Stereotactic radiofrequency ventral posterolateral thalamotomy for cancer pain

Palliative neuroablative procedures are often performed for medication-refractory cancer pain. A 57-year-old female with lung carcinoma and metastases to the brachial plexus and cervical spine with severe neuropathic pain affecting the right upper limb was referred to the authors’ functional neurosurgery service. This video shows her treatment with an awake stereotactic radiofrequency thalamotomy targeting the left ventral posterolateral nucleus. Postoperatively, she experienced immediate and complete resolution of the pain. Palliative radiofrequency thalamotomy can be a viable and effective procedure for somatotopically distributed regional cancer pain. The video can be found here: https://youtu.be/jykYWXTP3c

First-principles study on the origin of large thermopower in hole-doped LaRhO3 and CuRhO2

Based on first-principles calculations, we study the origin of the large thermopower in Ni-doped LaRhO3 and Mg-doped CuRhO2. We calculate the band structure and construct the maximally localized Wannier functions from which a tight binding Hamiltonian is obtained. The Seebeck coefficient is calculated within the Boltzmann's equation approach using this effective Hamiltonian. For LaRhO3, we find that the Seebeck coefficient remains nearly constant within a large hole concentration range, which is consistent with the experimental observation. For CuRhO2, the overall temperature dependence of the calculated Seebeck coefficient is in excellent agreement with the experiment. The origin of the large thermopower is discussed.Comment: 7 pages, to be published J. Phys.: Cond. Matt., Proc. QSD 200

Closed-loop DBS triggered by real-time movement and tremor decoding based on thalamic LFPs for essential tremor.

High frequency Deep Brain Stimulation (DBS) targeting the motor thalamus is an effective therapy for essential tremor (ET). However, since tremor mainly affects periods of voluntary movements and sustained postures in ET, conventional continuous stimulation may deliver unnecessary current to the brain. Here we tried to decode movement states based on local field potentials (LFPs) recorded from motor thalamus and zona incerta in real-time to trigger the switching on and off of DBS in three patients with ET. Patient-specific models were first identified using thalamic LFPs recorded while the patient performed movements that tended to trigger tremor in everyday life. During the real-time test, LFPs were continuously recorded to decode movements and tremor, and the detection triggered stimulation. Results show that voluntary movements can be detected with a mean sensitivity ranging from 76.8% to 88.6% and a false positive rate ranging from 16.0% to 23.1% Postural tremor was detected with similar accuracy. The closed-loop DBS triggered by tremor detection suppressed intention tremor by 90.5% with a false positive rate of 20.3%.Clinical Relevance- This is the first study on closed-loop DBS triggered by real-time movement and tremor decoding based solely on thalamic LFPs. The results suggest that responsive DBS based on movement and tremor detection can be achieved without any requirement for external sensors or additional electrocorticography strips

Local field potential activity dynamics in response to deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

Local field potentials (LFPs) may afford insight into the mechanisms of action of deep brain stimulation (DBS) and potential feedback signals for adaptive DBS. In Parkinson's disease (PD) DBS of the subthalamic nucleus (STN) suppresses spontaneous activity in the beta band and drives evoked resonant neural activity (ERNA). Here, we investigate how STN LFP activities change over time following the onset and offset of DBS. To this end we recorded LFPs from the STN in 14 PD patients during long (mean: 181.2 s) and short (14.2 s) blocks of continuous stimulation at 130 Hz. LFP activities were evaluated in the temporal and spectral domains. During long stimulation blocks, the frequency and amplitude of the ERNA decreased before reaching a steady state after ~70 s. Maximal ERNA amplitudes diminished over repeated stimulation blocks. Upon DBS cessation, the ERNA was revealed as an under-damped oscillation, and was more marked and lasted longer after short duration stimulation blocks. In contrast, activity in the beta band suppressed within 0.5 s of continuous DBS onset and drifted less over time. Spontaneous activity was also suppressed in the low gamma band, suggesting that the effects of high frequency stimulation on spontaneous oscillations may not be selective for pathological beta activity. High frequency oscillations were present in only six STN recordings before stimulation onset and their frequency was depressed by stimulation. The different dynamics of the ERNA and beta activity with stimulation imply different DBS mechanisms and may impact how these activities may be used in adaptive feedback

Pain in Parkinson’s disease and the role of the subthalamic nucleus

Pain is a frequent and poorly treated symptom of Parkinson’s disease, mainly due to scarce knowledge of its basic mechanisms. In Parkinson’s disease, deep brain stimulation of the subthalamic nucleus is a successful treatment of motor symptoms, but also might be effective in treating pain. However, it has been unclear which type of pain may benefit and how neurostimulation of the subthalamic nucleus might interfere with pain processing in Parkinson’s disease. We hypothesized that the subthalamic nucleus may be an effective access point for modulation of neural systems subserving pain perception and processing in Parkinson’s disease. To explore this, we discuss data from human neurophysiological and psychophysical investigations. We review studies demonstrating the clinical efficacy of deep brain stimulation of the subthalamic nucleus for pain relief in Parkinson’s disease. Finally, we present some of the key insights from investigations in animal models, healthy humans and Parkinson’s disease patients into the aberrant neurobiology of pain processing and consider their implications for the pain-relieving effects of subthalamic nucleus neuromodulation. The evidence from clinical and experimental studies supports the hypothesis that altered central processing is critical for pain generation in Parkinson’s disease and that the subthalamic nucleus is a key structure in pain perception and modulation. Future preclinical and clinical research should consider the subthalamic nucleus as an entry point to modulate different types of pain, not only in Parkinson’s disease but also in other neurological conditions associated with abnormal pain processing

Critical role of device geometry for the phase diagram of twisted bilayer graphene

The effective interaction between electrons in two-dimensional materials can be modified by their environment, enabling control of electronic correlations and phases. Here, we study the dependence of electronic correlations in twisted bilayer graphene (tBLG) on the separation to the metallic gate(s) in two device configurations. Using an atomistic tight-binding model, we determine the Hubbard parameters of the flat bands as a function of gate separation, taking into account the screening from the metallic gate(s), the dielectric spacer layers, and the tBLG itself. We determine the critical gate separation at which the Hubbard parameters become smaller than the critical value required for a transition from a correlated insulator state to a (semi)metallic phase. We show how this critical gate separation depends on twist angle, doping, and the device configuration. These calculations may help rationalize the reported differences between recent measurements of tBLG's phase diagram and suggest that correlated insulator states can be screened out in devices with thin dielectric layers

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future