{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp04_retrieval_first_paired20_20260802","cell_id":"negative_space_design__neuroscience","arm":"PROPOSAL_FIRST","candidate_id":"negative_space_design__neuroscience__protected_null_epochs","hypothesis_id":null,"version":0,"title":"Protected Null Epochs for Closed-Loop Neural Stimulation","problem":"A closed-loop experiment generator may schedule a new stimulus at nearly every eligible moment because each unused interval appears to be wasted capacity. When neural activity has not returned to a stable reference state, responses to successive stimuli overlap with adaptation, residual activation, or state transitions. The resulting record may not cleanly distinguish a stimulus-evoked response from carryover caused by preceding trials.","actors":["Neuroscience principal investigator","Experiment designer","Experiment operator","Research participants or laboratory animals","Data analyst"],"observable_state":"The event log contains few deliberately unstimulated intervals; prestimulus activity depends on the preceding stimulus sequence; response magnitude or shape changes with short inter-event spacing; and intentional silence, equipment failure, and missing event data are not represented as distinct states.","consequence":"Estimated stimulus-response relationships can depend on scheduling history, weakening causal interpretation and making replication or comparison across schedules difficult.","affected_objective":"Identify stimulus-evoked neural responses while preserving participant or animal safety, interpretable baseline measurements, and sufficient experimental coverage.","intervention":"Add bounded, explicitly coded null epochs to the stimulus generator. First map which scheduled events compete with recovery and baseline estimation, then omit selected low-priority events at genuine block or state boundaries. Protect each resulting interval from automatic backfilling. Keep acquisition, safety monitoring, synchronization, and contextual metadata active during the silence. Label whether an empty interval is intentional, recovery-triggered, operator-triggered, or caused by a fault. Resume stimulation only at a predeclared time or recovery criterion, subject to an approved maximum pause and operator override.","structural_mapping":[{"archetype_element":"Attention Competition Map","domain_realization":"A timeline analysis identifies stimuli whose residual responses overlap and shows where the generator competes with neural recovery and baseline observation."},{"archetype_element":"Omission Candidate","domain_realization":"A scheduled event becomes eligible for omission only if removing it preserves required condition coverage and safety checks."},{"archetype_element":"Protected Empty Space","domain_realization":"The generator reserves a null epoch during which optimization logic cannot insert replacement stimuli."},{"archetype_element":"Positive Form Relationship","domain_realization":"The unstimulated interval is tied to the following response estimate by providing a measurable reference state and separation from prior stimulation."},{"archetype_element":"Absence Boundary","domain_realization":"Start conditions, duration bounds, permissible monitoring, and the exact resumption rule are encoded in the protocol."},{"archetype_element":"Meaning-of-Absence Check","domain_realization":"Distinct event codes separate deliberate silence from loading delay, dropped commands, equipment failure, permission blocks, and session completion."},{"archetype_element":"Accessibility and Recoverability Guardrail","domain_realization":"All omitted event proposals remain in an audit log, while acquisition displays retain safety signals and an obvious manual resume or halt control."},{"archetype_element":"Clarity or Effect Test","domain_realization":"Analysts test whether activity immediately before post-gap stimuli is more stable and whether competing response models become more distinguishable."}],"mechanism_mapping":[{"mechanism_slug":"blank_or_rest_frame","role":"Places an unmistakably intentional quiet interval at a real experimental segment boundary and defines when stimulation returns.","counterfactual_removal":"Without this mechanism, the intervention becomes an arbitrary slowing of the schedule rather than a paced null epoch related to recovery and subsequent interpretation."},{"mechanism_slug":"editorial_cut","role":"Selects removable events by testing whether condition coverage and contextual meaning survive, while retaining every cut in a recoverable audit log.","counterfactual_removal":"Without this mechanism, gaps could be created by indiscriminate trial deletion, producing missing conditions or irrecoverable selection bias."},{"mechanism_slug":"empty_state_design","role":"Diagnoses and labels each no-stimulus interval so intentional recovery is not confused with a fault, missing data, completion, or blocked command.","counterfactual_removal":"Without this mechanism, operators and analysts cannot reliably interpret the absence and may wait during a failure or discard valid null-epoch data."}],"causal_chain":["A dense closed-loop schedule repeatedly stimulates before prior activity has demonstrably settled.","Residual activation and adaptation make prestimulus state depend on recent scheduling history.","The protocol omits selected events and protects the resulting null epochs from automatic backfilling.","Acquisition continues during each bounded silence, exposing recovery dynamics and an unstimulated reference interval.","Explicit state codes preserve the meaning of the absence, and a predeclared trigger restores stimulation.","Post-gap responses can then be compared with densely scheduled responses to test whether temporal carryover, rather than stimulus identity alone, explains the observed variation."],"baseline":"The ordinary baseline is a throughput-oriented generator that selects the next admissible stimulus as soon as timing and safety constraints permit, with either a short fixed inter-trial interval or no separately protected recovery state.","nearest_rivals":["Strongest rival: retain the dense schedule and use a model-based deconvolution or history-dependent response model to estimate and subtract overlapping activity.","Use a longer fixed inter-trial interval after every stimulus, regardless of observed state or segment boundary.","Reduce stimulus intensity or randomize trial order while leaving the available timeline filled."],"remaining_contrastive_claim":"The candidate differs from model correction by creating observable, protected no-stimulus intervals rather than inferring an unobserved baseline entirely from overlapping responses. Its testable contrast is whether these intervals improve held-out discrimination between stimulus effects and sequence-history effects enough to justify the lost event opportunities.","authority_safety":{"decision_authority":"The principal investigator controls the scientific schedule; the applicable ethics body and institutional safety authority must approve any live protocol change; the experiment operator retains immediate halt authority.","authorized_first_step":"Perform an offline analysis on one previously collected session: estimate recovery and serial-dependence timescales, simulate a small set of bounded null-epoch schedules, and predeclare comparison metrics. This step does not alter stimulation or expose a participant or animal to a new procedure.","excluded_actions":["No live stimulation change without required protocol and safety approval","No hiding of emergency controls, acquisition alarms, consent information, or welfare indicators","No automatic pause extension beyond the approved maximum","No deletion of omitted-event proposals or schedule-history logs","No increase in session duration merely to replace every omitted event without separate review"],"halt_rollback":"In any later approved pilot, halt on distress, safety-limit approach, synchronization loss, misclassified equipment failure, or excessive pause duration. The operator can restore the approved baseline schedule immediately; null-epoch logic remains disabled until its logs are reviewed."},"negative_tests":{"strongest_counterevidence":"A validated history-dependent model predicts held-out neural responses equally well across dense and spaced schedules, while null epochs only reduce condition coverage or lengthen sessions.","problem_falsifier":"The problem is unsupported if prestimulus activity is stable across recent stimulus histories and response estimates show no material dependence on inter-event spacing within the proposed operating range.","intervention_falsifier":"The intervention is unsupported if an approved randomized pilot shows that bounded null epochs do not improve preregistered baseline stability or stimulus-versus-history identifiability, or if any improvement disappears when equalizing trial count and elapsed time.","risks":["Fewer stimulated trials may reduce statistical precision.","Replacing omitted trials can lengthen sessions and increase fatigue or animal burden.","Recovery-triggered scheduling may preferentially sample particular neural states and create a new selection bias.","An intentional null epoch could be mistaken for equipment failure if state coding or displays fail.","A poorly chosen recovery signal could make the closed loop unstable or repeatedly suppress needed conditions.","Long silence may remove contextual continuity required to interpret the following response."]},"next_evidence_step":"On one existing session only, fit a response model with stimulus identity, recent history, and prestimulus-state terms; estimate where recovery plateaus; simulate no more than three null-epoch policies under the original safety and session-duration limits; and advance only if a preregistered held-out analysis predicts greater stimulus-versus-history identifiability without unacceptable loss of condition coverage.","prior_art_status":"UNSEARCHED","revision_record":{"parent_version":null,"progress_targets_addressed":[],"conceptual_changes":[],"operational_changes":[],"evidence_changes":[],"claim_changes":[]}}