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Parsimonious deep neural network models can be used for prediction of visual neuron responses.

The factors governing mouse decision-making strategies in changing environments remain unclear. Here the authors use a 4-state input-driven model to show that past stimuli/choices drive switches in bias, while past rewards drive switches in engagement.

Effusive volcanism dominates at water depths of 300 m or greater while phreatomagmatic Surtseyan eruptions become prevalent at shallower depths, according to analyses of high-resolution seismic reflection profiles, multibeam bathymetry, and seafloor imagery.

Here, the authors created a virtual reality task for monkeys and mice to explore if internal states like attention are similar across species. Their facial expressions during the task were similar, suggesting facial expressions reflect shared internal states.

Brain-wide recordings in mice reveal that prior expectations are distributed through recurrent loops across all levels of cortical and subcortical processing.

Behavioural experiments to study decision-making in response to context-dependent accumulation of evidence provide testable models that are consistent with the heterogeneity in neural signatures among rats that perform well in trials.

The authors implement model-based analyses to uncover strategies used by mice and humans during sensory decision-making. Contrary to common wisdom, mice do not lapse and, instead, switch between sustained engaged and disengaged states.

Analysis of the whole-brain fly connectome reveals high-dimensional dynamics supported by many small independent circuits, motivating a proposal for optogenetic perturbation to efficiently learn a whole-brain causal neural dynamics model.

The authors use virtual reality tasks and a latent state modeling approach to demonstrate that the opposing control of behavior by striatal pathways is dependent on both task demands and changes in internal state.

Antibiotic-resistant strains of Staphylococcus aureus, such as MRSA, are proving increasingly difficult to treat; here, one reason for this is confirmed to be the fact that S. aureus bacteria can reside in intracellular reservoirs where they are protected from antibiotics, but a new strategy—based on an antibody–antibiotic conjugate—can specifically target these reservoirs.

The International Brain Laboratory presents a brain-wide electrophysiological map obtained from pooling data from 12 laboratories that performed the same standardized perceptual decision-making task in mice.

Social spider colonies composed of ‘bold’ individuals have greater foraging success than ‘shy’ colonies, but this advantage diminishes as their frequency in the neighbourhood increases.

Neural representations in working memory are susceptible to internal noise, which scales with memory load. Here, the authors show that attractor dynamics mitigate the influence of internal noise by pulling memories towards a few stable representations.

SEUDO is a tool for detecting and correcting errors introduced by automated processing of calcium imaging data.

Perhaps the earliest known signs of life have been found in Quebec, where features such as haematite tubes suggest that filamentous microbes lived around hydrothermal vents at least 3,770 million years ago.

Lightning Pose is an efficient pose estimation approach that requires few labeled training data owing to its semi-supervised learning strategy and ensembling.

The functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses is analysed. Fitting the physiological data to a model of multi-neuron spike responses, it is found that a significant fraction of what is usually considered single-cell noise in trial-to-trial response variability can be explained by correlations, and that a significant amount of sensory information can be decoded from the correlation structure.

Aoi et al. used a new dimensionality-reduction method to disentangle the contributions of different task variables to neural population activity, which revealed rotational dynamics in monkey PFC during context-dependent decision-making.

A deep neural network with ‘knockout training’ is used to model sensorimotor transformations and neural perturbations of male Drosophila melanogaster during visually guided social behaviour and provides predictions and insights into relationships between stimuli, neurons and behaviour.

The authors analyze the Allen Institute Brain Observatory Ca²⁺ imaging data, focusing on mouse visual cortex during locomotive and quiescent states. They find that locomotion increases neural coding fidelity, regardless of whether population activity increases or decreases in response to the population’s preferred stimuli.

A new study shows that an efficient allocation of sensory resources can lead to Bayesian estimates that are biased away from the prior, accounting for effects such as the bias toward oblique angles in orientation perception.

The lateral intraparietal area (LIP) in monkeys plays an important role in decision-making. Here the authors use a statistical approach to decode the activity of LIP spikes and find multiplexed and temporally heterogeneous signals. This provides a framework for studying complex coding in higher brain areas.

Yuan and colleagues developed an artificial intelligence-based method to derive growth patterns and morphological features from hematoxylin and eosin-stained slides of lung adenocarcinoma samples, for improved tumor grading and patient prognostication.

Animals compose behaviors from both sensory cues and internal states. Calhoun et al. develop an unsupervised modeling framework to identify the dynamic internal states that shape social interactions in Drosophila and use the model to identify neurons that modulate the male’s internal state.

A strategy for protecting redox-active ortho-quinones, which show promise as anticancer agents but suffer from redox-cycling behaviour and systemic toxicity, has been developed. The ortho-quinones are derivatized to redox-inactive para-aminobenzyl ketols. Upon amine deprotection, an acid-promoted, self-immolative C–C bond-cleaving 1,6-elimination releases the redox-active hydroquinone. The strategy also enables conjugation to a carrier for targeted delivery of ortho-quinone species.

vTwINS enables high-speed volumetric calcium imaging via a V-shaped point spread function and a dedicated data-processing algorithm. Song et al. apply this strategy to image population activity in the mouse visual cortex and hippocampus.

Yates and colleagues statistically dissect MT and LIP responses during motion discrimination. They show decreasing temporal weighting of motion in MT, consistent with psychophysical weighting, and show that LIP spikes encode the upcoming choice more than integrated motion or simultaneously recorded MT spikes, suggesting an indirect relationship between these areas.

A study introduces innovative ways to test whether neural population activity exhibits structure above and beyond that of its basic components.

A modular architecture for managing and sharing electrophysiology, behavior, colony management and other data has been built to support individual laboratories or large consortia.

A revolution is underway in cognitive neuroscience, where tools and techniques from computer science and the tech industry are helping to extract more meaningful cognitive signals from noisy and increasingly large fMRI datasets. In this paper, the authors review the cutting edge of such computational analyses and discuss future opportunities and challenges.

Activity in regions of the brain have been correlated with decision making but determining whether such relationships are correlative or causative has been challenging; using a technique to reversibly inactivate brain areas in monkeys reveals that although there is decision-related activity in the lateral intraparietal (LIP) area, LIP is not critical for the perceptual decisions studied here.