HVC Ultra-Sparse Code
Neuro simulations · Episode 02

One burst per song

Zebra finch song is driven by a forebrain clock. In nucleus HVC, each neuron that projects to RA fires a single brief burst at one precise moment of the song motif and is silent the rest of the time. This page rebuilds that ultra-sparse code from the numbers and equations in Hahnloser, Kozhevnikov & Fee (2002).

  1. PAPERAn ultra-sparse code underlies the generation of neural sequences in a songbirdNature 419:65–70 (2002)
  2. HVC(RA)Projection neurons to RA: at most one burst per motifn = 16, 3 birds (singing)
  3. HVC(X) · HVC(i)Area X projectors burst 0–5 times; interneurons fire denselyn = 30 · n = 31
  4. RAMotor nucleus: many bursts per motif, driven from HVC→ vocal and respiratory motor neurons

What is from the paper and what is assumed. Burst statistics, timing jitter, sleep firing rates, correlation values and every equation come from the paper’s text and Methods, and are checked against it below. The song is synthetic (no recording could be used here). Interneuron rates during song, the HVC→RA weights and the synaptic kernel are illustrative; sections that use them carry an illustration tag.

Fig. 2 · singing bird

Ten neurons, ten renditions, one burst each

Each row is one rendition of the motif and each block is one neuron. HVC(RA) neurons fire a brief burst at a single moment, and do so on every rendition with sub-millisecond jitter. Interneurons fire throughout the song. Press play to hear the motif and follow the cursor.

Measured with the paper’s burst criterion

The generator is set from the paper’s means and s.d.; the bursts are then detected with the paper’s R(t) > 100 Hz rule and measured. With only ten neurons, sample means vary from draw to draw; press New neurons to see the spread.

Synthetic motif · spectrogram 0–10 kHz
Spike rasters aligned to the motifHVC(RA)HVC(X)HVC interneuron
Discussion · a code for time

Sort the neurons and a clock appears

Different HVC(RA) neurons burst at different times, “with no obvious timing relation to the onset or offset of song syllables”. Ordered by burst time, the population tiles the motif. At every moment a different small group is active: a code for time in the song, not for syllables.

Computed

Motif
One rendition, one row per neuronburstsyllable boundaries
Fraction of the motif covered by at least one burst1 − exp(−N·d/T)this population
Discussion · the score is in the synapses illustration

A sparse clock makes learning local

The paper proposes that the canonical sequence in HVC “is translated into a complex sequence in RA by a set of synaptic weights”. Here each RA neuron sums delayed, weighted HVC(RA) bursts. Click the RA trace to correct an “error” at that moment by weakening the synapses active just before it. With the sparse code only that moment changes. With a dense code, where every HVC neuron bursts many times, the same correction spreads across the song.

Effect of one local correction

HVC(RA) bursts (sorted) · highlighted: synapses weakened
Three RA neurons, instantaneous firing rate R(t) (click to place the correction)beforeafterchanged
Fig. 3 · sleeping bird

During sleep, HVC still drives RA

In the head-fixed sleeping bird, HVC(RA) neurons still burst sparsely and RA neurons fire bursts locked to them, before and after. The paper quantifies this with a conditional correlation K(τ) and a shuffle test, both implemented here exactly as in its Methods. Lidocaine in HVC abolished RA sleep bursts, leaving RA’s 10–20 Hz regular spiking.

Comparison with the paper

20 s of the paired recordingHVC(RA)RA
RA spikes aligned on each HVC(RA) burst (±400 ms)
Conditional correlation K(τ), Δt = 5 msK(τ)95% level (shuffles)largest significant peak
Putting it together

A time code in HVC plays a score written in RA

“The motor actions underlying song unfold when the ‘time code’ in HVC acts on the ‘muscle map’ in RA.” Here are all the pieces running together: the song, the HVC clock, and RA reading it out.

  1. CLOCK · HVC(RA)One moment each

    Each neuron bursts once per motif (6.1 ms, 4.5 spikes, 0.66 ms jitter). Together they mark every moment of the song.

    See the clock ↑
  2. SCORE · HVC→RA SYNAPSESWeights hold the song

    Which RA neurons fire at each moment depends on the synapses from the HVC neurons active then.

    See the readout ↑
  3. MUSCLE MAP · RAMany bursts each

    RA neurons burst about 13 times as often as HVC(RA) neurons and project to vocal and respiratory motor neurons.

    See RA ↑
  4. CAUSALITY · SLEEPHVC drives RA

    RA bursts follow interneuron bursts by about 4.5 ms and vanish when HVC is silenced. About 70% of RA sleep bursts are HVC-driven.

    See sleep ↑

The whole circuit, one motif

Measured in the paper

  • HVC(RA): at most one burst per motif; silent in awake, non-singing birds (< 0.001 spikes/s)
  • Bursts of 6.1 ± 2 ms, 4.5 ± 2 spikes, 613 ± 210 s⁻¹, jitter 0.66 ± 0.14 ms
  • Sleep: 0.06 ± 0.05 bursts/s; RA bursts 13 ± 3 times more often
  • RA–HVC(RA) peak K = 0.62; peaks within ±400 ms
  • Lidocaine in HVC abolishes RA sleep bursts; about 70% feed-forward contribution

Proposed, then tested later

  • HVC(RA) bursts form an explicit representation of time
  • The song’s “score” lies in HVC(RA)→RA synapses, a likely site of learning
  • Sparse coding avoids temporal interference, so errors can be fixed at one moment
  • How the sequence propagates within HVC was left open here. Later work tested a chain mechanism (Long & Fee 2008; Long, Jin & Fee 2010).
Methods

Equations, numbers and assumptions

Analysis (paper’s Methods)

R(t) = 1 / (ti+1 − ti),  ti < t ≤ ti+1instantaneous rate
burst: interval where R(t) > 100 Hzburst criterion
c(τ) = (1/NA) Σi Θ[Δt − minj |tAi − tBj − τ|]conditional spike probability
K(τ) = (c(τ) − c̄) / (1 − c̄),  c̄ ≤ 0.5conditional correlation
Δt = 5 ms;  τ ∈ [−1, 1] s;  A = train with fewer spikes
shuffle: 500 ms windows, cyclic shift ∈ [0, 500) ms, 300 shuffles, 95% of peak values
feed-forward fraction ≈ KRA–HVC(i) / KHVC(RA)–HVC(i) = 0.51 / 0.73

Θ is the Heaviside step. τ > 0 means the RA neuron follows the HVC(RA) neuron. c̄ is the mean of c(τ) over shuffled trains.

Numbers from the paper used to generate spikes

QuantityValueState
HVC(RA) bursts per motif≤ 1singing
HVC(RA) burst duration6.1 ± 2 mssinging
Spikes per burst4.5 ± 2singing
Intraburst rate613 ± 210 s⁻¹singing
Burst jitter (r.m.s.)0.66 ± 0.14 mssinging
HVC(X) bursts per motif0–5singing
Interneuron spontaneous rate11 ± 7 s⁻¹awake, not singing
HVC(RA) burst rate0.06 ± 0.05 s⁻¹sleep
RA : HVC(RA) burst ratio13 ± 3sleep
HVC(RA) sleep burst6.5 ± 1.8 ms · 3.2 ± 0.8 spikes · 347 ± 81 s⁻¹sleep
RA sleep burst duration11.5 ± 3.5 mssleep
RA regular spiking10–20 Hzsleep
Motif lengthabout 1 s(synthetic: 0.9 s)

Assumptions made here

  • Song: a synthetic 0.9 s motif of eight syllables (harmonic stacks, sweeps, noisy notes) at 22.05 kHz. It is a stand-in, not a recording.
  • HVC(RA) generator: burst time uniform over the motif. Spikes per burst ~ N(4.5, 2), clipped to 2–10, and burst duration ~ N(6.1, 2) ms; the intraburst rate is not set directly but follows from these two, and is measured. Burst onset jitter ~ N(0, σ). In sleep: N(3.2, 0.8) spikes over N(6.5, 1.8) ms.
  • Interneurons during song: an inhomogeneous Poisson process of 60–260 s⁻¹. The paper reports only “high rates of spiking and bursting”.
  • HVC→RA readout: 600 HVC(RA) neurons, 25% connectivity, exponential weights, a 3.5 ms delay (the mean antidromic latency) and a 5 ms exponential synaptic kernel. Each RA threshold is set to give about 13 bursts per motif.
  • Sleep: replay events at 0.14 s⁻¹, each replaying a random 0.2–0.7 s stretch of the motif. Within a replay, the HVC(RA) burst occurs with probability 0.85 and each RA sequence burst with probability 0.6, both with 2 ms jitter. RA has 18 sequence times per motif on top of 15 Hz regular spiking. These values were chosen so that the burst rate, the RA : HVC(RA) ratio and the peak correlation land near the paper’s averages. They are fitted, not predicted.

What this leaves out

  • No spiking mechanism inside HVC: the clock is imposed, not generated. Option (b) of this series would add a chain model.
  • No syrinx or respiratory model: RA activity is not turned into sound.
  • Calls, repeated syllables and HVC(RA) neurons silent during song (3 in the paper) are not simulated.
  • The HVC(RA) neurons’ burst times in the sleep model are fixed by construction, so the shuffle test checks the analysis, not the biology.