Networks and neural computation¶

Curriculum status

These entries are architecture specifications, not final lesson plans. They define teaching intent, logistics, outputs and scientific boundaries; release-ready settings, worksheets, notebooks and answer keys still require empirical validation.

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Family source cluster: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]

NET-01 — Feedforward excitation¶

Concept / theme	A presynaptic board can drive a downstream board through a positive synaptic connection.
Audience / context	School to undergraduate. Formal practical, workshop or modular course. Prior modules: SYN-01, EPH-03.
Logistics	45 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board circuit. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 2 — Direct board + GUI

Learning outcomes.

Identify and predict the principal behaviour described in a presynaptic board can drive a downstream board through a positive synaptic connection.
Configure or document wire axon output to downstream synapse and vary gain/input and record pre/post Vm, spike transfer, delay.
Measure, calculate or compare wire axon output to downstream synapse and vary gain/input using an explicit operational rule.
Interpret the result and state why connection represents functional event transmission, not a complete chemical synapse

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Wire axon output to downstream synapse and vary gain/input.

4. Acquire or inspect pre/post Vm, spike transfer, delay.

5. Produce network diagram and transfer-function trace.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: Connection represents functional event transmission, not a complete chemical synapse.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate wire axon output to downstream synapse and vary gain/input. The reusable output is network diagram and transfer-function trace.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: NET-02, NET-03. Development priority: Core module. Boundary: Connection represents functional event transmission, not a complete chemical synapse.

NET-02 — Feedforward inhibition¶

Concept / theme	An upstream board can suppress or delay a downstream response through negative gain.
Audience / context	Undergraduate. Formal practical, workshop or modular course. Prior modules: SYN-02, NET-01.
Logistics	60 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board experiment. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 3 — Hybrid board + Jupyter; 7 — Conceptual analogy

Learning outcomes.

Identify and predict the principal behaviour described in an upstream board can suppress or delay a downstream response through negative gain.
Configure or document add inhibitory pathway during a controlled downstream stimulus and record post spike count/latency with and without inhibition.
Measure, calculate or compare add inhibitory pathway during a controlled downstream stimulus using an explicit operational rule.
Interpret the result and state why no inhibitory transmitter or interneuron subtype is identified

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Add inhibitory pathway during a controlled downstream stimulus.

4. Acquire or inspect post spike count/latency with and without inhibition.

5. Produce controlled inhibition comparison.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: No inhibitory transmitter or interneuron subtype is identified.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate add inhibitory pathway during a controlled downstream stimulus. The reusable output is controlled inhibition comparison.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: NET-04, NET-05. Development priority: High-priority extension. Boundary: No inhibitory transmitter or interneuron subtype is identified.

NET-03 — Recurrent excitation and persistence¶

Concept / theme	Positive feedback can amplify, prolong or destabilise activity.
Audience / context	Advanced undergraduate. Formal practical, workshop or modular course. Prior modules: NET-01, EPH-06.
Logistics	60 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board circuit. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 3 — Hybrid board + Jupyter; 7 — Conceptual analogy

Learning outcomes.

Identify and predict the principal behaviour described in positive feedback can amplify, prolong or destabilise activity.
Configure or document close a recurrent excitatory loop and vary gain while monitoring safety/limits and record activity duration, rate, saturation, recovery.
Measure, calculate or compare close a recurrent excitatory loop and vary gain while monitoring safety/limits using an explicit operational rule.
Interpret the result and state why electronic loop delays and clipping can dominate; do not equate persistence with biological working memory without qualification

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Close a recurrent excitatory loop and vary gain while monitoring safety/limits.

4. Acquire or inspect activity duration, rate, saturation, recovery.

5. Produce regime map with stable/unstable regions.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: Electronic loop delays and clipping can dominate; do not equate persistence with biological working memory without qualification.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate close a recurrent excitatory loop and vary gain while monitoring safety/limits. The reusable output is regime map with stable/unstable regions.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: NET-06, EPI-02. Development priority: Advanced specialised module. Boundary: Electronic loop delays and clipping can dominate; do not equate persistence with biological working memory without qualification.

NET-04 — Reciprocal and lateral inhibition¶

Concept / theme	Mutual inhibition can produce competition, alternation or winner-take-all-like behaviour.
Audience / context	Advanced undergraduate to master’s. Formal practical, workshop or modular course. Prior modules: NET-02, SYN-04.
Logistics	60 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board experiment. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 3 — Hybrid board + Jupyter; 7 — Conceptual analogy

Learning outcomes.

Identify and predict the principal behaviour described in mutual inhibition can produce competition, alternation or winner-take-all-like behaviour.
Configure or document cross-connect two boards with negative gains and asymmetric drive and record winner identity, switching, rate difference.
Measure, calculate or compare cross-connect two boards with negative gains and asymmetric drive using an explicit operational rule.
Interpret the result and state why small deterministic circuit is an analogy to circuit motifs, not a cortical lateral-inhibition preparation

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Cross-connect two boards with negative gains and asymmetric drive.

4. Acquire or inspect winner identity, switching, rate difference.

5. Produce competition phase diagram.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: Small deterministic circuit is an analogy to circuit motifs, not a cortical lateral-inhibition preparation.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate cross-connect two boards with negative gains and asymmetric drive. The reusable output is competition phase diagram.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: NET-05, NET-06. Development priority: High-priority extension. Boundary: Small deterministic circuit is an analogy to circuit motifs, not a cortical lateral-inhibition preparation.

NET-05 — Disinhibition¶

Concept / theme	Inhibiting an inhibitory pathway can release a downstream unit from suppression.
Audience / context	Master’s/intensive workshop. Formal practical, workshop or modular course. Prior modules: NET-02, NET-04, MET-03.
Logistics	60 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board circuit. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 3 — Hybrid board + Jupyter; 7 — Conceptual analogy

Learning outcomes.

Identify and predict the principal behaviour described in inhibiting an inhibitory pathway can release a downstream unit from suppression.
Configure or document construct a three-board motif and compare control, inhibition and disinhibition conditions and record downstream response across three conditions.
Measure, calculate or compare construct a three-board motif and compare control, inhibition and disinhibition conditions using an explicit operational rule.
Interpret the result and state why requires careful sign and baseline control; functional disinhibition does not identify biological pathways

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Construct a three-board motif and compare control, inhibition and disinhibition conditions.

4. Acquire or inspect downstream response across three conditions.

5. Produce logic/motif table and causal intervention diagram.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: Requires careful sign and baseline control; functional disinhibition does not identify biological pathways.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate construct a three-board motif and compare control, inhibition and disinhibition conditions. The reusable output is logic/motif table and causal intervention diagram.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: NET-07, EPI-03. Development priority: Advanced specialised module. Boundary: Requires careful sign and baseline control; functional disinhibition does not identify biological pathways.

NET-06 — Oscillation, central-pattern-generation analogy and synchrony¶

Concept / theme	Reciprocal or delayed loops can generate rhythmic activity whose frequency and phase can be measured.
Audience / context	Advanced undergraduate to master’s. Formal practical, workshop or modular course. Prior modules: NET-03 or NET-04, EPH-04.
Logistics	60 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board + Jupyter. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 3 — Hybrid board + Jupyter; 8 — External computational comparison

Learning outcomes.

Identify and predict the principal behaviour described in reciprocal or delayed loops can generate rhythmic activity whose frequency and phase can be measured.
Configure or document build an oscillatory two- or three-board loop and vary gains/input and record period, phase difference, regularity.
Measure, calculate or compare build an oscillatory two- or three-board loop and vary gains/input using an explicit operational rule.
Interpret the result and state why timing, latency and saturation require validation; cpg terminology is analogical

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Build an oscillatory two- or three-board loop and vary gains/input.

4. Acquire or inspect period, phase difference, regularity.

5. Produce oscillation trace, phase plot and stability note.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: Timing, latency and saturation require validation; CPG terminology is analogical.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate build an oscillatory two- or three-board loop and vary gains/input. The reusable output is oscillation trace, phase plot and stability note.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: DAT-07, CMP-08. Development priority: Advanced specialised module. Boundary: Timing, latency and saturation require validation; CPG terminology is analogical.

NET-07 — Neural logic and temporal computation¶

Concept / theme	Signed connections and timing can implement AND-, OR-, NOT-like and coincidence operations.
Audience / context	School to master’s. Formal practical, workshop or modular course. Prior modules: SYN-04, SYN-05.
Logistics	60 min; 4–8; boards: 2–4; software: Multi-recording GUI or multiple laptops; prepared dataset: Generated; exemplar traces useful. Equipment: Standard USB cable; worksheet/protocol card.
Mode / stages	Multi-board challenge. Stages: 3–10, 11.
Spikeling relationship	4 — Multi-board implementation; 3 — Hybrid board + Jupyter; 7 — Conceptual analogy

Learning outcomes.

Identify and predict the principal behaviour described in signed connections and timing can implement and-, or-, not-like and coincidence operations.
Configure or document configure two-input motifs and test a truth table plus timing variants and record binary outputs, latency, error cases.
Measure, calculate or compare configure two-input motifs and test a truth table plus timing variants using an explicit operational rule.
Interpret the result and state why neural computation is graded and temporal; boolean labels are simplified operational descriptions

Roadmap.

1. Initial prediction or classification.

2. Configure the board, GUI, simulation or dataset and record metadata.

3. Configure two-input motifs and test a truth table plus timing variants.

4. Acquire or inspect binary outputs, latency, error cases.

5. Produce truth table, timing diagram and limits critique.

6. Compare conditions or models and justify the chosen measurement.

7. Answer a limitation question: Neural computation is graded and temporal; Boolean labels are simplified operational descriptions.

Inputs → outputs. Students receive a configuration/protocol prompt, variable definitions and any required starter data. They manipulate configure two-input motifs and test a truth table plus timing variants. The reusable output is truth table, timing diagram and limits critique.

Sources / connections / priority. Sources: [T1 Ch.10; T5 Chs.7–8; T6 Parts III–IV; O1; G1, G3]. Natural follow-ons: OSC-02, CMP-09. Development priority: High-priority extension. Boundary: Neural computation is graded and temporal; Boolean labels are simplified operational descriptions.