Neuroscience

eLife Assessment

This important study investigates how the size of an LLM may influence its ability to model the human neural response to language recorded by ECoG. Overall, solid evidence is provided that larger language models can better predict the human ECoG response. This study will be of interest to both neuroscientists and psychologists who work on language comprehension and computer scientists working on LLMs.

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 study provides important insights into the neural mechanisms linking sleep and long-term memory consolidation. By combining behavioural, genetic, imaging, and connectomic approaches in Drosophila, it identifies a target neural circuit that will be of broad interest to researchers studying sleep, memory, and neural circuits. The evidence supporting the involvement of the identified circuit in the regulation of sleep and memory is solid and represents a substantial advance in the field. Nevertheless, there is limited evidence to support the mechanistic claim that this circuit directly links sleep and memory consolidation within the available data, and some results should therefore be interpreted with appropriate caution.

eLife Assessment

This important work examines the effects of gaze on valuation signals in the human brain as participants choose between bundles of sequentially presented items food items. The paper provides convincing analyses of how gaze affects participants choice behaviour and how this varies across time. The work will be of interest to neuroscientists working on attention and decision-making.

eLife Assessment

This work establishes a valuable theoretical finding about how the spike timing dependence of inhibitory plasticity shapes recurrent network connectivity. The combination of theoretical analysis and simulations provides convincing evidence that effective inhibitory connectivity forms a so-called Mexican-hat profile when multiple inhibitory neuron types follow distinct learning rules. These mechanisms are thought to be implicated in the contextual modulation of neuronal responses to stimuli.

eLife Assessment

This valuable study describes a simple and robust approach for estimating information-limiting noise by splitting neural populations and comparing estimator values. The authors report more accurate and robust results compared to previous methods. The evidence for the robustness of the method is currently incomplete; some concerns regarding bias need to be resolved, and additional tests need to be provided on how the number of trials and neurons affect performance.

eLife Assessment

This paper describes a valuable tool for the detection and analysis of dentate spikes, network events in the dentate gyrus that are common yet understudied. This tool could help standardize dentate spike detection and analysis across labs and is therefore likely to be of interest to hippocampal neurophysiologists. However, the strength of evidence for its broad usefulness was viewed as incomplete, due to several identified bugs in the program and insufficient explanations of parameter selection and methods.

eLife Assessment

This valuable study provides fMRI evidence for a hierarchical representation of sequence, arranged along the anterior-posterior axis of the entorhinal cortex, as well as evidence from human single-unit recordings for sequence position coding in the hippocampus and entorhinal cortex. Weaknesses include tenuous links between the single-unit and fMRI datasets, incomplete evidence for some claims, lack of discussion of relevant hippocampal literature, and potential over-interpretation of the findings in relation to rodent grid coding. This work will be of interest to researchers studying memory, sequence representations, and spatial coding in the medial temporal lobe.

eLife Assessment

This study provides important insights into how researchers can use perceptual metamers to formally explore the limits of visual representations at different processing stages. The framework is compelling and the data support the claims.

eLife Assessment

This multimodal neuroimaging study leverages fMRI, PET, and deep learning to predict memory performance. The authors introduce the brain-cognition gap to link these different imaging modalities to cognition and evaluate their results in two independent cohorts. The results are solid and provide an important contribution to the literature and will be of interest to neuroscientists working at the interface of cognition, neuroimaging.