scholarly journals Metabolic and functional connectivity provide unique and complementary insights into cognition-connectome relationships

2021 ◽  
Author(s):  
Katharina Voigt ◽  
Emma Liang ◽  
Bratislav Misic ◽  
Phillip Ward ◽  
Gary Egan ◽  
...  
Keyword(s):  
Executive Functioning ◽  
Cognitive Neuroscience ◽  
Cerebral Oxygenation ◽  
Multimodality Imaging ◽  
Brain Connectivity ◽  
Neural Mechanisms ◽  
Human Cognition ◽  
Positron Emission ◽  
Neuroscience Research ◽  
Metabolic Connectivity

A major challenge in current cognitive neuroscience is how functional brain connectivity gives rise to human cognition. Functional magnetic resonance imaging (fMRI) describes brain connectivity based on cerebral oxygenation dynamics (hemodynamic connectivity), whereas [18 F]-fluorodeoxyglucose functional positron emission tomography (FDG-fPET) describes brain connectivity based on cerebral glucose uptake (metabolic connectivity), each providing a unique characterisation of the human brain. How these two modalities differ in their contribution to cognition and behaviour is unclear. We used simultaneous resting-state FDG-fPET/fMRI to investigate how hemodynamic connectivity and metabolic connectivity relate to cognitive function by applying partial least squares analyses. Results revealed that while for both modalities the frontoparietal anatomical subdivisions related the strongest to cognition, using hemodynamic measures this network expressed executive functioning, episodic memory, and depression, while for metabolic measures this network exclusively expressed executive functioning. These findings demonstrate the unique advantages that simultaneous FDG-PET/fMRI has to provide a comprehensive understanding of the neural mechanisms that underpin cognition and highlights the importance of multimodality imaging in cognitive neuroscience research.

scholarly journals Metabolic and haemodynamic resting-state connectivity of the human brain: a high-temporal resolution simultaneous BOLD-fMRI and FDG-fPET multimodality study

2020 ◽  
Author(s):  
Sharna D Jamadar ◽  
Phillip GD Ward ◽  
Emma Xingwen Liang ◽  
Edwina R Orchard ◽  
Zhaolin Chen ◽  
...  
Keyword(s):  
Human Brain ◽  
Temporal Resolution ◽  
Fdg Pet ◽  
Neurological Diseases ◽  
Brain Connectivity ◽  
Constant Infusion ◽  
High Temporal Resolution ◽  
Positron Emission ◽  
Metabolic Connectivity ◽  
The Brain

AbstractSimultaneous FDG-PET/fMRI ([18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging) provides the capacity to image two sources of energetic dynamics in the brain – glucose metabolism and haemodynamic response. Functional fMRI connectivity has been enormously useful for characterising interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease; but static FDG-PET cannot be used to estimate subjectlevel measures of connectivity, only across-subject covariance. Here, we applied high-temporal resolution constant infusion fPET to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterised by fronto-parietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with static FDG-PET metabolic covariance, indicating that metabolic brain connectivity is a non-ergodic process whereby individual brain connectivity cannot be inferred from group level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain, and open up the opportunity for novel fundamental studies of human brain connectivity as well as multi-modality biomarkers of neurological diseases.

scholarly journals Hierarchical Multivariate Covariance Analysis of Metabolic Connectivity

2014 ◽  
Vol 34 (12) ◽  
pp. 1936-1943 ◽  
Author(s):  
Felix Carbonell ◽  
Arnaud Charil ◽  
Alex P Zijdenbos ◽  
Alan C Evans ◽  
Barry J Bedell ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Correlation Coefficients ◽  
Brain Network ◽  
Angular Gyrus ◽  
Connectivity Analysis ◽  
Novel Approach ◽  
Positron Emission ◽  
Metabolic Connectivity ◽  
Magnetic Resonance Imaging Mri ◽  
The Individual

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Cognitive Neuroscience of Causal Reasoning

2017 ◽  
Author(s):  
Joachim T. Operskalski ◽  
Aron K. Barbey
Keyword(s):  
Cognitive Neuroscience ◽  
Causal Reasoning ◽  
Computational Models ◽  
Functional Neuroimaging ◽  
Brain Regions ◽  
Human Cognition ◽  
Composition Theory ◽  
Neuroscience Research ◽  
Experimental Findings ◽  
Shed Light

The era of functional neuroimaging promised to shed light on dark corners of the brain’s inner workings, breathing new life into subfields of psychology beset by controversy. Although revelations from neuroscience provide the foundation for current views on many aspects of human cognition, there continue to be areas of study in which a mismatch between the questions asked by psychologists and neuroscientists renders the implications of neuroscience research unclear. Causal reasoning is one such topic, for which decades of cognitive neuroscience findings have revealed a heterogeneity of participating brain regions and networks across different experimental paradigms. This chapter discusses (i) three cognitive and computational models of causal reasoning (mental models, causal models, and force composition theory), (ii) experimental findings on causal judgment and reasoning using cognitive neuroscience methods, and (iii) the need for a multidisciplinary approach to understanding the nature and mechanisms of causal reasoning.

Chills, Bets, and Dopamine

2021 ◽  
pp. 155-160
Author(s):  
Laura Ferreri ◽  
Jordi Riba ◽  
Robert Zatorre ◽  
Antoni Rodriguez-Fornells
Keyword(s):  
Positron Emission Tomography ◽  
Neural Mechanisms ◽  
Emission Tomography ◽  
Human Cognition ◽  
Attention And Memory ◽  
Pharmacological Interventions ◽  
Mesolimbic System ◽  
The Past ◽  
Positron Emission ◽  
The Brain

During the past decade, research in cognitive neuroscience has tried to understand how the organized acoustic information we call music is decoded in the brain as pleasant and rewarding stimulus. In this chapter, the authors retrace part of this intriguing journey: from the first positron emission tomography study revealing the association between the mesolimbic system and musical pleasure to the recent pharmacological interventions showing that dopamine causally mediates the subjectively rewarding experience elicited by music. The dopamine-dependent hedonic and motivational responses to music may depend on the modulations of several neural mechanisms related not only to emotion, but also to attention and memory. Musical reward arises therefore as a complex set of processes which constitute a special access key to the study of human cognition.

Metabolic and Hemodynamic Resting-State Connectivity of the Human Brain: A High-Temporal Resolution Simultaneous BOLD-fMRI and FDG-fPET Multimodality Study

2021 ◽  
Author(s):  
Sharna D Jamadar ◽  
Phillip G D Ward ◽  
Emma X Liang ◽  
Edwina R Orchard ◽  
Zhaolin Chen ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Human Brain ◽  
Temporal Resolution ◽  
Fdg Pet ◽  
Brain Connectivity ◽  
Emission Tomography ◽  
High Temporal Resolution ◽  
Positron Emission ◽  
Metabolic Connectivity ◽  
The Brain

Abstract Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the capacity to image 2 sources of energetic dynamics in the brain—glucose metabolism and the hemodynamic response. fMRI connectivity has been enormously useful for characterizing interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease, but FDG-sPET cannot be used to estimate subject-level measures of “connectivity,” only across-subject “covariance.” Here, we applied high-temporal resolution constant infusion functional positron emission tomography (fPET) to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterized by frontoparietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with FDG-sPET metabolic covariance, indicating that metabolic brain connectivity is a nonergodic process whereby individual brain connectivity cannot be inferred from group-level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain and open up the opportunity for novel fundamental studies of human brain connectivity as well as multimodality biomarkers of neurological diseases.

scholarly journals Disrupted metabolic connectivity in dopaminergic and cholinergic networks at different stages of dementia from 18F-FDG PET brain persistent homology network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tun-Wei Hsu ◽  
Jong-Ling Fuh ◽  
Da-Wei Wang ◽  
Li-Fen Chen ◽  
Chia-Jung Chang ◽  
...  
Keyword(s):  
Algebraic Topology ◽  
Fdg Pet ◽  
Persistent Homology ◽  
Network Connectivity ◽  
Brain Regions ◽  
Imaging Data ◽  
Cholinergic Pathways ◽  
Positron Emission ◽  
Metabolic Connectivity ◽  
Neurochemical Changes

AbstractDementia is related to the cellular accumulation of β-amyloid plaques, tau aggregates, or α-synuclein aggregates, or to neurotransmitter deficiencies in the dopaminergic and cholinergic pathways. Cellular and neurochemical changes are both involved in dementia pathology. However, the role of dopaminergic and cholinergic networks in metabolic connectivity at different stages of dementia remains unclear. The altered network organisation of the human brain characteristic of many neuropsychiatric and neurodegenerative disorders can be detected using persistent homology network (PHN) analysis and algebraic topology. We used 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) imaging data to construct dopaminergic and cholinergic metabolism networks, and used PHN analysis to track the evolution of these networks in patients with different stages of dementia. The sums of the network distances revealed significant differences between the network connectivity evident in the Alzheimer’s disease and mild cognitive impairment cohorts. A larger distance between brain regions can indicate poorer efficiency in the integration of information. PHN analysis revealed the structural properties of and changes in the dopaminergic and cholinergic metabolism networks in patients with different stages of dementia at a range of thresholds. This method was thus able to identify dysregulation of dopaminergic and cholinergic networks in the pathology of dementia.

scholarly journals Multimodality imaging review of focal renal lesions

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Jonathan Lyske ◽  
Rishi Philip Mathew ◽  
Christopher Hutchinson ◽  
Vimal Patel ◽  
Gavin Low
Keyword(s):  
Malignant Tumors ◽  
Multimodality Imaging ◽  
Lymphoproliferative Disease ◽  
Benign Tumors ◽  
Main Body ◽  
Imaging Features ◽  
Focal Lesions ◽  
Renal Lesions ◽  
Positron Emission ◽  
Neoplastic Lesions

Abstract Background Focal lesions of the kidney comprise a spectrum of entities that can be broadly classified as malignant tumors, benign tumors, and non-neoplastic lesions. Malignant tumors include renal cell carcinoma subtypes, urothelial carcinoma, lymphoma, post-transplant lymphoproliferative disease, metastases to the kidney, and rare malignant lesions. Benign tumors include angiomyolipoma (fat-rich and fat-poor) and oncocytoma. Non-neoplastic lesions include infective, inflammatory, and vascular entities. Anatomical variants can also mimic focal masses. Main body of the abstract A range of imaging modalities are available to facilitate characterization; ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), magnetic resonance (MR) imaging, and positron emission tomography (PET), each with their own strengths and limitations. Renal lesions are being detected with increasing frequency due to escalating imaging volumes. Accurate diagnosis is central to guiding clinical management and determining prognosis. Certain lesions require intervention, whereas others may be managed conservatively or deemed clinically insignificant. Challenging cases often benefit from a multimodality imaging approach combining the morphology, enhancement and metabolic features. Short conclusion Knowledge of the relevant clinical details and key imaging features is crucial for accurate characterization and differentiation of renal lesions.

The Default Network Distinguishes Construals of Proximal versus Distal Events

2011 ◽  
Vol 23 (10) ◽  
pp. 2945-2955 ◽  
Author(s):  
Diana I. Tamir ◽  
Jason P. Mitchell
Keyword(s):  
Cognitive Neuroscience ◽  
Psychological Distance ◽  
Individual Variability ◽  
Retrosplenial Cortex ◽  
Default Network ◽  
Implicit Measure ◽  
Four Dimensions ◽  
Neuroscience Research ◽  
Cognitive Theories ◽  
Different Dimensions

Humans enjoy a singular capacity to imagine events that differ from the “here-and-now.” Recent cognitive neuroscience research has linked such simulation processes to the brain's “default network.” However, extant cognitive theories suggest that perceivers reliably simulate only relatively proximal experiences—those that seem nearby, soon, likely to happen, or relevant to a close other. Here, we test these claims by examining spontaneous engagement of the default network while perceivers consider experiencing events from proximal and distal perspectives. Across manipulations of perspective in four dimensions, two regions of the default network—medial prefrontal cortex and retrosplenial cortex—were more active for proximal than distal events, supporting cognitive accounts that perceivers only richly simulate experiences that seem immediate and that perceivers represent different dimensions of distance similarly. Moreover, stable individual differences in default activity when thinking about distal events correlated with individual variability in an implicit measure of psychological distance, suggesting that perceivers naturally vary in their tendency to simulate far-off or unlikely experiences.

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