Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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Precision measurement and dynamical switching of visual cortical architecture

Neurons in the primary visual cortex are selective for the orientation of light/dark edges in their receptive fields [1]. In primates and carnivores the preferred orientation of the neurons changes systematically across the cortical surface forming iso-orientation domains ordered around point-like topological defects called pinwheel centers [2]. It is a long standing theoretical prediction that visual cortical circuits are in a state of flux, such that the preferred orientation of the neurons represents a non-equilibrium steady state of circuit turnover [3]. If this prediction is true and multiple steady states coexist, then signatures of the underlying dynamical process should be observable as a rearrangement of the domains over time.


Figure 1: (a-e) Precision measurement of orientation domains: a) Color coded orientation preference layout recorded in ferret V1. Inset size 640 micrometers. White dots mark the position of the pinwheels. b) Percentage of bootstrap samples in which corresponding pinwheels are found. Black lines mark the zero contours of the layout. Gray areas mark the confidence range of the pinwheel position. c) Pinwheel probabilities for the complete layout. d) Distribution of orientation preferences in the bootstrap samples for the three example pixels marked with black dots in a). e) Accuracy of the orientation preference estimation for each pixel in the layout. f-i) Pinwheel generation event: f-g) Layout and pinwheel probabilities for the same region in two consecutive imaging sessions. h) Orientation preference distribution of the pixel marked with a black dot in f) and g). i) Distance between the generated pinwheel pair in the different bootstrap samples.

We tested this hypothesis by investigating the occurrence of the largest topological change conceivable in the layout: the generation and annihilation of pinwheel pairs. We conducted acute high accuracy large scale intrinsic signal imaging experiments in 32 ferrets. In 24 of the ferrets we further employed an adapted pairing protocol [4] between imaging sessions to drive the cortical circuits out of a potential stationary state. To harvest significant topological changes we quantified the certainty of the measurements using re-sampling methods. The probability of pinwheel existence was calculated by tracking their position between bootstrap samples. The accuracy of the estimated orientation preference of individual pixels was computed from their inter-sample tuning distribution. We analyzed the dynamics of 2620 pinwheels by comparing the measured layouts in subsequent imaging sessions of 42 minutes each. Using this extensive data set and precise analysis methods we found rare but conclusive examples of pinwheel rearrangement. The rate of these events was increased when the pairing paradigm was used. These results demonstrate for the first time dynamical changes of visual cortical architecture driven by neuronal activity.

Contact:  Fred Wolf 

Members working within this Project:

 Juan Daniel Flórez Weidinger 
 Fred Wolf