Biology subjects

Lythgoe, D. J.

Publications and source records attributed to Lythgoe, D. J..

13 recordsLinked to original sources

bioRxiv2025

Susceptibility-matched padding improves the quality of cervical and lumbar spinal fMRI

Spinal cord functional magnetic resonance imaging (fMRI) has advanced significantly in recent years, revealing insights into the function of somatosensory and motor systems. However, the complex environment of the spinal cord induces unique sources of noise, limiting the quality of spinal fMRI recordings. Various hardware and software solutions have been proposed to address these challenges. Among them, susceptibility-matched padding has gained popularity due its low cost, ease of use, and effectiveness in reducing static B0 field inhomogeneities, which are a major source of artefacts in spinal fMRI. Despite anecdotal evidence, the impact of susceptibility-matched padding on the quality of spinal cord fMRI has not been assessed systematically. We investigated the effects of non-protonated perfluorocarbon liquid-filled padding (SatPad) on B0 field homogeneity and functional echo-planar imaging (EPI) in cervical and lumbar spinal cord in 10 healthy volunteers. Participants underwent two resting-state fMRI scanning sessions, one per cord section. Within each session they were scanned with and without SatPad in a pseudo-randomised order. The use of SatPad increased B0 field homogeneity and improved functional image quality metrics, including temporal signal-to-noise ratio, timeseries coefficient of variation, DVARS, and ghosting artefacts. While both cervical and lumbar cord data benefited from the use of SatPad, greater effects were observed in the cervical cord. These findings provide a compelling basis for integrating susceptibility-matched padding into routine spinal fMRI protocols.

neuroscience↗

bioRxiv2025

Test-retest reliability of sensorimotor activity measured with spinal cord fMRI

Establishing the reliability of spinal cord functional magnetic resonance imaging (fMRI) is critical before employing it to assess experimental or clinical interventions. Previous studies have mapped human motor activity primarily to the ipsilateral ventral horn, aligning with myotomal and dermatomal projections. Despite these insights, the test-retest reliability of spinal fMRI remains under-investigated. Here we assessed spinal cord activation during a sensorimotor paradigm involving right-hand grasping and grip force estimation in 30 healthy volunteers. Participants completed two identical scanning visits, each time performing the same task twice, enabling the investigation of test-retest reliability both within a single experimental visit and between visits performed on different days. Aggregating all task runs, motor-evoked activation was observed in ipsilateral ventro-dorsal regions of spinal segmental levels C5-T1, as well as in medial regions of levels C2-C3. Despite highly reliable task performance (grip force) and fMRI signal quality (temporal signal-to-noise ratio), the reliability of motor activation was predominantly poor-to-fair both within and between visits, with notable variability in spatial distribution observed across task runs. Increasing the number of task runs per individual improved the robustness of group-level activation, as indexed by higher activated voxel count, larger cluster spatial extent, and attenuated t-statistic distribution. Although we demonstrated that motor-evoked activation corresponds to the known neuroanatomical organisation of motor circuits, its low test-retest reliability presents a challenge for wider applications of spinal fMRI. Understanding the drivers of low reliability in functional imaging is warranted, but we suggest that looking beyond measurement error is required, including careful consideration of inherent within-individual variability underpinned by neurophysiological and psychological factors.

neuroscience↗

bioRxiv2025

EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data

Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.0, and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared to other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.

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bioRxiv2024

Decoupling of GABA and Glutamine-Glutamate Dynamics and their role in tactile perception: An fMRS Study

Tactile processing is fundamental for our daily lives. In particular, adaptation, the mechanism by which neural (and behavioural) responses change due to repeated stimulation, is key in adjusting our responses to the environment and is often affected in neurodevelopmental conditions such as autism and ADHD. While GABA and glutamate--the main inhibitory and excitatory neurotransmitters-- are known to be fundamental for encoding sensory input, we know little regarding the dynamic responses of the GABA and glutamatergic systems during tactile processing. Here, we examine how GABA and glutamine+glutamate (Glx) in vivo dynamics change during repetitive tactile stimulation and how these changes relate to tactile perception in a healthy population, using functional magnetic resonance spectroscopy (fMRS). Our study showed that repetitive tactile stimulation induced a decoupling between GABA and Glx during the first stimulation blocks as suggested by a negative correlation between GABA and Glx, which changed from a positive correlation at baseline. Subsequently, a multivariate time series analysis showed a predictive temporal relationship between Glx and GABA, showing that changes in these metabolites are temporally linked with an estimated lag of 6 seconds informing on a complex metabolite response function. The absence of gross metabolite change suggests that Glx and GABA adjust in relation to each other in response to repeated tactile stimulation. Furthermore, individual differences in the changed GABA and Glx levels correlated with perceptual measures of touch. Together, our study highlights the complex relationship between GABA and glutamate in tactile processing and demonstrates that experience-dependence plasticity induces a decoupling between these key metabolites. Further study into their dynamic interplay may be key to understanding adaptation as meso-levels in the brain and how these mechanisms differ in neurodevelopmental and neurological conditions.

neuroscience↗

bioRxiv2024

Ultra-low-field brain MRI morphometry: test-retest reliability and correspondence to high-field MRI

Magnetic resonance imaging (MRI) enables non-invasive monitoring of healthy brain development and disease. Widely used higher field (>1.5 T) MRI systems are associated with high energy and infrastructure requirements, and high costs. Recent ultra-low-field (<0.1T) systems provide a more accessible and cost-effective alternative. However, it remains uncertain whether anatomical ultra-low-field neuroimaging can be used to reliably extract quantitative measures of brain morphometry, and to what extent such measures correspond to high-field MRI. Here we scanned 23 healthy adults aged 20-69 years on two identical 64 mT systems and a 3 T system, using T1w and T2w scans across a range of (64 mT) resolutions. We segmented brain images into 4 global tissue types and 98 local structures, and systematically evaluated between-scanner reliability of 64 mT morphometry and correspondence to 3 T measurements, using correlations of tissue volume and Dice spatial overlap of segmentations. We report high 64 mT reliability and correspondence to 3 T across 64 mT scan contrasts and resolutions, with highest performance shown by combining three T2w scans with low through-plane resolution into a single higher-resolution scan using multi-resolution registration. Larger structures show higher 64 mT reliability and correspondence to 3 T. Finally, we showcase the potential of ultra-low-field MRI for mapping neuroanatomical changes across the lifespan, and monitoring brain structures relevant to neurological disorders. Raw images are publicly available, enabling systematic validation of pre-processing and analysis approaches for ultra-low-field neuroimaging.

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bioRxiv2023

A novel implementation of spinal fMRI demonstrates segmental organisation of functionally connected networks in the cervical spinal cord: A test-retest reliability study

Resting fMRI studies have identified intrinsic spinal cord activity, which forms organised motor (ventral) and sensory (dorsal) resting-state networks. However, to facilitate the use of spinal fMRI in, for example, clinical studies, it is crucial to first assess the reliability of the method, particularly given the unique anatomical, physiological, and methodological challenges associated with acquiring the data. Here we demonstrate a novel implementation for acquiring BOLD-sensitive resting-state spinal fMRI, which was used to characterise functional connectivity relationships in the cervical cord and assess their test-retest reliability in 23 young healthy volunteers. Resting-state networks were estimated in two ways: (1) by extracting the mean timeseries from anatomically constrained seed masks and estimating voxelwise connectivity maps and (2) by calculating seed-to-seed correlations between extracted mean timeseries. Seed regions corresponded to the four grey matter horns (ventral/dorsal and left/right) of C5-C8 segmental levels. Test-retest reliability was assessed using the intraclass correlation coefficient (ICC) in the following ways: for each voxel in the cervical spine; each voxel within an activated cluster; the mean signal as a summary estimate within an activated cluster; and correlation strength in the seed-to-seed analysis. Spatial overlap of clusters derived from voxelwise analysis between sessions was examined using Dice coefficients. Following voxelwise analysis, we observed distinct unilateral dorsal and ventral organisation of cervical spinal resting-state networks that was largely confined in the rostro-caudal extent to each spinal segmental level, with more sparse connections observed between segments (Bonferroni corrected p < 0.003, threshold-free cluster enhancement with 5000 permutations). Additionally, strongest correlations were observed between within-segment ipsilateral dorso-ventral connections, followed by within-segment dorso-dorsal and ventro-ventral connections. Test-retest reliability of these networks was mixed. Reliability was poor when assessed on a voxelwise level, with more promising indications of reliability when examining the average signal within clusters. Reliability of correlation strength between seeds was highly variable, with highest reliability achieved in ipsilateral dorso-ventral and dorso-dorsal/ventro-ventral connectivity. However, the spatial overlap of networks between sessions was excellent. We demonstrate that while test-retest reliability of cervical spinal resting-state networks is mixed, their spatial extent is similar across sessions, suggesting that these networks are characterised by a consistent spatial representation over time.

neuroscience↗

bioRxiv2022

Variation in glutamate and GABA genes and their association with brain structure and chemistry in autism

The excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between glutamatergic and GABAergic neurotransmission contributes to autism symptomatology. Whether this is due to altered GABAergic or glutamatergic functioning, or both, remains largely unknown. We integrated genetic, brain structure and brain chemistry data to investigate the relationship between E/I genetic variation and expression, glutamate concentrations and cortical thickness (CT). Participants (60 autism and 104 neurotypical controls, aged 8-13 years) underwent magnetic resonance imaging and spectroscopy for glutamate quantification in the anterior cingulate cortex (ACC) and left dorsal striatum. Genetic involvement in these regional glutamate concentration levels was investigated using competitive gene-set association and polygenic scores (PGS). Further, glutamate as well as GABA gene-set expression profiles were investigated in relation to CT. Aggregated genetic variation in the glutamate gene-set was associated with ACC but not striatal glutamate concentrations. PGS analysis, however, showed a genome-wide PGS for autism to be predictive of striatal but not ACC glutamate levels. Expression profiles of GABAergic-but not glutamatergic genes were associated with differences in cortical thickness between groups. This study showed differential involvement of aggregated glutamatergic and GABAergic genetic variation in brain structure and chemistry in autism, which suggests regional variability in E/I imbalance.

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bioRxiv2021

Rapid processing and quantitative evaluation of multicontrast EPImix scans for adaptive multimodal imaging

Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1-weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1-FLAIR, T2, T2*, T2-FLAIR, DWI & ADC contrasts, acquired in [~]1 minute), as well as to slower, more standard single-contrast T1-weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix and single-contrast T1-weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test-retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/430956v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@3ae0e9org.highwire.dtl.DTLVardef@1840d39org.highwire.dtl.DTLVardef@80339borg.highwire.dtl.DTLVardef@bc16cf_HPS_FORMAT_FIGEXP M_FIG Graphical abstract. C_FIG

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bioRxiv2020

Sailing in rough waters: examining volatility of fMRI noise

BackgroundThe assumption that functional magnetic resonance imaging (fMRI) noise has constant volatility has recently been challenged by studies examining heteroscedasticity arising from head motion and physiological noise. The present study builds on this work using latest methods from the field of financial mathematics to model fMRI noise volatility. MethodsMulti-echo nd human fMRI scans were used and realised volatility was estimated. The Hurst parameter H [isin] (0, 1), which governs the roughness/irregularity of realised volatility time series, was estimated. Calibration of H was performed pathwise, using well-established neural network calibration tools. ResultsIn all experiments the volatility calibrated to values within the rough case, H < 0.5, and on average fMRI noise was very rough with 0.03 < H < 0.05. Some edge effects were also observed, whereby H was larger near the edges of the phantoms. DiscussionThe findings suggest that fMRI volatility is not only non-constant, but also substantially more irregular than a standard Brownian motion. Thus, further research is needed to examine the impact such pronounced oscillations in the volatility of fMRI noise have on data analyses.

neuroscience↗

bioRxiv2020

Longitudinal alterations in fronto-striatal glutamate are associated with functioning during inhibitory control in autism spectrum disorder and obsessive compulsive disorder

BackgroundAutism spectrum disorder (ASD) and obsessive compulsive disorder (OCD) are neurodevelopmental disorders with overlapping symptomatology. Both show deficits in inhibitory control, which are associated with altered functioning and glutamate concentrations in the fronto-striatal circuitry. These parameters have never been examined together. Here we, for the first time, used a multi-center, longitudinal approach to investigate fronto-striatal functioning during an inhibitory control task and its association with fronto-striatal glutamate concentrations across these two disorders. Methods74 adolescents with ASD (24) or OCD (15) and controls (35) aged 8-17 were recruited across three sites of the European TACTICS consortium. They underwent two magnetic resonance imaging (MRI) sessions with a one-year interval. This included proton magnetic resonance spectroscopy (1H-MRS; n=74) and functional MRI during an inhibitory control task (n=57). We used linear mixed effects models to investigate, over time, the relationship between fronto-striatal functioning and glutamate concentrations across these groups and continuous measures of overlapping compulsivity symptoms. ResultsDuring failed inhibitory control, in OCD increased striatal glutamate was associated with increased neural activation of ACC, an effect that decreased over time. During successful inhibitory control, higher ACC glutamate was positively associated with striatal activation in OCD and compulsivity across time. ACC glutamate levels decreased over time in the ASD group compared to controls, while striatal glutamate decreased over time, independent of diagnosis. ConclusionsSignificant differences in fronto-striatal glutamate were observed in ASD and OCD, affecting functional activity during failed- and successful inhibitory control differently, especially in OCD, with effects changing over time.

neuroscience↗

bioRxiv2020

The Development of Cognitive Control in Children with Autism Spectrum Disorders or Obsessive-Compulsive Disorder: A Longitudinal fMRI study

Repetitive behavior is a core symptom of Autism Spectrum Disorder (ASD) and Obsessive-Compulsive Disorder (OCD), and has been associated with impairments in cognitive control. However, it is unclear how cognitive control and associated neural circuitry relate to the development of repetitive behavior in children with these disorders. In a multicenter, longitudinal study (TACTICS; Translational Adolescent and Childhood Therapeutic Interventions in Compulsive Syndromes), the development of cognitive control was assessed during late childhood using a longitudinal fMRI design with a modified stop-signal task in children with ASD or OCD, and typically developing (TD) children (baseline: N=122 (8-12y), follow-up: N=72 (10-14y), average interval: 1.2y). Stop-signal reaction time (SSRT) decreased over development, regardless of diagnosis. Repetitive behavior in children with ASD and OCD was not associated with performance on the stop-signal task. There were no whole-brain between-group differences in brain activity, but ROI-analyses showed increases in activity in right precentral gyrus over development for children with OCD. In sum, even though subtle differences were observed in the development of brain activity in children with OCD, the findings overall suggest that the development of cognitive control, as assessed by the stop signal task, is similar in children with and without ASD or OCD.

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bioRxiv2019

Different Whole-Brain Functional Connectivity Correlates of Reactive-Proactive Aggression and Callous-Unemotional Traits in Disruptive Children and Adolescents

BackgroundDisruptive behavior in children and adolescents can manifest itself in reactive (RA) and proactive (PA) aggression and is modulated by callous-unemotional (CU) traits and comorbidity. Research on aggression subtype-specific neural correlates is limited and the role of comorbid symptoms largely neglected.\n\nMethodsThe current multi-center study extended previous efforts by investigating unrestricted resting state functional connectivity (rsFC) alterations. The large sample (n = 207) of children and adolescents aged 8 - 18 years (mean age = 13.30 {+/-} 2.60 years) included 118 cases with disruptive behavior (80 diagnosed with Oppositional Defiant Disorder and/or Conduct Disorder) and 89 controls. Attention-deficit/hyperactivity disorder (ADHD) and anxiety symptoms were added as covariates. We measured changes in global and local voxel-to-voxel rsFC using functional magnetic resonance imaging at 3T (mean acquisition time = 8 min 25 sec).\n\nResultsCompared to controls, cases demonstrated altered rsFC including frontal areas when anxiety but not ADHD symptoms were considered. Within cases, RA and PA scores related to changes in global and local rsFC in central gyrus and precuneus previously linked to aggression-related impairments. CU trait severity correlated with global rsFC alterations including inferior and middle temporal gyrus implicated in empathy, emotion, and reward-related activity. Importantly, most observed aggression subtype-specific patterns could only be identified when ADHD and anxiety problems were also accounted for.\n\nConclusionsThe current study clarifies that distinct though overlapping brain connectivity measures can disentangle differing manifestations of aggressive behavior. Moreover, our results highlight the importance of considering comorbid symptoms for detecting aggression-related rsFC alterations.

neuroscience↗

bioRxiv2018

Aggression Subtypes Relate to Distinct Resting State Functional Connectivity in Disruptive Children and Adolescents

ObjectiveThere is increasing evidence to suggest altered resting state functional connectivity (rsFC) in adolescents with conduct problems. However, no rsFC studies have addressed the effects of reactive and proactive aggression. Herein, we examined the associations between these aggression subtypes along with subdimensions of callous-unemotional (CU) traits and rsFC using predefined seeds in aggression-related salience network (SN) and default mode network (DMN).\n\nMethodAggression subtype-specific whole-brain rsFC of SN and DMN seeds was investigated in a resting state sequence (mean acquisition time = 8 min 25 sec) acquired from 207 children and adolescents of both sexes aged 8 - 18 years (mean age (SD) = 13.30 (2.60) years; range = 8.02 - 18.35) in a multi-center study. One hundred eighteen individuals exhibited disruptive behavior (conduct disorder/oppositional defiant disorder) with different levels of comorbid ADHD symptoms, 89 were healthy.\n\nResultsCompared to healthy controls, cases demonstrated reduced DMN and - after controlling for ADHD scores - SN seed-based rsFC with left hemispheric frontal clusters. We found increased and distinct aggression-subtype specific rsFC patterns in brain regions linked to processes like emotion, empathy, moral, cognitive control, and decision-making. Specifically, reactive and proactive aggression correlated with distinct SN and DMN seed-based rsFC patterns. CU dimensions led to different DMN and SN rsFC with clusters including frontal, parietal, and cingulate areas, with uncaring-related clusters extended to cerebellar regions.\n\nConclusionsThis first study investigating reactive and proactive aggression along with CU dimensions reveals new subtype-specific whole-brain rsFC patterns, extending the knowledge of neural networks to further distinct forms of disruptive behavior.

neuroscience↗