Modeling the electrical field created by mass neural activity.

Gamma oscillations of large scale electrical activity are used in electrophysiological studies as markers for neural activity and functional processes in the cortex, yet the nature of this mass neural phenomenon and its relation to the evoked response potentials (ERP) are still not well understood. Many studies associated the gamma oscillations with oscillators around the 40 Hz frequency, yet recent studies have shown that gamma frequencies may be part of a broadband phenomenon ranging from 30 Hz up to 250 Hz. In this study we have examined the possibility that a simple model, based on available neurophysiological parameters, involving an increase in asynchronous (Poisson distributed) neural firing may be sufficient to generate the observed gamma power increases. Our simulation shows a roughly linear increase in gamma power as a function of the aggregated firing rate of the neural population, while the influence of the synchronization level within the neurons on the gamma power is limited. Our model supports the viewpoint that the broadband gamma response is mainly driven by the summed, asynchronous, activity of the neural population. We show that the time frequency spectrogram of the stimulus response can be reconstructed by combining two different phenomena-the broadband gamma power increase due to local processing and the more spatially distributed event related desynchronization (ERD). Our model thus raises the possibility that the broadband gamma response is closely linked to the aggregate population firing rate of the recorded neurons.

Antagonistic relationship between gamma power and visual evoked potentials revealed in human visual cortex.

Scalp electroencephalography and magnetoencephalography studies have revealed a rapid evoked potential "adaptation" where one visual stimulus suppresses the event-related potential (ERP) of the second stimulus. Here, we investigated a similar effect revealed in subdural intracranial recordings in humans. Our results show that the suppression of the subdural ERP is not associated with a reduction in the gamma frequency power, considered to reflect the underlying neural activity. Furthermore, the evoked potential suppression (EPS) phenomenon was not reflected in recognition behavior of the patients. Rather, the EPS was tightly linked to the level of gamma activity preceding the event, and this effect was independent of the interstimulus time interval. Analyzing other frequency bands failed to reveal a similar link. Our results thus show a consistent antagonism between subdural ERP and gamma power although both are considered markers for neural activity. We hypothesize that the ERP suppression is due to a desynchronization of neuronal firing resulting from recurrent neural activity in the vicinity of the freshly stimulated neurons and not an attenuation of the overall neural activity.

Neural "ignition": enhanced activation linked to perceptual awareness in human ventral stream visual cortex.

Human recognition performance is characterized by abrupt changes in perceptual states. Understanding the neuronal dynamics underlying such transitions could provide important insights into mechanisms of recognition and perceptual awareness. Here we examined patients monitored for clinical purposes with multiple subdural electrodes. The patients participated in a backward masking experiment in which pictures of various object categories were presented briefly followed by a mask. We recorded ECoG from 445 electrodes placed in 11 patients. We found a striking increase in gamma power (30-70 Hz) and evoked responses specifically associated with successful recognition. The enhanced activation occurred 150-200 ms after stimulus onset and consistently outlasted the stimulus presentation. We propose that the gamma and evoked potential activations reflect a rapid increase in recurrent neuronal activity that plays a critical role in the emergence of a recognizable visual percept in conscious awareness.

Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex.

Animal studies have shown robust electrophysiological activity in the sensory cortex in the absence of stimuli or tasks. Similarly, recent human functional magnetic resonance imaging (fMRI) revealed widespread, spontaneously emerging cortical fluctuations. However, it is unknown what neuronal dynamics underlie this spontaneous activity in the human brain. Here we studied this issue by combining bilateral single-unit, local field potentials (LFPs) and intracranial electrocorticography (ECoG) recordings in individuals undergoing clinical monitoring. We found slow (<0.1 Hz, following 1/f-like profiles) spontaneous fluctuations of neuronal activity with significant interhemispheric correlations. These fluctuations were evident mainly in neuronal firing rates and in gamma (40-100 Hz) LFP power modulations. Notably, the interhemispheric correlations were enhanced during rapid eye movement and stage 2 sleep. Multiple intracranial ECoG recordings revealed clear selectivity for functional networks in the spontaneous gamma LFP power modulations. Our results point to slow spontaneous modulations in firing rate and gamma LFP as the likely correlates of spontaneous fMRI fluctuations in the human sensory cortex.

Enhanced category tuning revealed by intracranial electroencephalograms in high-order human visual areas.

The functional organization of human sensory cortex was studied by comparing intracranial EEG (iEEG) recordings of local field potentials in neurosurgical patients with functional magnetic resonance imaging (fMRI) obtained in healthy subjects. Using naturalistic movie stimuli, we found a tight correlation between these two measures throughout the human sensory cortex. Importantly, the correlation between the iEEG and fMRI signals was site-specific, exhibiting neuroanatomically specific coupling. In several cortical sites the iEEG activity was confined strictly to one object category. This site selectivity was not limited to faces but included other object categories such as houses and tools. The selectivity of the iEEG signals to images of different object categories was remarkably higher when compared with the selectivity of the corresponding fMRI signals. A plausible interpretation of the fMRI and iEEG results concerns cortical organization in which object categories are organized in a mosaic of narrowly tuned object-selective clusters.