To meet the data-rate, power, and thermal constraints of intracortical Brain Computer Interfaces (BCIs), Imec has developed a neuromorphic compressive telemetry (NCT) chip for lossless, realtime data reduction.
The architecture is built around two key innovations (Y. He et al., 2024), (P. Russo et al., 2026):
Send-on-delta signal acquisition, replacing traditional Nyquest-rate sampling with an event‑driven scheme that produces data only when the neural signal changes.
A ternary packet-based AER serializer (eSER), which groups these events into compact packets for efficient serialization and deterministic transmission.
Together, these building blocks allow the NCT to eliminate redundant data – thus lowering (i)BCIs’ power and bandwidth requirements, while preserving all the information needed for high-fidelity spike reconstruction
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Figure 1: Imec has developed an NCT chip for lossless, realtime data reduction.
Most cortical neurons fire surprisingly infrequently – typically less than ten hertz, meaning just a few dozen spikes per second (and often even less). This inherent sparsity presents a major opportunity for data compression and reduction.
Traditional Nyquist-rate sampling captures signals at a fixed frequency – commonly 20-30kHz for neural sensing – regardless of whether any neural event (i.e., spike) is actually occurring. This produces a continuous stream of samples, the vast majority of which are redundant (when neurons are silent).
Imec’s send-on-delta sampling/encoding approach takes a fundamentally different path. Instead of sampling at fixed intervals, send-on-delta proposes an event-based, signal-dependent temporal sampling scheme: data is generated only when a signal changes by more than a predefined threshold (Δ). Thus, the output is not a dense waveform, but a sparse stream of information-rich events.
This brings several advantages: drastically fewer data points (often by an order of magnitude), significantly lower power consumption, and much lower bandwidth needs – while all spikes are captured with high fidelity.
A key improvement in imec’s latest (second-generation) send-on-delta mechanism is that the encoding now operates fully in the digital domain: instead of starting from raw analog voltages passing through a power-hungry send-on-delta analog-to-digital converter (ADC), the system works with a digital-state representation that reflects meaningful changes in the neural signal.
In simple terms, send-on-delta digitally detects when the signal changes, and then decides what to do with the underlying data.
While imec’s send-on-delta approach effectively exploits the sparsity of neural activity, it naturally produces spike-driven data streams (only when neural signals change, not at fixed intervals).
This is desirable to achieve power savings, but it requires a communication method that can handle irregular, spike-driven data.
Address-event representation (AER) protocols are a common solution for spike-driven event communication.
However, existing AER schemes show several limitations when applied to high-density neural recordings.
For example, when multiple readout channels generate events at the same time, classical AER relies on event arbitration or acknowledgement-based handshaking – which does not scale well to large channel counts, and introduces unpredictable latency.
In addition, neural spikes exhibit strong spatial correlation – a single spike may appear across several adjacent electrodes – yet traditional AER methods packetize and serialize each event independently, repeatedly transmitting redundant address information and incurring unnecessary protocol overhead.
To overcome these limitations, imec developed an event-based serializer (eSER) that combines send-on-delta with a ternary packet-based AER protocol – purpose-built for neural telemetry. Imec’s design introduces several key advantages:
Event-driven serial transmission – only when neural activity occurs,
Spatial grouping of correlated events – sending one compact packet instead of many little messages, which eliminates redundant metadata, and reduces protocol overhead by up to a factor of two,
No need for arbitration or collision-handling logic – rather than arbitrating between simultaneous events, the eSER first collects all Δ outputs and then emits one packet in a controlled sequence; this completely avoids event collisions, while removing the need for complex arbitration circuitry with indeterministic latency – a major bottleneck in conventional AER,
Rich, multi-bit (ternary) encoding for lossless reconstruction – imec’s AER packets contain Δ values, direction of change, and the channel ID to enable lossless spike waveform reconstruction (even for low amplitude spikes down to ~31 µV).
As such, imec’s AER solves the scalability, complexity, overhead, (indeterministic) latency, and power concerns of traditional implementations by aligning communication with the true nature of neural signals – sparse, bursty, and spatially correlated. By intelligently grouping events, encoding richer Δ information, and activating the serializer only when needed (when Δ does not equal zero), the system filters out redundant data at the source and achieves dramatically higher compression and ultra-low-power operation.
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Figure 2: Imec’s approach combines send-on-delta encoding for lossless, event-driven signal acquisition with a ternary packet-based AER protocol for advanced packetization and serialization. Source: imec.