Data courtesy: Alex Goddard Gamma-band spike-field coherence in the optic tectum of the barn owl Sridharan Devarajan, Kwabena Boahen, Eric Knudsen Departments.

Slides:



Advertisements
Similar presentations
Spectral sensitivity of cones
Advertisements

EXAM 3 REVIEW Katherine & Tina. Developments of Neural Circuits Lecture 19.
Driving fast-spiking cells induces gamma rhythm and controls sensory responses Driving fast-spiking cells induces gamma rhythm and controls sensory responses.
CNTRICS April 2010 Center-surround: Adaptation to context in perception Robert Shapley Center for Neural Science New York University.
The Physiology of Attention. Physiology of Attention Neural systems involved in orienting Neural correlates of selection.
Visual Attention Attention is the ability to select objects of interest from the surrounding environment A reliable measure of attention is eye movement.
Lecture 12: olfaction: the insect antennal lobe References: H C Mulvad, thesis ( Ch 2http://
A model for spatio-temporal odor representation in the locust antennal lobe Experimental results (in vivo recordings from locust) Model of the antennal.
$ recognition & localization of predators & prey $ feature analyzers in the brain $ from recognition to response $ summary PART 2: SENSORY WORLDS #09:
Neuronal Coding in the Retina and Fixational Eye Movements Christian Mendl, Tim Gollisch Max Planck Institute of Neurobiology, Junior Research Group Visual.
Synchrony in Neural Systems: a very brief, biased, basic view Tim Lewis UC Davis NIMBIOS Workshop on Synchrony April 11, 2011.
A saliency map model explains the effects of random variations along irrelevant dimensions in texture segmentation and visual search Li Zhaoping, University.
Perception of Stimuli Stephen Taylor.
Control of Attention and Gaze in the Natural World.
The visual system II Eye and retina. The primary visual pathway From perret-optic.ch.
How Patterned Connections Can Be Set Up by Self-Organization D.J. Willshaw C. Von Der Malsburg.
Brain Rhythms and Short-Term Memory Earl K. Miller The Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences, Massachusetts.
Electrophysiology of Visual Attention. Moran and Desimone (1985) “Classical” RF prediction: there should be no difference in responses in these two conditions.
Question Examples If you were a neurosurgeon and you needed to take out part of the cortex of a patient, which technique would you use to identify the.
Some concepts from Cognitive Psychology to review: Shadowing Visual Search Cue-target Paradigm Hint: you’ll find these in Chapter 12.
Exam 1 week from today in class assortment of question types including written answers.
Disorders of Orienting Lesions to parietal cortex can produce some strange behavioural consequences –patients fail to notice events on the contralesional.
1 Retinal Circuit and Processing March 23, 2007 Mu-ming Poo Overview of the retinal circuit Receptive field (RF) of retinal ganglion cells (RGC) Neural.
Levels in Computational Neuroscience Reasonably good understanding (for our purposes!) Poor understanding Poorer understanding Very poorer understanding.
How does the mind process all the information it receives?
The three main phases of neural development 1. Genesis of neurons (and migration). 2. Outgrowth of axons and dendrites, and synaptogenesis. 3. Refinement.
The visual system Lecture 1: Structure of the eye
Plasticity in sensory systems Jan Schnupp on the monocycle.
Mechanisms for phase shifting in cortical networks and their role in communication through coherence Paul H.Tiesinga and Terrence J. Sejnowski.
Functional Brain Signal Processing: Current Trends and Future Directions Kaushik Majumdar Indian Statistical Institute Bangalore Center
Michael P. Kilgard Sensory Experience and Cortical Plasticity University of Texas at Dallas.
1 Computational Vision CSCI 363, Fall 2012 Lecture 3 Neurons Central Visual Pathways See Reading Assignment on "Assignments page"
Changju Lee Visual System Neural Network Lab. Department of Bio and Brain Engineering.
THE VISUAL SYSTEM: EYE TO CORTEX Outline 1. The Eyes a. Structure b. Accommodation c. Binocular Disparity 2. The Retina a. Structure b. Completion c. Cone.
The Visual Cortex: Anatomy
How well do we understand the neural origins of the fMRI BOLD signal? Owen J Arthurs and Simon Boniface Trends in Neuroscience, 2002 Gillian Elizabeth.
Layer V pyramidal neuron
Chapter 7. Network models Firing rate model for neuron as a simplification for network analysis Neural coordinate transformation as an example of feed-forward.
$ recognition & localization of predators & prey $ feature analyzers in the brain $ from recognition to response $ summary PART 2: SENSORY WORLDS #10:
Version 0.10 (c) 2007 CELEST VISI  N BRIGHTNESS CONTRAST: ADVANCED MODELING CLASSROOM PRESENTATION.
Synchronous activity within and between areas V4 and FEF in attention Steve Gotts Laboratory of Brain and Cognition NIMH, NIH with: Georgia Gregoriou,
Interneuron diversity and the cortical circuit for attention
Rhythms and Cognition: Creation and Coordination of Cell Assemblies Nancy Kopell Center for BioDynamics Boston University.
The LGN.
Wang TINS 2001 Wang et al PNAS 2004 Wang Neuron ms.
Chapter 22 Fundamentals of Sensory Systems
Network Models (2) LECTURE 7. I.Introduction − Basic concepts of neural networks II.Realistic neural networks − Homogeneous excitatory and inhibitory.
A neural test bed for simulating executive control deficits in saccade generation Uday Jagadisan Neeraj Gandhi University of Pittsburgh.
PRINCIPLES OF SENSORY TRANSDUCTION
Theta, Gamma, and Working Memory
Contrast Dependant Center Surround Interactions in Area V4
BY DR. MUDASSAR ALI ROOMI (MBBS, M. Phil.)
Neuronal Synchrony: A Versatile Code for the Definition of Relations?
R.W. Guillery, S.Murray Sherman  Neuron 
Cellular Mechanisms for Direction Selectivity in the Retina
Volume 73, Issue 3, Pages (February 2012)
Feedback Synthesizes Neural Codes for Motion
EEG and MEG: Relevance to Neuroscience
How Inhibition Shapes Cortical Activity
Reciprocal Inhibition of Inhibition: A Circuit Motif for Flexible Categorization in Stimulus Selection  Shreesh P. Mysore, Eric I. Knudsen  Neuron  Volume.
David J Calkins, Peter Sterling  Neuron 
Yann Zerlaut, Alain Destexhe  Neuron 
The Spike-Timing Dependence of Plasticity
Neuromodulation of Attention
Descending Control of Neural Bias and Selectivity in a Spatial Attention Network: Rules and Mechanisms  Shreesh P. Mysore, Eric I. Knudsen  Neuron  Volume.
Cortical Microcircuits
Volume 86, Issue 5, Pages (June 2015)
What the Fish’s Eye Tells the Fish’s Brain
Disinhibition, a Circuit Mechanism for Associative Learning and Memory
Rapid Neocortical Dynamics: Cellular and Network Mechanisms
Presentation transcript:

Data courtesy: Alex Goddard Gamma-band spike-field coherence in the optic tectum of the barn owl Sridharan Devarajan, Kwabena Boahen, Eric Knudsen Departments of Neurobiology and Bioengineering, Stanford University J. V. Arthur, K. A. Boahen, IEEE Trans. Neural Netw. 18, 1815 (2007). H. Luksch, Rev. Neurosci. 14, 85 (2003). J. R. Muller, M. G. Philiastides, W. T. Newsome, Proc. Natl. Acad. Sci. U. S. A. 102, 524 (2005). T. Williford, J. H. R. Maunsell, J. Neurophysiol. 96, 40 (2006). Literature Cited Maintenance of a “goal” in working memory (e.g. distinguishing food from dirt) The Imc circuit is well-placed to suppress the representation of distractors (red). Attention Stimulus selection in the optic tectum Orienting to salient stimuli in the environment (e.g. sudden appearance of a predator) Enhanced firing rate, and sharpened receptive field (RF) Summary Previous models have attempted to link these two signatures of attention, but have ignored the underlying neural circuitry. Synchronization among neuronal spikes is known to be an important signature of target selection in primates. Little is known, however, about the cellular and network mechanisms underlying the induction of this synchrony. Using recordings of single neurons and local field potentials in the optic tectum of the barn owl (Tyto alba), we find that gamma-synchrony is a signature of stimulus selection and distractor suppression. By modeling the tectal circuit in-silico, on neuromorphic hardware, we show that mimicking the effects of neuromodulation by acetylcholine is a potential mechanism for evoking synchrony during bottom-up stimulus selection. Neuronal signatures Reduced threshold and increased sensitivity Network signatures Spikes synchronize and phase lock with LFP LFP shows strong gamma ( γ ) rhythm (30-90Hz) Here we focus on the neural mechanisms of bottom-up stimulus selection, a fundamental component of attention. Isthmotectal microcircuit Being part of the avian gaze control circuitry, the optic tectum (OT) is ideally suited for stimulus selection. Its homolog in primates (superior colliculus, SC) is known to contribute importantly to spatial attention (Muller et al, 2005). Target Enhancement Distractor Suppression The Ipc circuit is well-placed to enhance the representation of target stimuli. The cholinergic Ipc circuit, and the GABA-ergic Imc circuit can be engaged by bottom-up inputs from the retina or top-down inputs from the forebrain gaze fields (AGF), thereby initiating or suppressing motor output. Stimulus evoked gamma-band LFP We model a single column in OT with spatially localized RF on a neuromorphic chip with 1024 excitatory and 256 inhibitory neurons. Modeling the circuit in-silico Neuron Chip Arthur & Boahen, 2007 Ipc (green, biocytin) projects homotopically to the optic tectum (arrow, insert), terminating in layer 5, rich with inhibitory neurons (red, calbindin). These interneurons have widespread horizontal arbors. Excitatory cells (blue, DAPI) in layers 8-10 also send their dendrites up into layer 5. Retinal axons synapse onto both excitatory and inhibitory neurons in layers 1-5 (Luksch, 2003). Detailed isthmotectal neuroanatomy 4x 40x Image courtesy: Alex Goddard Image courtesy: Phyllis Knudsen Key Predictions and Future directions ACh input from Ipc to OT facilitates fast excitatory (AMPA) synapses from the retina onto both excitatory ( E ) and inhibitory ( I ) neurons.  Contrast response function shifts right (less sensitivity)  Gamma-synchrony reduces (if not eliminated) We hypothesize that neuronal and network signature of attention are linked by ACh neuromodulation This hypothesis predicts that inactivating the Ipc (ACh nucleus) should disrupt both neural and network signatures: Future work will involve testing the key predictions of the model by inactivating the Ipc, while recording in the OT (in-vivo), as well as microstimulating Ipc (in-vitro) to test if ACh input to OT can induce synchrony. The transient increase in synchrony upon stimulus offset will be incorporated into a revised model. Acknowledgments This work was supported by grants NIH1 R01-DC (EK) and the NIH Director’s Pioneer Award Program Grant DPI-OD (KB). SD wishes to thank John Arthur for his help with programming the chip, and Alex Goddard and Phyllis Knudsen for kindly sharing images. Spectral analyses were performed with the Chronux toolbox ( Data courtesy: Alex Goddard Contrast response Spatial tuning Neuronal signatureNetwork signature In collab. with: Shreesh Mysore Facilitation of excitation Facilitation of inhibition E Retina ACh L-8 Retina ACh L-8 I L-4 E Layer 4/5 Layer 8/10 Optic Tectum AMPA (excitatory) GABA (inhibitory) ACh (cholinergic) Synapses Retina Ipc E Imc I I Inhibitory Excitatory Neurons I E Gaze Control In-vivo In-silico ? LFP spectrogram Spatial tuningContrast response