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  • Roitman DC
    The original data files are organized into four zip packages and each contains a list of mat files for each neuron which are all b fd tar gz for monkey B Fixed Duration task all b rt tar gz for monkey B Reaction Time task all n fd tar gz for monkey N Fixed Duration task all n rt tar gz for monkey N Reaction Time task Most of the data is in multiple matlab files each with a single large structure To find out more about this struture please see the example script sampleScript m This script creates several raster plots as an example of how to use this structure Data file T1RT mat gz includes one zipped file that is a compilation of all data used to create Fig 7 of this paper It is in an easier format and all bad trials ones with recording problems or ones where the subject did not complete the task are already excluded File T1RT mat gz includes several variables x is the data matrix Each row is a separate trial and the columns are described in file ColumnNames608 m f is a column of file names Each row corresponds to a trial from matrix x and shows from which data file the trial originally came s is a column of cells Each cell corresponds to a trial from matrix x and has contained in it all of the spike times from that trial beginning 100 ms before the stimulus onset and ending 200 ms after the saccade Matlab code file lip rt roit fig 7 m is the main mfile to plot Fig 7 of this paper This file takes the data from a rather raw form and creates the PSTHs that are then plotted so depending on the speed

    Original URL path: https://www.shadlenlab.columbia.edu/resources/RoitmanDataCode.html (2015-06-03)
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  • Probabilistic
    content of each of the movies Versions of these diagrams are also reproduced dynamically at the bottom of the movies Each movie begins with acquisition of the fixation point FP and ends with a saccadic eye movement to the red or the green target The moving yellow dot shows the eye position of the monkey during the trial In the bottom of the movie spike trains are shown as ticks along the time line The traces depict the changing logLR associated with the appearance of the shapes height reflects the logLR in favor of Tin The color of the trace in the movies indicates whether the evidence currently favors the red or the green target Neither the eye position trace nor the diagrams were shown on the video display that was viewed by the monkey The movie soundtrack plays the spikes from the neuron There is a prominent transient response to the targets in the beginning of the 1st epoch The four shapes cause the firing rate to increase or decrease 200 ms after each is displayed Movies 1 3 are from the example neuron depicted in Figure 2 RF below and to the right of fixation Movies 4 6

    Original URL path: https://www.shadlenlab.columbia.edu/resources/ProbabilisticReasoningNeurons.html (2015-06-03)
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  • Probabilistic
    in which monkey E chose the left target Tin after viewing 7 shapes The movie is played at half speed Eye position is depicted by the yellow dot After acquiring fixation at the central white dot two red choice targets appear The left target is in the RF of the neuron After a delay shapes appear sequentially until the monkey initiates its saccade Action potentials can be heard as clicks They are also displayed as tick marks above the graph which shows the cumulative logLR associated with each new shape horizontal white line segments displaced by 200 ms relative to the spikes in order to compensate for the sensory delay τs see main text They are thus aligned approximately to the spikes induced by each new shape The neutral level of evidence logLR 0 is shown as a horizontal yellow line The eye position and lower graph were not displayed to the monkey nor were the audio clicks Only the fixation spot targets and shapes were visible to the monkey In this trial the cumulative logLR meandered around zero for the first few shapes and then favored Tin Reflecting this pattern the firing rate increased with the rise in the

    Original URL path: https://www.shadlenlab.columbia.edu/resources/WaldSequentialProbabilityRatioTest.html (2015-06-03)
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  • Christopher R. Fetsch, Ph.D. (Chris Fetsch)
    2011 Neural correlates of reliability based cue weighting during multisensory integration Nat Neurosci 15 1 146 54 Gu Y Liu S Fetsch CR Yang Y Fok S Sunkara A DeAngelis GC Angelaki DE 2011 Perceptual learning reduces interneuronal correlations in macaque visual cortex Neuron 71 4 750 61 Fetsch CR Rajguru SM Karunaratne A Gu Y DeAngelis GC and Angelaki DE 2010 Spatiotemporal properties of vestibular responses in area MSTd J Neurophysiol 104 3 1506 22 Fetsch CR DeAngelis GC and Angelaki DE 2010 Visual vestibular cue integration for heading perception applications of optimal cue integration theory Eur J Neurosci 31 10 1721 9 Gu Y Fetsch CR Gu Y Adeyemo B Angelaki DE and DeAngelis GC 2010 Decoding of MSTd population activity accounts for variations in the precision of heading perception Neuron 66 4 596 609 Fetsch CR Turner AH DeAngelis GC and Angelaki DE 2009 Dynamic re weighting of visual and vestibular cues during self motion perception J Neurosci 29 15601 12 Fetsch CR Wang S Gu Y DeAngelis GC and Angelaki DE 2007 Spatial reference frames of visual vestibular and multimodal heading signals in the dorsal subdivision of the medial superior temporal area J Neurosci 27 3

    Original URL path: https://www.shadlenlab.columbia.edu/people/chris_files/publications.html (2015-06-03)
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  • Shushruth, M.B.B.S., Ph.D.
    Werner JS eds 2014 Cambridge MIT Press Shushruth S pdf Exploring the neural basis of consciousness through anesthesia J Neurosci 2013 Jan 33 5 1757 8 Shushruth S Nurminen L Bijanzadeh M Ichida JM Vanni S Angelucci A pdf Different orientation tuning of near and far surround suppression in macaque primary visual cortex mirrors their tuning in human perception J Neurosci 2013 Jan 33 1 106 19 Shushruth S Mangapathy

    Original URL path: https://www.shadlenlab.columbia.edu/people/Shushruth/Home.html (2015-06-03)
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  • Shushruth, M.B.B.S., Ph.D.
    Feb 2004 Publications pdfs Seyedhosseini M Shushruth S Davis T Ichida JM House PA Greger B Angelucci A Tasdizen T Informative features of local field potential signals in primary visual cortex during natural image stimulation J Neurophysiol 2015 Mar 1 113 5 1520 32 Angelucci A Shushruth S Beyond the classical receptive field Surround modulation in primary visual cortex In The New Visual Neurosciences Chalupa LM Werner JS eds 2014 Cambridge MIT press Shushruth S Exploring the neural basis of consciousness through anesthesia J Neurosci 2013 Jan 33 5 1757 8 Shushruth S Nurminen L Bijanzadeh M Ichida JM Vanni S Angelucci A Different orientation tuning of near and far surround suppression in Macaque primary visual cortex mirrors their tuning in human perception J Neurosci 2013 Jan 33 1 106 19 Shushruth S Mangapathy P Ichida JM Bressloff PC Schwabe L Angelucci A Strong recurrent networks compute the orientation tuning of surround modulation in the primate primary visual cortex J Neurosci 2012 Jan 32 1 308 21 Schwabe L Ichida JM Shushruth S Mangapathy P Angelucci A Contrast dependence of surround suppression in Macaque V1 Experimental testing of a recurrent network model Neuroimage 2010 Sep 52 3 777 92 Shushruth S Ichida JM Levitt JB Angelucci A Comparison of spatial summation properties of neurons in macaque V1 and V2 J Neurophysiol 2009 Oct 102 4 2069 83 Conference Abstracts Presenting author Shushruth S Mazurek M Shadlen MN 2013 A comparison of categorization signals and decision related signals in Area LIP Soc Neurosci Abstr Online 668 07 Shushruth S Davis TS Tasdizen T Ichida JM House P Greger B Angelucci A 2011 LFP signals evoked by natural image stimulation of the far surround of V1 neurons carry contrast independent image specific information Soc Neurosci Abstr Online 483 11 Shushruth S Tasdizen

    Original URL path: https://www.shadlenlab.columbia.edu/people/Shushruth/CV.html (2015-06-03)
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