Functional coupling shows stronger stimulus dependency for fast oscillations than for low-frequency components in...

It has been argued that coupling among the neural signals activated by a visual object supports binding of local features into a coherent object perception. During visual stimulation by a grating texture we studied functional coupling by calculating spectral coherence among pairs of signals recorded in the striate cortex of awake monkeys. Multiple unit activity (MUA) and local field potentials (LFP, 1-140 Hz) were extracted from seven parallel broad band recordings. Spectral coherence was dominated by high-frequency oscillations in the range 35-50 Hz and often by additional low-frequency components (0-12 Hz). Functional coupling among separate cortical sites was more stimulus specific for MUA than for LFP: MUA coherence at high and low frequencies depended highly significantly on: (i) the similarity of the preferred orientations at the two sites - the more similar the higher the coherence; (ii) the orientation of the stimulus grating - with highest coherence at half angle between the preferred orientations at the two sites; (iii) cortical distance - coherence decreases to noise levels at approximately 3 mm (MUA) and 6 mm (LFP). Coherence of fast oscillations did not depend on the degree of coaxiality of the orientation-sensitive receptive fields, whereas low frequencies showed significant dependency. This indicates that different frequency components can engage different coupling networks in the striate cortex which probably support different coding tasks. Changes in average oscillation frequency with stimulus orientation were highly significant for fast oscillations while there was no dependency for low frequencies. Finally, stimulus-related spectral power and coherence of fast oscillations were considerably higher than of low frequency components. Fast oscillations may therefore contribute more to feature binding and coding of object continuity than low-frequency components, at least for texture surfaces as analysed here.