Spatial Properties and Functional Organization of Small Bistratified Ganglion Cells in Primate Retina
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MITOCW | 9: Receptive Fields - Intro to Neural Computation
MITOCW | 9: Receptive Fields - Intro to Neural Computation MICHALE FEE: So today, we're going to introduce a new topic, which is related to the idea of fine- tuning curves, and that is the notion of receptive fields. So most of you have probably been, at least those of you who've taken 9.01 or 9.00 maybe, have been exposed to the idea of what a receptive field is. The idea is basically that in sensory systems neurons receive input from the sensory periphery, and neurons generally have some kind of sensory stimulus that causes them to spike. And so one of the classic examples of how to find receptive fields comes from the work of Huble and Wiesel. So I'll show you some movies made from early experiments of Huble-Wiesel where they are recording in the visual cortex of the cat. So they place a fine metal electrode into a primary visual cortex, and they present. So then they anesthetize the cat so the cat can't move. They open the eye, and the cat's now looking at a screen that looks like this, where they play a visual stimulus. And they actually did this with essentially a slide projector that they could put a card in front of that had a little hole in it, for example, that allowed a spot of light to project onto the screen. And then they can move that spot of light around while they record from neurons in visual cortex and present different visual stimuli to the retina. -
The Roles and Functions of Cutaneous Mechanoreceptors Kenneth O Johnson
455 The roles and functions of cutaneous mechanoreceptors Kenneth O Johnson Combined psychophysical and neurophysiological research has nerve ending that is sensitive to deformation in the resulted in a relatively complete picture of the neural mechanisms nanometer range. The layers function as a series of of tactile perception. The results support the idea that each of the mechanical filters to protect the extremely sensitive recep- four mechanoreceptive afferent systems innervating the hand tor from the very large, low-frequency stresses and strains serves a distinctly different perceptual function, and that tactile of ordinary manual labor. The Ruffini corpuscle, which is perception can be understood as the sum of these functions. located in the connective tissue of the dermis, is a rela- Furthermore, the receptors in each of those systems seem to be tively large spindle shaped structure tied into the local specialized for their assigned perceptual function. collagen matrix. It is, in this way, similar to the Golgi ten- don organ in muscle. Its association with connective tissue Addresses makes it selectively sensitive to skin stretch. Each of these Zanvyl Krieger Mind/Brain Institute, 338 Krieger Hall, receptor types and its role in perception is discussed below. The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218-2689, USA; e-mail: [email protected] During three decades of neurophysiological and combined Current Opinion in Neurobiology 2001, 11:455–461 psychophysical and neurophysiological studies, evidence has accumulated that links each of these afferent types to 0959-4388/01/$ — see front matter © 2001 Elsevier Science Ltd. All rights reserved. a distinctly different perceptual function and, furthermore, that shows that the receptors innervated by these afferents Abbreviations are specialized for their assigned functions. -
Center Surround Receptive Field Structure of Cone Bipolar Cells in Primate Retina
Vision Research 40 (2000) 1801–1811 www.elsevier.com/locate/visres Center surround receptive field structure of cone bipolar cells in primate retina Dennis Dacey a,*, Orin S. Packer a, Lisa Diller a, David Brainard b, Beth Peterson a, Barry Lee c a Department of Biological Structure, Uni6ersity of Washington, Box 357420, Seattle, WA 98195-7420, USA b Department of Psychology, Uni6ersity of California Santa Barbara, Santa Barbara, CA, USA c Max Planck Institute for Biophysical Chemistry, Gottingen, Germany Received 28 September 1999; received in revised form 5 January 2000 Abstract In non-mammalian vertebrates, retinal bipolar cells show center-surround receptive field organization. In mammals, recordings from bipolar cells are rare and have not revealed a clear surround. Here we report center-surround receptive fields of identified cone bipolar cells in the macaque monkey retina. In the peripheral retina, cone bipolar cell nuclei were labeled in vitro with diamidino-phenylindole (DAPI), targeted for recording under microscopic control, and anatomically identified by intracellular staining. Identified cells included ‘diffuse’ bipolar cells, which contact multiple cones, and ‘midget’ bipolar cells, which contact a single cone. Responses to flickering spots and annuli revealed a clear surround: both hyperpolarizing (OFF) and depolarizing (ON) cells responded with reversed polarity to annular stimuli. Center and surround dimensions were calculated for 12 bipolar cells from the spatial frequency response to drifting, sinusoidal luminance modulated gratings. The frequency response was bandpass and well fit by a difference of Gaussians receptive field model. Center diameters were all two to three times larger than known dendritic tree diameters for both diffuse and midget bipolar cells in the retinal periphery. -
The Actions of Serotonergic Agonists and Antagonists Activity of Brisk Ganglion Cells in the Rabbit Retina On
The Journal of Neuroscience, December 1987, 7(12): 4054-4085 The Actions of Serotonergic Agonists and Antagonists on the Activity of Brisk Ganglion Cells in the Rabbit Retina William J. Brunken and Nigel W. Daw Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, Missouri 63110 Extracellular electrophysiological recordings were obtained of the CNS. For example, inhibitory input from GABAergic from rabbit retinal ganglion cells in either a superfused eye- neurons is necessary to elaborate direction and orientation se- cup or an in vivo preparation. Selective antagonists or ag- lectivity in rabbit retinal ganglion cells (Wyatt and Daw, 1976; onists of serotonin at the 5-HT, or 5-HT,, receptors were Caldwell et al., 1978); similar results have been obtained in cat applied, and the changes in light-evoked and spontaneous visual cortex (Sillito, 1977; Sillito et al., 1980). activity were studied. Both 5-HT,, agonists and 5-HT, an- Biochemical and histochemical data suggest that serotonin or tagonists reduced the ON-components of the light-evoked a related indoleamine is a neurotransmitter in the mammalian responses of all classes of brisk ganglion cell; spontaneous retina (reviewed by Ehinger, 1982; Osborne, 1982; and Red- activity was reduced in these cells as well. These results burn, 1984). Specific mechanisms have been identified for the suggest that the indoleamine-accumulating amacrine cells uptake (Ehinger and Floren, 1978; Osborne and Richardson, of the rabbit retina serve to facilitate the output of the de- 1980) and depolarization-dependent release (Osborne, 1980; polarizing rod bipolar cell and thereby increase the efficacy Thomas and Redbum, 1980; Mitchell and Redbum, 1985) of of transmission between this and other cells in the rabbit serotonin. -
The Visual System: Higher Visual Processing
The Visual System: Higher Visual Processing Primary visual cortex The primary visual cortex is located in the occipital cortex. It receives visual information exclusively from the contralateral hemifield, which is topographically represented and wherein the fovea is granted an extended representation. Like most cortical areas, primary visual cortex consists of six layers. It also contains, however, a prominent stripe of white matter in its layer 4 - the stripe of Gennari - consisting of the myelinated axons of the lateral geniculate nucleus neurons. For this reason, the primary visual cortex is also referred to as the striate cortex. The LGN projections to the primary visual cortex are segregated. The axons of the cells from the magnocellular layers terminate principally within sublamina 4Ca, and those from the parvocellular layers terminate principally within sublamina 4Cb. Ocular dominance columns The inputs from the two eyes also are segregated within layer 4 of primary visual cortex and form alternating ocular dominance columns. Alternating ocular dominance columns can be visualized with autoradiography after injecting radiolabeled amino acids into one eye that are transported transynaptically from the retina. Although the neurons in layer 4 are monocular, neurons in the other layers of the same column combine signals from the two eyes, but their activation has the same ocular preference. Bringing together the inputs from the two eyes at the level of the striate cortex provide a basis for stereopsis, the sensation of depth perception provided by binocular disparity, i.e., when an image falls on non-corresponding parts of the two retinas. Some neurons respond to disparities beyond the plane of fixation (far cells), while others respond to disparities in front of the plane of the fixation (near cells). -
A Virtual Model of the Retina Based on Histological Data As a Tool for Evaluation of the Visual Fields
Original Article Page 1 of 15 A virtual model of the retina based on histological data as a tool for evaluation of the visual fields Francisco-Javier Carreras1, Ángel V. Delgado2, José L. García-Serrano3, Javier Medina-Quero4 1Department of Surgery, Medical School, 2Department of Applied Physics, School of Sciences, University of Granada, Granada, Spain; 3Hospital Clínico San Cecilio, University of Granada, Granada, Spain; 4School of Computer Science, Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain Contributions: (I) Conception and design: FJ Carreras; (II) Administrative support: JL García-Serrano; (III) Provision of study materials and patients: All authors; (IV) Collection and assembly of data: FJ Carreras, J Medina-Quero; (V) Data analysis and interpretation: FJ Carreras, J Medina-Quero; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. Correspondence to: Francisco-Javier Carreras. MD, PhD, Department of Surgery, Medical School, University of Granada, Av. de la Investigación 11, Granada 18016, Spain. Email: [email protected]. Background: To settle the fundamentals of a numerical procedure that relates retinal ganglion-cell density and threshold sensitivity in the visual field. The sensitivity of a generated retina and visual pathways to virtual stimuli are simulated, and the conditions required to reproduce glaucoma-type defects both in the optic- nerve head (ONH) and visual fields are explored. Methods: A definition of selected structural elements of the optic pathways is a requisite to a translation of clinical knowledge to computer programs for visual field exploration. The program is able to generate a database of normalized visual fields. The relationship between the number of extant receptive fields and threshold sensitivity is plotted for background sensitivity and corresponding automated perimetry. -
Visual Properties of Human Retinal Ganglion Cells
bioRxiv preprint doi: https://doi.org/10.1101/766170; this version posted August 14, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Visual properties of human retinal ganglion cells Katja Reinhard1,2,3* & Thomas A. Münch1,4* 1 Retinal Circuits and Optogenetics, Centre for Integrative Neuroscience and Bernstein Center for Computational Neuroscience, University of Tübingen, Otfried-Müller-Str. 25, 72076 Tübingen, Germany; 2 Neuroscience Graduate School, University of Tübingen, Österbergstraße 3, 72074 Tübingen Germany; 3 Current address: Neuro- electronics Research Flanders, Kapeldreef 75, 3001 Leuven, Belgium; 4 Institute for Ophthalmic Research, University of Tübingen, Elfriede-Aulhorn-Straße 7, 72076 Tübingen, Germany * Corresponding authors Katja Reinhard: [email protected] and Thomas A. Münch: [email protected] The retinal output is the sole source of visual information for the brain. Studies in non-primate mammals estimate that this information is carried by several dozens of retinal ganglion cell types, each informing the brain about different aspects of a visual scene. Even though morphological studies of primate retina suggest a similar diversity of ganglion cell types, research has focused on the function of only a few cell types. In human retina, recordings from individual cells are anecdotal or focus on a small subset of identified types. Here, we present the first systematic ex-vivo recording of light responses from 342 ganglion cells in human retinas obtained from donors. -
Embryology, Anatomy, and Physiology of the Afferent Visual Pathway
CHAPTER 1 Embryology, Anatomy, and Physiology of the Afferent Visual Pathway Joseph F. Rizzo III RETINA Physiology Embryology of the Eye and Retina Blood Supply Basic Anatomy and Physiology POSTGENICULATE VISUAL SENSORY PATHWAYS Overview of Retinal Outflow: Parallel Pathways Embryology OPTIC NERVE Anatomy of the Optic Radiations Embryology Blood Supply General Anatomy CORTICAL VISUAL AREAS Optic Nerve Blood Supply Cortical Area V1 Optic Nerve Sheaths Cortical Area V2 Optic Nerve Axons Cortical Areas V3 and V3A OPTIC CHIASM Dorsal and Ventral Visual Streams Embryology Cortical Area V5 Gross Anatomy of the Chiasm and Perichiasmal Region Cortical Area V4 Organization of Nerve Fibers within the Optic Chiasm Area TE Blood Supply Cortical Area V6 OPTIC TRACT OTHER CEREBRAL AREASCONTRIBUTING TO VISUAL LATERAL GENICULATE NUCLEUSPERCEPTION Anatomic and Functional Organization The brain devotes more cells and connections to vision lular, magnocellular, and koniocellular pathways—each of than any other sense or motor function. This chapter presents which contributes to visual processing at the primary visual an overview of the development, anatomy, and physiology cortex. Beyond the primary visual cortex, two streams of of this extremely complex but fascinating system. Of neces- information flow develop: the dorsal stream, primarily for sity, the subject matter is greatly abridged, although special detection of where objects are and for motion perception, attention is given to principles that relate to clinical neuro- and the ventral stream, primarily for detection of what ophthalmology. objects are (including their color, depth, and form). At Light initiates a cascade of cellular responses in the retina every level of the visual system, however, information that begins as a slow, graded response of the photoreceptors among these ‘‘parallel’’ pathways is shared by intercellular, and transforms into a volley of coordinated action potentials thalamic-cortical, and intercortical connections. -
Seeing in Three Dimensions: the Neurophysiology of Stereopsis Gregory C
Review DeAngelis – Neurophysiology of stereopsis Seeing in three dimensions: the neurophysiology of stereopsis Gregory C. DeAngelis From the pair of 2-D images formed on the retinas, the brain is capable of synthesizing a rich 3-D representation of our visual surroundings. The horizontal separation of the two eyes gives rise to small positional differences, called binocular disparities, between corresponding features in the two retinal images. These disparities provide a powerful source of information about 3-D scene structure, and alone are sufficient for depth perception. How do visual cortical areas of the brain extract and process these small retinal disparities, and how is this information transformed into non-retinal coordinates useful for guiding action? Although neurons selective for binocular disparity have been found in several visual areas, the brain circuits that give rise to stereoscopic vision are not very well understood. I review recent electrophysiological studies that address four issues: the encoding of disparity at the first stages of binocular processing, the organization of disparity-selective neurons into topographic maps, the contributions of specific visual areas to different stereoscopic tasks, and the integration of binocular disparity and viewing-distance information to yield egocentric distance. Some of these studies combine traditional electrophysiology with psychophysical and computational approaches, and this convergence promises substantial future gains in our understanding of stereoscopic vision. We perceive our surroundings vividly in three dimen- lished the first reports of disparity-selective neurons in the sions, even though the image formed on the retina of each primary visual cortex (V1, or area 17) of anesthetized cats5,6. -
COGS 101A: Sensation and Perception 1
COGS 101A: Sensation and Perception 1 Virginia R. de Sa Department of Cognitive Science UCSD Lecture 4: Coding Concepts – Chapter 2 Course Information 2 • Class web page: http://cogsci.ucsd.edu/ desa/101a/index.html • Professor: Virginia de Sa ? I’m usually in Chemistry Research Building (CRB) 214 (also office in CSB 164) ? Office Hours: Monday 5-6pm ? email: desa at ucsd ? Research: Perception and Learning in Humans and Machines For your Assistance 3 TAS: • Jelena Jovanovic OH: Wed 2-3pm CSB 225 • Katherine DeLong OH: Thurs noon-1pm CSB 131 IAS: • Jennifer Becker OH: Fri 10-11am CSB 114 • Lydia Wood OH: Mon 12-1pm CSB 114 Course Goals 4 • To appreciate the difficulty of sensory perception • To learn about sensory perception at several levels of analysis • To see similarities across the sensory modalities • To become more attuned to multi-sensory interactions Grading Information 5 • 25% each for 2 midterms • 32% comprehensive final • 3% each for 6 lab reports - due at the end of the lab • Bonus for participating in a psych or cogsci experiment AND writing a paragraph description of the study You are responsible for knowing the lecture material and the assigned readings. Read the readings before class and ask questions in class. Academic Dishonesty 6 The University policy is linked off the course web page. You will all have to sign a form in section For this class: • Labs are done in small groups but writeups must be in your own words • There is no collaboration on midterms and final exam Last Class 7 We learned about the cells in the Retina This Class 8 Coding Concepts – Every thing after transduction (following Chris Johnson’s notes) Remember:The cells in the retina are neurons 9 neurons are specialized cells that transmit electrical/chemical information to other cells neurons generally receive a signal at their dendrites and transmit it electrically to their soma and axon. -
Neurons Show Their True Colours
RESEARCH NEWS & VIEWS VISION Neurons show 50 Years Ago their true colours How do we tell red from green? Work on the primate retina shows how neural An Introduction to the Logic of the circuitry combines signals from individual cone photoreceptor cells to provide Sciences. By R. Harré — This is a very the basic building blocks for colour vision. See Article p.673 welcome book. It should be said at the outset that the author’s intention to write largely for undergraduates JONATHAN B. DEMB & DAVID H. BRAINARD genes encoding the S and M/L cone opsins — in science may prove a little on the proteins that determine spectral sensitivity modest side, since many students he processing of visual information — diverged more than 500 million years ago4. working for higher degrees would begins in the retina, where special- Moreover, the primate retina contains special- probably produce substantially ized neurons called photoreceptors ized ganglion cells for computing S–(L+M) better theses if they could find time Tabsorb light and stimulate multiple neural opponent signals. The small bistratified to read what Dr. Harré has to relate circuits. Each circuit generates specific ganglion cells, for example, receive excitatory … The grand point is that — from patterns of electrical activity and converges on inputs from S cones through S-cone bipo- the aspect of discovery — disciplined one of about 20 types of retinal ganglion cell. lar cells, and (L+M) cone signals oppose the insight came first, and the These cells’ axons — the optic nerve fibres — S-cone signals by means of two distinct retinal application of mathematical analysis then convey signals to various brain targets. -
Reconstruction of Natural Images from Responses of Primate Retinal Ganglion Cells
bioRxiv preprint doi: https://doi.org/10.1101/2020.05.04.077693; this version posted May 5, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Reconstruction of natural images from responses of primate retinal ganglion cells Authors Nora Brackbill1, Colleen Rhoades2, Alexandra Kling3, Nishal P. Shah4, Alexander Sher5, Alan M. Litke5, E.J. Chichilnisky3 1. Department of Physics, Stanford University, Stanford, United States 2. Department of Bioengineering, Stanford University, Stanford, United States 3. Department of Neurosurgery, Stanford School of Medicine, Stanford, United States Department of Ophthalmology, Stanford University, Stanford, United States Hansen Experimental Physics Laboratory, Stanford University, Stanford, United States 4. Department of Electrical Engineering, Stanford University, Stanford, United States 5. Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, United States Abstract The visual message conveyed by a retinal ganglion cell (RGC) is often summarized by its spatial receptive field, but in principle should also depend on other cells’ responses and natural image statistics. To test this idea, linear reconstruction (decoding) of natural images was performed using combinations of responses of four high-density macaque RGC types, revealing consistent visual representations across retinas. Each cell’s visual message, defined by the optimal reconstruction filter, reflected natural image statistics, and resembled the receptive field only when nearby, same-type cells were included. Reconstruction from each cell type revealed different and largely independent visual representations, consistent with their distinct properties. Stimulus-independent correlations primarily affected reconstructions from noisy responses.