VERSION 0.9 · MAY 2026

Get Signal Studio. Free, open, local.

Runs entirely on your machine. No account, no telemetry, no calls home. Pick your OS, install, open. About ninety seconds to your first analysis.

macOS

v0.9.2 · Universal · 184 MB

Native build for Apple Silicon (M1/M2/M3/M4) and Intel Macs. Notarized, signed, ready to drag-and-drop into Applications.

Download .dmg
REQUIRES MACOS 12.0 +
8 GB RAM RECOMMENDED

Windows

v0.9.2 · x64 · 192 MB

Native x64 build for Windows 10 and 11. Signed installer, Start menu shortcut, file-association handlers for all formats.

Download .msi
REQUIRES WINDOWS 10 +
8 GB RAM RECOMMENDED

Linux

v0.9.2 · AppImage · 188 MB

AppImage runs on any modern distro — no install required. Also available as .deb, .rpm, and via Flatpak.

Download AppImage
.deb · .rpm · Flatpak available
8 GB RAM RECOMMENDED

Or build from source

Everything is on GitHub under the MIT license — fork it, audit it, build it your way.

View on GitHub git clone …
FIRST 90 SECONDS

From download to first plot.

Signal Studio onboards new users with a guided tour the first time it opens. These are the steps it walks you through.

STEP 01

Install & open

Drag to Applications (macOS), run the installer (Windows), or chmod the AppImage (Linux). Double-click. Signal Studio opens to the Welcome view.

STEP 02

Pick a template

Choose a starter workflow — ERP CORE, sleep staging, resting-state qEEG, or a blank canvas. Click "Use template" and you're in.

STEP 03

Drop your data

Drag any supported file onto the canvas. Signal Studio auto-detects format, channel types, and montage. The pipeline lights up green.

STEP 04

Run & inspect

Hit Run. Every node executes, every visualization updates. Scrub through your data in any of the eight tabs. That's it.

SYSTEM REQUIREMENTS

What it needs to run smoothly.

MINIMUM
RECOMMENDED
OSmacOS 12 · Windows 10 · Linux glibc 2.31+
OSmacOS 14 · Windows 11 · Ubuntu 24.04+
CPU4-core x86_64 / ARM64
CPU8-core Apple Silicon / Ryzen / Core i7
RAM4 GB free
RAM16 GB · 32 GB for multi-hour high-density
GPUIntegrated · Metal / Vulkan / DX12
GPUDiscrete · for 256ch real-time scrubbing
DISK500 MB install + cache
DISKNVMe SSD for out-of-core recordings
QUESTIONS

Things people ask before downloading.

Is it really free? What's the catch?

Yes, really. Free forever. MIT licensed. No tiers, no commercial version, no enterprise paywall. The project is funded by donations and grants. If you find it useful and have the budget, sponsor a contributor — but you'll never be required to.

Does it send my data anywhere?

No. Signal Studio runs entirely on your machine. There's no telemetry, no analytics, no "anonymized usage data." It only talks to the workflow hub when you explicitly fetch or publish a workflow. Perfect for clinical environments and air-gapped lab machines.

Can I keep using MNE-Python / EEGLAB alongside it?

Absolutely — that's the point. Signal Studio imports and exports MNE Raw/Epochs/Evoked objects natively, and supports EEGLAB .set files round-trip. Many of the built-in nodes are thin wrappers around MNE-Python. Use whichever interface fits the task.

How does it compare to commercial analyzers?

Feature-wise, comparable or better for most research workflows. Where commercial tools win is FDA-cleared clinical reporting — Signal Studio is a research tool, not a medical device. For everything else, see the comparison on the Software page.

I'm an undergrad with zero coding experience. Can I use this?

Yes. App Mode hides the node graph and shows just the parameters. Pick a community template, drop in your file, hit run. You'll likely produce your first publication-quality ERP figure within an afternoon, no Python required.

How do I cite Signal Studio in a paper?

Every workflow has an auto-generated cite-as block that credits both Signal Studio and the workflow's author, with versions pinned. Copy it into your methods section verbatim. For citing Signal Studio itself, see the "Cite Signal Studio" page in the footer.

Open the workspace.
See your data differently.

Pick your platform above, install, and you're a minute away from a working pipeline. Want a guided tour first? Watch the 4-minute walkthrough on YouTube.