Neuroscience

eLife Assessment

Using fMRI-based pRF mapping, this important study presents a novel method to estimate visual field (VF) and VF loss/or potential restoration, through analysis of contrast sensitivity patterns in the early visual cortex. While the approach is very interesting and the evidence supporting the claims of the authors is solid, some methodological concerns need to be addressed. The work will be of interest to researchers in vision/clinical vision, neuroscience, and brain imaging.

eLife Assessment

This valuable study shows that an odorant that is typically thought of as a repellant actually activates both attractant and repellant olfactory neurons in C. elegans. Solid evidence is provided that nematode worms can integrate signals using different pathways to drive different behavioral responses to the same cue. These findings will be of interest to scientists interested in combinatorial coding in sensory systems.

eLife Assessment

This is a convincing study of the morphological properties of Purkinje cell dendrites and dendritic spines in adult humans and mice, and the anatomical determinants of multi-innervation by climbing fibers. The data will provide an important resource for the field of cerebellar computation.

eLife Assessment

This important Research Advance presents compelling evidence on the neuroprotective effects of reserpine in a well-established model of retinitis pigmentosa (P23H-1). This study builds on previous work establishing reserpine as a neuroprotectant in models of Leber congenital amaurosis. Here authors show reserpine's disease gene-independent influence on photoreceptor survival and emphasizes the importance of considering biological sex in understanding inherited retinal degeneration and the impact of drug treatments on mutant retinas. The work will be of interest to vision researchers as well as a broad audience in translational research.

eLife Assessment

In this important and compelling study, Sánchez-León et al. investigate the effects of tDCS on the firing of single cerebellar neurons in awake and anesthetized mice. They find heterogeneous responses depending on the orientation of the recorded Purkinje cell. The paper may well explain part of the controversial and ambiguous outcomes of various clinical trials.

eLife Assessment

This important study provides significant insights into the dynamics of attentional re-orienting within visual working memory, demonstrating how expected and unexpected memory tests influence attention focus and re-focus. The evidence supporting these conclusions is convincing, with the use of state-of-the-art methodologies. This work will be of interest to cognitive neuroscientists studying attention and memory.

eLife Assessment

This valuable study uses state-of-the-art neural encoding and video reconstruction methods to achieve a substantial improvement in video reconstruction quality from mouse neural data, providing a convincing demonstration of how reconstruction performance can be improved by combining these methods. The findings showed that model ensembling and the number of neurons used for reconstruction were key determinants of reconstruction accuracy, but the theoretical contribution to understanding neural encoding was less clear. The treatment of how image masking improved reconstruction performance was also incomplete.

eLife Assessment

This manuscript provides valuable novel insights into the role of interpersonal guilt in social decision-making by showing that responsibility for a partner's bad lottery outcomes influences happiness. Through the integration of neuroimaging and computational modelling methods, and by combining findings from two studies, the authors provide solid support for their claims.

eLife Assessment

This paper provides an important proposal for why learning can be much faster and more accurate if synapses have a fast component that immediately corrects errors, as well as a slower component that corrects behavior averaged over a longer timescale. It is convincingly shown that integrating these two learning timescales improves performance compared to classical strategies, particularly in terms of robustness and generalization when learning new target signals. However, the biological plausibility and justification for the proposed rapid learning mechanism require further elaboration and supporting mechanistic examples.

eLife Assessment

This useful study introduces a deep learning-based algorithm that tracks animal postures with reduced drift by incorporating transformers for more robust keypoint detection. The efficacy of this new algorithm for single-animal pose estimation was demonstrated through comparisons with two popular algorithms. The strength of evidence is solid but would benefit from consideration of issues in multi-animal tracking. This work will be of interest to those interested in animal behavior tracking.