Drugowitsch Lab

ML-from-scratch-seminar

This repository is part of a "Machine Learning from Scratch" seminar at Harvard Medical School.

VBLinLogit

Variational Bayes linear and logistic regression

DiffModels.jl

Diffusion Model simulation and first-passage time densities in Julia

dm

C++ Diffusion model toolset with Python and Matlab interfaces

HippocampalSWRDynamics

Code for Krause and Drugowitsch (2022). "A large majority of awake hippocampal sharp-wave ripples feature spatial trajectories with momentum". Neuron.

MultiAlternativeDecisions

Code for Tajima et al. (2019). Optimal policy for multi-alternative decisions. Nature Neuroscience.

CoSMo2017

Data and scripts for the CoSMo 2017 summer school

FENS2015

Code for a tutorial on normative solutions to the speed-accuracy trade-off in perceptual decision making

motion-structure-used-in-perception

Python code and data for Bill et al. "Hierarchical structure is employed by humans during visual motion perception"

motion-structure-identification

Investigating how humans identify statistical motion relations in dynamic scenes.

remoteBook

Utilities for working remotely

BayesianRingAttractor

This repo contains the code for simulations and figures in Anna Kutschireiter, Melanie A Basnak, Rachel Wilson & Jan Drugowitsch. 2023. Bayesian inference in ring attractor networks. PNAS. https://doi.org/10.1073/pnas.2210622120

structure-in-motion

Code for the research paper "Structure in motion: visual motion perception as online hierarchical inference" by Johannes Bill, Samuel J Gershman, and Jan Drugowitsch

circKF

Code for Kutschireiter, Rast & Drugowitsch (2022). IEEE Transactions on Signal Processing.

DDMLearningWithConfidence

Scripts to generate plots of "Learning optimal decisions with confidence" paper

ImpactOfLearningDecisionsOnSAT

Code and data accompanying Mendonca et al., (2020): The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs.

Optimal-policy-attention-modulated-decisions

Code accompanying paper "Optimal policy for attention-modulated decisions explains human fixation behavior".

Optimal-policy-for-value-based-decision-making

These are the codes related to the following publication: Tajima, S., Drugowitsch, J., and Pouget, A. Optimal policy for value-based decision-making. Nature Communications, 7:12400, (2016).

Optimal-decision-making-with-time-varying-evidence-reliability

Code used to generate figures in Drugowitsch, Moreno-Bote & Pouget (2014). Optimal decision-making with time-varying evidence reliability.

OptimalMultisensoryDecisionMakingwithRT

Some code used in Drugowitsch, DeAngelis, Klier, Angelaki & Pouget (2014) and Drugowitsch, DeAngelis, Angelaki & Pouget (2015)

PPC-Geometry-NeurReps22

SensoryInformationScaling

Code for figures in Kafashan et al. (2021). Scaling of sensory information in large neural populations shows signatures of information-limiting correlations.