British physician Richard Caton used a galvanometer to detect spontaneous electrical signals on the exposed cortex of rabbits and monkeys.

The first evidence that the brain produces measurable electrical activity — the observation the entire field rests on.

Qusp today — every signal Qusp acquires traces back to this idea: the brain is electrically active, and that activity is data.

Hans Berger recorded electrical activity from the human scalp and identified the alpha rhythm (~10 Hz), publishing in 1929.

This created electroencephalography as a discipline and gave clinicians a non-invasive window into the living human brain.

Qusp today — scalp EEG is still Qusp's core modality — the same non-invasive recording Berger pioneered, now streamed and processed in real time.

Edgar Adrian and Bryan Matthews reproduced and rigorously verified Berger's alpha rhythm, lending it credibility in the English-speaking world.

Independent replication turned EEG from a curiosity into accepted science and standardized how rhythms were measured.

Qusp today — reproducibility is the same standard Qusp enforces — version-pinned pipelines so any result can be reproduced exactly.

Gibbs, Davis, and Lennox demonstrated the 3-Hz spike-and-wave discharge of absence seizures, linking a specific EEG pattern to a diagnosis.

The birth of clinical electroencephalography — EEG became a diagnostic tool, not just a research instrument.

Qusp today — Qusp's epilepsy-monitoring workflows automate the long-term capture and flagging this discovery first made clinically meaningful.

Herbert Jasper developed the international 10–20 system, defining standardized scalp electrode positions as proportions of skull landmarks.

It gave the field a common spatial language, making recordings comparable across labs, patients, and decades.

Qusp today — Qusp's montage configuration is built directly on the 10–20 system and its high-density extensions (10–10, 10–5).

Grey Walter showed that signals from motor cortex could trigger an external slide projector before the subject pressed a button.

An early demonstration that brain signals could control a device — a conceptual seed of the brain–computer interface.

Qusp today — the closed loop Walter glimpsed — brain to machine — is exactly what Qusp's low-latency BCI pipeline is engineered to close.

Researchers characterized averaged event-related potentials; the P300 — a positive deflection ~300 ms after a meaningful stimulus — became the most studied ERP component.

ERPs let scientists time-lock neural responses to events with millisecond precision, enabling cognitive neuroscience and later ERP spellers.

Qusp today — Qusp's sub-millisecond trigger alignment exists precisely so ERP labs can measure components like the P300 without timing jitter.

Jacques Vidal at UCLA published the first paper explicitly framing the brain–computer interface and asking whether EEG could drive real-time control.

It named and formalized the field of BCI, setting the research agenda for the next fifty years.

Qusp today — Qusp builds the modern infrastructure for the question Vidal first posed: turning live EEG into reliable control and insight.

A BCI that let users spell words by attending to flashing letters in a grid, detected via their P300 responses — no movement required.

It proved communication through thought alone was possible, a landmark for patients with severe motor impairment.

Qusp today — neurofeedback and BCI workflows on Qusp descend directly from paradigms like this — stimulus, response, decode, act.

Jonathan Wolpaw's group showed humans could move a cursor on screen by modulating sensorimotor rhythms recorded via scalp EEG.

It established non-invasive, learnable BCI control and shaped neurofeedback training protocols still used today.

Qusp today — real-time feedback like Wolpaw's requires the tight acquisition-to-display loop Qusp is purpose-built to deliver.

MATLAB-based toolboxes — most notably EEGLAB from the Swartz Center at UC San Diego — began standardizing EEG preprocessing and ICA-based artifact removal.

Shared, scriptable analysis made EEG methods transparent and repeatable across the research community.

Qusp today — Qusp interoperates with the EEGLAB/MNE lineage and shares its academic roots in the Swartz Center community.

Work from labs including Donoghue's and Nicolelis's showed primates — and later humans — controlling robotic effectors via implanted microelectrode arrays.

It demonstrated high-bandwidth invasive BCIs, expanding the field from scalp EEG to intracortical recording.

Qusp today — Qusp's hardware-agnostic acquisition spans scalp and high-density systems, meeting labs wherever their electrodes sit.

Developed out of the Swartz Center, LSL became the open standard for time-synchronized streaming of EEG, markers, and peripheral devices over a network.

It solved the multi-device synchronization problem — aligning data sources to sub-millisecond precision in real time.

Qusp today — LSL is native to Qusp: it's how the platform ingests any amplifier and keeps every stream aligned.

Companies like Emotiv and NeuroSky released affordable dry-electrode headsets, and OpenBCI later open-sourced research-grade hardware.

It democratized access to EEG, broadening who could build and experiment with brain-signal applications.

Qusp today — Qusp connects the full hardware spectrum — from consumer headsets to clinical amplifiers — over one interface.

MNE-Python and a growing scientific-Python ecosystem brought open, scriptable EEG/MEG analysis to a new generation of researchers.

It pushed the field toward reproducible, code-first pipelines and away from manual, click-based processing.

Qusp today — Qusp's processing pipelines are version-pinned and scriptable in this same spirit — reproducible by default.

The Brain Imaging Data Structure was extended to EEG, defining a common file and metadata layout for sharing datasets.

Standardized structure made data shareable, auditable, and reusable across studies and institutions.

Qusp today — Qusp exports BIDS-ready datasets with sidecar metadata, so studies are publication- and archive-ready from the start.

Research groups decoded attempted handwriting and speech from cortical activity in people with paralysis, restoring rapid communication.

It signaled the clinical maturation of BCI — from lab demonstrations to life-changing assistive systems.

Qusp today — this translation is Qusp's mission: moving neurotechnology from the lab bench to the clinic, reliably and reproducibly.

Modern systems combine high-density acquisition, real-time processing, and adaptive feedback for neurofeedback therapy, responsive stimulation, and live BCI control.

The field has converged on low-latency, reproducible, closed-loop platforms — the operating layer for clinical and research neuroscience.

Qusp today — this is the chapter Qusp is writing: clinical-grade acquisition, processing, monitoring, and export in one self-hosted platform.