Scanbox

Research

Data & Code

Neurotree

Publications

Department of Neurobiology & Psychology University of California, Los Angeles dario@ucla.edu

Mesoscope recordings from mouse visual cortex using 

The Ringach Lab

Local tuning biases in mouse primary visual cortex

The geometry of masking in neural populations 

Examples of recent research

Neuromodulatory control of localized dendritic spiking in critical period cortex

An inhibitory push-pull circuit in frontal cortex

Active learning of cortical connectivity from two-photon imaging data

Functional clusters of neurons in layer 6 of macaque V1

State-dependent subnetworks of parvalbumin-expressing interneurons in cortex

Community-based benchmarking improves spike-based inference from two-photon imaging data

Home

Orientation tuning in macaque V1

Download

This database describes the tuning curves of 308 neurons in macaque V1 (M. fascicularis). This are the raw data for all the figures in the paper Ringach et al, “Orientation Selectivity in Macaque V1: Diversity and Laminar Dependence”. J Neurosci. 22(13):5639-5651, 2002.  The variables in the file are as follows: db.orivar: circular variance of the orientation tuning curve based on mean spike rate db.maxdc: maximum spike rate across all orientations db.mindc: minimum spike rate across all orientations db.maxfirst: the first harmonic response at the optimal orientation db.po: The ratio between the responses at the orthogonal vs preferred orientation db.bw: Bandwidth of the tuning curve db.spont: Spontaneous firing rate db.depth: Normalized cortical distance (see paper for explanation) db.animal: Animal ID db.expt: Experiment ID db.chan: Electrode channel Funding: Work funded by NIH-EY12816, NSF-IBN-9720305, EY-08300, EY-01472

Spatial structure of simple cells in macaque V1

This database contains the analysis of shapes of 2D receptive fields in macaque V1 as described in Ringach, “Spatial Structure and Symmetry of Simple Cell Receptive Fields in Macaque V1" . J Neurophysiol. 88:455-463, 2002.  The variables in the file are as follows: db.nx: circular variance of the orientation tuning curve based on mean spike rate db.ny: maximum spike rate across all orientations db.ph: minimum spike rate across all orientations db.animal: Animal ID db.expt: Experiment ID db.chan: Electrode channel Funding: Work funded by NIH-EY12816, NSF-IBN-9720305, EY-08300, EY-01472

Overlap of ON and OFF subregions in macaque V1

This database contains the analysis of subregion overlap across 300 cells as described in Mata et al, “Spatial overlap of ON and OFF subregions and their relation to response modulation ration in macaque primary visual cortex" . J Neurophysiol. 2004.  The variables in the file are as follows: db(:,1): Discreteness measure (alpha) db(:,2): Correlation coefficient (rho) db(:,3): Normalized distance (delta)  db(:,4): Overlap index (omega)  db(:,5): Relative phase measure db(:,6): F1/F0 ratio Funding: Work funded by NIH-EY12816 and a Research to Prevent Blindness from the Jules Stein Institute

A Matlab implementation of the model described in Carandini and Ringach “Predictions of a recurrent model of orientation selectivity”, Vision Research,  1997

Model of orientation tuning 

An implementation of Hartigan’s dip test for bimodality in Matlab

Hartigan’s dip test

This Matlab function implements maximum liklihood estimation of tetrachoric correlation as described in Tallis, “The maximum likelihood of correlation from contingency tables”, Biometrika, 1962. 

Tetrachoric correlation

Orientation tuning in Macaque V1

Recurrent model of oreintation tuning

Some of our older data, code an algorithms can be found here.  More recent data can be found in CRCNS, Figshare and the NIH repository for the Brain Research Initiative.

Overlap of ON/OFF subregions in V1

Tetrachoric correlation estimation

Data, Code and Algorithms

Spatial Structure of Simple Cells in V1

Hartigan’s dip test of bimodality