R-3 Repository :: Browsing by Author "Kemere, Caleb"

Browsing by Author "Kemere, Caleb"

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A framework to identify structured behavioral patterns within rodent spatial trajectories
(Springer Nature, 2021) Donnarumma, Francesco; Prevete, Roberto; Maisto, Domenico; Fuscone, Simone; Irvine, Emily M.; van der Meer, Matthijs A.A.; Kemere, Caleb; Pezzulo, Giovanni
Animal behavior is highly structured. Yet, structured behavioral patterns—or “statistical ethograms”—are not immediately apparent from the full spatiotemporal data that behavioral scientists usually collect. Here, we introduce a framework to quantitatively characterize rodent behavior during spatial (e.g., maze) navigation, in terms of movement building blocks or motor primitives. The hypothesis that we pursue is that rodent behavior is characterized by a small number of motor primitives, which are combined over time to produce open-ended movements. We assume motor primitives to be organized in terms of two sparsity principles: each movement is controlled using a limited subset of motor primitives (sparse superposition) and each primitive is active only for time-limited, time-contiguous portions of movements (sparse activity). We formalize this hypothesis using a sparse dictionary learning method, which we use to extract motor primitives from rodent position and velocity data collected during spatial navigation, and successively to reconstruct past trajectories and predict novel ones. Three main results validate our approach. First, rodent behavioral trajectories are robustly reconstructed from incomplete data, performing better than approaches based on standard dimensionality reduction methods, such as principal component analysis, or single sparsity. Second, the motor primitives extracted during one experimental session generalize and afford the accurate reconstruction of rodent behavior across successive experimental sessions in the same or in modified mazes. Third, in our approach the number of motor primitives associated with each maze correlates with independent measures of maze complexity, hence showing that our formalism is sensitive to essential aspects of task structure. The framework introduced here can be used by behavioral scientists and neuroscientists as an aid for behavioral and neural data analysis. Indeed, the extracted motor primitives enable the quantitative characterization of the complexity and similarity between different mazes and behavioral patterns across multiple trials (i.e., habit formation). We provide example uses of this computational framework, showing how it can be used to identify behavioural effects of maze complexity, analyze stereotyped behavior, classify behavioral choices and predict place and grid cell displacement in novel environments.
Analysis of an open source, closed-loop, realtime system for hippocampal sharp-wave ripple disruption
(IOP Publishing, 2018) Dutta, Shayok; Ackermann, Etienne; Kemere, Caleb
Objective. The ability to modulate neural activity in a closed-loop fashion enables causal tests of hypotheses which link dynamically-changing neural circuits to specific behavioral functions. One such dynamically-changing neural circuit is the hippocampus, in which momentary sharp-wave ripple (SWR) events—≈ 100 ms periods of large 150–250 Hz oscillations—have been linked to specific mnemonic functions via selective closed-loop perturbation. The limited duration of SWR means that the latency in systems used for closed-loop interaction is of significant consequence compared to other longer-lasting circuit states. While closed-loop SWR perturbation is becoming more wide-spread, the performance trade-offs involved in building a SWR disruption system have not been explored, limiting the design and interpretation of paradigms involving ripple disruption. Approach. We developed and evaluated a low-latency closed-loop SWR detection system implemented as a module to an open-source neural data acquisition software suite capable of interfacing with two separate data acquisition hardware platforms. We first use synthetic data to explore the parameter space of our detection algorithm, then proceed to quantify the realtime in vivo performance and limitations of our system. Main results. We evaluate the realtime system performance of two data acquisition platforms, one using USB and one using ethernet for communication. We report that signal detection latency decomposes into a data acquisition component of 7.5–13.8 ms and 1.35–2.6 ms for USB and ethernet hardware respectively, and an algorithmic component which varies depending on the threshold parameter. Using ethernet acquisition hardware, we report that an algorithmic latency in the range of ≈20–66 ms can be achieved while maintaining <10 false detections per minute, and that these values are highly dependent upon algorithmic parameter space trade-offs. Significance. By characterizing this system in detail, we establish a framework for analyzing other closed-loop neural interfacing systems. Thus, we anticipate this modular, open-source, realtime system will facilitate a wide range of carefully-designed causal closed-loop experiments.
Beta and Low Gamma Oscillation Dynamics in Primary Motor Cortex of 6-OHDA hemi-Parkinson’s Rat during Voluntary Movement Initiation
(2020-05-27) Chen, Ziying; Kemere, Caleb
The reduction in the number of dopamine (DA) cells in subthalamic nucleus (STN) is the pathological signature of the patients with Parkinson’s Disease. With the loss of DA regulation, abnormally high power of electrophysiological oscillations, from 20 to 45 Hz near beta and low gamma band, in primary motor cortex (M1) is observed and is believed to be the reason of bradykinesia in DA patients. Studies using 6-hydroxydopamine (6-OHDA) rat model showed the frequency and power modulation of the abnormal oscillation during movement. However, constrained environment, for instance, treadmill for forced movement , did not demonstrate the voluntary aspect or allow to target the transition between behavioral statuses of 6-OHDA-lesioned rats. And the temporal dynamics of the abnormal rhythm during behavior and how it is different from healthy rat’s M1 signal oscillation is still not understood. Here, we used simultaneous video tracking and electrocorticography (ECoG) recording of M1 in both hemispheres of 6-OHDA-induced hemiparkinsonian rats during free moving on customized tracks. Behavioral performance degradation of rats from early lesion stage to late lesion stage was showed with the change of defined movement initiation (MI) events. Based on the findings, we suggest that there are components in different frequency bands in the abnormal oscillation in M1 of 6-OHDA lesioned rats and they have different likelihoods to happen during the initiation of a behavior. The potential multiple types of rhythm inside M1 could help us understand the dynamics of lack of regulation of DA cells in STN.
Deep imaging in scattering media with selective plane illumination microscopy
(SPIE, 2016) Pediredla, Adithya Kumar; Zhang, Shizheng; Avants, Ben; Ye, Fan; Nagayama, Shin; Chen, Ziying; Kemere, Caleb; Robinson, Jacob T.; Veeraraghavan, Ashok; Bioengineering; Electrical and Computer Engineering; Computer Science
In most biological tissues, light scattering due to small differences in refractive index limits the depth of optical imaging systems. Two-photon microscopy (2PM), which significantly reduces the scattering of the excitation light, has emerged as the most common method to image deep within scattering biological tissue. This technique, however, requires high-power pulsed lasers that are both expensive and difficult to integrate into compact portable systems. Using a combination of theoretical and experimental techniques, we show that if the excitation path length can be minimized, selective plane illumination microscopy (SPIM) can image nearly as deep as 2PM without the need for a high-powered pulsed laser. Compared to other single-photon imaging techniques like epifluorescence and confocal microscopy, SPIM can image more than twice as deep in scattering media (∼10 times the mean scattering length). These results suggest that SPIM has the potential to provide deep imaging in scattering media in situations in which 2PM systems would be too large or costly.
Depth Limit of Imaging through Scattering Media using Selective Plane of Illumination Microscopy (SPIM)
(2015-12-03) Zhang, Shizheng; Veeraraghavan, Ashok; Robinson, Jacob T; Kemere, Caleb
In most biological tissues, the maximum optical imaging depth is limited by light scattering. Confocal and multi-photon microscopy have been developed to increase the imaging depth by limiting the amount of scattered light that reaches the detector, however, these techniques acquire images one point at a time resulting in reduced image acquisition speed. Recently, Selective Plane of Illumination Microscopy (SPIM) has emerged as an alternative 3D microscopy technique with faster image acquisition speeds, enabled by capturing entire 2D planes rather than individual points. While the advantages of SPIM for high speed imaging are understood, here we demonstrate that SPIM also increases the imaging depth in scattering media compared to confocal and epifluorescence techniques. We show both analytically and experimentally that SPIM can image 2-3 times deeper than confocal microscopy (~10x the mean scattering length). The primary reason for the deeper imaging capability of SPIM is the fact that off-axis illumination reduces the out-of-focus fluorescence above the imaging plane. We find that for scattering media, multi- photon microscopy can image deeper than SPIM; however, the fact that SPIM does not require a high-power pulsed laser makes this approach a lower cost alternative to multi-photon microscopy for imaging into scattering media beyond the depths of conventional single photon microscopy techniques.
Dynamic Nuclear Polarization of Silicon for Targeted Molecular Imaging
(2019-04-17) McCowan, Caitlin; Kemere, Caleb; Bhattacharya, Pratip K.
Colorectal cancer is the second highest cause of cancer-related deaths and is the third most commonly diagnosed cancer in America. Although there are currently available screening methods such as colonoscopy, many patients remain undiagnosed until the disease has spread and thus likely advanced beyond hope of curative treatment. Also, colonoscopy carries the risk of intestinal perforation and is less apt to identify small or flat lesions. Patients diagnosed after metastasis make up 21% of all colorectal cancer cases, with a 5-year survival rate of only 13.5%. This presents an opportunity to improve screening methods with higher accuracy and safer implementation, namely through magnetic resonance imaging (MRI) of hyperpolarized silicon particles functionalized to specifically target colorectal cancer. MRI is a commonly used imaging modality that does not require ionizing radiation. Nevertheless, sensitivity and specificity are considered to be the major drawbacks regarding MRI. One method to improve the sensitivity is through hyperpolarization, a technique used to increase signal measured with MRI by at least 10,000-fold. Silicon is a promising candidate for in vivo medical applications due to its biocompatibility. Additionally, silicon is compatible with hyperpolarization due to its MR active isotope 29Si making up 4.7% of naturally occurring silicon. I have investigated the ability to functionalize silicon particles for targeted molecular imaging of colorectal cancer in vivo through hyperpolarized MRI. Furthermore, I have explored the feasibility of utilizing hyaluronic acid-based hydrogels to improve particle targeting ability.
Dynamics of brain networks during reading
(2015-10-05) Whaley, Meagan; Cox, Steven J; Dabaghian, Yuri; Kemere, Caleb; Tandon, Nitin
We recorded electrocorticographic (ECoG) data from 15 patients with intractable epilepsy during a word completion task to precisely describe the spatiotemporal brain dynamics underlying word reading. Using a novel technique of analyzing grouped ECoG, cortical regions distributed throughout the left hemisphere were identified as significantly active versus baseline during our word stem completion task. Regions of activity spread from fusiform to frontal regions, including pars opercularis, pars triangularis, and pre, post, and subcentral gyri during the time period approaching articulation onset. The ECoG data recorded from electrodes within these regions were fit into linear multivariate autoregressive models, which precisely reveal the time, frequency, and magnitude of information flow between localized brain regions. Grouped network dynamics were quantified with two metrics of evaluating statistical significance of post-stimulus interactions compared to baseline. Results from both methods reveal bidirectional exchanges between frontal regions with fusiform, supporting theories which incorporate top-down and bottom-up processing during single word reading.
Editorial: Towards the Next Generation of Deep Brain Stimulation Therapies: Technological Advancements, Computational Methods, and New Targets
(Frontiers, 2021) Santaniello, Sabato; McConnell, George C.; Gale, John T.; Faghih, Rose T.; Kemere, Caleb; Hilliard, Justin D.; Han, Martin
Evaluation of Aerosol Particle Leak and Standard Surgical Mask Fit With 3 Elastomeric Harness Designs
(American Medical Association, 2022) Ingabire, Jeannette; McKenney, Hannah; Sebesta, Charles; Badhiwala, Krishna; Kemere, Caleb; Kapur, Sahil; Robinson, Jacob T.
Extended Poisson Gaussian-Process Latent Variable Model for Unsupervised Neural Decoding
(2023-09-08) Luo, Della Daiyi; Kemere, Caleb
Dimension reduction on neural activity paves a way for unsupervised neural decoding by dissociating the measurement of internal neural state repetition from the measurement of external variable tuning. The Poisson Gaussian-process latent variable model (P-GPLVM) is a powerful tool to discover the low-dimensional latent structure for high-dimensional spike trains with minimum assumptions. This thesis extends the P-GPLVM to enable the latent variable inference of new data constrained by the previously learned smoothness and mapping information, thereby allowing the estimation of internal state repetition in new neural activity. A principled approach for analyzing temporally-compressed patterns of activity (i.e. population burst events (PBEs)), and metrics for assessing the new latent variables are described. From hippocampal neural activity during active maze exploration, P-GPLVM learns a latent space encoding animal position and context. By inferring the latent variables of new neural data during running, certain internal neural state is found repeated, validated by the similar running experiences encoded in its nearby neural trajectories of the training data manifold. Further, repetition of internal neural states can be measured for neural activity during PBEs, allowing the identification for versatile replay patterns. Thus, this extended P-GPLVM framework enables effective unsupervised decoding for neural activity both during behavior and during PBEs.
Hippocampal awake replay in fear memory retrieval
(Springer Nature, 2017) Wu, Chun-Ting; Haggerty, Daniel; Kemere, Caleb; Ji, Daoyun
Hippocampal place cells are key to episodic memories. How these cells participate in memory retrieval remains unclear. After rats acquired a fear memory by receiving mild footshocks in a shock zone on a track, we analyzed place cells when the animals were placed on the track again and displayed an apparent memory retrieval behavior: avoidance of the shock zone. We found that place cells representing the shock zone were reactivated, despite the fact that the animals did not enter the shock zone. This reactivation occurred in ripple-associated awake replay of place cell sequences encoding the paths from the animal's current positions to the shock zone but not in place cell sequences within individual cycles of theta oscillation. The result reveals a specific place-cell pattern underlying inhibitory avoidance behavior and provides strong evidence for the involvement of awake replay in fear memory retrieval.
Hippocampal Encoding of Space Induced by Novel Auditory VR System using One-Photon Miniaturized Microscope
(2020-04-24) Gao, Sibo; Kemere, Caleb; McGinley, Matthew
In virtual reality settings, spatial navigation in animal models has traditionally been studied using primarily visual cues. However, auditory cues play an important role in navigation for animals, especially when the visual system cannot detect objects or predators in the dark. We have developed a virtual reality system defined exclusively by auditory landmarks for head-fixed mice performing a navigation task. We report behavioral evidence that mice can learn to navigate in our task. Namely, we observed anticipatory licking and modest anticipatory slowing preceding the reward region. Furthermore, we found that the animal’s licking behavior changes when switching from a familiar virtual environment to a novel virtual environment, followed by reverting to normal licking behavior after the familiar virtual environment is re-introduced within the same session. While animals carried out the task, we performed in-vivo calcium imaging in the CA1 region of the hippocampus using a modified Miniscope system. We envision that this approach has the potential to provide new insight into how animals respond to stimuli using spatial aspects of sound in an environment. (abstract adapted from Gao et al., EMBC’20, forthcoming).
Investigating irregularly patterned deep brain stimulation signal design using biophysical models
(Frontiers Media S.A., 2015-06) Summerson, Samantha R.; Aazhang, Behnaam; Kemere, Caleb
Parkinson's disease (PD) is a neurodegenerative disorder which follows from cell loss of dopaminergic neurons in the substantia nigra pars compacta (SNc), a nucleus in the basal ganglia (BG). Deep brain stimulation (DBS) is an electrical therapy that modulates the pathological activity to treat the motor symptoms of PD. Although this therapy is currently used in clinical practice, the sufficient conditions for therapeutic efficacy are unknown. In this work we develop a model of critical motor circuit structures in the brain using biophysical cell models as the base components and then evaluate performance of different DBS signals in this model to perform comparative studies of their efficacy. Biological models are an important tool for gaining insights into neural function and, in this case, serve as effective tools for investigating innovative new DBS paradigms. Experiments were performed using the hemi-parkinsonian rodent model to test the same set of signals, verifying the obedience of the model to physiological trends. We show that antidromic spiking from DBS of the subthalamic nucleus (STN) has a significant impact on cortical neural activity, which is frequency dependent and additionally modulated by the regularity of the stimulus pulse train used. Irregular spacing between stimulus pulses, where the amount of variability added is bounded, is shown to increase diversification of response of basal ganglia neurons and reduce entropic noise in cortical neurons, which may be fundamentally important to restoration of information flow in the motor circuit.
Latent variable models for hippocampal sequence analysis
(2019-06-27) Ackermann, Etienne Rudolph; Kemere, Caleb
Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Indeed, the activity of ensembles of neurons within the hippocampus is thought to enable memory formation, storage, recall, and even decision making. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. Notably, these PBEs occur during times of inactivity, so that their representations cannot easily be matched with observable animal behavior. In my thesis, I present an approach to uncover temporal structure within hippocampal output patterns during PBEs. More specifically, I use hidden Markov models (HMMs) to study PBEs observed in rats during exploration of both linear tracks and open fields, and I demonstrate that estimated models are consistent with a spatial map of the environment. Moreover, I demonstrate how the model can be used to identify hippocampal replay without recourse to the place code. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Moreover, by forming models independent of animal behavior, I lay the groundwork for studies of non-spatial memory. Next, I present a new model, the "clusterless" switching Poisson hidden Markov model, which extends my work on HMMs of PBEs to the case where we only have multiunit (unsorted) spikes. Indeed, spike sorting is challenging, time-consuming, often subjective (not reproducible), and throws away potentially valuable information from unsorted spikes, as well as our certainty about the cluster assignments. It has previously been shown that we can often do just as well, or in some cases even better, if we forego the spike sorting process altogether, and work directly with the unsorted data. Consequently, my clusterless HMM will enable us to combine the benefits of unsupervised learning for internally generated neural activity, with the benefits of clusterless approaches (more data leading to higher fidelity, especially at fine temporal scales, and additional probabilistic / soft information to exploit). I demonstrate the model's ability to recover model parameters for simulated data, and show that it is able to learn a spatially-consistent representation of the environment from real experimental data.
Magneto-mechanical Neuromodulation
(2015-04-24) Murphy, Daniel B; Robinson, Jacob T; Kemere, Caleb; Hafner, Jason
Noninvasive control of the electrical activity in specific cells in the brain would transform fundamental neuroscience research and the development of therapeutic technologies. Current neural stimulation methods such as electrical or optogenetic stimulation achieve high levels of specificity, but are invasive. Magnetic stimulation is a potentially noninvasive stimulation modality because mammalian tissue is nearly transparent to magnetic fields. In this thesis we investigate a new neural modulation method based on magnetic fields that can potentially achieve similar levels of specificity with much lower invasiveness. Our method will use externally applied, uniform magnetic fields that induce dipole-dipole forces between superparamagnetic iron oxide nanoparticles bound to Piezo1, a mechanically sensitive ion channel. Based on our calculations and early preliminary results, these mechanical forces will be sufficient to open Piezo1, leading to cationic currents, that will alter cell activity. Expression of mutant Piezo1 protein can be targeted to genetically specific populations of cells by means of cell-type specific promoters in transgenic animals. This method is expected to achieve accurate control of genetically specific populations of cells, thereby enabling better research to answer fundamental biological questions and develop novel medical therapies.
MiniFAST: A Fast and Sensitive Microscope for in vivo Neural Imaging
(2020-06-30) Juneau, Jill; Kemere, Caleb
Imaging methods in neuroscience are used to visualize and record neural activity from large cell populations. Within imaging modalities, miniaturized microscopes, which typically weigh < 4 grams, have become widely used and feature the added advantage of recording in vivo neural activity with unrestrained behavior. The current designs have shown exciting results from imaging fluorescent genetically encoded calcium indicators (GECIs) which have bright and slow dynamics (> 1 s) easily captured by most image sensors at frame rates of 30 Hz or less. However, there are many neuroscience applications which would benefit from using other emerging neural indicators, such as fluorescent genetically-encoded voltage indicators (GEVIs) that have faster temporal resolution to match neuron spiking, or bioluminescent indicators which can eliminate autofluorescence and photobleaching that occurs in fluorescent indicators. Despite their potential, miniaturized microscopes are not in use with these indicators likely due to their inability to image at high speeds to capture the fast dynamics of GEVIs and inability to image with high sensitivity required for signals with low signal to noise ratio (SNR) inherent to current versions of GEVIs and bioluminescent indicators. We addressed this problem by integrating the latest CMOS image sensor technology into a popular open-source miniaturized microscope platform. MiniFAST is a fast and sensitive miniaturized microscope capable of 1080p video, 1.5um resolution, frame rates up to 500-Hz and high gain ability (up to 70 dB) to image in extremely low light conditions. We also report results of high speed 500-Hz in vitro imaging of a GEVI and ~300-Hz in vivo imaging of transgenic Thy1-GCaMP6f mice. Finally, we show the potential for a reduction in photobleaching effects by using high gain imaging with ultra-low excitation light power (0.05mW) at 60 Hz frame rates while still resolving Ca2+ spiking activity. Our results extend miniaturized microscope capabilities in high-speed imaging, high sensitivity and increased resolution opening the door for the open-source community to use fast and dim neural indicators.
Novel Mechanisms for Magnetogenetic Neuromodulation
(2017-10-24) Polali, Sruthi; Robinson, Jacob; Natelson, Douglas; Clementi, Cecilia; Kemere, Caleb
Magnetogenetic tools permit wireless stimulation of specific neurons located deep inside the brain of freely moving animals: a capability that improves the study of neural activity and its correlation to behavior. Recently, a fully genetically encoded, magnetically sensitive protein chimera consisting of ferritin and TRPV4, dubbed Magneto2.0, was shown to elicit action potentials in neurons when exposed to a magnetic field. The iron-sequestering protein, ferritin serves as the magnetically sensitive domain in this chimera, while TRPV4 is a cation selective channel that responds to mechanical and temperature stimuli. While it was suggested that the mode of operation was through mechanical stimulation of the channel by ferritin, later calculations show that the forces exerted by ferritin nanoparticles are orders of magnitude lower than what is required for channel gating. We propose an alternate mechanisms based on the magnetocaloric effect to explain how paramagnetic ferritin could gate the thermally sensitive TRPV4. A magnetic field reduces the entropy of the ferritin nanoparticles when its magnetic spins align, resulting in an increase in temperature that in turn gates the heat-sensitive TRPV4 channel. We support our theory with calculations and experimental data that demonstrate that the observed responses are indeed thermally mediated. To further prove the magnetocaloric mechanism, we designed a novel magnetogenetic channel consisting of fusion of ferritin and cold-sensitive channel TRPM8, dubbed MagM8. This channel is activated due to decrease in temperature caused by increase in entropy during demagnetization of ferritin. In addition to reconciling biological observations with physical properties of genetically encoded magnetic nanoparticles, our explanation will also aid the design of new magnetogenetic tools with improved magnetic sensitivity.
Projections and the Potential Societal Impact of the Future of Neurotechnologies
(Frontiers Media S.A., 2021) Gaudry, Kate S.; Ayaz, Hasan; Bedows, Avery; Celnik, Pablo; Eagleman, David; Grover, Pulkit; Illes, Judy; Rao, Rajesh P. N.; Robinson, Jacob T.; Thyagarajan, Krishnan; The Working Group on Brain-Interfacing Devices in 2040; Bains, Nena; Brigagliano, John; Carter, Robert; Kemere, Caleb; Mathison, Mark P.; Neiditz, Jon; Rommelfanger, Karen; Snyder, Joseph; Bioengineering; Electrical and Computer Engineering; Applied Physics
Traditionally, recording from and stimulating the brain with high spatial and temporal resolution required invasive means. However, recently, the technical capabilities of less invasive and non-invasive neuro-interfacing technology have been dramatically improving, and laboratories and funders aim to further improve these capabilities. These technologies can facilitate functions such as multi-person communication, mood regulation and memory recall. We consider a potential future where the less invasive technology is in high demand. Will this demand match that the current-day demand for a smartphone? Here, we draw upon existing research to project which particular neuroethics issues may arise in this potential future and what preparatory steps may be taken to address these issues.
Rapid and Continuous Modulation of Hippocampal Network State during Exploration of New Places
(Public Library of Science, 2013-09) Kemere, Caleb; Carr, Margaret F.; Karlsson, Mattias P.; Frank, Loren M.
Hippocampal information processing is often described as two-state, with a place cell state during movement and a reactivation state during stillness. Relatively little is known about how the network transitions between these different patterns of activity during exploration. Here we show that hippocampal network changes quickly and continuously as animals explore and become familiar with initially novel places. We measured the relationship between moment-bymoment changes in behavior and information flow through hippocampal output area CA1 in rats. We examined local field potential (LFP) patterns, evoked potentials and ensemble spiking and found evidence suggestive of a smooth transition from strong CA3 drive of CA1 activity at low speeds to entorhinal cortical drive of CA1 activity at higher speeds. These changes occurred with changes in behavior on a timescale of less than a second, suggesting a continuous modulation of information processing in the hippocampal circuit as a function of behavioral state.
Rodent deep brain stimulation hardware and mechanisms
(2018-08-10) Lewis, Eric; Kemere, Caleb
This thesis developed an inexpensive, wirelessly programmable deep brain stimulator to evaluate novel stimulation patterns in rodent Parkinson’s Disease (PD). Current deep brain stimulators for Parkinson’s patients only benefit two-thirds of people implanted. The need to develop more effective treatments for Parkinson’s inspired genetic disease models to study the mechanisms of the disease. Stimulators for rodent models exist but can be improved. The head-mounted stimulator in this thesis builds on prior designs through Near Field Communication (NFC) to program stimulator settings. Additionally, the stimulator can provide uniformly distributed offsets to pulse times called ”jitter.” The stimulator efficacy was evaluated in 6- Hydroxydopamine (OHDA) rats through methamphetamine induced rotation studies. High Frequency Stimulation (HFS) corrected ipsilateral rotation and induced transient contralateral rotation in agreement with prior behavioral studies. With this open source hardware, labs can implement novel deep brain stimulation patterns chronically in new disease models to improve stimulation performance for Parkinson’s.

Browsing by Author "Kemere, Caleb"

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