MOTIVATION LETTER The Conjunctive Consolidation Threshold model is a tripartite pharmacological framework for preventing reward-memory encoding in addiction, and it is fully open source. The code, the calibration pipeline, and the pre-registered hypotheses are all public on OSF and Zenodo. The model couples three axes: dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast, into a single ODE system solved with RK45 and calibrated with Bayesian MCMC using PyMC's DEMetropolisZ sampler. Fourteen free parameters were estimated from priors elicited from a systematic screen of 1,847 records in the literature. All five pre-registered hypotheses, H1 through H5, were confirmed, with posterior super-additivity of 13 to 22 percentage points across model versions. Three sole-authored preprints are under review at peer-reviewed journals: International Addiction Review and Therapeutics, Progress in Neuro-Psychopharmacology and Biological Psychiatry, and Neuroscience and Biobehavioral Reviews. A co-authored paper is under review at Alcohol, Elsevier. NLnet Foundation funds libre software that benefits the public. The CCT model is a non-commercial, reproducible computational tool that any researcher anywhere can run, modify, and audit. That matters because addiction neuroscience is dominated by labs in high-income countries with proprietary pipelines and expensive infrastructure. A Nigerian pharmacist with a B.Pharm from the University of Ibadan and an enrollment in the M.Sc. Digital Health program at Hasso Plattner Institute in Potsdam built this model independently. That is the perspective NLnet's diversity and inclusion criteria are designed to surface. The grant amount of 5,000 to 50,000 euros fits the next phase of this work precisely. The current model is calibrated and validated, but it needs three things: a web-based interactive simulator so clinicians and researchers in low-resource settings can run scenarios without installing Python or PyMC; a formal specification document that makes the mathematical assumptions auditable by non-modelers; and a maintained test suite that ensures the code remains reproducible as dependencies evolve. The budget is straightforward: 15,000 euros for a six-month development sprint, 5,000 euros for documentation and specification writing, and 5,000 euros for dissemination, including a workshop for African neuroscience researchers. Total requested: 25,000 euros. The technical quality is demonstrated by the work itself. The cardiotoxicity topology study, a pre-registered powered replication, found that bipartite persistent homology does not beat a plain descriptor baseline, AUROC 0.8426 versus 0.8782, settling a comparison the literature had never actually run. The TOPOLOGIX project, using ESM-2 protein-language-model delta-embeddings with Morgan fingerprints and a Random Forest classifier, achieves AUROC 0.804 plus or minus 0.025 on the Platinum benchmark of 553 mutations, beating structure-based baselines like mCSM-lig at approximately 0.70 while covering 100 percent of mutations versus approximately 18 percent for structure-limited tools. These projects demonstrate the same rigor applied to CCT: pre-registration, Bayesian calibration, honest reporting of negative results, and open code. The societal impact is direct. Addiction is a global health crisis with disproportionate burden in low- and middle-income countries. A free, open-source model that helps researchers understand how reward memories form and how to prevent their consolidation is a public good. NLnet's open science thematic area is the correct home for this project. The project is non-commercial, globally accessible, and built by an early-career researcher from an LMIC. I request 25,000 euros to complete the next phase of the CCT model as a libre software tool. RESEARCH STATEMENT The CCT model addresses a specific gap in addiction neuroscience: no existing computational framework integrates the three known pharmacological mechanisms of reward-memory encoding into a single predictive model. Dopaminergic reward prediction error, NMDAR-dependent long-term potentiation, and affective contrast are each studied extensively in isolation. The CCT model couples them into a system of ordinary differential equations solved with RK45 and calibrated with Bayesian MCMC. The model has 14 free parameters, all with priors elicited from a systematic screen of 1,847 records. All five pre-registered hypotheses were confirmed. Posterior super-additivity ranged from 13 to 22 percentage points across model versions, meaning the combined effect of the three axes exceeds the sum of their individual effects. This is the core scientific finding: the interaction matters, not just the components. The next phase has three deliverables. First, a web-based interactive simulator. The target user is a researcher or clinician in Nigeria, Kenya, or India who does not have access to high-performance computing or a Python environment. The simulator will allow them to adjust the 14 parameters, run the ODE solver in the browser, and visualize the predicted effect on reward-memory consolidation. The implementation will use WebAssembly to run the RK45 solver client-side, with no data leaving the user's machine. This addresses privacy and infrastructure constraints simultaneously. Second, a formal specification document. The mathematical assumptions of the model, the derivation of the priors, and the calibration protocol will be written in a format that is auditable by reviewers who are not computational modelers. This document will be published on Zenodo with a DOI and will be versioned alongside the code. The specification will include the full derivation of the three coupled axes, the justification for each prior distribution, and the exact likelihood function used in the Bayesian calibration. Third, a maintained test suite. The current codebase has tests, but they are not thorough enough for a tool that other researchers will depend on. The test suite will include unit tests for each ODE component, integration tests for the coupled system, regression tests against the published posterior distributions, and continuous integration via GitHub Actions. The repository will use semantic versioning and will be archived on Zenodo at each release. The timeline is six months. Month one: refactor the codebase into a library with a clean API. Month two: implement the WebAssembly solver and the browser interface. Month three: write the formal specification document and submit it for external review. Month four: build the test suite and set up continuous integration. Month five: run a workshop for African neuroscience researchers to test the simulator and collect feedback. Month six: revise based on feedback, publish the release, and archive on Zenodo. The budget is 25,000 euros. Fifteen thousand euros covers the development sprint, including the WebAssembly implementation and the test suite. Five thousand euros covers the specification document and external review. Five thousand euros covers the workshop, including travel support for participants from Nigerian and Kenyan universities, and dissemination. No part of this budget supports proprietary software, patents, or commercial activity. The entire output will be licensed under an open-source license approved by the Open Source Initiative, likely Apache 2.0 for code and CC-BY 4.0 for documentation. The alignment with NLnet is direct. NLnet funds libre software that benefits the public. This project is libre software, it benefits the public, and it is built by an independent researcher from an LMIC who has already demonstrated the ability to execute complex computational research without institutional backing. The technical quality is evidenced by the pre-registered hypotheses, the Bayesian calibration, and the honest reporting of negative results in the cardiotoxicity and resistance studies. The societal impact is evidenced by the global burden of addiction and the lack of accessible modeling tools for researchers in low-resource settings. The project is feasible within the requested budget and timeline, and the deliverables are concrete and verifiable. BUDGET JUSTIFICATION The total requested amount is 25,000 euros. The breakdown is as follows. Development sprint: 15,000 euros. This covers six months of focused development time for the refactor, the WebAssembly solver, the browser interface, and the test suite. The rate is 2,500 euros per month, which is below the market rate for a senior software engineer in Germany, where the applicant is enrolled at Hasso Plattner Institute. The applicant will do the work personally, so no subcontracting costs are included. Specification and review: 5,000 euros. This covers the time to write the formal specification document, the cost of external review by two independent researchers with expertise in dynamical systems and addiction neuroscience, and the publication fees for Zenodo archiving. The reviewers will be compensated at 1,000 euros each, and the remaining 3,000 euros covers the applicant's time and any editing or typesetting costs. Workshop and dissemination: 5,000 euros. This covers a two-day workshop for African neuroscience researchers, to be held virtually with a hybrid node in Lagos, Nigeria. The budget includes 2,000 euros for travel and accommodation support for up to five participants from Nigerian and Kenyan universities, 1,500 euros for the virtual platform and technical support, and 1,500 euros for dissemination, including video editing, captioning, and the production of a freely available workshop report. No overhead is charged. No equipment is purchased. No proprietary software licenses are required. The applicant already has the necessary hardware and software. The budget is cost-effective because the applicant is doing the majority of the work personally and is based in Nigeria, where living costs are lower than in Germany or the Netherlands. The workshop is designed to maximize reach per euro by using a hybrid format. The budget justification aligns with NLnet's criteria for cost-effectiveness and sustainability. The primary output, the CCT model as a libre software tool, will be maintained by the applicant and archived on Zenodo. The workshop report and the specification document will be open access. The project does not create a dependency on any commercial service or proprietary platform. CHECKLIST - [ ] Verify NLnet Foundation's current application form and submission portal at nlnet.nl - [ ] Confirm the exact grant category for open science and research software - [ ] Prepare the motivation letter as a PDF, 500 words maximum - [ ] Prepare the research statement as a PDF, 600 words maximum - [ ] Prepare the budget justification as a PDF, 300 words maximum - [ ] Attach the applicant's CV, including ORCID, GitHub, and zyco.org - [ ] Attach links to the three preprints on OSF and Zenodo - [ ] Attach links to the CCT model repository and the TOPOLOGIX repository - [ ] Attach the letter of endorsement from Kent Berridge, University of Michigan - [ ] Attach the letter of endorsement from Samuel Gershman, Harvard University - [ ] Attach proof of enrollment at Hasso Plattner Institute for the M.Sc. Digital Health program - [ ] Attach the PCN pharmacist license - [ ] Confirm the open-source license for all code and documentation - [ ] Confirm the Zenodo archive strategy for each release - [ ] Submit the application before the rolling deadline and record the submission date EDITOR NOTES - Eligibility risk: NLnet's mandate is specifically for libre software and hardware projects. The CCT model is a research output with software components. The application must frame the software as the primary deliverable, not the scientific findings. The research statement does this, but the motivation letter should be checked to ensure it does not drift into pure science funding language. - Verification needed: The exact NLnet grant category for this project should be confirmed. The URL provided in the profile points to a Kindora listing, not the NLnet website. The applicant must verify the current application form, the thematic areas, and whether there is a specific call for open science or digital rights that fits better than a general grant. - Verification needed: The endorsement letters from Berridge, Gershman, Daw, and Mattar are listed as collaborators or endorsements, but the profile does not specify whether letters have been written. The applicant must confirm that these letters exist and are ready to attach. - Gap: The profile does not specify the exact open-source license for the CCT model. The research statement proposes Apache 2.0 for code and CC-BY 4.0 for documentation, but the applicant must confirm this is acceptable to NLnet and that no prior publication on OSF or Zenodo used a different license. - Gap: The budget justification assumes the applicant will do the development work personally while enrolled in the M.Sc. program at Hasso Plattner Institute. The applicant must confirm that the program schedule allows for this level of commitment, or adjust the timeline and budget accordingly.