KAIST Neural Code Workshop
- Aug 29, 2016 (11:00:19)
KAIST Neural Code Workshop
NOV 2 Wednesday, 2016
Dream Hall (1st floor)
CHUNG Moon Soul building (E16)
KAIST main campus
*Registration is required (free).
The KAIST neural code workshop, Deciphering Brain’s Neural Codes, is a half-day event to discuss various approaches in computational/theoretical neuroscience, applied physics, and machine learning to understand brain functions.
Topics we will discuss include:
- 3D structures of neurons
- functional organization of neural networks
- cognitive control processes
- dimensionality of neural activities
- distributed information encoding of neurons
*Sponsors: KAIST Bio-IT Healthcare Initiative, Department of Bio and Brain Engineering
*Host: Sang Wan Lee (For inquiries, please contact us at email@example.com)
Registration form (it's free; coffee and snacks provided)
List of Speakers
Se-Bum Paik (KAIST, South Korea)
He is an assistant professor of the department of bio and brain engineering at KAIST. He received his PhD in physics at University of California, Berkeley. He was a postdoctoral associate at UCLA. He was awarded POSCO TJ Park Science Fellowship. His research interest is computational neuroscience, focusing on the dynamics of the functional organization of the neural networks in visual system.
Sang Wan Lee (KAIST, South Korea)
He is an assistant professor of the department of bio and brain engineering at KAIST. He received his PhD in electrical engineering and computer science at KAIST. He was a postdoctoral associate at MIT, and a Della Martin postdoctoral scholar at Caltech. His research interests include brain-inspired artificial intelligence and computational neuroscience.
Jinseop Kim (Korea Brain Research Institute, South Korea)
He is a senior research members at the Korea Brain Research Institute. He received his PhD in physics at Seoul National University. He was a postdoctoral researcher at MIT and Princeton. His research interests include computational neuroscience, neuroanatomy, and connectomics. He was a leading scientist of the brain-mapping game EyeWire to precisely map the cells of a mouse retina and shed a light on how those cells detect motion (Nature 2014).
Mattia Rigotti (IBM T.J. Watson Research Center, USA)
He is a research staff member in the Theory and Computational Physics Group at the IBM T. J. Watson Research Center. He received his PhD in neuroscience and M. Phil. in neurobiology and behavior at Columbia University. He was an associate research fellow at the Center for Theoretical Neuroscience and The Italian Academy for Advanced Studies at Columbia University. His research interests include neuromorphic engineering, computational neuroscience, neural networks and machine learning. He applies machine learning theory on electrophysiology data to understand neural coding schemes underlying rule-based behavior (Nature 2013, Nature 2015, and Neuron 2015).
14:00-14:10 [10min] Opening remarks (Sang Wan Lee)
14:10-14:40 [30min] Functional structure of cortical neural networks for visual information processing (Se-Bum Paik)
In the primary visual cortex of higher mammals, neurons are often spatially organized by their stimulus preference, forming various types of functional maps. Explaining the origin and role of these functional structures is crucial to understanding how various components of information are being processed in the brain. Our research over the past few years has focused on developing a new theoretical model of the initial development of functional structures in the primary visual cortex (V1). We built a unified model of developmental mechanism of various cortical functional maps, which not only successfully explains the observed geometrical correlations between different functional maps, but also accounts for the intriguing developmental mechanism of functional circuits in the brain for effective information processing. This theoretical model may significantly change our current view of the functional structure of the brain, and helps us better understand how we take theoretical and computational approaches to study the neural circuits for various brain functions.
14:40-15:10 [30min] Markov decision process unfolds within the human prefrontal cortex (Sang Wan Lee)
15:10-16:10 [60min] TBA (Jinseop Kim)
16:10-16:30 [30min] Coffee break
16:30-17:30 [60min] High and low-dimensional neural responses for learning and implementing context-dependent behavior (Mattia Rigotti)