IEEE Brain Webinar Series

IEEE Brain Webinar Series

Learn from the top subject matter experts in brain research and neurotechnology. The objective of the IEEE Brain Webinar Series is to be a point of learning for engineering and technology advancements that improve our understanding of the brain to treat diseases and to improve human condition.  We will be hosting a technical webinar approximately once every 2 months.


Upcoming Webinars

New IEEE Brain webinars coming soon!


Past Webinars

Modeling the Representation of Object Boundary Contours in Human fMRI Data
Dr. Mark Lescroart,
Assistant Professor, Cognitive & Brain Sciences Group, Department of Psychology, University of Nevada, Reno

Modeling the Representation of Object Boundary Contours in Human fMRI Data
Tuesday, 13 August 2019

The human visual system consists of a hierarchy of areas, each of which represents different features of the visual world. Recent studies have revealed that most brain areas—and even many individual neurons—represent information about multiple visual features. Thus, a complete model of the brain must specify the relative importance of multiple visual features across the visual hierarchy. This talk will describe our work to estimate the importance of object boundary contours relative to other features.
Boundary contours define the edges of figural objects in scenes, and figure/ground segmentation has long been held to be a critical process in human vision. However, the relative importance of boundary contours compared to both lower- and higher-level features (e.g. motion energy and visual categories) remains unknown. To address this issue, we measured fMRI responses while human subjects viewed two sets of movies that varied in many feature dimensions: rendered movies of artificial scenes and cinematic movies. We modeled responses to both sets of movies independently using the same three models: models of motion energy, object boundary contours, and visual categories. We used the encoding models to predict withheld fMRI data, and used variance partitioning to determine whether the various models explained unique or shared variance in each dataset. We found that the pattern of unique variance explained by the three models was qualitatively consistent across both datasets, with unique variance explained by boundary contours in Lateral Occipital cortex and other areas. However, the three models also shared substantially more variance in the cinematic movies, likely due to correlations between model features. For example, much of the motion energy in the cinematic movies was a result of people moving. The shared variance between all three models in the cinematic movies in particular highlights the need for complex stimulus sets in which features in different models are de-correlated from each other.


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Neurophotonic Systems: From Flexible Polymer Implants to in situ Ultrasonically-driven Light Guides with Dr. Maysam Chamanzar
Dr. Maysam Chamanzar,
Assistant Professor of Electrical Computer Engineering,
Carnegie Mellon University

Neurophotonic Systems: From Flexible Polymer Implants to in situ Ultrasonically-driven Light Guides
Tuesday, 18 June 2019

Understanding the neural basis of brain function and dysfunction may inform the design of effective therapeutic interventions for brain disorders and mental illnesses. Optical techniques have been recently developed for structural and functional imaging as well as targeted stimulation of neural circuits. One of the challenges of optical modality is light delivery deep into the brain tissue in a non-invasive or at least minimally invasive way.

Scattering and absorption prevents deep penetration of light in tissue and limits light-based methods to superficial layers of the tissue. To overcome this challenge, implantable photonic waveguides such as optical fibers or graded-index (GRIN) lenses have been used to deliver light into the tissue or collect photons for imaging. Existing large and rigid optical waveguides cause damage to the brain tissue and vasculature. In this talk, Dr. Maysam Chamanzar will discuss his research on developing next generation optical neural interfaces. First, Dr. Chamanzar will introduce a novel compact flexible photonic platform based on biocompatible polymers, Parylene C and PDMS, and GaN active light sources for optogenetic stimulation of neural circuits with high spatiotemporal resolution. This photonic platform can be monolithically integrated with implantable neural probes.

Then, Dr. Chamanzar will discuss his recent work on developing a novel complementary approach to guide and steer light in the brain using non-invasive ultrasound. Dr. Chamanzar will show that ultrasound waves can sculpt virtual graded-index (GRIN) waveguides in the tissue to define and steer the trajectory of light without physically implanting optical waveguides in the brain.

These novel neurophotonic techniques enable high-throughput bi-directional interfacing with the brain to understand the neural basis of brain function and design next generation neural prostheses.

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Euisik Yoon, Ph.D.
Professor, Dept. of Electrical Engineering and Computer Science
Professor, Dept. of Biomedical Engineering
Director, NSF International Program for Advancement of Neurotechnology
University of Michigan
Fiberless Optoelectrodes for Selective Optical Neuromodulation at Cellular Resolution
Tuesday, 30 April 2019

This talk will review the evolution of Michigan neural probe technologies toward scaling up the number of recording sites, enhancing the recording reliability, and introducing multi-modalities in neural interface including optogenetics. Modular system integration and compact 3D packaging approaches have been explored to realize high-density neural probe arrays for recording of more than 1,000 channels simultaneously. In order to obtain optical stimulation capability, optical waveguides were monolithically integrated on the silicon substrate to bring light to the probe shank tips. Excitation and inhibition of neural activities could be successfully validated by switching the wavelengths delivered to the distal end of the waveguide. For scaling of the number of stimulation sites, multiple micro-LEDs were directly integrated on the probe shank to achieve high spatial temporal modulation of neural circuits. Independent control of distinct cells was demonstrated ~50 μm apart and of differential somato-dendritic compartments of single neurons in the CA1 pyramidal layer of anesthetized and freely-moving mice.


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Anton Arkhipov, Ph.D.
Associate Investigator
Allen Institute for Brain Science
Data-Driven Modeling of Brain Circuits Based on a Systematic Experimental Platform
Wednesday, 20 February 2019

The Mindscope project at the Allen Institute aims to elucidate mechanisms underlying cortical function in the mouse, focusing on the visual system. This involves concerted efforts of multiple teams characterizing cell types, connectivity, and neuronal activity in behaving animals. An integral part of these efforts is the construction of models of the cortical tissue and cortical computations. To achieve this, multi-model experimental data are integrated into a highly realistic 230,000-neuron model of the mouse cortical area V1. We perform systematic comparisons of simulated responses to in vivo experiments and investigate the structure-function relationships in the models to make mechanistic predictions for experimental testing. To enable this work, we developed the software suite called Brain Modeling ToolKit (BMTK) and a modeling file format called SONATA. These tools, the models, and simulation results are all being made freely available to the community via the Allen Institute Modeling Portal.

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