Virtual Lesion Research Articles

Impaired motor-to-sensory transformation mediates auditory hallucinations.

Distinguishing reality from hallucinations requires efficient monitoring of agency. It has been hypothesized that a copy of motor signals, termed efference copy (EC) or corollary discharge (CD), suppresses sensory responses to yield a sense of agency; impairment of the inhibitory function leads to hallucinations. However, how can the sole absence of inhibition yield positive symptoms of hallucinations? We hypothesize that selective impairments in functionally distinct signals of CD and EC during motor-to-sensory transformation cause the positive symptoms of hallucinations. In an electroencephalography (EEG) experiment with a delayed articulation paradigm in schizophrenic patients with (AVHs) and without auditory verbal hallucinations (non-AVHs), we found that preparing to speak without knowing the contents (general preparation) did not suppress auditory responses in both patient groups, suggesting the absent of inhibitory function of CD. Whereas, preparing to speak a syllable (specific preparation) enhanced the auditory responses to the prepared syllable in non-AVHs, whereas AVHs showed enhancement in responses to unprepared syllables, opposite to the observations in the normal population, suggesting that the enhancement function of EC is not precise in AVHs. A computational model with a virtual lesion of an inhibitory inter-neuron and disproportional sensitization of auditory cortices fitted the empirical data and further quantified the distinct impairments in motor-to-sensory transformation in AVHs. These results suggest that "broken" CD plus "noisy" EC causes erroneous monitoring of the imprecise generation of internal auditory representation and yields auditory hallucinations. Specific impairments in functional granularity of motor-to-sensory transformation mediate positivity symptoms of agency abnormality in mental disorders.

Revolutionizing Skin Cancer Triage: The Role of Patient-Initiated Teledermoscopy in Remote Diagnosis.

Teledermatology, defined as the use of remote imaging technologies to provide dermatologic healthcare services to individuals in a distant setting, has grown considerably in popularity since its widespread implementation during the COVID-19 pandemic. Teledermoscopy employs a smartphone dermatoscope attachment paired with a smartphone camera to visualize colors and microstructures within the epidermis and superficial dermis that cannot be seen with the naked eye ABCD criteria alone. Our retrospective observational cohort and case-control study evaluated the utility of loaning a smartphone dermatoscope attachment to patients for remote triage of self-selected lesions of concern for skin cancer. The primary outcome was the number (percentage) of in-person follow-up visits required for patients who submitted lesion images, either with or without accompanying dermoscopic images. A medical record review was conducted on all Oregon Health & Science University Department of Dermatology spot check image submissions utilizing the smartphone dermatoscopes between August 2020 and August 2022. De-identified dermoscopic images of lesions that included corresponding non-dermoscopic clinical images in their submission (n = 70) were independently reviewed by a blinded expert dermoscopist. The expert used standard clinical algorithms (ABCD criteria for clinical images; dermoscopy three-point checklist for dermoscopic images) to determine whether the imaged lesion should be converted to an in-person visit for further evaluation and consideration for biopsy. Of the 70 lesions submitted with corresponding clinical and dermoscopy images, 60 met the criteria for in-person evaluation from clinical (non-dermoscopic) image review compared to 28 meeting the criteria for in-person evaluation from dermoscopic images of the same lesion. Thus, a 53% reduction in conversion to an in-person consultation with the addition of smartphone dermatoscope images in virtual lesion triage was observed (p < 0.001, McNemar's Test). Implementing patient-led teledermoscopy may reduce the frequency of in-person visits for benign lesions and consequently improve access to in-person dermatology consultations for patients with concerning and possibly malignant lesions.

Exploratory investigation of virtual lesions in gastrointestinal endoscopy using a novel phase‐shift method for three‐dimensional shape measurement

AbstractAccurate measurement of the size of lesions or distances between any two points during endoscopic examination of the gastrointestinal tract is difficult owing to the fisheye lens used in endoscopy. To overcome this issue, we developed a phase‐shift method to measure three‐dimensional (3D) data on a curved surface, which we present herein. Our system allows the creation of 3D shapes on a curved surface by the phase‐shift method using a stripe pattern projected from a small projecting device to an object. For evaluation, 88 measurement points were inserted in porcine stomach tissue, attached to a half‐pipe jig, with an inner radius of 21 mm. The accuracy and precision of the measurement data for our shape measurement system were compared with the data obtained using an Olympus STM6 measurement microscope. The accuracy of the path length of a simulated protruded lesion was evaluated using a plaster model of the curved stomach and graph paper. The difference in height measures between the measurement microscope and measurement system data was 0.24 mm for the 88 measurement points on the curved surface of the porcine stomach. The error in the path length measurement for a lesion on an underlying curved surface was &lt;1% for a 10‐mm lesion. The software was developed for the automated calculation of the major and minor diameters of each lesion. The accuracy of our measurement system could improve the accuracy of determining the size of lesions, whether protruded or depressed, regardless of the curvature of the underlying surface.

Endoscopic closure of large gastric defects with a novel through-the-scope closing device in a porcine model (with videos)

Background and aimAfter endoscopic full-thickness resection (EFTR), defects require a reliable and sustained closure. We present a novel, through-the-scope "bow-tie" (TTS-BT) closing device enabling direct defect closure without scope withdrawal. This preclinical study aimed to evaluate the feasibility and safety of this device for large defect closure after EFTR in a porcine model. MethodsExposed EFTR was performed for virtual lesions > 2 cm in the stomach of twelvepigs. Subsequently, TTS-BT closing devices were used for defect closure. Conventional metal clips were used to close any remaining defects. Gastroscopy was performed for 8 weeks to examine the wound sites and the pigs were subsequently sacrificed. After sacrificing the pigs, the wound healing was histologically verified by hematoxylin-eosin (HE) staining. The primary outcome was a successful closure rate, while the secondary outcomes were complete healing rate, closure time, and incidence of adverse events. ResultsThe median long and short diameters of perforations were 4.0 (3.0–6.0) cm and 3.0 (2.0–4.0) cm, respectively. Defect closure using novel TTS-BT closure devices and conventional metal clips was successfully performed in all pigs. Complete healing was achieved in the defects of 12 pigs. The median closure time was 13 (9–38) minutes. No serious adverse events occurred during the 8-week follow-up. ConclusionsThe novel TTS-BT closure device is feasible and safe for closing large gastric perforations and could be a promising tool for clinical practice.

Impact of white matter hyperintensities on structural connectivity and cognition in cognitively intact ADNI participants

We used indirect brain mapping with virtual lesion tractography to test the hypothesis that the extent of white matter tract disconnection due to white matter hyperintensities (WMH) is associated with corresponding tract-specific cognitive performance decrements. To estimate tract disconnection, WMH masks were extracted from FLAIR MRI data of 481 cognitively intact participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and used as regions of avoidance for fiber tracking in diffusion MRI data from 50 healthy young participants from the Human Connectome Project. Estimated tract disconnection in the right inferior fronto-occipital fasciculus, right frontal aslant tract, and right superior longitudinal fasciculus mediated the effects of WMH volume on executive function. Estimated tract disconnection in the left uncinate fasciculus mediated the effects of WMH volume on memory and in the right frontal aslant tract on language. In a subset of ADNI control participants with amyloid data, positive status increased the probability of periventricular WMH and moderated the relationship between WMH burden and tract disconnection in executive function performance.

Virtual lesions in MEG reveal increasing vulnerability of the language network from early childhood through adolescence

In childhood, language outcomes following brain injury are inversely related to age. Neuroimaging findings suggest that extensive representation and/or topological redundancy may confer the pediatric advantage. Here, we assess whole brain and language network resilience using in silico attacks, for 85 children participating in a magnetoencephalography (MEG) study. Nodes are targeted based on eigenvector centrality, betweenness centrality, or at random. The size of each connected component is assessed after iterated node removal; the percolation point, or moment of dis-integration, is defined as the first instance where the second largest component peaks in size. To overcome known effects of fixed thresholding on subsequent graph and resilience analyses, we study percolation across all possible network densities, within a Functional Data Analysis (FDA) framework. We observe age-related increases in vulnerability for random and betweenness centrality-based attacks for whole-brain and stories networks (adjusted-p < 0.05). Here we show that changes in topology underlie increasing language network vulnerability in development.

Neuromodulation-induced prehabilitation to leverage neuroplasticity before brain tumor surgery: a single-cohort feasibility trial protocol.

Neurosurgery for brain tumors needs to find a complex balance between the effective removal of targeted tissue and the preservation of surrounding brain areas. Neuromodulation-induced cortical prehabilitation (NICP) is a promising strategy that combines temporary inhibition of critical areas (virtual lesion) with intensive behavioral training to foster the activation of alternative brain resources. By progressively reducing the functional relevance of targeted areas, the goal is to facilitate resection with reduced risks of neurological sequelae. However, it is still unclear which modality (invasive vs. non-invasive neuromodulation) and volume of therapy (behavioral training) may be optimal in terms of feasibility and efficacy. Patients undertake between 10 and 20 daily sessions consisting of neuromodulation coupled with intensive task training, individualized based on the target site and neurological functions at risk of being compromised. The primary outcome of the proposed pilot, single-cohort trial is to investigate the feasibility and potential effectiveness of a non-invasive NICP protocol on neuroplasticity and post-surgical outcomes. Secondary outcomes investigating longitudinal changes (neuroimaging, neurophysiology, and clinical) are measured pre-NICP, post-NICP, and post-surgery. Ethics approval was obtained from the Research Ethical Committee of Fundació Unió Catalana d'Hospitals (approval number: CEI 21/65, version 1, 13/07/2021). The results of the study will be submitted to a peer-reviewed journal and presented at scientific congresses. ClinicalTrials.gov, identifier NCT05844605.

Influence of cortical inhibition on auditory efferents in humans

Auditory activity in humans is influenced by feedback networks in the brain. The final leg of this pathway originates in the brainstem and plays an important role in protecting and aiding communication in competing noise. Previous studies have used auditory and/or visual attention tasks to manipulate cortical activity when exploring its influence on the periphery via the auditory efferent system. Using subjective attention does not control for variability across individuals in attentional state, alertness, and arousal. Hence, a consensus on the relationship between cortical activity and how it influences more caudal efferent reflexes is still needed. Here we describe the first assay to non-invasively influence the human auditory cortex activity using repetitive transcranial magnetic stimulation and measure its consequence on peripheral structures using otoacoustic emissions. We hypothesized that depressing brain activity temporarily affects auditory functioning. By instigating a virtual cortical lesion in normal hearing participants, we were able to characterize the influence that the auditory cortex has on the sensory cells in the cochlea, mediated via the medial olivocochlear reflex. Our results will open avenues for further research into new diagnostic and therapeutic approaches for hearing disorders.

Disconnectome associated with progressive white matter hyperintensities in aging: a virtual lesion study.

White matter hyperintensities (WMH) are commonly seen on T2-weighted magnetic resonance imaging (MRI) in older adults and are associated with an increased risk of cognitive decline and dementia. This study aims to estimate changes in the structural connectome due to age-related WMH by using a virtual lesion approach. High-quality diffusion-weighted imaging data of 30 healthy subjects were obtained from the Human Connectome Project (HCP) database. Diffusion tractography using q-space diffeomorphic reconstruction (QSDR) and whole brain fiber tracking with 107 seed points was conducted using diffusion spectrum imaging studio and the brainnetome atlas was used to parcellate a total of 246 cortical and subcortical nodes. Previously published WMH frequency maps across age ranges (50's, 60's, 70's, and 80's) were used to generate virtual lesion masks for each decade at three lesion frequency thresholds, and these virtual lesion masks were applied as regions of avoidance (ROA) in fiber tracking to estimate connectivity changes. Connections showing significant differences in fiber density with and without ROA were identified using paired tests with False Discovery Rate (FDR) correction. Disconnections appeared first from the striatum to middle frontal gyrus (MFG) in the 50's, then from the thalamus to MFG in the 60's and extending to the superior frontal gyrus in the 70's, and ultimately including much more widespread cortical and hippocampal nodes in the 80's. Changes in the structural disconnectome due to age-related WMH can be estimated using the virtual lesion approach. The observed disconnections may contribute to the cognitive and sensorimotor deficits seen in aging.

A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Rumination is a cognitive style characterized by repetitive thoughts about one’s negative internal states and is a common symptom of depression. Previous studies have linked trait rumination to alterations in the default mode network, but predictive brain markers of rumination are lacking. Here, we adopt a predictive modeling approach to develop a neuroimaging marker of rumination based on the variance of dynamic resting-state functional connectivity and test it across 5 diverse subclinical and clinical samples (total n = 288). A whole-brain marker based on dynamic connectivity with the dorsomedial prefrontal cortex (dmPFC) emerges as generalizable across the subclinical datasets. A refined marker consisting of the most important features from a virtual lesion analysis further predicts depression scores of adults with major depressive disorder (n = 35). This study highlights the role of the dmPFC in trait rumination and provides a dynamic functional connectivity marker for rumination.

Young versus older subject diffusion magnetic resonance imaging data for virtual white matter lesion tractography.

White matter hyperintensity (WMH) lesions on T2 fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and changes in adjacent normal-appearing white matter can disrupt computerized tract reconstruction and result in inaccurate measures of structural brain connectivity. The virtual lesion approach provides an alternative strategy for estimating structural connectivity changes due to WMH. To assess the impact of using young versus older subject diffusion MRI data for virtual lesion tractography, we leveraged recently available diffusion MRI data from the Human Connectome Project (HCP) Lifespan database. Neuroimaging data from 50 healthy young (39.2 ± 1.6 years) and 46 healthy older (74.2 ± 2.5 years) subjects were obtained from the publicly available HCP-Aging database. Three WMH masks with low, moderate, and high lesion burdens were extracted from the WMH lesion frequency map of locally acquired FLAIR MRI data. Deterministic tractography was conducted to extract streamlines in 21 WM bundles with and without the WMH masks as regions of avoidance in both young and older cohorts. For intact tractography without virtual lesion masks, 7 out of 21 WM pathways showed a significantly lower number of streamlines in older subjects compared to young subjects. A decrease in streamline count with higher native lesion burden was found in corpus callosum, corticostriatal tract, and fornix pathways. Comparable percentages of affected streamlines were obtained in young and older groups with virtual lesion tractography using the three WMH lesion masks of increasing severity. We conclude that using normative diffusion MRI data from young subjects for virtual lesion tractography of WMH is, in most cases, preferable to using age-matched normative data.

Prediction of Post-stroke Motor Recovery Benefits from Measures of Sub-acute Widespread Network Damages (P12-8.002)

<h3>Objective:</h3> Developing a more accurate post-stroke motor recovery prediction model leveraging brain network connectivity measurements. <h3>Background:</h3> Following an acute ischemic stroke, some patients recover almost completely, while others barely recover. It is known that lesion volume, initial motor impairment, and cortico-spinal tract asymmetry (benchmark features) significantly impact motor changes over time. However, accurate prediction models of patients’ recovery are still missing. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Here, we built on this hypothesis to develop a more accurate post-stroke motor recovery prediction model. <h3>Design/Methods:</h3> We evaluated a dataset of 37 patients (17 women) with upper extremity motor strokes. Their impairment was assessed at 2 weeks (baseline) and 3 months after the stroke using the Fugl-Meyer-Assessment. 18 graph measures of global structural connectivity were obtained using the patients’ T2 lesion mask to virtually reproduce the lesions in 60 healthy streamline tractography connectomes. We added these indirect measures to the benchmark features, and we used a ridge regression regularization in a leave-one-out cross-validation framework to predict motor recovery at 3 months post-injury. <h3>Results:</h3> Prediction accuracy significantly increased when using brain connectivity measures (R²=0.68, 95% CI: 0.64–0.74) as compared to benchmark features alone (R²=0.38, 95% CI: 0.31–0.51). <h3>Conclusions:</h3> We report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients compared to focal and clinical measures used until now. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging (MRI) and would, therefore, have a more substantial clinical impact. <b>Disclosure:</b> An immediate family member of Dr. Pirondini has stock in Reach Neuro. The institution of Dr. Pirondini has received research support from NIH. The institution of an immediate family member of Dr. Pirondini has received research support from NIH. Dr. Pirondini has received intellectual property interests from a discovery or technology relating to health care. An immediate family member of Dr. Pirondini has received intellectual property interests from a discovery or technology relating to health care. Maria Giulia Preti has nothing to disclose. Dimitri Van De Ville has nothing to disclose. Prof. Guggisberg has nothing to disclose. Dr. Rivier has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Pyxis Partners.

Neural circuit mapping of waiting impulsivity and proactive inhibition with convergent evidence from fMRI and TMS

IntroductionWaiting and stopping are essential and distinct elements of appropriate behavioral control with its dysfunction implicated in various impulsivity related mental disorders. Although rodent and human studies have investigated both phenomena, the role of preparing to stop in waiting impulsivity has rarely been investigated. Furthermore, convergent evidence from multi-modal investigation tools remains a poorly utilized approach in addressing such questions.ObjectivesHere, we conducted two separate, but hierarchical studies, using functional magnetic resonance imaging (fMRI) to map the neural circuit involved in waiting impulsivity and proactive stopping, and subsequently provide mechanistic and causal evidence of disruption of this circuit by transcranial magnetic stimulation (TMS). In the second study, based on our fMRI study data, we attempted to investigate possible causation between the LIFG and waiting impulsivity by modulating LIFG, i.e. non-invasively producing a “virtual lesion” with an inhibitory transcranial magnetic stimulation (TMS) protocol called continuous theta burst stimulationMethodsWe recruited 41 healthy volunteers who performed an adapted version (1CSRT) of the well-established 5 choice serial reaction time task to capture waiting impulsivity. We developed a novel task measuring proactive inhibition. We scanned participants while completing these two tasks. Our fMRI data showed a strong association between LIFG activity and waiting impulsivity on the 1CSRT task. We conducted a single-blind, randomized, between-subjects design of cTBS of the LIFG on a sample of 51 healthy volunteers who completed an adapted version of the 1CSRT task (2CSRT task). Our a priori hypothesis was that cTBS would transiently decrease local cortical activity of the LIFG and increase the frequency of premature responses on both fixed and delayed cue-target interval trials on the 2CSRT task.ResultsWe first show a shared neural network comprising the pre-supplementary motor area and bilateral anterior insula underlying both waiting impulsivity and proactive stopping. We further demonstrate activity in dorsomedial prefrontal cortex and left inferior frontal gyrus (LIFG) negatively correlated with waiting impulsivity in trials with additional target onset delay. We demonstrate active stimulation significantly increased waiting impulsivity.ConclusionsIn these two studies, we validated a novel task measuring proactive inhibition. We further validated the significance of task structure for assessing distinct aspects of impulsivity, which is of translational interest. We further established a causal role of lIFG for waiting impulsivity thus highlighting the integrity of LIFG and related neural circuitry required in waiting impulsivity.Disclosure of InterestNone Declared

Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages.

Following a stroke in regions of the brain responsible for motor activity, patients can lose their ability to control parts of their body. Over time, some patients recover almost completely, while others barely recover at all. It is known that lesion volume, initial motor impairment and cortico-spinal tract asymmetry significantly impact motor changes over time. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Models that consider damage to the entire network instead of only local structural alterations lead to a more accurate prediction of patients' recovery. However, assessing white matter connections in stroke patients is challenging and time-consuming. Here, we evaluated in a data set of 37 patients whether we could predict upper extremity motor recovery from brain connectivity measures obtained by using the patient's lesion mask to introduce virtual lesions in 60 healthy streamline tractography connectomes. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging. We added these measures to benchmark structural features, and we used a ridge regression regularization to predict motor recovery at 3 months post-injury. As hypothesized, accuracy in prediction significantly increased (R 2 = 0.68) as compared to benchmark features (R 2 = 0.38). This improved prediction of recovery could be beneficial to clinical care and might allow for a better choice of intervention.

Disentangling Some Conceptual Knots.

Disentangling Some Conceptual Knots.

Abstract 7: Prediction Of Post-stroke Motor Recovery Benefits From Measures Of Sub-acute Widespread Network Damages

Background: Following an acute ischemic stroke, some patients recover almost completely, while others barely recover. It is known that lesion volume, initial motor impairment, and cortico-spinal tract asymmetry (benchmark features) significantly impact motor changes over time. However, accurate prediction models of patients’ recovery are still missing. Recent work suggested that disabilities arise not only from focal structural changes, but also from widespread alterations in inter-regional connectivity. Here, we built on this hypothesis to develop a more accurate post-stroke motor recovery prediction model. Methods: We evaluated a dataset of 37 patients (17 women) with upper extremity motor strokes. Their impairment was assessed at 2 weeks (baseline) and 3 months after the stroke using the Fugl-Meyer-Assessment. 18 graph measures of global structural connectivity were obtained using the patients’ T2 lesion mask to virtually reproduce the lesions in 60 healthy streamline tractography connectomes. We added these indirect measures to the benchmark features, and we used a ridge regression regularization in a leave-one-out cross-validation framework to predict motor recovery at 3 months post-injury. Results: Accuracy in prediction significantly increased when using brain connectivity measures (R 2 =0.68, 95% CI: 0.64-0.74) as compared to benchmark features alone (R 2 =0.38, 95% CI: 0.31-0.51). Conclusion: We reported that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients compared to focal and clinical measures used until now. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging (MRI) and would, therefore, have a more substantial clinical impact.

Mechanisms of Cognitive Decline due to White Matter Lesions in Cognitively Intact Older Adults

AbstractBackgroundWhite matter hyperintensities (WMH) on FLAIR MRI are highly prevalent in older adults and are linked to cognitive deficits as well as dementia. Likely mechanisms underlying associations between WMH and cognitive deficits include widespread partial disconnection due to the diffuse nature of progressive WMH and/or tract‐specific disconnection syndromes. We used a virtual lesion approach to evaluate cognitive deficits in domains associated with three tracts: left arcuate fasciculus (LAF; verbal working memory), inferior longitudinal fasciculus (ILF; visual processing), and fornix (memory).MethodWMH were semi‐automatically segmented from FLAIR MRI data in 481 ADNI controls and applied as regions of avoidance for probabilistic fiber tracking on DTI data in 46 healthy older subjects from the Human Connectome Lifespan database. Correlations between overall WMH burden or individual tract disruption and global or tract‐domain‐specific cognitive tests were assessed. Tract disconnection was also compared in subgroups with enriched disruption of specific tracts with respect to global WMH burden, Amyloid beta deposition status, and best (&gt;Mean+1SD) versus worst (&lt;Mean‐1SD) test performance.ResultAll three tracts showed disconnections due to WMH and the mean tract disconnection increased significantly with overall WMH burden (ILF; p&lt;0.001, LAF: p&lt;0.001, Fornix; p=0.025) (Figure 1A). Also, both overall WMH burden and percent disconnection in ILF were associated with prolonged Trail A and Trail B times after correction for age and education (Table 1). In subgroup analyses, Amyloid beta positive status significantly moderated correlation of Trail B times with overall WMH burden (p=0.007) and ILF disconnection (p=0.020) (Figure 2). Subjects with enriched ILF disconnection (Figure 1B) also had prolonged Trail A times than the average group (34.3 vs 30.2, p=0.003). Based on cognitive tests performance, subjects with better scores on verbal category fluency or verbal logical memory tests had lower LAF (p=0.035) and fornix (Test I; p=0.003, Test II; 0.025) disconnection.ConclusionWhile overall WMH burden correlates with cognitive deficits in ADNI controls, significant correlations between specific tract disconnection and tract‐domain‐specific cognitive tests are also observed. Both mechanisms likely contribute to age‐associated cognitive decline. Furthermore, amyloid beta accumulation strengthens these relationships.

Machine learning of large-scale multimodal brain imaging data reveals neural correlates of hand preference

Lateralization is a fundamental characteristic of many behaviors and the organization of the brain, and atypical lateralization has been suggested to be linked to various brain-related disorders such as autism and schizophrenia. Right-handedness is one of the most prominent markers of human behavioural lateralization, yet its neurobiological basis remains to be determined. Here, we present a large-scale analysis of handedness, as measured by self-reported direction of hand preference, and its variability related to brain structural and functional organization in the UK Biobank (N = 36,024). A multivariate machine learning approach with multi-modalities of brain imaging data was adopted, to reveal how well brain imaging features could predict individual's handedness (i.e., right-handedness vs. non-right-handedness) and further identify the top brain signatures that contributed to the prediction. Overall, the results showed a good prediction performance, with an area under the receiver operating characteristic curve (AUROC) score of up to 0.72, driven largely by resting-state functional measures. Virtual lesion analysis and large-scale decoding analysis suggested that the brain networks with the highest importance in the prediction showed functional relevance to hand movement and several higher-level cognitive functions including language, arithmetic, and social interaction. Genetic analyses of contributions of common DNA polymorphisms to the imaging-derived handedness prediction score showed a significant heritability (h2=7.55%, p <0.001) that was similar to and slightly higher than that for the behavioural measure itself (h2=6.74%, p <0.001). The genetic correlation between the two was high (rg=0.71), suggesting that the imaging-derived score could be used as a surrogate in genetic studies where the behavioural measure is not available. This large-scale study using multimodal brain imaging and multivariate machine learning has shed new light on the neural correlates of human handedness.

Phantom study of stereotactic radioablation for ventricular tachycardia (STRA-MI-VT) using Cyberknife Synchrony Respiratory Tracking System with a single fiducial marker

PurposeWithin the STRA-MI-VT phase Ib/II trial (NCT04066517), the aim of this phantom study was to explore the feasibility of Cyberknife treatments on cardiac lesions by tracking as a single marker the lead tip of an implantable cardioverter defibrillator. The residual displacement of the lesion during the tracking was studied, planning margins were found and the dosimetric accuracy of the treatment was checked. Materials and methodsA lead was inserted into a phantom (EasyCube phantom, Sun Nuclear Co, USA) and then placed on the translating ExacTrac Gating System (BrainLAB AG, Germany). The phantom was rotated, a virtual lesion was identified and its displacement during the tracking was studied. Two plans were compared, calculated on the unrotated volume and on the envelope of the unrotated and the rotated volumes. The plans were delivered using the Cyberknife System (Accuray Inc, USA) and their dosimetric accuracy verified by gamma analysis with gafchromic films. ResultsThe residual margin increases enhancing the distance between the lead and the lesion. It is 4 mm for distance 0 cm and 5 mm for distance 5 cm. The coverage is reduced by 3.8% (interquartile range 2.5%–4.7%) when the dose is prescribed on the unrotated volume. All treatment plans are accurate and 3% 3 mm gamma analysis results are greater than 94%. ConclusionsResults showed that tracking with a single marker is feasible considering adequate residual planning margins. The volumes could be further reduced by using additional markers, for example by placing them on the patient's skin.

The resting-state causal human connectome is characterized by hub connectivity of executive and attentional networks

We demonstrate a data-driven approach for calculating a “causal connectome” of directed connectivity from resting-state fMRI data using a greedy adjacency search and pairwise non-Gaussian edge orientations. We used this approach to construct n = 442 causal connectomes. These connectomes were very sparse in comparison to typical Pearson correlation-based graphs (roughly 2.25% edge density) yet were fully connected in nearly all cases. Prominent highly connected hubs of the causal connectome were situated in attentional (dorsal attention) and executive (frontoparietal and cingulo-opercular) networks. These hub networks had distinctly different connectivity profiles: attentional networks shared incoming connections with sensory regions and outgoing connections with higher cognitive networks, while executive networks primarily connected to other higher cognitive networks and had a high degree of bidirected connectivity. Virtual lesion analyses accentuated these findings, demonstrating that attentional and executive hub networks are points of critical vulnerability in the human causal connectome. These data highlight the central role of attention and executive control networks in the human cortical connectome and set the stage for future applications of data-driven causal connectivity analysis in psychiatry.