Motion processing with wide-field neurons in the retino-tecto-rotundal pathway

The retino-tecto-rotundal pathway is the main visual pathway in non-mammalian vertebrates and has been found to be highly involved in visual processing. Despite the extensive receptive fields of tectal and rotundal wide-field neurons, pattern discrimination tasks suggest a system with high spatial resolution. In this paper, we address the problem of how global processing performed by motion-sensitive wide-field neurons can be brought into agreement with the concept of a local analysis of visual stimuli. As a solution to this problem, we propose a firing-rate model of the retino-tecto-rotundal pathway which describes how spatiotemporal information can be organized and retained by tectal and rotundal wide-field neurons while processing Fourier-based motion in absence of periodic receptive-field structures. The model incorporates anatomical and electrophysiological experimental data on tectal and rotundal neurons, and the basic response characteristics of tectal and rotundal neurons to moving stimuli are captured by the model cells. We show that local velocity estimates may be derived from rotundal-cell responses via superposition in a subsequent processing step. Experimentally testable predictions which are both specific and characteristic to the model are provided. Thus, a conclusive explanation can be given of how the retino-tecto-rotundal pathway enables the animal to detect and localize moving objects or to estimate its self-motion parameters

Motion processing with wide-field neurons in the retino-tecto-rotundal pathway

The retino-tecto-rotundal pathway is the main visual pathway in nonmammalian vertebrates and has been found to be highly involved in visual processing. Despite the extensive receptive fields of tectal and rotundal wide-field neurons, pattern discrimination tasks suggest a system with high spatial resolution. In this paper, we address the problem of how global processing performed by motion-sensitive wide-field neurons can be brought into agreement with the concept of a local analysis of visual stimuli. As a solution to this problem, we propose a firing-rate model of the retino-tectorotundal pathway which describes how spatiotemporal information can be organized and retained by tectal and rotundal wide-field neurons while processing Fourier-based motion in absence of periodic receptive-field structures. The model incorporates anatomical and electrophysiological experimental data on tectal and rotundal neurons, and the basic response characteristics of tectal and rotundal neurons to moving stimuli are captured by the model cells. We show that local velocity estimates may be derived from rotundal-cell responses via superposition in a subsequent processing step. Experimentally testable predictions which are both specific and characteristic to the model are provided. Thus, a conlusive explanation can be given of how the retino-tecto-rotundal pathway enables the animal to detect and localize moving objects or to estimate its self-motion parameters

Utilizing the 3D Environment to Facilitate Learning of Complex Visual Neural Pathways in the Avian Brain

Neuroanatomical pathways are difficult to study often due to the limit of methods used to visualize the anatomical and physiologic characteristics. In many studies, a neural pathway is presented using 2D representations for structural connectivity. A problem is deciding which of three planes: coronal, sagittal, or horizontal is best for visualizing the pathway’s components clearly and spatially precise for those wanting to learn and utilize that information. A 3D environment would be imperative in solving this issue. We therefore attempted to develop a means of accurately presenting detailed anatomical structures within the 3D regions they occurred. It is our hope that accurate, spatial representations of visual neural pathways will result in learning specific structures, their subdivisions, and their spatial organizations. Advancements in imaging techniques address this issue and have allowed for a new avenue of investigation for studying the morphology of anatomical systems. One such technique, diffusible iodine-based contrast-enhanced computed tomography (diceCT), has allowed for nondestructive visualization of an appropriately fixed brain. In other words, it allows one to image the entire brain, and visualize any of the three planes without damaging the specimen. We have chosen the visual tectofugal and thalamofugal pathways in an avian brain as they are some of the most well studied systems that seems to have much disparity in their anatomical organization and connectivity. The tectofugal pathway begins in the eyeball with retinal ganglion cells projecting to the optic tectum which in turn send projections to a thalamic nucleus. This thalamic nucleus then projects to a region of the forebrain, completing the ascending pathway. The thalamofugal pathway begins in the eyeball with retinal ganglion cells projecting to the lateral geniculate complex, which in turn projects bilaterally to a large terminal forebrain structure occupying the dorsomedial brain surface. For our investigation we employed two techniques: (1) a series of stacked histologic sections of four chick brains, and (2) a diceCT stained whole brain of a chick. For histological sections, we used series of coronal, sagittal, and horizontal sections stained with Nissl (cell bodies revealed) and Luxol Fast Blue or Gallyas silver myelin (fiber tracts revealed). Sections were imported into Brainmaker (Microbrightfield Biosciences), a software that stacks image sequences and reconstructs volumes based on sequential contours. For our diceCT investigation, we rendered the eyeball and brain within the skull of the bird. This allowed an accurate spatial representation of the eyeball with respect to the brain. Post model processing was essential to integrate detailed 2D images in the appropriate plane of the 3D environment. Using the histological image stacks, diceCT scanned eye and brain, and 3D editing software, we created an interactive 3D model of the avian visual tectofugal and thalamofugal pathways. The combination of histochemical sections with diceCT 3D modeling is necessary when detailed anatomical and spatial organization of complex neural pathways such as the tectofugal visual system are desired

Utilizing the 3D Environment to Facilitate Learning of Complex Visual Neural Pathways in the Avian Brain

Neuroanatomical pathways are difficult to study often due to the limit of methods used to visualize the anatomical and physiologic characteristics. In many studies, a neural pathway is presented using 2D representations for structural connectivity. A problem is deciding which of three planes: coronal, sagittal, or horizontal is best for visualizing the pathway’s components clearly and spatially precise for those wanting to learn and utilize that information. A 3D environment would be imperative in solving this issue. We therefore attempted to develop a means of accurately presenting detailed anatomical structures within the 3D regions they occurred. It is our hope that accurate, spatial representations of visual neural pathways will result in learning specific structures, their subdivisions, and their spatial organizations. Advancements in imaging techniques address this issue and have allowed for a new avenue of investigation for studying the morphology of anatomical systems. One such technique, diffusible iodine-based contrast-enhanced computed tomography (diceCT), has allowed for nondestructive visualization of an appropriately fixed brain. In other words, it allows one to image the entire brain, and visualize any of the three planes without damaging the specimen. We have chosen the visual tectofugal and thalamofugal pathways in an avian brain as they are some of the most well studied systems that seems to have much disparity in their anatomical organization and connectivity. The tectofugal pathway begins in the eyeball with retinal ganglion cells projecting to the optic tectum which in turn send projections to a thalamic nucleus. This thalamic nucleus then projects to a region of the forebrain, completing the ascending pathway. The thalamofugal pathway begins in the eyeball with retinal ganglion cells projecting to the lateral geniculate complex, which in turn projects bilaterally to a large terminal forebrain structure occupying the dorsomedial brain surface. For our investigation we employed two techniques: (1) a series of stacked histologic sections of four chick brains, and (2) a diceCT stained whole brain of a chick. For histological sections, we used series of coronal, sagittal, and horizontal sections stained with Nissl (cell bodies revealed) and Luxol Fast Blue or Gallyas silver myelin (fiber tracts revealed). Sections were imported into Brainmaker (Microbrightfield Biosciences), a software that stacks image sequences and reconstructs volumes based on sequential contours. For our diceCT investigation, we rendered the eyeball and brain within the skull of the bird. This allowed an accurate spatial representation of the eyeball with respect to the brain. Post model processing was essential to integrate detailed 2D images in the appropriate plane of the 3D environment. Using the histological image stacks, diceCT scanned eye and brain, and 3D editing software, we created an interactive 3D model of the avian visual tectofugal and thalamofugal pathways. The combination of histochemical sections with diceCT 3D modeling is necessary when detailed anatomical and spatial organization of complex neural pathways such as the tectofugal visual system are desired