Evolution of evolvability for neuroevolution

Scientists have been in awe of the powers of evolution since comprehending the fundamental principles of natural selection. As Darwin eloquently put it, nature has given rise to “endless forms most beautiful”. However, beyond the mesmerizing beauty of nature, lies an even more fascinating aspect - the creation of human intelligence. Although AI research has produced impressive outcomes in the past decade, the techniques employed to accomplish these outcomes diverge considerably from the natural process of brain evolution. The primary dissimilarity stems from the fact that nature employs the evolution of DNA code, which encodes the instructions for brain development, whereas mainstream AI represents all brain parameters directly. This disparity is noteworthy as the indirect representation utilized by nature confers upon it a potent ability to enhance evolvability over time, a feature that is absent in direct representation. This potential stems from the ability to choose instructions in a manner that renders the brain resistant to change in certain directions while facilitating easy modification in other directions. The present thesis delves into the potential of leveraging indirect encoding and evolvability during the neural network evolution process. To this end, we propose two algorithms, namely Quality Evolvability ES and Evolvability Map Elites, which enable direct selection for evolvability. We conduct an evaluation of the efficacy of these algorithms in the context of robotics locomotion tasks. Additionally, we investigate the necessary conditions for indirect encoding to be useful for learning and conduct experiments to verify our hypothesis in the domain of image recognition task

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata

Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells. Recent developments in NCAs lie in the 2D domain, namely reconstructing target images from a single pixel or infinitely growing 2D textures. In this work, we propose an extension of NCAs to 3D, utilizing 3D convolutions in the proposed neural network architecture. Minecraft is selected as the environment for our automaton since it allows the generation of both static structures and moving machines. We show that despite their simplicity, NCAs are capable of growing complex entities such as castles, apartment blocks, and trees, some of which are composed of over 3,000 blocks. Additionally, when trained for regeneration, the system is able to regrow parts of simple functional machines, significantly expanding the capabilities of simulated morphogenetic systems. The code for the experiment in this paper can be found at: https://github.com/real-itu/3d-artefacts-nca

Raman-assisted crystallography reveals end-on peroxide intermediates in a nonheme iron enzyme.

International audienceIron-peroxide intermediates are central in the reaction cycle of many iron-containing biomolecules. We trapped iron(III)-(hydro)peroxo species in crystals of superoxide reductase (SOR), a nonheme mononuclear iron enzyme that scavenges superoxide radicals. X-ray diffraction data at 1.95 angstrom resolution and Raman spectra recorded in crystallo revealed iron-(hydro)peroxo intermediates with the (hydro)peroxo group bound end-on. The dynamic SOR active site promotes the formation of transient hydrogen bond networks, which presumably assist the cleavage of the iron-oxygen bond in order to release the reaction product, hydrogen peroxide

IP3 receptor isoforms differently regulate ER-mitochondrial contacts and local calcium transfer

Contact sites of endoplasmic reticulum (ER) and mitochondria locally convey calcium signals between the IP3 receptors (IP3R) and the mitochondrial calcium uniporter, and are central to cell survival. It remains unclear whether IP3Rs also have a structural role in contact formation and whether the different IP3R isoforms have redundant functions. Using an IP3R-deficient cell model rescued with each of the three IP3R isoforms and an array of super-resolution and ultrastructural approaches we demonstrate that IP3Rs are required for maintaining ER-mitochondrial contacts. This role is independent of calcium fluxes. We also show that, while each isoform can support contacts, type 2 IP3R is the most effective in delivering calcium to the mitochondria. Thus, these studies reveal a non-canonical, structural role for the IP3Rs and direct attention towards the type 2 IP3R that was previously neglected in the context of ER-mitochondrial calcium signaling

Cortex-wide response mode of VIP-expressing inhibitory neurons by reward and punishment

Neocortex is classically divided into distinct areas, each specializing in different function, but all could benefit from reinforcement feedback to inform and update local processing. Yet it remains elusive how global signals like reward and punishment are represented in local cortical computations. Previously, we identified a cortical neuron type, vasoactive intestinal polypeptide (VIP)-expressing interneurons, in auditory cortex that is recruited by behavioral reinforcers and mediates disinhibitory control by inhibiting other inhibitory neurons. As the same disinhibitory cortical circuit is present virtually throughout cortex, we wondered whether VIP neurons are likewise recruited by reinforcers throughout cortex. We monitored VIP neural activity in dozens of cortical regions using three-dimensional random access two-photon microscopy and fiber photometry while mice learned an auditory discrimination task. We found that reward and punishment during initial learning produce rapid, cortex-wide activation of most VIP interneurons. This global recruitment mode showed variations in temporal dynamics in individual neurons and across areas. Neither the weak sensory tuning of VIP interneurons in visual cortex nor their arousal state modulation was fully predictive of reinforcer responses. We suggest that the global response mode of cortical VIP interneurons supports a cell-type-specific circuit mechanism by which organism-level information about reinforcers regulates local circuit processing and plasticity