| --- |
| license: cc-by-nc-4.0 |
| tags: |
| - pong |
| - spiking-neural-network |
| - connectome |
| - drosophila |
| - rsnn |
| --- |
| |
| # CentralComplex_Pong v1 |
| |
| Synaptic weights for the Pong game of **[BeatTheFly](https://phclab.github.io/BeatTheFly/pong/)** -- *A Smart Fruit Fly is playing Pong against you*: |
| a spiking network wired as the real *Drosophila* central complex connectome that moves a Pong paddle in real time. |
| |
| **The anatomical connectome gives you wiring, not synaptic strengths. Ours are trained.** |
| |
| Synaptic weights trained with PHCSSM parallel-scan mode, deployment in sequential RSNN mode ([PHCSSM](https://arxiv.org/abs/2604.01295)). |
| |
| made by Po-Han Chiang @ NYCU |
| |
| ## What the central complex does in the fly |
| The central complex is the fly's navigation and steering centre: it keeps track of heading and turns it into steering commands. Its plasticity gate is driven by 123 neuromodulatory cells — dopamine, serotonin and octopamine — over 793 real synapses, and what they write into the fast weight fades within about two frames. In the real fly, the central complex keeps track of heading with a ring-shaped “internal compass”, integrates the path travelled, and steers where the fly goes next. |
| |
| ## Architecture |
| * **Wiring:** MaleCNS v1.0 central complex -- 2,950 neurons (Ring neurons (ER, ExR) 308; PFN columnar neurons 456; PFL output neurons 50; Other central-complex neurons 2,136) and 439,500 |
| neuron-to-neuron connections. The connectivity mask is fixed to the connectome; 360,336 connections |
| carry a nonzero weight and 0 weights lie off the connectome. |
| * **Dale's law:** one sign per presynaptic neuron from predicted neurotransmitters (excitatory 1,873, |
| inhibitory 918, modulatory 159); 0 weights violate it. |
| * **Input:** each frame provides 6 numbers seen from the fly's side of the court: the ball's position and |
| velocity and the positions of both paddles. A linear encoder with LayerNorm drives only the input population: |
| 764 ER ring (landmark/visual) + PFN (self-motion via NO) + ExR. |
| * **Neurons:** leaky integrate-and-fire with per-neuron leak, threshold and reset; synaptic delay of one step. |
| * **Readout:** linear map from the membrane voltage of the output population only, 50 PFL1/2/3 (steering -> LAL), |
| to 3 paddle commands (stay, up, down). |
| * **Neuromodulatory gate:** 123 of this region's own known-neuromodulator cells (dopamine+octopamine+serotonin) gate the |
| current into the output population, masked to the 793 real gate-cell -> output synapses in the connectome. |
| * **Fast weight:** a value written onto the 1,556 real input -> output synapses, gated by the same cells, read |
| back into the output neurons' voltages. It is read with the current frame's input spikes and written with the same |
| frame's, and it decays: one trainable factor per output neuron, a decay time constant of about 1.80 frames (30.0 ms at 60 fps). |
| * **Deployment:** sequential RSNN mode, one timestep per frame at 60 frames per second, with the neuron state carried |
| across the whole game. |
| |
| ## Data sources |
| Data source: actions of a scripted Pong player. |
| |
| ## Evaluation |
| 20 games to 11 points against each scripted player, the fly playing its top command every frame: |
| |
| | opponent | games won | point share | fly's return rate | |
| |---|---|---|---| |
| | a noisy scripted player | 11 / 20 | 0.520 | 88.2% | |
| | a weak scripted player | 20 / 20 | 0.880 | 91.9% | |
| | a perfect scripted player | 0 / 20 | 0.000 | 91.7% | |
| |
| On 131,072 held-out frames the fly's choice matches the scripted player's action on 97.1% in sequential RSNN mode, and the parallel-scan and sequential modes choose the same action on 99.68% of frames. |
| |
| ## Files |
| * `manifest.json` -- every tensor (file, dtype, shape, bytes), the model scalars and a connectome audit. |
| * `info.json` -- neuron metadata used by the page (cell classes, hemispheres, soma coordinates). |
| * `selfcheck_<precision>.json` -- reference observations and logits that the page replays when it loads. |
| * `fp16/`, `fp32/` -- raw little-endian arrays. |
|
|
| Two precisions are listed in the manifest: `fp16w32` (default, 2.4 MB: float16 for the |
| readout matrix `dec_w`, float32 for the recurrent weights and all other tensors) and |
| `fp16` (1.7 MB, recurrent weights in float16 as well). |
|
|
| The recurrent weight matrix W[dst, src] is stored in CSC order by source neuron (`W_colptr`, `W_rowidx`, `W_vals`): |
| each step multiplies W by a sparse binary spike vector, so the engine visits only the columns of the neurons that |
| spiked. `in_idx` lists the input population and `out_idx` the output population. `enc_obs_T` [6, H] is the |
| observation encoder and `dec_w` [3, 50] is read against the output population's voltage. |
|
|
| | name | file | dtype | shape | |
| |---|---|---|---| |
| | `enc_obs_T` | `fp32/enc_obs_T.bin` | float32 | 6x2950 | |
| | `enc_obs_b` | `fp32/enc_obs_b.bin` | float32 | 2950 | |
| | `ln_obs_w` | `fp32/ln_obs_w.bin` | float32 | 2950 | |
| | `ln_obs_b` | `fp32/ln_obs_b.bin` | float32 | 2950 | |
| | `teach_T` | `fp32/teach_T.bin` | float32 | 6x123 | |
| | `teach_b` | `fp32/teach_b.bin` | float32 | 123 | |
| | `W_gate` | `fp32/W_gate.bin` | float32 | 50x123 | |
| | `W_val` | `fp32/W_val.bin` | float32 | 50x123 | |
| | `gate_idx` | `fp32/gate_idx.bin` | int32 | 123 | |
| | `fw_in` | `fp32/fw_in.bin` | int32 | 1556 | |
| | `fw_out` | `fp32/fw_out.bin` | int32 | 1556 | |
| | `gamma` | `fp32/gamma.bin` | float32 | 50 | |
| | `dec_w` | `fp16/dec_w.bin` | float16 | 3x50 | |
| | `dec_b` | `fp32/dec_b.bin` | float32 | 3 | |
| | `alpha_exc` | `fp32/alpha_exc.bin` | float32 | 2950 | |
| | `alpha_inh` | `fp32/alpha_inh.bin` | float32 | 2950 | |
| | `v_th` | `fp32/v_th.bin` | float32 | 2950 | |
| | `reset_weight` | `fp32/reset_weight.bin` | float32 | 2950 | |
| | `in_idx` | `fp32/in_idx.bin` | int32 | 764 | |
| | `out_idx` | `fp32/out_idx.bin` | int32 | 50 | |
| | `W_colptr` | `fp32/W_colptr.bin` | uint32 | 2951 | |
| | `W_rowidx` | `fp32/W_rowidx.bin` | uint16 | 360336 | |
| | `W_vals` | `fp32/W_vals.bin` | float32 | 360336 | |
|
|
| **Numerical check:** 0 of 27,281,600 spike bits differ from the reference on the same weights (2,048 held-out frames and a 7,200-frame closed-loop game). |
|
|
| ## Limitations |
| The fly learned by copying a scripted player: it gets no reward and does not plan ahead. It has been tested only in |
| this simulator and only against scripted players, and it loses every game to a perfect one. |
|
|
| ## License and attribution |
| Weights: [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/). They are derived from the MaleCNS v1.0 connectome (Janelia FlyEM and |
| collaborators, https://male-cns.janelia.org/, [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) and trained with PHCSSM (https://arxiv.org/abs/2604.01295); |
| please credit both. |
|
|
| ## Citation |
| PHCSSM: https://arxiv.org/abs/2604.01295 |
|
|
