| 1. |
- Forni, Matilde, et al.
(författare)
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Sustained and potent analgesia with negligible side effects enabled by adaptive individualized granular stimulation in rat brainstem
- 2023
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Ingår i: Journal of Neural Engineering. - 1741-2560. ; 20:3
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Tidskriftsartikel (refereegranskat)abstract
- Objectives. To clarify if an adaptive current stimulation protocol, in which current amplitude is modulated during continuous stimulation, provides better efficacy than constant current stimulation protocol with respect to analgesia caused by individualized stimulation in rat periaqueductal gray matter (PAG) /dorsal raphe nuclei (DRN). Approach. Ultrathin microelectrodes adapted for recording (n = 6) and stimulation (n = 16) were implanted in rat primary somatosensory cortex and PAG/DRN, respectively. In each animal included (n = 12), a subset of PAG/DRN microelectrodes (n = 1-3 per animal) was selected that on simultaneous stimulation blocked nociceptive withdrawal reflexes in awake unrestrained animals without noticeable side effects. Analgesic effects were subsequently assessed from both nociceptive withdrawal reflexes and intracortical pain-related responses on CO2 laser hind paw stimulation. The analgesic effects of adaptive current PAG/DRN stimulation comprising incremental increases of 5 μA/microelectrode (initial median current 30 μA/microelectrode) when effects declined were compared to the effects of constant current stimulation. Behavioral effects and brain state related changes were analyzed using quantitative movement analysis and electrocorticography (recorded on top of the dura mater), respectively. Tissue reactions and probe placement in PAG/DRN were assessed with immunohistochemistry. Main results. Powerful and sustained (4 h) analgesia was achieved with the adaptive current protocol within a rather wide area of PAG/DRN. Analgesic after-effects were seen for up to 30 min. Behavioral and brain state related side effects were minimal. Moreover, 6 weeks after implantation, there were no traces of bleedings, only small glial reactions and small but not statistically significant loss of neurons nearby indicating that the microelectrode stimulation employed is biocompatible. Significance. The results indicate that sustained and powerful analgesia with minimal side effects can be achieved by granular and individualized stimulation in PAG/DRN using an adaptive current stimulation protocol. This microelectrode technology and stimulation paradigm thus has the potential of providing a highly efficient and safe pain therapy.
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| 2. |
- Mohammed, Mohsin, et al.
(författare)
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Microelectrode clusters enable therapeutic deep brain stimulation without noticeable side-effects in a rodent model of Parkinson's disease
- 2022
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Ingår i: Journal of Neuroscience Methods. - : Elsevier BV. - 0165-0270. ; 365
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Tidskriftsartikel (refereegranskat)abstract
- Background: Deep Brain Stimulation (DBS) is an established treatment for motor symptoms in Parkinson's disease (PD). However, side effects often limit the usefulness of the treatment. New method: To mitigate this problem, we developed a novel cluster of ultrathin platinum-iridium microelectrodes (n = 16) embedded in a needle shaped gelatin vehicle. In an established rodent PD-model (6-OHDA unilateral lesion), the clusters were implanted in the subthalamic area for up to 8 weeks. In an open field setting, combinations of microelectrodes yielding therapeutic effects were identified using statistical methods. Immunofluorescence techniques were used for histological assessments of biocompatibility. Results: In all rats tested (n = 5), we found subsets of 3–4 microelectrodes which, upon stimulation (160 Hz, 60 μs pulse width, 25–40 μA/microelectrode), prompted normal movements without noticeable side effects. Other microelectrode subsets often caused side effects such as rotation, dyskinesia and tremor. The threshold (per microelectrode) to elicit normal movements strongly depended on the number of activated microelectrodes in the selected subset. The histological analysis revealed viable neurons close to the electrode contacts, minor microglial and astrocytic reactions and no major changes in the vasculature, indicating high biocompatibility. Comparison to existing methods and conclusion: By contrast to the continuous and relatively large stimulation fields produced by existing DBS electrodes, the developed microelectrode cluster enables a fine-tuned granular and individualized microstimulation. This granular type of stimulation pattern provided powerful and specific therapeutic effects, free of noticeable side effects, in a PD animal model.
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| 3. |
- Forni, Matilde, et al.
(författare)
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3D microelectrode cluster and stimulation paradigm yield powerful analgesia without noticeable adverse effects
- 2021
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Ingår i: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:41
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Tidskriftsartikel (refereegranskat)abstract
- The lack of satisfactory treatment for persistent pain profoundly impairs the quality of life for many patients. Stimulation of brainstem pain control systems can trigger powerful analgesia, but their complex network organization frequently prevents separation of analgesia from side effects. To overcome this long-standing challenge, we developed a biocompatible gelatin-embedded cluster of ultrathin microelectrodes that enables fine-tuned, high-definition three-dimensional stimulation in periaqueductal gray/dorsal raphe nucleus in awake rats. Analgesia was assessed from both motor reactions and intracortical signals, corresponding to pain-related signals in humans. We could select an individual-specific subset of microelectrodes in each animal that reliably provided strong pain inhibition during normal and hyperalgesia conditions, without noticeable behavioral side effects. Gait, spontaneous cortical activity at rest, and cortical tactile responses were minimally affected, indicating a highly selective action. In conclusion, our developed biocompatible microelectrode cluster and stimulation paradigm reliably enabled powerful, fine-tuned, and selective analgesia without noticeable side effects.
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| 4. |
- Mohammed, Mohsin, et al.
(författare)
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Ice coating –A new method of brain device insertion to mitigate acute injuries
- 2020
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Ingår i: Journal of Neuroscience Methods. - : Elsevier BV. - 0165-0270. ; 343
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Tidskriftsartikel (refereegranskat)abstract
- Background: Reduction of insertion injury is likely important to approach physiological conditions in the vicinity of implanted devices intended to interface with the surrounding brain. New methods: We have developed a novel, low-friction coating around frozen, gelatin embedded needles. By introducing a layer of thawing ice onto the gelatin, decreasing surface friction, we mitigate damage caused by the implantation. Results and comparison with existing methods: The acute effects of a transient stab on neuronal density and glial reactions were assessed 1 and 7 days post stab in rat cortex and striatum both within and outside the insertion track using immunohistochemical staining. The addition of a coat of melting ice to the frozen gelatin embedded needles reduced the insertion force with around 50 %, substantially reduced the loss neurons (i.e. reduced neuronal void), and yielded near normal levels of astrocytes within the insertion track 1 day after insertion, as compared to gelatin coated probes of the same temperature without ice coating. There were negligible effects on glial reactions and neuronal density immediately outside the insertion track of both ice coated and cold gelatin embedded needles. This new method of implantation presents a considerable improvement compared to existing modes of device insertion. Conclusions: Acute brain injuries following insertion of e.g. ultra-flexible electrodes, can be reduced by providing an outer coat of ultra-slippery thawing ice. No adverse effect of lowered implant temperature was found, opening the possibility of locking fragile electrode construct configurations in frozen gelatin, prior to implantation into the brain.
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| 5. |
- Etemadi, Leila, et al.
(författare)
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Embedded Ultrathin Cluster Electrodes for Long-Term Recordings in Deep Brain Centers
- 2016
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:5
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Tidskriftsartikel (refereegranskat)abstract
- Neural interfaces which allow long-term recordings in deep brain structures in awake freely moving animals have the potential of becoming highly valuable tools in neuroscience. However, the recording quality usually deteriorates over time, probably at least partly due to tissue reactions caused by injuries during implantation, and subsequently micro-forces due to a lack of mechanical compliance between the tissue and neural interface. To address this challenge, we developed a gelatin embedded neural interface comprising highly flexible electrodes and evaluated its long term recording properties. Bundles of ultrathin parylene C coated platinum electrodes (N = 29) were embedded in a hard gelatin based matrix shaped like a needle, and coated with Kollicoat™ to retard dissolution of gelatin during the implantation. The implantation parameters were established in an in vitro model of the brain (0.5% agarose). Following a craniotomy in the anesthetized rat, the gelatin embedded electrodes were stereotactically inserted to a pre-target position, and after gelatin dissolution the electrodes were further advanced and spread out in the area of the subthalamic nucleus (STN). The performance of the implanted electrodes was evaluated under anesthesia, during 8 weeks. Apart from an increase in the median-noise level during the first 4 weeks, the electrode impedance and signal-to-noise ratio of single-units remained stable throughout the experiment. Histological postmortem analysis confirmed implantation in the area of STN in most animals. In conclusion, by combining novel biocompatible implantation techniques and ultra-flexible electrodes, long-term neuronal recordings from deep brain structures with no significant deterioration of electrode function were achieved.
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| 6. |
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| 7. |
- Thorbergsson, Palmi Thor, et al.
(författare)
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Strategies for high-performance resource-efficient compression of neural spike recordings.
- 2014
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:4
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Tidskriftsartikel (refereegranskat)abstract
- Brain-machine interfaces (BMIs) based on extracellular recordings with microelectrodes provide means of observing the activities of neurons that orchestrate fundamental brain function, and are therefore powerful tools for exploring the function of the brain. Due to physical restrictions and risks for post-surgical complications, wired BMIs are not suitable for long-term studies in freely behaving animals. Wireless BMIs ideally solve these problems, but they call for low-complexity techniques for data compression that ensure maximum utilization of the wireless link and energy resources, as well as minimum heat dissipation in the surrounding tissues. In this paper, we analyze the performances of various system architectures that involve spike detection, spike alignment and spike compression. Performance is analyzed in terms of spike reconstruction and spike sorting performance after wireless transmission of the compressed spike waveforms. Compression is performed with transform coding, using five different compression bases, one of which we pay special attention to. That basis is a fixed basis derived, by singular value decomposition, from a large assembly of experimentally obtained spike waveforms, and therefore represents a generic basis specially suitable for compressing spike waveforms. Our results show that a compression factor of 99.8%, compared to transmitting the raw acquired data, can be achieved using the fixed generic compression basis without compromising performance in spike reconstruction and spike sorting. Besides illustrating the relative performances of various system architectures and compression bases, our findings show that compression of spikes with a fixed generic compression basis derived from spike data provides better performance than compression with downsampling or the Haar basis, given that no optimization procedures are implemented for compression coefficients, and the performance is similar to that obtained when the optimal SVD based basis is used.
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| 8. |
- Thorbergsson, Palmi Thor, et al.
(författare)
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Computationally efficient simulation of extracellular recordings with multielectrode arrays
- 2012
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Ingår i: Journal of Neuroscience Methods. - : Elsevier BV. - 1872-678X .- 0165-0270. ; 211:1, s. 133-144
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we present a novel, computationally and memory efficient way of modeling the spatial dependency of measured spike waveforms in extracellular recordings of neuronal activity. We use compartment models to simulate action potentials in neurons and then apply linear source approximation to calculate the resulting extracellular spike waveform on a three dimensional grid of measurement points surrounding the neurons. We then apply traditional compression techniques and polynomial fitting to obtain a compact mathematical description of the spatial dependency of the spike waveform. We show how the compressed models can be used to efficiently calculate the spike waveform from a neuron in a large set of measurement points simultaneously and how the same procedure can be inversed to calculate the spike waveforms from a large set of neurons at a single electrode position. The compressed models have been implemented into an object oriented simulation tool that allows the simulation of multielectrode recordings that capture the variations in spike waveforms that are expected to arise between the different recording channels. The computational simplicity of our approach allows the simulation of a multi-channel recording of signals from large populations of neurons while simulating the activity of every neuron with a high level of detail. We have validated our compressed models against the original data obtained from the compartment models and we have shown, by example, how the simulation approach presented here can be used to quantify the performance in spike sorting as a function of electrode position.
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| 9. |
- Thorbergsson, Palmi Thor, et al.
(författare)
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Minimizing data transfer with sustained performance in wireless brain–machine interfaces
- 2012
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Ingår i: Journal of Neural Engineering. - : IOP Publishing. - 1741-2560 .- 1741-2552. ; 9:3
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Tidskriftsartikel (refereegranskat)abstract
- Brain–machine interfaces (BMIs) may be used to investigate neural mechanisms or to treat the symptoms of neurological disease and are hence powerful tools in research and clinical practice. Wireless BMIs add flexibility to both types of applications by reducing movement restrictions and risks associated with transcutaneous leads. However, since wireless implementations are typically limited in terms of transmission capacity and energy resources, the major challenge faced by their designers is to combine high performance with adaptations to limited resources. Here, we have identified three key steps in dealing with this challenge: (1) the purpose of the BMI should be clearly specified with regard to the type of information to be processed; (2) the amount of raw input data needed to fulfill the purpose should be determined, in order to avoid over- or under-dimensioning of the design; and (3) processing tasks should be allocated among the system parts such that all of them are utilized optimally with respect to computational power, wireless link capacity and raw input data requirements. We have focused on step (2) under the assumption that the purpose of the BMI (step 1) is to assess single- or multi-unit neuronal activity in the central nervous system with single-channel extracellular recordings. The reliability of this assessment depends on performance in detection and sorting of spikes. We have therefore performed absolute threshold spike detection and spike sorting with the principal component analysis and fuzzy c-means on a set of synthetic extracellular recordings, while varying the sampling rate and resolution, noise level and number of target units, and used the known ground truth to quantitatively estimate the performance. From the calculated performance curves, we have identified the sampling rate and resolution breakpoints, beyond which performance is not expected to increase by more than 1–5%. We have then estimated the performance of alternative algorithms for spike detection and spike sorting in order to examine the generalizability of our results to other algorithms. Our findings indicate that the minimization of recording noise is the primary factor to consider in the design process. In most cases, there are breakpoints for sampling rates and resolution that provide guidelines for BMI designers in terms of minimum amount raw input data that guarantees sustained performance. Such guidelines are essential during system dimensioning. Based on these findings we conclude by presenting a quantitative task-allocation scheme that can be followed to achieve optimal utilization of available resources.
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| 10. |
- Thorbergsson, Palmi Thor
(författare)
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Signal Modeling and Data Reduction for Wireless Brain-Machine Interfaces
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Brain-machine interfaces (BMIs) provide a uni- or bidirectional communication link between the central nervous system and the outside world. This link facilitates the studying of neuronal mechanisms underlying behavior as well as the treatment of neurological disease. Wired BMIs are limited in the sense that they restrict the mobility of the subject and they increase the risks for post-surgical complications. While wireless BMIs ideally solve these problems, their designers face the challenge of combining high information throughput with limited wireless link capacity and energy resources. Therefore, measures have to be taken to maximize the utilization of the wireless link and energy resources by designing computationally efficient and reliable data reduction techniques. The design and validation of such techniques requires the presence of well defined test data, where the true information content is known a priori. This thesis deals with both the modeling of the neural signal to provide realistic and practical means of generating test data, as well as low-complexity methods for data reduction that lead to efficient utilization of the wireless link and the energy resources at hand. The main part of the thesis is a collection of papers that address these aspects. Paper I presents the design and implementation of a simple telemetry system for the wireless transmission of neural data from four measurement channels. This paper highlights some of the design challenges that need to be considered and thereby serves as a pilot investigation for the following papers. Paper II presents a recording model and a simulation tool for generating single-channel test recordings for the validation of algorithms for spike detection and spike sorting. Having set up the geometry of the recording, each neuron is assigned a random spike waveforms from a library of experimentally obtained templates. The contribution of each neuron is generated by adding the corresponding waveform at randomly generated spike times and the spike trains are added up to form the entire recording. Spike times are modeled by a renewal process. The model is evaluated in terms of realism by comparing the power spectral density and autocorrelation of synthetic biological noise generated by the model, to noise obtained from real recordings. Paper III extends the finite spike library provided in paper II in order to provide a greater, still realistic, variation in spike waveforms. Principal component analysis and Gaussian mixture models are used to model the statistical properties of the original spike library and the statistical model can then be used to generate an arbitrary number of spike wavforms with realistic properties. The extension is shown to be usable in providing access to arbitrarily large libraries of spikes with realistic properties. Paper IV uses the models presented in papers II and III to explore the effects of sampling rate and resolution on the performance in spike detection and spike sorting at various noise levels and numbers of target neurons. Performance curves are analyzed to find sampling rate and resolution breakpoints for spike detection and spike sorting. These breakpoints serve as guidelines for selecting sampling parameters when dimensioning wireless BMIs. The paper presents methods for quantifying the accuracy in spike detection and spike sorting and provides general insight into how the performance of these processing tasks are influenced by sampling parameters, noise level and number of target units. Paper V presents a preliminary study of the characteristic relationship between physical electrode movements and movements of detected spikes in feature space, using the signal models presented in paper VI. We then model this relationship as a linear transformation between two coordinate systems and show that given that a training procedure is introduced at the time of electrode insertion, future electrode movements can be estimated directly from the feature space representation of spikes. Paper VI presents a new, computationally and memory efficient approach for modeling the extracellular signal. We use traditional compression techniques and polynomial fitting to derive a deterministic model that can be used for fast calculation of spike waveforms in arbitrary measurement points surrounding a compartment model of a neuron. Four different neuron models are derived and they are all shown to accurately predict the spike waveforms produced by the original compartment model, both in terms of spike shape and amplitude. The model is implemented into a simulation tool that efficiently and realistically synthesizes recordings with multielectrode arrays of arbitrary geometries. Paper VII addresses low-complexity methods of compressing detected spike waveforms in wireless BMIs to ensure efficient use of the wireless link and energy resources at hand. The paper shows that given the correct choice of overall system architecture and spike detector, spike waveforms can be compressed with fixed generic compression bases, derived from experimentally obtained spike libraries, without significant loss in accuracy in spike reconstruction and sorting.
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