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For instance, Craft et al. [90] propose a neural mechanism of 'figure ground organization' based on border ownership to model complex cells in the primary visual cortex (V1).
The output signals of model complex cells subsequently undergo a centre-surround inhibition that is realized by a lateral divisive inhibition mechanism.
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Our data define the role of LIS1 and 14.3.3ε in maintaining the cortical niche and highlight the utility of organoid-based systems for modeling complex cell-cell interactions in vitro.
A framework for modeling complex cell-biologic processes is proposed here.
A framework for modeling complex cell-biologic pathways is described here.
In our model, the likelihood function is constructed on the basis of the disparity energy model because complex cells are considered as front-end disparity encoders in the visual pathway.
This model can therefore be interpreted as a Gaussian derivative-based analogue of the energy model for complex cells proposed by (Adelson and Bergen 1985; Heeger 1992).
For simplicity, a quadrature pair of space-time Gabor filters has been employed in an energy model of complex cells [9 11].
Specifically, the second-stage smoothing (125) of the pointwise quasi-quadrature measure is in good agreement with the model of complex cell responses in (Rust et al. (2005), Fig. 8, page 953) based on weighted averaging of a set of quadrature pairs.
To obtain a comprehensive insight into the changes specific for human cells, we evaluated in detail multiple tri- and tetrasomic cell lines as well as model complex aneuploid human cell lines with hypotetraploid karyotypes more similar to cancer cells.
The framework presented here addresses how to develop increasingly descriptive models of complex cell-biologic processes.
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