Neuroscience

Age-dependent predictors of effective reinforcement motor learning across childhood

1. Nayo M Hill
2. Haley M Tripp
3. Daniel M Wolpert
4. Laura A Malone
5. Amy J Bastian

• Curated by eLife

  eLife Assessment

  This important study tests the development of motor reinforcement learning from toddlerhood to adulthood, using a large online sample. They show that learning improves with age in a task that, like real-life movement, involves a continuous range of response options and probabilistic rewards, and link this shift to reduced movement variability and more efficient feedback-based learning through behavioural modeling. Simplifying the task with discrete actions and deterministic outcomes boosted younger children's performance, suggesting early learning is limited by spatial and probabilistic processing. The evidence is convincing, although future work may investigate more naturalistic movement.

Reviewed by eLife

Elucidating the selection mechanisms in context-dependent computation through low-rank neural network modeling

1. Yiteng Zhang
2. Jianfeng Feng
3. Bin Min

• Curated by eLife

  eLife Assessment

  This study provides an important set of analyses and theoretical derivations to understand the mechanisms used by recurrent neural networks (RNNs) to perform context-dependent accumulation of evidence. The results regarding the dimensionality and neural dynamical signatures of RNNs are convincing and provide new avenues to study the mechanisms underlying context-dependent computations. This manuscript will be of interest to a broad audience in systems and computational neuroscience.

Reviewed by eLife

Human Brain-Wide Activation of Sleep Rhythms

1. Haiteng Wang
2. Qihong Zou
3. Jinbo Zhang
4. Jia-Hong Gao
5. Yunzhe Liu

• Curated by eLife

  eLife Assessment

  The study reports valuable findings from a very rich EEG-fMRI dataset, including 107 participants, which was collected during nocturnal naps. Using overall solid methods, the authors link activity in memory-related brain regions (e.g., hippocampus, thalamus, and medial prefrontal cortex), and their functional connectivity to the occurrence of canonical sleep rhythms (spindles and slow oscillations) in non-rapid eye movement sleep. This work will be of broad interest to sleep and memory researchers and beyond.

Reviewed by eLife

Neural dynamics of reversal learning in the prefrontal cortex and recurrent neural networks

1. Christopher M Kim
2. Carson C Chow
3. Bruno B Averbeck

• Curated by eLife

  eLife Assessment

  The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible behavior in changing environments. The study contains interesting comparisons between neural data and models, including evidence for partial consistency with line attractor models in this probabilistic reversal learning task. However, it remains incomplete due to issues related to how the RNN training and the analysis of its dynamics, which renders the evidence as not complete.

Reviewed by eLife

Material Damage to Multielectrode Arrays after Electrolytic Lesioning is in the Noise

1. Alice Tor
2. Stephen E Clarke
3. Iliana E Bray
4. Paul Nuyujukian
5. the Brain Interfacing Laboratory

• Curated by eLife

  eLife Assessment

  This useful manuscript addresses a stability issue for long-term chronically implanted array recordings and electrolytic lesioning, which is relevant to both basic science and translational research. The authors provide a systematic scanning electron microscopy (SEM) of explanted arrays, evaluating electrode damage and sharing extensive datasets accessible through interactive plots. The strength of the evidence is solid, but it can be improved by performing additional analyses on complementary neurophysiology, functional, or histological data.

Reviewed by eLife

Calpain cleaves the carboxyl terminus of TRPV1 and modulates receptor tachyphylaxis

1. Jinyan Jiang
2. Xiaochen Wang
3. Jing Yang
4. Shuwen Gao
5. Jixuan Xu
6. Jiao Liu
7. Yun Wang
8. Ping Liang
9. Ying Zhang

Reviewed by Arcadia Science

Intrinsic dynamic shapes responses to external stimulation in the human brain

1. Maximilian Nentwich
2. Marcin Leszczynski
3. Charles E Schroeder
4. Stephan Bickel
5. Lucas C Parra

• Curated by eLife

  eLife Assessment

  This manuscript presents an interesting new framework (VARX) for simultaneously quantifying effective connectivity in brain activity during sensory stimulation and how that brain activity is being driven by that sensory stimulation. The reviewers thought the model was original and its conclusion that intrinsic connectivity is reduced (rather than increased) during sensory stimulation is very interesting, but that for ideal performance, one must specify all sensory features in the model, which is not possible. Overall, however, this work is important with convincing evidence for its conclusions - it will be of interest to neuroscientists working on brain connectivity and dynamics.

Reviewed by eLife

The oneirogen hypothesis: modeling the hallucinatory effects of classical psychedelics in terms of replay-dependent plasticity mechanisms

1. Colin Bredenberg
2. Fabrice Normandin
3. Blake Richards
4. Guillaume Lajoie

• Curated by eLife

  eLife Assessment

  This paper provides a useful new theory of the hallucinatory effects of psychedelics. The authors present convincing evidence that a computational model trained with the Wake-Sleep algorithm can reproduce some features of hallucinations by varying the strength of top-down connections in the model, but discussion of the model's relationships to the psychedelics and sleep literatures is incomplete. The work will be of interest to researchers studying hallucinations or offline activity and learning more broadly.

Reviewed by eLife

Trial-level Representational Similarity Analysis

1. Shenyang Huang
2. Cortney M Howard
3. Paul C Bogdan
4. Ricardo Morales-Torres
5. Matthew Slayton
6. Roberto Cabeza
7. Simon W Davis

• Curated by eLife

  eLife Assessment

  This study proposes a potentially useful improvement on a popular fMRI method for quantifying representational similarity in brain measurements by focusing on representational strength at the single trial level and adding linear mixed effects modeling for group-level inference. The manuscript demonstrates increased sensitivity with no loss of precision compared to more classic versions of the method. However, the framing of the work with respect to these prior approaches is incomplete, several assumptions are insufficiently motivated, and it is unclear to what extent the approach would generalize to other paradigms.

Reviewed by eLife

Coordinated spinal locomotor network dynamics emerge from cell-type-specific connectivity patterns

1. F David Wandler
2. Benjamin K Lemberger
3. David L McLean
4. James M Murray

• Curated by eLife

  eLife Assessment

  In this valuable study, Wandler et al. provide convincing theoretical evidence for alternate mechanisms of rhythm generation by CPGs. Their model shows that cell-type-specific connectivity and a dominant inhibitory drive could underlie rhythm generation. Excitatory input could act to enhance the frequency range of these rhythms. This modeling study could motivate further experimental investigation of these mechanisms to understand CPG rhythmogenesis.

Reviewed by eLife