While the
notion that object representation is embedded in sequences of action potentials
is fairly well accepted amongst neuroscientists, there is less agreement
concerning the actual representation schemes (i.e. neuronal activity features)
that carry stimulus-relevant information at the assembly level. Here we offer a
general approach to the issue, enabling a systematic and well controlled experimental
analysis of constraints and tradeoffs, imposed by the physiology of neuronal
populations, on plausible representation schemes. Using in vitro networks of
rat cortical neurons as a model system, we compared the efficacy of different
kinds of “neural codes” to represent both spatial and temporal input features.
Two rate-based representation schemes and two time-based representation schemes
were considered. Our results indicate that, by large, all representation
schemes perform well in the various discrimination tasks tested, indicating the
inherent redundancy in neural population activity; Nevertheless, differences in
representation efficacy are identified when unique aspects of input features
are considered. We discuss these differences in the context of neural
population dynamics.
