scholarly journals Predictive utility of task-related functional connectivity vs. voxel activation

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249947
Author(s):  
Christian Habeck ◽  
Qolamreza Razlighi ◽  
Yaakov Stern
Keyword(s):  
Functional Connectivity ◽  
Brain Structure ◽  
Reference Model ◽  
Functional Neuroimaging ◽  
Research Effort ◽  
Cognitive Task ◽  
Cognitive Outcome ◽  
Predictive Utility ◽  
Fluid Reasoning ◽  
And Task

Functional connectivity, both in resting state and task performance, has steadily increased its share of neuroimaging research effort in the last 1.5 decades. In the current study, we investigated the predictive utility regarding behavioral performance and task information for 240 participants, aged 20–77, for both voxel activation and functional connectivity in 12 cognitive tasks, belonging to 4 cognitive reference domains (Episodic Memory, Fluid Reasoning, Perceptual Speed, and Vocabulary). We also added a model only comprising brain-structure information not specifically acquired during performance of a cognitive task. We used a simple brain-behavioral prediction technique based on Principal Component Analysis (PCA) and regression and studied the utility of both modalities in quasi out-of-sample predictions, using split-sample simulations (= 5-fold Monte Carlo cross validation) with 1,000 iterations for which a regression model predicting a cognitive outcome was estimated in a training sample, with a subsequent assessment of prediction success in a non-overlapping test sample. The sample assignments were identical for functional connectivity, voxel activation, and brain structure, enabling apples-to-apples comparisons of predictive utility. All 3 models that were investigated included the demographic covariates age, gender, and years of education. A minimal reference model using simple linear regression with just these 3 covariates was included for comparison as well and was evaluated with the same resampling scheme as described above. Results of the comparison between voxel activation and functional connectivity were mixed and showed some dependency on cognitive outcome; however, mean differences in predictive utility between voxel activation and functional connectivity were rather small in terms of within-modality variability or predictive success. More notably, only in the case of Fluid Reasoning did concurrent functional neuroimaging provided compelling about cognitive performance beyond structural brain imaging or the minimal reference model.

scholarly journals Survivors of SARS-CoV-2 Infection Show Neuropsychiatric Sequelae Measured by Surveys, Neurocognitive Testing, and Magnetic Resonance Imaging: Preliminary Results

2021 ◽  
Author(s):  
Laura M. Hack ◽  
Jacob Brawer ◽  
Megan Chesnut ◽  
Xue Zhang ◽  
Max Wintermark ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Functional Connectivity ◽  
Brain Structure ◽  
Functional Neuroimaging ◽  
Structure And Function ◽  
Self Report ◽  
Neurocognitive Testing ◽  
Preliminary Results ◽  
Brain Structure And Function ◽  
And Function

AbstractA significant number of individuals experience physical, cognitive, and mental health symptoms in the months after acute infection with SARS-CoV-2, the virus that causes COVID-19. This study assessed depressive and anxious symptoms, cognition, and brain structure and function in participants with symptomatic COVID-19 confirmed by PCR testing (n=100) approximately three months following infection, leveraging self-report questionnaires, objective neurocognitive testing, and structural and functional neuroimaging data. Preliminary results demonstrated that over 1/5 of our cohort endorsed clinically significant depressive and/or anxious symptoms, and >40% of participants had cognitive impairment on objective testing across multiple domains, consistent with ‘brain-fog’. While depression and one domain of quality of life (physical functioning) were significantly different between hospitalized and non-hospitalized participants, anxiety, cognitive impairment, and most domains of functioning were not, suggesting that the severity of SARS-CoV-2 infection does not necessarily relate to the severity of neuropsychiatric outcomes and impaired functioning in the months after infection. Furthermore, we found that the majority of participants in a subset of our cohort who completed structural and functional neuroimaging (n=15) had smaller olfactory bulbs and sulci in conjunction with anosmia. We also showed that this subset of participants had dysfunction in attention network functional connectivity and ventromedial prefrontal cortex seed-based functional connectivity. These functional imaging dysfunctions have been observed previously in depression and correlated with levels of inflammation. Our results support and extend previous findings in the literature concerning the neuropsychiatric sequelae associated with long COVID. Ongoing data collection and analyses within this cohort will allow for a more comprehensive understanding of the longitudinal relationships between neuropsychiatric symptoms, neurocognitive performance, brain structure and function, and inflammatory and immune profiles.

scholarly journals The role of neural flexibility in cognitive aging

2021 ◽  
Author(s):  
Eleanna Varangis ◽  
Weiwei Qi ◽  
Yaakov Stern ◽  
Seonjoo Lee
Keyword(s):  
Functional Connectivity ◽  
Cognitive Performance ◽  
Resting State ◽  
Cognitive Aging ◽  
Cognitive Task ◽  
Cognitive Networks ◽  
Cognitive Outcomes ◽  
Matrix Reasoning ◽  
Flexibility Measures ◽  
And Task

AbstractStudies assessing relationships between brain and cognitive changes in healthy aging have shown that a variety of aspects of brain structure and function explain a significant portion of the variability in cognitive outcomes throughout adulthood. Many studies assessing relationships between brain function and cognition have utilized time-averaged, or static functional connectivity methods to explore ways in which brain network organization may contribute to aspects of cognitive aging. However, recent studies in this field have suggested that time-varying, or dynamic measures of functional connectivity, which assess changes in functional connectivity throughout a scan session, may play a stronger role in explaining cognitive outcomes in healthy young adults. Further, both static and dynamic functional connectivity studies suggest that there may be differences in patterns of brain-cognition relationships as a function of whether or not the participant is performing a task during the scan. Thus, the goals of the present study were threefold: (1) assess whether dynamic connectivity (neural flexibility) during both resting as well as task-based scans is related to participant age and cognitive performance in a lifespan aging sample, (2) determine whether neural flexibility moderates relationships between age and cognitive performance, and (3) explore differences in neural flexibility between rest and task. Participants in the study were 423 healthy adults between the ages of 20-80 who provided resting state and/or task-based (Matrix Reasoning) functional magnetic resonance imaging (fMRI) scan data as part of their participation in two ongoing studies of cognitive aging. Neural flexibility measures from both resting and task-based scans reflected the number of times each node changed network assignment, and were averaged both across the whole brain (global neural flexibility) as well as within nine somatosensory/cognitive networks. Results showed that neural flexibility during the task was higher in older adults, and that neural flexibility in Default Mode and Visual networks was negatively related to performance on the Matrix Reasoning task. Resting state neural flexibility was not significantly related to either participant age or cognitive performance. Additionally, no neural flexibility measures that significantly moderated relationships between participant age and cognitive outcomes. Further, neural flexibility differed as a function of scan type, with resting state neural flexibility exhibiting significantly more variability than task-based neural flexibility. Thus, neural flexibility measures computed during a cognitive task may be more strongly related to cognitive performance across the adult lifespan, and are more sensitive to the effects of participant age on brain organization.

scholarly journals Peripheral BDNF: a candidate biomarker of healthy neural activity during learning is disrupted in schizophrenia

2014 ◽  
Vol 45 (4) ◽  
pp. 841-854 ◽  
Author(s):  
A. J. Skilleter ◽  
C. S. Weickert ◽  
A. Vercammen ◽  
R. Lenroot ◽  
T. W. Weickert
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Healthy Adults ◽  
Enzyme Linked Immunosorbent Assay ◽  
Association Learning ◽  
Healthy Humans ◽  
Important Regulator ◽  
Learning Test ◽  
Parietal Cortices ◽  
And Task

Background.Brain-derived neurotrophic factor (BDNF) is an important regulator of synaptogenesis and synaptic plasticity underlying learning. However, a relationship between circulating BDNF levels and brain activity during learning has not been demonstrated in humans. Reduced brain BDNF levels are found in schizophrenia and functional neuroimaging studies of probabilistic association learning in schizophrenia have demonstrated reduced activity in a neural network that includes the prefrontal and parietal cortices and the caudate nucleus. We predicted that brain activity would correlate positively with peripheral BDNF levels during probabilistic association learning in healthy adults and that this relationship would be altered in schizophrenia.Method.Twenty-five healthy adults and 17 people with schizophrenia or schizo-affective disorder performed a probabilistic association learning test during functional magnetic resonance imaging (fMRI). Plasma BDNF levels were measured by enzyme-linked immunosorbent assay (ELISA).Results.We found a positive correlation between circulating plasma BDNF levels and brain activity in the parietal cortex in healthy adults. There was no relationship between plasma BDNF levels and task-related activity in the prefrontal, parietal or caudate regions in schizophrenia. A direct comparison of these relationships between groups revealed a significant diagnostic difference.Conclusions.This is the first study to show a relationship between peripheral BDNF levels and cortical activity during learning, suggesting that plasma BDNF levels may reflect learning-related brain activity in healthy humans. The lack of relationship between plasma BDNF and task-related brain activity in patients suggests that circulating blood BDNF may not be indicative of learning-dependent brain activity in schizophrenia.

scholarly journals Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory Simchick ◽  
Kelly M. Scheulin ◽  
Wenwu Sun ◽  
Sydney E. Sneed ◽  
Madison M. Fagan ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Brain Network ◽  
Network Activity ◽  
Anatomical Structures ◽  
Healthy Control ◽  
And Task

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

Contributions of Brain Function and Structure to Three Different Domains of Cognitive Control in Normal Aging

2021 ◽  
pp. 1-22
Author(s):  
Jenny R. Rieck ◽  
Giulia Baracchini ◽  
Cheryl L. Grady
Keyword(s):  
Working Memory ◽  
Cognitive Control ◽  
Task Performance ◽  
Brain Structure ◽  
Functional Activity ◽  
Brain Activity ◽  
Diffusion Imaging ◽  
Normal Aging ◽  
Control Mechanisms ◽  
And Task

Cognitive control involves the flexible allocation of mental resources during goal-directed behavior and comprises three correlated but distinct domains—inhibition, shifting, and working memory. The work of Don Stuss and others has demonstrated that frontal and parietal cortices are crucial to cognitive control, particularly in normal aging, which is characterized by reduced control mechanisms. However, the structure–function relationships specific to each domain and subsequent impact on performance are not well understood. In the current study, we examined both age and individual differences in functional activity associated with core domains of cognitive control in relation to fronto-parietal structure and task performance. Participants ( N = 140, aged 20–86 years) completed three fMRI tasks: go/no-go (inhibition), task switching (shifting), and n-back (working memory), in addition to structural and diffusion imaging. All three tasks engaged a common set of fronto-parietal regions; however, the contributions of age, brain structure, and task performance to functional activity were unique to each domain. Aging was associated with differences in functional activity for all tasks, largely in regions outside common fronto-parietal control regions. Shifting and inhibition showed greater contributions of structure to overall decreases in brain activity, suggesting that more intact fronto-parietal structure may serve as a scaffold for efficient functional response. Working memory showed no contribution of structure to functional activity but had strong effects of age and task performance. Together, these results provide a comprehensive and novel examination of the joint contributions of aging, performance, and brain structure to functional activity across multiple domains of cognitive control.

scholarly journals Predicting dysfunctional age-related task activations from resting-state network alterations

2019 ◽  
Author(s):  
Ravi D. Mill ◽  
Brian A. Gordon ◽  
David A. Balota ◽  
Jeffrey M. Zacks ◽  
Michael W. Cole
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Functional Connectivity ◽  
Resting State ◽  
Cognitive Task ◽  
Low Risk ◽  
Flow Modeling ◽  
Resting State Functional Connectivity ◽  
Age Related

AbstractAlzheimer’s disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the timecourse of illness. Study of these fMRI correlates of unhealthy aging has been conducted in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC network alterations associated with Alzheimer’s disease disrupt the ability for activations to flow between brain regions, leading to aberrant task activations. We apply this activity flow modeling framework in a large sample of clinically unimpaired older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) risk factors for AD. We identified healthy task activations in individuals at low risk for AD, and then by estimating activity flow using at-risk AD restFC data we were able to predict the altered at-risk AD task activations. Thus, modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy aged activations. These results provide evidence that activity flow over altered intrinsic functional connections may act as a mechanism underlying Alzheimer’s-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights linking restFC with cognitive task activations, this approach has potential clinical utility as it enables prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.Significance StatementDeveloping analytic approaches that can reliably predict features of Alzheimer’s disease is a major goal for cognitive and clinical neuroscience, with particular emphasis on identifying such diagnostic features early in the timeline of disease. We demonstrate the utility of an activity flow modeling approach, which predicts fMRI cognitive task activations in subjects identified as at-risk for Alzheimer’s disease. The approach makes activation predictions by transforming a healthy aged activation template via the at-risk subjects’ individual pattern of fMRI resting-state functional connectivity (restFC). The observed prediction accuracy supports activity flow as a mechanism linking age-related alterations in restFC and task activations, thereby providing a theoretical basis for incorporating restFC into imaging biomarker and personalized medicine interventions.

Functional Connectivity in Frontoparietal Network: Indicator of Preoperative Cognitive Function and Cognitive Outcome Following Surgery in Patients with Glioma

2017 ◽  
Vol 105 ◽  
pp. 913-922.e2 ◽  
Author(s):  
Stefan Lang ◽  
Ismael Gaxiola-Valdez ◽  
Michael Opoku-Darko ◽  
Lisa A. Partlo ◽  
Bradley G. Goodyear ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Functional Connectivity ◽  
Cognitive Outcome ◽  
Frontoparietal Network
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