Understanding the nature of the neural code is of intrinsic scientific interest since it brings us closer to understanding the computational basis of intelligence. In addition, technical advances have made it possible to monitor the activity of populations of neurons in human subjects. The volume of data generated by multiple-neuron recordings poses significant challenges for data analysis. The development of new statistical techniques is necessary to provide a meaningful basis for testing hypotheses about the nature of neural coding. One concrete example is in the area of neuronal synchrony. The coordination on a short time scale of neuronal populations has been suggested as the basis for multiple neural processes such as attention and feature binding. However, the co-variation in firing rates among neurons, especially on a short time scale, poses significant practical challenges to specifying appropriate data analysis and statistical methods.
This award provides support for an international symposium on the topic of Statistical Modeling and Data Analysis for Neural Coding to be held in conjunction with the International Statistics Institute's biennial meeting at Durban, South Africa, August 2009. This symposium will bring together several statistical experts on neural coding to discuss a range of approaches to this problem. These approaches include both the generation of surrogate data sets and new statistical methods. These statistical methods may also have value for other scientific areas where multiple elements show short time scale temporal co-variation. The symposium is part of a large meeting of statistical experts. In addition to bringing together the symposium speakers to address this issue, the symposium will expose the larger statistical community to these questions and to the new statistical approaches. As the meeting will be happening on the African continent, the meeting provides an opportunity for education and outreach to African university and graduate students.
