Beyond human perception: challenges in AI interpretability of orangutan artwork.

Drawings serve as a profound medium of expression for both humans and apes, offering unique insights into the cognitive and emotional landscapes of the artists, regardless of their species. This study employs artificial intelligence (AI), specifically Convolutional Neural Networks (CNNs) and the interpretability tool Captum, to analyse non-figurative drawings by Molly, an orangutan. The research utilizes VGG19 and ResNet18 models to decode seasonal nuances in the drawings, achieving notable accuracy in seasonal classification and revealing complex influences beyond human-centric methods.

Epoxyeicosatrienoic acids (EETs): A novel class of second messengers of hormonal functional responses.

Epoxyeicosatrienoic acids (EETs) are a class of cytochrome P450 (P450) arachidonic acid (AA) metabolites with diverse biological activities including anti-hypertensive, vasodilatory, angiogenic, and anti-inflammatory properties. While their functions as autocrine and paracrine mediators in cardiovascular and renal systems are well established, their mechanism of action and roles in hormonal functional responses are yet to be fully defined. In this review, we highlight extant evidence of their participation in hormonal transmembrane signal transduction leading to the activation of the ERK1/2 or Akt serine/threonine kinases.

A comparison of force adaptation in toddlers and adults during a drawer opening task.

Adapting movements to rapidly changing conditions is fundamental for interacting with our dynamic environment. This adaptability relies on internal models that predict and evaluate sensory outcomes to adjust motor commands. Even infants anticipate object properties for efficient grasping, suggesting the use of internal models.

Community-based reconstruction and simulation of a full-scale model of the rat hippocampus CA1 region.

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, it has been challenging to integrate information obtained from diverse experimental approaches. To address this challenge, we present a community-based, full-scale in silico model of the rat CA1 that integrates a broad range of experimental data, from synapse to network, including the reconstruction of its principal afferents, the Schaffer collaterals, and a model of the effects that acetylcholine has on the system.