,

2013). More generally, we foresee an expansion of new types of multifaceted probes for electrophysiological recording and stimulation that might incorporate not only capabilities for light detection or delivery, but also drug delivery or microfluidic sampling. Another major area in which electrical engineering is exerting a strong influence on neuroscience find more concerns brain-machine interfaces. An established class of such interfaces concerns sensory perception, with the cochlear implant as a paradigmatic example. Likewise, there has been sustained progress toward retinal prosthetics for restoring vision (Mathieson et al., 2012) and toward motor prosthetics for achieving artificial-limb control using neural signals sent from the brain and transduced into Selleckchem BMS-754807 electronic commands. Recent progress has conferred the ability to control a computer cursor or robotic arm by motor-impaired patients (Hochberg et al., 2012). This realm of prosthesis engineering is building heavily upon concepts from computational and analytical aspects of electrical engineering and computer science, including dynamical systems modeling, state space analysis, dimensionality reduction, and adaptive filtering (Dangi et al., 2013, Gilja et al., 2011 and Shenoy et al., 2013). We note that the notion of a neural prosthetic is conceptually broad, and nonelectrical prosthetics

(e.g., optical or magnetic) might be developed to augment or correct aspects of cognition or behavior. For basic neuroscience experimentation, all-optical approaches to brain-machine interfaces should also be feasible (optical readouts combined with optical manipulation of neural dynamics). We expect to see increased complexity in this prosthetics-focused fusion of engineering and systems neuroscience, as the needs and opportunities are enormous. For imaging the human brain, engineering and physics have long played key roles; for secondly example, magnetic resonance imaging (MRI) arose from nuclear magnetic resonance spectroscopy. We expect

continued major progress in the realm of MRI, with new computational approaches and instrumentation allowing unprecedented levels of detail to be revealed concerning the human brain and cognition. This will include not just instrumentation advances such as higher magnetic field strengths, but also improved computational approaches for registration of brain anatomy across different individuals and new methods for interpreting with high confidence the nature of the signals seen, as with diffusion tractography. And for controlling human nervous systems, there has been recent engineering progress in the design and development of optogenetic interfaces that may be useful for bidirectional modulation of activity, such as for major peripheral nerves (Liske et al., 2013). Finally, we take note of miniaturization, which involves electrical, mechanical, and materials engineering, among other domains.