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Arterial spin labeling (ASL) is a non-invasive MRI technique, allowing quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. Therefore, there is a strong need for standardization of ASL data storage, including acquisition metadata. Recently ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. The structure of the ASL data, focusing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information, are discussed. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. It is anticipated that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Arterial spin labeling (ASL) is a non-invasive MRI technique, allowing quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. Therefore, there is a strong need for standardization of ASL data storage, including acquisition metadata. Recently ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. The structure of the ASL data, focusing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information, are discussed. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. It is anticipated that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Arterial spin labeling (ASL) is a non-invasive MRI technique, allowing quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. Therefore, there is a strong need for standardization of ASL data storage, including acquisition metadata. Recently ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. The structure of the ASL data, focusing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information, are discussed. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. It is anticipated that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Arterial spin labeling (ASL) is a non-invasive MRI technique, allowing quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. Therefore, there is a strong need for standardization of ASL data storage, including acquisition metadata. Recently ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. The structure of the ASL data, focusing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information, are discussed. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. It is anticipated that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

Effects of physiological and/or psychological inter-individual differences on the resting brain state have not been fully established. The present study investigated the effects of individual differences in basal autonomic tone and positive and negative personality dimensions on resting brain activity. Whole-brain resting cerebral perfusion images were acquired from 32 healthy subjects (16 males) using arterial spin labeling perfusion MRI. Neuroticism and extraversion were assessed with the Eysenck Personality Questionnaire-Revised. Resting autonomic activity was assessed using a validated measure of baseline cardiac vagal tone (CVT) in each individual. Potential associations between the perfusion data and individual CVT (27 subjects) and personality score (28 subjects) were tested at the level of voxel clusters by fitting a multiple regression model at each intracerebral voxel. Greater baseline perfusion in the dorsal anterior cingulate cortex (ACC) and cerebellum was associated with lower CVT. At a corrected significance threshold of p<0.01, strong positive correlations were observed between extraversion and resting brain perfusion in the right caudate, brain stem, and cingulate gyrus. Significant negative correlations between neuroticism and regional cerebral perfusion were identified in the left amygdala, bilateral insula, ACC, and orbitofrontal cortex. These results suggest that individual autonomic tone and psychological variability influence resting brain activity in brain regions, previously shown to be associated with autonomic arousal (dorsal ACC) and personality traits (amygdala, caudate, etc.) during active task processing. The resting brain state may therefore need to be taken into account when interpreting the neurobiology of individual differences in structural and functional brain activity.

While several studies have investigated interactions between the electroencephalography (EEG) and functional magnetic resonance imaging BOLD signal fluctuations, less is known about the associations between EEG oscillations and baseline brain haemodynamics, and few studies have examined the link between EEG power outside the alpha band and baseline perfusion. Here we compare whole-brain arterial spin labelling perfusion MRI and EEG in a group of healthy adults (n=16, ten females, median age: 27years, range 21-48) during an eyes closed rest condition. Correlations emerged between perfusion and global average EEG power in low (delta: 2-4Hz and theta: 4-7Hz), middle (alpha: 8-13Hz), and high (beta: 13-30Hz and gamma: 30-45Hz) frequency bands in both cortical and sub-cortical regions. The correlations were predominately positive in middle and high-frequency bands, and negative in delta. In addition, central alpha frequency positively correlated with perfusion in a network of brain regions associated with the modulation of attention and preparedness for external input, and central theta frequency correlated negatively with a widespread network of cortical regions. These results indicate that the coupling between average EEG power/frequency and local cerebral blood flow varies in a frequency specific manner. Our results are consistent with longstanding concepts that decreasing EEG frequencies which in general map onto decreasing levels of activation

Effects of physiological and/or psychological inter-individual differences on the resting brain state have not been fully established. The present study investigated the effects of individual differences in basal autonomic tone and positive and negative personality dimensions on resting brain activity. Whole-brain resting cerebral perfusion images were acquired from 32 healthy subjects (16 males) using arterial spin labeling perfusion MRI. Neuroticism and extraversion were assessed with the Eysenck Personality Questionnaire-Revised. Resting autonomic activity was assessed using a validated measure of baseline cardiac vagal tone (CVT) in each individual. Potential associations between the perfusion data and individual CVT (27 subjects) and personality score (28 subjects) were tested at the level of voxel clusters by fitting a multiple regression model at each intracerebral voxel. Greater baseline perfusion in the dorsal anterior cingulate cortex (ACC) and cerebellum was associated with lower CVT. At a corrected significance threshold of p < 0.01, strong positive correlations were observed between extraversion and resting brain perfusion in the right caudate, brain stem, and cingulate gyrus. Significant negative correlations between neuroticism and regional cerebral perfusion were identified in the left amygdala, bilateral insula, ACC, and orbitofrontal cortex. These results suggest that individual autonomic tone and psychological variability influence resting brain activity in brain regions, previously shown to be associated with autonomic arousal (dorsal ACC) and personality traits (amygdala, caudate, etc.) during active task processing. The resting brain state may therefore need to be taken into account when interpreting the neurobiology of individual differences in structural and functional brain activity.

There is a need for objective imaging markers of Parkinson's disease status and progression. Positron emission tomography and single photon emission computed tomography studies have suggested patterns of abnormal cerebral perfusion in Parkinson's disease as potential functional biomarkers. This study aimed to identify an arterial spin labelling magnetic resonance-derived perfusion network as an accessible, non-invasive alternative. We used pseudo-continuous arterial spin labelling to measure cerebral grey matter perfusion in 61 subjects with Parkinson's disease with a range of motor and cognitive impairment, including patients with dementia and 29 age- and sex-matched controls. Principal component analysis was used to derive a Parkinson's disease-related perfusion network via logistic regression. Region of interest analysis of absolute perfusion values revealed that the Parkinson's disease pattern was characterized by decreased perfusion in posterior parieto-occipital cortex, precuneus and cuneus, and middle frontal gyri compared with healthy controls. Perfusion was preserved in globus pallidus, putamen, anterior cingulate and post- and pre-central gyri. Both motor and cognitive statuses were significant factors related to network score. A network approach, supported by arterial spin labelling-derived absolute perfusion values may provide a readily accessible neuroimaging method to characterize and track progression of both motor and cognitive status in Parkinson's disease

Effects of physiological and/or psychological inter-individual differences on the resting brain state have not been fully established. The present study investigated the effects of individual differences in basal autonomic tone and positive and negative personality dimensions on resting brain activity. Whole-brain resting cerebral perfusion images were acquired from 32 healthy subjects (16 males) using arterial spin labeling perfusion MRI. Neuroticism and extraversion were assessed with the Eysenck Personality Questionnaire-Revised. Resting autonomic activity was assessed using a validated measure of baseline cardiac vagal tone (CVT) in each individual. Potential associations between the perfusion data and individual CVT (27 subjects) and personality score (28 subjects) were tested at the level of voxel clusters by fitting a multiple regression model at each intracerebral voxel. Greater baseline perfusion in the dorsal anterior cingulate cortex (ACC) and cerebellum was associated with lower CVT. At a corrected significance threshold of p<0.01, strong positive correlations were observed between extraversion and resting brain perfusion in the right caudate, brain stem, and cingulate gyrus. Significant negative correlations between neuroticism and regional cerebral perfusion were identified in the left amygdala, bilateral insula, ACC, and orbitofrontal cortex. These results suggest that individual autonomic tone and psychological variability influence resting brain activity in brain regions, previously shown to be associated with autonomic arousal (dorsal ACC) and personality traits (amygdala, caudate, etc.) during active task processing. The resting brain state may therefore need to be taken into account when interpreting the neurobiology of individual differences in structural and functional brain activity.

While several studies have investigated interactions between the electroencephalography (EEG) and functional magnetic resonance imaging BOLD signal fluctuations, less is known about the associations between EEG oscillations and baseline brain haemodynamics, and few studies have examined the link between EEG power outside the alpha band and baseline perfusion. Here we compare whole-brain arterial spin labelling perfusion MRI and EEG in a group of healthy adults (n=16, ten females, median age: 27years, range 21-48) during an eyes closed rest condition. Correlations emerged between perfusion and global average EEG power in low (delta: 2-4Hz and theta: 4-7Hz), middle (alpha: 8-13Hz), and high (beta: 13-30Hz and gamma: 30-45Hz) frequency bands in both cortical and sub-cortical regions. The correlations were predominately positive in middle and high-frequency bands, and negative in delta. In addition, central alpha frequency positively correlated with perfusion in a network of brain regions associated with the modulation of attention and preparedness for external input, and central theta frequency correlated negatively with a widespread network of cortical regions. These results indicate that the coupling between average EEG power/frequency and local cerebral blood flow varies in a frequency specific manner. Our results are consistent with longstanding concepts that decreasing EEG frequencies which in general map onto decreasing levels of activation