8 papers
Task-guided cross-subject latent alignment: a multi-encoder-decoder VAE
Angeliki Papathanasiou, Jascha Achterberg, Thomas E. Nichols +1
Aligning neural activity across subjects offers the promise of discovering shared computational principles and generalizable decoders. However, traditional alignment methods requir…
Algorithm-hardware co-design of neuromorphic networks with dual memory pathways
Pengfei Sun, Zhe Su, Jascha Achterberg +3
Spiking neural networks excel at event-driven sensing. Yet, maintaining task-relevant context over long timescales both algorithmically and in hardware, while respecting both tight…
The Principle of Maximum Heterogeneity Optimises Productivity in Distributed Production Systems Across Biology, Economics, and Computing
Guillhem Artis, Danyal Akarca, Jascha Achterberg
The world is full of systems of distributed agents, collaborating and competing in complex ways: firms and workers specialise within economies, neurons adapt their tuning across br…
Brain-Like Processing Pathways Form in Models With Heterogeneous Experts
Jack Cook, Danyal Akarca, Rui Ponte Costa +1
The brain is made up of a vast set of heterogeneous regions that dynamically organize into pathways as a function of task demands. Examples of such pathways can be found in the int…
Exploiting heterogeneous delays for efficient computation in low-bit neural networks
Pengfei Sun, Jascha Achterberg, Zhe Su +2
Neural networks rely on learning synaptic weights. However, this overlooks other neural parameters that can also be learned and may be utilized by the brain. One such parameter is…
Dynamical similarity analysis can identify compositional dynamics developing in RNNs
Quentin Guilhot, MichaŠWójcik, Jascha Achterberg +1
Methods for analyzing representations in neural systems have become a popular tool in both neuroscience and mechanistic interpretability. Having measures to compare how similar act…