Neuroscience

From Syllables to Words: EEG Evidence of Different Age Trajectories in Speech Tracking and Statistical Learning in Infants at High and Low Likelihood for Autism

1. Michel Godel
2. Ana Fló
3. Lucas Benjamin
4. Ghislaine Dehaene-Lambertz
5. Marie Schaer

• Curated by eLife

  eLife Assessment

  This study addresses a key question in developmental cognitive neuroscience by identifying early neural correlates of variability in language learning and showing how syllable tracking and word segmentation develop from birth to two years in infants with differing likelihoods of autism. The evidence is generally strong, with rigorous longitudinal EEG acquisition, careful preprocessing, and validated statistical approaches, though several methodological clarifications would further strengthen confidence in the inferences. Overall, the findings offer important insights with clear theoretical implications for understanding early mechanisms of speech perception and statistical learning, supported by convincing evidence.

Reviewed by eLife

Uncovering the electrical synapse proteome in retinal neurons via in vivo proximity labeling

1. Stephan Tetenborg
2. Eyad Shihabeddin
3. Elizebeth Olive Akansha Manoj Kumar
4. Crystal L Sigulinsky
5. Karin Dedek
6. Ya-Ping Lin
7. Fabio A Echeverry
8. Hannah Hoff
9. Alberto E Pereda
10. Bryan W Jones
11. Christophe P Ribelayga
12. Klaus Ebnet
13. Ken Matsuura
14. John O'Brien

• Curated by eLife

  eLife Assessment

  This study aims to identify the proteins that make up the electrical synapse, which are much less understood than those of the chemical synapse. These findings represent an important step toward understanding the molecular function of chemical synapses and will have broad utility for the wider neuroscience field. The experimental evidence is convincing.

Reviewed by eLife

Spatial learning in multi-scale environments: Roles of hippocampus, orbitofrontal cortex, and retrosplenial cortex

1. Yidan Qiu
2. Senning Zheng
3. Huakang Li
4. Shuting Lin
5. Ruiwang Huang

• Curated by eLife

  eLife Assessment

  The goal of this useful study is to examine learning-related changes in neural representations of global and local spatial reference frames in a spatial navigation task. Although the study addresses an interesting question, the evidence for neural representations in the hippocampus and retrosplenial cortex remains incomplete because of confounds in the experimental design and partial data analysis. There are further concerns about the framing of the study in the context of the relevant literature as well as the discussion.

Reviewed by eLife

Functional connectivity-based attractor dynamics of the human brain in rest, task, and disease

1. Robert Englert
2. Balint Kincses
3. Raviteja Kotikalapudi
4. Giuseppe Gallitto
5. Jialin Li
6. Kevin Hoffschlag
7. Choong-Wan Woo
8. Tor D Wager
9. Dagmar Timmann
10. Ulrike Bingel
11. Tamas Spisak

• Curated by eLife

  eLife Assessment

  This study presents a valuable approach for revealing large-scale brain attractor dynamics during resting states, task processing, and disease conditions using insights from Hopfield neural networks. The evidence supporting the findings is convincing across the many datasets analysed. The work will be of broad interest to neuroscientists using neuroimaging data with interest in computational modelling of brain activity.

Reviewed by eLife

A unifying account of replay as context-driven memory reactivation

1. Zhenglong Zhou
2. Michael J Kahana
3. Anna C Schapiro

• Curated by eLife

  eLife Assessment

  This is an important account of replay as recency-weighted context-guided memory reactivation that explains a number of empirical findings across human and rodent memory literatures. The evidence is compelling and the work is likely to inspire further adaptions to incorporate additional biological and cognitive features.

Reviewed by eLife

Synergistic MAPT mutations as a platform to uncover modifiers of tau pathogenesis

1. Miles R Bryan
2. Michael F Almeida
3. Kyle Pellegrino
4. Carli K Opland
5. J Ethan Paulakonis
6. Jake McGillion-Moore
7. Hanna Trzeciakiewicz
8. Diamond King
9. Xu Tian
10. Jui-Heng Tseng
11. Jonathan C Schisler
12. Nicholas G Brown
13. Ben A Bahr
14. Todd J Cohen

• Curated by eLife

  eLife Assessment

  This study presents compelling new data that combine two FTD-tau mutations, P301L/S320F (PL-SF), that reliably induce spontaneous full-length tau aggregation across multiple cellular systems. The findings are important for the field of neurodegenerative disease. The strength of evidence is solid; however, several conclusions would benefit from more validation.

Reviewed by eLife

Decoding Spine Nanostructure in Mental Disorders Reveals a Schizophrenia-Linked Role for Ecrg4

1. Yutaro Kashiwagi
2. Qingrui Liu
3. Yasuhiro Go
4. Ryo Saito
5. Atsu Aiba
6. Takanobu Nakazawa
7. Shigeo Okabe

• Curated by eLife

  eLife Assessment

  By investigating spine nanostructure and dynamics across multiple genetic mouse models for neurodevelopmental disorders, this important study has the potential to uncover convergent or divergent synaptic phenotypes that may be specifically associated with autism versus schizophrenia risk. While the imaging and breadth are impressive, there are potential methodological concerns, especially around statistical analyses, which render the evidence incomplete and should be addressed. The purely in vitro nature of the study also slightly limits the generalisability of the findings.

Reviewed by eLife

A neuropeptide-specific signaling pathway for state-dependent regulation of the mesolimbic dopamine system

1. Mollie X. Bernstein
2. Omar Koita
3. Marta Trzeciak
4. Andrew Fan
5. Daniel T. McAuley
6. Seung-Woo Jin
7. Larry S. Zweifel

Reviewed by PREreview

ATF4 activates a transcriptional program that chronically suppresses mTOR activity promoting neurodegeneration in Parkinson’s disease models

1. Matthew D. Demmings
2. Erica A. Kane
3. Elizabeth C. Tennyson
4. Kate Hurley
5. Joy Zhao
6. Nicholas A. Cruickshanks
7. Victoria Ciz
8. Jordan M. Krupa
9. Stephen H. Pasternak
10. Sean P. Cregan

Reviewed by PREreview

Grid cells encode reward distance during path integration in cue-rich environments

1. Satoshi Kuroki
2. Sébastien Royer

Reviewed by PREreview