Cognitive Architecture: Learning, Memory, and Development
Examine the computational, systemic, and neurocognitive mechanisms underpinning how minds acquire, store, and restructure knowledge. Move beyond introductory models into modern theories of prediction errors, trace consolidation, and developmental dynamics.
Like Duolingo, but for Cognitive Architecture: Learning, Memory, and Development. Tomo turns the whole topic into a game you play five minutes a day, until it actually sticks.
21 levels across 3 sections, about 42 minutes end to end, roughly 8 days at five minutes a day. It moves through Updating Predictive Models: Learning and Credit Assignment; Memory Dynamics: Storage, Consolidation, and Retrieval; and Developmental Trajectories and Representational Change.
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Key ideas in Cognitive Architecture: Learning, Memory, and Development
- Contiguity without surprise fails to drive further synaptic or associative weight modification
- When cumulative predictive value matches actual reward magnitude, prediction error falls to zero regardless of high temporal contiguity
- Associative change is governed by delta-V proportional to (lambda - sum of V), where lambda equals asymptotic unconditioned stimulus value
- In blocking, an existing conditioned stimulus claims all available associative weight, preventing an added novel stimulus from generating prediction error
- In overshadowing, simultaneously presented cues compete for a finite associative asymptote weighted by physical salience
- Conditioned inhibition requires negative prediction error when an expected reinforcer is omitted in the presence of an inhibitory cue
- Phasic dopamine initially fires as a positive prediction error at unexpected unconditioned stimulus delivery
- As learning proceeds, dopamine firing transfers back to the earliest reliable predictor (conditioned stimulus) while firing at anticipated reward arrival returns to tonic baseline
- When an expected outcome is withheld at the anticipated time, dopamine neurons exhibit a phasic pause below baseline firing
- Extinction creates an inhibitory latent cause or context-dependent safety association rather than unlearning the original synaptic memory trace
- Discrepancies in context, time delay (spontaneous recovery), or unsignaled shock (reinstatement) trigger the brain to infer that the original acquisition latent cause is active again
- Latent cause inference models explain renewal and recovery as state-splitting rather than trace degradation
- Backward blocking trains compound AB+ followed by A+ alone, which retrospectively reduces the associative strength of cue B without B ever being presented in the second phase
- Unshadowing or recovery from overshadowing extinguishes cue A alone (A-) after compound training (AB+), retrospectively elevating responding to cue B
- Classic real-time Rescorla-Wagner rules cannot account for retrospective revaluation because cues with zero activation cannot update weights, requiring modified models (e.g., Van Hamme-Wasserman or Dickinson-Burke)
- Transitional probability drops sharply across word boundaries compared to within-word syllable transitions
You've tried the other tabs
Thirty open tabs. Four facts you actually kept.
You watched. You nodded. By Sunday it was gone.
One answer, then back to scrolling.
Eight weeks. You meant to finish. You didn't.
Tomo gives Cognitive Architecture: Learning, Memory, and Development the Duolingo treatment: levels, streaks, and quick quizzes that test what you just learned. That game loop is what the tabs above never had, so it's the one you actually finish.
Here's what playing it feels like
A real question from this course. Take your best guess.
A tone has preceded a sugar drop 100 times, and responding has plateaued. On trial 101, the tone plays and the exact same sugar drop arrives. Why does learning pause here?
Get it right to open this lesson and 20 more in the app.
Where Cognitive Architecture: Learning, Memory, and Development takes you
- 1
Updating Predictive Models: Learning and Credit Assignment
- Prediction Error and Associative Computation
- Statistical Regularities and Structural Learning
- 2
Memory Dynamics: Storage, Consolidation, and Retrieval
- Working Memory and Attentional Gating
- Trace Transformation and System Consolidation
- Episodic Reconstruction and Metamemory
- 3
Developmental Trajectories and Representational Change
- Dynamic Systems and Probabilistic Epigenesis
- Social Cognition, Scaffolding, and Representational Drift
3 sections · 7 units · 21 levels. Built to play, not to enroll.
You pick the voice
Cognitive Architecture: Learning, Memory, and Development is taught in the The Bestie style: your friend who just gets it. Want a different feel? In the app you can spin up the same topic in any of Tomo's teaching styles. Same facts, totally different vibe.
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