Neuroscience

eLife Assessment

This work of fundamental significance introduces a novel statistical model of spiking activity that incorporates continuous-time gain modulation. The authors provide exceptional evidence that the model outperforms earlier approaches and alternative candidates in capturing spiking responses across multiple visual areas in the macaque. Beyond its methodological contribution, the study offers new insights into how stimulus-driven variability and internally generated gain fluctuations evolve over time and between brain areas. The framework is likely to find broad application beyond the datasets examined here.

eLife Assessment

This valuable study demonstrates how individual taste preferences shift over time, how these changes relate to cortical activity, and how experience reshapes both. The evidence is largely solid, although additional analyses are needed to strengthen some of the conclusions. The results should be of interest to neuroscientists studying sensory physiology.

eLife Assessment

This study presents valuable insights into cellular sites of monoamine production and presence in Pristionchus pacificus, providing a comparative reference for the detailed knowledge of C. elegans, as well as using this information to compare serotonergic anatomy in 22 nematode species. Functional assays support evolved differences in monoaminergic control over certain, but not all, tested behaviors. The evidence is convincing, combining careful genetic experiments and comparative analysis that are well aligned with the conclusions. The results will serve as a basis for (comparative) structural-functional studies of nematode behavior.

eLife Assessment

This study presents valuable findings on how retrieval practice protects memory inferences from stress via covert memory reactivation. Via two EEG experiments manipulating stress and retrieval practice, the authors provide solid evidence supporting the conclusion. This work will be of interest to cognitive and affective neuroscientists working on the intersection between memory and stress.

eLife Assessment

This study presents valuable findings on the ability of a state-of-the-art method, Temporally Delayed Linear Modelling (TDLM), to detect the replay of sequences in human memory. The investigation provides compelling evidence that TDLM has significant limitations in its sensitivity to detect replay in extended (minutes-long) rest periods. The work will be of strong interest to researchers investigating memory reactivation in humans, especially using iEEG, MEG, and EEG.

eLife Assessment

Karimian et al. present a valuable new model to explain how gamma-band synchrony (30-80 Hz) can support human visual feature binding by selectively grouping image elements, countering recent criticisms that the stimulus dependence of gamma oscillations limits their functional role. Grounded in the theory of weakly coupled oscillators the model captures behavioural patterns observed in human psychophysics, offering support for the potential role of synchrony-based mechanisms in feature-binding. The development of the model in alignment with primate electrophysiology convincingly supports the paper's claims that gamma synchrony may be the underlying mechanism. While the paper does not present electrophysiological results that directly link gamma oscillations to figure-ground segregation in the presented task, the model makes several predictions that can be tested experimentally.

eLife Assessment

This paper describes an important advance in a 2D in vitro neural culture system to generate mature, functional, diverse, and geometrically consistent cultures, in a 384-well format with defined dimensions and the absence of the necrotic core, which persists for up to 300 days. The well-based format and conserved geometry make it a promising tool for arrayed screening studies. The evidence is compelling and provides a method for generating consistent 3D cortical layer-like organization.

eLife Assessment

This study presents a valuable finding on the neural representation of time from two distinct egocentric and allocentric reference frames. The evidence is solid and largely supports the hypothesis, with one caveat that the task differences could impact the observed effects. The work will be of interest to cognitive neuroscientists working on the perception and memory of time.

eLife Assessment

This study presents a valuable contribution by introducing a model-based, Bayesian method for inferring action potentials from calcium imaging data that directly quantifies uncertainty in spike timing through posterior distributions. Using a Monte Carlo particle Gibbs sampling approach, the method achieves temporal resolution and accuracy comparable to existing techniques while offering the key added benefit of principled uncertainty estimates. The underlying methodology and characterization are convincing, and the work will be of particular interest to theoretically oriented neuroscientists seeking rigorous new tools for data-driven parameter inference.

eLife Assessment

This fundamental study investigates whether neural prediction of words can be measured through pre-activation of neural network word representations in the brain; convincing evidence is provided that neural network representations of neighboring words are correlated in natural language. This study urges future studies to carefully differentiate between neural activity that predicts the upcoming word and neural activity that encodes the current words, which contain information that can be used to predict the upcoming word. The study is of potential interest to researchers investigating language encoding in the brain or in large language models.