AREADNE 2024: Research in Encoding and Decoding of Neural Ensembles

In late June 2024, I had the pleasure of attending the “Research in Encoding And Decoding of Neural Ensembles” (AREADNE) conference, held on the Greek island of Milos.

A Conference Built for Discussion

AREADNE is held on a comparatively small scale (~100 participants) and is deliberately designed to engage all attendees in discussion and community building. Each of the four days featured two oral sessions, interspersed with a long afternoon break that gave participants time to meet one another, share their research, and explore the island. It was a refreshing contrast to large conferences where it can be hard to have meaningful conversations.

Sunset Poster Sessions

The poster sessions, held outdoors at sunset after the evening talks, created a truly unique atmosphere. The setting made discussions feel relaxed and genuinely enjoyable. Science at golden hour on a Greek island is hard to beat.

One particularly democratic aspect of AREADNE: essentially every participant is required to give a poster presentation, regardless of career stage. This made it easy for early-career scientists to get in touch with leading researchers in the field. I presented my work on the functional organisation of visual input in the superior colliculus.

Scientific Highlights

The conference’s focus on new and largely unpublished research contributed to the interactive, discussion-friendly atmosphere. Some personal highlights:

• Martin Usrey gave a talk on how spikes are transmitted through the LGN from the retina to the visual cortex.
• Haim Sompolinsky presented work on the separability of representational manifolds at different layers in deep neural networks, and the alignment of representations across modalities (visual and language models).
• Gilles Laurent presented his argument for studying intelligence in species beyond the usual suspects, illustrated beautifully with ongoing work on cuttlefish and their remarkable camouflage behaviour.
• Anthony Zador discussed the future of neuroscience and AI, including the ethical implications and the importance of passing information across generations through the genetic bottleneck as a mechanism for faster learning.

Overall Impressions

AREADNE was a genuinely great experience, both scientifically and in terms of community building. As a PhD student, it was particularly motivating to engage so directly with leading researchers in an environment that felt open and collaborative rather than hierarchical. I would highly recommend it to anyone working in systems or computational neuroscience.