Contextual Feedback to Superficial Layers of V1

Slides:



Advertisements
Similar presentations
Volume 26, Issue 24, Pages (December 2016)
Advertisements

Volume 60, Issue 4, Pages (November 2008)
Volume 60, Issue 5, Pages (December 2008)
Volume 25, Issue 21, Pages (November 2015)
Decoding Sound and Imagery Content in Early Visual Cortex
Araceli Ramirez-Cardenas, Maria Moskaleva, Andreas Nieder 
Michael S Beauchamp, Kathryn E Lee, Brenna D Argall, Alex Martin 
Analysis of the Neuronal Selectivity Underlying Low fMRI Signals
Pattern and Component Motion Responses in Mouse Visual Cortical Areas
Linking Electrical Stimulation of Human Primary Visual Cortex, Size of Affected Cortical Area, Neuronal Responses, and Subjective Experience  Jonathan.
Volume 21, Issue 19, Pages (October 2011)
Volume 23, Issue 18, Pages (September 2013)
Representation of Object Weight in Human Ventral Visual Cortex
Decoding Neuronal Ensembles in the Human Hippocampus
Mismatch Receptive Fields in Mouse Visual Cortex
Sing-Hang Cheung, Fang Fang, Sheng He, Gordon E. Legge  Current Biology 
Scale-Invariant Movement Encoding in the Human Motor System
Yukiyasu Kamitani, Frank Tong  Current Biology 
Face Pareidolia in the Rhesus Monkey
Volume 26, Issue 3, Pages (February 2016)
Dustin E. Stansbury, Thomas Naselaris, Jack L. Gallant  Neuron 
Volume 82, Issue 5, Pages (June 2014)
Dynamic Shape Integration in Extrastriate Cortex
FMRI Activation in Response to Illusory Contours and Salient Regions in the Human Lateral Occipital Complex  Damian A. Stanley, Nava Rubin  Neuron  Volume.
Deciphering Cortical Number Coding from Human Brain Activity Patterns
Volume 26, Issue 7, Pages (April 2016)
Volume 22, Issue 21, Pages (November 2012)
Talia Konkle, Aude Oliva  Neuron  Volume 74, Issue 6, Pages (June 2012)
Michael S Beauchamp, Kathryn E Lee, Brenna D Argall, Alex Martin 
Confidence Is the Bridge between Multi-stage Decisions
Volume 27, Issue 23, Pages e3 (December 2017)
The Functional Neuroanatomy of Object Agnosia: A Case Study
BOLD fMRI Correlation Reflects Frequency-Specific Neuronal Correlation
Decoding the Yellow of a Gray Banana
Volume 19, Issue 6, Pages (March 2009)
John T. Arsenault, Koen Nelissen, Bechir Jarraya, Wim Vanduffel  Neuron 
Near-Real-Time Feature-Selective Modulations in Human Cortex
Human Dorsal and Ventral Auditory Streams Subserve Rehearsal-Based and Echoic Processes during Verbal Working Memory  Bradley R. Buchsbaum, Rosanna K.
Integration of Local Features into Global Shapes
Perception Matches Selectivity in the Human Anterior Color Center
Broca's Area and the Hierarchical Organization of Human Behavior
Pattern and Component Motion Responses in Mouse Visual Cortical Areas
High-Resolution fMRI Reveals Laminar Differences in Neurovascular Coupling between Positive and Negative BOLD Responses  Jozien Goense, Hellmut Merkle,
Volume 19, Issue 3, Pages (February 2009)
Direct Two-Dimensional Access to the Spatial Location of Covert Attention in Macaque Prefrontal Cortex  Elaine Astrand, Claire Wardak, Pierre Baraduc,
Volume 23, Issue 21, Pages (November 2013)
Visual Feature-Tolerance in the Reading Network
Michael A. Silver, Amitai Shenhav, Mark D'Esposito  Neuron 
Vahe Poghosyan, Andreas A. Ioannides  Neuron 
Volume 26, Issue 14, Pages (July 2016)
Sébastien Marti, Jean-Rémi King, Stanislas Dehaene  Neuron 
Volume 35, Issue 3, Pages (August 2002)
Volume 16, Issue 20, Pages (October 2006)
John T. Serences, Geoffrey M. Boynton  Neuron 
Attention Samples Stimuli Rhythmically
Encoding of Stimulus Probability in Macaque Inferior Temporal Cortex
Volume 18, Issue 19, Pages (October 2008)
Category Selectivity in the Ventral Visual Pathway Confers Robustness to Clutter and Diverted Attention  Leila Reddy, Nancy Kanwisher  Current Biology 
Volume 16, Issue 20, Pages (October 2006)
Perceptual Classification in a Rapidly Changing Environment
The Perception and Misperception of Specular Surface Reflectance
Color Signals in Human Motion-Selective Cortex
Hippocampal-Prefrontal Theta Oscillations Support Memory Integration
Color Constancy for an Unseen Surface
Volume 16, Issue 15, Pages (August 2006)
Taosheng Liu, Franco Pestilli, Marisa Carrasco  Neuron 
Attention-Dependent Representation of a Size Illusion in Human V1
Clark Fisher, Winrich A. Freiwald  Current Biology 
Visual Feature-Tolerance in the Reading Network
Michael A. Silver, Amitai Shenhav, Mark D'Esposito  Neuron 
Presentation transcript:

Contextual Feedback to Superficial Layers of V1 Lars Muckli, Federico De Martino, Luca Vizioli, Lucy S. Petro, Fraser W. Smith, Kamil Ugurbil, Rainer Goebel, Essa Yacoub  Current Biology  Volume 25, Issue 20, Pages 2690-2695 (October 2015) DOI: 10.1016/j.cub.2015.08.057 Copyright © 2015 The Authors Terms and Conditions

Current Biology 2015 25, 2690-2695DOI: (10.1016/j.cub.2015.08.057) Copyright © 2015 The Authors Terms and Conditions

Figure 1 Experimental Procedure (A) Example stimulus for the “feedback” condition, in which the lower right quadrant was occluded by a white mask (see [14]). The “feedforward” condition comprised the full image (not shown). (B) “Target” and “surround” checkerboards (presented individually during scanning) to locate voxels responding to the lower right visual field. (C) Left hemisphere cortical reconstruction of subject 2 in experiment 1, overlaid with a contrast of target response greater than surround response (light blue V1 and V3; dark blue V2). The cortical grid mesh depicts reconstructed depth layers from deep/inner (purple; close to white matter) to superficial/outer (red; close to the pial surface) cortical boundary. (D) Corresponding regions of interest to (C) overlaid onto GE-EPI images. Current Biology 2015 25, 2690-2695DOI: (10.1016/j.cub.2015.08.057) Copyright © 2015 The Authors Terms and Conditions

Figure 2 Layer-Specific Regions of Interest (A) For subject 1: surface reconstruction overlaid with “target > surround” activity map (left); cortical grid lines depicting depth layers (middle); regions of interest in depth layers overlaid onto GE-EP images (right). (B) For subject 3: inflated surface reconstruction overlaid with map of target responses outlined in red (V1), green (V2), and white (V3); borders between visual areas V1 and V3 are shown by black (dashed) lines (left); inflated surface reconstruction overlaid with polar angle retinotopic mapping data (middle); regions of interest colored in activity (top) or depth overlaid onto GE-EP images (right). (C) As in (B), but for subject 4. Note: The cortex appears thicker when the slice plane cuts through it at a shallow angle (right column). Current Biology 2015 25, 2690-2695DOI: (10.1016/j.cub.2015.08.057) Copyright © 2015 The Authors Terms and Conditions

Figure 3 Layer-Specific Information Decoding (A) For V1 using GE fMRI data, SVM classification performance for all four subjects during feedforward (red dashed) and feedback (green) processing, in individual depths (color-coded purple to red). Chance decoding level was 33%, and significant classification is marked by circles. (B) For V1, V2, and V3 averaged across subjects using GE fMRI data, SVM classification performance in cortical depths (from white matter 90% depth to superficial depth 10%). Left panels show prediction of single trials in the left out run; right panel shows the averaged condition of the left out run. Significant differences in decoding performance between depths are marked on subject-averaged single run plots (permutation tested); error bars represent SEM (across subjects and leave-one-run-out folds). (C) As in (A), but for subject 2 and 4’s 3D-GRASE fMRI data. (D) We trained an SVM algorithm on a given cortical depth and a given signal (i.e., either feedforward or feedback) and tested its performance against the same or the other signal across all depths. Asterisks indicate significance against theoretical chance level (FDR q < 0.05). See also Figures S1–S4. Current Biology 2015 25, 2690-2695DOI: (10.1016/j.cub.2015.08.057) Copyright © 2015 The Authors Terms and Conditions

Figure 4 Feedback Sensitivity to Shifts of the Surround (A) Occluded stimuli used in experiment 2. We shifted the original stimuli (0°) by 2° and 8°. (B) Cortical depth layers shown in the sagittal plane of subject 2, from deep, inner (purple) to superficial, outer (red). (C) SVM decoding performance for different depths of V1 when cross-classifying images of different shifts, for all four subjects. Current Biology 2015 25, 2690-2695DOI: (10.1016/j.cub.2015.08.057) Copyright © 2015 The Authors Terms and Conditions