Spectral fingerprints of large-scale neuronal interactions

Key Points Goal-directed, sensory-guided behaviour relies on both feedforward and feedback interactions between brain regions. Studies of sensorimotor decision-making and top-down attention show that these large-scale interactions are reflected by the phase coherence and amplitude correlation of oscillations between brain regions. Phase coherence and amplitude correlation provide insights into the large-scale neuronal interactions underlying cognition. The frequencies of large-scale coherent oscillations reflect the neuronal circuit mechanisms of the canonical computations underlying cognition. The frequencies of large-scale coherent oscillations may constitute indices, or 'fingerprints', of these canonical computations. 'Spectral fingerprints' provide a level of description situated in between the 'processes' defined by cognitive psychology and the underlying neuronal circuit mechanisms. This level of description may help to identify commonalities and differences between cognitive processes. Cognition results from large-scale interactions among widely distributed brain regions. Siegel and colleagues review studies showing that these interactions are reflected by correlated neuronal oscillations. They propose that correlated oscillations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes. Cognition results from interactions among functionally specialized but widely distributed brain regions; however, neuroscience has so far largely focused on characterizing the function of individual brain regions and neurons therein. Here we discuss recent studies that have instead investigated the interactions between brain regions during cognitive processes by assessing correlations between neuronal oscillations in different regions of the primate cerebral cortex. These studies have opened a new window onto the large-scale circuit mechanisms underlying sensorimotor decision-making and top-down attention. We propose that frequency-specific neuronal correlations in large-scale cortical networks may be 'fingerprints' of canonical neuronal computations underlying cognitive processes.