title: Economy of scale: a motion sensor with variable speed tuning.
abstract: We have previously presented a model of how neurons in the primate middle temporal (MT/V5) area can develop selectivity for image speed by using common properties of the V1 neurons that precede them in the visual motion pathway (J. A. Perrone & A. Thiele, 2002). The motion sensor developed in this model is based on two broad classes of V1 complex neurons (sustained and transient). The S-type neuron has low-pass temporal frequency tuning, p(omega), and the T-type has band-pass temporal frequency tuning, m(omega). The outputs from the S and T neurons are combined in a special way (weighted intersection mechanism [WIM]) to generate a sensor tuned to a particular speed, v. Here I go on to show that if the S and T temporal frequency tuning functions have a particular form (i.e., p(omega)/(m(omega) = k/omega), then a motion sensor with variable speed tuning can be generated from just two V1 neurons. A simple scaling of the S- or T-type neuron output before it is incorporated into the WIM model produces a motion sensor that can be tuned to a wide continuous range of optimal speeds.
authors.affiliation: Department of Psychology, The University of Waikato, Hamilton, New Zealand. jpnz@waikato.ac.nz
authors.forename: John A
authors.initials: JA
authors.lastname: Perrone
mesh_terms: D000818:Animals; D008253:Macaca mulatta; D008433:Mathematics; D008959:Models, Neurological; D009039:Motion Perception / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D014793:Visual Cortex / Q000166:cytology*; D014795:Visual Pathways / Q000502:physiology