Multiple single unit recording in the cortex of monkeys using independently moveable microelectrodes.

Simultaneous recording from multiple single neurones presents many technical difficulties. However, obtaining such data has many advantages, which make it highly worthwhile to overcome the technical problems. This report describes methods which we have developed to permit recordings in awake behaving monkeys using the 'Eckhorn' 16 electrode microdrive. Structural magnetic resonance images are collected to guide electrode placement. Head fixation is achieved using a specially designed headpiece, modified for the multiple electrode approach, and access to the cortex is provided via a novel recording chamber. Growth of scar tissue over the exposed dura mater is reduced using an anti-mitotic compound. Control of the microdrive is achieved by a computerised system which permits several experimenters to move different electrodes simultaneously, considerably reducing the load on an individual operator. Neurones are identified as pyramidal tract neurones by antidromic stimulation through chronically implanted electrodes; stimulus control is integrated into the computerised system. Finally, analysis of multiple single unit recordings requires accurate methods to correct for non-stationarity in unit firing. A novel technique for such correction is discussed.

Fundamental limits on the suppression of molecular fluctuations.

Negative feedback is common in biological processes and can increase a system's stability to internal and external perturbations. But at the molecular level, control loops always involve signalling steps with finite rates for random births and deaths of individual molecules. Here we show, by developing mathematical tools that merge control and information theory with physical chemistry, that seemingly mild constraints on these rates place severe limits on the ability to suppress molecular fluctuations. Specifically, the minimum standard deviation in abundances decreases with the quartic root of the number of signalling events, making it extremely expensive to increase accuracy. Our results are formulated in terms of experimental observables, and existing data show that cells use brute force when noise suppression is essential; for example, regulatory genes are transcribed tens of thousands of times per cell cycle. The theory challenges conventional beliefs about biochemical accuracy and presents an approach to the rigorous analysis of poorly characterized biological systems.