activity
20222026
most citedIAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimation

10 citations · 10 across the 8 of their papers we have counts for

collaborators
Showing q-bio.NCShow all

5 papers · 1 filter

q-bio.NC2026

Decoding Alignment without Encoding Alignment: A critique of similarity analysis in neuroscience

Johannes Bertram, Luciano Dyballa, T. Anderson Keller +2

Decoding approaches are widely used in neuroscience and machine learning to compare stimulus representations across neural systems, such as different brain regions, organisms, and…

q-bio.NC2026

Inferring Active Neural Circuits Using Diffusion Scores

Savik Kinger, Johannes Bertram, Luciano Dyballa +2

In biological systems, neural circuits compute through directed, short-latency interactions whose effects unfold across multiple time scales and behavioral contexts. We address the…

q-bio.NC2026

How 'Neural' is a Neural Foundation Model?

Johannes Bertram, Luciano Dyballa, Anderson Keller +2

Foundation models have shown remarkable success in fitting biological visual systems; however, their black-box nature inherently limits their utility for understanding brain functi…

q-bio.NC2025

Manifolds and Modules: How Function Develops in a Neural Foundation Model

Johannes Bertram, Luciano Dyballa, T. Anderson Keller +2

Foundation models have shown remarkable success in fitting biological visual systems; however, their black-box nature inherently limits their utility for understanding brain functi…

q-bio.NC2024

Learning dynamic representations of the functional connectome in neurobiological networks

Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley +2

The static synaptic connectivity of neuronal circuits stands in direct contrast to the dynamics of their function. As in changing community interactions, different neurons can part…