Neuroscience

Environmental dynamics shape human learning: change points versus random walks

1. Cedric Foucault
2. Lilian A Weber
3. Laurence Hunt

• Curated by eLife

  eLife Assessment

  Foucault and colleagues examine how human adaptive learning depends on the structure of the learning task. The authors provide useful findings clarifying the differences in how people learn in environments that are continuously versus discontinuously changing. While they provide solid evidence for most conclusions, support for some of the claims is incomplete in the current form.

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. 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

Neural signatures of model-based and model-free reinforcement learning across prefrontal cortex and striatum

1. Bruno Miranda
2. James L Butler
3. W M Nishantha Malalasekera
4. Timothy EJ Behrens
5. Peter Dayan
6. Steven W Kennerley

• Curated by eLife

  eLife Assessment

  This important study presents single-unit activity collected during model-based (MB) and model-free (MF) reinforcement learning in non-human primates. The dataset was carefully collected, and the statistical analyses, including the modeling, are rigorous. The evidence convincingly supports different roles for particular cortical and subcortical areas in representing key variables during reinforcement learning.

Reviewed by eLife

Sofosbuvir protects human brain organoids against SARS-CoV-2

1. Pinar Mesci
2. Angela Macia
3. Aurian Saleh
4. Laura Martin-Sancho
5. Xin Yin
6. Cedric Snethlage
7. Simoni Avansini
8. Sumit K. Chanda
9. Alysson Muotri

Reviewed by Rapid Reviews Infectious Diseases, ScreenIT

SARS-CoV-2 infects brain choroid plexus and disrupts the blood-CSF-barrier

1. Laura Pellegrini
2. Anna Albecka
3. Donna L. Mallery
4. Max J. Kellner
5. David Paul
6. Andrew P. Carter
7. Leo C. James
8. Madeline A. Lancaster

Reviewed by Rapid Reviews Infectious Diseases, ScreenIT, preLights

Working Memory Guides Perceptual Decisions Through Fast Capture and Slow Drift

1. Hyung-Bum Park
2. Weiwei Zhang

• Curated by eLife

  eLife Assessment

  This study provides important insights into how working memory shapes perceptual decisions, using a dual-task design, continuous mouse tracking, and hierarchical Bayesian modeling. By dissociating fast attentional capture effects from slower, sustained perceptual biases within single trials, the authors provide compelling evidence that working memory-perception interactions unfold through distinct dynamic processes rather than a single mechanism. This work will be of interest to researchers studying working memory, perception, decision-making, and mouse-tracking methodology.

Reviewed by eLife

Cholinergic blockade reveals a role for human hippocampal theta in memory encoding but not retrieval

1. Tamara Gedankien
2. Jennifer Kriegel
3. Erfan Zabeh
4. David McDonagh
5. Bradley Lega
6. Joshua Jacobs

• Curated by eLife

  eLife Assessment

  This fundamental work advances our understanding of the role of human hippocampal theta oscillations in memory encoding and retrieval. The evidence supporting the conclusions is convincing, using both scopolamine administration and intracranial EEG recordings. This work will be of broad interest to neuroscientists and has translational implications.

Reviewed by eLife

Mesoscale functional architecture in medial posterior parietal cortex

1. Riichiro Hira
2. Leah B Townsend
3. Ikuko T Smith
4. Che-Hang Yu
5. Jeffrey N Stirman
6. Yiyi Yu
7. Spencer LaVere Smith

• Curated by eLife

  eLife Assessment

  This fundamental study measures the functional specialization of distinct subregions within the mouse posterior parietal cortex (PPC) using mesoscopic two-photon calcium imaging during visual discrimination and choice history-dependent tasks. It presents compelling evidence supporting the existence of functional specialized subregions within the PPC. The work will be of interest to system and computational neuroscientists interested in decision-making, working memory, and multisensory integration.

Reviewed by eLife

Readout and delayed transmission of initial afferent V1 activity in decisions about stimulus contrast

1. Kieran S Mohr
2. Simon P Kelly

• Curated by eLife

  eLife Assessment

  This important study reports that EEG recordings of the earliest stage of information processing in human visual cortex can be used to predict subsequent choice responses. The findings provide novel, convincing evidence for integrative processing in low-level sensory cortices at the level of scalp-recorded potentials, with the exact nature of the neural signals at the single cell level to be determined. The paper is likely to be of interest to neuroscientists interested in the contribution of early sensory signals to decision making.

Reviewed by eLife

iGABASnFR2 is an improved genetically encoded protein sensor of GABA

1. Ilya Kolb
2. Jeremy P Hasseman
3. Akihiro Matsumoto
4. Thomas P Jensen
5. Olga Kopach
6. Benjamin J Arthur
7. Yan Zhang
8. Arthur Tsang
9. Daniel Reep
10. Getahun Tsegaye
11. Jihong Zheng
12. Ronak H Patel
13. Loren L Looger
14. Jonathan S Marvin
15. Wyatt L Korff
16. Dmitri A Rusakov
17. Keisuke Yonehara
18. GENIE Project Team
19. Glenn C Turner

• Curated by eLife

  eLife Assessment

  This manuscript reports the development and characterization of iGABASnFR2, a genetically encoded GABA sensor that demonstrates substantially improved performance compared to its predecessor, iGABASnFR1. The work is comprehensive and methodologically rigorous, combining high-throughput mutagenesis, functional screening, structural analysis, biophysical characterization, and in vivo validation. The significance of the findings is fundamental, and the supporting evidence is compelling. iGABASnFR2 represents a notable advance in GABA sensor engineering, enabling enhanced imaging of GABA transmission both in brain slices and in vivo, and constitutes a timely, technically robust addition to the molecular toolkit for neuroscience research.

Reviewed by eLife, PREreview