Deep Brain Stimulation Programming 2.0: Future Perspectives for Target Identification and Adaptive Closed Loop Stimulation

Deep brain stimulation has developed into an established treatment for movement disorders and is being actively investigated for numerous other neurological as well as psychiatric disorders. An accurate electrode placement in the target area and the effective programming of DBS devices are considered the most important factors for the individual outcome. Recent research in humans highlights the relevance of widespread networks connected to specific DBS targets. Improving the targeting of anatomical and functional networks involved in the generation of pathological neural activity will improve the clinical DBS effect and limit side-effects. Here, we offer a comprehensive overview over the latest research on target structures and targeting strategies in DBS. In addition, we provide a detailed synopsis of novel technologies that will support DBS programming and parameter selection in the future, with a particular focus on closed-loop stimulation and associated biofeedback signals

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

Adaptive Parameter Selection for Deep Brain Stimulation in Parkinson’s Disease

Each year, around 60,000 people are diagnosed with Parkinson’s disease (PD) and the economic burden of PD is at least $14.4 billion a year in the United States. Pharmaceutical costs for a Parkinson’s patient can be reduced from$12,000 to $6,000 per year with the addition of neuromodulation therapies such as Deep Brain Stimulation (DBS), transcranial Direct Current Stimulation (tDCS), Transcranial Magnetic Stimulation (TMS), etc. In neurodegenerative disorders such as PD, deep brain stimulation (DBS) is a desirable approach when the medication is less effective for treating the symptoms. DBS incorporates transferring electrical pulses to a specific tissue of the central nervous system and obtaining therapeutic results by modulating the neuronal activity of that region. The hyperkinetic symptoms of PD are associated with the ensembles of interacting oscillators that cause excess or abnormal synchronous behavior within the Basal Ganglia (BG) circuitry. Delayed feedback stimulation is a closed loop technique shown to suppress this synchronous oscillatory activity. Deep Brain Stimulation via delayed feedback is known to destabilize the complex intermittent synchronous states. Computational models of the BG network are often introduced to investigate the effect of delayed feedback high frequency stimulation on partially synchronized dynamics. In this work, we developed several computational models of four interacting nuclei of the BG as well as considering the Thalamo-Cortical local effects on the oscillatory dynamics. These models are able to capture the emergence of 34 Hz beta band oscillations seen in the Local Field Potential (LFP) recordings of the PD state. Traditional High Frequency Stimulations (HFS) has shown deficiencies such as strengthening the synchronization in case of highly fluctuating neuronal activities, increasing the energy consumed as well as the incapability of activating all neurons in a large-scale network. To overcome these drawbacks, we investigated the effects of the stimulation waveform and interphase delays on the overall efficiency and efficacy of DBS. We also propose a new feedback control variable based on the filtered and linearly delayed LFP recordings. The proposed control variable is then used to modulate the frequency of the stimulation signal rather than its amplitude. In strongly coupled networks, oscillations reoccur as soon as the amplitude of the stimulus signal declines. Therefore, we show that maintaining a fixed amplitude and modulating the frequency might ameliorate the desynchronization process, increase the battery lifespan and activate substantial regions of the administered DBS electrode. The charge balanced stimulus pulse itself is embedded with a delay period between its charges to grant robust desynchronization with lower amplitude needed. The efficiency and efficacy of the proposed Frequency Adjustment Stimulation (FAS) protocol in a delayed feedback method might contribute to further investigation of DBS modulations aspired to address a wide range of abnormal oscillatory behaviors observed in neurological disorders. Adaptive stimulation can open doors towards simultaneous stimulation with MRI recordings. We additionally propose a new pipeline to investigate the effect of Transcranial Magnetic Stimulation (TMS) on patient specific models. The pipeline allows us to generate a full head segmentation based on each individual MRI data. In the next step, the neurosurgeon can adaptively choose the proper location of stimulation and transmit accurate magnetic field with this pipeline

Parkinsoni tõbi ja depressioon: ajumehhanismid ja mitteinvasiivse ajustimulatsiooni põhised ravistrateegiad

Väitekirja elektrooniline versioon ei sisalda publikatsiooneParkinsoni tõbi (PT) on maailmas teine kõige sagedamini esinev neurodegeneratiivne haigus. PT-d iseloomustavad motoorsed ja mittemotoorsed tunnused, viimaste hulka kuuluvad ka neuropsühhiaatrilised häired. Neuropsühhiaatrilised häired (näiteks emotsionaalsed ja kognitiivsed sümptomid) esinevad PT puhul sageli ja neil on oluline mõju inimese elukvaliteedile. Üle maailma esineb kuni 50%-l PT patsientidest kliiniliselt olulisi depressioonisümptomeid, mis on oluliselt kõrgem levimus kui üldpopulatsioonis (hinnanguliselt 13,5%). Suur osa patsientidest ei saavuta neuropsühhiaatriliste häirete ravi käigus täielikku remissiooni erinevatel põhjustel, mille hulka kuuluvad ka ravi puudutavad põhjused nagu ebasobiv ravivalik, ravi kõrvaltoimed, koostoimed teiste ravimitega, vastunäidustused, ravi enneaegne lõpetamine jpt. Mitteinvasiivsed ajustimulatsioonimeetodid nagu korduv transkraniaalne magnetstimulatsioon (rTMS) on näidanud võimekust dorsolateraalse prefrontaalkoore (DLPFK) stimuleerimise kaudu leevendada turvaliselt ja efektiivselt emotsionaalseid, vähesemal määral ka kognitiivseid häireid. Käesoleva doktoritöö peamine eesmärk oli koondada ja laiendada teadmisi tõhusa rTMS ravi kohaldamise kohta patsientidel, kellel on diagnoositud nii PT kui ka depressioon, otsides potentsiaalseid neuropsühhiaatrilisi mõjutusi ka väljaspool meeleoluhäiret (näiteks kognitiivsed probleemid ja kõrgenenud ärevus) ning kaardistada seeläbi võimalikke positiivseid efekte inimese elukvalieedile. Väitekirjas sisalduvate uuringute kokkuvõttena saab esitada järgnevad väited: 1. Depressioonisümptomite raskusaste on oluline PT kliinilisi aspekte ja patsientide elukvaliteeti mõjutav tegur. Ajutüve raphe-tuumade neuroanatoomilised muutused on otseselt seotud depressioonihäirete patogeneesiga ning rõhutavad depressiooni neurokuvamuslike biomarkerite kasvavat tähtsust ja diagnostilist rakendatavust PT kontekstis. 2. DLPFK stimuleerimine rTMS-ga on efektiivne PT’ga seotud depressiooni ravistrateegia, kusjuures võimalik on ka positiivme mõju teistele neuropsühhiatrilistele probleemidele (nt kognitiivsed häired, ärevushäired, apaatsus) − viimaste osas on vajalikud kinnitused edaspidistes kliinilistes uuringutes. 3. Raviresistentse depressiooniga PT patsiendid kujutavad endast keerukat kliinilist valimit, millel on palju, sageli ebapiisavalt kaetud ravivajadusi. Rõhutada tuleb individuaalset varieeruvust nii kliinilises seisundis kui ka võimalikus ravivastuses, mis seeläbi õigustab isikupärastatavaid ravialaseid sekkumisviise, mille hulka sobib nii eraldivõetuna kui ka teiste meetoditega kombinatsioonis rakendatav mitteinvasiivne ajustimulatsioon (sh rTMS).Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. PD is characterized by motor and non-motor features, the latter including neuropsychiatric disorders. Neuropsychiatric disorders (such as emotional and cognitive symptoms) are common in PD and have a significant impact on a person's quality of life. Worldwide, up to 50% of PD patients have clinically significant depressive symptoms, which is higher in prevalence than in the general population (estimated at 13.5%). A large proportion of patients do not achieve complete remission during treatment for neuropsychiatric disorders for a variety of reasons, including treatment-related causes such as inappropriate treatment options, side effects of treatment, interactions with other drugs, contraindications, premature discontinuation of treatment, and others. Non-invasive brain stimulation methods such as repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC), have been shown to safely and effectively alleviate emotional, and to a lesser extent, cognitive, problems. The main objective of this doctoral dissertation was to gather and expand the knowledge on the application of effective rTMS treatment in patients diagnosed with both PT and depression, also being mindful of potential neuropsychiatric effects outside the mood domain (i.e. cognitive problems and anxiety). The following statements can be stated to summarize the research of the dissertation: 1. The severity of depressive symptoms is an important factor influencing the clinical aspects of PD, and the quality of life of patients. Neuroanatomical changes in the raphe nuclei of the brainstem are directly related to the pathogenesis of depressive disorders and underline the growing importance and diagnostic applicability of brain-based biomarkers of depression in the context of PD. 2. Targeting the DLPFC with rTMS is an effective treatment strategy for PD-related depression, with the potential for positive effects on other neuropsychiatric problems (e.g., cognitive impairment, anxiety disorders, apathy), the latter of which will need to be confirmed in future clinical trials. 3. PD patients with treatment-resistant depression represent a complex clinical sample with many, often insufficiently covered, treatment needs, emphasizing individual variability in both clinical status and potential treatment response, thereby justifying personalized treatment interventions that include rTMS as a standalone method and in combination with others.https://www.ester.ee/record=b545705

Functional impairment following axonal injury

Following trauma or other neurological disorders, a series of events happen that cause axonal dysfunction or ultimately lead to axonal death. Computational modeling of the nervous system facilitates systematic study of the effects of each injury parameter on the output. The overall goal of this research was to develop a new method of simulating axon damage in a biophysical model and quantify the effects of structural damage on signal conduction. To achieve this, three objectives were addressed 1) quantify the effects of normal morphological variation and demyelination on axonal conduction characteristics, 2) develop a new computationally efficient method for modeling damage in axons, and 3) characterize the structure changes observed in human axons and quantify the relationship between these observed changes and axonal function. Biophysical computational models developed in NEURON were employed to characterize morphological changes in damaged axons and study the effects of some of the most common axonal injuries such as myelin damage and spheroid formation on signal propagation in axons with different calibers. To facilitate efficient computational simulation, a new approach for increasing geometrical resolution in NEURON was developed and assessed. To investigate the effects of axonal swelling on action potential conduction in myelinated axons, the morphological properties of axonal spheroids were characterized by analyzing a series of confocal images captured from post-mortem human brain samples of patients with MS and infarction. Our results indicate that subtle abnormalities in nodal, paranodal and juxtaparanodal regions may have sizable effects on action potential amplitude and velocity and more targeted treatments need to be developed that focus on these regions. In addition, the results of our histopathological and computational studies suggest that axons with different diameters may respond differently to injuries and diseases. Therefore, it is important to perform experimental injury models across a wide range of axons to get a more comprehensive understanding of the relationship between axonal morphological features, injury parameters and functional responses. We expect this research to lay the quantitative foundation for finding new potential functional markers of white matter tissue damage and provide further insights into how myelin damage and axonal spheroids may affect function

Application of MRI Connectivity in Stereotactic Functional Neurosurgery

This thesis examines potential applications of advanced MRI-connectivity studies in stereotactic functional neurosurgery. Several new analysis methodologies are employed to: (1) build predictive models of DBS surgery outcome; (2) refine the surgical target and (3) help build a better understanding of the pathogenesis of the treated conditions and the mechanism of action of DBS therapy. The experimental component is divided into three main parts focusing on the following pathologies: (1) Parkinson’s disease (PD), (2) tremor and (3) trigeminal autonomic cephalalgias (TAC). Section I: In the first experiment (chapter 3), resting state fMRI was used to find radiological biomarkers predictive of response to L-DOPA in 19 patients undergoing subthalamic nucleus (STN) DBS for PD. A greater improvement in UPDRS-III scores following L-DOPA administration was characterized by higher resting state functional connectivity (fcMRI) between the prefrontal cortex and the striatum (p=0.001) and lower fcMRI between the pallidum (p=0.001), subthalamic nucleus (p=0.003) and the paracentral lobule. In the second experiment (chapter 4), structural (diffusion) connectivity was used to map out the influence of the hyperdirect pathways on outcome and identify the therapeutic ‘sweet spots’ in twenty PD patients undergoing STN-DBS. Clusters corresponding to maximum improvement in symptoms were in the posterior, superior and lateral portion of the STN. Greater connectivity to the primary motor area, supplementary motor area and prefrontal cortex was predictive of higher improvement in tremor, bradykinesia and rigidity, and rigidity respectively. The third experiment (chapter 5) examined pyramidal tract (PT) activation in 20 PD patients with STN-DBS. Volume of tissue activation (VTA) around DBS contacts were modelled in relation to the PT. VTA/ PT overlap predicted EMG activation thresholds. Sections II: Pilot data suggest that probabilistic tractography techniques can be used to segment the ventrolateral (VL) and ventroposterior (VP) thalamus based on cortical and cerebellar connectivity in nine patients who underwent thalamic DBS for tremor (chapter 6). The thalamic area, best representing the ventrointermedialis nucleus (VIM), was connected to the contralateral dentate cerebellar nucleus. Streamlines corresponding to the dentato-rubro-thalamic tract (DRT) connected M1 to the contralateral dentate nucleus via the dentato-thalamic area. Good response was seen when the active contact’s VTA was in the thalamic area with the highest connectivity to the contralateral dentate nucleus. Section III: The efficacy and safety of DBS in the ventral tegmental area (VTa) in the treatment of chronic cluster headache (CH) and short lasting unilateral neuralgiform headache attacks (SUNA) were examined (chapters 7 and 8). The optimum stimulation site within the VTa that best controls symptoms was explored (chapter 9). The average responders’ deep brain stimulation activation volume lay on the trigemino-hypothalamic tract, connecting the trigeminal system and other nociceptive brainstem nuclei, with the hypothalamus, and the prefrontal and mesial temporal areas