scholarly journals Multifocal tDCS modulates resting-state functional connectivity in older adults depending on induced electric field and baseline connectivity

2020 ◽  
Author(s):  
Kilian Abellaneda-Pérez ◽  
Lídia Vaqué-Alcázar ◽  
Ruben Perellón-Alfonso ◽  
Cristina Solé-Padullés ◽  
Núria Bargalló ◽  
...  
Keyword(s):  
Older Adults ◽  
Electric Field ◽  
Electric Fields ◽  
Resting State ◽  
Element Model ◽  
Individual Variability ◽  
Neural Dynamics ◽  
Resting State Functional Connectivity ◽  
The Individual ◽  
Resting State Connectivity

AbstractBackgroundAdvancing age affects the brain’s resting-state functional networks. Combining non-invasive brain stimulation (NIBS) with neuroimaging is a promising approach to modulate activity across resting-state functional systems and explore their true contribution to cognitive function in aging. However, substantial individual variability in the response to NIBS has been reported and, hence, identifying the individual predictors of NIBS-induced modulatory effects is crucial if we are to harness their potential.MethodsThirty-one cognitively healthy older adults (71.68 ± 2.5 years; 19 females) underwent two different multifocal real tDCS conditions (C1 and C2) and a sham condition in a crossover design during a resting-state functional magnetic resonance imaging (rs-fMRI) acquisition. The real tDCS conditions were designed to induce two distinct electric field distribution patterns either targeting generalized cortical overactivity or a dissociation between the frontal areas and the posteromedial cortex. Stimulation was delivered through an MRI-compatible device using 8 small circular electrodes. Each individuals’ anatomical T1-weighted MRI was used to generate a finite element model to define the individual electric field generated by each tDCS condition.ResultsThe two tDCS conditions modulated resting-state connectivity differently. C1 increased the coactivation of numerous functional couplings as compared to sham, however, a smaller amount of connections increased in C1 as compared to C2, while no differences between C2 and sham were appreciated. At the group level, C1-induced modulations primarily included temporo-occipital areas and distinct cerebellar regions. This functional pattern was anatomically consistent with the estimated distribution of the induced electric field in the C1 condition. Finally, at the individual level, the extent of tDCS-induced rs-fMRI modulation in C1 was predicted by baseline resting-state connectivity and simulation-based electric field magnitude.DiscussionOur results highlighted that multifocal tDCS procedures can effectively change neural dynamics in the elderly consistently with the spatial distribution of the estimated electric fields on the brain. Furthermore, we showed that specific brain factors that have been revealed to explain part of the individual variability to NIBS in young samples are also relevant in older adults. In accordance, designing multifocal tDCS configurations based on specific fMRI patterns appears to be a valuable approach to precisely adjust those complex neural dynamics sustaining cognition that are affected as a function of age. Furthermore, these innovative NIBS-based interventions should be individually-tailored based on subject-specific structural and functional data to ultimately boost their potential in aged populations.

scholarly journals Resting state functional connectivity in early post-anesthesia recovery is characterized by globally reduced anticorrelations

2019 ◽  
Author(s):  
Tommer Nir ◽  
Yael Jacob ◽  
Kuang-Han Huang ◽  
Arthur E. Schwartz ◽  
Jess W. Brallier ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Resting State ◽  
Regions Of Interest ◽  
Resting State Networks ◽  
Resting State Functional Connectivity ◽  
Healthy Human ◽  
Healthy Older Adults ◽  
Human Volunteers ◽  
Resting State Connectivity

ABSTRACTThough a growing body of literature is addressing the possible longer-term cognitive effects of anesthetics, to date no study has delineated the normal trajectory of neural recovery due to anesthesia alone in older adults. We obtained resting state functional magnetic resonance imaging scans on 62 healthy human volunteers between ages forty and eighty before, during, and after sevoflurane (general) anesthesia, in the absence of surgery, as part of a larger study on cognitive function post-anesthesia. Resting state networks expression decreased consistently one hour after emergence from anesthesia. This corresponded to a global reduction in anticorrelated functional connectivity post-anesthesia, seen across individual regions-of-interest. Positively correlated functional connectivity remained constant across peri-anesthetic states. All measures returned to baseline 1 day later, with individual regions-of-interest essentially returning to their pre-anesthesia connectivity levels. These results define normal peri-anesthetic changes in resting state connectivity in healthy older adults.

scholarly journals The effect of amyloid deposition on longitudinal resting-state functional connectivity in cognitively normal older adults

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Chemin Lin ◽  
Maria Ly ◽  
Helmet T. Karim ◽  
Wenjing Wei ◽  
Beth E. Snitz ◽  
...  
Keyword(s):  
Neural Networks ◽  
Older Adults ◽  
Cognitive Function ◽  
Functional Connectivity ◽  
Resting State ◽  
Clinical Symptoms ◽  
Rate Of Change ◽  
Resting State Functional Connectivity ◽  
Cognitive Changes ◽  
Cognitively Normal

Abstract Background Pathological processes contributing to Alzheimer’s disease begin decades prior to the onset of clinical symptoms. There is significant variation in cognitive changes in the presence of pathology, functional connectivity may be a marker of compensation to amyloid; however, this is not well understood. Methods We recruited 64 cognitively normal older adults who underwent neuropsychological testing and biannual magnetic resonance imaging (MRI), amyloid imaging with Pittsburgh compound B (PiB)-PET, and glucose metabolism (FDG)-PET imaging for up to 6 years. Resting-state MRI was used to estimate connectivity of seven canonical neural networks using template-based rotation. Using voxel-wise paired t-tests, we identified neural networks that displayed significant changes in connectivity across time. We investigated associations among amyloid and longitudinal changes in connectivity and cognitive function by domains. Results Left middle frontal gyrus connectivity within the memory encoding network increased over time, but the rate of change was lower with greater amyloid. This was no longer significant in an analysis where we limited the sample to only those with two time points. We found limited decline in cognitive domains overall. Greater functional connectivity was associated with better attention/processing speed and executive function (independent of time) in those with lower amyloid but was associated with worse function with greater amyloid. Conclusions Increased functional connectivity serves to preserve cognitive function in normal aging and may fail in the presence of pathology consistent with compensatory models.

scholarly journals Differential resting state connectivity responses to glycemic state in type 1 diabetes

2019 ◽  
Author(s):  
Lisa Parikh ◽  
Dongju Seo ◽  
Cheryl Lacadie ◽  
Renata Belfort-DeAguiar ◽  
Derek Groskreutz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Functional Connectivity ◽  
Resting State ◽  
Medical Center ◽  
Academic Medical Center ◽  
Angular Gyrus ◽  
Resting State Functional Connectivity ◽  
The Impact ◽  
Resting State Connectivity

Abstract Context Individuals with type 1 diabetes (T1DM) have alterations in brain activity which have been postulated to contribute to the adverse neurocognitive consequences of T1DM; however, the impact of T1DM and hypoglycemic unawareness on the brain’s resting state activity remains unclear. Objective To determine whether individuals with T1DM and hypoglycemia unawareness (T1DM-Unaware) had changes in the brain resting state functional connectivity compared to healthy controls (HC) and those with T1DM and hypoglycemia awareness (T1DM-Aware). Design Observational study Setting Academic medical center Participants 27 individuals with T1DM and 12 healthy control volunteers participated in the study. Intervention All participants underwent BOLD resting state fMRI brain imaging during a 2-step hyperinsulinemic euglycemic (90 mg/dl)-hypoglycemic (60mg/dl) clamp. Outcome Changes in resting state functional connectivity Results Using two separate methods of functional connectivity analysis, we identified distinct differences in the resting state brain responses to mild hypoglycemia amongst HC, T1DM-Aware and T1DM-Unaware participants, particularly in the angular gyrus, an integral component of the default mode network (DMN). Furthermore, changes in angular gyrus connectivity also correlated with greater symptoms of hypoglycemia (r = 0.461, P = 0.003) as well as higher scores of perceived stress (r = 0.531, P = 0.016). Conclusion These findings provide evidence that individuals with T1DM have changes in the brain’s resting state connectivity patterns, which may be further associated with differences in awareness to hypoglycemia. These changes in connectivity may be associated with alterations in functional outcomes amongst individuals with T1DM.

scholarly journals BEM Modelling of High Voltage ELF electric field applied to a 3D pregnant woman model

2010 ◽  
Vol 6 (1) ◽  
pp. 31 ◽  
Author(s):  
Cristina Peratta ◽  
Andres Peratta ◽  
Dragan Poljak
Keyword(s):  
Pregnant Woman ◽  
Electric Field ◽  
Electric Fields ◽  
High Voltage ◽  
Medical Information ◽  
Three Dimensional ◽  
Low Frequency ◽  
Element Model ◽  
The Body ◽  
Geometrical Properties

The paper introduces a three dimensional multidomainboundary element model of a pregnant woman and foetus for the analysis of exposure to high voltage extremely low frequency electric fields. The definition of the differentphysical and geometrical properties of the relevant tissues is established according to medical information available in existing literature. The model takes into account changes in geometry, body mass, body fat, and overall chemical composition in the body which influence the electrical properties, throughout the different gestational periods. The developed model is used to solve the case of exposure to overhead power transmission lines at different stages of pregnancy including weeks 8, 13, 26 and 38. The results obtained are in line with those published in the earlier works considering different approaches. In addition, a sensitivity analysis involving varying scenarios of conductivity, foetus postures and geometry for each stage is defined and solved. Finally, a correlation between the externally applied electric field and the current density inside the foetus is established and the zones of maximum exposure are identified.

scholarly journals Discriminating Suicide Attempters and Predicting Suicide Risk Using Altered Frontolimbic Resting-State Functional Connectivity in Patients With Bipolar II Disorder

2020 ◽  
Vol 11 ◽  
Author(s):  
Rongxin Zhu ◽  
Shui Tian ◽  
Huan Wang ◽  
Haiteng Jiang ◽  
Xinyi Wang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Suicide Risk ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Resting State Functional Connectivity ◽  
Bipolar Ii Disorder ◽  
Individual Level ◽  
Bipolar Ii ◽  
The Individual

Bipolar II disorder (BD-II) major depression episode is highly associated with suicidality, and objective neural biomarkers could be key elements to assist in early prevention and intervention. This study aimed to integrate altered brain functionality in the frontolimbic system and machine learning techniques to classify suicidal BD-II patients and predict suicidality risk at the individual level. A cohort of 169 participants were enrolled, including 43 BD-II depression patients with at least one suicide attempt during a current depressive episode (SA), 62 BD-II depression patients without a history of attempted suicide (NSA), and 64 demographically matched healthy controls (HCs). We compared resting-state functional connectivity (rsFC) in the frontolimbic system among the three groups and explored the correlation between abnormal rsFCs and the level of suicide risk (assessed using the Nurses' Global Assessment of Suicide Risk, NGASR) in SA patients. Then, we applied support vector machines (SVMs) to classify SA vs. NSA in BD-II patients and predicted the risk of suicidality. SA patients showed significantly decreased frontolimbic rsFCs compared to NSA patients. The left amygdala-right middle frontal gyrus (orbital part) rsFC was negatively correlated with NGASR in the SA group, but not the severity of depressive or anxiety symptoms. Using frontolimbic rsFCs as features, the SVMs obtained an overall 84% classification accuracy in distinguishing SA and NSA. A significant correlation was observed between the SVMs-predicted NGASR and clinical assessed NGASR (r = 0.51, p = 0.001). Our results demonstrated that decreased rsFCs in the frontolimbic system might be critical objective features of suicidality in BD-II patients, and could be useful for objective prediction of suicidality risk in individuals.

scholarly journals (334) BMI associated sex differences in pain reports and resting state functional connectivity in older adults

2016 ◽  
Vol 17 (4) ◽  
pp. S59
Author(s):  
S. Atalla ◽  
J. Gore ◽  
S. Bruehl ◽  
B. Rogers ◽  
M. Dietrich ◽  
...  
Keyword(s):  
Older Adults ◽  
Sex Differences ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Functional Connectivity ◽  
Pain Reports

Timing dysfunction and cerebellar resting state functional connectivity abnormalities in youth at clinical high-risk for psychosis

2020 ◽  
pp. 1-10 ◽  
Author(s):  
K. Juston Osborne ◽  
Katherine S. F. Damme ◽  
Tina Gupta ◽  
Derek J. Dean ◽  
Jessica A. Bernard ◽  
...  
Keyword(s):  
High Risk ◽  
Resting State ◽  
Negative Symptoms ◽  
Brain Regions ◽  
Internal Clock ◽  
Clinical High Risk ◽  
Resting State Functional Connectivity ◽  
Schizophrenia Spectrum ◽  
Temporal Bisection Task ◽  
Resting State Connectivity

Abstract Background Consistent with pathophysiological models of psychosis, temporal disturbances in schizophrenia spectrum populations may reflect abnormal cortical (e.g. prefrontal cortex) and subcortical (e.g. striatum) cerebellar connectivity. However, few studies have examined associations between cerebellar connectivity and timing dysfunction in psychosis populations, and none have been conducted in youth at clinical high-risk (CHR) for psychosis. Thus, it is currently unknown if impairments in temporal processes are present in CHR youth or how they may be associated with cerebellar connectivity and worsening of symptoms. Methods A total of 108 (56 CHR/52 controls) youth were administered an auditory temporal bisection task along with a resting state imaging scan to examine cerebellar resting state connectivity. Positive and negative symptoms at baseline and 12 months later were also quantified. Results Controlling for alcohol and cannabis use, CHR youth exhibited poorer temporal accuracy compared to controls, and temporal accuracy deficits were associated with abnormal connectivity between the bilateral anterior cerebellum and a right caudate/nucleus accumbens striatal cluster. Poor temporal accuracy accounted for 11% of the variance in worsening of negative symptoms over 12 months. Conclusions Behavioral findings suggest CHR youth perceive durations of auditory tones as shortened compared to objective time, which may indicate a slower internal clock. Poorer temporal accuracy in CHR youth was associated with abnormalities in brain regions involved in an important cerebellar network implicated in prominent pathophysiological models of psychosis. Lastly, temporal accuracy was associated with worsening of negative symptoms across 12 months, suggesting temporal dysfunction may be sensitive to illness progression.

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