Projects & Publications

The goal of my work is to uncover the computational principles that enable intelligence in both biological and artificial systems at scale. I investigate how the brain's distributed architecture produces flexible cognition and translate these insights into novel algorithms and computing systems. My empirical work draws on neuroimaging data of the developing brain, large-scale human decision-making datasets, and single-cell recordings in non-human primates to understand the organizational principles of neural circuits. From theoretical models to hardware prototypes, I work across the full pipeline of translating these insights into practical systems—developing specialized computing architectures that implement brain-inspired connectivity patterns and designing how networks of processors and hardware components interact. This allows me to test these designs against conventional architectures and identify which biological features provide specific computational advantages.

Some of my ideas on brain-inspired system architecture for algorithms are described in the paper: Building artificial neural circuits for domain-general cognition: a primer on brain-inspired systems-level architecture https://arxiv.org/abs/2303.13651, with additional discussion of computing hardware applications covered in my PhD thesis.

Ongoing

Note that some example projects are highlighted with dedicated subpages under 'Project Summaries'. More generally, my current focus is on the following projects:

• I started work on a new theoretical piece on identifying joint computational principles underlying distributed computations in brains and silicon chips. This is at an early stage but a first preprint should be out soon, with more work to follow early 2026. If this is of interest to you, please reach out!

• We have recently expanded Mixture of Experts architectures to follow a more brain-inspired system-level architecture, as we describe in our recent preprint: Mixture of Pathways

• Uncovering the neuronal algorithms underlying structural inference and reasoning in a large population of PFC neurons. 

  • Link to the preprint and a project overview can be found here: Maze project

• We introduced the new spatially-embedded Recurrent Neural Network model which can recapitulate numerous neuroscientific findings, from large scale connectome structure down to functional codes used by single neurons. We are in the process of expanding this model with further biophysical constrains and a theoretical analysis of dynamics for optimising network communication. 

  • See details of project here

Selected publications

• Artificial neural networks: Achterberg, J., Akarca, D., Strouse D., Duncan, J. & Astle, D (2023, preprint). Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings. Nature Machine Intelligence. doi: https://www.nature.com/articles/s42256-023-00748-9 

  • I gave a seminar on this paper at SNUFA: https://www.youtube.com/watch?v=DaG92jBCu68&t 

• Highly functional biological networks: Achterberg, J., Kadohisa, M., Watanabe, K., Kusunoki, M., Buckley, M., & Duncan, J. (2021). A One-Shot Shift from Explore to Exploit in Monkey Prefrontal Cortex. The Journal Of Neuroscience, 42(2), 276-287. doi: 10.1523/JNEUROSCI.1338-21.2021 

• Human decision making: Ruggeri, K., Panin, A., Vdovic, M., Veckalov, B., Abdul-Salaam, N, Achterberg, J., [...], & Garcia-Garzon, E. (2022). The globalizability of temporal discounting. Nature Human Behaviour doi: 10.1038/s41562-022-01392-w 

All academic publications

A complete list of my academic publications is available on my Google Scholar profile.

Other publications

• "Domain-general cognition in brains and artificial neural networks". Jascha Achterberg. Presentation and interview as part of the Researcher App Series on AI in Neuroscience 2023. Recording available on: https://www.researcher-app.com/paper/14604093 

• “Intelligence in brain and machines”. Jascha Achterberg. Short video for the Cambridge Science Festival 2021. Hosted on YouTube.

• “Want to Build Intelligent Machines? Mind the Brain!”. Jascha Achterberg. Article in the 2020 version of Gates Cambridge’s magazine “The Scholar”