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September 30, 2025PLoS ONE0 citationsOpen Access

Orientation selectivity properties for integrated affine quasi quadrature models of complex cells

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TLTony Lindeberg

Key Points

  • Enhanced orientation selectivity properties were observed in models of complex cells, indicating their improved performance.
  • The analysis revealed that including variability in receptive fields leads to more comprehensive behavior across the models.
  • The investigation involved comparing model predictions with neurophysiological data from biological orientation selectivity curves.
  • Results may enable better evaluation of computational models of complex cells against biological measurements and predictions.

Abstract

This paper presents an analysis of the orientation selectivity properties of idealized models of complex cells in terms of affine quasi quadrature measures, which combine the responses of idealized models of simple cells in terms of affine Gaussian derivatives by (i) pointwise squaring, (ii) summation of responses for different orders of spatial derivation and (iii) spatial integration. Specifically, this paper explores the consequences of assuming that the family of spatial receptive fields should be covariant under spatial affine transformations, thereby implying that the receptive fields ought to span a variability over the degree of elongation. We investigate the theoretical properties of three main ways of defining idealized models of complex cells and compare the predictions from these models to neurophysiologically obtained receptive field histograms over the resultant of biological orientation selectivity curves. It is shown that the extended modelling mechanisms lead to more uniform behaviour and a wider span over the values of the resultant that are covered, compared to an earlier presented idealized model of complex cells without spatial integration. More generally, we propose to, based on the presented results: (i) include an explicit variability over the degree of elongation of the receptive fields in functional models of complex cells, and that (ii) the suggested methodology with comparisons to biological orientation selectivity curves and orientation selectivity histograms could be used as a new tool to evaluate other computational models of complex cells in relation to biological measurements.

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Cite This Study

Tony Lindeberg (2025) studied this question.

synapsesocial.com/papers/68dc1e3f8a7d58c25ebb2083https://doi.org/10.1371/journal.pone.0332139
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