Cortical oscillations and sensory predictions

Many theories of perception are anchored in the central notion that the brain continuously updates an internal model of the world to infer the probable causes of sensory events. In this framework, the brain needs not only to predict the causes of sensory input, but also when they are most likely to happen. In this article, we review the neurophysiological bases of sensory predictions of “what’ (predictive coding) and ‘when’ (predictive timing), with an emphasis on low-level oscillatory mechanisms. We argue that neural rhythms offer distinct and adapted computational solutions to predicting ‘what’ is going to happen in the sensory environment and ‘when’. Many theories of perception are anchored in the central notion that the brain continuously updates an internal model of the world to infer the probable causes of sensory events. In this framework, the brain needs not only to predict the causes of sensory input, but also when they are most likely to happen. In this article, we review the neurophysiological bases of sensory predictions of “what’ (predictive coding) and ‘when’ (predictive timing), with an emphasis on low-level oscillatory mechanisms. We argue that neural rhythms offer distinct and adapted computational solutions to predicting ‘what’ is going to happen in the sensory environment and ‘when’. the idea that the brain generates hypotheses about the possible causes of forthcoming sensory events and that these hypotheses are compared with incoming sensory information. The difference between top-down expectation and incoming sensory inputs, that is, prediction error, is propagated forward throughout the cortical hierarchy. an extension of the notion of predictive coding to the exploitation of temporal regularities (such as a beat) or associative contingencies (for instance, temporal relation between two inputs) to infer the occurrence of future sensory events. efferent neural operations that convey the internal goals or states of the observer. This notion generally includes different cognitive processes, such as attention and expectations (Box 1). neurophysiological electromagnetic signals [from Local Field Potentials (LFP), electroencephalographic (EEG) and magnetoencephalographic recordings (MEG)] that reflect coherent neuronal population behavior at different spatial scales. These signals have been labeled as a function of their frequency from human surface EEG: delta (2–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12– 30 Hz), and gamma bands (30–100 Hz). The mechanistic properties of oscillations are computationally interesting as a means of explaining various aspects of perception and cognition, for example, long-distance communication across brain regions, unification of various attributes of the same object, segmentation of the sensory input, memory etc.