{"schema_version":1,"research_id":"eoa_inverse_innovation_exp04_external_evaluation_20260802","source_assessment_id":"negative_space_design__neuroscience:PROPOSAL_FIRST:v0","cell_id":"negative_space_design__neuroscience","search_queries":["closed-loop neural stimulation adaptive inter stimulus interval carryover recovery baseline null trials","DBS washout period crossover trial stimulation carryover","event related fMRI null events jitter stochastic design Friston","FDA investigational device exemption neurological stimulation significant risk IRB","site:braininitiative.nih.gov closed-loop neuromodulation funding opportunity adaptive stimulation 2025","site:nih.gov funding opportunity closed loop neuromodulation recording stimulation BRAIN Initiative","Learning to Control the Brain through Adaptive Closed-Loop Patterned Stimulation PDF 2020","neural stimulation artifact refractory adaptation interstimulus interval evoked potential primary research","\"Influence of inter-stimulus interval on auditory evoked potentials\" PDF","\"Subcortical short-term plasticity elicited by deep brain stimulation\" full text","\"A Deep Brain Stimulation Trial Period for Treating Chronic Pain\" JCM","site:grants.nih.gov NOT-NS-24-080 coordinated neural stimulating recording"],"sources":[{"source_id":"S01","title":"Learning to Control the Brain through Adaptive Closed-Loop Patterned Stimulation","publisher":"Journal of Neural Engineering / IOP Publishing","url":"https://www.timbuschman.com/_files/ugd/568973_dda3daa9a6ea4ad8bd4b580f543adaab.pdf","source_class":"PRIMARY_RESEARCH","publication_date":"2020-10-13","accessed_at":"2026-08-02","claims_supported":["Adaptive closed-loop stimulation was implemented in vivo with real-time recording and stimulation.","The learned electrical-stimulation response was affected by preceding visual stimulation, directly demonstrating adaptation and history dependence.","The implementation shows that closed-loop schedule and response logic can be added to an operational stimulation system."]},{"source_id":"S02","title":"Influence of Inter-Stimulus Interval on Auditory Evoked Potentials","publisher":"IEEE Engineering in Medicine and Biology Society / PubMed","url":"https://pubmed.ncbi.nlm.nih.gov/17282637/","source_class":"PRIMARY_RESEARCH","publication_date":"2005","accessed_at":"2026-08-02","claims_supported":["In paired-stimulus human recordings, the succeeding auditory evoked potential was completely inhibited when the inter-stimulus interval was shorter than 150 milliseconds.","Neural response magnitude can depend materially on the timing of the preceding stimulus."]},{"source_id":"S03","title":"Stochastic Designs in Event-Related fMRI","publisher":"NeuroImage / Academic Press","url":"https://web.mit.edu/swg/ImagingPubs/experimental-design/friston_stochastic.1999.pdf","source_class":"PRIMARY_RESEARCH","publication_date":"1999-11","accessed_at":"2026-08-02","claims_supported":["Trial-free periods permitting baseline attainment were already formalized as null events in rapid event-related neuroscience experiments.","Null events can improve estimation of evoked responses relative to continuously filled schedules.","Design efficiency depends on the target contrast, so adding null events trades event opportunities against response identifiability."]},{"source_id":"S04","title":"A Deep Brain Stimulation Trial Period for Treating Chronic Pain","publisher":"Journal of Clinical Medicine / University of California eScholarship","url":"https://escholarship.org/content/qt136119hb/qt136119hb.pdf?t=qzpyob","source_class":"AUTHORITATIVE_SECONDARY","publication_date":"2020-09-29","accessed_at":"2026-08-02","claims_supported":["DBS trial methodology already treats wash-in and wash-out periods as functions of expected stimulation effects.","Adaptive DBS development creates demand for neurophysiological recording and rigorous stimulation-effect testing.","Longer observation and wash-out periods improve confidence but impose time, cost, infection, and participant-burden tradeoffs."]},{"source_id":"S05","title":"Subcortical Short-Term Plasticity Elicited by Deep Brain Stimulation","publisher":"Annals of Clinical and Translational Neurology / PubMed Central","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC8108424/","source_class":"PRIMARY_RESEARCH","publication_date":"2021-05-04","accessed_at":"2026-08-02","claims_supported":["Human DBS-evoked field-potential amplitude, area, and latency changed significantly with interstimulus interval.","The study observed absolute and relative refractory periods and stimulation-history-dependent facilitation.","The analysis used artifact removal and template subtraction, illustrating the strongest model-correction rival to deliberate spacing."]},{"source_id":"S06","title":"Neural Recording and Modulation","publisher":"NIH BRAIN Initiative","url":"https://www.braininitiative.nih.gov/research/neural-recording-and-modulation","source_class":"OFFICIAL_ORGANIZATION_DATA","publication_date":"not stated","accessed_at":"2026-08-02","claims_supported":["NIH BRAIN explicitly supports development and optimization of technologies for neural recording and modulation.","The program identifies electrical recording, manipulation, adaptive instrumentation, and signal processing as fundable capabilities.","NIH BRAIN, NINDS, and NIMH are identifiable potential funders, although the page does not express demand specifically for protected null epochs."]},{"source_id":"S07","title":"IDE Approval Process","publisher":"U.S. Food and Drug Administration","url":"https://www.fda.gov/medical-devices/investigational-device-exemption-ide/ide-approval-process","source_class":"GOVERNMENT_OR_REGULATOR","publication_date":"not stated","accessed_at":"2026-08-02","claims_supported":["A significant-risk device study requires FDA and IRB approval before initiation.","Investigational-device studies require informed consent, monitoring, records, reports, and compliance with the approved protocol.","An offline analysis of previously collected data avoids changing live stimulation, while a later human pilot may require an amended investigational plan and regulatory review."]},{"source_id":"S08","title":"Center for Research Informatics Price Guide, FY26","publisher":"University of Chicago Center for Research Informatics","url":"https://cri.uchicago.edu/wp-content/uploads/2025/07/CRI-BIO.Recharge_Rates.FY26.pdf","source_class":"OFFICIAL_ORGANIZATION_DATA","publication_date":"2025-07-01","accessed_at":"2026-08-02","claims_supported":["FY26 internal research-informatics rates include $160 per hour for bioinformatics analysis and application development.","External academic or commercial application-development and data-warehousing rates are approximately $246–$338 per hour.","The listed services include application development, data warehousing, de-identification, IRB-writing assistance, storage, and project support."]}],"problem_evidence":{"support":"STRONG","rationale":"Multiple human and animal studies directly show that neural responses depend on preceding stimulation and interstimulus timing. Established event-related fMRI methodology uses null events to recover baseline information, while DBS studies document refractory, facilitation, wash-in, and wash-out effects. These findings validate the mechanism and potential consequence, but public evidence does not quantify how often modern closed-loop generators actually overfill eligible intervals or how much inferential error this causes in practice.","source_ids":["S01","S02","S03","S04","S05"]},"stakeholder_evidence":{"support":"MODERATE","rationale":"Neuroscience principal investigators are identifiable schedule owners, with IRBs, institutional safety bodies, and sometimes FDA serving as authorizers. NIH BRAIN is an identifiable funder that expressly supports neural recording, modulation, and signal-processing technologies. Adaptive-DBS researchers also express a need for rigorous neurophysiological observation and stimulation-effect testing. No source establishes a named laboratory's commitment to adopt this particular null-epoch implementation.","source_ids":["S04","S06","S07"]},"prior_art":{"proximity":"ADJACENT_PRIOR_ART","closest_analogues":[{"name":"Null events in stochastic event-related fMRI","similarity":"Deliberately includes no-event periods as a modeled condition so evoked responses can be estimated against a baseline without uniformly lengthening every interval.","remaining_difference":"The published method is an experimental-design practice for fMRI, not recovery-triggered, explicitly state-coded, protected silence inside a closed-loop neural-stimulation generator.","source_ids":["S03"]},{"name":"DBS wash-in and wash-out scheduling","similarity":"Uses bounded periods without a stimulation-condition change to reduce carryover and distinguish effects across conditions.","remaining_difference":"Washout is generally fixed and condition-level; the candidate proposes event-level null epochs selected by schedule or recovery state, protected against automatic backfilling, and evaluated against history models.","source_ids":["S04"]},{"name":"History-dependent modeling and template subtraction","similarity":"Models or removes activity attributable to preceding stimulation so a subsequent response can be estimated.","remaining_difference":"This rival infers or subtracts carryover from overlapping observations, whereas the candidate creates observed unstimulated intervals and retains the model as a comparator.","source_ids":["S05"]},{"name":"Adaptive closed-loop patterned stimulation","similarity":"Provides a working real-time record-stimulate-update architecture and directly encounters adaptation caused by preceding input.","remaining_difference":"The demonstrated controller optimizes stimulation patterns; it does not describe protected, semantically coded null epochs selected to improve stimulus-versus-history identifiability.","source_ids":["S01"]}],"distinctive_claim_remaining":"Against a dense schedule analyzed with a history-dependent model, a uniformly longer fixed interval, and randomized trial omission, recovery-bounded and explicitly coded null epochs will improve held-out discrimination of stimulus identity effects from sequence-history effects, after equalizing elapsed time and stimulated-trial count, enough to outweigh lost condition coverage.","confidence":"MODERATE"},"implementation_evidence":{"support":"MODERATE","rationale":"Real-time closed-loop recording and stimulation, event-related null conditions, recovery-sensitive response analysis, and audit-capable research software are all technically established. An offline simulation on existing data is straightforward. The combined policy—recovery estimation, omission eligibility, protected scheduling state, fault-versus-intent codes, operator override, and preregistered identifiability analysis—has not been directly demonstrated. Live human use remains protocol-, device-, IRB-, and potentially FDA-dependent, and modality-specific safety consequences cannot be inferred from web evidence alone.","source_ids":["S01","S03","S04","S05","S07","S08"]},"scores":{"meaningful_impact":{"score":4,"rationale":"If dense scheduling materially confounds stimulus effects with recent history, improved identifiability would strengthen causal interpretation and replication; prevalence and realized effect size remain unknown.","source_ids":["S01","S02","S03","S05"]},"stakeholder_pull":{"score":3,"rationale":"NIH and adaptive-DBS researchers visibly support better recording, modulation, and stimulation-effect characterization, but no adopter has requested this exact intervention.","source_ids":["S04","S06"]},"incremental_advantage":{"score":3,"rationale":"Observed recovery intervals could add information unavailable to purely model-based correction, but null events, washout periods, and history models are already credible alternatives.","source_ids":["S03","S04","S05"]},"distinctiveness_plausibility":{"score":2,"rationale":"The integrated state-coded, recovery-bounded scheduling rule is distinguishable, but its components are close to established null-event, washout, adaptive-control, and audit-log practices.","source_ids":["S01","S03","S04","S05"]},"technical_implementability":{"score":4,"rationale":"Offline simulation and a scheduling-state prototype are conventional software and analysis work; live integration and recovery-signal validation are the unresolved portions.","source_ids":["S01","S05","S08"]},"adoption_authority_feasibility":{"score":3,"rationale":"A PI can authorize offline work, but human live changes require institutional and potentially FDA authorization, and animal work requires the applicable animal-care approval.","source_ids":["S06","S07"]},"evidence_readiness":{"score":4,"rationale":"The claim can first be tested on one existing session with preregistered models and simulated schedules, although proprietary event-level data are required.","source_ids":["S01","S03","S05"]},"safety_net_benefit":{"score":3,"rationale":"Explicit pause-state codes, audit logs, maximum durations, and operator override could make silence safer to interpret, but incorrect recovery criteria or longer sessions could introduce burden or instability.","source_ids":["S04","S07"]},"scalability":{"score":4,"rationale":"A software scheduling state and event-code vocabulary could transfer across compatible experimental platforms, but recovery criteria and safety bounds must be validated separately for each modality and protocol.","source_ids":["S01","S03","S05"]}},"score_confidence":"MODERATE","costs":{"first_evidence":{"band_2026_usd":"UNDER_10K","scope":"One previously collected session; protocol specification; history-dependent response model; simulation of no more than three null-epoch policies; preregistered held-out comparison.","confidence":"MODERATE","assumptions":["Existing synchronized neural, stimulus, and safety logs are available without new acquisition.","Twenty to forty hours of analyst or research-software effort are sufficient.","No new device integration, participant contact, or regulatory submission is included."],"source_ids":["S08"]},"initial_deployment_startup":{"band_2026_usd":"10K_TO_50K","scope":"Research-grade scheduler module, explicit null/fault state codes, audit logging, replay tests, operator display changes, protocol documentation, and institutional review preparation.","confidence":"MODERATE","assumptions":["The existing controller exposes a supported scheduling interface.","Approximately 80–160 hours of engineering, analysis, quality-assurance, and protocol support are required.","No custom implant hardware or new acquisition equipment is purchased."],"source_ids":["S01","S07","S08"]},"operational_launch":{"band_2026_usd":"50K_TO_250K","scope":"Single-site, small approved pilot on an existing stimulation and recording platform, including integration validation, monitoring, operator training, analysis, and regulatory or ethics administration.","confidence":"LOW","assumptions":["Existing participants or animals, laboratory infrastructure, and stimulation hardware are available.","The pilot does not require a new implant procedure solely for this feature.","Clinical staffing, sponsor duties, insurance, and FDA requirements could move the cost outside this band.","Omitted trials are not automatically replaced by extending every session."],"source_ids":["S04","S07","S08"]},"annual_recurring":{"band_2026_usd":"10K_TO_50K","scope":"Software maintenance, storage, periodic validation, incident and audit-log review, analyst support, and retraining across several protocols at one site.","confidence":"LOW","assumptions":["One institution operates the feature on existing systems.","One-quarter to one-half FTE equivalent support plus modest secure storage is sufficient.","Costs of surgeries, devices, routine experimental sessions, and participant care are excluded."],"source_ids":["S08"]}},"verified_pipeline_gates":{"externally_supported_problem":{"status":"YES","reason":"Primary studies directly demonstrate stimulation-history, refractory, adaptation, and interstimulus-interval effects, while null-event methodology shows why unfilled intervals can aid baseline estimation.","source_ids":["S01","S02","S03","S05"]},"externally_credible_adopter_or_authorizer":{"status":"YES","reason":"The neuroscience PI is the immediate scientific schedule authority; IRBs and potentially FDA are identifiable live-study authorizers; NIH BRAIN is an identifiable funder of neural recording and modulation technologies. Commitment to this exact design is not established.","source_ids":["S06","S07"]},"distinct_testable_incremental_claim":{"status":"YES","reason":"The proposal can be compared directly with a dense history-modeled schedule, a longer fixed interval, and randomized omission using held-out identifiability, baseline stability, coverage, and elapsed-time metrics.","source_ids":["S03","S05"]},"bounded_next_evidence_step":{"status":"YES","reason":"A single existing session supports a no-contact offline analysis limited to three simulated policies and declared comparators and falsifiers.","source_ids":["S01","S03","S05","S08"]},"no_unresolved_safety_or_authority_stop":{"status":"YES","reason":"The immediate evidence step changes no live stimulation. Any subsequent pilot is explicitly stopped pending applicable PI, ethics, institutional-safety, and FDA determinations, with visible override and baseline rollback required.","source_ids":["S07"]},"credible_cost_scope_and_range":{"status":"YES","reason":"The four estimates state their included work and exclusions and are anchored to FY26 research-informatics rates; live-pilot estimates remain low-confidence because device, clinical, and regulatory circumstances are site-specific.","source_ids":["S04","S07","S08"]}},"next_evidence_step":"With one previously collected, fully synchronized session, preregister and fit a response model containing stimulus identity, recent stimulus history, elapsed time, and prestimulus-state terms. Estimate the recovery plateau without using held-out trials, then replay no more than three policies: a fixed null epoch, a recovery-threshold null epoch, and randomized omission matched for omitted-trial count. Compare each with (1) the original dense schedule plus the best history-dependent model and (2) a uniformly longer fixed inter-event interval. Evaluate held-out response error, stimulus-versus-history parameter identifiability, prestimulus-state stability, condition coverage, and simulated elapsed time. Falsify the intervention if the recovery policy fails to improve the preregistered held-out identifiability metric after matching trial count and elapsed time, if improvement is matched by randomized omission or model correction, if required-condition coverage falls below its prespecified floor, or if recovery estimates are too unstable to define bounded resumption. Do not proceed to live testing without separate protocol and safety authorization.","blocking_evidence":["No public study directly compares recovery-bounded protected null epochs with dense scheduling plus history-dependent modeling in a closed-loop neural-stimulation experiment.","The prevalence of throughput-oriented generators that leave too few deliberate null intervals is not quantified.","No named laboratory or principal investigator has committed data, engineering access, or adoption authority to this candidate.","Event-level proprietary data are needed to estimate recovery and simulate schedule counterfactuals.","The reliability and causal validity of a candidate recovery signal are unknown and likely modality-specific.","The effect of null epochs on condition coverage, session burden, fatigue, animal welfare, and closed-loop stability requires data or live validation.","The applicable IRB, animal-care, device-sponsor, institutional-safety, and FDA classifications depend on the eventual site, device, population, and protocol."],"research_disposition":"PARTNERED_RESEARCH_PROGRAM","world_novelty_boundary":"This evaluation establishes only that the proposal is adjacent to published null-event designs, DBS washout practices, adaptive closed-loop stimulation, and history-dependent response correction. It does not measure world novelty, patentability, freedom to operate, market size, or realized impact, and it does not exclude unpublished laboratory practices, proprietary controller features, patents, or standards outside the bounded search.","arm":"PROPOSAL_FIRST","candidate_version":0,"controller_recommendation":{"action":"STOP_EMPIRICAL_RESEARCH_NEEDED","repairable":true,"material_progress_observed":true,"progress_targets":["Secure one eligible synchronized session and a data-use agreement from a stimulation laboratory.","Preregister the recovery estimator, policy definitions, comparators, coverage floor, primary identifiability metric, and falsification rules.","Run the bounded offline replay and report results after matching stimulated-trial count and elapsed time.","Obtain a named PI's assessment of workflow fit, acceptable condition loss, operator-state semantics, and willingness to sponsor a pilot.","Before live use, document device-sponsor constraints and obtain the applicable IRB, institutional-safety, animal-care, and FDA determinations.","Advance only if recovery-bounded null epochs outperform dense history modeling and matched randomized omission without unacceptable coverage or burden."],"reason":"Bounded web research establishes the problem mechanism, adjacent prior art, plausible implementation, authority path, and cost scope, but it cannot determine the candidate's incremental effect. The decisive evidence requires proprietary event-level data and, if offline results pass, an authorized live comparison."}}