Cognitive neuroscientist at Unicog. My homepage is at pallier.org.
Tools for building and running psychology/neuroscience experiments with precise timing.
| Repository | Description | Language |
|---|---|---|
| goxpyriment | General-purpose framework for building behavioral experiments — stimuli, trials, blocks, logging | Go |
| gostim2 | Fixed-schedule multimedia stimulus delivery (image, audio, text, video) with millisecond timing and VSYNC sync | Go |
| Pinel-localizer-go | fMRI functional localizer (Pinel et al. 2007) identifying brain regions for perception, motor, reading, language, arithmetic | Go |
| retinotopy-go | HCP retinotopic mapping — flickering checkerboard/wedge stimuli for visual cortex fMRI | Go |
| Posner_attention_networks_task | Attention Network Test (ANT-R) measuring alerting, orienting, and executive control | Python |
| Pinel_localizer | Python/expyriment version of the Pinel functional localizer | Python |
| Audiovis | Audio-visual stimulus presentation based on expyriment | Python |
| Expe3000 | Fixed-schedule audio/visual stimulus delivery | C |
Tools for generating and randomizing experimental stimulus lists.
| Repository | Description | Language |
|---|---|---|
| shuffle-go | Randomize lists with sequential constraints (max repetitions, minimum gap) | Go |
| dot-array-generator-go | Generate non-symbolic number stimuli (dot arrays) with configurable spatial constraints | Go |
| match-go | Implementation of van Casteren & Davis Mix & Match — match items across conditions on selected variables | Go |
| Repository | Description | Language |
|---|---|---|
| OpenLexicon | Platform providing access to lexical databases for psycholinguistic research, including Lexique | Python / R / JS |
| unipseudo-go | Pseudoword generator using trigram Markov chains from real word dictionaries (port of UniPseudo) | Go |
| llm_pseudoword_generator | Neural pseudoword generator trained with a character-level language model | Python |
| jabberwocky | Generates syntactically correct French nonsense text by replacing content words with pseudowords | Python |
| Repository | Description | Language |
|---|---|---|
| bbtkv3 | Capture stimulus/response events using the Black Box ToolKit v3 | Go |
| bbtkv2_python | Python module for precise timing acquisition with the Black Box ToolKit v2 | Python |
| dlp-io8-g | Send/read TTL triggers via an FTDI chip | Go |
| keyboard_scanner | HID event monitor — captures and timestamps keyboard/mouse input | Go / Python |
| neurospin_meg_response_keys_parallel_port | Record response button presses during MEG experiments via parallel port | Python |
Multi-modal neuroimaging study in which participants listened to The Little Prince audiobook.
| Repository | Description |
|---|---|
| lpp-paradigms | Experimental stimuli and presentation code across EEG, fMRI, and MEG modalities |
| LePetitPrince | Pipeline computing cross-validated R² maps of how well computational models predict brain activity |
| lpp-scripts3 | Full fMRI analysis pipeline: regressor generation, first/second-level analyses, ROI studies |
| Repository | Description |
|---|---|
| llms_brain_lateralization | NeurIPS 2024 — fMRI predictors from language models of increasing complexity recover left lateralization for language |
| llm_training_brain_asym | arXiv:2602.12811 — Left-right brain asymmetry in LLM-based fMRI prediction across OLMo-2 training stages |
| td_llms_brain_lateralization | Research code correlating LLMs (GPT-2, Qwen, Pythia) with fMRI brain activity patterns |
| Repository | Description | Language |
|---|---|---|
| mri-tools | Command-line utilities for processing fMRI data: image transformation, signal extraction, visualization | Python |
| Repository | Description |
|---|---|
| PCBS | Programming for Cognitive and Brain Sciences — full course |
| programming-psychology-experiments | Programming Psychology Experiments (subset of PCBS) |
| statistics_with_R | Basic statistical analyses with R |
| Repository | Description |
|---|---|
| linux-tips | Linux command-line tips and howtos |
| images2gv | Convert image sequences into GPU-accelerated video (.gv) with LZ4 compression and efficient frame seeking |