Neuroscience

eLife Assessment

This important contribution to the field demonstrates the role of a single transcription factor with cell-autonomous functions in the differentiation of two distinct neuronal populations in regulating the interactions between those cells in a non-autonomous manner to generate their final organized projection pattern. There are additional quantifications and controls that would enhance the study and would improve the strength of the evidence from incomplete if they were performed.

eLife Assessment

This valuable study presents a theoretical framework in which spatial periodicity in grid cell firing emerges as the optimal solution for encoding two-dimensional spatial trajectories via sequential neural activation. The idea is supported by solid evidence, though it rests on several key assumptions that merit careful consideration. This work will be of interest to neuroscientists investigating the neural mechanisms underlying spatial navigation.

eLife Assessment

This important study uses an innovative task design combined with eye tracking and fMRI to distinguish brain regions that encode the value of individual items from those that accumulate those values for value-based choices. It shows that distinct brain regions carry signals for currently evaluated and previously accumulated evidence. The study provides solid evidence in support of most of its claims, albeit with current minor weaknesses concerning the evidence in favour of gaze-modulation of the fMRI signal. The work will be of interest to neuroscientists working on attention and decision-making.

eLife Assessment

This important study investigates how neural representations in the postrhinal and medial entorhinal cortices evolve with the learning of a visual associative memory task in mice. The findings provide new insights into how non-spatial information is differentially encoded across interconnected brain areas, with strong evidence that stimulus encoding is robust in the postrhinal cortex and emerges more weakly in the medial entorhinal cortex with learning. The evidence is solid overall, particularly in the use of sophisticated population-level analyses and two-photon imaging across learning phases, although the interpretation of regression models and clustering would benefit from additional clarity and control. The work will be of broad interest to systems neuroscientists studying learning, memory, and cortical circuit function.

eLife Assessment

This important study reports human single-neuron recordings in subcortical structures while participants performed a tactile detection task around the perceptual threshold. The study and the analyses are well conducted and provide convincing evidence that the thalamus and the subthalamic nucleus contain neurons whose activity correlates with the task, with stimulus presentation, and even with whether the stimulation is consciously detected or not. The study will be relevant for researchers interested in the role of subcortical structures in tactile perception and the neural correlates of consciousness.

eLife Assessment

This study examines how self-citations in selected neurology, neuroscience, and psychiatry journals differ according to seniority, geography, gender and subfield. The evidence supporting the claims is convincing, and the article is a valuable addition to the literature on self-citations.

eLife Assessment

Using highly sophisticated switching linear dynamical systems (SLDS) analyses applied to functional MRI data, this study provides important insights into network dynamics underlying threat processing. After identifying distinct neural network states associated with varying levels of threat proximity, the paper provides compelling evidence of intrinsically and extrinsically driven contributions to these within-state dynamics and between-state transitions. Although the findings could be made more biologically meaningful, this work will be of interest to a wider functional neuroimaging and systems neuroscience community.

eLife Assessment

This manuscript shows that chronic chemogenetic excitation of dopaminergic neurons in the mouse midbrain results in differential degeneration of axons and somas across distinct regions (SNc vs VTA). These findings are important for two reasons. This approach can be used as a mouse model for Parkinson's Disease without the need for the infusion of toxins (e.g. 6-OHDA or MPTP) — this mouse model also has the advantage of showing axon-first degeneration over a time course (2–4 weeks) that is suitable for experimental investigation. Also, the findings that direct excitation of dopaminergic neurons causes differential degeneration sheds light on the mechanisms of dopaminergic neuron selective vulnerability. The evidence that activation of dopaminergic neurons causes degeneration, alters motor behavior, and alters mRNA expression is convincing. This is an exciting paper that will have an impact on the Parkinson's Disease field.

eLife Assessment

The authors show that an automated approach using artificial neural networks, which focuses on behaviourally relevant dimensions, can predict human similarity data up to a certain level of granularity. This study has the potential to be a valuable contribution to the broader field of cognitive computational neuroscience, as it provides a tool for the automated collection of similarity judgments under certain conditions. However, as of now, the significance of this method is somewhat limited because of its inability to generalise beyond between-category distinctions and the limited model evaluation. In terms of broader implications, the degree to which this work provides insights into DNN-brain alignment and a better understanding of the functional organisation of the visual system is supported by incomplete evidence.

eLife Assessment

The granularity with which neural activity in the sensorimotor cortex of mice corresponds to voluntary forelimb motion is a key open question. This paper provides convincing evidence for the encoding of low-level features like joint angles and represents an important step forward toward understanding the cortical origins of limb control signals.