Brain nicotinic receptors: structure and regulation, role in learning and reinforcement

Abstract

The introduction, in the late sixties, of the concepts and methods of molecular biology to the study of the nervous system had a profound impact on the field, primarily through the identification of its basic molecular components. These structures include, for example, the elementary units of the synapse: neurotransmitters, neuropeptides and their receptors, but also ionic channels, intracellular second messengers and the relevant enzymes, cell surface adhesion molecules, or growth and trophic factors [21,78,81, 52,79]. Attempts to establish appropriate causal relationships between these molecular components, the actual organisation of neural networks, and a defined behavior, nevertheless, still must overcome many difficulties. A first problem is the recognition of the minimum levels of organisation, from the molecular, cellular, or multicellular (circuit) to the higher cognitive levels, that determine the given physiological and/or behavioral performance under investigation. A common difficulty (and potential source of errors of interpretation) is to relate a cognitive function to a network organization which does not possess the required structural complexity and vice-versa. Another problem is to distinguish, among the components of the system, those which are actually necessary and those which, taken together, suffice for a given behavior to take place. Identification of such a minimal set of building blocks may receive decisive insights from the elaboration of neurally plausible formal models that bring together, within a single and coherent 'artificial organism', the neuronal network, the circulating activity, and the behavior they determine (see [42,43,45,72,30]). In this communication, we shall attempt, still in a preliminary fashion, to bring together: (1) our recent knowledge on the molecular biology of brain nicotinic receptors (nAChRs) and their allosteric properties and (2) integrated behaviors, such as cognitive learning, investigated for instance with delayed-response or passive avoidance tasks that are likely to involve nAChRs in particular at the level of reinforcement (or reward) mechanisms (see [18,29,135]).