Building artificial neural circuits for domain-general cognition: a primer on brain-inspired systems-level architecture. - Jascha Achterberg; Danyal Akarca; Moataz Assem; Moritz P. Heimbach; Duncan E. Astle; John Duncan (CoRR, 2023)

Brain-inspired learning in artificial neural networks: a review. - Samuel Schmidgall; Jascha Achterberg; Thomas Miconi; Louis Kirsch; Rojin Ziaei; S. Pardis Hajiseyedrazi; Jason Eshraghian (CoRR, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings. - Jascha Achterberg; Danyal Akarca; D. J. Strouse; John Duncan; Duncan E. Astle (Nat. Mac. Intell., 2023)

Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience. - Zhonghao He; Jascha Achterberg; Katie Collins; Kevin K. Nejad; Danyal Akarca; Yinzhu Yang; Wes Gurnee; Ilia Sucholutsky; Yuhan Tang; Rebeca Ianov; George Ogden; Chole Li; et al. (CoRR, 2024)

Spatial embedding promotes a specific form of modularity with low entropy and heterogeneous spectral dynamics. - Cornelia Sheeran; Andrew S. Ham; Duncan E. Astle; Jascha Achterberg; Danyal Akarca (CoRR, 2024)

Dynamical similarity analysis uniquely captures how computations develop in RNNs. - Quentin Guilhot; Jascha Achterberg; Michal Wójcik; Rui Ponte Costa (CoRR, 2024)

Accelerated AI Inference via Dynamic Execution Methods. - Haim Barad; Jascha Achterberg; Tien Pei Chou; Jean Yu (CoRR, 2024)

Brain-Like Processing Pathways Form in Models With Heterogeneous Experts. - Jack Cook; Danyal Akarca; Rui Ponte Costa; Jascha Achterberg (CoRR, 2025)