Neuroscience

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.

eLife Assessment

This important study by Liu et al. presents a comprehensive structure-function analysis of the presynaptic protein UNC-13, leading to new insights into how its distinct domains control neurotransmitter release. The methods, data, and analyses are convincing, and the genetic and electrophysiological approaches support many of their conclusions. The work will be of interest to neuroscientists studying synaptic transmission, as it provides a foundation for future mechanistic studies of Munc13/UNC-13 family proteins.

eLife Assessment

This study provides a valuable contribution to our understanding of causal inference in visual perception. The evidence provided through multiple well-designed psychophysical experiments is convincing. The current study targets very specific visual features of launch events, future work will be able to build on this to study the implementation of causal inference in general.

eLife Assessment

This study presents a valuable open-source and cost-effective method for automating the quantification of male aggression and courtship in Drosophila melanogaster. The work as presented provides solid evidence that the use of the behavioral setup that the authors designed - using readily available laboratory equipment and standardised high-performing classifiers they developed using existing software packages - accurately and reliably characterises social behavior in Drosophila. The work will be of interest to Drosophila neurobiologists and particularly to those working on male social behaviors.

eLife Assessment

This paper explores how diverse forms of inhibition impact firing rates in models for cortical circuits. In particular, the paper studies how the network operating point affects the balance of direct inhibition from SOM inhibitory neurons to pyramidal cells, and disinhibition from SOM inhibitory input to PV inhibitory neurons. This is an important issue as these two inhibitory pathways have largely been studied in isolation. A combination of analytical calculations and direct numerical simulations provides convincing evidence that the interplay of these inhibitory circuits can separately control network gain and stability.

eLife assessment

Using intracellular in vitro and in vivo recordings and a deep learning approach, this study shows that mouse dentate gyrus mossy cells (MCs) and CA3 pyramidal cells process information from an important electrophysiological hall mark of hippocampus, sharp wave-ripples (SWRs). The innovative use of deep learning to predict SWR waveforms from MC membrane potentials represents an interesting methodological advance. While the key findings are potentially fundamental, some of the evidence is currently incomplete and should be revised to better support the findings.

eLife Assessment

This manuscript presents a potentially important strategy for stimulating mammalian Müller glia to proliferate in vivo by manipulating cell cycle components. The results are convincing that a large number of Müller glia can be induced to re-enter the cell cycle without a damage stimulus. These findings are likely to appeal to retinal biologists and neuroscientists in general.

eLife Assessment

This valuable study presents a computational model that simulates walking motions in Drosophila and suggests that, if sensorimotor delays in the neural circuitry were any longer, the system would be easily destabilized by external perturbations. The hierarchical control model is sensible and the evidence supporting the conclusions convincing. The modular model, which has many interacting components with varying degrees of biological realism, will serve as a well-grounded starting point for future studies that incorporate richer or more complete empirical data.

eLife Assessment

This important study shows a surprising scale-invariance of the covariance spectrum of large-scale recordings in the zebrafish brain in vivo. A convincing analysis demonstrates that a Euclidean random matrix model of the covariance matrix recapitulates these properties. The results provide several new and insightful approaches for probing large-scale neural recordings.