One of the greatest challenges in neuroengineering, whether toward new therapies for neurological diseases or toward new means of human-computer interaction, is to advance our fundamental understanding of how the brain functions to the point where we may effectively interface the human brain with engineered systems that approach its intelligence.
Professor Cauwenberghs pioneered the design and implementation of highly energy efficient, massively parallel microchips that emulate function and structure of adaptive neural circuits in silicon. Embedded mechanisms of synaptic plasticity in these silicon microcircuits model the adaptive intelligence of biological nervous systems interacting with variable and unpredictable environments, and assist in optimizing the energy efficiency and noise robustness of nanoscale circuit components implementing the neural functions. Recently the Cauwenberghs group demonstrated synaptic arrays in silicon for adaptive template-based visual pattern recognition operating at less than a femtojoule of energy per synaptic operation, exceeding the nominal energy efficiency of synaptic transmission in the human brain.
A main focus of current work is on extending integrated sensing and actuation to dynamical interfaces to neural and brain activity. Recent developments include implantable and wireless microelectrode arrays for distributed recording of electrical and chemical neural activity, and biopotential sensor arrays and integrated signal processing for electroencephalogram and electrocorticogram functional brain imaging. These dynamical interfaces between living and artificial nervous systems offer tremendous opportunities for transformative, integrative neuroscience and neuroengineering that are the focus of continued research in the Cauwenberghs laboratory, in collaboration with partners in academia, industry, and the clinical sector.