We introduce temporal working memory (TWM), which aims to enhance the temporal modeling capabilities of Multimodal foundation models (MFMs). This plug-and-play module can be easily integrated into existing MFMs. With our TWM, nine state-of-the-art models exhibit significant performance improvements across QA, captioning, and retrieval tasks.

Personalized Training for the Sequence Learning task with the NAO robot and the MUSE EEG sensor

Spiking neuronal network simulations (Python, NEST Simulator) for continuous attractor working memory networks with short-term plasticity.

A setup to evaluate working memory using EEG signals

Visual Working Memory Game in Python which gives you the gameplay data

This repository contains all codes necessary to reproduce figures and results reported in Stein, Barbosa et al. (Nature Communications, 2020) from the raw data acquired in human behavioral experiments (data included in the repository), and from the relevant model simulations.

A unified working & short-term memory task for artificial neural networks.

Generative working memory in Transformer decoder

These are short example PsychoPy Scripts

These scripts compute mean accuracy and total trial counts for working memory performance in the Secondary Memory (SM) tasks (letter position and word-word) developed by Wilhelm et al., 2013.