Neural Cognitive Modelling: A Biologically Constrained Spiking Neuron Model of the Tower of Hanoi Task
Why this work is in the frame
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Bibliographic record
Abstract
We present a computational model capable of solving arbitrary Tower of Hanoi problems.All elements except visual input and motor output are implemented using 150,000 LIF spiking neurons.Properties of these neurons (firing rate, post-synaptic time constant, etc.) are set based on the neurons in corresponding areas of the brain, and connectivity is similarly constrained.Cortical components are all generalpurpose modules (for storing state information and for storing and retrieving short-term memories of previous state information), and could be used for other tasks.The only task-specific components are particular synaptic connection weights from cortex to basal ganglia and from thalamus to cortex, which implement 19 context-specific rules.The model has a single free parameter (the synaptic connection weights of the input to short-term memory), and produces timing behaviour similar to that of human participants.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it