Plenary Speaker
Masakatsu G. Fujie, PhD.

"Robot project in Japan -Basic Technology Development for Practical Application of Human Support Robots"

Plenary Speaker
Jack Gallant, PhD.

"Lets see what you think! Bayesian reconstruction of perceptual experiences from human brain activity"

Recent interest in brain-computer interfaces has pushed development of decoding models that aim to classify, identify or reconstruct visual stimuli directly from measured brain activity. Most decoding models are based on non-parametric algorithms such as SVM and do not exploit current computational models of visual processing. We have pioneered an alternative approach in which the decoding algorithm is inferred from one or more explicit visual processing (nonlinear filtering) models. In previous work we showed that our approach extracts far more information from functional MRI measurements than was generally believed possible. In this task I will describe a new Bayesian decoding model that can actually reconstruct natural images that were seen by an observer from brain activity measured using fMRI. The decoder combines three elements: (1) a structural encoding model that characterizes signals from early visual areas; (2) a semantic encoding model that characterizes signals from higher visual areas; and (3) appropriate priors that incorporate statistical information about the structure and semantics of natural scenes. By combining all these elements the decoder produces reconstructions that accurately reflect the distribution, structure and semantic category of the objects contained in the original image. These results help clarify how distinct representations in different parts of the brain can be combined to provided a coherent reconstruction of the visual world; they also highlight a potentially important role for prior knowledge in visual perception. Our Bayesian decoding framework can be generalized directly to permit reconstruction of other perceptual dimensions, and might facilitate reconstruction of subjective perceptual processes such as visual imagery and dreaming. In the future Bayesian decoding algorithms might form the basis of powerful new brain-reading technologies and brain-computer interfaces.

Plenary Speaker
Arto V. Nurmikko, PhD.

"Developments in Implantable Wireless Cortical Interfaces for Neural Prosthetics"

Neuroscience has made remarkable progress in unraveling the machinery of the human (mammalian) brain, especially at the cellular and to some extent at the systems level (brain as a neural network computer). From this has emerged a fascinating contemporary technical (and ethical) challenge: Is it possible to implement a functional interconnect from the brain to implantable microelectronic circuits, to further advance our understanding of the brain per se, as well as for applications in neural prosthetics.

This presentation will selectively highlight current research which aims at developing a wireless electronic link to the brain via implantable active microchips. The works draws from recent advances in recording and deciphering selected command signals issued from the motor cortex by small targeted population of neurons for specific motor tasks. While in this instance only a passive cortical microelectrode recording array resides physically within the body of a subject, we will show examples of current developments where active electronics on a chipscale are integrated to the microscale neural probes within the skin envelope – with transcutaneous telemetry ‘broadcasting’ multichannel neural signals as a single high-speed digital data stream. The ultralow power requirements associated with implanting of such chips within the brain, as well as achieving wideband telemetry of signals across the skull and skin envelopes both require innovations through microelectronics and photonics. Likewise, encapsulation (packaging) techniques for effectively hermetically sealing active electronics, with full biocompatibility, are a key challenge yet to be fully resolved for chronic implants. We will review the present technology which at this writing involves short term (~ month) implants in non-human primate models.
Research Supported by U.S. National Institutes of Health