The 2018 Neural Computation and Engineering Connection (NCEC) was held on January 18-19, 2018. This annual event brings together the UW neuroengineering and computational neuroscience communities to share and discuss new research and facilitate collaborations. The event is sponsored annually by the UW Institute for Neuroengineering (UWIN), the Center for Sensorimotor Neural Engineering (CSNE), and the UW Computational Neuroscience Center. This year’s connection drew 140 attendees and was highlighted by five invited keynote lectures, four talks by local UW faculty, two talks by senior UWIN postdoctoral fellows, seven talks by senior graduate and undergraduate students, a series of lightning talks by new graduate students and postdoctoral fellows, and a poster session. A huge thank you to all those who attended and participated!
Day 1: Thursday, January 18, 2018
Day 1 of NCEC kicked off with a poster session over lunch. 20 UW faculty members and students presented their work on a variety of neural engineering and computational neuroscience topics.
(Click on thumbnails to see full-size images)
Keynote lecture: “Engineering Haptic Illusions”
Allison Okamura, Professor, Department of Mechanical Engineering, Stanford University
In the first keynote lecture, Allison Okamura spoke about her work with haptics, the study of human touch sensing. She provided examples of situations in which haptic feedback can be beneficial when the sense of touch is absent or has been lost: in robot-assisted surgery, with prostheses, for manipulation of robots/tools in dangerous situations (e.g., in space, or mine diffusion). Okamura discussed a few of the many ways her lab focuses on haptics:
- Design and control of haptic systems: When does it make sense to provide haptic feedback rather than visual feedback?
- How haptic feedback can optimize robot-assisted minimally invasive surgery.
- Wearable haptics, to be used by stroke patients during exercise(s).
“Sparse sensing by arrays of wing mechanosensors for insect flight control”
Thomas Mohren, UWIN graduate fellow, S. Brunton and Daniel labs
Mohren seeks to answer the question of how insect mechanosensors work to sense things; specifically, how distributed sensors combine information to assess rotational movement. He uses a computational model of a moth wing, building in computations for flapping and rotation in an attempt to distinguish flapping vs. flapping + rotation.
“Synaptic specialization and convergence of visual channels in the retina”
Phil Mardoum, UWIN graduate fellow, Rieke and Wong labs
Mardoum asks if signals from rods and cones in the retina are filtered differently; specifically, if postsynaptic receptor mechanisms differ between rods and cones. He records from bipolar cells in zebrafish while exposing the fish to lights of different wavelengths and/or disrupting cell signaling in the retina.
“Visual learning and processing in the honeybee, Apis mellifera“
Claire Rusch, UWIN graduate fellow, Riffell lab
Rusch asks how honeybees are capable of complex learning and behavior with so few neurons in their brains (1 million neurons total in the honeybee brain, 170,000 in the mushroom body, the center of learning/memory). She records activity from the honeybee brain and assesses how learning changes neural activity.
“Engineering direct cortical stimulation in humans”
David Caldwell, UWIN/BDGN graduate fellow, Rao and Ojemann labs
Caldwell’s goal is to enhance neural connectivity through electrical cortical stimulation. He looks at the behavioral and neural effects of cortical stimulation in humans, working with patients implanted with electrocorticographic (ECoG) grids in preparation for epilepsy surgery.
“Simulating Axon Health’s Impacts in the Setting of Cochlear Implants”
Jesse Resnick, Computational Neuroscience Training Grant graduate fellow, Rubinstein lab
Even with cochlear implants (CIs), some hearing tasks can still be challenging for people who have lost their hearing: localizing the source of a sound and speech recognition in noisy environments. These tasks require assessing the time difference in sound arrival between the ears (Interaural Time Difference, ITD). By building a computational model of demyelination in auditory neurons, Resnick is working to asses if variability in demyelination severity contributes to ITD detection ability.
“Rod-cone flicker cancellation: retinal processing and perception in intermediate light”
Adree Songco-Aguas, Computational Neuroscience Training Grant undergraduate fellow, Rieke lab
The rods and cones in our retina make vision seamless across day and night. Songco-Aguas is interested in how the retina behaves in intermediate light, assessing how retinal ganglion cells respond when photoreceptors are stimulated with intermediate light levels.
“Spatiochromatic integration by V1 double opponent neurons”
Abhishek De, Computaional Neuroscience Training Grant graduate fellow, Horwitz lab
De addresses the question of how color is processed spatially. Specifically, he asks how neurons in area V1 of the visual cortex combine color signals across their spatial fields. He records extracellularly from V1 neurons in primates to see how neurons process color across receptive fields.
Day 2: Friday, January 19, 2018
Panel Discussion on Ethics in Neuroscience.
Day 2 started with breakfast and a lively discussion of ethics in neuroscience by a panel composed of UW and visiting faculty. The panel began by discussing effective collaboration between theorists and experimentalists, particularly as it pertains to authorship on publications. The session then shifted to a discussion about our responsibilities as scientists in presenting results to the public. There were discussions about balancing highlighting the novelty and general interest of research vs. realism about data, especially given the pressure for needing exciting results to generate funding.
(Seated from left to right are: Adrienne Fairhall (UW), Rafael Yuste (Columbia), Beth Buffalo (UW), David Perkel (UW), Tom Daniel (UW), Eric Shea-Brown (UW), Michael Berry (Princeton))
“Behavioral Implementation of Mnemonic Processing”
Sheri Mizumori, Professor, UW Department of Psychology
Mizumori addresses the question of how the hippocampus influences behavior; in other words, how memory drives behavior choice. During her lecture, she spoke about possible connectivity routes in the brain related to the question, and discussed her research showing the lateral habenula’s (LHb) role in reinforcement learning. Her research provided evidence that the hippocampus and LHb are part of the same memory-driven system, linked to a theta-generating network; and that the LHb is involved in the same flexible behaviors the hippocampus is involved in.
“Optogenetic stimulation leads to connectivity changes across sensorimotor cortex in non-human primates”
Azadeh Yazdan, Washington Research Foundation Innovation Assistant Professor of Neuroengineering, UW Departments of Bioengineering and Electrical Engineering
One focus of Yazdan’s lab is the development of efficient stimulation-based therapies for stroke. She developed a large-scale interface for optogenetics in non-human primates, and is looking at how this technique can be used to change functional connectivity between somatosensory and motor cortices. Her future work in stimulation-based stroke therapies will focus on three components: mechanisms of stimulation-induced plasticity, stroke studies in non-human primates, and large-scale interfaces.
Keynote lecture: “Emergence of dynamically reconfigurable hippocampal responses by learning to perform probabilistic spatial reasoning”
Ila Fiete, Associate Professor, Department of Neuroscience, UT Austin
Fiete’s goal is to learn how the brain computes and to better understand neural coding and dynamics. She asks how neural computation unfolds over time, and how neural responses underlie the computations that are performed. One difficult problem her lab considers is how to simultaneously know where you are in the environment, and also build a map of where you are. Her lab trained a neural network to solve these problems, to report an accurate estimation of position in complex tasks.
Keynote lecture & Robotics Colloquium: “Robotic-assisted movement training after stroke: Why does it work and how can it be made to work better?”
David Reinkensmeyer, Professor, Departments of Mechanical and Aerospace Engineering, Anatomy and Neurobiology, and Biomedical Engineering, UC Irvine
Robot-assisted stroke therapy can provide improvements to stroke patients, but there is high variability. By what mechanisms of plasticity or motor learning does robot-assisted therapy work? To answer this question, Reikensmeyer’s lab is building computational models of recovery after stroke, testing and refining them with data from patients receiving robotic-assisted therapy. During his lecture, he showed examples of various types of robotic-assisted therapy, including rehabilitation devices available to the public.
“Info in a bottleneck”
Gabrielle Gutierrez, UWIN postdoctoral fellow, UW Applied Mathematics Department
Gutierrez asks how signal processing in the retina preserves image information. In the retina, many bipolar cells converge onto one retinal ganglion cell (RGC). She looked at response functions between bipolar cells and RGCs, finding that many bipolar cells converging on one RGC helps with noise processing.
“Modeling the perceptual experience of retinal prosthesis patients”
Michael Beyeler, UWIN postdoctoral fellow, UW Psychology Department & the UW eScience Institute
Retinal prostheses can restore some sight to individuals who have lost vision due to conditions such as macular degeneration and retinitis pigmentosa. Beyeler asks what people with retinal prostheses actually see; visual perception with a retinal prosthesis is highly distorted relative to normal vision. He is working on a computational model that predicts what people with retinal prostheses will actually see, using data from patients with retinal prostheses. His ultimate goal is to use the model to improve and optimize the stimulation protocol for these prostheses to improve what patients actually see.
Keynote lecture: “Neural substrates of prospection”
Loren Frank, Professor, Kavli Institute for Fundamental Neuroscience, Department of Physiology, UC San Francisco
One role played by memories is their use in decision-making. Frank discussed his lab’s work using large-scale recording techniques to record activity in the hippocampus, as well as other areas of the brain, to relate patterns of activity to the basic cognitive functions of the structure. He shared research showing neural activity in the hippocampus was not just a representation of past locations, but also representation of possible future paths in space; recorded neural activity guides future behavior.
“Interfaces to monitor and manipulate large-scale neural circuits in primates”
Amy Orsborn, Clare Boothe Luce Assistant Professor, UW Electrical Engineering & Bioengineering Departments
Brain-machine interfaces (BMIs) can restore motor abilities; individuals who are paralyzed or missing a limb can control robotic limbs through motor cortex activity in their brain. Orsborn studies motor learning in order to improve BMIs. She discussed research working to improve the algorithms used to map neural activity onto control of robotic devices in BMIs. Orsborn also talked about tools she is developing to study neural networks across multiple spatial scales.
“Dynamic Mechanisms underlying rhythm generation in cortical and brainstem microcircuits”
Nino Ramirez, Professor, UW Neurological Surgery Department, Director, Center for Integrative Brain Research, Seattle Children’s Research Institute
Ramirez discussed microcircuits in the brain that establish rhythms for breathing, and specifically presented work on the role of inhibition and excitation in breathing mechanisms. Understanding these mechanisms has implications for understanding conditions associated with disordered respiratory rhythms.
Keynote lecture: “Circuit basis for behavioral flexibility”
Takaki Komiyama, Associate Professor of Neurobiology and Neurosciences, UC San Diego
Komiyama studies how circuits of neurons allow for behavioral flexibility; noting how amazing the flexibilities of the brain and our behavior are. He addresses the questions of what circuits are involved in motor learning over many repetitions and practice, and if the relationship between brain activity and movement is stable. Komiyama uses wide-field calcium imaging to assess how brain activity changes with motor learning.