The activity of neurons of the medial posterior parietal area V6A in macaque monkeys is modulated by many aspects of reach task. In the past, research was mostly focused on modulating the effect of single parameters upon the activity of V6A cells. Here, we used Generalized Linear Models (GLMs) to simultaneously test the contribution of several factors upon V6A cells during a fix-to-reach task. This approach resulted in the definition of a representative "functional fingerprint" for each neuron. We first studied how the features are distributed in the population. Our analysis highlighted the virtual absence of units strictly selective for only one factor and revealed that most cells are characterized by "mixed selectivity." Then, exploiting our GLM framework, we investigated the dynamics of spatial parameters encoded within V6A. We found that the tuning is not static, but changed along the trial, indicating the sequential occurrence of visuospatial transformations helpful to guide arm movement.
Keywords: Behavioral Neuroscience; Biocomputational Method; Neuroscience.
© 2020 The Author(s).