How functional connectivity influences behaviour: a study from the Welsh Advanced Neuroimaging Database Functional connectivity, which impacts all brain functions including cognition, can be assessed using resting-state functional magnetic resonance imaging (rsfMRI). This non-invasive technique provides high spatial resolution for evaluating brain connectivity. Loss of functional connectivity often occurs in neurological diseases and can precede measurable brain atrophy. We present preliminary results from the Welsh Advanced Neuroimaging Database (WAND), which aims to generate a comprehensive description of brain coupling across multiple domains. WAND includes data on macro- and micro-structural, functional, metabolic, chemical, and behavioural measures from a large population of healthy participants aged 18-65 years. In this study, we analyze rsfMRI data from a subset of 103 participants in the WAND study. Eyes-open rsfMRI data were acquired on a Siemen’s 3T Prisma scanner, with repetition time=2000ms, echo time=30ms and multiband factor=4. Physiological data such as heart rate and respiration were monitored during the scan. Data processing and analysis were performed using SPM, the PhysIO package, fMRIprep and FSL. Motion and physiological noise parameters were estimated for each participant. Noise regressors were used to remove physiological noise from the data following preprocessing with fMRIprep. Group ICA was used to reconstruct the main resting-state networks, and subject-specific network maps were obtained using dual regression. The relationship between the resting-state networks and behavioural data will be assessed using FSL’s randomise. Although the analysis is still ongoing, we have successfully identified physiological noise regressors for all participants. We anticipate finding significant associations between functional connectivity and age, as well as with behavioural test results.

How functional connectivity influences behaviour: a study from the Welsh Advanced Neuroimaging Database / Singh, Taljinder; Stylianopoulou, Elena; Mcnabb, Carolyn; Canese, Rossella; Cercignani, Mara. - (2023). (Intervento presentato al convegno 50th National Congress on Magnetic Resonance GIDRM 2023 tenutosi a Rome).

How functional connectivity influences behaviour: a study from the Welsh Advanced Neuroimaging Database

Taljinder Singh;
2023

Abstract

How functional connectivity influences behaviour: a study from the Welsh Advanced Neuroimaging Database Functional connectivity, which impacts all brain functions including cognition, can be assessed using resting-state functional magnetic resonance imaging (rsfMRI). This non-invasive technique provides high spatial resolution for evaluating brain connectivity. Loss of functional connectivity often occurs in neurological diseases and can precede measurable brain atrophy. We present preliminary results from the Welsh Advanced Neuroimaging Database (WAND), which aims to generate a comprehensive description of brain coupling across multiple domains. WAND includes data on macro- and micro-structural, functional, metabolic, chemical, and behavioural measures from a large population of healthy participants aged 18-65 years. In this study, we analyze rsfMRI data from a subset of 103 participants in the WAND study. Eyes-open rsfMRI data were acquired on a Siemen’s 3T Prisma scanner, with repetition time=2000ms, echo time=30ms and multiband factor=4. Physiological data such as heart rate and respiration were monitored during the scan. Data processing and analysis were performed using SPM, the PhysIO package, fMRIprep and FSL. Motion and physiological noise parameters were estimated for each participant. Noise regressors were used to remove physiological noise from the data following preprocessing with fMRIprep. Group ICA was used to reconstruct the main resting-state networks, and subject-specific network maps were obtained using dual regression. The relationship between the resting-state networks and behavioural data will be assessed using FSL’s randomise. Although the analysis is still ongoing, we have successfully identified physiological noise regressors for all participants. We anticipate finding significant associations between functional connectivity and age, as well as with behavioural test results.
2023
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1699828
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