Neuroscience

eLife Assessment

This study presents valuable findings on the neuromodulatory underpinnings of adaptive learning in dynamic, probabilistic environments. Solid evidence for these claims comes from showing spatial correlations between model-derived fMRI responses and PET-based receptor density maps. The work will be of interest to cognitive and systems neuroscientists working on decision-making.

eLife Assessment

This useful study combines behavioral reports, EEG decoding, and computational modeling to address an interesting question: how delay-period distractors bias working-memory representations, and how these effects depend on target relevance, distractor location, and the strength of memory maintenance and distractor encoding. However, the supporting evidence is incomplete, as several key claims require clearer statistical tests, better integration of the behavioral and neural results, and more careful consideration of alternative explanations. Stronger engagement with prior literature would also substantially strengthen the manuscript and increase its potential interest to researchers in systems, cognitive, and computational neuroscience.

eLife Assessment

This important study provides a quantitative comparison of how zebrafish and medaka larvae process visual motion, revealing clear differences in how they integrate information across space and time. The evidence is convincing, combining a broad set of behavioral assays with response decomposition and mechanistic modeling that together support the central conclusions. Some aspects remain incomplete, particularly the link between the spatial and temporal findings, the extent to which the model accounts for the full range of behavioral results, and the framing of broader evolutionary or social interpretations. Overall, the work offers a careful and informative analysis that should be of broad interest to researchers studying visual processing, sensorimotor computation, and comparative neuroscience.

eLife Assessment

This study presents a large-scale characterization of single-neuron responses during reading and listening, enabling examination of both 'low-level' (orthographic/phonological) and 'higher-level' (syntactic) features, as well as links between single-neuron activity and multi-scale field potentials, making it a valuable resource for bridging micro- and macroscale accounts of language processing. The analyses identify modality-specific and putatively modality-independent responses across distributed brain regions, offering an intriguing framework for understanding how sensory-specific and abstract representations may relate. However, the evidence supporting the central claims is currently incomplete, due to limited population-level quantification, insufficient statistical characterization of how many neurons encode the relevant features, ambiguity in the interpretation of encoding model results, and a lack of rigorous tests of cross-modal generalization and alternative accounts, which together weaken the conclusions about amodal representations and hierarchical processing.