This short course provides a three-days long introduction to the field of computational neuroscience. Theoretical studies of brain functions have focused on the information processing properties of individual neurons, neural circuits and networks systems. Computational neuroscience seeks to study these functions as revealed by neurophysiological experiments through computational means, and, as such, is high interdisciplinary and cross-disciplinary. Our program brings together experimentalist, modelers, and theoreticians to illustrate the diverse approaches and disciplines that make up computational neuroscience.
The 2018 short course is sponsored by the Chinese Society for Neuroscience (Committee on Computational Neuroscience and Neural Engineering)，CSIAM Mathematical Life Sciences, the SJTU Institute of Natural Sciences, and the SJTU Zhiyuan College.
December 10 ~ 12, 2018
Room 601, Pao Yue-Kong Library, Minhang Campus, Shanghai Jiao Tong University
Please register online. Apply Online
Preference is given to, but not limited to, applicants with a basic understanding of ordinary differential equations and probability and a working knowledge of Matlab.
No registration fee. Participants should cover their own lodging and meals.
| Date | Time | Speaker & Short Bio | Title |
|---|---|---|---|
| Dec 10 | 08:55-09:00 | Group Photo | |
| 09:00-10:20 | Dezhong Yao | 90 Years of Human EEG — History、Current and the Future | |
| 10:40-12:00 | Dezhong Yao | 90 Years of Human EEG — History、Current and the Future | |
| 14:00-15:20 | Quan Wen | Motor Systems: Searching for Principles | |
| 15:40-17:00 | Quan Wen | Motor Systems: Searching for Principles | |
| Dec 11 | 09:00-10:20 | Xiao-Jing Wang | Models of Cognitive-type Neural Circuits and Large-scale Cortex |
| 10:40-12:00 | Xiao-Jing Wang | Models of Cognitive-type Neural Circuits and Large-scale Cortex | |
| Dec 12 | 09:00-10:20 | John Rinzel | Dynamics of Auditory Processing and Perception |
| 10:40-12:00 | John Rinzel | Dynamics of Auditory Processing and Perception | |
| 14:00-15:20 | Xiaohui Zhang | Neuronal Cirucit Mechanisms underlying Information Processing, Brain Plasticity and Learning | |
| 15:40-17:00 | Xiaohui Zhang | Neuronal Cirucit Mechanisms underlying Information Processing, Brain Plasticity and Learning |
By Dezhong Yao
Course time:
Abstract:
The first report of Human EEG was published in 1929 that was about 90 years ago, what have happend in this domain since then? and what’s the future for EEG in one hundred? In this lecture, we will review the temporal and spatial aspects of EEG with typical application examples to show the advantages and disadvantages, expecially the key techniques used in current psychological and clinic studies. Finally, the potential areas for the future are discussed，including fusing with other techniques and further mining the implicit information in EEG recordings.
By Quan Wen
Course time:
Abstract:
I will discuss our recent progress towards an algorithmic understanding of flexible control of motor behaviors. We are paying special attention to the one millimeter long nematode C. elegans, a unique systems neuroscience model to test computational theories via a combination of genetic and imaging methods.
Course time:
Abstract:
In this lecture, I will first introduce the concept of “cognitive-type” cortical microcircuits capable of working memory and decision-making, which are mathematically described as a strongly nonlinear neurodynamical system characterized by a duality of slow transients and attractor dynamics. Then, I will discuss recent work on modeling multi-regional large-scale cortex, using recently published databases of directed and weighted connectivity. We found that, by taking into account quantitative heterogeneity across cortical areas, such a large network naturally gives rise to a hierarchy of timescales: early sensory areas respond rapidly to an external input and the response decays away immediately after stimulus offset (appropriate for sensory processing), whereas association areas higher in the brain hierarchy are capable of integrating inputs over a long time and exhibit persistent activity (suitable for decision-making and working memory). This model has been expanded to incorporate a laminar structure of the cortex and to investigate frequency-dependent feedforward versus feedback neural signaling. Moreover, in such a complex brain system, routing of information between areas must be flexibly gated according to behavioral demands. For instance, when you try to read a book in a noisy café, it is desirable for your brain to “gate in” visual information while “gating out” auditory inputs. We propose such a gating mechanism with a disinhibitory circuit motif implemented by several subtypes of inhibitory neurons. The model provides a computational platform for investigating dynamics and functions of a large-scale brain.
By John Rinzel
Course time:
Abstract:
We will cover 3 main topics:
Slides:
Course time:
Abstract:
Diverse types of neurons are interconnected via local or long-range synapses to form specific neural circuits for executing particular brain functions and behaviors. Among the neuron constituents in many circuits, different subtypes of interneuron that releases inhibitory transmitter gamma-amino butyric acid (GABA) greatly enhance the complexity of circuit architecture and dynamic regulation. In the talk, I will present recent findings of our laboratory on the connectivity, function and plasticity of the hippocampal-cortical circuit, more emphasis on that of GABAergic inhibitory circuits. First, by extensive electrophysiological recording in the developing visual cortex ex vivo and in vivo, we have elucidated the circuit basis for the long-standing inhibition gating mechanism underlying a heightened experience-dependent cortical plasticity during a postnatal critical-period over development, as well as for the dynamic regulation of rhythmic cortical activity (oscillations) by distinct inhibitory cell circuits. Second, using viral-tool or ChR2-assisted circuitry mapping, we have delineated the fine-scale connectivity of an entorhinal cortex (EC)→hippocampal CA1 direct-circuit that is required for olfactory associative learning. On both technical and intellectual aspects, these findings also establish a solid basis for our further studies that unveil the principal maps of local and long-range connections of cortico-hippocampal circuits and a potentially novel form of plasticity in these circuit architectures induced by learning or early experience.
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