A modern brain–computer interface reads a thousand electrodes at tens of kilohertz — hundreds of megabits per second — through a wireless link that carries a small fraction of that. The gap is the binding constraint of implantable neurotech. SC-NeuroCore closes it with lossless neural codecs that exploit how sparse and structured spike data is, and a mode that is bit-true to on-implant hardware.
The numbers are stark. Raw electrode data out-runs the uplink by one to two orders of magnitude, and the radio is fixed by power and thermal limits inside the skull — so the data has to shrink, losslessly, before it leaves.
| System | Channels | Raw rate | Uplink | Gap | Codec |
|---|---|---|---|---|---|
| Neuralink N1 | 1,024 | 205 Mbps | 10–20 Mbps | 10–20× | WaveformCodec (~25×) |
| Neuralink next-gen | 3,072 | 614 Mbps | 10–20 Mbps | 30–60× | WaveformCodec |
| Neuropixels 2.0 | 384 | 77 Mbps | archival | storage | WaveformCodec |
| Closed-loop BCI | 256–1024 | 51–205 Mbps | on-chip | < 1 ms | StreamingCodec |
Raw rate assumes 30 kHz × 10-bit sampling per channel; the codec ratio follows the measured ISI curve (hundreds-fold on very sparse trains, single-digit on dense ones) or the ~24× hybrid WaveformCodec. Illustrative of the trade — exact ratios depend on the recording.
The headline codec is a hybrid that splits the raw signal into what matters where: the spike band is reduced to spike times and coded losslessly (inter-spike intervals + Huffman), while the slow background field potential is down-sampled, delta-coded, quantised and entropy-packed. Measured around 24–25× on realistic recordings — enough to drop a 1,024-channel Neuralink-class stream into a Bluetooth uplink.
When the data is already a spike raster, six codecs each attack its structure differently. Because spikes are rare, the achievable ratio scales inversely with firing density — enormous on quiet trains, single-digit when everything is firing at once.
recommend_codec(n_channels, firing_rate, latency_ms) helper picks one from the constraints, and all of them round-trip losslessly — the spike-codec notebook on this site benchmarks them across densities.Compression only helps if it can run inside the implant, on a power budget of milliwatts. The predictive codec has an LFSR mode in Q8.8 fixed-point that is bit-true to generated Verilog — the same compression, provable on the same silicon path as the rest of the toolkit, so the codec is ASIC-deployable rather than a host-side afterthought.
A therapeutic closed loop — read, decode, stimulate — cannot wait for a big buffer to fill. The StreamingCodec compresses incrementally with a bounded per-window latency (sub-millisecond targets), trading a little ratio for the timing a control loop needs, while the archival path uses the higher-ratio block codecs.
| Codec | Best for | Method | Measured ratio |
|---|---|---|---|
| ISI | general purpose | inter-spike intervals + varint/Huffman | ~400× at 0.1%, ~9× at 30% |
| Predictive (context) | structured / bursty | Markov context + XOR residual | ~25× on bursty (≈3× over ISI) |
| Predictive (LFSR) | on-implant hardware | Q8.8 LFSR, bit-true Verilog | same ratio, ASIC-deployable |
| WaveformCodec | raw electrode streams | hybrid spike + LFP | ~24–25× |
| StreamingCodec | closed-loop < 1 ms | incremental, bounded latency | latency-bounded |
Compression figures are measured on specific recordings and densities and are directional, not guarantees; every codec here round-trips losslessly (except the WaveformCodec's background-LFP stage, which is deliberately lossy). System bandwidths cite published device specifications.