Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Form-function relations in cone-tipped stimulating microelectrodes.

Metal microelectrodes are widely used in neuroscience research, and could potentially replace macroelectrodes in various neuro-stimulation applications where their small size, specificity, and their ability to also measure unit activity are desirable. The design of stimulating microelectrodes for specific applications requires knowledge on how tip geometry affects function, but several fundamental aspects of this relationship are not yet well understood. This study uses a combined experimental and physical finite elements simulation approach to formulate three new relationships between the geometrical and electrical properties of stimulating cone-tipped tungsten microelectrodes: (1) The empirical relationship between microelectrode 1-kHz impedance and the exposed tip surface area is best approximated by an inverse square-root function (as expected for a cone-tipped resistive interface). (2) Tip angle plays a major role in determining current distribution along the tip, and as a consequence crucially affects the charge injection capacity of a microelectrode. (3) The critical current for the onset of corrosion is independent of tip surface area in sharp microelectrodes.