Category: Events (Page 1 of 4)

February 2019 UWIN seminar: talk by Adam Calhoun

February  2019 UWIN speaker Adam Calhoun

The February 2019 UWIN seminar features a talk by visiting speaker Adam Calhoun, who is a Postdoctoral Fellow in the Princeton Neuroscience Institute at Princeton University. His talk is titled “Quantitative methods to identify behavioral states”.

The seminar is on Wednesday, February 13, 2019 at 3:30 in Husky Union Building (HUB) 337. Refreshments will be served prior to the talk.


Animals must flexibly alter their responses to stimuli according to changing internal needs or behavioral contexts. This source of behavioral variability is often ignored because we lack of methods that are able to identify the changing internal state of an animal. To address this gap, we have developed a novel unsupervised method to identify internal states and have applied it to the study of a dynamic social interaction. During courtship, Drosophila melanogaster males chase and sing to females and, in a manner analogous to human conversation, the structure of their songs is actively patterned by interactions with the female. We identify the internal states of the male use this new model to identify neural correlates of state switching. Our results reveal how animals compose behavior from previously invisible states, a necessary step for quantitative descriptions of animal behavior that link environmental cues, internal needs, neuronal activity, and motor outputs.

January 2019 UWIN seminar: talk by Guillaume Lajoie

January 2019 UWIN Seminar speaker Guillaume Lajoie

The first UWIN seminar of 2019 features a talk by visiting speaker Guillaume Lajoie from Université de Montréal’s Department of Mathematics and Statistics. The talk is titled “Successful learning in artificial networks thanks to individual neuron failure”.

Guillaume is an Assistant Professor in the Department of Mathematics and Statistics at the Université de Montréal, and is also an Associate Member of Mila, the Quebec Institute for Learning Algorithms. We are especially excited to welcome Guillaume back to UW as he was previously a UWIN postdoctoral fellow!

The seminar is on Wednesday, January 9, 2019 at 3:30 in Husky Union Building (HUB) 337. Refreshments will be served prior to the talk.

This talk will outline work in progress. Not unlike the brain, artificial neural networks can learn complex computations by extracting information from several examples of a task. Typically, this is achieved by adjusting the parameters of the network in order to minimize a loss function via gradient descent methods. It is known that introducing artificial failure of single neurons during a deep network’s training, a procedure known as dropout, helps promote robustness. While dropout methods and variants thereof have been successfully employed in a variety of contexts, their effect is not entirely understood, and relies on stochastic processes to select which units to drop. Here, I will discuss two methods designed to purposely select which units would best benefit learning if dropped or temporarily modified, based on their tuning, activation and the current network state: The first method is aimed at improving generalization in deep networks, and the second combats gradient exploding and vanishing in recurrent networks, when learning long-range temporal relations. While gradient descent methods for artificial networks are not biologically plausible, I will discuss how relationships between neural tuning and failure during training can inform exploration of learning mechanisms in the brain.

Registration open for 2019 Neural Computation and Engineering Connection (NCEC)

Poster for the 2019 Neural Computation and Engineering Connection

Registration is open for the 2019 Neural Computation and Engineering Connection (NCEC)! It will be held on the afternoon of Thursday, January 24, 2019 and all day Friday, January 25, 2019.  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 2019 are: Mitra Hartmann (Northwestern), Abby Person (University of Colorado Denver), Andrea Behrman (University of Louisville), and Maryam Shanechi (University of Southern California).

Local speakers include: Andre Berndt (UW Bioengineering), Kat Steele (UW Mechanical Engineering), Nick Steinmetz (UW Biological Structure), and Mari Ostendorf (UW Electrical & Computer Engineering).  UWIN and Computational Neuroscience graduate and postdoctoral fellows will also be giving talks.

Registration is free but required.
Please register at:

Registration closes on Friday, January 11, 2019.

Thursday’s events will be at the Center for Neurotechnology (Russell Hall Suite 204, 1414 NE 42nd St.), starting with a poster session during lunch, followed by student talks, a keynote lecture by Andrea Behrman, and a panel discussion on ethics in neuroscience.

Friday’s events will be all-day at the Husky Union Building (HUB) room 334, including keynote talks by Mitra Hartmann, Abby Person, and Maryam Shanechi, talks by UW faculty Andre Berndt, Kat Steele, Nick Steinmetz, and Mari Ostendorf, and talks by senior UWIN and Swartz postdoctoral fellows. NCEC will end with a late afternoon reception on Friday in HUB 332.

December 2018 UWIN seminar: Short talks by Tom Daniel and Chris Rudell

December 2018 UWIN Seminar Speakers Tom Daniel and Chris RudellPlease join us for the December 2018 UWIN seminar! This seminar features a pair of short talks by UWIN faculty members Tom Daniel and Chris Rudell:

  • Engineering Odor Guided Flight”
    Tom Daniel, Professor, Department of Biology, University of Washington
  • Highly-Integrated Neural Stimulation Electronics for Bidirectional Brain-Computer Interfaces (BBCI) including Artifact Cancellation”
    Chris Rudell, Associate Professor, Department of Electrical and Computer Engineering, University of Washington

The seminar is on Wednesday, December 12, 2018 at 3:30pm in Husky Union Building (HUB) 337. Refreshments will be served prior to the talks.


“Engineering Odor Guided Flight” (Tom Daniel):

The capacity for animals to localize odor sources far exceeds what can be manufactured today. In part, this extraordinary capacity is due to the behavioral mechanisms animals use and in part to the neural machine they deploy. This talk will review past work in odor localization and then continue to a neuro-integrated system that draws on the unparalleled sensory capabilities of animals. It is also possible I may change my mind and talk about something else.


“Highly-Integrated Neural Stimulation Electronics for Bidirectional Brain-Computer Interfaces (BBCI) including Artifact Cancellation” (Chris Rudell):

Miniaturization of neural stimulation and recording electronics is a key obstacle to the vision of using in vivo Bidirectional Brain Computer Interfaces (BBCI) for neuromodulation. This presentation will highlight techniques enabling integration of BBCI systems in single chip form. Specifically, our group has focused on integrating stimulation electronics using low-voltage digital CMOS to achieve a reliable high-voltage compliant (+/-12V) single-chip stimulator. The chip is capable of delivering a Biphasic Current Pulse of up to 2mA into a broad range of electrode impedances, from purely resistive to capacitive. The presentation will conclude with the description of a recently fabricated BBCE chip. A product of joint collaborative efforts, this 2mm x 2mm single chip integrates a 64-channel neural recording front-end with 4-stimulation channels and both differential- and common-mode artifact cancellation in a 65nm TSMC process.

November 2018 UWIN Seminar: Joint seminar with the eScience Institute, talk by Reza Hosseini Ghomi

Reza Hosseini Ghomi, the November 2018 UWIN seminar speaker The November 2018 UWIN seminar is a special joint seminar with the eScience Institute! The seminar will be given by Reza Hosseini Ghomi, a Senior Fellow in the Department of Neurology at the University of Washington, and the Chief Medical Officer of NeuroLex Laboratories.  He will be speaking on:

Digital Biomarkers: Do they hold promise for better neuropsychiatric disease detection?

The seminar is on Wednesday, November 14th, 2018, at 3:30pm in Health Science Building (HSB) K-069. Refreshments will be served prior to the talk.


For this talk I would like to review the field of digital biomarkers and provide some background and context for our work. Specifically, what are digital biomarkers and how are they useful? I will show some results of our early work using recorded voice samples, accelerometer data, neuroimaging measures, and several other objective and subjective measures from patients with Parkinson’s, Depression, Schizophrenia, and from the Framingham Heart Study’s cognitive aging cohort. We will touch on the shifting paradigm of research to complete work in this area of big data and what we can do differently moving forward to offer novel insights.


Reza’s passion lies at the intersection of neuropsychiatry, technology, and education. He is most interested in bringing significant and measurable improvement to the screening, diagnosis, and treatment of neuropsychiatric illness through the advancement of technology, and empowerment through collaboration.

To that end, when he is not practicing neuropsychiatry, he is director of the DigiPsych Lab and chief medical officer for NeuroLex Laboratories where his research and development work focuses on the exciting new field of voice diagnostics – using a brief recording of voice to screen, diagnose, and track a wide range of illnesses in an ultra-rapid, cost-effective, accurate, and accessible way.

Drawing on his previous experience as an engineer – he develops imaging technology at Massachusetts General Hospital and an electronic health record for VecnaCares. He is also a founding partner of Stanford Brainstorm, the first behavioral health innovation and entrepreneurship laboratory.

He holds a BS in electrical and computer engineering from Rensselaer Polytechnic Institute, an MSE in biomedical and electrical engineering from Johns Hopkins University, and an MD from University of Massachusetts Medical School, and is now completing and transitioning from the University of Washington’s psychiatry residency to their neurology movement disorders fellowship to focus on neurodegenerative disease

October 2018 UWIN seminar: Short talks by Howard Chizeck and Bill Moody

Howard Chizeck and Bill Moody will give short talks at the October 2018 UWIN seminarThe UWIN seminar series resumes for the 2018-19 academic year!  The October 2018 UWIN seminar features an exciting pair of short talks by UWIN faculty members Howard Chizeck and Bill Moody:

  • “Challenges in Optimizing Deep Brain Stimulation”
    Howard Chizeck, Professor, Department of Electrical & Computer Engineering, University of Washington
  • “Trans-skull imaging of brain activity in neonatal mice during spontaneous sleep-wake cycles”
    Bill Moody, Professor, Department of Biology, University of Washington

The seminar is on Wednesday, October 10, 2018 at 3:30pm in Health Sciences Building (HSB) G-328.  Refreshments will be served prior to the talks.


“Challenges in Optimizing Deep Brain Stimulation” (Howard Chizeck):

Deep Brain Stimulation is an approved treatment for Parkinson’s Disease and essential tremor, and is under investigation at various institutions for several other neurological conditions. New devices make it possible to optimally select stimulation parameters for currently approved “open loop” treatments, and to implement closed loop algorithms that adjust stimulation “on the fly,” so as to address tradeoffs between symptom management and side effects. Recent results that we have obtained will be briefly described, and current challenges will be described.


“Trans-skull imaging of brain activity in neonatal mice during spontaneous sleep-wake cycles” (Bill Moody):

Widely propagating waves of electrical activity occur throughout the brain during early development, where they provide long- and short-range synchrony in neuronal activity that helps to establish cortical circuitry. Neuronal activity that is synchronized over large distances also occurs during adult slow-wave sleep and serves a central role in memory consolidation. Using trans-skull optical imaging of brain activity in neonatal mice, combined with power spectral analysis of EMG activity to measure sleep-wake cycles and dimensionality reduction methods to analyze the spatio-temporal patterns of brain activity, we have discovered that pan-cortical waves of activity, which had previously been thought to occur during all behavioral states in the developing brain, are in fact already segregated into sleep cycles by the end of the first postnatal week. Our results suggest that pan-cortical waves of activity in development may establish the long-range neuronal circuitry that is used in adult sleep to consolidate events experienced during wakefulness into long-term memory.

May 2018 UWIN seminar: Short talks by David Perkel and Rajiv Saigal

David Perkel and Rajiv Saigal, the 2018 May UWIN seminar speakers.Please join us for the May 2018 UWIN seminar! This installment features a fascinating pair of short talks by UWIN faculty members David Perkel and Rajiv Saigal:

  • A simple microcircuit for generating neural variability to support vocal learning”
    David Perkel, Professor,  Departments of Biology and Otolaryngology, University of Washington
  • “Opportunities and Limitations of Neuroengineering approaches to CNS injury”
    Rajiv Saigal, Assistant Professor, Department of Neurological Surgery, University of Washington

The seminar is on Wednesday, May 9th, 2018, at 3:30pm in Husky Union Building (HUB) 337. Refreshments will be served prior to the talks.


A simple microcircuit circuit for generating neural variability for vocal learning” (David Perkel):

Songbirds, like humans, learn their vocalizations from other individuals using a trial-and-error process. We study the neural mechanisms underlying this ability as a model both for speech learning but also more generally as a model for reinforcement learning of complex motor skills. One requirement of trial-and-error learning is variability from trial to trial. Songbirds have a basal ganglia circuit that generates and rapidly modulates neural and behavioral variability, and we have identified experimentally a simple neural microcircuit that can contribute to generating variability. We have also used a highly constrained neural model to explore this possible mechanism for exploring acoustic space during vocal learning.


“Opportunities and Limitations of Neuroengineering approaches to CNS injury” (Rajiv Saigal):

Both traumatic brain and spinal cord injury (TBI and SCI) involve a primary mechanical trauma and well-elucidated secondary injury mechanisms. In spite of this knowledge and promising pre-clinical data, multiple clinical trials have failed to demonstrate benefit for human patients. This talk will review some of the clinical challenges and unmet needs for treating these complex injuries. There is a growing body of literature on engineering approaches for treating TBI and SCI. We will review promising approaches and opportunities for collaboration at UW.


April 2018 UWIN seminar: Joint seminar with the eScience Institute, talk by John Darrell Van Horn

John Darrell Van Horn, the 2018 April UWIN/eScience Institute seminar speaker.Please join us for the April 2018 UWIN seminar! This month’s installment is special joint seminar with the eScience Institute and features a talk by John Darrell Van Horn, Associate Professor of Neurology, University of Southern California:

“Making data science training resources FAIR”

The seminar is on April 11th, 2018, at 3:30pm in Physics/Astronomy Auditorium (PAA) A102.


In our rapidly evolving information era, methods for handling large quantities of data obtained in biomedical research have emerged as powerful tools for confronting critical research questions. These methods are having significant impacts in diverse domains ranging from genomics, to health informatics, to environmental research, and beyond. The NIH’s Big Data to Knowledge (BD2K) Training Consortium, in particular, has worked to empower current and future generations of researchers with a comprehensive understanding of the data science ecosystem, giving them the ability to explore, prepare, analyze, visualize, and interpret Big Data. To this end, the BD2K Training Coordinating Center (TCC) was funded to facilitate in-person and online learning, and to open the concepts of data science to the widest possible audience. In this presentation, I will describe the activities of the BD2K TCC, particularly the construction of the Educational Resource Discovery Index (ERuDIte). ERuDIte identifies, collects, describes, and organizes over 10,000 data science training resources, including: online data science materials from BD2K awardees; open online courses; and videos from scientific lectures and tutorials. Given the richness of online training materials and the constant evolution of biomedical data science, computational methods applying information retrieval, natural language processing, and machine learning techniques are required. In effect, data science is being used to inform training in data science where the so-called FAIR principles apply equally to these resources as well as to the datatypes and methods they describe. As a result, the work of the TCC has aimed to democratize novel insights and discoveries brought forth via large-scale data science training. This presentation will be of interest to anyone seeking to personalize their own data science education, craft unique online training curricula, and/or share their own online training content.



Dr. Van Horn is an associate professor of neurology with additional appointments in neuroscience and in electrical engineering at the University of Southern California (USC) in Los Angeles, California. He received his bachelor’s degree in psychology from Eastern Washington University in Cheney, WA, a masters in electrical engineering and computer science from the University of Maryland, College Park, and his PhD from the University of London in the United Kingdom. He is an accomplished author (over 150 publications, h-index>45), university-level educator, and is known internationally as an expert in neuroinformatics and data sharing. He enjoys traveling, road cycling, mountaineering, is a private pilot, and lives in Los Angeles, CA, with his wife and two daughters.


March 2018 UWIN seminar: Short talks by Steve Perlmutter and Steve Brunton

Steve Perlmutter and Steve Brunton, the 2018 March UWIN seminar speakers.Please join us for the March 2018 UWIN seminar! This installment features a captivating duo of short talks by UWIN faculty members Steve Perlmutter and Steve Brunton:

  • Changes in Corticospinal Synaptic Strength Lead to Compensatory Changes in Cortical Neuron Firing. What’s the Feedback Signal?”
    Steve Perlmutter, Research Associate Professor, Department of Physiology & Biophysics, University of Washington
  • Learning physics and the physics of learning”
    Steve Brunton, Assistant Professor, Department of Mechanical Engineering, University of Washington

The seminar is on Wednesday, March 14th, 2018, at 3:30pm in Husky Union Building (HUB) 337.  Refreshments will be served prior to the talks.


“Changes in Corticospinal Synaptic Strength Lead to Compensatory Changes in Cortical Neuron Firing. What’s the Feedback Signal?” (Steve Perlmutter):

We are using activity-dependent electrical stimulation to induce synaptic plasticity in behaving non-human primates. Spinal stimulation triggered by corticomotoneuronal cell activity leads to increases in synaptic strength at the synapse to spinal motoneurons.  The activity pattern of the triggering cell changes after the conditioning in a compensatory manner.  The mechanism for this compensatory change is not clear, but suggests an unexpectedly tight feedback loop to precisely regulate cortical output to motoneurons.


Learning physics and the physics of learning” (Steve Brunton):

The ability to discover physical laws and governing equations from data is one of humankind’s greatest intellectual achievements.  A quantitative understanding of dynamic constraints and balances in nature has facilitated rapid development of knowledge and enabled advanced technology, including aircraft, combustion engines, satellites, and electrical power.  There are many more critical data-driven problems, such as understanding cognition from neural recordings, inferring patterns in climate, determining stability of financial markets, predicting and suppressing the spread of disease, and controlling turbulence for greener transportation and energy.  With abundant data and elusive laws, data-driven discovery of dynamics will continue to play an increasingly important role in these efforts.  This work develops a general framework to discover the governing equations underlying a dynamical system simply from data measurements, leveraging advances in sparsity-promoting techniques and machine learning.

2018 Neural Computation and Engineering Connection Highlights

Poster for the 2018 Neural Computation and Engineering ConnectionThe 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

Poster Session

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)

Poster session at the 2018 Neural Computation and Engineering ConnectionPoster session at the 2018 Neural Computation and Engineering ConnectionPoster session at the 2018 Neural Computation and Engineering ConnectionPoster session at the 2018 Neural Computation and Engineering Connection


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).

Allison Okamura speaks at the 2018 Neural Computation and Engineering Connection

Allison Okamura speaks at the 2018 Neural Computation and Engineering Connection







“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))

Neuroscience ethics panel at the 2018 Neural Computation and Engineering Connection





“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.

Azadeh Yazdan speaks at the 2018 Neural Computation and Engineering Connection





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.

David Reinkensmeyer speaks at the 2018 Neural Computation and Engineering Connection




“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.


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