Implications on cerebellar function from information coding

Abstract

One function of the cerebellar cortex is to process information. There are at least two types of information. Temporal information is encoded in the timing pattern of action and synaptic potentials, whereas structural information is encoded in the spatial pattern of the cerebellar synaptic circuitry. Intuitively, analysis of highly complex information in the time domain would require a cerebellar cortex with structural complexity to match. Information theory offers a way to estimate quantitatively both types of information and thereby helps to test hypotheses or advance theories of cerebellar neurobiology. These estimates suggest: (i) That the mossy-fiber-granule-cell system carries far more (temporal) information than the climbing fiber system, (ii) that Purkinje cells extract only a fraction of the (temporal) information from their afferents, and (iii) that the cerebellar cortex has a large (spatial) information coding capacity. Concerning information, one can argue that the cerebellar cortex analyzes temporal information in its afferents as a search engine, in search of coincidental mossy fiber events based on timing cues provided by climbing fiber events. Results of successive searches are continuously being converted into structural information encoded in the spatial distribution pattern of granule-cell-Purkinje-cell synapses along granule cell axons, thereby providing an adaptive and indeed self-correcting dimension to the structural information code. The search engine operation involves cellular mechanisms acting on temporal events and is part of an associative learning process. The conversion and generation of structural information involves neuroplasticity mechanisms acting at the synaptic level, with electrophysiological as well as structural consequences, and may be part of the short- and long-term memory process. These and other attributes qualify the cerebellar cortex as a dynamic information processing center, contributing to memory and learning while linking motor output with sensory events.