Publications associées à Animal language

Driving and suppressing the human language network using large language models

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

Nature Portfolio2024

Beyond undulation! Body morphology and sensing components of elongated animals and robots reveal skills to maintain competent locomotion

Laura Isabel Paez Coy

Locomotion is an essential evolutive innovation of living beings that allows them to colonize and dominate the planet. As diverse as animal morphologies are (living) and were (extinct), their locomotion modalities are also diverse. In particular, animal mo ...

EPFL2023

No need to shout: Effect of signal loudness on sibling communication in barn owls

Hervé Lissek, Xavier Falourd, Patrick Marmaroli

In animal communication, signal loudness is often ignored and seldom measured. We used a playback experiment to examine the role of vocal loudness (i.e., sound pressure level) in sibling to sibling communication of nestling barn owls Tyto alba. In this spe ...

2017

Detection of Optogenetic Stimulation in Somatosensory Cortex by Non-Human Primates - Towards Artificial Tactile Sensation

Fabien Bertrand Paul Wagner, David Allenson Borton

Neuroprosthesis research aims to enable communication between the brain and external assistive devices while restoring lost functionality such as occurs from stroke, spinal cord injury or neurodegenerative diseases. In future closed-loop sensorimotor prost ...

Public Library of Science2014

A Robotic System for Quantitative Assessment and Poststroke Training of Forelimb Retraction in Mice

Silvestro Micera

Background. Neurorehabilitation protocols based on the use of robotic devices have recently shown to provide promising clinical results. However, their efficacy is still limited because of the poor comprehension of the mechanisms at the basis of functional ...

Sage Publications Inc2014

Decoding the mechanisms of gait generation in salamanders by combining neurobiology, modeling and robotics

Auke Ijspeert, Andrej Bicanski, Jérémie Knüsel

Vertebrate animals exhibit impressive locomotor skills. These locomotor skills are due to the complex interactions between the environment, the musculo-skeletal system and the central nervous system, in particular the spinal locomotor circuits. We are inte ...

Springer Berlin Heidelberg2013

From lamprey to salamander: an exploratory modeling study on the architecture of the spinal locomotor networks in the salamander

Auke Ijspeert, Andrej Bicanski

The evolutionary transition from water to land required new locomotor modes and corresponding adjustments of the spinal "central pattern generators" for locomotion. Salamanders resemble the first terrestrial tetrapods and represent a key animal for the stu ...

Springer Berlin Heidelberg2013

Real-Time Noninvasive Imaging of Fatty Acid Uptake in Vivo

Gennady Nikitin

Detection and quantification of fatty acid fluxes in animal model systems following physiological, pathological, or pharmacological challenges is key to our understanding of complex metabolic networks as these macronutrients also activate transcription fac ...

American Chemical Society2012

Relatedness influences signal reliability in evolving robots

Dario Floreano, Laurent Keller, Sara Mitri

Communication is an indispensable component of animal societies, yet many open questions remain regarding the factors affecting the evolution and reliability of signalling systems. A potentially important factor is the level of genetic relatedness between ...

2011

Effects of stress and genotype on meta-parameter dynamics in reinforcement learning

Wulfram Gerstner, Maria del Carmen Sandi Perez, Gediminas Luksys, Jérémie Knüsel

Stress and genetic background regulate different aspects of behavioral learning through the action of stress hormones and neuromodulators. In reinforcement learning (RL) models, meta-parameters such as learning rate, future reward discount factor, and expl ...

2007

Evolving Neuromodulatory Topologies for Reinforcement Learning-like Problems

Dario Floreano, Claudio Mattiussi, Peter Dürr

Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advantage. Recent studies suggest that neuromodulatory dynamics are a key factor in reg ...

IEEE Press2007