Elucidating the principles behind neural processing with application to neuromodulation and implant design

利用目前的成像技术和仪器，可以从人脑中获得丰富的信息。但是，我们如何最好地解释这些数据，以便更好地了解大脑的功能，以进行科学探索和改善人类健康？理解大脑语言或其神经代码的一个挑战是，它本质上是复杂的。我们试图通过发展新的理论思想和应用这些方法来解决这个问题，以一种以前不可能的方式来理解和分类大脑状态。我们工作的一个领域是更好地表征脑电生理信号，我们一直在开发新技术来表征人类大脑的状态。目前还没有已知的治疗神经系统疾病如帕金森病的方法。然而，通过对运动系统的研究，我们将探索可以改善大脑植入和神经调节的策略。对这项研究的支持不仅可以更好地了解疾病，而且可以更清楚地了解运动系统的功能。与此同时，模拟大脑通路的基础工作正在进行。一项基于外周感觉神经元信息传递的新技术使我们能够理解，也许是第一次，大脑解释我们周围世界的一般原理。这种方法使用信息论和复杂性理论对感觉系统进行定量的理解。通过对感官信息加工的研究，我们的模型可以帮助设计视觉修复装置，使视力丧失者恢复视力。

With current imaging technology and instrumentation, there is a wealth of information that can be obtained from the human brain. But how do we best interpret this data to obtain a better understanding of the functioning of the brain both for scientific exploration and for the improvement of human health? A challenge with understanding the language of the brain, or its neural code, is that it is complex in nature. We attempt to tackle this problem by developing new theoretical ideas and applying these approaches to understand and classify brain states in a manner not previously possible. One area of our work has been to better characterize brain electrophysiological signals, where we have been developing new techniques to characterize the state of the human brain. Currently there are no known cures for neurological diseases like Parkinsonism. However through the study of the motor system, we will explore strategies that can improve brain implants and neuromodulation. Support for this research will not only allow better understanding of disease but allow a clearer picture of how the motor system functions. Parallel to this, fundamental work on modelling brain pathway is undergoing. A new technique based on the information transmission of peripheral sensory neurons allows us to understand, perhaps for the very first time, the generic principles by which the brain interprets the world around us. This method uses information theory and complexity theory to provide a quantitative understanding of the sensory system. By investigating sensory information processing, our model may help in the design of visual prosthetic devices which restore eyesight to those with vision loss.