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Distinguished Lecturer Series in Brain and Cognitive Sciences
Distinguished Lecturer Series in Brain and Cognitive Sciences will begin its second season of public lectures by nationally and internationally-recognized researchers on Wednesday, March 17, 2010 beginning at 4pm.
All lectures are free and open to the public and no reservations are necessary, For more information about the Distinguished Lecturer Series, Contact Jieun Esther Shin at +82-2-880-9108.
| Speaker | Data & Time | Title | Location |
| Min Zhuo | 3/17 W 4-6pm | Where is my Pain? | Mok-am Hall, Bldg 501 |
| Sebastian Seung | 3/24 W 4-6pm | Tracing the Brain's Wires with Computer Vision | Mok-am Hall, Bldg 501 |
| Raymond Kesner | 4/14 W 4-6pm | Different Functions for Different Subregins of the Hippocampus: a Process and Pathway Analysis |
Mok-am Hall, Bldg 501 |
| Marcus Kaiser | 5/19 W 4-6pm | Ghost in the Shell: Simulating Brain Network Dynamics in Health and Disease | Mok-am Hall, Bldg 501 |
Wednesday, March 17
Min Zhuo
Brain and Cognitive Sciences, SNU
University of Toronto
- Title: Where is my Pain?
- Time: 4pm
- Location: Mok-am Hall, Bldg 501
New automated methods of serial electron microscopy are expected to produce teravoxel and petavoxel-sized images of the brain's neural networks. Analysis of these 3d images involves a number of difficult challenges, the foremost being accurate tracing of the "wires" of the brain, its axons and dendrites. This is an example of a long-standing problem in computer vision known as image segmentation. I will describe BLOTC and MALIS, the first supervised learning methods based on genuine measures of image segmentation performance. These methods can be used to train convolutional networks that are much more accurate at image segmentation than competing algorithms developed with less complete (or no) use of machine learning. If the tracing problem were solved, it would become possible to find "wiring diagrams" or “connectomes," which in turn would pose further challenges for computational neuroscience. I will describe how algorithms for graph analysis could be applied to connectomes to test neural network theories of brain function. One of the most exciting prospects would be to decode the memories that are hypothesized to be stored in connectomes.
Wednesday, March 24
Sebastian Seung
Brain and Cognitive Sciences, SNU
MIT
- Title: Tracing the Brain's Wires with Computer Vision
- Time: 4pm
- Location: Mok-am Hall, Bldg 501
Computational neuroanatomy is an emerging .eld that utilizes various non-invasive brain imaging modalities such as magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations in macroscopic level. This discipline emerged about twenty years ago and has made substantial progress in the past decade. It usually deals with computational problems arising from the quanti.cation of within- and between-subject variations associated with the structure and the function of the human brain. Major challenges in the .eld are caused by the massive amount of nonstandard high dimensional non-Euclidean imaging data that are difficult to analyze using traditional methods. This requires new computational solutions that incorporates geometric and topological nature of brain structures. Overview of various computational issues in neuroanatomy will be presented with example studies on autism.
Wednesday, April 14
Raymond Kesner
Brain and Cognitive Sciences, SNU
- Title: Different Functions for Different Subregions of the Hippocampus: a Process and Pathway Analysis
- Time: 4pm
- Location: Mok-am Hall, Bldg 501
In recent years, there has been an increasing interest in determining whether specific subregions [dentate gryus (DG), CA3, and CA1] of the hippocampus are differentially involved in mnemonic processes that are assumed to be mediated by the hippocampus. I will present evidence showing that (a) the DG has at least three major functions including conjunctive encoding of multiple sensory inputs, spatial pattern separation, and facilitation of encoding of spatial information, (b) the CA3 has at least three major functions including short-term memory and rapid encoding, arbitrary associations, and pattern completion, and (c) the CA1 has at least four major functions including temporal processing of information (temporal order memory), association across time, intermediate-term memory, and consolidation of new information. I will present additional evidence suggesting that there are both associations and dissociations among the DG, CA1 and CA3 subregions of the hippocampus.
Wednesday, May 19
Marcus Kaiser
Brain and Cognitive Sciences, SNU
Institute of Neuroscience, Newcastle University, UK
- Title: Unlimited events in a limited space - The hippocampal dilemma
- Time: 4pm
- Location: Mok-am Hall, Bldg 501
The human brain consists of connections between neurons at the local level and of connections between brain regions at the global level. The study of the entire network, the connectome, has become a recent focus in neuroscience research. Using routines from physics and the social sciences, neuronal networks were found to show properties of scale-free networks, making them robust towards random damage, and of small-world systems leading to better information integration. I will describe the main features of the topological and spatial organisation of neural systems and how they differ from artificial systems information processing systems such as computers. Recent clinical studies in the last three years have shown that the network features of the healthy brain differ from that of schizophrenia, epilepsy, and Alzheimer’s disease patients. These features even differ depending on cognitive features such as IQ. I will show how network features and simulations of brain activity can be used to assess and model changes in patients. For example, simulating the spreading of epileptic seizures can inform of underlying reasons for epilepsy. I will finally outline how these methods could improve therapies for mental and cognitive disorders in the future.
