ABSTRACT
At the beginning of the 60s’, the pioneering studies by Wiesel and Hubel (1963) opened large avenues of researches aimed at understanding the mechanisms underlying functional reorganizations in sensory systems. However, these outstanding studies also had a drastic impact on the conception of sensory cortex: for more than two decades the general view, both in the field of sensory physiology and in the field of learning, was that sensory representations could be subjected to experience-dependent plasticity only during development, not in adulthood. This dogma was progressively reconsidered in the middle of the 80s’ when some studies pointed out that reorganizations can take place in the adult sensory cortex after deafferentations (e.g., Merzenich et al., 1983; for review see Weinberger, 1995). In the auditory system, the first demonstration of such reorganizations came from the work by Robertson and Irvine (1989). One month after localized damages of the cochlea, leading to important increase in threshold for a particular frequency range, cortical territories normally allocated to the deafferented frequency range were responding to adjacent frequencies. Similar reorganizations were recently described at the thalamic level (Kamke et al., 2003) and patchy reorganizations were also reported at the level of the inferior colliculus (Irvine & Rajan, 1994). Thus, it seems that, from the cortex to subthalamic stations, sensory systems remain capable to display functional reorganizations in adult brains. This view
now prevails in any sensory modality. This is not a surprise for investigators who for decades have described the impact of learning on auditory evoked responses (see for review, Weinberger and Diamond, 1987). However, as explained below, most, if not all, of the studies describing experience-dependent plasticity in sensory systems based their findings on the firing rate collected during a time window related to stimulus presentation. This contrasts with a long tradition in auditory physiology which emphasizes the fact that temporal organizations of neuronal discharges code for basic properties of a sound (frequency, intensity) more efficiently than rate coding does (Hind et al., 1963). As I shall defend in the last section, describing results exclusively in terms of firing rate, or exclusively in terms of temporal coding, probably contributes to keep separated lines of research which should rather cooperate to reach a major goal: unravelling the neural code and its plasticity.
