Draft — DeSci on Gitcoin Community Grants

MOTIVATION LETTER

The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention in addiction, was developed entirely outside a university laboratory. Three sole-authored preprints on OSF and Zenodo, a provisional patent filed Q3 2026, and endorsements from Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU confirm the science is sound. The CCT model reduces encoding probability from 0.855 to 0.122, an 85.8 percent reduction, with super-additivity of 12.8 percentage points. All five pre-registered hypotheses H1 through H5 were confirmed using ODE/RK45 and Bayesian MCMC validation.

This work embodies the DeSci on Gitcoin mission. Every line of code for IMPRINT, TOPOLOGIX, and GATE is on GitHub under Apache 2.0 or permissive licenses. All hypotheses were pre-registered. All data and analysis scripts are publicly archived. The provisional patent is a defensive public-good filing, not a barrier to open science. The target population is addiction patients in low- and middle-income countries, including Nigeria, where treatment access is below 10 percent.

The DeSci on Gitcoin Community Grants programme funds exactly this kind of independent, decentralized research. The rolling deadline and global eligibility allow a 29-year-old Nigerian pharmacist with a B.Pharm from the University of Ibadan and no current MSc enrollment to compete on scientific merit alone. The requested 8,000 USD will support three specific deliverables: first, a formal computational validation of the CCT model against human neuroimaging data from the Human Connectome Project; second, deployment of the IMPRINT screening platform as a public web tool for addiction liability assessment; third, a workshop for 20 early-career Nigerian researchers on pre-registration, open-source code, and decentralized research infrastructure.

The CCT model challenges the mainstream dopamine-centric addiction paradigm by proposing a conjunctive consolidation threshold that integrates dopamine, glutamate, and norepinephrine signaling. This is a new framework with formal mathematical specification, Bayesian population dynamics, and a clinical trial architecture already published on Zenodo. A review article is under review at Neuroscience and Biobehavioral Reviews. A co-authored paper is under review at Alcohol.

DeSci on Gitcoin provides the funding, community, and visibility to move this work from preprint to clinical validation. The 8,000 USD budget covers cloud compute for HCP data analysis, server costs for IMPRINT deployment, and stipends for workshop facilitators. All outputs will remain open access, all code will remain permissive, and all data will be deposited in public repositories.

SHORT ESSAY ON OPEN SCIENCE AND DECENTRALIZATION

The CCT model was built on three principles that match the DeSci on Gitcoin ethos. First, pre-registration. All five hypotheses H1 through H5 were registered on OSF before any data was collected or analyzed. The foundational paper, the formal mathematical specification, and the Bayesian population dynamics paper are all on OSF or Zenodo with permanent DOIs. Second, open code. IMPRINT, TOPOLOGIX, and GATE are on GitHub under Apache 2.0. TOPOLOGIX uses persistent homology and bipartite simplicial complexes for drug-protein interaction analysis, and its hERG cardiotoxicity MVP is fully reproducible from the repository. Third, decentralized infrastructure. The provisional patent on the CCT core architecture is filed as a defensive measure to prevent patent trolls from blocking open access, not to restrict use. The patent text will be published alongside the open-source implementation.

The community impact is direct. Nigeria has an estimated 3.5 million people with substance use disorders and fewer than 200 addiction psychiatrists. IMPRINT, the addiction-liability screening platform, can be deployed as a low-cost, open-source tool for primary care clinics. GATE, the BCI neural-stimulation safety evaluation platform, addresses a gap in neurotechnology regulation that disproportionately affects LMICs. The workshop for 20 Nigerian early-career researchers will train participants in pre-registration, open-source code practices, and decentralized research tools. All workshop materials will be published on Zenodo under a Creative Commons license.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold model proposes that reward-memory encoding in addiction requires simultaneous activation of three neurotransmitter systems: dopamine, glutamate, and norepinephrine. No single system is sufficient. The threshold is conjunctive, meaning all three must cross a critical level within a narrow time window for consolidation to occur. This explains why existing pharmacotherapies targeting single systems show limited efficacy and high relapse rates.

The formal mathematical specification, published on OSF, models the threshold as a nonlinear dynamical system with three coupled differential equations. The Bayesian population dynamics paper on Zenodo extends this to a hierarchical model that accounts for individual variability in receptor densities, neurotransmitter turnover rates, and metabolic clearance. The clinical trial architecture proposes a three-arm, double-blind, placebo-controlled design with a triple combination therapy targeting all three systems simultaneously.

Validation used ODE/RK45 numerical integration and Bayesian MCMC with PyMC. Encoding probability dropped from 0.855 to 0.122, an 85.8 percent reduction. Super-additivity of 12.8 percentage points indicates that the triple combination outperforms the sum of individual effects. All five pre-registered hypotheses were confirmed.

The next step is validation against human neuroimaging data. The Human Connectome Project provides resting-state fMRI and diffusion MRI for 1,200 subjects, including measures of reward circuit connectivity. The CCT model predicts that individuals with higher conjunctive consolidation thresholds will show lower addiction liability scores on standardized instruments. This analysis requires cloud compute resources for preprocessing and statistical modeling, estimated at 3,000 USD.

The IMPRINT platform will be deployed as a public web tool using Supabase and Postgres for the backend and JavaScript for the frontend. Users input demographic, genetic, and behavioral data, and the platform returns an addiction liability score based on the CCT model. Deployment costs are estimated at 2,000 USD for server hosting and domain registration for one year.

The workshop for 20 Nigerian early-career researchers will cover pre-registration on OSF, open-source code practices with GitHub, and decentralized research tools including IPFS and blockchain-based timestamping. Each participant will complete a pre-registered mini-project. Workshop costs are estimated at 3,000 USD for venue, internet, and stipends.

BUDGET

Cloud compute for HCP data analysis: 3,000 USD
Server hosting and domain for IMPRINT deployment: 2,000 USD
Workshop venue, internet, and stipends for 20 participants: 3,000 USD
Total: 8,000 USD

CHECKLIST

- [ ] Completed application form on Karma Halo
- [ ] Motivation letter (this document)
- [ ] Short essay on open science and decentralization (this document)
- [ ] Research statement (this document)
- [ ] Budget table (this document)
- [ ] Link to ORCID profile: 0009-0001-9272-6735
- [ ] Link to GitHub profile: github.com/AmunRaPtah
- [ ] Link to OSF preprint: 10.17605/OSF.IO/KG7B5
- [ ] Link to OSF mathematical specification: 10.17605/OSF.IO/EMY4U
- [ ] Link to Zenodo Bayesian paper: 10.5281/zenodo.20492472
- [ ] Link to IMPRINT repository on GitHub
- [ ] Link to TOPOLOGIX repository on GitHub
- [ ] Link to GATE repository on GitHub
- [ ] Provisional patent filing confirmation (Q3 2026)
- [ ] Endorsement letters from Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar (optional but recommended)
- [ ] Proof of PCN pharmacist license
- [ ] B.Pharm transcript from University of Ibadan

EDITOR NOTES

- Eligibility risk: DeSci on Gitcoin Community Grants typically fund projects, not individuals. The application should frame the 8,000 USD as project funding for three specific deliverables, not as a personal fellowship. If the programme requires a legal entity, Eniola may need to register as a sole proprietor or use ZYCO as the recipient.
- Fact verification: The claim that Nigeria has 3.5 million people with substance use disorders and fewer than 200 addiction psychiatrists needs a citation. Eniola should provide the source or replace with a verifiable statistic from the WHO or Nigerian Ministry of Health.
- Gap: The application does not mention any prior relationship with DeSci on Gitcoin or the Karma Halo platform. Eniola should check whether the programme requires a community vote or DAO approval and adjust the strategy accordingly. If community voting is required, he should engage with the DeSci on Gitcoin community before submitting.

MOTIVATION LETTER

The Conjunctive Consolidation Threshold model, a tripartite pharmacological framework for reward-memory encoding prevention in addiction, was developed entirely outside a university laboratory. Three sole-authored preprints on OSF and Zenodo, a provisional patent filed Q3 2026, and endorsements from Kent Berridge at Michigan, Samuel Gershman at Harvard, Nathaniel Daw at Princeton, and Marcelo Mattar at NYU confirm the science is sound. The CCT model reduces encoding probability from 0.855 to 0.122, an 85.8 percent reduction, with super-additivity of 12.8 percentage points. All five pre-registered hypotheses H1 through H5 were confirmed using ODE/RK45 and Bayesian MCMC validation.

This work embodies the DeSci on Gitcoin mission. Every line of code for IMPRINT, TOPOLOGIX, and GATE is on GitHub under Apache 2.0 or permissive licenses. All hypotheses were pre-registered. All data and analysis scripts are publicly archived. The provisional patent is a defensive public-good filing, not a barrier to open science. The target population is addiction patients in low- and middle-income countries, including Nigeria, where treatment access is below 10 percent.

The DeSci on Gitcoin Community Grants programme funds exactly this kind of independent, decentralized research. The rolling deadline and global eligibility allow a 29-year-old Nigerian pharmacist with a B.Pharm from the University of Ibadan and no current MSc enrollment to compete on scientific merit alone. The requested 8,000 USD will support three specific deliverables: first, a formal computational validation of the CCT model against human neuroimaging data from the Human Connectome Project; second, deployment of the IMPRINT screening platform as a public web tool for addiction liability assessment; third, a workshop for 20 early-career Nigerian researchers on pre-registration, open-source code, and decentralized research infrastructure.

The CCT model challenges the mainstream dopamine-centric addiction paradigm by proposing a conjunctive consolidation threshold that integrates dopamine, glutamate, and norepinephrine signaling. This is a new framework with formal mathematical specification, Bayesian population dynamics, and a clinical trial architecture already published on Zenodo. A review article is under review at Neuroscience and Biobehavioral Reviews. A co-authored paper is under review at Alcohol.

DeSci on Gitcoin provides the funding, community, and visibility to move this work from preprint to clinical validation. The 8,000 USD budget covers cloud compute for HCP data analysis, server costs for IMPRINT deployment, and stipends for workshop facilitators. All outputs will remain open access, all code will remain permissive, and all data will be deposited in public repositories.

SHORT ESSAY ON OPEN SCIENCE AND DECENTRALIZATION

The CCT model was built on three principles that match the DeSci on Gitcoin ethos. First, pre-registration. All five hypotheses H1 through H5 were registered on OSF before any data was collected or analyzed. The foundational paper, the formal mathematical specification, and the Bayesian population dynamics paper are all on OSF or Zenodo with permanent DOIs. Second, open code. IMPRINT, TOPOLOGIX, and GATE are on GitHub under Apache 2.0. TOPOLOGIX uses persistent homology and bipartite simplicial complexes for drug-protein interaction analysis, and its hERG cardiotoxicity MVP is fully reproducible from the repository. Third, decentralized infrastructure. The provisional patent on the CCT core architecture is filed as a defensive measure to prevent patent trolls from blocking open access, not to restrict use. The patent text will be published alongside the open-source implementation.

The community impact is direct. Nigeria has an estimated 3.5 million people with substance use disorders and fewer than 200 addiction psychiatrists. IMPRINT, the addiction-liability screening platform, can be deployed as a low-cost, open-source tool for primary care clinics. GATE, the BCI neural-stimulation safety evaluation platform, addresses a gap in neurotechnology regulation that disproportionately affects LMICs. The workshop for 20 Nigerian early-career researchers will train participants in pre-registration, open-source code practices, and decentralized research tools. All workshop materials will be published on Zenodo under a Creative Commons license.

RESEARCH STATEMENT

The Conjunctive Consolidation Threshold model proposes that reward-memory encoding in addiction requires simultaneous activation of three neurotransmitter systems: dopamine, glutamate, and norepinephrine. No single system is sufficient. The threshold is conjunctive, meaning all three must cross a critical level within a narrow time window for consolidation to occur. This explains why existing pharmacotherapies targeting single systems show limited efficacy and high relapse rates.

The formal mathematical specification, published on OSF, models the threshold as a nonlinear dynamical system with three coupled differential equations. The Bayesian population dynamics paper on Zenodo extends this to a hierarchical model that accounts for individual variability in receptor densities, neurotransmitter turnover rates, and metabolic clearance. The clinical trial architecture proposes a three-arm, double-blind, placebo-controlled design with a triple combination therapy targeting all three systems simultaneously.

Validation used ODE/RK45 numerical integration and Bayesian MCMC with PyMC. Encoding probability dropped from 0.855 to 0.122, an 85.8 percent reduction. Super-additivity of 12.8 percentage points indicates that the triple combination outperforms the sum of individual effects. All five pre-registered hypotheses were confirmed.

The next step is validation against human neuroimaging data. The Human Connectome Project provides resting-state fMRI and diffusion MRI for 1,200 subjects, including measures of reward circuit connectivity. The CCT model predicts that individuals with higher conjunctive consolidation thresholds will show lower addiction liability scores on standardized instruments. This analysis requires cloud compute resources for preprocessing and statistical modeling, estimated at 3,000 USD.

The IMPRINT platform will be deployed as a public web tool using Supabase and Postgres for the backend and JavaScript for the frontend. Users input demographic, genetic, and behavioral data, and the platform returns an addiction liability score based on the CCT model. Deployment costs are estimated at 2,000 USD for server hosting and domain registration for one year.

The workshop for 20 Nigerian early-career researchers will cover pre-registration on OSF, open-source code practices with GitHub, and decentralized research tools including IPFS and blockchain-based timestamping. Each participant will complete a pre-registered mini-project. Workshop costs are estimated at 3,000 USD for venue, internet, and stipends.

BUDGET

Cloud compute for HCP data analysis: 3,000 USD
Server hosting and domain for IMPRINT deployment: 2,000 USD
Workshop venue, internet, and stipends for 20 participants: 3,000 USD
Total: 8,000 USD

CHECKLIST

- [ ] Completed application form on Karma Halo
- [ ] Motivation letter (this document)
- [ ] Short essay on open science and decentralization (this document)
- [ ] Research statement (this document)
- [ ] Budget table (this document)
- [ ] Link to ORCID profile: 0009-0001-9272-6735
- [ ] Link to GitHub profile: github.com/AmunRaPtah
- [ ] Link to OSF preprint: 10.17605/OSF.IO/KG7B5
- [ ] Link to OSF mathematical specification: 10.17605/OSF.IO/EMY4U
- [ ] Link to Zenodo Bayesian paper: 10.5281/zenodo.20492472
- [ ] Link to IMPRINT repository on GitHub
- [ ] Link to TOPOLOGIX repository on GitHub
- [ ] Link to GATE repository on GitHub
- [ ] Provisional patent filing confirmation (Q3 2026)
- [ ] Endorsement letters from Kent Berridge, Samuel Gershman, Nathaniel Daw, or Marcelo Mattar (optional but recommended)
- [ ] Proof of PCN pharmacist license
- [ ] B.Pharm transcript from University of Ibadan

EDITOR NOTES

- Eligibility risk: DeSci on Gitcoin Community Grants typically fund projects, not individuals. The application should frame the 8,000 USD as project funding for three specific deliverables, not as a personal fellowship. If the programme requires a legal entity, Eniola may need to register as a sole proprietor or use ZYCO as the recipient.
- Fact verification: The claim that Nigeria has 3.5 million people with substance use disorders and fewer than 200 addiction psychiatrists needs a citation. Eniola should provide the source or replace with a verifiable statistic from the WHO or Nigerian Ministry of Health.
- Gap: The application does not mention any prior relationship with DeSci on Gitcoin or the Karma Halo platform. Eniola should check whether the programme requires a community vote or DAO approval and adjust the strategy accordingly. If community voting is required, he should engage with the DeSci on Gitcoin community before submitting.

AI Draft — DeSci on Gitcoin Community Grants