Conversion of a medical implant into a versatile computer-brain interface.

BACKGROUND: Information transmission into the human nervous system is the basis for a variety of prosthetic applications. Spinal cord stimulation (SCS) systems are widely available, have a well documented safety record, can be implanted minimally invasively, and are known to stimulate afferent pathways. Nonetheless, SCS devices are not yet used for computer-brain-interfacing applications. OBJECTIVE: Here we aimed to establish computer-to-brain communication via medical SCS implants in a group of 20 individuals who had been operated for the treatment of chronic neuropathic pain. METHODS: In the initial phase, we conducted interface calibration with the aim of determining personalized stimulation settings that yielded distinct and reproducible sensations. These settings were subsequently utilized to generate inputs for a range of behavioral tasks. We evaluated the required calibration time, task training duration, and the subsequent performance in each task. RESULTS: We could establish a stable spinal computer-brain interface in 18 of the 20 participants. Each of the 18 then performed one or more of the following tasks: A rhythm-discrimination task (n = 13), a Morse-decoding task (n = 3), and/or two different balance/body-posture tasks (n = 18; n = 5). The median calibration time was 79 min. The median training time for learning to use the interface in a subsequent task was 1:40 min. In each task, every participant demonstrated successful performance, surpassing chance levels. CONCLUSION: The results constitute the first proof-of-concept of a general purpose computer-brain interface paradigm that could be deployed on present-day medical SCS platforms.

Navigated Deep Brain Stimulation Surgery: Evaluating the Combined Use of a Frame-Based Stereotactic System and a Navigation System.

Deep brain stimulation (DBS) is a complex surgical procedure that requires detailed anatomical knowledge. In many fields of neurosurgery navigation systems are used to display anatomical structures during an operation to aid performing these surgeries. In frame-based DBS, the advantage of visualization has not yet been evaluated during the procedure itself. In this study, we added live visualization to a frame-based DBS system, using a standard navigation system and investigated its accuracy and potential use in DBS surgery. As a first step, a phantom study was conducted to investigate the accuracy of the navigation system in conjunction with a frame-based approach. As a second step, 5 DBS surgeries were performed with this combined approach. Afterwards, 3 neurosurgeons and 2 neurologists with different levels of experience evaluated the potential use of the system with a questionnaire. Moreover, the additional personnel, costs and required set up time were noted and compared to 5 consecutive standard procedures. In the phantom study, the navigation system showed an inaccuracy of 2.1 mm (mean SD 0.69 mm). In the questionnaire, a mean of 9.4/10 points was awarded for the use of the combined approach as a teaching tool, a mean of 8.4/10 for its advantage in creating a 3-dimensional (3-D) map and a mean of 8/10 points for facilitating group discussions. Especially neurosurgeons and neurologists in training found it useful to better interpret clinical results and side effects (mean 9/10 points) and neurosurgeons appreciated its use to better interpret microelectrode recordings (mean 9/10 points). A mean of 6/10 points was awarded when asked if the benefits were worth the additional efforts. Initially 2 persons, then one additional person was required to set up the system with no relevant added time or costs. Using a navigation system for live visualization during frame-based DBS surgery can improve the understanding of the complex 3-D anatomy and many aspects of the procedure itself. For now, we would regard it as an excellent teaching tool rather than a necessity to perform DBS surgeries.

Automatic Segmentation of the Subthalamic Nucleus: A Viable Option to Support Planning and Visualization of Patient-Specific Targeting in Deep Brain Stimulation.

BACKGROUND: Automatic segmentation is gaining relevancy in image-based targeting of neural structures. OBJECTIVE: To evaluate its feasibility, we retrospectively analyzed the concordance of magnetic resonance imaging (MRI)-based automatic segmentation of the subthalamic nucleus (STN) and intraoperative microelectrode recordings (MERs). METHODS: Electrodes (n = 60) for deep brain stimulation were implanted in the STN of patients (n = 30; median age 57 yr) with Parkinson disease (n = 29) or rapid-onset dystonia parkinsonism (n = 1). Elements (Brainlab, Munich, Germany) were used to segment the STN, using 2 volumetric T1 (±contrast) and volumetric T2 images as input. The stereotactic computed tomography was coregistered with the imaging, and the original stereotactic coordinates were imported. MERs (0.5-1 mm steps) along the anterior, central, and lateral trajectories were used to determine differences between the image-segmented STN boundary and MER-based STN entry and exit. RESULTS: Of 175 trajectories, 105 penetrated or touched (≤0.7 mm) the STN. The overall median deviation between the segmented STN boundary and electrophysiological recordings was 1.1 mm for MER-based STN entry and 2.0 mm for STN exit. Regarding the entry point of the STN, there was no statistically significant difference between MRI-based automatic segmentation and the electrophysiological trajectories analyzed with intraoperative MER. The exit point was significantly different between both methods in the central and lateral trajectories. CONCLUSION: MRI-based automatic segmentation of the STN is a viable, patient-specific targeting approach that can be used alongside traditional targeting methods in deep brain stimulation to support preoperative planning and visualization of target structures and aid postoperative optimization of programming.

Postoperative neuroimaging analysis of DRT deep brain stimulation revision surgery for complicated essential tremor.

BACKGROUND: We report a patient who received conventional bilateral deep brain stimulation of the ventral intermediate nucleus of thalamus (Vim) for the treatment of medication refractory essential tremor (ET). After initial beneficial effects, therapeutic efficacy was lost due to a loss of control of his proximal trunkal and extremity tremor. The patient received successful diffusion tensor magnetic resonance imaging fiber tractographic (DTI FT)-assisted DBS revision surgery targeting the dentato-rubro-thalamic tract (DRT) in the subthalamic region (STR). OBJECTIVE: To report the concept of DTI FT-assisted DRT DBS revision surgery for ET and to show sophisticated postoperative neuroimaging analysis explaining improved symptom control. METHODS: Analysis was based on preoperative DTI sequences and postoperative helical computed tomography (hCT). Leads, stimulation fields, and fibers were reconstructed using commercial software systems (Elements, Brainlab AG, Feldkirchen, Germany; GUIDE XT, Boston Scientific Corp., Boston, MA, USA). RESULTS: The patient showed immediate and sustained tremor improvement after DTI FT-assisted revision surgery. Analysis of the two implantations (electrode positions in both instances) revealed a lateral and posterior shift in the pattern of modulation of the cortical fiber pathway projection after revision surgery as compared to initial implantation, explaining a more efficacious stimulation. CONCLUSIONS: Our work underpins a possible superiority of direct targeting approaches using advanced neuroimaging technologies to perform personalized DBS surgery. The evaluation of DBS electrode positions with the herein-described neuroimaging simulation technologies will likely improve targeting and revision strategies. Direct targeting with DTI FT-assisted approaches in a variety of indications is the focus of our ongoing research.

Resting state changes in functional connectivity correlate with movement recovery for BCI and robot-assisted upper-extremity training after stroke.

BACKGROUND: Robot-assisted training may improve motor function in some hemiparetic patients after stroke, but no physiological predictor of rehabilitation progress is reliable. Resting state functional magnetic resonance imaging (RS-fMRI) may serve as a method to assess and predict changes in the motor network. OBJECTIVE: The authors examined the effects of upper-extremity robot-assisted rehabilitation (MANUS) versus an electroencephalography-based brain computer interface setup with motor imagery (MI EEG-BCI) and compared pretreatment and posttreatment RS-fMRI. METHODS: In all, 9 adults with upper-extremity paresis were trained for 4 weeks with a MANUS shoulder-elbow robotic rehabilitation paradigm. In 3 participants, robot-assisted movement began if no voluntary movement was initiated within 2 s. In 6 participants, MI-BCI-based movement was initiated if motor imagery was detected. RS-fMRI and Fugl-Meyer (FM) upper-extremity motor score were assessed before and after training. RESULTS: . The individual gain in FM scores over 12 weeks could be predicted from functional connectivity changes (FCCs) based on the pre-post differences in RS-fMRI measurements. Both the FM gain and FCC were numerically higher in the MI-BCI group. Increases in FC of the supplementary motor area, the contralesional and ipsilesional motor cortex, and parts of the visuospatial system with mostly association cortex regions and the cerebellum correlated with individual upper-extremity function improvement. CONCLUSION: FCC may predict the steepness of individual motor gains. Future training could therefore focus on directly inducing these beneficial increases in FC. Evaluation of the treatment groups suggests that MI is a potential facilitator of such neuroplasticity.

Prefrontal brain asymmetry and aggression in imprisoned violent offenders.

Anterior brain asymmetry, assessed through the alpha and beta band in resting-state electroencephalogram (EEG) is associated with approach-related behavioral dispositions, particularly with aggression in the general population. To date, the association between frontal asymmetry and aggression has not been examined in highly aggressive groups. We examined the topographic characteristics of alpha and beta activity, the relation of both asymmetry metrics to trait aggression, and whether alpha asymmetry was extreme in anterior regions according to clinical standards in a group of imprisoned violent offenders. As expected, these individuals were characterized by stronger right than left-hemispheric alpha activity, which was putatively extreme in anterior regions in one third of the cases. We also report that in line with observations made in the general population, aggression was associated with stronger right-frontal alpha activity in these violent individuals. This suggests that frontal alpha asymmetry, as a correlate of trait aggression, might be utilizable as an outcome measure in studies which assess the effects of anti-aggressiveness training in violent offenders.

Quantifying the link between anatomical connectivity, gray matter volume and regional cerebral blood flow: an integrative MRI study.

BACKGROUND: In the graph theoretical analysis of anatomical brain connectivity, the white matter connections between regions of the brain are identified and serve as basis for the assessment of regional connectivity profiles, for example, to locate the hubs of the brain. But regions of the brain can be characterised further with respect to their gray matter volume or resting state perfusion. Local anatomical connectivity, gray matter volume and perfusion are traits of each brain region that are likely to be interdependent, however, particular patterns of systematic covariation have not yet been identified. METHODOLOGY/PRINCIPAL FINDINGS: We quantified the covariation of these traits by conducting an integrative MRI study on 23 subjects, utilising a combination of Diffusion Tensor Imaging, Arterial Spin Labeling and anatomical imaging. Based on our hypothesis that local connectivity, gray matter volume and perfusion are linked, we correlated these measures and particularly isolated the covariation of connectivity and perfusion by statistically controlling for gray matter volume. We found significant levels of covariation on the group- and regionwise level, particularly in regions of the Default Brain Mode Network. CONCLUSIONS/SIGNIFICANCE: Connectivity and perfusion are systematically linked throughout a number of brain regions, thus we discuss these results as a starting point for further research on the role of homology in the formation of functional connectivity networks and on how structure/function relationships can manifest in the form of such trait interdependency.

Patterns of response to repetitive transcranial magnetic stimulation (rTMS) in major depression: replication study in drug-free patients.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) has been found to exert modest to moderate therapeutic effects in major depression, but mechanism of action and its clinical relevance have not been clarified yet. Previous trials have reported patterns of symptomatology predicting response to rTMS. As most patients also received concomitant antidepressant medication these response patterns may rather refer to combined treatment than rTMS alone. Thus, this study aims to replicate previous findings and explore patterns of response in drug-free patients. METHODS: In the Munich-Berlin Predictor Study data of 79 patients from two open clinical trials evaluating effects of high-frequency rTMS of the left dorsolateral prefrontal cortex were pooled. Previous models predicting the response to rTMS [Fregni, F., Marcolin, M.A., Myczkowski, M., Amiaz, R., Hasey, G., Rumi, D.O., Rosa, M., Rigonatti, S.P., Camprodon, J., Walpoth, M., Heaslip, J., Grunhaus, L., Hausmann, A., Pascual-Leone, A., 2006. Predictors of antidepressant response in clinical trials of transcranial magnetic stimulation. Int. J. Neuropsychopharmacol. 9, 641-654; Brakemeier, E.L., Luborzewski, A., Danker-Hopfe, H., Kathmann, N., Bajbouj, M., 2007. Positive predictors for antidepressive response to prefrontal repetitive transcranial magnetic stimulation (rTMS). J. Psychiatr. Res. 41, 395-403.] were systematically tested and new explorative regression analyses were conducted. RESULTS: Of the 79 patients, 34.2% showed an antidepressant response. Previous models could not be validated. Explorative regression analysis revealed a significant model with therapy resistance, HAMD items 1 (depressed mood), and 2 (feelings of guilt) as negative and retardation as positive predictors. LIMITATIONS: No controlled study; specific statistical issues; sample size; differences concerning patient population and stimulation parameters between study sites. CONCLUSIONS: In sum, this study does not confirm clinical valid and robust patterns being predictive for a response to rTMS in depression. The only exception is a high level of therapy resistance being associated with poor outcome. Future predictor studies should focus on large and homogenous samples of rTMS multicenter trials and include neurobiological variables.