Population-averaged atlas of the macroscale human structural connectome and its network topology

The Role of Anatomic Connectivity in Inhibitory Control Revealed by Combining Connectome-based Lesion-symptom Mapping with Event-related Potentials

Inhibitory control refers to the ability to suppress cognitive or motor processes. Current neurocognitive models indicate that this function mainly involves the anterior cingulate cortex and the inferior frontal cortex. However, how the communication between these areas influence inhibitory control performance and their functional response remains unknown. We addressed this question by injecting behavioral and electrophysiological markers of inhibitory control recorded during a Go/NoGo task as the 'symptoms' in a connectome-based lesion-symptom mapping approach in a sample of 96 first unilateral stroke patients. This approach enables us to identify the white matter tracts whose disruption by the lesions causally influences brain functional activity during inhibitory control. We found a central role of left frontotemporal and frontobasal intrahemispheric connections, as well as of the connections between the left temporoparietal and right temporal areas in inhibitory control performance. We also found that connections between the left temporal and right superior parietal areas modulate the conflict-related N2 event-related potential component and between the left temporal parietal area and right temporal and occipital areas for the inhibition P3 component. Our study supports the role of a distributed bilateral network in inhibitory control and reveals that combining lesion-symptom mapping approaches with functional indices of cognitive processes could shed new light on post-stroke functional reorganization. It may further help to refine the interpretation of classical electrophysiological markers of executive control in stroke patients.

Evaluating a motor progression connectivity model across Parkinson's disease stages

BACKGROUND

Stimulation of a specific site in the dorsolateral subthalamic nucleus (STN) was recently associated with slower motor progression in Parkinson's Disease (PD), based on the deep brain stimulation (DBS) in early-stage PD pilot clinical trial. Here, subject-level visualizations are presented of this early-stage PD dataset to further describe the relationship between active contacts and motor progression. This study also evaluates whether stimulation of the sweet spot and connectivity model associated with slower motor progression is also associated with improvements in long-term motor outcomes in patients with advanced-stage PD.

METHODS

Active contacts of the early-stage PD cohort (N = 14) were analyzed alongside the degree of two-year motor progression. Sweet spot and connectivity models derived from the early-stage PD cohort were then used to determine how well they can estimate the variance in long-term motor outcomes in an independent STN-DBS cohort of advanced-stage PD patients (N = 29).

RESULTS

In early-stage PD, proximity of stimulation to the dorsolateral STN was associated with slower motor progression. In advanced-stage PD, stimulation proximity to the early PD connectivity model and sweet spot were associated with better long-term motor outcomes (R = 0.60, P < 0.001; R = 0.37, P = 0.046, respectively).

CONCLUSIONS

Results suggest stimulation of a specific site in the dorsolateral STN is associated with both slower motor progression and long-term motor improvements in PD.

Multivariate and network lesion mapping reveals distinct architectures of domain-specific post-stroke cognitive impairments

BACKGROUND

The purpose of this study was to identify patterns of structural disconnection and multivariate lesion-behaviour relationships associated with post-stroke deficits across six commonly impacted cognitive domains: executive function, language, memory, numerical processing, praxis, and visuospatial attention.

METHODS

Stroke survivors (n = 593) completed a brief domain-specific cognitive assessment (the Oxford Cognitive Screen (OCS)) during acute hospitalisation. Network-level and multivariate (sparce canonical correlation) lesion mapping analyses were conducted to identify focal neural correlates and distributed patterns of structural disconnection associated with impairment on each of the 16 OCS measures.

RESULTS

Network-level and multivariate lesion mapping analyses identified significant correlates for 12/16 and 10/16 OCS measures, respectively which were largely consistent with correlates reported in past work. Language impairments were reliably localised to network- and voxel-level correlates centred in left fronto-temporal regions. Memory impairments were associated with disconnection in a large network of left hemisphere regions. Number processing deficits were associated with damage to voxels centred in the left insular/opercular cortex, as well as disconnection within the surrounding white matter tracts. Within the domain of attention, different subtypes of visuospatial neglect were linked to distinct but partially overlapping patterns of disconnection and voxel-level damage. Praxis impairment was not linked to any voxel-level regions but was significantly associated with disconnection within the left hemisphere dorsal attention network.

CONCLUSION

These results highlight the utility of routine, domain-specific cognitive assessment and imaging data for theoretically-driven lesion mapping analyses, while providing novel insight into the complex anatomical correlates of common and debilitating post-stroke cognitive impairments.

Diffusion tensor imaging and gray matter volumetry to evaluate cerebral remodeling processes after a pure motor stroke: a longitudinal study

BACKGROUND AND OBJECTIVES

Clinical factors are not sufficient to fix a prognosis of recovery after stroke. Pyramidal tract or alternate motor fiber (aMF: reticulo-, rubrospinal pathways and transcallosal fibers) integrity and remodeling processes assessable by diffusion tensor MRI (DTI) and voxel-based morphometry (VBM) may be of interest. The primary objective was to study longitudinal cortical brain changes using VBM and longitudinal corticospinal tract changes using DTI during the first 4 months after lacunar cerebral infarction. The second objective was to determine which changes were correlated to clinical improvement.

METHODS

Twenty-one patients with deep brain ischemic infarct with pure motor deficit (NIHSS score ≥ 2) were recruited at Purpan Hospital and included. Motor deficit was measured [Nine peg hole test (NPHT), dynamometer (DYN), Hand-Tapping Test (HTT)], and a 3T MRI scan (VBM and DTI) was performed during the acute and subacute phases.

RESULTS

White matter changes: corticospinal fractional anisotropy (FACST) was significantly reduced at follow-up (approximately 4 months) on the lesion side. FAr (FA ratio in affected/unaffected hemispheres) in the corona radiata was correlated to the motor performance at the NPHT, DYN, and HTT at follow-up. The presence of aMFs was not associated with the extent of recovery. Grey matter changes: VBM showed significant increased cortical thickness in the ipsilesional premotor cortex at follow-up. VBM changes in the anterior cingulum positively correlated with improvement in motor measures between baseline and follow-up.

DISCUSSION

To our knowledge, this study is original because is a longitudinal study combining VBM and DTI during the first 4 months after stroke in a series of patients selected on pure motor deficit. Our data would suggest that good recovery relies on spared CST fibers, probably from the premotor cortex, rather than on the aMF in this group with mild motor deficit. The present study suggests that VBM and FACST could provide reliable biomarkers of post-stroke atrophy, reorganization, plasticity and recovery.

CLINICALTRIALS

GOV IDENTIFIER

NCT01862172, registered May 24, 2013.

Potentiation of cortico-spinal output via targeted electrical stimulation of the motor thalamus

Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for therapies aimed at improving volitional muscle activation. Here we hypothesize that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby immediately potentiating motor output. To test this hypothesis, we identify optimal thalamic targets and stimulation parameters that enhance upper-limb motor-evoked potentials and grip forces in anesthetized monkeys. This potentiation persists after white matter lesions. We replicate these results in humans during intra-operative testing. We then design a stimulation protocol that immediately improves strength and force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.

Exploring the late maturation of an intrinsic episodic memory network: A resting-state fMRI study

Previous research suggests that episodic memory relies on functional neural networks,which are present even in the absence of an explicit task. The regions that integrate.these networks and the developmental changes in intrinsic functional connectivity.remain elusive. In the present study, we outlined an intrinsic episodic memory network.(iEMN) based on a systematic selection of functional connectivity studies, and.inspected network differences in resting-state fMRI between adolescents (13-17 years.old) and adults (23-27 years old) from the publicly available NKI-Rockland Sample.Through a review of brain regions commonly associated with episodic memory.networks, we identified a potential iEMN composed by 14 bilateral ROIs, distributed.across temporal, frontal and parietal lobes. Within this network, we found an increase.in resting-state connectivity from adolescents to adults between the right temporal pole.and two regions in the right lateral prefrontal cortex. We argue that the coordination of.these brain regions, connecting areas of semantic processing and areas of controlled.retrieval, arises as an important feature towards the full maturation of the episodic.memory system. The findings add to evidence suggesting that adolescence is a key.period in memory development and highlights the role of intrinsic functional.connectivity in such development.

Dynamic functional connectivity in verbal cognitive control and word reading

Cognitive control processes enable the suppression of automatic behaviors and the initiation of appropriate responses. The Stroop color naming task serves as a benchmark paradigm for understanding the neurobiological model of verbal cognitive control. Previous research indicates a predominant engagement of the prefrontal and premotor cortex during the Stroop task compared to reading. We aim to further this understanding by creating a dynamic atlas of task-preferential modulations of functional connectivity through white matter. Patients undertook word-reading and Stroop tasks during intracranial EEG recording. We quantified task-related high-gamma amplitude modulations at 547 nonepileptic electrode sites, and a mixed model analysis identified regions and timeframes where these amplitudes differed between tasks. We then visualized white matter pathways with task-preferential functional connectivity enhancements at given moments. Word reading, compared to the Stroop task, exhibited enhanced functional connectivity in inter- and intra-hemispheric white matter pathways from the left occipital-temporal region 350-600 ms before response, including the posterior callosal fibers as well as the left vertical occipital, inferior longitudinal, inferior fronto-occipital, and arcuate fasciculi. The Stroop task showed enhanced functional connectivity in the pathways from the left middle-frontal pre-central gyri, involving the left frontal u-fibers and anterior callosal fibers. Automatic word reading largely utilizes the left occipital-temporal cortices and associated white matter tracts. Verbal cognitive control predominantly involves the left middle frontal and precentral gyri and its connected pathways. Our dynamic tractography atlases may serve as a novel resource providing insights into the unique neural dynamics and pathways of automatic reading and verbal cognitive control.

Atlas-based structural disconnectomes are associated to cognitive performance in brain tumors

BACKGROUND

Brain tumors are associated with impaired cognitive functioning, which may result from disruptions in brain structural connectivity. Estimating structural disconnections is a more advantageous representation of tumor impact and can be performed indirectly through normative brain atlases.

MATERIALS AND METHODS

Using a publicly available dataset of glioma and meningioma patient MRI scans and tumor masks, latent correlations were estimated between measures of structural disconnection and attention-based cognitive functioning. These measures included gray matter (GM) parcel damage, white matter tract (WMT) damage, GM parcel-to-parcel disconnections, and reaction time (RTI) as part of the Cambridge Neuropsychological Test Automated Battery (CANTAB) to assess attention.

RESULTS

Preprocessing pipelines with two different methods of minimizing the pathology impact on MRI normalization were utilized: cost function masking and lesion filling. The results across both pipelines were nearly consistent, with significant correlations mainly found between RTI measures and the damage to left inferior fronto-occipital and uncinate fasciculus, as well as the left prefrontal-visual disconnections.

CONCLUSIONS

This alludes to the importance of left-hemispheric prefrontal-visual coupling in attention-based tasks, particularly those involving object- and feature-based attention.

Metric comparison of connectome-based lesion-symptom mapping in post-stroke aphasia

Connectome-based lesion-symptom mapping relates behavioural impairments to disruption of structural brain connectivity. Connectome-based lesion-symptom mapping can be based on different approaches (diffusion MRI versus lesion mask), network scales (whole brain versus regions of interest) and measure types (tract-based, parcel-based, or network-based metrics). We evaluated the similarity of different connectome-based lesion-symptom mapping processing choices and identified factors that influence the results using multiverse analysis-the strategy of conducting and displaying the results of all reasonable processing choices. Metrics derived from lesion masks and diffusion-weighted images were tested for association with Boston Naming Test and Token Test performance in a sample of 50 participants with aphasia following left hemispheric stroke. 'Direct' measures were derived from diffusion-weighted images. 'Indirect' measures were derived by overlaying lesion masks on a white matter atlas. Parcel-based connectomes were constructed for the whole brain and regions of interest (14 language-relevant parcels). Numerous tract-based and network-based metrics were calculated. There was a high discrepancy across processing approaches (diffusion-weighted images versus lesion masks), network scales (whole brain versus regions of interest) and metric types. Results indicate weak correlations and different connectome-based lesion-symptom mapping results across the processing choices. Substantial methodological work is needed to validate the various decision points that arise when conducting connectome-based lesion-symptom mapping analyses. Multiverse analysis is a useful strategy for evaluating the similarity across different processing choices in connectome-based lesion-symptom mapping.

Cortical and subcortical substrates of working memory in the right hemisphere: A connectome-based lesion-symptom mapping study

Working Memory (WM) is a cognitive system whose crucial role is to temporarily hold and manipulate information. Early studies suggest that verbal WM is typically associated with left hemisphere (LH) brain regions, while the processing of visuospatial information in WM more specifically depends on the right hemisphere (RH). However, recent evidence suggests a more complex network involving both hemispheres' prefrontal and posterior parietal cortices in these processes. Unfortunately, previous lesion studies often examined only one modality (either verbal, or visuospatial) or one hemisphere, which limits the possible conclusions regarding non-lateralized hemispheric involvement. Using connectome-based lesion-symptom mapping on a large sample of patients with left (LBD) and right (RBD) focal brain damage, we examined whether gray matter damage and white matter disconnections predict deficits of WM updating in an N-back task. Patients were examined with two WM tasks that differed regarding modality (verbal, spatial) and cognitive load (1-back, 2-back). Behavioral outcomes indicated that RBD patients showed significant deficits in WM updating, regardless of task modality or load. This observation was supported by whole-brain voxel-based analysis, revealing associations between WM deficits and gray matter clusters in the RH. Specifically, damage to the right lateral frontal cortex including the brain region homologous to Broca's area was associated with verbal WM deficits, while damage to the right inferior parietal lobe and posterior temporal cortex predicted spatial WM deficits. Additionally, white matter analyses identified severely impacted tracts in the RH, predicting deficits in both verbal and spatial WM. Our findings suggest that the mental manipulation of both verbal and visuospatial information in WM updating relies on the integrity of the RH, irrespective of the specific type of information held in mind.

Contributions of network structure, chemoarchitecture and diagnostic categories to transitions between cognitive topographies

The mechanisms linking the brain's network structure to cognitively relevant activation patterns remain largely unknown. Here, by leveraging principles of network control, we show how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic database. Specifically, we systematically integrated large-scale multimodal neuroimaging data from functional magnetic resonance imaging, diffusion tractography, cortical morphometry and positron emission tomography to simulate how anatomically guided transitions between cognitive states can be reshaped by neurotransmitter engagement or by changes in cortical thickness. Our model incorporates neurotransmitter-receptor density maps (18 receptors and transporters) and maps of cortical thickness pertaining to a wide range of mental health, neurodegenerative, psychiatric and neurodevelopmental diagnostic categories (17,000 patients and 22,000 controls). The results provide a comprehensive look-up table charting how brain network organization and chemoarchitecture interact to manifest different cognitive topographies, and establish a principled foundation for the systematic identification of ways to promote selective transitions between cognitive topographies.

Organization of conceptual tool knowledge following left and right brain lesions: Evidence from neuropsychological dissociations and multivariate disconnectome symptom mapping

The aim of this work was to better understand the organization of conceptual tool knowledge following stroke. We explored specifically the link between manipulation kinematics and manipulation hand posture; and the link between manipulation kinematics and function relations in left brain-damaged (n = 30) and right brain-damaged (n = 30) patients. We examined the performance of brain-damaged patients in conceptual tool tasks using neuropsychological dissociations and disconnectome symptom mapping. Our results suggest that manipulation kinematics is more impaired than function relations, following left or right brain lesions. We also observed that manipulation kinematics and manipulation hand posture are dissociable dimensions but are still highly interrelated, particularly in left brain-damaged patients. We also found that the corpus callosum and bilateral superior longitudinal fasciculus are involved in action and semantic tool knowledge following left brain lesions. Our results provide evidence that the right hemisphere contains conceptual tool representations. Further studies are needed to better understand the mechanisms supporting the cognitive recovery of conceptual tool knowledge. An emerging hypothesis is that the right hemisphere may support functional recovery through interhemispheric transfer following a left hemisphere stroke.

Validation of Tenths Stereotactic Coordinates Method Using Probabilistic Tractography of the Ansa Lenticularis in Parkinson's Disease Patients

OBJECTIVE

To evaluate the accuracy of stereotactic coordinates to target the ansa lenticularis (AL) using 2 surgical planning methods, the conventional millimeter method (MM) and the normalized Tenths method (TM), assessed through individualized probabilistic tractography.

METHODS

Stereotactic targeting of the AL was assessed in 2 groups: 16 patients with Parkinson's disease and 16 healthy controls from Group 1, and 39 Parkinson's disease patients from Group 2. Structural and diffusion magnetic resonance imaging probabilistic tractography identified the AL based on the Schaltenbrand-Wahren Atlas. The MM defined stereotactic coordinates in millimeters, while the TM refined the planning by dividing the intercommissural line (AC-PC) distance into 10 equal parts, normalizing the "X," "Y," and "Z" coordinates for each patient. We subsequently compared the percentage of structural connectivity (%conn) of the AL with predefined regions of interest (ROIs), including the frontopontine-corticothalamic tracts, globus pallidus internus-ventral oral anterior, and ventral oral posterior, and quantified the streamlines in 142 brain hemispheres using the MM and TM coordinates.

RESULTS

Despite anatomical variations in intercommissural (AC-PC) line lengths between both groups (22.5 ± 2.09 mm and 24.4 ± 2.56 mm, respectively; P = 0.002), as well as differences in magnetic resonance imaging acquisition parameters, we found that the TM significantly enhanced streamline identification and %conn compared to the MM. These enhancements were noted across ROIs: frontopontine-corticothalamic and globus pallidus internus-ventral oral anterior in both hemispheres, and globus pallidus internus-ventral oral posterior in the left (P < 0.001) and right hemispheres (P = 0.03).

CONCLUSIONS

TM surpasses MM in identifying the structural connectivity between the AL and predefined ROIs, underscoring the advantages of coordinate normalization. However, variations in AC-PC line lengths and Euclidean distances between methods could lead to inaccuracies in the coordinate settings, potentially affecting the precision of structural connectivity and the efficacy of therapeutic outcomes.

White matter correlates of cognition: A diffusion magnetic resonance imaging study

BACKGROUND

Our comprehension of the interplay of cognition and the brain remains constrained. While functional imaging studies have identified cognitive brain regions, structural correlates of cognitive functions remain underexplored. Advanced methods like Diffusion Magnetic Resonance Imaging (DMRI) facilitate the exploration of brain connectivity and White Matter (WM) tract microstructure. Therefore, we conducted connectometry method on DMRI data, to reveal WM tracts associated with cognition.

METHODS

125 healthy participants from the National Institute of Mental Health Intramural Healthy Volunteer Dataset were recruited. Multiple regression analyses were conducted between DMRI-derived Quantitative Anisotropy (QA) values within WM tracts and scores of participants in Flanker Inhibitory Control and Attention Test (attention), Dimensional Change Card Sort (executive function), Picture Sequence Memory Test (episodic memory), and List Sorting Working Memory Test (working memory) tasks from National Institute of Health toolbox. The significance level was set at False Discovery Rate (FDR)<0.05.

RESULTS

We identified significant positive correlations between the QA of WM tracts within the left cerebellum and bilateral fornix with attention, executive functioning, and episodic memory (FDR=0.018, 0.0002, and 0.0002, respectively), and a negative correlation between QA of WM tracts within bilateral cerebellum with attention (FDR=0.028). Working memory demonstrated positive correlations with QA of left inferior longitudinal and left inferior fronto-occipital fasciculi (FDR=0.0009), while it showed a negative correlation with QA of right cerebellar tracts (FDR=0.0005).

CONCLUSION

Our results underscore the intricate link between cognitive performance and WM integrity in frontal, temporal, and cerebellar regions, offering insights into early detection and targeted interventions for cognitive disorders.

Sex differences in patterns of white matter neuroplasticity after balance training in young adults

Introduction

In past work we demonstrated different patterns of white matter (WM) plasticity in females versus males associated with learning a lab-based unilateral motor skill. However, this work was completed in neurologically intact older adults. The current manuscript sought to replicate and expand upon these WM findings in two ways: (1) we investigated biological sex differences in neurologically intact young adults, and (2) participants learned a dynamic full-body balance task.

Methods

24 participants (14 female, 10 male) participated in the balance training intervention, and 28 were matched controls (16 female, 12 male). Correlational tractography was used to analyze changes in WM from pre- to post-training.

Results

Both females and males demonstrated skill acquisition, yet there were significant differences in measures of WM between females and males. These data support a growing body of evidence suggesting that females exhibit increased WM neuroplasticity changes relative to males despite comparable changes in motor behavior (e.g., balance).

Discussion

The biological sex differences reported here may represent an important factor to consider in both basic research (e.g., collapsing across females and males) as well as future clinical studies of neuroplasticity associated with motor function (e.g., tailored rehabilitation approaches).

BundleAGE: Predicting White Matter Age using Along-Tract Microstructural Profiles from Diffusion MRI

Brain Age Gap Estimation (BrainAGE) is an estimate of the gap between a person's chronological age (CA) and a measure of their brain's 'biological age' (BA). This metric is often used as a marker of accelerated aging, albeit with some caveats. Age prediction models trained on brain structural and functional MRI have been employed to derive BrainAGE biomarkers, for predicting the risk of neurodegeneration. While voxel-based and along-tract microstructural maps from diffusion MRI have been used to study brain aging, no studies have evaluated along-tract microstructure for computing BrainAGE. In this study, we train machine learning models to predict a person's age using along-tract microstructural profiles from diffusion tensor imaging. We were able to demonstrate differential aging patterns across different white matter bundles and microstructural measures. The novel Bundle Age Gap Estimation (BundleAGE) biomarker shows potential in quantifying risk factors for neurodegenerative diseases and aging, while incorporating finer scale information throughout white matter bundles.

A practical guide for combining functional regions of interest and white matter bundles

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset.

Deep multimodal saliency parcellation of cerebellar pathways: Linking microstructure and individual function through explainable multitask learning

Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion magnetic resonance imaging tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while relying solely on fibre tract structure. However, each fibre tract may relay information related to multiple cognitive and motor functions of the cerebellum. Hence, it may be beneficial for parcellation to consider the potential importance of the fibre tracts for individual motor and cognitive functional performance measures. In this work, we propose a multimodal data-driven method for cerebellar pathway parcellation, which incorporates both measures of microstructure and connectivity, and measures of individual functional performance. Our method involves first training a multitask deep network to predict various cognitive and motor measures from a set of fibre tract structural features. The importance of each structural feature for predicting each functional measure is then computed, resulting in a set of structure-function saliency values that are clustered to parcellate cerebellar pathways. We refer to our method as Deep Multimodal Saliency Parcellation (DeepMSP), as it computes the saliency of structural measures for predicting cognitive and motor functional performance, with these saliencies being applied to the task of parcellation. Applying DeepMSP to a large-scale dataset from the Human Connectome Project Young Adult study (n = 1065), we found that it was feasible to identify multiple cerebellar pathway parcels with unique structure-function saliency patterns that were stable across training folds. We thoroughly experimented with all stages of the DeepMSP pipeline, including network selection, structure-function saliency representation, clustering algorithm, and cluster count. We found that a 1D convolutional neural network architecture and a transformer network architecture both performed comparably for the multitask prediction of endurance, strength, reading decoding, and vocabulary comprehension, with both architectures outperforming a fully connected network architecture. Quantitative experiments demonstrated that a proposed low-dimensional saliency representation with an explicit measure of motor versus cognitive category bias achieved the best parcellation results, while a parcel count of four was most successful according to standard cluster quality metrics. Our results suggested that motor and cognitive saliencies are distributed across the cerebellar white matter pathways. Inspection of the final k = 4 parcellation revealed that the highest-saliency parcel was most salient for the prediction of both motor and cognitive performance scores and included parts of the middle and superior cerebellar peduncles. Our proposed saliency-based parcellation framework, DeepMSP, enables multimodal, data-driven tractography parcellation. Through utilising both structural features and functional performance measures, this parcellation strategy may have the potential to enhance the study of structure-function relationships of the cerebellar pathways.

Asymmetry of the Frontal Aslant Tract Depends on Handedness

BACKGROUND AND PURPOSE

The human brain displays structural and functional disparities between its hemispheres, with such asymmetry extending to the frontal aslant tract. This plays a role in a variety of cognitive functions, including speech production, language processing, and executive functions. However, the factors influencing the laterality of the frontal aslant tract remain incompletely understood. Handedness is hypothesized to impact frontal aslant tract laterality, given its involvement in both language and motor control. In this study, we aimed to investigate the relationship between handedness and frontal aslant tract lateralization, providing insight into this aspect of brain organization.

MATERIALS AND METHODS

The Automated Tractography Pipeline was used to generate the frontal aslant tract for both right and left hemispheres in a cohort of 720 subjects sourced from the publicly available Human Connectome Project in Aging database. Subsequently, macrostructural and microstructural parameters of the right and left frontal aslant tract were extracted for each individual in the study population. The Edinburgh Handedness Inventory scores were used for the classification of handedness, and a comparative analysis across various handedness groups was performed.

RESULTS

An age-related decline in both macrostructural parameters and microstructural integrity was noted within the studied population. The frontal aslant tract demonstrated a greater volume and larger diameter in male subjects compared with female participants. Additionally, a left-side laterality of the frontal aslant tract was observed within the general population. In the right-handed group, the volume (P < .001), length (P < .001), and diameter (P = .004) of the left frontal aslant tract were found to be higher than those of the right frontal aslant tract. Conversely, in the left-handed group, the volume (P = .040) and diameter (P = .032) of the left frontal aslant tract were lower than those of the right frontal aslant tract. Furthermore, in the right-handed group, the volume and diameter of the frontal aslant tract showed left-sided lateralization, while in the left-handed group, a right-sided lateralization was evident.

CONCLUSIONS

The laterality of the frontal aslant tract appears to differ with handedness. This finding highlights the complex interaction between brain lateralization and handedness, emphasizing the importance of considering handedness as a factor in evaluating brain structure and function.

Sleep Deprivation Effects on Brain State Dynamics Are Associated With Dopamine D2 Receptor Availability Via Network Control Theory

BACKGROUND

Sleep deprivation (SD) negatively affects brain function. Most brain imaging studies have investigated the effects of SD on static brain function. SD effects on functional brain dynamics and their relationship with molecular changes remain relatively unexplored.

METHODS

We used functional magnetic resonance imaging to examine resting-brain state dynamics after one night of SD compared with rested wakefulness (N = 41) and assessed the association of brain state dynamics with striatal brain dopamine D2 receptor availability measured by positron emission tomography [11C]raclopride using network control theory.

RESULTS

SD reduced dwell time and persistence probabilities, with the strongest effects in two brain states, one characterized by high default mode network and low dorsal attention network activity and the other by high frontoparietal network and low somatomotor network activity. Using network control theory, we showed that after SD, there was an overall increase in the control energy required for brain state transitions, with effects varying for different brain state transitions. Control energy requirement was negatively associated with transition probabilities under SD and restful wakefulness and accounted for SD-induced changes in transition probabilities. Alteration in the energy landscape was associated with SD-induced changes in striatal D2 receptor distribution.

CONCLUSIONS

These findings demonstrate altered occurrence of internally and externally oriented brain states following acute SD and suggest an association with energy requirements for brain state transitions modulated by striatal D2 receptors.

Amyloid, Tau, and APOE in Alzheimer's Disease: Impact on White Matter Tracts

Alzheimer's disease (AD) is characterized by cognitive decline and memory loss due to the abnormal accumulation of amyloid-beta (Aβ) plaques and tau tangles in the brain; its onset and progression also depend on genetic factors such as the apolipoprotein E (APOE) genotype. Understanding how these factors affect the brain's neural pathways is important for early diagnostics and interventions. Tractometry is an advanced technique for 3D quantitative assessment of white matter tracts, localizing microstructural abnormalities in diseased populations in vivo. In this work, we applied BUAN (Bundle Analytics) tractometry to 3D diffusion MRI data from 730 participants in ADNI3 (phase 3 of the Alzheimer's Disease Neuroimaging Initiative; age range: 55-95 years, 349M/381F, 214 with mild cognitive impairment, 69 with AD, and 447 cognitively healthy controls). Using along-tract statistical analysis, we assessed the localized impact of amyloid, tau, and APOE genetic variants on the brain's neural pathways. BUAN quantifies microstructural properties of white matter tracts, supporting along-tract statistical analyses that identify factors associated with brain microstructure. We visualize the 3D profile of white matter tract associations with tau and amyloid burden in Alzheimer's disease; strong associations near the cortex may support models of disease propagation along neural pathways. Relative to the neutral genotype, APOE ϵ3/ϵ3, carriers of the AD-risk conferring APOE ϵ4 genotype show microstructural abnormalities, while carriers of the protective ϵ2 genotype also show subtle differences. Of all the microstructural metrics, mean diffusivity (MD) generally shows the strongest associations with AD pathology, followed by axial diffusivity (AxD) and radial diffusivity (RD), while fractional anisotropy (FA) is typically the least sensitive metric. Along-tract microstructural metrics are sensitive to tau and amyloid accumulation, showing the potential of diffusion MRI to track AD pathology and map its impact on neural pathways.

Microstructural properties of attention-related white matter tracts are associated with the renewal effect of extinction

The tendency to show the renewal effect of extinction appears as an intra-individually stable, reproducible processing strategy associated with differential patterns of BOLD activation in hippocampus, iFG and vmPFC, as well as differential resting-state functional connectivity between prefrontal regions and the dorsal attention network. Also, pharmacological modulations of the noradrenergic system that influence attentional processing have partially different effects upon individuals with (REN) and without (NoREN) a propensity for renewal. However, it is as yet unknown whether REN and NoREN individuals differ regarding microstructural properties in attention-related white matter (WM) regions, and whether such differences are related to noradrenergic processing. In this diffusion tensor imaging (DTI) analysis we investigated the relation between microstructural properties of attention-related WM tracts and ABA renewal propensity, under conditions of noradrenergic stimulation by means of the noradrenergic reuptake inhibitor atomoxetine, compared to placebo. Fractional anisotropy (FA) was higher in participants with noradrenergic stimulation (ATO) compared to placebo (PLAC), the effect was predominantly left-lateralized and based on the comparison of ATO REN and PLAC REN participants. In REN participants of both treatment groups, FA in several WM tracts showed a positive correlation with the ABA renewal level, suggesting higher renewal levels were associated with higher microstructural integrity. These findings point towards a relation between microstructural properties of attention-related WM tracts and the propensity for renewal that is not specifically dependent on noradrenergic processing.

Clinical and neuroimaging characteristics of primary lateral sclerosis with overlapping features of progressive supranuclear palsy

BACKGROUND AND PURPOSE

Primary lateral sclerosis (PLS) is a neurodegenerative disorder that primarily affects the central motor system. In rare cases, clinical features of PLS may overlap with those of progressive supranuclear palsy (PSP). We investigate neuroimaging features that can help distinguish PLS with overlapping features of PSP (PLS-PSP) from PSP.

METHODS

Six patients with PLS-PSP were enrolled between 2019 and 2023. We compared their clinical and neuroimaging characteristics with 18 PSP-Richardson syndrome (PSP-RS) patients and 20 healthy controls. Magnetic resonance imaging, 18F-flortaucipir positron emission tomography (PET), quantitative susceptibility mapping, and diffusion tensor imaging tractography (DTI) were performed to evaluate eight brain regions of interest. Area under the receiver operating characteristic curve (AUROC) was calculated.

RESULTS

Five of the six PLS-PSP patients (83.3%) were male. Median age at symptom onset was 61.5 (52.5-63) years, and all had mixed features of PLS and PSP. Volumes of the pallidum, caudate, midbrain, and cerebellar dentate were smaller in PSP-RS than PLS-PSP, providing good discrimination (AUROC = 0.75 for all). The susceptibilities in pallidum, midbrain, and cerebellar dentate were greater in PSP-RS compared to PLS-PSP, providing excellent discrimination (AUROC ≥ 0.90 for all). On DTI, fractional anisotropy (FA) in the posterior limb of the internal capsule from the corticospinal tract was lower in PLS-PSP compared to PSP-RS (AUROC = 0.86), but FA in the superior cerebellar peduncle was lower in PSP-RS (AUROC = 0.95). Pallidum flortaucipir PET uptake was greater in PSP-RS compared to PLS-PSP (AUROC = 0.74).

CONCLUSIONS

Regional brain volume, tractography, and magnetic susceptibility, but not tau-PET, are useful in distinguishing PLS-PSP from PSP.

Multivariate mapping of low-resilient neurocognitive systems within and around low-grade gliomas

Accumulating evidence suggests that the brain exhibits a remarkable capacity for functional compensation in response to neurological damage, a resilience potential that is deeply rooted in the malleable features of its underlying anatomofunctional architecture. This propensity is particularly exemplified by diffuse low-grade glioma, a subtype of primary brain tumour. However, functional plasticity is not boundless, and surgical resections directed at structures with limited neuroplasticity can lead to incapacitating impairments. Yet, maximizing diffuse low-grade glioma resections offers substantial oncological benefits, especially when the resection extends beyond the tumour margins (i.e. supra-tumour or supratotal resection). In this context, the primary objective of this study was to identify which cerebral structures were associated with less favourable cognitive outcomes after surgery, while accounting for intra-tumour and supra-tumour features of the surgical resections. To achieve this objective, we leveraged a unique cohort of 400 patients with diffuse low-grade glioma who underwent surgery with awake cognitive mapping. Patients benefitted from a neuropsychological assessment consisting of 18 subtests administered before and 3 months after surgery. We analysed changes in performance and applied topography-focused and disconnection-focused multivariate lesion-symptom mapping using support vector regressions, in an attempt to capture resected cortico-subcortical structures less amenable to full cognitive compensation. The observed changes in performance were of a limited magnitude, suggesting an overall recovery (13 of 18 tasks recovered fully despite a mean resection extent of 92.4%). Nevertheless, lesion-symptom mapping analyses revealed that a lack of recovery in picture naming was linked to damage in the left inferior temporal gyrus and inferior longitudinal fasciculus. Likewise, for semantic fluency abilities, an association was established with damage to the left precuneus/posterior cingulate. For phonological fluency abilities, the left dorsomedial frontal cortex and the frontal aslant tract were implicated. Moreover, difficulties in spatial exploration were associated with injury to the right dorsomedial prefrontal cortex and its underlying connectivity. An exploratory analysis suggested that supra-tumour resections were associated with a less pronounced recovery following specific resection patterns, such as supra-tumour resections of the left uncinate fasciculus (picture naming), the left corticostriatal tract and the anterior corpus callosum (phonological fluency), the hippocampus and parahippocampus (episodic memory) and the right frontal-mesial areas (visuospatial exploration). Collectively, these patterns of results shed new light on both low-resilient neural systems and the prediction of cognitive recovery following glioma surgery. Furthermore, they indicate that supra-tumour resections were only occasionally less well tolerated from a cognitive viewpoint. In doing so, they have deep implications for surgical planning and rehabilitation strategies.

Optimal Concentric Tube Robot Design for Safe Intracerebral Hemorrhage Removal

Purpose

The purpose of this paper is to investigate the geometrical design and path planning of Concentric tube robots (CTR) for intracerebral hemorrhage (ICH) evacuation, with a focus on minimizing the risk of damaging white matter tracts and cerebral arteries.

Methods

To achieve our objective, we propose a parametrization method describing a general class of CTR geometric designs. We present mathematical models that describe the CTR design constraints and provide the calculation of a path risk value. We then use a genetic algorithm to determine the optimal tube geometry for targeting within the brain.

Results

Our results show that a multi-tube CTR design can significantly reduce the risk of damaging critical brain structures compared to the conventional straight tube design. However, there is no significant relationship between the path risk value and the number and shape of the additional inner curved tubes.

Conclusion

Considering the challenges of CTR hardware design, fabrication, and control, we conclude that the most practical geometry for a CTR path in ICH treatment is a straight outer tube followed by a planar curved inner tube. These findings have important implications for the development of safe and effective CTRs for ICH evacuation by enabling dexterous manipulation to minimize damage to critical brain structures.

Power and reproducibility in the external validation of brain-phenotype predictions

Brain-phenotype predictive models seek to identify reproducible and generalizable brain-phenotype associations. External validation, or the evaluation of a model in external datasets, is the gold standard in evaluating the generalizability of models in neuroimaging. Unlike typical studies, external validation involves two sample sizes: the training and the external sample sizes. Thus, traditional power calculations may not be appropriate. Here we ran over 900 million resampling-based simulations in functional and structural connectivity data to investigate the relationship between training sample size, external sample size, phenotype effect size, theoretical power and simulated power. Our analysis included a wide range of datasets: the Healthy Brain Network, the Adolescent Brain Cognitive Development Study, the Human Connectome Project (Development and Young Adult), the Philadelphia Neurodevelopmental Cohort, the Queensland Twin Adolescent Brain Project, and the Chinese Human Connectome Project; and phenotypes: age, body mass index, matrix reasoning, working memory, attention problems, anxiety/depression symptoms and relational processing. High effect size predictions achieved adequate power with training and external sample sizes of a few hundred individuals, whereas low and medium effect size predictions required hundreds to thousands of training and external samples. In addition, most previous external validation studies used sample sizes prone to low power, and theoretical power curves should be adjusted for the training sample size. Furthermore, model performance in internal validation often informed subsequent external validation performance (Pearson's r difference <0.2), particularly for well-harmonized datasets. These results could help decide how to power future external validation studies.

Harnessing the frontal aslant tract's structure to assess its involvement in cognitive functions: new insights from 7-T diffusion imaging

The first therapeutical goal followed by neurooncological surgeons dealing with prefrontal gliomas is attempting supramarginal tumor resection preserving relevant neurological function. Therefore, advanced knowledge of the frontal aslant tract (FAT) functional neuroanatomy in high-order cognitive domains beyond language and speech processing would help refine neurosurgeries, predicting possible relevant cognitive adverse events and maximizing the surgical efficacy. To this aim we performed the recently developed correlational tractography analyses to evaluate the possible relationship between FAT's microstructural properties and cognitive functions in 27 healthy subjects having ultra-high-field (7-Tesla) diffusion MRI. We independently assessed FAT segments innervating the dorsolateral prefrontal cortices (dlPFC-FAT) and the supplementary motor area (SMA-FAT). FAT microstructural robustness, measured by the tract's quantitative anisotropy (QA), was associated with a better performance in episodic memory, visuospatial orientation, cognitive processing speed and fluid intelligence but not sustained selective attention tests. Overall, the percentual tract volume showing an association between QA-index and improved cognitive scores (pQACV) was higher in the SMA-FAT compared to the dlPFC-FAT segment. This effect was right-lateralized for verbal episodic memory and fluid intelligence and bilateralized for visuospatial orientation and cognitive processing speed. Our results provide novel evidence for a functional specialization of the FAT beyond the known in language and speech processing, particularly its involvement in several higher-order cognitive domains. In light of these findings, further research should be encouraged to focus on neurocognitive deficits and their impact on patient outcomes after FAT damage, especially in the context of glioma surgery.

Corticospinal premotor fibers facilitate complex motor control after stroke

OBJECTIVE

The corticospinal tract (CST) is considered the most important motor output pathway comprising fibers from the primary motor cortex (M1) and various premotor areas. Damage to its descending fibers after stroke commonly leads to motor impairment. While premotor areas are thought to critically support motor recovery after stroke, the functional role of their corticospinal output for different aspects of post-stroke motor control remains poorly understood.

METHODS

We assessed the differential role of CST fibers originating from premotor areas and M1 in the control of basal (single-joint muscle synergies and strength) and complex motor control (involving inter-joint coordination and visuomotor integration) using a novel diffusion imaging approach in chronic stroke patients.

RESULTS

While M1 sub-tract anisotropy was positively correlated with basal and complex motor skills, anisotropy of PMd, PMv, and SMA sub-tracts was exclusively associated with complex motor tasks. Interestingly, patients featuring persistent motor deficits showed an additional positive association between premotor sub-tract integrity and basal motor control.

INTERPRETATION

While descending M1 output seems to be a prerequisite for any form of upper limb movements, complex motor skills critically depend on output from premotor areas after stroke. The additional involvement of premotor tracts in basal motor control in patients with persistent deficits emphasizes their compensatory capacity in post-stroke motor control. In summary, our findings highlight the pivotal role of descending corticospinal output from premotor areas for motor control after stroke, which thus serve as prime candidates for future interventions to amplify motor recovery.

Connectivity of the Piriform Cortex and its Implications in Temporal Lobe Epilepsy

Background

The piriform cortex has been implicated in the initiation, spread and termination of epileptic seizures. This understanding has extended to surgical management of epilepsy, where it has been shown that resection or ablation of the piriform cortex can result in better outcomes. How and why the piriform cortex may play such a crucial role in seizure networks is not well understood. To answer these questions, we investigated the functional and structural connectivity of the piriform cortex in both healthy controls and temporal lobe epilepsy (TLE) patients.

Methods

We studied a retrospective cohort of 55 drug-resistant unilateral TLE patients and 26 healthy controls who received structural and functional neuroimaging. Using seed-to-voxel connectivity we compared the normative whole-brain connectivity of the piriform to that of the hippocampus, a region commonly involved in epilepsy, to understand the differential contribution of the piriform to the epileptogenic network. We subsequently measured the inter-piriform coupling (IPC) to quantify similarities in the inter-hemispheric cortical functional connectivity profile between the two piriform cortices. We related differences in IPC in TLE back to aberrations in normative piriform connectivity, whole brain functional properties, and structural connectivity.

Results

We find that relative to the hippocampus, the piriform is functionally connected to the anterior insula and the rest of the salience ventral attention network (SAN). We also find that low IPC is a sensitive metric of poor surgical outcome (sensitivity: 85.71%, 95% CI: [19.12%, 99.64%]); and differences in IPC within TLE were related to disconnectivity and hyperconnectivity to the anterior insula and the SAN. More globally, we find that low IPC is associated with whole-brain functional and structural segregation, marked by decreased functional small-worldness and fractional anisotropy.

Conclusions

Our study presents novel insights into the functional and structural neural network alterations associated with this structure, laying the foundation for future work to carefully consider its connectivity during the presurgical management of epilepsy.

A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations

The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool in assessing white matter (WM) connectivity and brain tissue microstructure across different populations. However, a comprehensive investigation into WM fiber tracts between Eastern and Western populations is challenged due to the lack of a cross-population WM atlas and the large site-specific variability of dMRI data. This study presents a dMRI tractography atlas, namely the East-West WM Atlas, for concurrent WM mapping between Eastern and Western populations and creates a large, harmonized dMRI dataset (n=306) based on the Human Connectome Project and the Chinese Human Connectome Project. The curated WM atlas, as well as subject-specific data including the harmonized dMRI data, the whole brain tractography data, and parcellated WM fiber tracts and their diffusion measures, are publicly released. This resource is a valuable addition to facilitating the exploration of brain commonalities and differences across diverse cultural backgrounds.

Diffusion spectrum imaging in patients with idiopathic normal pressure hydrocephalus: correlation with ventricular enlargement

BACKGROUND

To investigate the association between white matter changes and ventricular expansion in idiopathic normal pressure hydrocephalus (iNPH) based on diffusion spectrum imaging (DSI).

METHODS

We included 32 patients with iNPH who underwent DSI using a 3T MRI scanner. The lateral ventricles were manually segmented, and ventricular volumes were measured. Two methods were utilised in the study: manual region-of-interest (ROI) delineation and tract diffusion profile analysis. General fractional anisotropy (GFA) and fractional anisotropy (FA) were extracted in different white matter regions, including the bilateral internal capsule (anterior and posterior limbs) and corpus callosum (body, genu, and splenium) with manual ROI delineation. The 18 main tracts in the brain of each patient were extracted; the diffusion metrics of 100 equidistant nodes on each fibre were calculated, and Spearman's correlation coefficient was used to determine the correlation between diffusion measures and ventricular volume of iNPH patients.

RESULTS

The GFA and FA of all ROI showed no significant correlation with lateral ventricular volume. However, in the tract diffusion profile analysis, lateral ventricular volume was positively correlated with part of the cingulum bundle, left corticospinal tract, and bilateral thalamic radiation posterior, whereas it was negatively correlated with the bilateral cingulum parahippocampal (all p < 0.05).

CONCLUSIONS

The effect of ventricular enlargement in iNPH on some white matter fibre tracts around the ventricles was limited and polarizing, and most white matter fibre tract integrity changes were not associated with ventricular enlargement; this reflects that multiple pathological mechanisms may have been combined to cause white matter alterations in iNPH.

Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients

Computational whole-brain models describe the resting activity of each brain region based on a local model, inter-regional functional interactions, and a structural connectome that specifies the strength of inter-regional connections. Strokes damage the healthy structural connectome that forms the backbone of these models and produce large alterations in inter-regional functional interactions. These interactions are typically measured by correlating the time series of the activity between two brain regions in a process, called resting functional connectivity. We show that adding information about the structural disconnections produced by a patient's lesion to a whole-brain model previously trained on structural and functional data from a large cohort of healthy subjects enables the prediction of the resting functional connectivity of the patient and fits the model directly to the patient's data (Pearson correlation = 0.37; mean square error = 0.005). Furthermore, the model dynamics reproduce functional connectivity-based measures that are typically abnormal in stroke patients and measures that specifically isolate these abnormalities. Therefore, although whole-brain models typically involve a large number of free parameters, the results show that, even after fixing those parameters, the model reproduces results from a population very different than that on which the model was trained. In addition to validating the model, these results show that the model mechanistically captures the relationships between the anatomical structure and the functional activity of the human brain.

White matter alterations predict outcomes of comprehensive behavioral intervention for tics in children with Tourette syndrome: A diffusion MRI study

AIM

Tourette syndrome (TS) is a neurodevelopmental disorder that cause sudden uncontrolled rapid and repeated vocal sounds or movements called tics. Herein, diffusion magnetic resonance imaging (dMRI) connectometry was implemented to evaluate the white matter connectivity differences among TS patients.

METHODS

A total of 63 TS and 77 typically developed (TD) individuals were enrolled in the present study. dMRI connectometry was utilized to identify differences in connectivity patterns of white matter tracts in TS patients based on quantitative anisotropy (QA). QA was compared between TS and TD patients and correlated with severity scores such as Yale Global Tic Severity Scale (YGTSS) and Premonitory Urge for Tics Scale (PUTS).

RESULTS

Higher white matter connectivity of corpus callosum and bilateral cingulum as well as lower connectivity of corticothalamic and corticostriatal pathways were evident in TS relative to TD. The baseline YGTSS motor, YGTSS total, and PUTS were negatively correlated with corticostriatal pathway, corticothalamic pathway, and bilateral cingulum integrity, respectively. The changes in tic severity scores were also positively correlated with alterations in the white matter integrity of these brain regions following behavioral therapy.

CONCLUSION

Patients with TS have several abnormalities in their white matter microstructure particularly in the cortico-striato-thalamo-cortical (CSTC) circuit, correlated with the severity of the disease. Besides, the post-behavioral therapy changes in the white matter integrity of these regions are demonstrated as response predictors.

Population Atlas Analysis of Emerging Brain Structural Connections in the Human Fetus

BACKGROUND

A lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences.

PURPOSE

To evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI).

STUDY TYPE

Retrospective.

POPULATION

Publicly available diffusion atlases, based on 60 healthy women (age 18-45 years) with normal prenatal care, from 23 and 35 weeks of gestation.

FIELD STRENGTH/SEQUENCE

3.0 Tesla/DTI acquired with diffusion-weighted echo planar imaging (EPI).

ASSESSMENT

We performed whole-brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small-worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality.

STATISTICAL TESTS

Linear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. The t-tests were used to assess SW. P-values were corrected using Holm-Bonferroni method. A corrected P-value <0.05 was considered statistically significant.

RESULTS

Network analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32-7.37), LE (5.43%/week, 95% CI 3.63-7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes.

DATA CONCLUSION

Extensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning

Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and clinical research. However, it is challenging to segment SWM due to the short adjacent gyri connection in a U-shaped pattern. In this work, we propose an Anatomically-guided Superficial Fiber Segmentation (Anat-SFSeg) framework to improve the performance on SWM segmentation. The framework consists of a unique fiber anatomical descriptor (named FiberAnatMap) and a deep learning network based on point-cloud data. The spatial coordinates of fibers represented as point clouds, as well as the anatomical features at both the individual and group levels, are fed into a neural network. The network is trained on Human Connectome Project (HCP) datasets and tested on the subjects with a range of cognitive impairment levels. One new metric named fiber anatomical region proportion (FARP), quantifies the ratio of fibers in the defined brain regions and enables the comparison with other methods. Another metric named anatomical region fiber count (ARFC), represents the average fiber number in each cluster for the assessment of inter-subject differences. The experimental results demonstrate that Anat-SFSeg achieves the highest accuracy on HCP datasets and exhibits great generalization on clinical datasets. Diffusion tensor metrics and ARFC show disorder severity associated alterations in patients with Alzheimer's disease (AD) and mild cognitive impairments (MCI). Correlations with cognitive grades show that these metrics are potential neuroimaging biomarkers for AD. Furthermore, Anat-SFSeg could be utilized to explore other neurodegenerative, neurodevelopmental or psychiatric disorders.

Mapping the interplay of atrial fibrillation, brain structure, and cognitive dysfunction

INTRODUCTION

Atrial fibrillation (AF) is associated with an elevated risk of cognitive impairment and dementia. Understanding the cognitive sequelae and brain structural changes associated with AF is vital for addressing ensuing health care needs.

METHODS AND RESULTS

We examined 1335 stroke-free individuals with AF and 2683 matched controls using neuropsychological assessments and multimodal neuroimaging. The analysis revealed that individuals with AF exhibited deficits in executive function, processing speed, and reasoning, accompanied by reduced cortical thickness, elevated extracellular free-water content, and widespread white matter abnormalities, indicative of small vessel pathology. Notably, brain structural differences statistically mediated the relationship between AF and cognitive performance.

DISCUSSION

Integrating a comprehensive analysis approach with extensive clinical and magnetic resonance imaging data, our study highlights small vessel pathology as a possible unifying link among AF, cognitive decline, and abnormal brain structure. These insights can inform diagnostic approaches and motivate the ongoing implementation of effective therapeutic strategies. Highlights We investigated neuropsychological and multimodal neuroimaging data of 1335 individuals with atrial fibrillation (AF) and 2683 matched controls. Our analysis revealed AF-associated deficits in cognitive domains of attention, executive function, processing speed, and reasoning. Cognitive deficits in the AF group were accompanied by structural brain alterations including reduced cortical thickness and gray matter volume, alongside increased extracellular free-water content as well as widespread differences of white matter integrity. Structural brain changes statistically mediated the link between AF and cognitive performance, emphasizing the potential of structural imaging markers as a diagnostic tool in AF-related cognitive decline.

Presurgical structural imaging and clinical outcome in combined bed nucleus of the stria terminalis-nucleus accumbens deep brain stimulation for treatment-resistant depression

Background

Structural imaging holds great potential for precise targeting and stimulation for deep brain stimulation (DBS). The anatomical information it provides may serve as potential biomarkers for predicting the efficacy of DBS in treatment-resistant depression (TRD).

Aims

The primary aim is to identify preoperative imaging biomarkers that correlate with the efficacy of DBS in patients with TRD.

Methods

Preoperative imaging parameters were estimated and correlated with the 6-month clinical outcome of patients with TRD receiving combined bed nucleus of the stria terminalis (BNST)-nucleus accumbens (NAc) DBS. White matter (WM) properties were extracted and compared between the response/non-response and remission/non-remission groups. Structural connectome was constructed and analysed using graph theory. Distances of the volume of activated tissue (VAT) to the main modulating tracts were also estimated to evaluate the correlations.

Results

Differences in fibre bundle properties of tracts, including superior thalamic radiation and reticulospinal tract, were observed between the remission and non-remission groups. Distance of the centre of the VAT to tracts connecting the ventral tegmental area and the anterior limb of internal capsule on the left side varied between the remission and non-remission groups (p=0.010, t=3.07). The normalised clustering coefficient (γ) and the small-world property (σ) in graph analysis correlated with the symptom improvement after the correction of age.

Conclusions

Presurgical structural alterations in WM tracts connecting the frontal area with subcortical regions, as well as the distance of the VAT to the modulating tracts, may influence the clinical outcome of BNST-NAc DBS. These findings provide potential imaging biomarkers for the DBS treatment for patients with TRD.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is an immune-mediated neurological disorder, and up to 50% of patients experience depression. We investigated how white matter network disruption is related to depression in MS.

METHODS

Using electronic health records, 380 participants with MS were identified. Depressed individuals (MS+Depression group; n = 232) included persons who had an ICD-10 depression diagnosis, had a prescription for antidepressant medication, or screened positive via Patient Health Questionnaire (PHQ)-2 or PHQ-9. Age- and sex-matched nondepressed individuals with MS (MS-Depression group; n = 148) included persons who had no prior depression diagnosis, had no psychiatric medication prescriptions, and were asymptomatic on PHQ-2 or PHQ-9. Research-quality 3T structural magnetic resonance imaging was obtained as part of routine care. We first evaluated whether lesions were preferentially located within the depression network compared with other brain regions. Next, we examined if MS+Depression patients had greater lesion burden and if this was driven by lesions in the depression network. Primary outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain.

RESULTS

MS lesions preferentially affected fascicles within versus outside the depression network (β = 0.09, 95% CI = 0.08 to 0.10, p < .001). MS+Depression patients had more lesion burden (β = 0.06, 95% CI = 0.01 to 0.10, p = .015); this was driven by lesions within the depression network (β = 0.02, 95% CI = 0.003 to 0.040, p = .020).

CONCLUSIONS

We demonstrated that lesion location and burden may contribute to depression comorbidity in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression patients had more disease than MS-Depression patients, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways

Neuroimaging studies have consistently demonstrated concurrent activation of the human precuneus and temporal pole (TP), both during resting-state conditions and various higher-order cognitive functions. However, the precise underlying structural connectivity between these brain regions remains uncertain despite significant advancements in neuroscience research. In this study, we investigated the connectivity of the precuneus and TP by employing parcellation-based fiber micro-dissections in human brains and fiber tractography techniques in a sample of 1065 human subjects and a sample of 41 rhesus macaques. Our results demonstrate the connectivity between the posterior precuneus area POS2 and the areas 35, 36, and TG of the TP via the fifth subcomponent of the cingulum (CB-V) also known as parahippocampal cingulum. This finding contributes to our understanding of the connections within the posteromedial cortices, facilitating a more comprehensive integration of anatomy and function in both normal and pathological brain processes. PRACTITIONER POINTS: Our investigation delves into the intricate architecture and connectivity patterns of subregions within the precuneus and temporal pole, filling a crucial gap in our knowledge. We revealed a direct axonal connection between the posterior precuneus (POS2) and specific areas (35, 35, and TG) of the temporal pole. The direct connections are part of the CB-V pathway and exhibit a significant association with the cingulum, SRF, forceps major, and ILF. Population-based human tractography and rhesus macaque fiber tractography showed consistent results that support micro-dissection outcomes.

Predicting conversion from mild cognitive impairment to Alzheimer's disease: a multimodal approach

Successively predicting whether mild cognitive impairment patients will progress to Alzheimer's disease is of significant clinical relevance. This ability may provide information that can be leveraged by emerging intervention approaches and thus mitigate some of the negative effects of the disease. Neuroimaging biomarkers have gained some attention in recent years and may be useful in predicting the conversion of mild cognitive impairment to Alzheimer's disease. We implemented a novel multi-modal approach that allowed us to evaluate the potential of different imaging modalities, both alone and in different degrees of combinations, in predicting the conversion to Alzheimer's disease of mild cognitive impairment patients. We applied this approach to the imaging data from the Alzheimer's Disease Neuroimaging Initiative that is a multi-modal imaging dataset comprised of MRI, Fluorodeoxyglucose PET, Florbetapir PET and diffusion tensor imaging. We included a total of 480 mild cognitive impairment patients that were split into two groups: converted and stable. Imaging data were segmented into atlas-based regions of interest, from which relevant features were extracted for the different imaging modalities and used to construct machine-learning models to classify mild cognitive impairment patients into converted or stable, using each of the different imaging modalities independently. The models were then combined, using a simple weight fusion ensemble strategy, to evaluate the complementarity of different imaging modalities and their contribution to the prediction accuracy of the models. The single-modality findings revealed that the model, utilizing features extracted from Florbetapir PET, demonstrated the highest performance with a balanced accuracy of 83.51%. Concerning multi-modality models, not all combinations enhanced mild cognitive impairment conversion prediction. Notably, the combination of MRI with Fluorodeoxyglucose PET emerged as the most promising, exhibiting an overall improvement in predictive capabilities, achieving a balanced accuracy of 78.43%. This indicates synergy and complementarity between the two imaging modalities in predicting mild cognitive impairment conversion. These findings suggest that β-amyloid accumulation provides robust predictive capabilities, while the combination of multiple imaging modalities has the potential to surpass certain single-modality approaches. Exploring modality-specific biomarkers, we identified the brainstem as a sensitive biomarker for both MRI and Fluorodeoxyglucose PET modalities, implicating its involvement in early Alzheimer's pathology. Notably, the corpus callosum and adjacent cortical regions emerged as potential biomarkers, warranting further study into their role in the early stages of Alzheimer's disease.

A sensorimotor-association axis of thalamocortical connection development

Human cortical development follows a sensorimotor-to-association sequence during childhood and adolescence1-6. The brain's capacity to enact this sequence over decades indicates that it relies on intrinsic mechanisms to regulate inter-regional differences in the timing of cortical maturation, yet regulators of human developmental chronology are not well understood. Given evidence from animal models that thalamic axons modulate windows of cortical plasticity7-12, here we evaluate the overarching hypothesis that structural connections between the thalamus and cortex help to coordinate cortical maturational heterochronicity during youth. We first introduce, cortically annotate, and anatomically validate a new atlas of human thalamocortical connections using diffusion tractography. By applying this atlas to three independent youth datasets (ages 8-23 years; total N = 2,676), we reproducibly demonstrate that thalamocortical connections develop along a maturational gradient that aligns with the cortex's sensorimotor-association axis. Associative cortical regions with thalamic connections that take longest to mature exhibit protracted expression of neurochemical, structural, and functional markers indicative of higher circuit plasticity as well as heightened environmental sensitivity. This work highlights a central role for the thalamus in the orchestration of hierarchically organized and environmentally sensitive windows of cortical developmental malleability.

Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics

Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines' suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline's performance across criteria and datasets, to inform future best practices in functional connectomics.

Cortical and white matter substrates supporting visuospatial working memory

OBJECTIVE

In tasks involving new visuospatial information, we rely on working memory, supported by a distributed brain network. We investigated the dynamic interplay between brain regions, including cortical and white matter structures, to understand how neural interactions change with different memory loads and trials, and their subsequent impact on working memory performance.

METHODS

Patients undertook a task of immediate spatial recall during intracranial EEG monitoring. We charted the dynamics of cortical high-gamma activity and associated functional connectivity modulations in white matter tracts.

RESULTS

Elevated memory loads were linked to enhanced functional connectivity via occipital longitudinal tracts, yet decreased through arcuate, uncinate, and superior-longitudinal fasciculi. As task familiarity grew, there was increased high-gamma activity in the posterior inferior-frontal gyrus (pIFG) and diminished functional connectivity across a network encompassing frontal, parietal, and temporal lobes. Early pIFG high-gamma activity was predictive of successful recall. Including this metric in a logistic regression model yielded an accuracy of 0.76.

CONCLUSIONS

Optimizing visuospatial working memory through practice is tied to early pIFG activation and decreased dependence on irrelevant neural pathways.

SIGNIFICANCE

This study expands our knowledge of human adaptation for visuospatial working memory, showing the spatiotemporal dynamics of cortical network modulations through white matter tracts.

White matter microstructure organization across the transition to fatherhood

The transition to parenthood remains an understudied window of potential neuroplasticity in the adult brain. White matter microstructural (WMM) organization, which reflects structural connectivity in the brain, has shown plasticity across the lifespan. No studies have examined how WMM organization changes from the prenatal to postpartum period in men becoming fathers. This study investigates WMM organization in men transitioning to first-time fatherhood. We performed diffusion-weighted imaging to identify differences in WMM organization, as indexed by fractional anisotropy (FA). We also investigated whether FA changes were associated with fathers' postpartum mental health. Associations between mental health and WMM organization have not been rarely examined in parents, who may be vulnerable to mental health problems. Fathers exhibited reduced FA at the whole-brain level, especially in the cingulum, a tract associated with emotional regulation. Fathers also displayed reduced FA in the corpus callosum, especially in the forceps minor, which is implicated in cognitive functioning. Postpartum depressive symptoms were linked with increases and decreases in FA, but FA was not correlated with perceived or parenting stress. Findings provide novel insight into fathers' WMM organization during the transition to parenthood and suggest postpartum depression may be linked with fathers' neuroplasticity during the transition to parenthood.

Differential tractography and whole brain connectometry in primary motor area gliomas resection: A feasibility study

OBJECTIVE

Establish the evolution of the connectome before and after resection of motor area glioma using a comparison of connectome maps and high-definition differential tractography (DifT).

METHODS

DifT was done using normalized quantitative anisotropy (NQA) with DSI Studio. The quantitative analysis involved obtaining mean NQA and fractional anisotropy (FA) values for the disrupted pathways tracing the corticospinal tract (CST), and white fiber network changes over time.

RESULTS

We described the baseline tractography, DifT, and white matter network changes from two patients who underwent resection of an oligodendroglioma (Case 1) and an IDH mutant astrocytoma, grade 4 (Case 2).

CASE 1

There was a slight decrease in the diffusion signal of the compromised CST in the immediate postop. The NQA and FA values increased at the 1-year follow-up (0.18 vs. 0.32 and 0.35 vs. 0.44, respectively).

CASE 2

There was an important decrease in the immediate postop, followed by an increase in the follow-up. In the 1-year follow-up, the patient presented with radiation necrosis and tumor recurrence, increasing NQA from 0.18 in the preop to 0.29. Fiber network analysis: whole-brain connectome comparison demonstrated no significant changes in the immediate postop. However, in the 1-year follow up there was a notorious reorganization of the fibers in both cases, showing the decreased density of connections.

CONCLUSIONS

Connectome studies and DifT constitute new potential tools to predict early reorganization changes in a patient's networks, showing the brain plasticity capacity, and helping to establish timelines for the progression of the tumor and treatment-induced changes.

Multimodal cross-examination of progressive apraxia of speech by diffusion tensor imaging-based tractography and Tau-PET scans

Progressive apraxia of speech (PAOS) is a 4R tauopathy characterized by difficulties with motor speech planning. Neurodegeneration in PAOS targets the premotor cortex, particularly the supplementary motor area (SMA), with degeneration of white matter (WM) tracts connecting premotor and motor cortices and Broca's area observed on diffusion tensor imaging (DTI). We aimed to assess flortaucipir uptake across speech-language-related WM tracts identified using DTI tractography in PAOS. Twenty-two patients with PAOS and 26 matched healthy controls were recruited by the Neurodegenerative Research Group (NRG) and underwent MRI and flortaucipir-PET. The patient population included patients with primary progressive apraxia of speech (PPAOS) and non-fluent variant/agrammatic primary progressive aphasia (agPPA). Flortaucipir PET scans and DTI were coregistered using rigid registration with a mutual information cost function in subject space. Alignments between DTI and flortaucipir PET were inspected in all cases. Whole-brain tractography was calculated using deterministic algorithms by a tractography reconstruction tool (DSI-studio) and specific tracts were identified using an automatic fiber tracking atlas-based method. Fractional anisotropy (FA) and flortaucipir standardized uptake value ratios (SUVRs) were averaged across the frontal aslant tract, arcuate fasciculi, inferior frontal-occipital fasciculus, inferior and middle longitudinal fasciculi, as well as the SMA commissural fibers. Reduced FA (p < .0001) and elevated flortaucipir SUVR (p = .0012) were observed in PAOS cases compared to controls across all combined WM tracts. For flortaucipir SUVR, the greatest differentiation of PAOS from controls was achieved with the SMA commissural fibers (area under the receiver operator characteristic curve [AUROC] = 0.83), followed by the left arcuate fasciculus (AUROC = 0.75) and left frontal aslant tract (AUROC = 0.71). Our findings demonstrate that flortaucipir uptake is increased across WM tracts related to speech/language difficulties in PAOS.

Improving the Visualization of Superior Longitudinal Fascicule-2 and Superior Longitudinal Fascicule -3 Using Photoshop Filters

BACKGROUND AND OBJECTIVES

Several studies are currently exploring the anatomical origins of superior longitudinal fascicule (SLF) 2 and SLF-3, which are components of the frontoparietal network. This study aimed to achieve optimum visualization of the anatomical corridors of these fibers using Photoshop filters.

METHODS

Four postmortem brain hemispheres were dissected in accordance with the method proposed by Klingler and Ludwig. Dissections were performed under a surgical microscope (Carl Zeiss AG, Oberkochen, Germany) at 4× and 40× magnification. All dissections were documented at each stage using a professional digital camera (Canon EOS 600D) with a macro 100 mm lens (Canon), ring-flash attachment (Canon), and professional tripod (Manfrotto 808 C4). We aimed to improve the visual quality of the images by avoiding monotone using various the features and filters in Photoshop.

RESULTS

SLF-2 originates from the angular gyrus (Brodmann area [BA] 39) in the right hemisphere and has been observed to project fibers from BA7 and BA19 and toward BA8, 9, 10, and 46. Further, these fibers traverse from the depths of BA40, 2, 3, 1, and 6 as they progress. SLF-2 also projects fibers from the supramarginal gyrus in the left hemisphere. SLF-3 lies between the supramarginal gyrus and the inferior frontal lobe in both the right and left hemispheres.

CONCLUSIONS

The visual descriptions of the dissections were enriched after using Photoshop to avoid monotony. Increasing the visual quality with Photoshop features enable us to gain a better understanding of these pathways. Additionally, it facilitates the comprehension of the symptoms associated with pathology. We hope these results will further aid in reducing the occurrence of postoperative complications.

The effect of propofol on effective brain networks

OBJECTIVE

We compared the effective networks derived from Single Pulse Electrical Stimulation (SPES) in intracranial electrocorticography (ECoG) of awake epilepsy patients and while under general propofol-anesthesia to investigate the effect of propofol on these brain networks.

METHODS

We included nine patients who underwent ECoG for epilepsy surgery evaluation. We performed SPES when the patient was awake (SPES-clinical) and repeated this under propofol-anesthesia during the surgery in which the ECoG grids were removed (SPES-propofol). We detected the cortico-cortical evoked potentials (CCEPs) with an automatic detector. We constructed two effective networks derived from SPES-clinical and SPES-propofol. We compared three network measures (indegree, outdegree and betweenness centrality), the N1-peak-latency and amplitude of CCEPs between the two effective networks.

RESULTS

Fewer CCEPs were observed during SPES-propofol (median: 6.0, range: 0-29) compared to SPES-clinical (median: 10.0, range: 0-36). We found a significant correlation for the indegree, outdegree and betweenness centrality between SPES-clinical and SPES-propofol (respectively rs = 0.77, rs = 0.70, rs = 0.55, p < 0.001). The median N1-peak-latency increased from 22.0 ms during SPES-clinical to 26.4 ms during SPES-propofol.

CONCLUSIONS

Our findings suggest that the number of effective network connections decreases, but network measures are only marginally affected.

SIGNIFICANCE

The primary network topology is preserved under propofol.

brainlife.io: a decentralized and open-source cloud platform to support neuroscience research

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.