OA Week: The Troubling U-turn of Open Access

 

Who Owns Our Knowledge? Troubling trends have emerged.

As academics, media producers, and authors: Who Owns Our Knowledge? I present two troubling scenarios. Each of these have happened in the past few decades and is a heady mix of hypocrisy and gross power imbalance.

Intellectual Property Rights!

2006: RIAA Persecutes people for downloading music.

2013: Aaron Schwartz is persecuted for downloading JSTOR articles, resulting in his suicide.

2025: Technology companies use intellectual property without author permissions to train Large Language Models (LLMs). Everyone celebrates tech company profit margins, and LLMs can drive some people to suicide. 

Which of these things is not like the other? To be fair, the final example (in red text) is at the expense of legacy publishers and intellectual property laws. But that is the point. Intellectual property rights are enforced in ways that totally benefit the largest entity. 

Open Access to the.....logical endpoint?

Once upon a time, people were excited about radical open access. Post a preprint, post-peer review, and eliminate the bias of prestige journals. Now, it is the prestigious journals that enjoy Gold (!!) open access (for an exorbitant fee).

Although there are a number of options outside of this paradigm (e.g. Green Open Access), the goals of the open access reform movement seem to have become obscured. More specifically, the transition from words and slogans to institutional normalization has not been smooth.

So is the highlighted scenario the logical endpoint for open access? Probably not, but more work is needed. Not the easy work, but the harder work of changing systems and institutions.

That is all.

Can these scenarios be stopped? This is up to us.

Welcome to our Google Summer of Code scholars for 2025!

 

The Orthogonal Research and Education Laboratory is pleased to welcome three students to the lab as Google Summer of Code (GSoC) scholars. Two (Lalith Baru and Jayadratha Gayen) will be joining the DevoWorm group and one (Vidhi Rohira) will be joining the Open-source Sustainability project.

Lalith and Jayadratha will be working on different aspects of our DevoGraph project (Github). Lalith’s successful project proposal is called “NDP-HNN: Modelling Neural Developmental Programs of C. elegans Using Growing Hypergraph Neural Networks”, while Jayadratha’s successful project proposal is called “DevoTG: Dynamic Graph Neural Networks for Modeling C. elegans Development”. Good luck to both of them! They will be working with the DevoWorm group and active in our weekly meetings. They will also be hosted by the OpenWorm Foundation and contributing to their mission.

Vidhi will be contributing to OREL's Open-source Sustainability project (Github) by working at the intersection of Reinforcement Learning and Agent-based Modeling. Vidhi’s successful project proposal is called “SustainHub: Adaptive Agent-Based Model for Open-Source Community Sustainability”. Check out her updates as part of the Saturday Morning NeuroSim meeting series.

We have also invited our unsuccessful candidates to join our Open-source interest group. We host this meeting every Friday at 12 Noon Eastern time, and cover promoting open-source practices, project development, and project management education.

OAWeek 2024: Intrinsic and Extrinsic Approaches to Open Access

This post is in celebration of Open Access (OA) Week 2024. The theme for this year is "Community over Commercialization". 

How do we incentivize people to adopt Open Access practices? We can take lessons from motivational Psychology to think about routes to better practice. Before doing so, we need to consider the current (and often sorry state) of open access.

It could be argued that in some important ways, Open Access has failed. The system of access to academic goods as currently structured is built on significant benefits to publishers and costs to libraries and authors. This benefit has been accrued by publishers due to reputational benefits: being published in Nature, Science, or Cell is highly prestigious. Yet the benefits of this prestige are necessarily limited to a few groups with lots of resources. And the beneficial attributes of open access have been captured by commercial entities. Similar problems plague the open-source community, a shift to the open ethos is the only way out.  

The different types of open access also play different roles in the marketplace of academic goods. Green open access, or self-archiving artifacts, are community goods. While this can be susceptible to the tragedy of the commons, proper social investment can ameliorate maintenance and growth imperatives. This is often seen as the highest standard for open access but requires community investment. Building a sustainable infrastructure of preprints, open peer review, and overlay journals has been elusive.

The Economic Benefits and Costs of Different Colored Access

Black open access using tools such as Sci-Hub is considered piracy (hence the "black" label). From an economic perspective, piracy is symptomatic of a dysfunctional market. Indeed, part of open access' failure is due to the dominant position of publishers and their own economic imperatives. In fact, black open access can be considered a rational response to closing access to article in a research culture of sharing and finding alternate routes to success [1-3]. 

To focus more on the publisher's advantage, and the failure point of open access more generally, is the current state of Gold, Diamond, and Platinum open access. Gold open access involves payment of an APC (Article Processing Charges) fee to the publisher. This often reduces the burdens on libraries, as they previously paid excessive subscription fees. This is because APCs actually increase the burden on individual authors, with disappointing results on the prestige economy. Without market power for the authors (or home institutions), there is no incentive to build Diamond and Platinum access systems. In such systems, no APC fee is paid, and we get the prestige that people seek. One barrier to this is shifting the burden back to publishers, but with proper management of community resources it is the least bad option.

Up to this point, I have been speaking in economically coded language. Without thinking about various motivations, however, we cannot fully understand ways to move forward. Let's think about various intrinsic/extrinsic motivations of authors and their institutions to reclaim open access. Intrinsic motivations are properties of individual cognition, while extrinsic motivations are things that motivate individual behaviors from the outside world.

Intrinsic motivations

There are many intrinsic motivations that drive acceptance and adoption of open access. But there are many that do not, and these motivations often come into tension. Positive drivers include striving for a better community, an imperative for sharing results with the community, the ability to provide different platforms for scientific communication (datasets, hypotheses, theory, out-of-scope studies), and recognition for unsung components of the scientific process (such as technical reports or negative results). Negative drivers include a need to satiate cultural traditions, an inability to convey prestige through open means, a conflation of open access with fraud and low-quality work, and an inability to meet the quality needed to do open access successfully.  

Extrinsic motivations

The multitude extrinsic motivations include institutional support, the need for career promotion, community rewards and prestige, the pressure for cost savings, and technological ease of adoption. These can be a mix of positive and negative drivers that make adoption of open access hard to justify. Interactions with open-source software can also drive open access adoption, as the commitment needed to develop shared data and code can be easily extended to other academic artifacts.

What is the path forward? 

Sometimes considering motivations are not enough, and the community is much pettier and more irrational than we like to admit. It is worth thinking about eLife's model in open peer review, which in part lead to a backlash against the editorial staff [4, 5] by less sympathetic members of the scientific community (and barely-disguised corporate interests). Part of this is a disagreement about open strategies, but this is also about the gatekeeping nature the scientific community itself. The eLife model allows for papers to be preprinted, and then peer reviewed. The paper remains live on eLife's website even if the reviews recommend rejection (although the rejection is noted) [6, 7]. This is not novel amongst open peer review platforms but has rankled the more hierarchically oriented members of the scientific community. Perhaps we need to also consider "irrational management strategies", or what intrinsic motivations drive decisions that favor obsolete conventions.

References:

[1] Melvin et.al (2020). Communicating and disseminating research findings to study participants: Formative assessment of participant and researcher expectations and preferences. Journal of Clinical and Translational Science, 4(3), 233–242.

[2] Casci and Adams (2020). Research Culture: Setting the right tone. eLife, 9, e55543.

[3] Nosek et.al (2015). Promoting an open research culture. Science, 348(6242), 1422-1425.

[4] eLife latest in string of major journals put on hold from Web of Science. RetractionWatch. https://retractionwatch.com/2024/10/24/elife-latest-in-string-of-major-journals-put-on-hold-from-web-of-science/

[5] Abbot (2023). Strife at eLife: inside a journal’s quest to upend science publishing. Nature News, March 17. https://www.nature.com/articles/d41586-023-00831-6

[6] F1000 Staff (2022). Open peer review: establishing quality. March 7.  https://www.f1000.com/blog/peer-review-establishing-quality

[7] McCallum et.al (2021). OpenReview NeurIPS 2021 Summary Report. https://docs.openreview.net/reports/conferences/openreview-neurips-2021-summary-report

Google Summer of Code 2024

 

Welcome to the new Google Summer of Code scholars for 2024! INCF is sponsoring four students for which I (Bradly Alicea) am acting as mentor: two students for the DevoWorm group (via the OpenWorm Foundation community) and two students for the Orthogonal Research and Education Laboratory. 

D-GNNs (sponsored by the DevoWorm group)

Congratulations to Pakhi Banchalia and Mehul Arora for being accepted to work on the Developmental Graph Neural Networks (D-GNNs) project. Pakhi will be working on incorporating Neural Developmental Programs (NDPs) into GNN models. Mehul will be working on hypergraph techniques for developmental lineage trees and embryogenesis [1]. Himanshu Chougule (Google Summer of Code scholar) is a co-mentor for this project.

Virtual Reality for Research and Open-source Sustainability (sponsored by the Orthogonal Research and Education Lab)

Congratulations to Sarrah Bastawala for being accepted to work on the Open-source Sustainability project [2]. Sarrah is incorporating Large Language Models (LLMs) into the collection of agent-based approaches for this project. Jesse Parent is a co-mentor for this project.

We also have two Open-source Development scholars for Summer 2024: Adama Koita and Shubham Soni. They will be participating in the Orthogonal Lab's open-source weekly meetings in addition to projects based around Virtual Reality and Open-source Sustainability, respectively. 

Google Summer of Code 2023

Welcome to the new Google Summer of Code scholars for 2023! INCF is sponsoring four students for which I (Bradly Alicea) am acting as mentor: two students for the DevoWorm group (via the OpenWorm Foundation community) and two students for the Orthogonal Research and Education Laboratory. These four students are pursuing three projects.

D-GNNs and DevoLearn (sponsored by the DevoWorm group)

Congratulations to Himanshu Chougule and Sushmanth Reddy Mereddy for being accepted to work on the Developmental Graph Neural Networks (D-GNNs) project. Sushmanth has been contributing to the DevoLearn platform for quite some time and will spend this summer working on improving the image segmentation to GNN embedding pipeline. Himanshu was a part of last Summer's GSoC cohort in the Orthogonal Research and Education Laboratory, working on the Open-source Sustainability project. His work resulted in developing Agent-based Model-Reinforcement Learning hybrid models. This year, he will be working on building Topological Data Analytic capabilities into the D-GNN pipeline. 

Mayukh Deb and Jiahang Li are co-mentors for this project.

Virtual Reality for Research and Open-source Sustainability (sponsored by the Orthogonal Research and Education Lab)

Congratulations to Vrushali Nandurkar and R.V. Rajagopalan for being accepted to work on the projects Virtual Reality for Research and Open-source Sustainability, respectively. Vrushali is enthusiastic about working on creating open-source virtual world assets for scientific research and educational initiatives. R.V. will be working on a continuation of the Open-source Sustainability project, helping to augment the existing models and web interface.

Jesse Parent is a co-mentor for both projects, while Brian McCorkle is a co-mentor for the Open-source Sustainability project. 

OAWeek 2022: Managing Virtual and Hybrid Meetings

Welcome to International Open Access Week, 2022 edition! Last year, we discussed the vision of a distributed research organization. This year, we will explore this theme a bit further. One aspect of distributed organizations is the need to work both synchronously and asynchronously. This brings the real-world experience closer to the collaborator without the travel, carbon emissions, or expense of being at a centralized institute. As our collaborators live in many time zones and have different lifestyles, it is important to capture their full attention in different ways. 

One way this is done is through the live attendance and replay of group meetings. The Orthogonal Research and Education Lab (OREL) offers a number of regular topical meetings, in addition to a general meeting on Saturdays, that engages collaborators from all over the world using a number of different pedagogical and technological techniques. 

An example of a virtual distributed meeting with collaborators dropping in from different parts of the globe.

An open meeting has a number of moving parts that need to be thoughtfully considered to ensure success. The first of these is choosing a meeting platform. OREL has found success with Jitsi, as it is lightweight and free to use (open source). While Jitsi can be used as a service, installing it on your own server opens up its many customizable features. Jitsi even works with Virtual Reality, with interactions between the 2-D meeting world and immersive 3-D being available in the Wolvic browser and Meta Quest casting option.

Sample scenes from screensharing within Meta Quest and the casting option.

Secondly, programming the meeting is a non-trivial detail that can make the most of your time. For our Saturday Morning NeuroSim meetings, we have settled on the following format: updates, light features, discussion, open collaboration, and finally, papers of the week. Agenda-setting should be flexible with respect to your attendee's availability. Not everyone can make an entire meeting, so allowing them to "drop into" participation is encouraged. 

Notetaking and live feeds are also good for augmenting our meetings. The OREL Lab Manager (Jesse Parent) We use notetaking tools such as Obsidian and Notion with allied feeds (Slack and Discord) for coordinating the various fragments of ideas and themes that emerge during meeting time. Feed technology is also good for sharing papers, and the vision of a stream feed is key to realizing the multimedia aspect of real-time meeting immersion, even when attendees are asynchronous.     

Different types of notetaking and stream feeding within a meeting (from the Cognition Futures Reading Group).

As a tool for participatory engagement, this can be done in a number of different ways. Lead by Daniel Ari Friedman and Bleu Knight, the Active Inference Institute has taken the route of invited livestreams and summary podcasts. These materials introduce collaborators to difficult academic concepts while making them more accessible. While YouTube has options for live streaming, it is not always the best option. I use OBS Studio (free and open source) to compose a desktop recording and edit before making it public. 

Recorded meetings are also good for coding demos, particularly when they do not go as planned. One can either prepare a recording in advance to include in the meeting recording or strip the demo down to a minimal approach using a CoLab notebook. This reduces the friction of failed screenshares and execution errors, while also easing the burden of performing in front of a group.

Coding demos from a recent Saturday Morning NeuroSim meeting.

But completely virtual experiences are not the only option for bringing people together from around the world. OREL has been experimenting with hybrid meetings. This type of meeting brings the ethos of virtual meetings to more traditional in-person meetings. This enables more inclusive participation from distant geographical points. Last Spring, we experimented with our own virtual meeting experience at the New York Celebration of Women in Computing (NYCWiC), hosted live at Fort William Henry, NY. The hybrid session "Frontiers in Data Privacy and Tech Ethics" featured a buffet of topics on AI and technology ethics. Soem of the participants were live, while others were virtual (recorded or located in different parts of the globe). For this type of meeting, experimenting with ways to optimize live/virtual synchronization and media capture quality are essential. We plan to experiment with this more in the near future. 

Virtual (top) and in-person (bottom) components of the session.

Google Summer of Code 2022 in the OpenWorm Community (DevoWorm)

Welcome to Google Summer of Code 2022! I am pleased to announce that this year, we have two funded projects: D-GNNs and Digital Microspheres! These projects will both take place in conjunction with the DevoWorm part of the OpenWorm community. DevoWorm is an interdisciplinary group engaged in both computational and biological data analysis. We have weekly meetings on Jit.si, and are a part of the OpenWorm Foundation. 

This year, we were able to fund two students per project. They will be working on complementary solutions to each problem, and we will see how far they get by the end of the Summer. 

D-GNNs (Developmental Graph Neural Networks)

The description for this project is as follows:

Biological development features many different types of networks: neural connectomes, gene regulatory networks, interactome networks, and anatomical networks. Using cell tracking and high-resolution microscopy, we can reconstruct the origins of these networks in the early embryo. Building on our group's past work in deep learning and pre-trained models, we look to apply graph neural networks (GNNs) to developmental biological analysis.

The contributor will create graph embeddings that resemble actual biological networks found throughout development. Potential activities include growing graph embeddings using biological rules, differentiation of nodes in the network, and GNNs that generate different types of movement output based on movement seen in microscopy movies. The goal is to create a library of GNNs that can simulate developmental processes by analyzing time-series microscopy data.

When completed, D-GNNs will become part of the DevoWorm AI library. Ultimately, we will be integrating the GNN work with the DevoLearn (open-source pre-trained deep learning) software. 

Jiahang Li

Jiahang Li is a first year MPhil candidate in Computing Department at Hong Kong Polytechnic University. His research interests cover graph representation learning and its applications. Jiahang's approach to the project is to provide a pipeline that converts microscopic video data of C. elegans and other organisms into graph structures, on which advanced network analysis techniques and graph neural networks will be employed to obtain high-level representation of embryogenesis and to solve applied problems.

Wataru Kawakami

Wataru is a student at Kyoto University with interests in Machine Learning (in particular Graph Neural Networks) and Neuroimaging.

Digital Microspheres

The description for this problem is as follows: 

This project will build upon the specialized microscopy techniques to develop a shell composed of projected microscopy images, arranged to represent the full external surface of a sphere. This will allow us to create an atlas of the embryo’s outer surface, which in some species (e.g. Axolotl) enables us to have a novel perspective on neural development.

The contributor will build a computational tool that allows us to visualize 4D data derived from the surface of an Axolotl embryo. The spatial model and animation (4th dimension) of microscopy image data can be created in a 3-D modeling software of your choice.

This project is based on previous research by DevoWorm contributors Richard Gordon and Susan Crawford-Young. The flipping and ball microscopy research involve the design and fabrication of specialized microscopes to image embryos in a 4-D context (3 dimensions of space plus time).

Spherical Embryo Maps: Gordon, R. (2009). Google Embryo for Building Quantitative Understanding of an Embryo As It Builds Itself. II. Progress Toward an Embryo Surface Microscope. Biological Theory, 4, 396–412.

Flipping Microscopy: Crawford-Young, S., Dittapongpitch, S., Gordon, R., and Harrington, K. (2018). Acquisition and reconstruction of 4D surfaces of axolotl embryos with the flipping stage robotic microscope. Biosystems, 173, 214-220.

Ball Microscopy: Crawford-Young, S.J. and Young Williment, J.L. (2021). A ball microscope for viewing the entire surface of amphibian embryos. Biosystems, 208, 104498.

Karan Lohaan

Karan is a student at Amrita Vishwa Vidyapeetham University, and is a member of the AMFoss program there. He is interested in Machine Learning and Image Processing. 

Harikrishna Pillai

I am Harikrishna pursuing my B.Tech in Computer Science and Artificial Intelligence from Amrita Vishwa Vidyapeetham University. I completed my schooling in Mumbai. I started with python as my first language and eventually developed interest for AI. Due to my interest in Android apps, I have done Android development in Kotlin. Also, I have been interested in open source for some time now and therefore, I wanted to start my open source journey with GSoC.

We also have two GSoC mentors for these projects: Bradly Alicea is a mentor for D-GNNs and Digital Microspheres, and Jesse Parent is a mentor for D-GNNs. Richard Gordon and Susan Crawford-Young are serving as collaborators for the Digital Microspheres project.

If you would like to check on their progress, please check out our weekly meetings available on our YouTube channel.

MAIN and Neuromatch Conference Presentations

The Orthogonal Research and Education Lab is on the virtual move! We have been featured at two conferences this week. The first conference is MAIN (Montreal Artificial Intelligence-Neuroscience) conference, a hybrid conference that focused on cutting-edge research in Neuro-AI. Our submission (Developmental Embodied NeuroSimulation) is a group effort and summarizes our work in this area over the past few years. The graphical abstract can be found below.

Graphical Abstract for Developmental Embodied NeuroSimulation.

We also had a presence at Neuromatch 4, with four flash talk presentations on four different topics. Neuromatch 4 was a great time, with two days of keynote talks, short talks, flash talks, and debate panels. 

Each flash talk was 7.5 minutes long, which requires an efficiency of words and ideas not typical of a longer format. The first talk is "The Universal Theory of Switching", which focuses on transitory "switching" phenomena. Switching behavior is ubiquitous across biological, physical, and algorithmic systems, and is controlled by sudden, first-order phase transition-like behavior we characterize as zeroth-order cybernetic regulation. 

Another talk is on "Allostatic Kinds". Allostatic Kinds are a way to regulate the boundaries of meaning and regulation of internal emotional and conscious states. This talk is presented by Jesse Parent, and features a mix of complex systems regulation, philosophy of mind, and consciousness studies. This talk was in conjunction with CEEALAR (Center for Enabling EA Learning and Research), an academic hostel located in Blackpool, UK.

Daniela Cialfi has built upon the lab's work on Meta-brain Models to develop "Economic Meta-brains", which are bio-economic agents that behave according to the free energy principle. Meta-brains are layered computational models that enable different levels of representation in the same agent. These model layers can be configured in geometrically specific ways, which in turn affects their function. The free energy principle enriches the meta-brains approach by adding a mathematically rigorous energetic component to a meta-brain agent. 

Finally, our presentation on "Gibsonian Information" comes with a preprint. Gibsonian Information is the information content of direct perceptual processing (sensu J.J. Gibson). We draw parallels between Shannon and Gibsonian Information, in addition to the role of such information in the dynamic interactions between agents and their environments. See our graphical abstract below, which simplifies the mathematics in the preprint. The talk also features a number of naturalistic settings in which Gibsonian Information can be demonstrated.

Graphical abstract for the Gibsonian Information paper/presentation (direct perception as information content).

Multidimensional Chess Convoluted to a Pretty Picture

At last Monday's DevoWorm Group meeting, I gave a short lecture on ways to interpret multidimensional data using PCA, tSNE, and UMAP.  Here are the slides (below) and the YouTube link. The focus here is on Developmental Molecular Biology, but are generally useful, particularly for comparing methods. Here are the slides with a bonus from Leland McInnes, one of the originators of the UMAP technique!

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Welcome, Summer of Coders (2020)!

The Google Summer of Code selections for 2020 have been made! Congratulations to Ujjwal Singh and Mayukh Deb, who will be joining the OpenWorm Foundation and the DevoWorm group for a summer of community engagement and code. Ujjwal's project is called OpenDevoCell Integration, and here is the description:

This project will focus on improving the data science and machine learning infrastructure of the DevoWorm group. The work will focus on an extension of the Summer of Code projects completed in 2017 and 2019. The first two aims are to improve upon the OpenDevoCell web interface and to improve segmentation techniques overall. While the OpenDevoCell interface has been implemented as a Heroku app, we would like to develop a dashboard for interpretation as well as tighter integration with DevoZoo's collection of open-source microscopy data. The third aim is to deploy the code package as a unified Python library, which would be done in concert with the improvement of segmentation techniques.The priority for this Summer is to improve the web interface both in terms of interactivity and functionality. Ideally, we would like to provide users with multiple options for analysis. This includes the ability to incorporate new forms of analysis as well as algorithms for new types of data. Currently, our web app is optimized for microscopy images acquired using the SPIM technique. However, we would also like to segment microscopy images acquired using a wide range of technologies. Feeding into this is the ability to segment and obtain features for the data in our DevoZoo. The ability to extract quantitative data from these movie images is key to conducting the comparative and time-series analysis. The development of a dashboard would ideally enable users to employ various machine learning and simulation techniques in one place.These improvements are meant to increase participation in our open science initiative and make sophisticated analytical techniques more accessible to students and potential collaborators alike. 

Mayukh's project is called Pre-trained Models for Developmental Neuroscience, and is based on previous work done in the group during the DevoWormML course [1]. This project is described thusly:

This project will center around building a pre-trained model for shapes and processes related to Developmental Biology and Neurobiology and extracted from image data. Our organization's Machine Learning interest group (DevoWormML) has published a blog post [1] on the advantages and need for pre-trained models in this area. In short, biological development is characterized by characteristic shapes, movements, changes in shape, and temporal processes that define important features. Pre-trained models are used in NLP and Deep Learning for the domains of sequence discovery in language processing (GPT-2) and bounding box methods for segmenting complex images (DeepLabv3). Models specialized for biology, however, do not exist. A suitable pre-trained model would greatly reduce the need for input data without sacrificing the ability to generalize to different contexts.Our main interest is in extracting spatiotemporal features from image data. We will focus on microscopy data such as that found in the DevoZoo or from more specialized sources [2]. For a typical pre-trained model, the network is pre-trained with non-random weights that approximate the generalized versions of the features we would like to discover. However, we are also interested in a semantic component, particularly the ability to incorporate elements such as meaning assigned to static knowledge (semantics) and multiple meanings for a single feature (polysemy). This will enable relational modeling and the mapping of segmented image data to lineage trees and taxonomies. This will enable relational modeling and the mapping of segmented image data to lineage trees and taxonomies. Our model, tentatively called DevLearningv1, should be applicable to a wide range of neural network and deep learning techniques.

Thanks to INCF for sponsoring our activities once again this year. Thanks also go to Vinay Varma, who will be providing support on all things mentorship this summer. Vinay was a GSoC student last summer, and will be sharing his wisdom with this year's students. I would also like to invite all those who applied for these projects to contribute to the Organization in some other way. Often, interaction with the community now can lead to additional opportunities down the road. 

As for the Orthogonal Research and Education Lab project (Contextual Neurodevelopmental Dynamics), we unfortunately did not get any slots this year. Thanks to Ankit Gupta and Jesse Parent for their excellent proposals. But I would like to continue pursuing the initiative as an open-source effort, hopefully leading to other avenues for development and funding. The same community interaction advice given for OpenWorm applies to Orthogonal Lab as well. 

We are going to be developing in the Meta-Brain repository on Github. Be sure to check out our Saturday Morning NeuroSim meetings for more information on this project (join our mailing list!). And register for the Neuromatch Summer School if you have not already, as it will be quite relevant to what we will be doing.

A sample of Saturday Morning NeuroSim (with a recap of the ICLR conference). Click to enlarge.

UPDATE (5/5): One of our regular meeting attendees (Devansh Batra) has also received a Google Summer of Code position with the OpenCV organization. Congrats!

NOTES:

[1] Alicea, B., Gordon, R., Kohrmann, A., Parent, J., and Varma, V. (2019). Pre-trained Machine Learning Models for Developmental Biology. The Node blog, October 29.