The UWIN seminar series continue in March 2020 with a pair of short talks by Azadeh Yazdan and Adrian KC Lee. The seminar is on Wednesday, March 11, 2020 at 3:30pm in Husky Union Building (HUB) 337. Refreshments will be served prior to the talks.
“Targeted cortical reorganization using optogenetics in non-human primates”
Azadeh Yazdan, Assistant Professor, Departments of Bioengineering and Electrical & Computer Engineering, University of Washington
“Inferring function connectivity in auditory attention tasks”
Adrian KC Lee, Professor, Department of Speech and Hearing Sciences, University of Washington
“Targeted cortical reorganization using optogenetics in non-human primates” (Azadeh Yazdan)
The brain shows marked plasticity across a variety of learning and memory tasks as well as during recovery after injury. Many have proposed to leverage this innate plasticity using brain stimulation to treat neural disorders. Implementing such treatments requires advanced engineering tools and a thorough understanding of how stimulation-induced plasticity drives changes in network dynamics and connectivity at a large scale and across multiple brain areas. In this talk, I will cover our efforts to investigate targeted stimulation of sensorimotor cortex to drive cortical plasticity towards functional recovery. We have developed a large-scale interface consisting of state-of-the-art electrophysiology and optogenetics to simultaneously record and manipulate activity from about 5 cm2 of sensorimotor cortex in awake behaving macaques. Using this interface, for the first time, we have shown the feasibility of inducing targeted changes in sensorimotor networks using optogenetics. Furthermore, we have incorporated the capability of producing ischemic lesions in the same interface enabling us to stimulate the cortex around the site of injury and monitor functional recovery via change in blood flow, neurophysiology and behavior. Currently we are using these technologies towards developing therapeutic interventions for neurological disorders such as stroke.
“Inferring function connectivity in auditory attention tasks” (Adrian KC Lee)
Connectivity of the dynamical brain at a systems neuroscience level is a relatively underexplored area, owing perhaps to the unsolved challenge of modeling structured relationships between time series in a big data setting. We have collected MEG data to reveal the connectivity of the auditory attentional network when participants were asked to either maintain or switch attention between two competing sound streams. This computational development paves the way to study the neurobiological basis of a still-controversial clinical construct known as central auditory processing disorder. Specifically, this approach provides a way for us to answer this open question: whether the connectivity structure of the auditory attentional network helps to elucidate the neural underpinnings of certain aspects of auditory dysfunction, e.g., the inability to maintain or switch attention between speakers.
Join us in welcoming UWIN’s newest undergraduate and post-baccalaureate fellows! Six undergraduate students and five post-baccalaureate researchers were awarded 2020 UWIN Fellowships. You can read all about their exciting research below, and follow the links to see all of UWIN’s undergraduate and post-baccalaureate fellows.
2020 UWIN Undergraduate Fellows
Hailey Chadwick (2020 fellow) is an undergraduate student in Biology working with Samira Moorjani in the department of Physiology and Biophysics. Hailey’s project focuses on changes in functional connectivity in the corticospinal tract during recovery from chronic spinal-cord injury. By using environmental enrichment in combination with neuromodulator delivery to promote behavioral recovery in a rat model of spinal cord injury, while documenting changes in neuronal connectivity related to motor function in the paralyzed limb, Hailey’s project hopes to develop novel treatments for patients suffering from spinal-cord injuries.
Shivalika Chavan (2020 fellow) is an undergraduate student in Bioengineering with a minor in Applied Mathematics. She is working with Azadeh Yazdan-Shahmorad in the Bioengineering and Electrical and Computer Engineering departments. Shivalika’s research focuses on the characterization of neural network connectivity, specifically the functional and anatomical changes that occur due to cortical lesions in non-human primates. Knowledge of these changes is critical for developing stimulation-based therapies for stroke, in which these networks are manipulated.
Qilang Ding (2020 fellow) is an undergraduate student in Mechanical Engineering: Mechatronics. His research with Kat Steele in the Ability & Innovation Lab is on the fabrication, assembly, and tuning of a dynamic walking bipedal robot. The robot will serve as a testbed for validating the Ability & Innovation Lab’s simulation framework used to evaluate whether discrepancy modeling with data-driven approaches enables more accurate dynamic solutions of bipedal movement with both unaltered and altered control.
Tom McIlwain (2020 fellow) is an undergraduate student in Bioengineering working with Amy Orsborn in the Electrical Engineering and Bioengineering departments. Tom’s research focus is in computational neural engineering, and his current project is exploring the use of machine learning algorithms in high-dimensional brain-machine interface tasks. In the future, Tom hopes to pursue a Master’s degree and develop devices for neuro-rehabilitation in industry.
Lauren Peterson (2020 fellow) is an undergraduate student in Electrical Engineering. She works with Sam Burden and Momona Yamagami in the Biorobotics Lab to investigate how individuals learn to use continuous robotic systems. Currently, she collects and analyzes data on how individuals with and without motor impairments transfer their understanding of the continuous robotic system between their dominant and non-dominant hands, with the overall goal of improving rehabilitation techniques for individuals recovering from stroke.
Katie Rupp (2020 fellow) is an undergraduate student in Applied and Computational Mathematical Sciences with a concentration in Biological and Life Sciences. She is working with John Tuthill in the Physiology and Biophysics department. Katie’s research uses computational methods to study the leg kinematics of walking and grooming in fruit flies. Her current project involves analyzing leg joint positions and angles to characterize the types of movements that the fly produces during site-specific grooming behaviors. These analyses will be used to determine the degree of stereotypy that is present among different grooming behaviors and will allow her to theorize about the underlying neural circuitry that gives rise to grooming.
2020 UWIN Post-baccalaureate Fellows
Abbey Green (2020 fellow) is a post-baccalaureate researcher working with Rajiv Saigal in the department of Neurological Surgery. Abbey’s research focuses on determining which method of electrical stimulation, epidural or transcutaneous, in combination with physical therapy, best improves the long-term locomotive abilities of individuals with incomplete spinal cord injuries. In addition, Abbey is involved with a preclinical project focused on the development of implantable polymer devices for drug delivery, which are aimed to improve patient outcomes following traumatic spinal cord injury. Abbey graduated from Middlebury College with a Bachelor’s degree in Neuroscience and a minor in Global Health.
John Kruper (2020 fellow) is a post-baccalaureate researcher working with Ariel Rokem at the eScience Institute. John’s research is on the analysis of diffusion MRI, which is used to find major white matter fascicles in the living human brain. He is helping develop a software called Automated Fiber Quantification in Python (pyAFQ; https://github.com/yeatmanlab/pyAFQ) which automatically models the white matter of the brain and extracts diffusion measurements along major tracts given dMRI data that has undergone standard preprocessing. This kind of analysis aids learning about how connections within the human brain interact with cognitive abilities, diverse behaviors, and neurological and psychiatric disorders. John will graduate from the University of Washington in 2020 with a Bachelor’s degree in Computer Engineering.
Augusto Millevolte (2020 fellow) is a post-baccalaureate researcher working with Amy Orsborn in the Bioengineering department. Augusto’s research focuses on how network connectivity relates to learning in a brain-machine interface (BMI), mapping functional connectivity through optogenetic stimulation and electrical recording in the sensorimotor cortex. Through understanding how this functional connectivity changes over time, he aims to optimize the initial implementation of a BMI and improve learning rates for control. This work will translate into more intuitive neuroprosthetics for patients requiring functional restoration of damaged or impaired limbs. Augusto’s passion for this work follows from experience in the military, after which he received a Bachelor’s degree in Electrical Engineering and Neurobiology from the University of Wisconsin – Madison.
Adree Songco Aguas (2020 fellow) is a post-baccalaurate researcher working with Fred Rieke and Gabrielle Gutierrez in the Physiology and Biophysics department. Adree is interested in how visual processing occurs in the rod-cone retinal circuitry, particularly in the context of how we process motion in dim lighting. She develops computational models trained on electrophysiological data in conjunction with designing human psychophysics experiments. Findings from her research provide insight into how parallel processing in neural circuits underlie sensory encoding and human perception. Adree received her Bachelor’s degree from University of Washington, where she majored in Neuroscience and minored in Applied Mathematics.
Abby von Hagel (2020 fellow) is a post-baccalaureate researcher working with Tom Daniel and Alison Weber in the Department of Biology. Abby is conducting research that aims to identify the features of the mechanical stimuli that drive neuronal responses. Using the insect model Manduca sexta (Hawkmoth), she hopes to understand how limited information about wing deformation is encoded to enable flight control through electrophysiological recording, high-speed image-tracking, and computational techniques. Abby attended the University of Washington where she received Bachelor’s degrees in Biology and Neuroscience with Interdisciplinary Honors.
This year’s connection drew 172 attendees, with a multitude of talks: four by invited keynote lecturers, four from local UWIN faculty, four talks by senior UWIN/Swartz postdoctoral fellows, and eight talks by senior UWIN and Computational Neuroscience graduate and undergraduate students. Alongside these talks, there was a poster session, and an ethics panel. Thank you to all who attended and participated!
Day 1: Thursday, January 30, 2020`
Day 1 of NCEC kicked off with a poster sessions over lunch! UW faculty members and students presented their work on a variety of neural engineering and computational neuroscience topics.
“The Smellicopter: a bio-hybrid odor localizing nano-air vehicle”
Anderson focuses on the Smellicopter which is, to their knowledge, the first flying biohybrid chemosensing robot, the first odor-localizing robot using feedback only from sensors carried on-board, and the fastest odor localizing robot to date. These results represent a significant step forward in odor localizing robots and a step toward robots that have the speed and sensitivity of biological systems.
“Go with the FLOW: Spatiotemporal Dynamics in Optical Widefield Calcium Imaging”
Esquenazi examines the current state of retinal and cortical visual implants, and whether patients might be able to learn to decode an unnatural on-and-off cell pattern. This is investigated by training normally sighted individuals with visual input that was distorted to produce abnormal conflicting on-and-off cell responses and observing the improvement.
“Tuning for global motion in ventral visual area V4 ”
Bigelow discussed the identification of a global motion signal in ventral visual area V4, a region typically associated with form processing, and how this provides a unique opportunity to study the integration of form and motion signals in the mammalian visual system.
“Anipose: a full system for robust 3D markerless tracking”
Karaschuk introduces Anipose, a comprehensive open-source library for robust, markerless 3D tracking from multiple camera views. Adiopose helps quantify body position and movement which is critical for understanding animal behavior and the neuromechanical systems that underlie it.
“Stimulation rebound in deep brain stimulation for essential tremor.”
Farrell focuses on how Recurrent Neural Networks learn to increase and reduce the dimensionality of their internal representation in a way that matches the demands of a classification task.
“A Toolbox for Studying Ischemic Stroke in Non-Human Primate Cortex”
Karam Khateeb, Bioengineering graduate student, Yazdan-Shahmorad lab
Khateeb introduces a toolbox to study stroke in non-human primates as a pre-clinical model, which can provide critical insight into the mechanisms of ischemic stroke and advance the development of stimulation-based stroke therapies.”
Keynote lecture: “Modulating neural sequencing to improve recovery after stroke”
Dr. Sejnowski examines the process of storage and switching in the prefrontal cortex, focusing on a recurrent gating model of the prefrontal cortex that grows adaptively. This model exhibits transfer learning and robust memory savings, providing a fundamental framework for how the prefrontal cortex may handle the abundance of schemas necessary to navigate the real world.
“Large-scale brain network dynamics informed by ultrafast functional MRI”
Dr. Kutz investigates how neural pathways from input stimuli to motor-neuron driven behavioral responses function. Comparison of a small, stereotyped connectivity graph and a large, randomly connected network for processing can give insight into the diversity of neurosensory strategies available to organisms.
“Comparing the effects of frontal and temporal neurostimulation on second language learning”
Dr. Bice examines how neurostimulation shapes language learning in adults by comparing how stimulation of different brain regions (frontal vs. temporal areas) affects learning specific aspects of language. Results from an artificial grammar learning study reveal that frontal stimulation enhanced the acquisition of procedural information (akin to grammar) whereas temporal stimulation facilitated learning of explicit information (like vocabulary).
“Simulating the perceptual experience of patients implanted with cortical visual prosthetics”
Within a decade, individuals living with incurable blindness are likely to have a broad range of options for sight restoration. Here Dr. Fine describe the idea of ‘virtual patients’ – models that simulate neural responses and perceptual outcomes for a range of sight restoration technologies, and show how this model can predict patient percepts for a cortical prosthetic.
Keynote Lecture: “A Design Principle for Population Neural Codes”
Michael Berry, Princeton University
“From intention to movement: low-power, high performance communication protocol for backscattered-based neural implants”
Dr. Arojna presents work on developing a custom high-performance protocol and reader for bi-directional communication with neural implants Eventually enable a closed-loop operation, improving neural implants potential for significant impact in medicine.
“Using a fluorescent voltage sensor to measure membrane potential in Drosophila proprioceptive axons”
Dr. Deady touched on the computation required from different types of proprioceptors which send various information about where one’s body is in space to the central nervous system. These incoming stimuli from primary proprioceptive neurons perform complex computations to enhance or diminish various information, resulting an awareness of body position.
“The Role of Corticospinal Tract Plasticity in Motor Recovery Induced by Targeted Activity Dependent Spinal Stimulation”
Dr. Widman walks through creating a novel therapy termed targeted activity-dependent spinal stimulation (TADSS), where spinal stimulation is delivered when muscle activity is detected. Using spike timing dependent plasticity principles, she tests if muscle activity can be used as a noninvasive surrogate for brain activity promotes the strengthening of spared cortical connections to spinal cord.
“Neural processing and behavioral strategies used by mice to navigate with dynamic odor plumes”
Dr. Gire discusses results from large scale imaging of the early olfactory system that determine the population dynamics that emerge during odor plume encounters. As well as experiments in freely moving mice navigating to odor sources that determine the strategies mice use to accumulate directional information from intermittent odor encounters.
Keynote Lecture: “Comparing high-dimensional neural recordings across time, space, and behavior”
The UWIN seminar series continue in February 2020 with a pair of short talks by Ariel Rokem and Samira Moorjani. The seminar is on Wednesday, February 12, 2020 at 3:30pm in Husky Union Building (HUB) 337. Refreshments will be served prior to the talks.
“Automated detection of glaucoma in multi-modal retinal images with interpretable deep learning”
Ariel Rokem, Senior Data Scientist, eScience Institute, University of Washington
“‘Movement-triggered electrical stimulation for strengthening cortical connections”
Samira Moorjani, Research Assistant Professor, Department of Physiology & Biophysics, University of Washington
“Automated detection of glaucoma in multi-modal retinal images with interpretable deep learning” (Ariel Rokem)
Glaucoma is a leading cause of irreversible blindness worldwide, affecting tens of millions of people. Automated systems to diagnose glaucoma could decrease the incidence of undiagnosed cases of glaucoma and facilitate earlier initiation of therapeutic mitigation strategies that can be effective in slowing the progression of the disease. We trained a machine learning model that can accurately detect the presence of glaucoma, using data from the UK Biobank study. Our model combines information from demographic, systemic medical data, and ocular data with deep learning (DL) models trained to analyze both color fundus photos (CFP) and retinal optical coherence tomography scans (OCT). Our model accurately detected glaucoma in a test set of held-out subjects with an area under the receiver operating characteristics curve (AUC) of 0.97. Using new methods for machine learning model interpretation provides additional insight into the features of the images and other variables used in determination of the predicted diagnosis.
“Movement-triggered electrical stimulation for strengthening cortical connections” (Samira Moorjani)
Activity-dependent electrical stimulation, inspired by spike-timing-dependent plasticity of neural circuits, has been employed in vivo in rats and monkeys for modulating synaptic connectivity. In my talk, I will describe a closed-loop stimulation paradigm in which electrical stimuli are triggered by volitional movements. When paired with successive use of the electrically-conditioned motor pathways, movement-triggered stimulation (MTS) led to lasting strengthening of cortical connections in behaving monkeys. Importantly, neither physical activity alone nor electrical conditioning alone produced similar effects. These experiments suggest that MTS creates a plastic landscape in which repetition of the conditioned movement drives cortical strengthening long after the stimulation has ended. Taken together, our data alludes to a crucial role of behavior in neural plasticity and provides support for combining MTS with physical therapy for strengthening motor pathways weakened by injury or disease.
Registration is open for the 2020 Neural Computation and Engineering Connection (NCEC)! It will be held on the afternoon of Thursday, January 30, 2020 and all day Friday, January 31, 2020. NCEC brings together the University of Washington neuroengineering and computational neuroscience communities in an exciting and stimulating event! This event is sponsored by the UW Institute for Neuroengineering (UWIN), the UW Computational Neuroscience Center, and the Center for Neurotechnology.
The keynote speakers for NCEC 2020 are: Terry Sejnowski (Salk Institute), Eva Dyer (Georgia Tech), Michel Maharbiz (UC Berkeley), and Karunesh Ganguly (UCSF).
Local speakers include: Ione Fine (UW Psychology), Nathan Kutz (UW Applied Math), Hesam Jahanian (UW Radiology), and David Gire (UW Psychology) . UWIN and Computational Neuroscience graduate and postdoctoral fellows will also be giving talks.
Thursday’s events will be at the Husky Union Building (HUB) in rooms 332 and 334, starting with a poster session during lunch, followed by student talks, a keynote lecture by Karunesh Ganguly (UCSF), and a panel discussion on ethics in neuroscience.
Friday’s events will be all-day at the Bill & Melinda Gates Center (CSE2) Zillow Commons and will include keynote talks by Terry Sejnowski (Salk Institute), Eva Dyer (Georgia Tech) and Michel Maharbiz (UC Berkeley), talks by UW faculty Ione Fine (Psychology), Nathan Kutz (Applied Math), Hesam Jahanian (Radiology), and David Gire (Psychology), and talks by senior UWIN postdoctoral fellows. NCEC will end with a late afternoon reception on Friday in HUB 332.
More information about the schedule can be found here.
The UWIN seminars start in January 2020 with a pair of short talks by Fred Rieke and Arka Majumdar. The seminar is on Wednesday, January 8, 2020 at 3:30pm in Husky Union Building (HUB) 337. Refreshments will be served prior to the talks.
“Towards generalizable models for sensory responses”
Fred Rieke, Professor, Department of Physiology and Biophysics, University of Washington
“Extreme miniaturization of optics using metasurface and computational imaging”
Arka Majumdar, Assistant Professor, Department of Electrical and Computer Engineering, University of Washington
“Towards generalizable models for sensory responses” (Fred Rieke)
Receptive field models attempt to concisely summarize neuronal responses to sensory inputs. These models instantiate our understanding of the mechanistic basis of circuit function, and by doing so, help identify gaps in that understanding. Current models often fail to generalize to predict responses to stimuli other than those to which they were directly fit. Such failures are particularly striking for stimuli with the large dynamic range and strong temporal and spatial correlations characteristic of natural visual images. I will summarize recent work aimed at generating models with better ability to generalize across stimuli, and discuss what those models can reveal about key circuit functions.
“Extreme miniaturization of optics using metasurface and computational imaging” (Arka Majumdar)
Modern image sensors consist of systems of cascaded and bulky spherical optics for imaging with minimal aberrations. While these systems provide high quality images, the improved functionality comes at the cost of increased size and weight. One route to reduce a system’s complexity is via computational imaging, in which much of the aberration correction and functionality of the optical hardware is shifted to post-processing in the software realm. Alternatively, a designer could miniaturize the optics by replacing them with diffractive optical elements, which mimic the functionality of refractive systems in a more compact form factor. Metasurfaces are an extreme example of such diffractive elements, in which quasiperiodic arrays of resonant subwavelength optical antennas impart spatially-varying changes on a wavefront. While separately both computational imaging and metasurfaces are promising avenues toward simplifying optical systems, a synergistic combination of these fields can further enhance system performance and facilitate advanced capabilities. In this talk, I will present a method to combine these two techniques to perform full-color imaging across the whole visible spectrum. I will also discuss the use of computational techniques to design new metasurfaces, and using metasurfaces to perform computation on wavefronts, with applications in optical information processing and sensing.
The UWIN seminars continue with a pair of short talks by Jeff Riffell and Josh Smith. The seminar is on Wednesday, December 11, 2019 at 3:30pm in Husky Union Building (HUB) 337. Refreshments will be served prior to the talks.
“The sensory biology and neurobiology of the mosquito – the world’s deadliest animal”
Jeff Riffell, Professor, Department of Biology, University of Washington
Josh Smith, Professor, Department of Computer Science and Engineering, University of Washington
“The sensory biology and neurobiology of the mosquito – the world’s deadliest animal” ( Jeff Riffell)
Here, in this talk, I will focus our recent work on the Aedes aegypti mosquito, an important disease vector. Little is known about the neural circuits that drive mosquito host-finding behavior, but I will describe our efforts towards characterizing the neural bases of behavior at different life-history stages (adult sugar-seeking, host-locating), and developing new tools for interrogating those circuits. Further, I will argue that such an understanding can lead to new interventions and tools for mosquito control.
“Acoustic Levitation” (Josh Smith)
I will present some early work in my group on using ultrasound to levitate small objects. After introducing the technique, I will discuss potential applications in neuroscience, neurotechnology, robotics, and other areas.
The Weill Neurohub is a recently launched collaborative research network with the purpose of spurring neuroscience research into brain disease and disorders. This collaboration is being funding by a $106 million dollar initiative given by the Weill Family Foundation. Former Wall Street financier Sanford Weill and his wife, Joan Weill, operate the Weill Family Foundation which has a continued history of support in neuroscience, with total gifts exceeding $300 million dollars.
The new Neurohub will combine the experience of three universities, as well as the resources of seventeen national laboratories overseen by the Department of Energy. The intent of this extensive collaboration is to forge and nurture collaborations between neuroscientists and researchers working in other disciplines to speed development of therapies for neurological diseases and disorders.
Neurohub will be headed by a leadership committee including representatives from all 3 schools, their neuroscience departments, and the Weill Family Foundation. The committee includes UWIN co-director, and professor of biology at the UW, Tom Daniel. The committee is looking forward to establishing, as Tom Daniel sees it, a “nationally unique enterprise — drawing on diverse approaches to accomplish goals no single institution could reach alone, as well as seeding and accelerating research and discovery. ”
The Neurohub plans on providing funding for faculty, postdoctoral fellows, and graduate students at the UW, Berkeley and UCSF working on cross-disciplinary projects, including funding for “high-risk/high-reward” proposals that are particularly innovative and less likely to find support through conventional funding sources. They will also be funding novel cross institutional projects in the “pillars” of neuro-discovery: imaging; engineering; genomics and molecular therapeutics; and computation and data analytics.
This project has been written about in many different mediums including:
The November 2019 UWIN seminar features a talk by Keith Hengen. The seminar is on Wednesday, November 6, 2019 at 3:30pm in Husky Union Building (HUB) 214 . Refreshments will be served prior to the talk.
“Long term computational stability in the brain (and 500 single units in a freely behaving mouse)”
Keith Hengen, Assistant Professor of Biology, Washington University in St. Louis
Neuronal computation is extremely robust across a lifetime. Our data suggest that the brain actively tunes itself to criticality, a computational regime that maximizes information processing. To address these types of ideas, we developed methods to record from 500-1000 single units throughout the brain of a freely behaving mouse. Further, we can follow these neurons for months without pause, allowing the consideration of complex, natural behaviors on ethologically relevant timescales.
The second focus of the UWIN fellow research series is Raymond Sanchez, a graduate student in the UW Neuroscience Program and Department of Biology. Ray is advised by Horacia de la Iglesia, and received a UWIN fellowship in 2017. His research focuses on sleep disturbances related to seizures, and methods of detection and prevention of seizures during sleep.
Epilepsy is among the most common neurological disorders in the world, and are typically accompanied by sleep and circadian rhythm disturbances. These disturbances include waking up during the night, difficulty maintaining a consistent sleep cycle, and tiredness throughout the waking day. These disturbances tend to increase the likelihood and severity of seizures and other associated cognitive and developmental deficits. Additionally, frequent nocturnal seizures put patients at high risk for sudden unexpected death, particularly in children.
Investigating Sleep Disturbances
Dravet syndrome is a specific type of epilepsy syndrome that
begins in infancy or early childhood, and is caused by a brain wide change in
the SCN1A gene (which controls the sodium-ion exchange that is crucial in the
action of a nervous system). Due to the specific gene mutation, Dravet syndrome
can be induced in animal models and studied in specific locations of the brain.
This allows for isolation of the modification of the SCN1A gene in the sleep
section of the brain, clarifying the relationship between sleep and epilepsy.
Using existing techniques in mice, a gene can be tagged,
modified, and removed, in this case, inducing physiological changes associated
with Dravet syndrome in the sleep section of the brain. This allows these mice
to act as Dravet syndrome models in research. With these mice models available,
Ray is able to directly study the repercussions of Dravet syndrome in long
scale sleep studies that can lend information about how environmental changes
modify sleep architecture. Determining the sleep architecture of a night’s rest
is important; while the total amount of sleep and the types of each sleep cycle
is important, the order in which each sleep stage occurs also matters.
One of the most consistent observations of caretakers of
individuals with Dravet syndrome is that travel is very hard to recover from,
specifically jet lag and the transition to a new time zone or circadian rhythm.
Ray looked into this phenomenon by observing the sleep regularity within two
sets of mice, one with the Dravet syndrome mutation, the other without, while
the light schedule was changed to simulate a time-zone change.
A way of visually depicting circadian sleep cycles is using
an actogram. The actogram above is double plotted, meaning that the current day
is plotted beside the previous day, allowing for an easier comparison from day
to day. This plot compares the time and duration of activity during the day
(x-axis) over the course of a 30 day (y-axis) observational period. The light
gray shading represents the period ‘night’ time with lights off, while the
light areas indicate the ‘day’ hours or lights on. During the day, an ECoG/EMG
recording is taken of each mouse, with the black sections showing the sleeping
times of the mouse, and the white gaps showing active times. This experiment
was conducted for both a Wild Type control mouse (left) and a Dravet Syndrome
model mouse (right), and observed sleep patterns as a “jet lag” time shift
occurred. Visually, the common sleep disturbances with the Dravet Syndrome are
present: inconsistent sleep during the night and tiredness or more resting
though the day. These long-term sleep studies over multiple days are useful for
understanding the severity and the circadian cycle adjustment needs over the
Wild type and the Dravet Syndrome mice.
Sleep Stage Detection
An important distinction in the sleep architecture lies in
what type of sleep stage is occurring. There are five different sleep stages,
REM sleep, stage 1 and 2 (light sleep stages), stages 3 and 4 (deep sleep
stages). These stages all serve a different purpose during a night’s rest, with
the deep sleep stages encouraging the body to recover and rest during the
night. This includes heart health, immune health, and brain help, even aiding
the transfer of short-term memories into long term storage.
Patients with Dravet Syndrome often find it hard to get
enough total sleep or enough of the deeper sleep cycles. This lack of sleep
often serves as a future seizure trigger. The mouse studies have been useful in
determining correlations in sleep and seizure activities, but due to the length
of the study (multiple days), analyzing the data can be challenging.
To aid in this data analysis, Ray is currently developing a
machine learning model for sleep stage classification. This will allow him to process long term
sleep recordings with the same accuracy as a human, but automated and much
quicker. This model is the first step in predicting when a seizure might occur.
The ability to detect the type of sleep stage allows for a device to identify
if there is a sleep stage that has been skipped, or ended early. This also
allows the program to check large scale correlations for artifacts in the
readings that are specific to a specific stage before a seizure occurs.
Once the data analysis is automated, Ray is looking towards
how to detect, prevent, and interrupt night seizures. In order to accurately
predict when a night seizure is going to occur, there needs to be
identification and automatic detection of pre-markers of the seizures. While
the seizure prediction models are still in the future for Ray, he imagines a
noninvasive device that can measure the child’s sleep, and detect markers for a
seizure. This device would then be able to wake the child or warn the
caregivers before the seizure would occur. There is still work to be done in
the development of a device like this, but Ray is looking forward for his work to
be useful for therapeutic devices in the future.
Ray has presented this work at the Computation Neuroscience Conference in 2019 and has had his manuscript, “Circadian Regulation of Sleep in a Pre-Clinical Model of Dravet Syndrome: Dynamics of Sleep Stage and Siesta Re-entrainment” accepted intoSleep.