The statistical properties of the spontaneous background electrocorticogram (ECoG) were modeled,

The statistical properties of the spontaneous background electrocorticogram (ECoG) were modeled, starting with random numbers, constraining the distributions, and identifying characteristic deviations from randomness in ECoG from subjects at rest and during intentional behaviors. after band pass filtering in the beta and gamma ranges revealed beats from interference among distributed frequencies in band pass filtered noise called Rayleigh noise. The beats were displayed as repetitive down spikes in log10 analytic power. Repetition rates were proportional to filter bandwidths for all those center frequencies. Resting ECoG often gave histograms of the magnitudes and intervals of down spikes that conformed to noise. Histograms from active ECoG often deviated from noise in Rayleigh distributions of VX-950 cost down spike intervals by giving what are called Rice (Mathematical analysis of random noiseand appendixestechnical publications monograph B-1589. Bell Telephone Labs Inc., New York, 1950) distributions. Adding power to noise VX-950 cost as signals at single frequencies simulated those deviations. The beats in dynamic theory are deemed essential for belief, by gating beta and gamma bursts at theta rates through enhancement of the cortical signal-to-noise ratio in exceptionally deep down spikes called null spikes. or activity. When the brain initiates intentional behavior and receives an expected stimulus, the appearance of brain activity changes from this background in directions that are related to the kind of stimulus and what sort of intentional behavior emerges (Freeman 2006b, VX-950 cost 2007d). The obvious evolutionary advantage of having the background activity, despite its high metabolic cost, lies in the readiness of the brain to respond to any environmental threat or opportunity with minimal delay. The problem resolved here is to describe the biophysical properties of the cortical background activity, so as to explain how the brain can so abruptly transit from rest to intentional action. The proposed answer is usually to ascribe to the brain the state of criticality (SOC). The archetype for this state is the cone of sand in an hourglass that by avalanches (sudden state transitions) maintains its crucial slope under continuous increase in height (Jensen 1998). Many physicists regard the VX-950 cost concept as lacking in theoretical substance; nevertheless it usefully explains the spatiotemporal appearance of the ECoG on the surface of sensory cortex, which resembles a pan of boiling water holding itself at its crucial heat (Freeman 2004b, 2007b). That brain state of readiness can also be described as (Kelso 1995; Bressler and Kelso 2001) anditinerant(Tsuda 2001). The Rabbit Polyclonal to ENDOGL1 transition from rest or expectancy to action can be brought on by a stimulus or by unknown brain processes, but with an unpredictable endogenous delay (Freeman 2007c). The focus in this statement is around the properties of an event manifested in a recurrent discontinuity in the analytic phase derived from band pass filtered ECoG. VX-950 cost The event is a repetitive abrupt decrease in the analytic power in filtered ECoG called a from intermittent cancellation and summation. The deepest of the down spikes 10?4 from your maximal power are called (Freeman et al. 2008). This statement is focused around the questions raised by (Rice 1950): what is the repetition rate of down spikes, and how is it related to the width of the pass band for signals in the ECoG? The questions are important, because these beats may be closely related to the velocity of belief. It is already known that beats in band pass filtered EEG (Freeman et al. 2003) and ECoG (Freeman 2004a, b) tend to recur at theta frequencies, and that beta and gamma bursts likewise recur in what is known as the in activity which is found in allocortical ECoG (Freeman 1975; Fell et al. 2003; Lisman 2005), neocortical ECoG (Chrobak and Buzski 1998; Freeman 2005b), and human scalp EEG (Schack et al. 2002; Freeman et al. 2003; Canolty et al. 2006). Success in simulations of this cross-spectral linkage with filtered noise would provide strong evidence that the background activity of brains emerges from noise. If it could be shown how the background activity in brains originates in random noise, that obtaining would facilitate the detection of brain signals and help to define the elusive and uncertain state of rest in the brain. It would aid in the detection of distortions and artifacts in data analysis, by giving a canonical form for the PSD of resting ECoG. Deviations from that form would constitute either signals or non-random artifacts. Most importantly, the triggering by null spikes from thin band carrier frequencies of transitions could then be explored in terms of a remarkably simple neural mechanism for cinematographic framing in belief (Freeman 2007c): beats with intervals in what is called the (after Rice 1950) may.