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Most electrophysiology is a one-way street: record activity, analyze it later, draw conclusions. Closed-loop experiments break that pattern. By detecting a specific pattern of neural activity — a ripple, a phase of theta, a decoded memory representation — the instant it occurs and triggering a perturbation either in the brain or in the environment in response, researchers can move from merely observing brain dynamics to testing them causally, in real time, while an animal is behaving. A recent review by Wenxuan Fang, Afsoon Mombeini, and Manu Madhav frames these efforts as part of a broader shift in experimental neuroscience, arguing that advances in real-time recording, decoding, and miniaturized stimulation hardware are letting researchers reshape neural computation it while it’s underway to gain a more detailed understanding of how the brain functions. This kind of experiment places extraordinary demands on hardware: recording and processing have to be fast enough, and precise enough, that the intervention actually lands on the neural event it’s meant to target.

Scaling Up Multichannel Electrophysiology: SpikeGadgets and the Push Toward Higher Channel Counts
For decades, the central bottleneck in systems neuroscience wasn’t a lack of good questions — it was a lack of good hardware. You could record from a handful of neurons in one region, or a few hundred in one probe, but the brain doesn’t work one region at a time. Understanding how sensory information becomes a decision, or how one hemisphere’s worth of circuitry supports cognition, means recording simultaneously across many sites, many regions, and — ideally — many thousands of channels at once. Three recent papers show how SpikeGadgets’ multichannel electrophysiology hardware is being pushed toward exactly that kind of large-scale recording, and what that scale makes possible.

High-density Neuropixels probes can record from hundreds to thousands of neurons at once — but that density used to come at the cost of freedom of movement, since the probe’s data had to be streamed out through a cable to a fixed acquisition system. SpikeGadgets’ Neuropixels-compatible dataloggers remove that constraint: the systems write probe data straight to onboard storage, so the animal can carry the whole recording system with it, wirelessly, while behaving naturally. Over the past twelve months, four papers have put this combination — Neuropixels probes plus a SpikeGadgets datalogger — to work in freely moving and freely flying animals, and the results are reshaping some long-standing assumptions about hippocampal replay, prefrontal sequence coding, and vocal communication. Here’s a roundup.

SpikeGadgets is proud to announce the release of the Pixie 384 Datalogger Headstage. Inspired by the best-selling HH128 and HH256 dataloggers, the Pixie384 boasts triple the channels of the HH128 datalogger with 50% longer record time (using a 400mAh battery)!

SpikeGadgets is proud to announce that our Neuropixels Datalogger Headstage played a crucial role in a landmark study published in Nature, marking the first successful wireless Neuropixels recording of large-scale neural activity from freely flying bats. This breakthrough research, conducted at UC Berkeley by a team led by Michael Yartsev, represents a significant advancement in our understanding of how the mammalian brain processes three-dimensional navigation.

SpikeGadgets is thrilled to announce the release of the Sprite32 Datalogger – a 32-channel headstage lightweight enough for untethered datalogging with animals as small as mice!

A recent paper from Loren Frank’s lab at UCSF has unveiled a significant advancement in brain-machine interface (BMI) technology, specifically designed for studying memory retrieval processes in rats. With help from SpikeGadgets, they developed a sophisticated closed-loop hippocampal neurofeedback system that allowed rats to generate specific remote spatial representations without sensory cues or physical movement toward target locations.