Dynamics of neuronal interactions: Relation to behavior, firing rates, and distance between neurons

Abstract

This report describes exploration of the hypothesis that cortical function is mediated by dynamic modulation of coherent firing in groups of neurons. We recorded neuronal activity in the frontal cortex of behaving monkeys and found that correlation between neurons changed frequently within a fraction of a second and in relation to behavior. Those modulations can happen without modulation of firing rates. When firing rates are modulated, the modulation of correlation is not related to it in a simple way. Moreover, the dynamic patterns of correlation depend on the distance between neurons. These findings support the notion that, in order to perform a computational task, neurons can associate rapidly into a functional group, while dissociating from concurrently activated competing groups.

Neural Correlate of Spatial Presence in an Arousing and Noninteractive Virtual Reality: An EEG and Psychophysiology Study

“…This assumption is supported by electrophysiology, where neighboring neuronal populations show highly correlated activity. 49 The version of LORETA employed here used a three-shell spherical head model registered to the digitized Talairach and Tournoux 50 atlas (Brain Imaging Centre, Montreal Neurological Institute). The registration between spherical and Talairach and Tournoux head geometry used the realistic EEG electrode coordinates reported by Towle et al 51 Further, the source solution space was limited to cortical gray matter and hippocampi according to digitized probability atlas provided by the Montreal Neurologic Institute (number of voxels, 2394; voxel dimension, 7 mm 3 ).…”

Face-elicited ERPs and affective attitude: brain electric microstate and tomography analyses

“…assuming related orientations and strengths of neighboring neuronal sources). The assumption of simultaneous and synchronous activation of neighboring neurons is supported by animal single unit recordings (Llinas, 1988;Kreiter and Singer, 1992;Haalman and Vaadia, 1997). At each voxel, LORETA computes current density as the linear, weighted sum of the scalp electric potentials.…”

Comparison of simultaneously recorded [H215O]‐PET and LORETA during cognitive and pharmacological activation

“…It solves the inverse problem based on the assumption that the smoothest of all possible activity distributions is the most plausible one. This assumption is supported by electrophysiology, where neighboring neuronal populations show highly correlated activity [Haalman and Vaadia, 1997;Llinás, 1988]. Thus, EEG-LORETA results in solutions where neighboring voxels have maximally similar activity.…”

“…One such algorithm that has gained particular attention recently is Low Resolution Brain Electromagnetic Tomography (LORETA) [Pascal-Marqui et al, 1994;Pascual-Marqui, 1999]. LORETA is based on the assumption that the "smoothest" distribution of neuroelectric generators is the most likely one, i.e., that the activity of neighboring neurons is maximally correlated [Llinás, 1988;Haalman and Vaadia, 1997]. Although LORETA has localization power [Pascual-Marqui, 1999], its spatial resolution is, unlike that of PET, very low (ϳ3-4 cm).…”