Searching for Autocoherence in the Cortical Network with a Time-Frequency Analysis of the Local Field Potential

Abstract

Gamma-band peaks in the power spectrum of local field potentials (LFP) are found in multiple brain regions. It has been theorized that gamma oscillations may serve as a 'clock' signal for the purposes of precise temporal encoding of information and 'binding' of stimulus features across regions of the brain. Neurons in model networks may exhibit periodic spike firing or synchronized membrane potentials that give rise to a gamma-band oscillation that could operate as a 'clock.' The phase of the oscillation in such models is conserved over the length of the stimulus. We define these types of oscillations to be 'autocoherent.' We investigated the hypothesis that autocoherent oscillations are the basis of the experimentally observed gamma-band peaks: the autocoherent oscillator (ACO) hypothesis. To test the ACO hypothesis, we developed a new technique to analyze the autocoherence of a time-varying signal. This analysis used the continuous Gabor transform to examine the time evolution of the phase of each frequency component in the power spectrum. Using this analysis method, we formulated a statistical test to compare the ACO hypothesis with measurements of the LFP in macaque primary visual cortex, V1. The experimental data were not consistent with the ACO hypothesis. Gamma-band activity recorded in V1 did not have the properties of a 'clock' signal during visual stimulation. We propose instead that the source of the gamma-band spectral peak is the resonant V1 network driven by random inputs.

Differences in Gamma Frequencies across Visual Cortex Restrict Their Possible Use in Computation

“…Combined with these results, our findings support the idea that gamma rhythms are a resonant phenomenon arising from the interaction between local excitation and inhibition (Atallah and Scanziani, 2009; Brunel and Wang, 2003; Kang et al, 2009; Burns et al, 2010). Several fundamental cortical mechanisms such as divisive normalization (Heeger, 1992), adaptation (Heiss et al, 2008; Higley and Contreras, 2006) and gain control (Chance et al, 2002; Shu et al, 2003) rely on excitatory-inhibitory interactions; thus it is not surprising that detectable gamma rhythm is also present and is modulated during a variety of cognitive tasks such as attention (Fries et al, 2001; Womelsdorf and Fries, 2007), working memory (Pesaran et al, 2002) or cortico-spinal interactions (Schoffelen et al, 2005).…”

On the Universal Mechanism Underlying Conscious Systems and the Foundations for a Theory of Consciousness

“…Such a moment of disorder creates the prerequisites for a stimulus to induce a reorganization of the background activity and to prompt the emergence of the subsequent attractor (Freeman, 2004(Freeman, , 2009). These results imply that noise plays a fundamental role in the functioning of the brain, which has been confirmed by investigations of other groups (Kitajo, Doesburg, Yamanaka, Nozaki, Ward, & Yamamoto, 2007;Burns, Xing, Shelley, & Shapley, 2010;Burns, Xing, & Shapley, 2011).…”

Do gamma oscillations play a role in cerebral cortex?

“…Finally, recent studies that have looked at the reliability and consistency of gamma rhythms have reported that gamma is highly stochastic and lacks the attributes necessary to provide a clock or a communication channel (Figure 2e) [63–65]. Although part of this stochasticity could be due to changes in the behavioural state of the animal or variability associated with the estimation of power, and the proposed mechanisms could potentially operate even when gamma is not a perfect clocking signal [66], these mechanisms still require gamma to have enough power to generate time epochs in which the neurons are sufficiently depolarized to temporally coordinate their firing.…”