scholarly journals Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy ageing subjects

2021 ◽  
Author(s):  
Xulin Liu ◽  
Lorraine K Tyler ◽  
James B Rowe ◽  
Kamen A Tsvetanov ◽  
Keyword(s):  
Fluid Intelligence ◽  
Functional Organization ◽  
Imaging Modality ◽  
Healthy Ageing ◽  
Multimodal Fusion ◽  
Network Activity ◽  
Functional Network ◽  
Brain Morphology ◽  
Multimodal Approach ◽  
Frontoparietal Network

Cognitive ageing is a complex process which requires multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization and vascular dynamics. However, most neuroimaging studies of ageing have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and the interpretation of neural correlates of cognitive decline in ageing. Here, we used linked independent component analysis as a data-driven multimodal approach to jointly analyze magnetic resonance imaging of grey matter density, cerebrovascular, and functional network topographies. Neuroimaging and behavioural data (n = 215) from the Cambridge Centre for Ageing and Neuroscience study were used, containing healthy subjects aged 18 to 88. In the output components, fusion was found between structural and cerebrovascular topographies in multiple components with cognitive-relevance across the lifespan. A component reflecting global atrophy with regional cerebrovascular changes and a component reflecting right frontoparietal network activity were correlated with fluid intelligence over and above age and gender. No meaningful fusion between functional network topography and structural or cerebrovascular signals was observed. We propose that integrating multiple neuroimaging modalities allows to better characterize brain pattern variability and to differentiate brain changes in healthy ageing.

scholarly journals Parallel Group ICA + ICA: Joint Estimation of Linked Functional Network Variability and Structural Covariation with Application to Schizophrenia

2019 ◽  
Author(s):  
Shile Qi ◽  
Jing Sui ◽  
Jiayu Chen ◽  
Jingyu Liu ◽  
Rongtao Jiang ◽  
...  
Keyword(s):  
Imaging Modality ◽  
Real Data ◽  
Structural Mri ◽  
Joint Estimation ◽  
Multimodal Fusion ◽  
Functional Network ◽  
Cognitive Domain ◽  
Imaging Biomarkers ◽  
Parallel Group ◽  
Group Ica

ABSTRACTThere is growing evidence that rather than using a single brain imaging modality to study its association with physiological or symptomatic features, the field is paying more attention to fusion of multimodal information. However, most current multimodal fusion approaches that incorporate functional magnetic resonance imaging (fMRI) are restricted to second-level 3D features, rather than the original 4D fMRI data. This trade-off is that the valuable temporal information is not utilized during the fusion step. Here we are motivated to propose a novel approach called “parallel group ICA+ICA” that incorporates temporal fMRI information from GICA into a parallel ICA framework, aiming to enable direct fusion of first-level fMRI features with other modalities (e.g.structural MRI), which thus can detect linked functional network variability and structural covariations. Simulation results show that the proposed method yields accurate inter-modality linkage detection regardless of whether it is strong or weak. When applied to real data, we identified one pair of significantly associated fMRI-sMRI components that show group difference between schizophrenia and controls in both modalities. Finally, multiple cognitive domain scores can be predicted by the features identified in the linked component pair by our proposed method. We also show these multimodal brain features can predict multiple cognitive scores in an independent cohort. Overall, results demonstrate the ability of parallel GICA+ICA to estimate joint information from 4D and 3D data without discarding much of the available information up front, and the potential for using this approach to identify imaging biomarkers to study brain disorders.

scholarly journals Tool Selectivity in Left Occipitotemporal Cortex Develops without Vision

2013 ◽  
Vol 25 (8) ◽  
pp. 1225-1234 ◽  
Author(s):  
Marius V. Peelen ◽  
Stefania Bracci ◽  
Xueming Lu ◽  
Chenxi He ◽  
Alfonso Caramazza ◽  
...  
Keyword(s):  
Functional Organization ◽  
Auditory Task ◽  
Anatomical Location ◽  
Resting State Functional Connectivity ◽  
Frontoparietal Network ◽  
Congenitally Blind ◽  
Occipitotemporal Cortex ◽  
Auditory Tasks ◽  
Tool Motion ◽  
Selective Activity

Previous studies have provided evidence for a tool-selective region in left lateral occipitotemporal cortex (LOTC). This region responds selectively to pictures of tools and to characteristic visual tool motion. The present human fMRI study tested whether visual experience is required for the development of tool-selective responses in left LOTC. Words referring to tools, animals, and nonmanipulable objects were presented auditorily to 14 congenitally blind and 16 sighted participants. Sighted participants additionally viewed pictures of these objects. In whole-brain group analyses, sighted participants showed tool-selective activity in left LOTC in both visual and auditory tasks. Importantly, virtually identical tool-selective LOTC activity was found in the congenitally blind group performing the auditory task. Furthermore, both groups showed equally strong tool-selective activity for auditory stimuli in a tool-selective LOTC region defined by the picture-viewing task in the sighted group. Detailed analyses in individual participants showed significant tool-selective LOTC activity in 13 of 14 blind participants and 14 of 16 sighted participants. The strength and anatomical location of this activity were indistinguishable across groups. Finally, both blind and sighted groups showed significant resting state functional connectivity between left LOTC and a bilateral frontoparietal network. Together, these results indicate that tool-selective activity in left LOTC develops without ever having seen a tool or its motion. This finding puts constraints on the possible role that this region could have in tool processing and, more generally, provides new insights into the principles shaping the functional organization of OTC.

scholarly journals Severe Sexual Abuse Reduces Frontoparietal Network Activity during Model-Based Reinforcement Learning Updates

2019 ◽  
Author(s):  
Allison Letkiewicz ◽  
Amy L. Cochran ◽  
Josh M. Cisler
Keyword(s):  
Sexual Abuse ◽  
Reinforcement Learning ◽  
Learning Styles ◽  
Computational Models ◽  
Learning Strategy ◽  
Network Activity ◽  
Model Based ◽  
Model Free ◽  
Frontoparietal Network ◽  
Assaultive Trauma

Trauma and trauma-related disorders are characterized by altered learning styles. Two learning processes that have been delineated using computational modeling are model-free and model-based reinforcement learning (RL), characterized by trial and error and goal-driven, rule-based learning, respectively. Prior research suggests that model-free RL is disrupted among individuals with a history of assaultive trauma and may contribute to altered fear responding. Currently, it is unclear whether model-based RL, which involves building abstract and nuanced representations of stimulus-outcome relationships to prospectively predict action-related outcomes, is also impaired among individuals who have experienced trauma. The present study sought to test the hypothesis of impaired model-based RL among adolescent females exposed to assaultive trauma. Participants (n=60) completed a three-arm bandit RL task during fMRI acquisition. Two computational models compared the degree to which each participant’s task behavior fit the use of a model-free versus model-based RL strategy. Overall, a greater portion of participants’ behavior was better captured by the model-based than model-free RL model. Although assaultive trauma did not predict learning strategy use, greater sexual abuse severity predicted less use of model-based compared to model-free RL. Additionally, severe sexual abuse predicted less left frontoparietal network encoding of model-based RL updates, which was not accounted for by PTSD. Given the significant impact that sexual trauma has on mental health and other aspects of functioning, it is plausible that altered model-based RL is an important route through which clinical impairment emerges.

scholarly journals Functional network activity during errorless and trial‐and‐error color‐name association learning

2020 ◽  
Vol 10 (8) ◽  
Author(s):  
Madoka Yamashita ◽  
Tetsuya Shimokawa ◽  
Ferdinand Peper ◽  
Rumi Tanemura
Keyword(s):  
Network Activity ◽  
Functional Network ◽  
Trial And Error ◽  
Association Learning ◽  
Color Name

scholarly journals A Systematic Review of Behavioral, Physiological, and Neurobiological Cognitive Regulation Alterations in Obsessive-Compulsive Disorder

2020 ◽  
Vol 10 (11) ◽  
pp. 797
Author(s):  
Sónia Ferreira ◽  
José Miguel Pêgo ◽  
Pedro Morgado
Keyword(s):  
Systematic Review ◽  
Obsessive Compulsive Disorder ◽  
Brain Activity ◽  
Intrusive Thoughts ◽  
Network Activity ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Cognitive Regulation ◽  
Frontoparietal Network ◽  
Pubmed Database

Obsessive-compulsive disorder (OCD) is characterized by cognitive regulation deficits. However, the current literature has focused on executive functioning and emotional response impairments in this disorder. Herein, we conducted a systematic review of studies assessing the behavioral, physiological, and neurobiological alterations in cognitive regulation in obsessive-compulsive patients using the PubMed database. Most of the studies included explored behavioral (distress, arousal, and frequency of intrusive thoughts) and neurobiological measures (brain activity and functional connectivity) using affective cognitive regulation paradigms. Our results pointed to the advantageous use of reappraisal and acceptance strategies in contrast to suppression to reduce distress and frequency of intrusive thoughts. Moreover, we observed alterations in frontoparietal network activity during cognitive regulation. Our conclusions are limited by the inclusion of underpowered studies with treated patients. Nonetheless, our findings support the OCD impairments in cognitive regulation of emotion and might help to improve current guidelines for cognitive therapy.

Left frontoparietal network activity is modulated by drug stimuli in cocaine addiction

2017 ◽  
Vol 12 (5) ◽  
pp. 1259-1270 ◽  
Author(s):  
Víctor Costumero ◽  
Patricia Rosell-Negre ◽  
Juan Carlos Bustamante ◽  
Paola Fuentes-Claramonte ◽  
Juan José Llopis ◽  
...  
Keyword(s):  
Cocaine Addiction ◽  
Network Activity ◽  
Frontoparietal Network

scholarly journals Novel Age-Dependent Cortico-Subcortical Morphologic Interactions Predict Fluid Intelligence: A Multi-Cohort Geometric Deep Learning Study

2021 ◽  
Author(s):  
Yunan Wu ◽  
Pierre Besson ◽  
Emanuel Azcona ◽  
Sarah Bandt ◽  
Todd Parrish ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Fluid Intelligence ◽  
State Of The Art ◽  
Brain Morphology ◽  
Subcortical Structures ◽  
Human Connectome Project ◽  
Strong Hypothesis ◽  
Age Dependent ◽  
Relationship Of ◽  
The Relationship

Abstract The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

scholarly journals Is baseline pupil size related to cognitive ability? Yes (under proper lighting conditions).

2020 ◽  
Author(s):  
Jason S. Tsukahara ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Ability ◽  
Pupil Size ◽  
Large Scale ◽  
Fluid Intelligence ◽  
Functional Organization ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Lighting Conditions

We found that individual differences in baseline pupil size correlated with fluid intelligence and working memory capacity. Larger pupil size was associated with higher cognitive ability. However, other researchers have not been able to replicate our 2016 finding – though they only measured working memory capacity and not fluid intelligence. In a reanalysis of Tsukahara et al. (2016) we show that reduced variability on baseline pupil size will result in a higher probability of obtaining smaller and non-significant correlations with working memory capacity. In two large-scale studies, we demonstrated that reduced variability in baseline pupil size values was due to the monitor being too bright. Additionally, fluid intelligence and working memory capacity did correlate with baseline pupil size except in the brightest lighting conditions. Overall, our findings demonstrated that the baseline pupil size – working memory capacity relationship was not as strong or robust as that with fluid intelligence. Our findings have strong methodological implications for researchers investigating individual differences in task-free or task-evoked pupil size. We conclude that fluid intelligence does correlate with baseline pupil size and that this is related to the functional organization of the resting-state brain through the locus coeruleus-norepinephrine system.

scholarly journals Cross-species Functional Alignment Reveals Evolutionary Hierarchy Within the Connectome

2019 ◽  
Author(s):  
Ting Xu ◽  
Karl-Heinz Nenning ◽  
Ernst Schwartz ◽  
Seok-Jun Hong ◽  
Joshua T. Vogelstein ◽  
...  
Keyword(s):  
Functional Organization ◽  
Geodesic Distance ◽  
Brain Morphology ◽  
Angular Gyrus ◽  
Default Network ◽  
Anatomical Landmarks ◽  
Functional Changes ◽  
Cortical Organization ◽  
Posterior Cingulate ◽  
Cognitive Hierarchy

AbstractEvolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we demonstrate a function-based method for cross-species cortical alignment that leverages recent advances in understanding cortical organization and that enables the quantification of homologous regions across species, even when their location is decoupled from anatomical landmarks. Critically, our method establishes that cross-species similarity in cortical organization decreases with geodesic distance from unimodal systems, and culminates in the most pronounced changes in posterior regions of the default network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default network, as the apex of a cognitive hierarchy, as is seen in humans, is a relatively recent evolutionary adaptation. They also highlight functional changes in regions such as the posterior cingulate cortex and angular gyrus as key influences on uniquely human features of cognition.

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