Higher-dimensional neurons explain the tuning and dynamics of working memory cells

Measurements of neural activity in working memory during a somatosensory discrimination task show that the content of working memory is not only stimulus dependent but also strongly time varying. We present a biologically plausible neural model that reproduces the wide variety of characteristic responses observed in those experiments. Central to our model is a heterogeneous ensemble of two-dimensional neurons that are hypothesized to simultaneously encode two distinct stimuli dimensions. We demonstrate that the spiking activity of each neuron in the population can be understood as the result of a two-dimensional state space trajectory projected onto the tuning curve of the neuron. The wide variety of observed responses is thus a natural consequence of a population of neurons with a diverse set of preferred stimulus vectors and response functions in this two-dimensional space. In addition, we propose a taxonomy of network topologies that will generate the two-dimensional trajectory necessary to exploit this population. We conclude by proposing some experimental indicators to help distinguish among these possibilities.