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Time-Delay Latency of Resting-State Blood Oxygen Level-Dependent Signal Related to the Level of Consciousness in Patients with Severe Consciousness Impairment.

Sat, 03/21/2020 - 21:31
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Time-Delay Latency of Resting-State Blood Oxygen Level-Dependent Signal Related to the Level of Consciousness in Patients with Severe Consciousness Impairment.

Brain Connect. 2020 Mar;10(2):83-94

Authors: Rudas J, Martínez D, Castellanos G, Demertzi A, Martial C, Carriére M, Aubinet C, Soddu A, Laureys S, Gómez F

Abstract
Recent evidence on resting-state functional magnetic resonance imaging (rs-fMRI) suggests that healthy human brains have a temporal organization represented in a widely complex time-delay structure. This structure seems to underlie brain communication flow, integration/propagation of brain activity, as well as information processing. Therefore, it is probably linked to the emergence of highly coordinated complex brain phenomena, such as consciousness. Nevertheless, possible changes in this structure during an altered state of consciousness remain poorly investigated. In this work, we hypothesized that due to a disruption in high-order functions and alterations of the brain communication flow, patients with disorders of consciousness (DOC) might exhibit changes in their time-delay structure of spontaneous brain activity. We explored this hypothesis by comparing the time-delay projections from fMRI resting-state data acquired in resting state from 48 patients with DOC and 27 healthy controls (HC) subjects. Results suggest that time-delay structure modifies for patients with DOC conditions when compared with HC. Specifically, the average value and the directionality of latency inside the midcingulate cortex (mCC) shift with the level of consciousness. In particular, positive values of latency inside the mCC relate to preserved states of consciousness, whereas negative values change proportionally with the level of consciousness in patients with DOC. These results suggest that the mCC may play a critical role as an integrator of brain activity in HC subjects, but this role vanishes in an altered state of consciousness.

PMID: 32195610 [PubMed - as supplied by publisher]

Reduced complexity in stroke with motor deficits: a resting-state fMRI study.

Sat, 03/21/2020 - 21:31
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Reduced complexity in stroke with motor deficits: a resting-state fMRI study.

Neuroscience. 2020 Mar 17;:

Authors: Liang L, Hu R, Luo X, Feng B, Long W, Song R

Abstract
Recently, alterations of complexity due to brain disorders have been demonstrated using brain entropy (BEN), while the changes of brain complexity in stroke, a common cerebrovascular disease, remain unclear. In this research, resting-state functional magnetic resonance imaging (fMRI) was performed to explore the alterations of brain complexity using BEN in twenty stroke patients with motor deficits and nineteen matched healthy controls. The sample entropy (SampEn) was applied to build the BEN mapping for each participant. Compared with healthy controls, stroke patients exhibited lower BEN values in the contralesional precentral gyrus (preCG), bilateral dorsolateral superior frontal gyrus (SFGdor) and bilateral supplementary motor area (SMA). Moreover, significantly positive correlations between BEN values and Fugl-Meyer Assessment scores were detected in the ipsilesional SFGdor and ipsilesional SMA. Mutual information independence was observed between BEN and regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), respectively, in the stroke patients. Our findings implied that brain complexity had been impacted after stroke, and also suggested that BEN could be a complementary tool for evaluating the motor impairment after stroke.

PMID: 32194224 [PubMed - as supplied by publisher]

Resting state BOLD variability of the posterior medial temporal lobe correlates with cognitive performance in older adults with and without risk for cognitive decline.

Sat, 03/21/2020 - 21:31
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Resting state BOLD variability of the posterior medial temporal lobe correlates with cognitive performance in older adults with and without risk for cognitive decline.

eNeuro. 2020 Mar 13;:

Authors: Good TJ, Villafuerte J, Ryan JD, Grady CL, Barense MD

Abstract
Local brain signal variability (standard deviation of the BOLD signal [SDBOLD]) correlates with age and cognitive performance, and recently differentiated Alzheimer's disease (AD) patients from healthy controls. However, it is unknown if changes to SDBOLD precede diagnosis of AD or mild cognitive impairment (MCI). We compared ostensibly healthy older adult humans who scored below the recommended threshold on the Montreal Cognitive Assessment (MoCA) and who showed reduced medial temporal lobe (MTL) volume in a previous study ('at-risk' group, n=20), with healthy older adults who scored within the normal range on the MoCA ('control' group, n=20). Using multivariate partial least squares analysis we assessed the correlations between SDBOLD and age, MoCA score, global fractional anisotropy, global mean diffusivity, and four cognitive factors. Greater SDBOLD in the MTL and occipital cortex positively correlated with performance on cognitive control/speed tasks but negatively correlated with memory scores in the control group. These relations were weaker in the at-risk group. A post-hoc analysis assessed associations between MTL volumes and SDBOLD in both groups. This revealed a negative correlation, most robust in the at-risk group, between MTL SDBOLD and MTL subregion volumetry, particularly the entorhinal and parahippocampal regions. Taken together, these results suggest that the association between SDBOLD and cognition differs between the at-risk and control groups, which may be due to lower MTL volumes in the at-risk group. Our data indicate relations between MTL SDBOLD and cognition may be helpful in understanding brain differences in individuals who may be at risk for further cognitive decline.Significance Statement Moment-to-moment variability in the BOLD signal, once dismissed as nuisance noise, is now understood to be an information-bearing signal. BOLD variability correlates with age and cognitive performance and was recently used to differentiate Alzheimer's disease (AD) patients from controls. As AD is a progressive disease, AD patients may benefit from its early detection. We found that older adults at-risk for cognitive decline showed differences in the relationships between BOLD variability and cognitive performance, relative to healthy controls. Notably, the differences were strongest in medial temporal lobe (MTL), areas where AD is known to begin. Our data suggest correlations between MTL BOLD variability and cognition may be useful for understanding brain differences in individuals at risk for further cognitive decline.

PMID: 32193364 [PubMed - as supplied by publisher]

Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition.

Sat, 03/21/2020 - 21:31
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Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition.

Proc Natl Acad Sci U S A. 2020 Mar 19;:

Authors: Ozdemir RA, Tadayon E, Boucher P, Momi D, Karakhanyan KA, Fox MD, Halko MA, Pascual-Leone A, Shafi MM, Santarnecchi E

Abstract
Large-scale brain networks are often described using resting-state functional magnetic resonance imaging (fMRI). However, the blood oxygenation level-dependent (BOLD) signal provides an indirect measure of neuronal firing and reflects slow-evolving hemodynamic activity that fails to capture the faster timescale of normal physiological function. Here we used fMRI-guided transcranial magnetic stimulation (TMS) and simultaneous electroencephalography (EEG) to characterize individual brain dynamics within discrete brain networks at high temporal resolution. TMS was used to induce controlled perturbations to individually defined nodes of the default mode network (DMN) and the dorsal attention network (DAN). Source-level EEG propagation patterns were network-specific and highly reproducible across sessions 1 month apart. Additionally, individual differences in high-order cognitive abilities were significantly correlated with the specificity of TMS propagation patterns across DAN and DMN, but not with resting-state EEG dynamics. Findings illustrate the potential of TMS-EEG perturbation-based biomarkers to characterize network-level individual brain dynamics at high temporal resolution, and potentially provide further insight on their behavioral significance.

PMID: 32193345 [PubMed - as supplied by publisher]

Connectome-wide search for functional connectivity locus associated with pathological rumination as a target for real-time fMRI neurofeedback intervention.

Sat, 03/21/2020 - 21:31
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Connectome-wide search for functional connectivity locus associated with pathological rumination as a target for real-time fMRI neurofeedback intervention.

Neuroimage Clin. 2020 Mar 12;26:102244

Authors: Misaki M, Tsuchiyagaito A, Al Zoubi O, Paulus M, Bodurka J, Tulsa 1000 Investigators

Abstract
Real-time fMRI neurofeedback (rtfMRI-nf) enables noninvasive targeted intervention in brain activation with high spatial specificity. To achieve this promise of rtfMRI-nf, we introduced and demonstrated a data-driven framework to design a rtfMRI-nf intervention through the discovery of precise target location associated with clinical symptoms and neurofeedback signal optimization. Specifically, we identified the functional connectivity locus associated with rumination symptoms, utilizing a connectome-wide search in resting-state fMRI data from a large cohort of mood and anxiety disorder individuals (N = 223) and healthy controls (N = 45). Then, we performed a rtfMRI simulation analysis to optimize the online functional connectivity neurofeedback signal for the identified functional connectivity. The connectome-wide search was performed in the medial prefrontal cortex and the posterior cingulate cortex/precuneus brain regions to identify the precise location of the functional connectivity associated with rumination severity as measured by the ruminative response style (RRS) scale. The analysis found that the functional connectivity between the loci in the precuneus (-6, -54, 48 mm in MNI) and the right temporo-parietal junction (RTPJ; 49, -49, 23 mm) was positively correlated with RRS scores (depressive, p < 0.001; brooding, p < 0.001; reflective, p = 0.002) in the mood and anxiety disorder group. We then performed a rtfMRI processing simulation to optimize the online computation of the precuneus-RTPJ connectivity. We determined that the two-point method without a control region was appropriate as a functional connectivity neurofeedback signal with less dependence on signal history and its accommodation of head motion. The present study offers a discovery framework for the precise location of functional connectivity targets for rtfMRI-nf intervention, which could help directly translate neuroimaging findings into clinical rtfMRI-nf interventions.

PMID: 32193171 [PubMed - as supplied by publisher]

Regularized Joint Estimation of Related Vector Autoregressive Models.

Fri, 03/20/2020 - 21:30
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Regularized Joint Estimation of Related Vector Autoregressive Models.

Comput Stat Data Anal. 2019 Nov;139:164-177

Authors: Skripnikov A, Michailidis G

Abstract
In a number of applications, one has access to high-dimensional time series data on several related subjects. A motivating application area comes from the neuroimaging field, such as brain fMRI time series data, obtained from various groups of subjects (cases/controls) with a specific neurological disorder. The problem of regularized joint estimation of multiple related Vector Autoregressive (VAR) models is discussed, leveraging a group lasso penalty in addition to a regular lasso one, so as to increase statistical efficiency of the estimates by borrowing strength across the models. A modeling framework is developed that it allows for both group-level and subject-specific effects for related subjects, using a group lasso penalty to estimate the former. An estimation procedure is introduced, whose performance is illustrated on synthetic data and compared to other state-of-the-art methods. Moreover, the proposed approach is employed for the analysis of resting state fMRI data. In particular, a group-level descriptive analysis is conducted for brain inter-regional temporal effects of Attention Deficit Hyperactive Disorder (ADHD) patients as opposed to controls, with the data available from the ADHD-200 Global Competition repository.

PMID: 32189818 [PubMed]

Head Motion During MRI Predicted by out-of-Scanner Sustained Attention Performance in Attention-Deficit/Hyperactivity Disorder.

Fri, 03/20/2020 - 21:30
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Head Motion During MRI Predicted by out-of-Scanner Sustained Attention Performance in Attention-Deficit/Hyperactivity Disorder.

J Atten Disord. 2020 Mar 19;:1087054720911988

Authors: Thomson P, Johnson KA, Malpas CB, Efron D, Sciberras E, Silk TJ

Abstract
Objective: To characterize head movements in children with ADHD using an ex-Gaussian distribution and examine associations with out-of-scanner sustained attention. Method: Fifty-six children with ADHD and 61 controls aged 9 to 11 years completed the Sustained Attention to Response Task (SART) and resting-state functional magnetic resonance imaging (fMRI). In-scanner head motion was calculated using ex-Gaussian estimates for mu, sigma, and tau in delta variation signal and framewise displacement. Sustained attention was evaluated through omission errors and tau in response time on the SART. Results: Mediation analysis revealed that out-of-scanner attention lapses (omissions during the SART) mediated the relationship between ADHD diagnosis and in-scanner head motion (tau in delta variation signal), indirect effect: B = 1.29, 95% confidence interval (CI) = [0.07, 3.15], accounting for 29% of the association. Conclusion: Findings suggest a critical link between trait-level sustained attention and infrequent large head movements during scanning (tau in head motion) and highlight fundamental challenges in measuring the neural basis of sustained attention.

PMID: 32189534 [PubMed - as supplied by publisher]

Effect and Neuroimaging Mechanism of Electroacupuncture for Vascular Cognitive Impairment No Dementia: Study Protocol for a Randomized, Assessor-Blind, Controlled Clinical Trial.

Thu, 03/19/2020 - 21:30
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Effect and Neuroimaging Mechanism of Electroacupuncture for Vascular Cognitive Impairment No Dementia: Study Protocol for a Randomized, Assessor-Blind, Controlled Clinical Trial.

Evid Based Complement Alternat Med. 2020;2020:7190495

Authors: Lin R, Huang J, Xu J, Tao J, Xu Y, Liu J, Liu W, Liang S, Yang M, Chen L

Abstract
Vascular cognitive impairment no dementia (VCIND) is likely to develop into vascular dementia (VD) without intervention. The clinical efficacy of electroacupuncture (EA) for VCIND has been previously demonstrated. However, the neuroimaging mechanism of EA for VCIND has not been elucidated clearly. This trial is designed to provide solid evidence for the efficacy and neuroimaging mechanism of EA treatment for patients with VCIND. This ongoing study is an assessor-blind, parallel-group, randomized controlled trial. 140 eligible subjects will be recruited from the General Hospital of Ningxia Medical University and randomized into either the electroacupuncture (EA) group or the control group (CG). All subjects will receive basic treatment, and participants in the CG will receive health education performed weekly. Except for basic treatment and health education, participants in the EA group will receive treatment 5 times per week for a total of 40 sessions over 8 weeks. The primary outcome in this study is Montreal Cognitive Assessment (MoCA), and the secondary outcomes are Auditory Verbal Learning Test (AVLT), Stroop color-naming condition (STROOP), Rey-Osterrieth Complex Graphics Testing, and resting-state functional magnetic resonance imaging (rs-fMRI). All of the outcome measures will be assessed at baseline and 8 weeks of intervention. The medical abstraction of adverse events will be done at each visit. The results of this trial will demonstrate the efficacy and neuroimaging mechanism of EA treatment for VCIND, thus supporting EA treatment as an ideal choice for VCIND treatment. The trial was registered at the Chinese Clinical Trial Registry on 28 July 2018 (ChiCTR1800017398).

PMID: 32184898 [PubMed]

Transcranial Focused Ultrasound to the Right Prefrontal Cortex Improves Mood and Alters Functional Connectivity in Humans.

Thu, 03/19/2020 - 21:30
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Transcranial Focused Ultrasound to the Right Prefrontal Cortex Improves Mood and Alters Functional Connectivity in Humans.

Front Hum Neurosci. 2020;14:52

Authors: Sanguinetti JL, Hameroff S, Smith EE, Sato T, Daft CMW, Tyler WJ, Allen JJB

Abstract
Transcranial focused ultrasound (tFUS) is an emerging method for non-invasive neuromodulation akin to transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). tFUS offers several advantages over electromagnetic methods including high spatial resolution and the ability to reach deep brain targets. Here we describe two experiments assessing whether tFUS could modulate mood in healthy human volunteers by targeting the right inferior frontal gyrus (rIFG), an area implicated in mood and emotional regulation. In a randomized, placebo-controlled, double-blind study, participants received 30 s of 500 kHz tFUS or a placebo control. Visual Analog Mood Scales (VAMS) assessed mood four times within an hour (baseline and three times after tFUS). Participants who received tFUS reported an overall increase in Global Affect (GA), an aggregate score from the VAMS scale, indicating a positive shift in mood. Experiment 2 examined resting-state functional (FC) connectivity using functional magnetic resonance imaging (fMRI) following 2 min of 500 kHz tFUS at the rIFG. As in Experiment 1, tFUS enhanced self-reported mood states and also decreased FC in resting state networks related to emotion and mood regulation. These results suggest that tFUS can be used to modulate mood and emotional regulation networks in the prefrontal cortex.

PMID: 32184714 [PubMed]

Differential Reorganization of SMA Subregions After Stroke: A Subregional Level Resting-State Functional Connectivity Study.

Thu, 03/19/2020 - 21:30
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Differential Reorganization of SMA Subregions After Stroke: A Subregional Level Resting-State Functional Connectivity Study.

Front Hum Neurosci. 2019;13:468

Authors: Liu H, Cai W, Xu L, Li W, Qin W

Abstract
Background and Purpose: The human supplementary motor area (SMA) contains two functional subregions of the SMA proper and preSMA; however, the reorganization patterns of the two SMA subregions after stroke remain uncertain. Meanwhile, a focal subcortical lesion may affect the overall functional reorganization of brain networks. We sought to identify the differential reorganization of the SMA subregions after subcortical stroke using the resting-state functional connectivity (rsFC) analysis. Methods: Resting-state functional MRI was conducted in 25 patients with chronic capsular stroke exhibiting well-recovered global motor function (Fugl-Meyer score >90). The SMA proper and preSMA were identified by the rsFC-based parcellation, and the rsFCs of each SMA subregion were compared between stroke patients and healthy controls. Results: Despite common rsFC with the fronto-insular cortex (FIC), the SMA proper and preSMA were mainly correlated with the sensorimotor areas and cognitive-related regions, respectively. In stroke patients, the SMA proper and preSMA exhibited completely different functional reorganization patterns: the former showed increased rsFCs with the primary sensorimotor area and caudal cingulate motor area (CMA) of the motor execution network, whereas the latter showed increased rsFC with the rostral CMA of the motor control network. Both of the two SMA subregions showed decreased rsFC with the FIC in stroke patients; the preSMA additionally showed decreased rsFC with the prefrontal cortex (PFC). Conclusion: Although both SMA subregions exhibit functional disconnection with the cognitive-related areas, the SMA proper is implicated in the functional reorganization within the motor execution network, whereas the preSMA is involved in the functional reorganization within the motor control network in stroke patients.

PMID: 32184712 [PubMed]

Neural correlates of non-specific skin conductance responses during resting state fMRI.

Thu, 03/19/2020 - 21:30
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Neural correlates of non-specific skin conductance responses during resting state fMRI.

Neuroimage. 2020 Mar 14;:116721

Authors: Gertler J, Novotny S, Poppe A, Chung YS, Gross JJ, Pearlson G, Stevens MC

Abstract
Skin conductance responses (SCRs) reliably occur in the absence of external stimulation. However, the neural correlates of these non-specific SCRs have been less explored than brain activity associated with stimulus-elicited SCRs. This study modeled spontaneous skin conductance responses observed during an unstructured resting state fMRI scan in 58 adolescents. A Finite Impulse Response (FIR) fMRI model was used to detect any type of hemodynamic response shape time-locked to non-specific SCRs; the shape of these responses was then carefully characterized. The strongest evidence for signal change was found in several sub-regions of sensorimotor cortex. There also was evidence for engagement of discrete areas within the lateral surfaces of the parietal lobe, cingulate cortex, fronto-insular operculum, and both visual and auditory primary processing areas. The hemodynamic profile measured by FIR modeling clearly resembled an event-related response. However, it was a complex response, best explained by two quickly successive, but opposing neuronal impulses across all brain regions - a brief positive response that begins several seconds prior to the SCR with a much longer negative neuronal impulse beginning shortly after the SCR onset. Post hoc exploratory analyses linked these two hemodynamic response phases to different emotion-related individual differences. In conclusion, this study shows the neural correlates of non-specific SCRs are a widespread, cortical network of brain regions engaged in a complex, seemingly biphasic fashion. This bimodal response profile should be considered in replication studies that attempt to directly link brain activity to possible homeostatic mechanisms or seek evidence for alternative mechanisms.

PMID: 32184189 [PubMed - as supplied by publisher]

Uncovering complex central autonomic networks at rest: a functional magnetic resonance imaging study on complex cardiovascular oscillations.

Thu, 03/19/2020 - 21:30
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Uncovering complex central autonomic networks at rest: a functional magnetic resonance imaging study on complex cardiovascular oscillations.

J R Soc Interface. 2020 Mar;17(164):20190878

Authors: Valenza G, Passamonti L, Duggento A, Toschi N, Barbieri R

Abstract
This study aims to uncover brain areas that are functionally linked to complex cardiovascular oscillations in resting-state conditions. Multi-session functional magnetic resonance imaging (fMRI) and cardiovascular data were gathered from 34 healthy volunteers recruited within the human connectome project (the '100-unrelated subjects' release). Group-wise multi-level fMRI analyses in conjunction with complex instantaneous heartbeat correlates (entropy and Lyapunov exponent) revealed the existence of a specialized brain network, i.e. a complex central autonomic network (CCAN), reflecting what we refer to as complex autonomic control of the heart. Our results reveal CCAN areas comprised the paracingulate and cingulate gyri, temporal gyrus, frontal orbital cortex, planum temporale, temporal fusiform, superior and middle frontal gyri, lateral occipital cortex, angular gyrus, precuneous cortex, frontal pole, intracalcarine and supracalcarine cortices, parahippocampal gyrus and left hippocampus. The CCAN visible at rest does not include the insular cortex, thalamus, putamen, amygdala and right caudate, which are classical CAN regions peculiar to sympatho-vagal control. Our results also suggest that the CCAN is mainly involved in complex vagal control mechanisms, with possible links with emotional processing networks.

PMID: 32183642 [PubMed - in process]

[Resting state functional magnetic resonance imaging applications in the temporal lobe epilepsy surgery].

Wed, 03/18/2020 - 21:28
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[Resting state functional magnetic resonance imaging applications in the temporal lobe epilepsy surgery].

Rev Neurol. 2020 Apr 01;70(7):257-263

Authors: García-Casares N, Fernández-Cornax A

Abstract
INTRODUCTION: There is a growing interest in the functional magnetic resonance imaging (fMRI) and his clinical applications in the planning of the epilepsy surgery. The conventional method of using the fMRI require the cooperation of the patient. Currently it is being studied the possibility of using this technique without the performance of specific tasks by the patient in the modality of resting state.
AIM: To study the clinical applications of the fMRI in resting state, in the planning of the temporal epilepsy surgery.
DEVELOPMENT: We carried out a systematic review helped by a bibliographic research in different databases, including PubMed, Science Direct, Scopus and Cochrane. We included articles focused on the use of resting state fMRI written in Spanish and English, excluding studies exclusively focused on pediatric patients or related with the presence of epileptogenic tumors and other structural pathologies except for the temporal sclerosis. We found 11 articles which describe different clinical applications for the resting state fMRI in the context of epilepsy surgery. In five, the objective was to identify the epileptogenic hemisphere; in two, it was planned to predict the improvement of the disease; and in four of the articles, it has been studied the possibility of predicting worsening of cognitive functions that are frequently affected after the surgery.
CONCLUSION: The resting state fMRI is a technique with a great potential of developing an useful tool in the context of planning the epilepsy surgery, as well as in the prediction of postsurgical morbidity.

PMID: 32182373 [PubMed - as supplied by publisher]

Identifying brain network topology changes in task processes and psychiatric disorders.

Wed, 03/18/2020 - 21:28
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Identifying brain network topology changes in task processes and psychiatric disorders.

Netw Neurosci. 2020;4(1):257-273

Authors: Rezaeinia P, Fairley K, Pal P, Meyer FG, Carter RM

Abstract
A central goal in neuroscience is to understand how dynamic networks of neural activity produce effective representations of the world. Advances in the theory of graph measures raise the possibility of elucidating network topologies central to the construction of these representations. We leverage a result from the description of lollipop graphs to identify an iconic network topology in functional magnetic resonance imaging data and characterize changes to those networks during task performance and in populations diagnosed with psychiatric disorders. During task performance, we find that task-relevant subnetworks change topology, becoming more integrated by increasing connectivity throughout cortex. Analysis of resting state connectivity in clinical populations shows a similar pattern of subnetwork topology changes; resting scans becoming less default-like with more integrated sensory paths. The study of brain network topologies and their relationship to cognitive models of information processing raises new opportunities for understanding brain function and its disorders.

PMID: 32181418 [PubMed]

Psychopathy and Corticostriatal Connectivity: The Link to Criminal Behavior in Methamphetamine Dependence.

Wed, 03/18/2020 - 21:28
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Psychopathy and Corticostriatal Connectivity: The Link to Criminal Behavior in Methamphetamine Dependence.

Front Psychiatry. 2020;11:90

Authors: Hoffman WF, Jacobs MB, Dennis LE, McCready HD, Hickok AW, Smith SB, Kohno M

Abstract
Methamphetamine use and psychopathy are associated with criminal behavior; however, it is unclear how methamphetamine use and psychopathy interact to promote violent, economic and drug offenses. Abnormalities in corticostriatal functional connectivity are exhibited in both psychopathic and methamphetamine dependent individuals, which may contribute to criminal behavior through maladaptive and impulsive decision-making processes. This study shows that psychopathic traits contribute to weaker corticostriatal connectivity in methamphetamine dependence and contributes to an increase in criminal behavior. As the propensity to engage in criminal activity is dependent on a number of factors, a hierarchical regression identifies the contribution of the impulsive antisocial domain of psychopathy, anxiety, years of methamphetamine use and corticostriatal connectivity on different types of criminal offenses. Methamphetamine use and psychopathic traits reduce treatment responsiveness and increase the likelihood of recidivism, and it is therefore important to understand the factors underlying the propensity to engage in criminal behavior.

PMID: 32180738 [PubMed]

Disambiguating the role of blood flow and global signal with partial information decomposition.

Wed, 03/18/2020 - 21:28
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Disambiguating the role of blood flow and global signal with partial information decomposition.

Neuroimage. 2020 Mar 13;:116699

Authors: Colenbier N, Van de Steen F, Uddin LQ, Poldrack RA, Calhoun VD, Marinazzo D

Abstract
Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal. Global signal regression (GSR) effectively removes the impact of physiological noise and other artifacts, but at the same time it alters correlational patterns in unpredicted ways. Performing GSR taking into account the underlying physiology (mainly the blood arrival time) has been proven to be beneficial. From these observations we aimed to: 1) characterize the effect of GSR on network-level functional connectivity in a large dataset; 2) assess the complementary role of global signal and vessels; and 3) use the framework of partial information decomposition to further look into the joint dynamics of the global signal and vessels, and their respective influence on the dynamics of cortical areas. We observe that GSR affects intrinsic connectivity networks in the connectome in a non-uniform way. Furthermore, by estimating the predictive information of blood flow and the global signal using partial information decomposition, we observe that both signals are present in different amounts across intrinsic connectivity networks. Simulations showed that differences in blood arrival time can largely explain this phenomenon, while using hemodynamic and calcium mouse recordings we were able to confirm the presence of vascular effects, as calcium recordings lack hemodynamic information. With these results we confirm network-specific effects of GSR and the importance of taking blood flow into account for improving de-noising methods. Additionally, and beyond the mere issue of data denoising, we quantify the diverse and complementary effect of global and vessel BOLD signals on the dynamics of cortical areas.

PMID: 32179104 [PubMed - as supplied by publisher]

Hippocampal functional network: The mediating role between obsession and anxiety in adult patients with obsessive-compulsive disorder.

Tue, 03/17/2020 - 21:27
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Hippocampal functional network: The mediating role between obsession and anxiety in adult patients with obsessive-compulsive disorder.

World J Biol Psychiatry. 2020 Mar 16;:1-11

Authors: Li K, Zhang H, Wang B, Yang Y, Zhang M, Li W, Li X, Lv L, Zhao J, Zhang H

Abstract
Objectives: Anxiety is a very common symptom and closely related to obsessive-compulsive symptoms in obsessive-compulsive disorder (OCD). However, the association between anxiety and obsessive-compulsive symptoms at the hippocampus network level remains unclear.Methods: This study enrolled 42 patients with OCD and 42 healthy controls (HCs), who underwent resting-state functional magnetic resonance imaging (fMRI) and clinical evaluation. Multiple linear regression analysis was performed to investigate the behavioural significance and interactive effects of obsessive-compulsive and anxiety symptoms on the hippocampus functional connectivity (HFC). The mediation analysis model was used to explore whether the hippocampus functional connectivity (FC) network indirectly mediated the relationship between obsessive-compulsive symptoms and anxiety.Results: Results showed that the FCs with the cerebellum, middle temporal gyrus (MTG) and anterior cingulate gyrus (ACG) were increased in the hippocampus FC network in patients with OCD compared with those in HCs. The regions of interactive effects between anxiety and obsession, which are mainly located in the prefrontal cortex and MTG, were positively correlated. The mediation effect is 0.018 between obsession and anxiety on the HFC networks in patients with OCD.Conclusions: The FC between the hippocampus and MTG plays a key role in the relationship between anxiety and obsession.

PMID: 32174208 [PubMed - as supplied by publisher]

Bootstrapping promotes the RSFC-behavior associations: An application of individual cognitive traits prediction.

Tue, 03/17/2020 - 21:27
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Bootstrapping promotes the RSFC-behavior associations: An application of individual cognitive traits prediction.

Hum Brain Mapp. 2020 Mar 16;:

Authors: Wei L, Jing B, Li H

Abstract
Resting-state functional connectivity (RSFC) records enormous functional interaction information between any pair of brain nodes, which enriches the individual-phenotypic prediction. To reduce high-dimensional features, correlation analysis is a common way for feature selection. However, resting state fMRI signal exhibits typically low signal-to-noise ratio and the correlation analysis is sensitive to outliers and data distribution, which may bring unstable features to prediction. To alleviate this problem, a bootstrapping-based feature selection framework was proposed and applied to connectome-based predictive modeling, support vector regression, least absolute shrinkage and selection operator, and Ridge regression to predict a series of cognitive traits based on Human Connectome Project data. To systematically investigate the influences of different parameter settings on the bootstrapping-based framework, 216 parameter combinations were evaluated and the best performance among them was identified as the final prediction result for each cognitive trait. By using the bootstrapping methods, the best prediction performances outperformed the baseline method in all four prediction models. Furthermore, the proposed framework could effectively reduce the feature dimension by retaining the more stable features. The results demonstrate that the proposed framework is an easy-to-use and effective method to improve RSFC prediction of cognitive traits and is highly recommended in future RSFC-prediction studies.

PMID: 32173976 [PubMed - as supplied by publisher]

Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T.

Tue, 03/17/2020 - 21:27
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Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T.

Neuroimage. 2020 Mar 12;:116731

Authors: Bhandari R, Kirilina E, Caan M, Suttrup J, De Sanctis T, De Angelis L, Keysers C, Gazzola V

Abstract
Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 T scanner using five sequences up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit.

PMID: 32173409 [PubMed - as supplied by publisher]

Causes and Consequences of Diagnostic Heterogeneity in Depression: Paths to Discovering Novel Biological Depression Subtypes.

Tue, 03/17/2020 - 21:27
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Causes and Consequences of Diagnostic Heterogeneity in Depression: Paths to Discovering Novel Biological Depression Subtypes.

Biol Psychiatry. 2020 Jan 28;:

Authors: Lynch CJ, Gunning FM, Liston C

Abstract
Depression is a highly heterogeneous syndrome that bears only modest correlations with its biological substrates, motivating a renewed interest in rethinking our approach to diagnosing depression for research purposes and new efforts to discover subtypes of depression anchored in biology. Here, we review the major causes of diagnostic heterogeneity in depression, with consideration of both clinical symptoms and behaviors (symptomatology and trajectory of depressive episodes) and biology (genetics and sexually dimorphic factors). Next, we discuss the promise of using data-driven strategies to discover novel subtypes of depression based on functional neuroimaging measures, including dimensional, categorical, and hybrid approaches to parsing diagnostic heterogeneity and understanding its biological basis. The merits of using resting-state functional magnetic resonance imaging functional connectivity techniques for subtyping are considered along with a set of technical challenges and potential solutions. We conclude by identifying promising future directions for defining neurobiologically informed depression subtypes and leveraging them in the future for predicting treatment outcomes and informing clinical decision making.

PMID: 32171465 [PubMed - as supplied by publisher]