anne-urai Goto Github PK

2017_urai_pupil-uncertainty

Urai AE, Braun A, Donner TH. (2017) Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nature Communications 8:14637.

2018_bergturai_pupil-memory

Bergt A, Urai AE, Donner TH, Schwabe L (2018) Reading memory formation from the eyes. European Journal of Neuroscience

2019_urai_choice-history-ddm

Urai AE, de Gee JW, Tsetsos K, Donner TH (2019) Choice history biases subsequent evidence accumulation. eLife

2022_urai_choicehistory_meg

Urai & Donner (2022). Persistent Activity in Human Parietal Cortex Mediates Perceptual Choice Repetition Bias

anne-urai.github.io

behavenet

Behavioral and neural analysis toolbox based on https://papers.nips.cc/paper/9701-behavenet-nonlinear-embedding-and-bayesian-neural-decoding-of-behavioral-videos.pdf

cleanbib

Probabilistically assign gender and race proportions of first/last authors pairs in bibliography entries

climate_dataviz

Net-zero pathways and their predictions for CO2 and global temperatures

climate_psychology

Collected examples and resources for incorporating climate crisis and action into the psychology curriculum.

confidence_racemodel

simulate simple LCA, see if RTs scale with decision uncertainty

course-content

Summer course content for Neuromatch Academy

ddm_mediation

decoding-toolbox

Personal mini-toolbox for decoding MEG data

fieldtrip

The MATLAB software toolbox for MEG and EEG analysis

hddm

HDDM is a python module that implements Hierarchical Bayesian parameter estimation of Drift Diffusion Models (via PyMC).

ibl-pipeline

DataJoint pipeline for IBL project

iblscripts

Deployment scripts for ibl

lab_wiki

This is the lab wiki. For more info about our team, research, blog and publications see https://anneurai.net.

largescale_recordings

Urai AE, Doiron B, Leifer AM & Churchland AK (2022) Large-scale neural recordings call for new insights to link brain and behavior. Nature Neuroscience

mentoring

Various tips and tools for students

model-free_model-based_workshop

This folder contains all the material to be used in the FLUX 2021 Model-free and Model-based computational workshop

motion_energy_filtering

Urai AE & Wimmer K (2016). Spatiotemporal motion energy filtering: a Matlab implementation.

mouse_history_ddm

nsci801-quantneuro

NSCI 801 (Queen's U) Quantitative Neuroscience course materials

plot_gitlab_ibl_data

pupil_preprocessing_tutorial

Preprocess EyeLink pupillometry data using the FieldTrip toolbox

seaborn

Statistical data visualization using matplotlib

slow_drift_correction

Fitting the model from Gupta & Brody to human behavioral data

tics-2020-tutorial

Tutorial on computational modeling and statistical model fitting part of the *Trends in Computational Neuroscience* graduate course of the University of Geneva (2020).

tools

all kinds of random code tools