AI-driven Neuroethology: towards new frontiers in neuroscience

The rapid technological advancements of the 21st century offer unprecedented opportunities to study the brain. By merging neuro-technologies with artificial intelligence (AI), we can pioneer a new class of research: longitudinal neuroethology. This paradigm allow us to study the brain during innate and instinctive behaviors over extended periods, from weeks to years. AI and neuro-technologies facilitate the creation of large-scale, novel datasets, and enable the study of neural computation and the ontology of diseases. Moreover, the tools will help reduce animal use and enhance their well-being via enriched and increasingly natural environments.

At Netholabs, we are dedicated to advancing several key areas:

Mechatronics and Robotics: Building naturalistic home environments and open arenas.
Automation: Streamlining neural and behavior recordings and data processing to minimize animal stress and human interaction.
Deep Learning: Developing foundation models and AI methods for analyzing behavior and neural time series.

We are currently hiring for our teams in London and Berlin. If you are passionate about neuroscience and AI, reach out.

Neuroethology for psychiatric disease research

Complex brain disorders like schizophrenia (SZ) have polygenic roots but manifest as cognitive disorders, such as impairments in the sense of agency (SoA) over thoughts and actions. Understanding how the brain computes SoA during natural behaviors can unveil new insights into the anatomical and functional circuits involved in SZ, which are often elusive in genetic studies alone.

Our approach integrates and standardizes neuro-technologies to study both healthy models and disorder models using neuroethological paradigms.

Whole-Brain-Emulation (WBE): a path to digitized rodent models

Neuroethology frameworks will increasingly enable the generation of platforms for whole-brain-emulation (WBE): i.e. measuring, modeling and emulating biological nervous systems in digital environments.

WBE paradigms are theoretically and experimentally sound and can provide a new way to conceptualize neural dynamics from the whole-organism perspective. Emulators - or digital models of animals - can advance our scientific knowledge while decreasing the burden on research animals.

Our preprint on Emulator Theory is out now: arxiv.