Neuroscience

eLife Assessment

This study concerns how macaque visual cortical area MT represents stimuli composed of more than one speed of motion. The study is valuable because little is known about how the visual pathway segments and preserves information about multiple stimuli, and the study involves perceptual reports from both humans and one monkey regarding whether there are one or two speeds in the stimulus. The study presents compelling evidence that (on average) MT neurons shift from faster-speed-takes-all at low speeds to representing the average of the two speeds at higher speeds. Ultimately, this study raises intriguing questions about how exactly the response patterns in visual cortical area MT might preserve information about each speed, since such information could potentially be lost in an average response as described here, depending on assumptions about how MT activity is evaluated by other visual areas.

eLife Assessment

This study presents a valuable finding on whether executive resources mediate the impact of language predictability in reading in the context of aging. The evidence is solid in the investigation of prediction in reading, with one caveat that the text materials used could be biased against the aging population. The work will be of interest to cognitive neuroscientists working on reading, language comprehension, and executive control.

eLife Assessment

The authors analyzed spectral properties of neural activity recorded using laminar probes while mice engaged in a global/local visual oddball paradigm. They found solid evidence for an increase in gamma (and theta in some cases) for unpredictable versus predictable stimuli, and a reduction in alpha/beta, which they consider evidence towards a "predictive routing" scheme. The study is overall important because it addresses the basis of predictive processing in the cortex, but some of the analytical choices could be better motivated, and overall, the manuscript can be improved by performing additional analyses.

eLife Assessment

Mark and colleagues developed and validated a valuable method for examining subspace generalization in fMRI data and applied it to understand whether the entorhinal cortex uses abstract representations that generalize across different environments with the same structure. The manuscript presents convincing evidence for the conclusion that abstract entorhinal representations of hexagonal associative structures generalize across different stimulus sets.

eLife Assessment

This is a useful study that examines the relationship between neuropeptide signaling and the precision of vocal motor output using the songbird as a model system. The study presents evidence based on differential expression patterns and genetic or pharmacological inhibition of various neuropeptide genes for a causal role in song performance; however, this evidence is incomplete.

eLife Assessment

This important series of studies provides converging results from complementary neuroimaging and behavioral experiments to identify human brain regions involved in representing regular geometric shapes and their core features. Geometric shape concepts are present across diverse human cultures and possibly involved in human capabilities such as numerical cognition and mathematical reasoning. Identifying the brain networks involved in geometric shape representation is of broad interest to researchers studying human visual perception, reasoning, and cognition. The evidence supporting the presence of representation of geometric shape regularity in dorsal parietal and prefrontal cortex is solid, but does not directly demonstrate that these circuits overlap with those involved in mathematical reasoning. Furthermore, the links to defining features of geometric objects and with mathematical and symbolic reasoning would benefit from stronger evidence from more fine-tuned experimental tasks varying the stimuli and experience.

eLife Assessment

This valuable study addresses a critical and timely question regarding the role of a subpopulation of cortical interneurons (Chrna2-expressing Martinotti cells) in motor learning and cortical dynamics. However, while some of the behavior and imaging data are impressive, the small sample sizes and incomplete behavioral and activity analyses make interpretation difficult; therefore, they are insufficient to support the central conclusions. The study may be of interest to neuroscientists studying cortical neural circuits, motor learning, and motor control.

eLife Assessment

This valuable study shows that regions of the human auditory cortex that respond strongly to voices are also sensitive to vocalizations from closely related primate species. The study is methodologically solid, though additional analyses - particularly those isolating the acoustic features that differentiate chimpanzee from bonobo calls - would further strengthen the conclusions. With additional analyses and discussions, the work has the potential to offer key insights into the evolutionary continuity of voice processing and would be of interest to researchers studying auditory processing and evolutionary neuroscience in general.

eLife Assessment

This important study describes a novel Bayesian psychophysical approach that efficiently measures how well humans can discriminate between colors across the entire isoluminant plane. The evidence was considered compelling, as it included successful model validation against hold-out data and published datasets. This approach could prove to be of use to color vision scientists, as well as to those who use computational psychophysics and attempt to model perceptual stimulus fields with smooth variations over coordinate spaces.

eLife Assessment

This valuable study demonstrates that self-motion strongly affects neural responses to visual stimuli, comparing humans moving through a virtual environment to passive viewing. However, evidence that the modulation is due to prediction is incomplete as it stands, since participants may come to expect visual freezes over the course of the experiment. This study bridges human and rodent studies on the role of prediction in sensory processing, and is therefore expected to be of interest to a large community of neuroscientists.