Power-Law Scaling in the Brain Surface Electric Potential

Recent studies have identified broadband phenomena in the electric potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the electric potential has the power-law form from 80 to 500 Hz. This scaling index, , is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, , increases. We observe a “knee” in the spectra at , implying the existence of a characteristic time scale . Below , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory “asynchronous,” scale-free, changes in cortical potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent “synchronous” rhythm-based paradigm

Economic Analysis of Knowledge: The History of Thought and the Central Themes

Following the development of knowledge economies, there has been a rapid expansion of economic analysis of knowledge, both in the context of technological knowledge in particular and the decision theory in general. This paper surveys this literature by identifying the main themes and contributions and outlines the future prospects of the discipline. The wide scope of knowledge related questions in terms of applicability and alternative approaches has led to the fragmentation of research. Nevertheless, one can identify a continuing tradition which analyses various aspects of the generation, dissemination and use of knowledge in the economy

Multi-scale analysis of neural activity in humans: Implications for micro-scale electrocorticography

Objective: Electrocorticography grids have been used to study and diagnose neural pathophysiology for over 50 years, and recently have been used for various neural prosthetic applications. Here we provide evidence that micro-scale electrodes are better suited for studying cortical pathology and function, and for implementing neural prostheses. Methods: This work compares dynamics in space, time, and frequency of cortical field potentials recorded by three types of electrodes: electrocorticographic (ECoG) electrodes, non-penetrating micro-ECoG (μECoG) electrodes that use microelectrodes and have tighter interelectrode spacing; and penetrating microelectrodes (MEA) that penetrate the cortex to record single- or multiunit activity (SUA or MUA) and local field potentials (LFP). Results: While the finest spatial scales are found in LFPs recorded intracortically, we found that LFP recorded from μECoG electrodes demonstrate scales of linear similarity (i.e., correlation, coherence, and phase) closer to the intracortical electrodes than the clinical ECoG electrodes. Conclusions: We conclude that LFPs can be recorded intracortically and epicortically at finer scales than clinical ECoG electrodes are capable of capturing. Significance: Recorded with appropriately scaled electrodes and grids, field potentials expose a more detailed representation of cortical network activity, enabling advanced analyses of cortical pathology and demanding applications such as brain–computer interfaces