Neuroscience

eLife Assessment

This manuscript presents important findings that challenge traditional models of speech processing by demonstrating that theta-gamma phase-amplitude coupling in the auditory cortex is primarily a stimulus-driven alignment to external acoustic structures rather than an intrinsic neural oscillatory mechanism. The evidence supporting these claims is convincing, grounded in a robust cross-linguistic acoustic analysis and high-fidelity, time-resolved intracranial recordings.

eLife Assessment

This is a potentially important study comparing infants (8 months) and adults with respect to rhythmic EEG response properties during periodic and aperiodic visual stimulation. The results provide solid evidence for a ~4 Hz EEG response in infants that emerges independently of stimulation frequency. At this stage, additional work will be required to conclusively establish that this theta-band effect reflects genuine neural resonance rather than oculomotor processes.

eLife Assessment

This important study examined age-related changes in cerebellar function by testing a large sample of younger and older adults, including 30 over 80 years old, on motor and cognitive tasks linked to the cerebellum and conducting structural imaging. Their findings show that cerebellar-dependent functions are mostly maintained or even enhanced across the lifespan, with cerebellar-mediated motor abilities remaining intact despite degeneration, in contrast to non-cerebellar measures. Overall, the authors provide compelling evidence in support of preserved cerebellar function with age. These results highlight the resilience and redundancy of cerebellar circuits and offer key insights into aging and motor behavior.

eLife Assessment

This study presents valuable findings and employs modern analytical approaches on how transient absence of visual input (darkness) affects tactile encoding in the rat somatosensory cortex (S1). The evidence supporting the authors' claims is solid, as population-level neural activity recorded in S1 and decoded by a CNN carries more discriminable texture information in darkness. The underlying basis of this effect remains only partly resolved, however, because it is still unclear which neural features from the CNN drive the decoding and if visual interference is appropriately accounted for, which might confound true neural representational change.