determined at a follow-up at least 1 year after surgery. Using a regularized supervised machine learning paradigm with fivefold cross-validation, we demonstrated that patient-specific functional anomalies predicted postsurgical seizure outcome with 76 ± 4% accuracy, outperforming classifiers operating on clinical and structural imaging features.
SIGNIFICANCE: Our findings suggest connectivity distance contractions as a macroscale substrate of TLE. Functional topological isolation may represent a microstructurally mediated network mechanism that tilts the balance toward epileptogenesis in affected networks and that may assist in patient-specific surgical prognostication.

PMID: 32452574 [PubMed - as supplied by publisher]

Balancing act: Neural correlates of affect dysregulation in youth depression and substance use - A systematic review of functional neuroimaging studies.

Wed, 05/27/2020 - 13:20
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Balancing act: Neural correlates of affect dysregulation in youth depression and substance use - A systematic review of functional neuroimaging studies.

Dev Cogn Neurosci. 2020 Apr;42:100775

Authors: Rakesh D, Allen NB, Whittle S

Abstract
Both depression and substance use problems have their highest incidence during youth (i.e., adolescence and emerging adulthood), and are characterized by emotion regulation deficits. Influential neurodevelopmental theories suggest that alterations in the function of limbic and frontal regions render youth susceptible to these deficits. However, whether depression and substance use in youth are associated with similar alterations in emotion regulation neural circuitry is unknown. In this systematic review we synthesized the results of functional magnetic resonance imaging (fMRI) studies investigating the neural correlates of emotion regulation in youth depression and substance use. Resting-state fMRI studies focusing on limbic connectivity were also reviewed. While findings were largely inconsistent within and between studies of depression and substance use, some patterns emerged. First, youth depression appears to be associated with exaggerated amygdala activity in response to negative stimuli; second, both depression and substance use appear to be associated with lower functional connectivity between the amygdala and prefrontal cortex during rest. Findings are discussed in relation to support for existing neurodevelopmental models, and avenues for future work are suggested, including studying neurodevelopmental trajectories from a network perspective.

PMID: 32452461 [PubMed - in process]

Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

Wed, 05/27/2020 - 13:20
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Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

J Child Psychol Psychiatry. 2020 May 26;:

Authors: Chen B, Linke A, Olson L, Ibarra C, Reynolds S, Müller RA, Kinnear M, Fishman I

Abstract
BACKGROUND: Symptoms of autism spectrum disorder (ASD) emerge in the first years of life. Yet, little is known about the organization and development of functional brain networks in ASD proximally to the symptom onset. Further, the relationship between brain network connectivity and emerging ASD symptoms and overall functioning in early childhood is not well understood.
METHODS: Resting-state fMRI data were acquired during natural sleep from 24 young children with ASD and 23 typically developing (TD) children, aged 17-45 months. Intrinsic functional connectivity (iFC) within and between resting-state functional networks was derived with independent component analysis (ICA).
RESULTS: Increased iFC between visual and sensorimotor networks was found in young children with ASD compared to TD participants. Within the ASD group, the degree of overconnectivity between visual and sensorimotor networks was associated with greater autism symptoms. Age-related weakening of the visual-auditory between-network connectivity was observed in the ASD but not the TD group.
CONCLUSIONS: Taken together, these results provide evidence for disrupted functional network maturation and differentiation, particularly involving visual and sensorimotor networks, during the first years of life in ASD. The observed pattern of greater visual-sensorimotor between-network connectivity associated with poorer clinical outcomes suggests that disruptions in multisensory brain circuitry may play a critical role for early development of behavioral skills and autism symptomatology in young children with ASD.

PMID: 32452051 [PubMed - as supplied by publisher]

Advanced network neuroscience approaches in sleep neurobiology on extreme environments.

Wed, 05/27/2020 - 13:20
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Advanced network neuroscience approaches in sleep neurobiology on extreme environments.

Conf Proc IEEE Eng Med Biol Soc. 2019 07;2019:4046-4067

Authors: Frantzidis CA, Nday CM, Chriskos P, Gkivogkli PT, Bamidis PD, Kourtidou-Papadeli C

Abstract
In this paper we propose a novel methodology for investigating pathological sleep patterns through network neuroscience approaches. It consists of initial identification of statistically significant alterations in cortical functional connectivity patterns. The resulting sub-network is then analyzed by employing graph theory for estimating both global performance metrics (integration and specialization) as well as the significance of specific network nodes and their hierarchical organization. So, nodes with important role in network structure are recognized and their functionality is correlated with adenosine biomarker which is important in sleep regulation and promotion. The aforementioned pipeline is applied in a dataset of sleep data gathered during a microgravity simulation experiment. The analysis was performed on cortical resting-state networks involved in sleep physiology. It demonstrated the detrimental effects of microgravity which were more prominent for the group which did not perform reactive sledge jumps as a countermeasure.

PMID: 31946760 [PubMed - indexed for MEDLINE]

Amyloid and tau accumulate across distinct spatial networks and are differentially associated with brain connectivity.

Wed, 05/27/2020 - 13:20
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Amyloid and tau accumulate across distinct spatial networks and are differentially associated with brain connectivity.

Elife. 2019 12 09;8:

Authors: Pereira JB, Ossenkoppele R, Palmqvist S, Strandberg TO, Smith R, Westman E, Hansson O

Abstract
The abnormal accumulation of amyloid-β and tau targets specific spatial networks in Alzheimer's disease. However, the relationship between these networks across different disease stages and their association with brain connectivity has not been explored. In this study, we applied a joint independent component analysis to 18F- Flutemetamol (amyloid-β) and 18F-Flortaucipir (tau) PET images to identify amyloid-β and tau networks across different stages of Alzheimer's disease. We then assessed whether these patterns were associated with resting-state functional networks and white matter tracts. Our analyses revealed nine patterns that were linked across tau and amyloid-β data. The amyloid-β and tau patterns showed a fair to moderate overlap with distinct functional networks but only tau was associated with white matter integrity loss and multiple cognitive functions. These findings show that amyloid-β and tau have different spatial affinities, which can be used to understand how they accumulate in the brain and potentially damage the brain's connections.

PMID: 31815669 [PubMed - indexed for MEDLINE]

Dynamic modular-level alterations of structural-functional coupling in clinically isolated syndrome.

Wed, 05/27/2020 - 13:20
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Dynamic modular-level alterations of structural-functional coupling in clinically isolated syndrome.

Brain. 2019 11 01;142(11):3428-3439

Authors: Koubiyr I, Besson P, Deloire M, Charre-Morin J, Saubusse A, Tourdias T, Brochet B, Ruet A

Abstract
Structural and functional connectivity abnormalities have been reported previously in multiple sclerosis. However, little is known about how each modality evolution relates to the other. Recent studies in other neurological disorders have suggested that structural-functional coupling may be more sensitive in detecting brain alterations than any single modality. Accordingly, this study aimed to investigate the longitudinal evolution of structural-functional coupling, both at the global and modular levels, in the first year following clinically isolated syndrome. We hypothesized that during the course of multiple sclerosis, patients exhibit a decoupling between functional and structural connectivity due to the disruptive nature of the disease. Forty-one consecutive patients with clinically isolated syndrome were prospectively enrolled in this study, along with 19 age-, sex- and educational level-matched healthy control subjects. These participants were followed for 1 year and underwent resting-state functional MRI and diffusion tensor imaging at each time point, along with an extensive neuropsychological assessment. Graph theory analysis revealed structural reorganization at baseline that appeared as an increase in the clustering coefficient in patients compared to controls (P < 0.05), as well as modular-specific alterations. After 1 year of follow-up, both structural and functional reorganization was depicted with abnormal modular-specific connectivity and an increase of the functional betweenness centrality in patients compared to controls (P < 0.01). More importantly, structural-functional decoupling was observed in the salience, visual and somatomotor networks. These alterations were present along with preserved cognitive performance at this stage. These results depict structural damage preceding functional reorganization at a global and modular level during the first year following clinically isolated syndrome along with normal cognitive performance, suggesting a compensation mechanism at this stage of the disease. Principally, structural-functional decoupling observed for the first time in multiple sclerosis suggests that functional reorganization occurs along indirect anatomical pathways.

PMID: 31504228 [PubMed - indexed for MEDLINE]

Deep brain stimulation has state-dependent effects on motor connectivity in Parkinson's disease.

Wed, 05/27/2020 - 13:20
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Deep brain stimulation has state-dependent effects on motor connectivity in Parkinson's disease.

Brain. 2019 08 01;142(8):2417-2431

Authors: Kahan J, Mancini L, Flandin G, White M, Papadaki A, Thornton J, Yousry T, Zrinzo L, Hariz M, Limousin P, Friston K, Foltynie T

Abstract
Subthalamic nucleus deep brain stimulation is an effective treatment for advanced Parkinson's disease; however, its therapeutic mechanism is unclear. Previous modelling of functional MRI data has suggested that deep brain stimulation has modulatory effects on a number of basal ganglia pathways. This work uses an enhanced data collection protocol to collect rare functional MRI data in patients with subthalamic nucleus deep brain stimulation. Eleven patients with Parkinson's disease and subthalamic nucleus deep brain stimulation underwent functional MRI at rest and during a movement task; once with active deep brain stimulation, and once with deep brain stimulation switched off. Dynamic causal modelling and Bayesian model selection were first used to compare a series of plausible biophysical models of the cortico-basal ganglia circuit that could explain the functional MRI activity at rest in an attempt to reproduce and extend the findings from our previous work. General linear modelling of the movement task functional MRI data revealed deep brain stimulation-associated signal increases in the primary motor and cerebellar cortices. Given the significance of the cerebellum in voluntary movement, we then built a more complete model of the motor system by including cerebellar-basal ganglia interactions, and compared the modulatory effects deep brain stimulation had on different circuit components during the movement task and again using the resting state data. Consistent with previous results from our independent cohort, model comparison found that the rest data were best explained by deep brain stimulation-induced increased (effective) connectivity of the cortico-striatal, thalamo-cortical and direct pathway and reduced coupling of subthalamic nucleus afferent and efferent connections. No changes in cerebellar connectivity were identified at rest. In contrast, during the movement task, there was functional recruitment of subcortical-cerebellar pathways, which were additionally modulated by deep brain stimulation, as well as modulation of local (intrinsic) cortical and cerebellar circuits. This work provides in vivo evidence for the modulatory effects of subthalamic nucleus deep brain stimulation on effective connectivity within the cortico-basal ganglia loops at rest, as well as further modulations in the cortico-cerebellar motor system during voluntary movement. We propose that deep brain stimulation has both behaviour-independent effects on basal ganglia connectivity, as well as behaviour-dependent modulatory effects.

PMID: 31219504 [PubMed - indexed for MEDLINE]

The association between prenatal endocrine-disrupting chemical exposure and altered resting-state brain fMRI in teenagers.

Tue, 05/26/2020 - 12:00

The association between prenatal endocrine-disrupting chemical exposure and altered resting-state brain fMRI in teenagers.

Brain Struct Funct. 2020 May 25;:

Authors: Weng JC, Hong CI, Tasi JD, Shen CY, Su PH, Wang SL

Abstract
Many studies have reported that prenatal exposure to endocrine-disrupting chemicals (EDCs) can cause adverse behavioral effects or cognitive dysfunction in children. This study aimed to investigate a relationship of the concentration of prenatal EDCs and brain function in teenagers. We recruited 59 mother-child pairs during the third trimester of pregnancy, and collected and examined the concentration of EDCs, such as heavy metals, phthalates and perfluoroalkyl substances (PFASs), in maternal urine and serum. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected in teenagers 13-16 years of age, and fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) were performed to find the association between maternal EDC concentrations and the functional development of the teenage brain. We found a correlation between MBP concentration and activity in the superior frontal gyrus, middle frontal gyrus, middle temporal gyrus and inferior temporal gyrus in the combined group of boys and girls. We also observed a correlation between MBzP concentration and activity in the anterior cingulum gyrus and insula in girls. We found a correlation between lead concentration and activity in the cuneus in the combined group. We also observed a correlation between MeHg concentration and activity in the superior temporal gyrus, caudate nucleus and putamen in the combined group. The PFOS results revealed a negative relationship between activity in the right putamen in boys, girls and the combined group after phthalate or heavy metals were applied as covariates. The PFNA results showed a negative correlation between activity in the left/right putamen and left caudate nucleus in boys, girls and the combined group after phthalate, heavy metals or PFOS were applied as covariates. We examined the correlations between maternal EDC concentrations and brain development and found that the associations with resting-state teenage brains in some circumstances are sex-related.

PMID: 32448957 [PubMed - as supplied by publisher]

The Anterior-posterior Functional Connectivity Disconnection in the Elderly with Subjective Memory Impairment and Amnestic Mild Cognitive Impairment.

Tue, 05/26/2020 - 12:00

The Anterior-posterior Functional Connectivity Disconnection in the Elderly with Subjective Memory Impairment and Amnestic Mild Cognitive Impairment.

Curr Alzheimer Res. 2020 May 24;:

Authors: Tao W, Sun J, Li X, Shao W, Pei J, Yang C, Wang W, Xu K, Wang J, Zhang Z

Abstract
BACKGROUND: Subjective memory impairment (SMI) may tremendously increase the risk of Alzheimer's disease (AD). The full understanding of the neuromechanism of SMI will shed light on the early intervention of AD.
METHODS: In the current study, 23 healthy controls (HC), 22 SMI subjects and 24 amnestic mild cognitive impairment (aMCI) subjects underwent the comprehensive neuropsychological assessment and the resting-state functional magnetic resonance imaging scan. The difference in the connectivity of the default mode network (DMN) and functional connectivity (FC) from the region of interest (ROI) to the whole brain were compared, respectively.
RESULTS: The results showed that HC and SMI subjects had significantly higher connectivity in the region of the precuneus area compared to aMCI subjects. However, from this region to the whole brain, SMI and aMCI subjects had significant FC decrease in the right anterior cingulum, left superior frontal and left medial superior frontal gyrus compared to HC. In addition, this FC change was significantly correlated with the cognitive function decline in participants.
CONCLUSION: Our study indicated that SMI subjects had relatively intact DMN connectivity but impaired FC between the anterior and posterior brain. The findings suggest that long-distance FC is more vulnerable than the short ones in the people with SMI.

PMID: 32448103 [PubMed - as supplied by publisher]

Age-Related Differences in Functional and Structural Connectivity in the Spatial Navigation Brain Network.

Tue, 05/26/2020 - 12:00
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Age-Related Differences in Functional and Structural Connectivity in the Spatial Navigation Brain Network.

Front Neural Circuits. 2019;13:69

Authors: Ramanoël S, York E, Le Petit M, Lagrené K, Habas C, Arleo A

Abstract
Spatial navigation involves multiple cognitive processes including multisensory integration, visuospatial coding, memory, and decision-making. These functions are mediated by the interplay of cerebral structures that can be broadly separated into a posterior network (subserving visual and spatial processing) and an anterior network (dedicated to memory and navigation planning). Within these networks, areas such as the hippocampus (HC) are known to be affected by aging and to be associated with cognitive decline and navigation impairments. However, age-related changes in brain connectivity within the spatial navigation network remain to be investigated. For this purpose, we performed a neuroimaging study combining functional and structural connectivity analyses between cerebral regions involved in spatial navigation. Nineteen young (μ = 27 years, σ = 4.3; 10 F) and 22 older (μ = 73 years, σ = 4.1; 10 F) participants were examined in this study. Our analyses focused on the parahippocampal place area (PPA), the retrosplenial cortex (RSC), the occipital place area (OPA), and the projections into the visual cortex of central and peripheral visual fields, delineated from independent functional localizers. In addition, we segmented the HC and the medial prefrontal cortex (mPFC) from anatomical images. Our results show an age-related decrease in functional connectivity between low-visual areas and the HC, associated with an increase in functional connectivity between OPA and PPA in older participants compared to young subjects. Concerning the structural connectivity, we found age-related differences in white matter integrity within the navigation brain network, with the exception of the OPA. The OPA is known to be involved in egocentric navigation, as opposed to allocentric strategies which are more related to the hippocampal region. The increase in functional connectivity between the OPA and PPA may thus reflect a compensatory mechanism for the age-related alterations around the HC, favoring the use of the preserved structural network mediating egocentric navigation. Overall, these findings on age-related differences of functional and structural connectivity may help to elucidate the cerebral bases of spatial navigation deficits in healthy and pathological aging.

PMID: 31736716 [PubMed - indexed for MEDLINE]

Expanding the role of education in frontotemporal dementia: a functional dynamic connectivity (the chronnectome) study.

Mon, 05/25/2020 - 11:20

Expanding the role of education in frontotemporal dementia: a functional dynamic connectivity (the chronnectome) study.

Neurobiol Aging. 2020 Apr 29;93:35-43

Authors: Premi E, Cristillo V, Gazzina S, Benussi A, Alberici A, Cotelli MS, Calhoun VD, Iraji A, Magoni M, Cotelli M, Micheli A, Gasparotti R, Padovani A, Borroni B

Abstract
In the present study, we aim at investigating whether education modulates dynamical properties of time-varying whole-brain network connectivity (the chronnectome) in frontotemporal dementia (FTD) at a given level of symptom severity. Dynamic connectivity parameters were evaluated in 128 patients with FTD using independent component analysis, sliding-time window correlation, and k-means approach to resting state-magnetic resonance imaging data. We evaluated the relationship between education, a proxy measure of cognitive reserve, and 4 indexes of metastate dynamic connectivity: (1) the number of distinct metastates a patient passes through, (2) the number of switches from one metastate to another, (3) the span of the realized metastates, and (4) the total distance traveled in the state space. We found a significant inverse correlation between years of education and the 4 indexes of metastate dynamic fluidity (all p-values ≤ 0.03, false discovery rate-corrected). This study suggests that patients with FTD with higher education but comparable clinical severity show more global functional brain impairment, suggesting that patients with higher cognitive reserve can cope with more global brain fluidity reduction.

PMID: 32447010 [PubMed - as supplied by publisher]

Uncovering the modulatory interactions of brain networks in cognition with central thalamic deep brain stimulation using functional magnetic resonance imaging.

Mon, 05/25/2020 - 11:20

Uncovering the modulatory interactions of brain networks in cognition with central thalamic deep brain stimulation using functional magnetic resonance imaging.

Neuroscience. 2020 May 21;:

Authors: Li SJ, Lo YC, Lai HY, Lin SH, Lin HC, Lin TC, Chang CW, Chen TC, Chin-Jung Hsieh C, Yang SH, Chiu FM, Kuo CH, Chen YY

Abstract
Deep brain stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. It acts by altering brain networks and facilitating synaptic plasticity. For enhancing cognitive functions, the central thalamus (CT) has been shown to be a potential DBS target. The network-level mechanisms contributing to the effect exerted by DBS on the CT (CT-DBS) remain unknown. Combining CT-DBS with functional magnetic resonance imaging (fMRI), this study explored brain areas activated while applying CT-DBS in rats, using a newly developed neural probe that was compatible with MRI and could minimize the image distortion and resolve safety issues. Results showed activation of the anterior cingulate cortex, motor cortex, primary and secondary somatosensory cortices, caudate putamen, hypothalamus, thalamus, and hippocampus, suggesting that the corticostriatal, corticolimbic, and thalamocortical brain networks were affected. Behaviorally, the CT-DBS group required a shorter time than sham controls to learn a water-reward lever-pressing task and made more correct choices in a T-maze task. Concurrent with enhanced learning performance, bilateral CT-DBS resulted in alteration in the functional connectivity of brain networks determined by resting-state fMRI. Western blot analyses showed that the protein level of both dopamine D1 and α4-nicotinic acetylcholine receptors was increased, and dopamine D2 receptor was decreased. These data suggest that CT-DBS can enhance cognitive performance as well as brain connectivity through the modulation of synaptic plasticity, such that CT is a target providing high potential for the remediation of acquired cognitive learning and memory disabilities.

PMID: 32446855 [PubMed - as supplied by publisher]

Investigation of Functional Variability and Connectivity in Temporal Lobe Epilepsy: A Resting State fMRI Study.

Mon, 05/25/2020 - 11:20

Investigation of Functional Variability and Connectivity in Temporal Lobe Epilepsy: A Resting State fMRI Study.

Neurosci Lett. 2020 May 21;:135076

Authors: Dumlu SN, Ademoğlu A, Sun W

Abstract
It is crucial to reveal the variability between patients with epilepsy and healthy subjects to elucidate the underpinnings of the disease pathology. Herein, we assessed the inter-subject variability between patients with temporal lobe epilepsy (TLE) and healthy subjects in terms of estimating the functional connectivity using resting-state functional magnetic resonance (rs-fMRI) scans. According to inter-subject variability results between healthy and TLE population, the latter showed more variability mainly in frontoparietal control, default mode, dorsal/ventral attention, visual and somatomotor networks in line with the broad seizure onset and propagation pathway. As a result of 17-Network parcellation, a significant attenuation is observed in functional connectivity, mostly in bilateral frontoparietal control, somatomotor, default mode and ventral attention networks associated with the functional impairment in attention, long/short term memory, executive functioning. The results are in favor of the argument that the functional disruption in TLE spreads throughout the cortex beyond the temporal lobe with an implication of greater diversity in the TLE population.

PMID: 32446775 [PubMed - as supplied by publisher]

A Comprehensive Framework for Differentiating Autism Spectrum Disorder From Neurotypicals by Fusing Structural MRI and Resting State Functional MRI.

Mon, 05/25/2020 - 11:20

A Comprehensive Framework for Differentiating Autism Spectrum Disorder From Neurotypicals by Fusing Structural MRI and Resting State Functional MRI.

Semin Pediatr Neurol. 2020 Jul;34:100805

Authors: Dekhil O, Ali M, Haweel R, Elnakib Y, Ghazal M, Hajjdiab H, Fraiwan L, Shalaby A, Soliman A, Mahmoud A, Keynton R, Casanova MF, Barnes G, El-Baz A

Abstract
Autism spectrum disorder is a neurodevelopmental disorder characterized by impaired social abilities and communication difficulties. The golden standard for autism diagnosis in research rely on behavioral features, for example, the autism diagnosis observation schedule, the Autism Diagnostic Interview-Revised. In this study we introduce a computer-aided diagnosis system that uses features from structural MRI (sMRI) and resting state functional MRI (fMRI) to help predict an autism diagnosis by clinicians. The proposed system is capable of parcellating brain regions to show which areas are most likely affected by autism related abnormalities and thus help in targeting potential therapeutic interventions. When tested on 18 data sets (n = 1060) from the ABIDE consortium, our system was able to achieve high accuracy (sMRI 0.75-1.00; fMRI 0.79-1.00), sensitivity (sMRI 0.73-1.00; fMRI 0.78-1.00), and specificity (sMRI 0.78-1.00; fMRI 0.79-1.00). The proposed system could be considered an important step toward helping physicians interpret results of neuroimaging studies and personalize treatment options. To the best of our knowledge, this work is the first to combine features from structural and functional MRI, use them for personalized diagnosis and achieve high accuracies on a relatively large population.

PMID: 32446442 [PubMed - as supplied by publisher]

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

Sun, 05/24/2020 - 16:20

Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

Neuroimage Clin. 2020 Apr 22;27:102262

Authors: Nicholson AA, Harricharan S, Densmore M, Neufeld RWJ, Ros T, McKinnon MC, Frewen PA, Théberge J, Jetly R, Pedlar D, Lanius RA

Abstract
Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of the current study was to a) compare ICN functional connectivity between PTSD, dissociative subtype PTSD (PTSD+DS) and healthy individuals; and b) to examine the use of multivariate machine learning algorithms in classifying PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. Our neuroimaging dataset consisted of resting-state fMRI scans from 186 participants [PTSD (n = 81); PTSD + DS (n = 49); and healthy controls (n = 56)]. We performed group-level independent component analyses to evaluate functional connectivity differences within each ICN. Multiclass Gaussian Process Classification algorithms within PRoNTo software were then used to predict the diagnosis of PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. When comparing the functional connectivity of ICNs between PTSD, PTSD+DS and healthy controls, we found differential patterns of connectivity to brain regions involved in emotion regulation, in addition to limbic structures and areas involved in self-referential processing, interoception, bodily self-consciousness, and depersonalization/derealization. Machine learning algorithms were able to predict with high accuracy the classification of PTSD, PTSD+DS, and healthy individuals based on ICN functional activation. Our results suggest that alterations within intrinsic connectivity networks may underlie unique psychopathology and symptom presentation among PTSD subtypes. Furthermore, the current findings substantiate the use of machine learning algorithms for classifying subtypes of PTSD illness based on ICNs.

PMID: 32446241 [PubMed - as supplied by publisher]

Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands.

Sun, 05/24/2020 - 16:20

Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands.

Commun Biol. 2020 May 22;3(1):261

Authors: Cornblath EJ, Ashourvan A, Kim JZ, Betzel RF, Ciric R, Adebimpe A, Baum GL, He X, Ruparel K, Moore TM, Gur RC, Gur RE, Shinohara RT, Roalf DR, Satterthwaite TD, Bassett DS

Abstract
A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain's trajectories across a set of single time point activity patterns from functional magnetic resonance imaging data acquired during the resting state and an n-back working memory task. We find that specific temporal sequences of brain activity are modulated by cognitive load, associated with age, and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we apply tools from network control theory to show that linear spread of activity along white matter connections constrains the probabilities of these sequences at rest, while stimulus-driven visual inputs explain the sequences observed during the n-back task. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.

PMID: 32444827 [PubMed - as supplied by publisher]

A systematic comparison of structural-, structural connectivity-, and functional connectivity-based thalamus parcellation techniques.

Sat, 05/23/2020 - 15:00
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A systematic comparison of structural-, structural connectivity-, and functional connectivity-based thalamus parcellation techniques.

Brain Struct Funct. 2020 May 21;:

Authors: Iglehart C, Monti M, Cain J, Tourdias T, Saranathan M

Abstract
The thalamus consists of several histologically and functionally distinct nuclei increasingly implicated in brain pathology and important for treatment, motivating the need for development of fast and accurate thalamic parcellation. The contrast between thalamic nuclei as well as between the thalamus and surrounding tissues is poor in T1- and T2-weighted magnetic resonance imaging (MRI), inhibiting efforts to date to segment the thalamus using standard clinical MRI. Automatic parcellation techniques have been developed to leverage thalamic features better captured by advanced MRI methods, including magnetization prepared rapid acquisition gradient echo (MP-RAGE), diffusion tensor imaging (DTI), and resting-state functional MRI (fMRI). Despite operating on fundamentally different image contrasts, these methods claim a high degree of agreement with the Morel stereotactic atlas of the thalamus. However, no comparison has been undertaken to compare the results of these disparate parcellation methods. We have implemented state-of-the-art structural-, diffusion-, and functional imaging-based thalamus parcellation techniques and used them on a single set of subjects. We present the first systematic qualitative and quantitative comparison of these methods. The results show that DTI parcellation agrees more with structural parcellation in the larger thalamic nuclei, while rsfMRI parcellation agrees more with structural parcellation in the smaller nuclei. Structural parcellation is the most accurate in the delineation of small structures such as the habenular, antero-ventral, and medial geniculate nuclei.

PMID: 32440784 [PubMed - as supplied by publisher]

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