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Relating individual differences in cognitive traits to brain functional organization is a long-lasting challenge for the neuroscience community. Individual intelligence scores were previously predicted from whole-brain connectivity patterns, extracted from functional magnetic resonance imaging (fMRI) data acquired at rest. Recently, it was shown that task-induced brain activation maps outperform these resting-state connectivity patterns in predicting individual intelligence, suggesting that a cognitively demanding environment improves prediction of cognitive abilities. Here, we use data from the Human Connectome Project to predict task-induced brain activation maps from resting-state fMRI, and proceed to use these predicted activity maps to further predict individual differences in a variety of traits. While models based on original task activation maps remain the most accurate, models based on predicted maps significantly outperformed those based on the resting-state connectome. Thus, we provide a promising approach for the evaluation of measures of human behavior from brain activation maps, that could be used without having participants actually perform the tasks.

The normal variability in breath size and frequency results in breath-to-breath variability of end-tidal PCO2 (PETCO2), the measured variable, and arterial partial pressure of carbon dioxide (PaCO2), the independent variable affecting cerebral blood flow (CBF). This study examines the effect of variability in PaCO2 on the pattern of resting-state functional MRI (rs-fMRI) connectivity. A region of interest (ROI)-to-ROI and Seed-to-Voxel first-level bivariate correlation, hemodynamic response function (hrf)-weighted analysis for measuring rs-fMRI connectivity was performed during two resting-state conditions: (a) normal breathing associated with breath-to-breath variation in PaCO2 (poikilocapnia), and (b) normal breathing with breath-to-breath variability of PETCO2 dampened using sequential rebreathing (isocapnia). End-tidal PCO2 (PETCO2) was used as a measurable surrogate for fluctuations of PaCO2. During poikilocapnia, enhanced functional connections were found between the cerebellum and inferior frontal and supramarginal gyrus (SG), visual cortex and occipital fusiform gyrus; and between the primary visual network (PVN) and the hippocampal formation. During isocapnia, these associations were not seen, rather enhanced functional connections were identified in the corticostriatal pathway between the putamen and intracalacarine cortex, supracalcarine cortex (SCC), and precuneus cortex. We conclude that vascular responses to variations in PETCO2, account for at least some of the observed resting state synchronization of blood oxygenation level-dependent (BOLD) signals.

Introduction A meta-analysis by Gürsel et al. (2018) found altered functional connectivity in OCD patients within and between default mode (DMN), salience (SN), and frontoparietal networks (FPN), as well as evidence for aberrant fronto-striatal circuitry. Objectives Testing the replicability of meta-analysis rsfMRI findings in OCD patients. Methods We measured functional connectivity during resting-state fMRI in a sample of OCD patients (n=24) and controls matched for age and sex (n=33). The CONN toolbox implemented in SPM was used to perform seed-to-voxel analysis using 30 seed regions based on the previous meta-analytic findings. Results OCD patients showed reduced functional connectivity between SN and DMN compared to controls, replicating previous findings. We did not observe significant group differences of functional connectivity within the DMN, SN, or FPN. The strongest finding consisted of altered connectivity between DMN and SN to the visual network. OCD patients showed reduced functional connectivity between the left lateral parietal seed (LPl) and the inferior lateral occipital pole left (iLOCl) compared to controls. Furthermore, the LPl was found to be hyperconnected with the right superior lateral occipital cortex (sLOCr) and the right precuneus. This finding was positively correlated to OCD symptom severity, especially compulsions. Conclusions Our findings replicated partly the meta-analysis findings, specifically reduced connectivity between SN and DMN. Using seeds based on the meta-analysis, we identified aberrations between the SN and, in particular, the DMN to the visual network. This raises the question about the visual system’s involvement in OCD symptoms and the abnormal connectivity of a unimodal region to the multimodal DMN. Disclosure No significant relationships.

The normal variability in breath size and frequency results in breath-to-breath variability of end-tidal PCO2 (PETCO2), the measured variable, and arterial partial pressure of carbon dioxide (PaCO2), the independent variable affecting cerebral blood flow (CBF). This study examines the effect of variability in PaCO2 on the pattern of resting-state functional MRI (rs-fMRI) connectivity. A region of interest (ROI)-to-ROI and Seed-to-Voxel first-level bivariate correlation, hemodynamic response function (hrf)-weighted analysis for measuring rs-fMRI connectivity was performed during two resting-state conditions: (a) normal breathing associated with breath-to-breath variation in PaCO2 (poikilocapnia), and (b) normal breathing with breath-to-breath variability of PETCO2 dampened using sequential rebreathing (isocapnia). End-tidal PCO2 (PETCO2) was used as a measurable surrogate for fluctuations of PaCO2. During poikilocapnia, enhanced functional connections were found between the cerebellum and inferior frontal and supramarginal gyrus (SG), visual cortex and occipital fusiform gyrus; and between the primary visual network (PVN) and the hippocampal formation. During isocapnia, these associations were not seen, rather enhanced functional connections were identified in the corticostriatal pathway between the putamen and intracalacarine cortex, supracalcarine cortex (SCC), and precuneus cortex. We conclude that vascular responses to variations in PETCO2, account for at least some of the observed resting state synchronization of blood oxygenation level-dependent (BOLD) signals. [ABSTRACT FROM AUTHOR]

The User-Friendly Functional Connectivity (UF2C) software provides researchers with a platform to analyze functional magnetic resonance neuroimages from the initial preprocessing steps to the generation of manuscript-quality figures. UF2C is implemented in Matlab language and falls within the FreeBSD license. Our toolbox builds on a combination of existing methods to increase the user’s power to perform different types of resting-state functional connectivity, event-related, and task activation analyses. To keep up with ongoing advances in this field, UF2C is regularly updated to reflect these advances and incorporate user demands.

Resting state functional connectivity magnetic resonance imaging (rsfcMRI) has become a key component of investigations of neurocognitive and psychiatric behaviors. Over the past two decades, several methods and paradigms have been adopted to utilize and interpret data from resting-state fluctuations in the brain. These findings have increased our understanding of changes in many disease states. As the amount of resting state data available for research increases with big datasets and data-sharing projects, it is important to review the established traditional analysis methods and recognize areas where research methodology can be adapted to better accommodate the scale and complexity of rsfcMRI analysis. In this paper, we review established methods of analysis as well as areas that have been receiving increasing attention such as dynamic rsfcMRI, independent vector analysis, multiband rsfcMRI and network of networks. [ABSTRACT FROM AUTHOR]

Introduction: Falls are associated with numerous risk factors, such as motor and cognitive impairments. However, the neural correlates of falls are poorly understood.Objectives: Here, we aimed to assess patterns of structural, and resting-state functional connectivity (FC) alterations related to falls in a group of older adults with a history of falls compared to non-fallers.Methods: Fourteen elderly fallers (mean age = 78.1 ± 1.5 yrs, >2 falls previous six months), and 20 healthy controls (mean age = 69.6 ± 1.3 yrs) were examined. All participants underwent a 3T MRI scan obtaining 3D T1-weighted images, and eyes-open resting-state (rs)-fMRI. Voxel-based morphometry was conducted to detect grey matter differences between the groups. Independent component analysis was conducted based on rs-fMRI and number of attention-and-motor related functional networks was identified and compared between groups using an independent-sample T-test.Results: No differences were observed in grey matter between the groups after correcting for age and gender (p > 0.01, FWEc). Compared with non-fallers, the fallers had lower FC in cerebellar, frontal and parietal cortical nodes within the sensorimotor network (SMN), lateral motor network (M1), Cerebellar network (CBL), frontal-striatal network (FSN), executive control network (ECN), and dorsal attention network (DAN). Moreover, fallers had increased FC in the basal ganglia network (BGN), Left paracentral in M1 and SMN, and right hippocampus in DAN (p < 0.01, FWEc).Conclusions: Among fallers, reduced connectivity was observed in areas that relate to integration of information, while increased connectivity was found in areas associated with motor and sensory information processing. Together, these results provide evidence to the complex multidimensionality of the neural underpinnings of falls. Furthermore, these findings may help emphasize the importance of interventions that target both motor and cognitive aspects. [ABSTRACT FROM AUTHOR]

The striatum codes motivated behavior. Delineating age-related differences within striatal circuitry can provide insights into neural mechanisms underlying ontogenic behavioral changes and vulnerabilities to mental disorders. To this end, a dual ventral/dorsal model of striatal function was examined using resting state intrinsic functional connectivity (iFC) imaging in 106 healthy individuals, ages 9–44. Broadly, the dorsal striatum (DS) is connected to prefrontal and parietal cortices and contributes to cognitive processes; the ventral striatum (VS) is connected to medial orbitofrontal and anterior cingulate cortices, and contributes to affective valuation and motivation. Findings revealed patterns of age-related changes that differed between VS and DS iFCs. We found an age-related increase in DS iFC with posterior cingulate cortex (pCC) that stabilized after the mid-twenties, but a decrease in VS iFC with anterior insula (aIns) and dorsal anterior cingulate cortex (dACC) that persisted into mid-adulthood. These distinct developmental trajectories of VS vs. DS iFC might underlie adolescents’ unique behavioral patterns and vulnerabilities to psychopathology, and also speaks to changes in motivational networks that extend well past 25 years old.

The striatum codes motivated behavior. Delineating age-related differences within striatal circuitry can provide insights into neural mechanisms underlying ontogenic behavioral changes and vulnerabilities to mental disorders. To this end, a dual ventral/dorsal model of striatal function was examined using resting state intrinsic functional connectivity (iFC) imaging in 106 healthy individuals, ages 9–44. Broadly, the dorsal striatum (DS) is connected to prefrontal and parietal cortices and contributes to cognitive processes; the ventral striatum (VS) is connected to medial orbitofrontal and anterior cingulate cortices, and contributes to affective valuation and motivation. Findings revealed patterns of age-related changes that differed between VS and DS iFCs. We found an age-related increase in DS iFC with posterior cingulate cortex (pCC) that stabilized after the mid-twenties, but a decrease in VS iFC with anterior insula (aIns) and dorsal anterior cingulate cortex (dACC) that persisted into mid-adulthood. These distinct developmental trajectories of VS vs. DS iFC might underlie adolescents’ unique behavioral patterns and vulnerabilities to psychopathology, and also speaks to changes in motivational networks that extend well past 25 years old. [ABSTRACT FROM AUTHOR]

• We present a method for prediction of individual traits from resting-state fMRI. • Transforming rs-data to predicted task maps improves trait prediction accuracy. • Combining multiple task contrasts improves trait prediction from both actual and predicted task maps. • The method is flexible and applicable to a variety of traits and tasks. Relating individual differences in cognitive traits to brain functional organization is a long-lasting challenge for the neuroscience community. Individual intelligence scores were previously predicted from whole-brain connectivity patterns, extracted from functional magnetic resonance imaging (fMRI) data acquired at rest. Recently, it was shown that task-induced brain activation maps outperform these resting-state connectivity patterns in predicting individual intelligence, suggesting that a cognitively demanding environment improves prediction of cognitive abilities. Here, we use data from the Human Connectome Project to predict task-induced brain activation maps from resting-state fMRI, and proceed to use these predicted activity maps to further predict individual differences in a variety of traits. While models based on original task activation maps remain the most accurate, models based on predicted maps significantly outperformed those based on the resting-state connectome. Thus, we provide a promising approach for the evaluation of measures of human behavior from brain activation maps, that could be used without having participants actually perform the tasks. [ABSTRACT FROM AUTHOR]

Introduction: A meta-analysis by Gürsel et al. (2018) found altered functional connectivity in OCD patients within and between default mode (DMN), salience (SN), and frontoparietal networks (FPN), as well as evidence for aberrant fronto-striatal circuitry. Objectives: Testing the replicability of meta-analysis rsfMRI findings in OCD patients. Methods: We measured functional connectivity during restingstate fMRI in a sample of OCD patients (n=24) and controls matched for age and sex (n=33). The CONN toolbox implemented in SPM was used to perform seed-to-voxel analysis using 30 seed regions based on the previous meta-analytic findings. Results: OCD patients showed reduced functional connectivity between SN and DMN compared to controls, replicating previous findings. We did not observe significant group differences of functional connectivity within the DMN, SN, or FPN. The strongest finding consisted of altered connectivity between DMN and SN to the visual network. OCD patients showed reduced functional connectivity between the left lateral parietal seed (LPl) and the inferior lateral occipital pole left (iLOCl) compared to controls. Furthermore, the LPl was found to be hyperconnected with the right superior lateral occipital cortex (sLOCr) and the right precuneus. This finding was positively correlated to OCD symptom severity, especially compulsions. Conclusions: Our findings replicated partly the meta-analysis findings, specifically reduced connectivity between SN and DMN. Using seeds based on the meta-analysis, we identified aberrations between the SN and, in particular, the DMN to the visual network. This raises the question about the visual system's involvement in OCD symptoms and the abnormal connectivity of a unimodal region to the multimodal DMN. [ABSTRACT FROM AUTHOR]

The normal variability in breath size and frequency results in breath-to-breath variability of end-tidal PCO 2 (P ET CO 2 ), the measured variable, and arterial partial pressure of carbon dioxide (PaCO 2 ), the independent variable affecting cerebral blood flow (CBF). This study examines the effect of variability in PaCO 2 on the pattern of resting-state functional MRI (rs-fMRI) connectivity. A region of interest (ROI)-to-ROI and Seed-to-Voxel first-level bivariate correlation, hemodynamic response function (hrf)-weighted analysis for measuring rs-fMRI connectivity was performed during two resting-state conditions: (a) normal breathing associated with breath-to-breath variation in PaCO 2 (poikilocapnia), and (b) normal breathing with breath-to-breath variability of P ET CO 2 dampened using sequential rebreathing (isocapnia). End-tidal PCO 2 (P ET CO 2 ) was used as a measurable surrogate for fluctuations of PaCO 2 . During poikilocapnia, enhanced functional connections were found between the cerebellum and inferior frontal and supramarginal gyrus (SG), visual cortex and occipital fusiform gyrus; and between the primary visual network (PVN) and the hippocampal formation. During isocapnia, these associations were not seen, rather enhanced functional connections were identified in the corticostriatal pathway between the putamen and intracalacarine cortex, supracalcarine cortex (SCC), and precuneus cortex. We conclude that vascular responses to variations in P ET CO 2 , account for at least some of the observed resting state synchronization of blood oxygenation level-dependent (BOLD) signals., Competing Interests: JF and DM are among the developers of the RespirAct™ for MRI studies at the University Health Network, part of the University of Toronto. Thornhill Research Inc. (TRI) is a for-profit biomedical manufacturing company that was spun off from UHN. It assembles the RespirAct™, on a non-profit basis to enable MRI research at UHN and around the world. JF receives income for work done for TRI and DM holds a minor equity position in TRI. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 McKetton, Sam, Poublanc, Crawley, Sobczyk, Venkatraghavan, Duffin, Fisher and Mikulis.)