Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks.

Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.

Cross-dimensional interference between time and distance during spatial navigation is mediated by speed representations in intraparietal sulcus and area hMT.

When navigating a straight path, perceived travel time and perceived traveled distance are linked via movement speed. Behavioral studies have revealed systematic interferences between the perception of travel time and distance, but the role of neuronal representations of movement speed for these effects has not been addressed to date. Using a combined fMRI-behavioral paradigm, we investigate the neuronal representations that underlie cross-dimensional interferences between travel time and traveled distance. Participants underwent fMRI while experiencing visual forward movements for either a short or a long duration, and covering either a short or a long distance. At the behavioral level, we found bi-directional interference effects between time and distance perception, which was correlated with greater representational similarity in speed-sensitive brain regions. The strength of the distance-on-time effect scaled with representational similarity in the left human middle temporal complex (hMT+), and the strength of the time-on-distance effect scaled with representational similarity in the right intraparietal sulcus (IPS). In accordance with the idea that the interference is mediated by the perception of speed, distance-on-time and time-on-distance effects were of opposing directions. Increases in traveled distance led to increases in perceived travel time, while increases in travel time led to decreases in perceived traveled distance. Together, these findings support the view that cross-dimensional interference effects between travel time and traveled distance are mediated by neuronal representations of movement speed.

Rapid improvement of cognitive maps in the awake state.

Post-navigation awake quiescence, relative to task engagement, benefits the accuracy of a new "cognitive map". This effect is hypothesized to reflect awake quiescence, like sleep, being conducive to the consolidation and integration of new spatial memories. Sleep has been shown to improve cognitive map accuracy over time. It remained unknown whether awake quiescence can induce similar time-related improvements in new cognitive maps, or whether it simply counteracts their decay. We examined this question via two experiments. In Experiment 1, using an established cognitive mapping paradigm, we reveal that map accuracy for a virtual town was significantly better in people whose memory was probed after 10 min of post-navigation awake quiescence or ongoing cognitive engagement, relative to those whose memory was probed shortly after initial navigation. In Experiment 2, using a newly developed cognitive mapping task that involved a more complex and real-life virtual town, we again found that map accuracy was superior in those whose memory was probed after 10 min of awake quiescence than those who were tested soon after navigation. These findings indicate that actual improvements in human memories are not restricted to sleep. Thus, contrary to conventional wisdom and theories, the passage of (day)time need not always result in forgetting.

Effects of estrogen on spatial navigation and memory.

RATIONALE: Animal studies suggest that the so-called "female" hormone estrogen enhances spatial navigation and memory. This contradicts the observation that males generally out-perform females in spatial navigation and tasks involving spatial memory. A closer look at the vast number of studies actually reveals that performance differences are not so clear. OBJECTIVES: To help clarify the unclear performance differences between men and women and the role of estrogen, we attempted to isolate organizational from activational effects of estrogen on spatial navigation and memory. METHODS: In a double-blind, placebo-controlled study, we tested the effects of orally administered estradiol valerate (E2V) in healthy, young women in their low-hormone menstrual cycle phase, compared to healthy, young men. Participants performed several first-person, environmentally rich, 3-D computer games inspired by spatial navigation and memory paradigms in animal research. RESULTS: We found navigation behavior suggesting that sex effects dominated any E2 effects with men performing better with allocentric strategies and women with egocentric strategies. Increased E2 levels did not lead to general improvements in spatial ability in either sex but to behavioral changes reflecting navigation flexibility. CONCLUSION: Estrogen-driven differences in spatial cognition might be better characterized on a spectrum of navigation flexibility rather than by categorical performance measures or skills.

Detection of RF unsafe devices using a parallel transmission MR system.

PURPOSE: The permanent presence of devices (pacemakers) inside a patient, or the need to use other devices (catheters), for diagnosis and treatment, usually represents a contraindication for a magnetic resonance examination. To help overcome this problem, a novel and noninvasive magnetic resonance system-based concept is proposed to detect potentially unsafe radio frequency (RF) conditions of such devices to ensure patient safety. METHODS: This concept makes use of parallel transmit technology by monitoring currents in individual RF transmit coil elements during RF transmission using suitable current sensors. For interventional devices, current changes can be directly measured, whereas for implanted devices, the use of reference signals is proposed, which cannot be measured in the patient. RESULTS: Coupling of unsafe devices to transmit coils led to detectable current changes in the elements because of energy absorption into the device. The concept was successfully tested on interventional and implantable devices and turned out to be so sensitive that even very weak RF coupling to these devices was detectable. CONCLUSION: In this study, basic feasibility to detect RF unsafe conditions was successfully demonstrated. In the future, RF patient safety may be improved in the presence of implanted devices, as well as during interventions using this concept.

Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is highly effective in controlling motor symptoms in patients with Parkinson's disease. However, correct selection of stimulation parameters is pivotal to treatment success and currently follows a time-consuming and demanding trial-and-error process. We aimed to assess treatment effects of stimulation parameters suggested by a recently published algorithm (StimFit) based on neuroimaging data. METHODS: This double-blind, randomised, crossover, non-inferiority trial was carried out at Charité - Universitätsmedizin, Berlin, Germany, and enrolled patients with Parkinson's disease treated with directional octopolar electrodes targeted at the STN. All patients had undergone DBS programming according to our centre's standard of care (SoC) treatment before study recruitment. Based on perioperative imaging data, DBS electrodes were reconstructed and StimFit was applied to suggest optimal stimulation settings. Patients underwent motor assessments using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) during OFF-medication and in OFF-stimulation and ON-stimulation states under both conditions, StimFit and SoC parameter settings. Patients were randomly assigned (1:1) to receive either StimFit-programmed DBS first and SoC-programmed DBS second, or SoC-programmed DBS first and StimFit-programmed DBS second. The allocation schedule was generated using a computerised random number generator. Both the rater and patients were masked to the sequence of SoC and StimFit stimulation conditions. All patients who participated in the study were included in the analysis. The primary endpoint of this study was the absolute mean difference between MDS-UPDRS-III scores under StimFit and SoC stimulation, with a non-inferiority margin of 5 points. The study was registered at the German Register for Clinical Trials (DRKS00023115), and is complete. FINDINGS: Between July 10, 2020, and Oct 28, 2021, 35 patients were enrolled in the study; 18 received StimFit followed by SoC stimulation, and 17 received SoC followed by StimFit stimulation. Mean MDS-UPDRS-III scores improved from 47·3 (SD 17·1) at OFF-stimulation baseline to 24·7 (SD 12·4) and 26·3 (SD 12·4) under SoC and StimFit stimulation, respectively. Mean difference between motor scores was -1·6 (SD 7·1; 95% CI -4·0 to 0·9; superiority test psuperiority=0·20; n=35), establishing non-inferiority of StimFit stimulation at a margin of -5 points (non-inferiority test pnon-inferiority=0·0038). In six patients (17%), initial programming of StimFit settings resulted in acute side-effects and amplitudes were reduced until side-effects disappeared. INTERPRETATION: Automated data-driven algorithms can predict stimulation parameters that lead to motor symptom control comparable to SoC treatment. This approach could significantly decrease the time necessary to obtain optimal treatment parameters. FUNDING: Deutsche Forschungsgemeinschaft through NeuroCure Clinical Research Center and TRR 295.

Neuroimaging-based analysis of DBS outcomes in pediatric dystonia: Insights from the GEPESTIM registry.

INTRODUCTION: Deep brain stimulation (DBS) is an established treatment in patients of various ages with pharmaco-resistant neurological disorders. Surgical targeting and postoperative programming of DBS depend on the spatial location of the stimulating electrodes in relation to the surrounding anatomical structures, and on electrode connectivity to a specific distribution pattern within brain networks. Such information is usually collected using group-level analysis, which relies on the availability of normative imaging resources (atlases and connectomes). Analysis of DBS data in children with debilitating neurological disorders such as dystonia would benefit from such resources, especially given the developmental differences in neuroimaging data between adults and children. We assembled pediatric normative neuroimaging resources from open-access datasets in order to comply with age-related anatomical and functional differences in pediatric DBS populations. We illustrated their utility in a cohort of children with dystonia treated with pallidal DBS. We aimed to derive a local pallidal sweetspot and explore a connectivity fingerprint associated with pallidal stimulation to exemplify the utility of the assembled imaging resources. METHODS: An average pediatric brain template (the MNI brain template 4.5-18.5 years) was implemented and used to localize the DBS electrodes in 20 patients from the GEPESTIM registry cohort. A pediatric subcortical atlas, analogous to the DISTAL atlas known in DBS research, was also employed to highlight the anatomical structures of interest. A local pallidal sweetspot was modeled, and its degree of overlap with stimulation volumes was calculated as a correlate of individual clinical outcomes. Additionally, a pediatric functional connectome of 100 neurotypical subjects from the Consortium for Reliability and Reproducibility was built to allow network-based analyses and decipher a connectivity fingerprint responsible for the clinical improvements in our cohort. RESULTS: We successfully implemented a pediatric neuroimaging dataset that will be made available for public use as a tool for DBS analyses. Overlap of stimulation volumes with the identified DBS-sweetspot model correlated significantly with improvement on a local spatial level (R = 0.46, permuted p = 0.019). The functional connectivity fingerprint of DBS outcomes was determined to be a network correlate of therapeutic pallidal stimulation in children with dystonia (R = 0.30, permuted p = 0.003). CONCLUSIONS: Local sweetspot and distributed network models provide neuroanatomical substrates for DBS-associated clinical outcomes in dystonia using pediatric neuroimaging surrogate data. Implementation of this pediatric neuroimaging dataset might help to improve the practice and pave the road towards a personalized DBS-neuroimaging analyses in pediatric patients.

Compromised Grid-Cell-like Representations in Old Age as a Key Mechanism to Explain Age-Related Navigational Deficits.

A progressive loss of navigational abilities in old age has been observed in numerous studies, but we have only limited understanding of the neural mechanisms underlying this decline [1]. A central component of the brain's navigation circuit are grid cells in entorhinal cortex [2], largely thought to support intrinsic self-motion-related computations, such as path integration (i.e., keeping track of one's position by integrating self-motion cues) [3-6]. Given that entorhinal cortex is particularly vulnerable to neurodegenerative processes during aging and Alzheimer's disease [7-14], deficits in grid cell function could be a key mechanism to explain age-related navigational decline. To test this hypothesis, we conducted two experiments in healthy young and older adults. First, in an fMRI experiment, we found significantly reduced grid-cell-like representations in entorhinal cortex of older adults. Second, in a behavioral path integration experiment, older adults showed deficits in computations of self-position during path integration based on body-based or visual self-motion cues. Most strikingly, we found that these path integration deficits in older adults could be explained by their individual magnitudes of grid-cell-like representations, as reduced grid-cell-like representations were associated with larger path integration errors. Together, these results show that grid-cell-like representations in entorhinal cortex are compromised in healthy aging. Furthermore, the association between grid-cell-like representations and path integration performance in old age supports the notion that grid cells underlie path integration processes. We therefore conclude that impaired grid cell function may play a key role in age-related decline of specific higher-order cognitive functions, such as spatial navigation.