Updated May 12th, 2026
Research Spotlight
The perception of tastes influences food choice and has profound implications for the development of healthy eating habits. Schiff et al. reports that the gustatory cortex undergoes an extended period of postnatal maturation that relies on changes in neuronal morphology, excitability, synaptic transmission and refinement of the connectivity of inhibitory neurons expressing parvalbumin. The time course of these circuit modifications extends beyond the known periods of maturation for other sensory systems. This extended maturation time may depend on the need to use other sensory information to identify nutritious food and make the decision to ingest it.
Jacqueline Fulvio and Bradley Postle, from the University of Wisconsin-Madison, used transcranial magnetic stimulation on a brain region to understand how this brain area influences the processing of irrelevant information from memories as well as information that just isn’t prioritized in memories. These distinct kinds of information processing may have unique mechanisms.
Combating the opioid crisis relies on identifying new prevention strategies for problematic fentanyl use. In a collaboration between Washington State University and Washington University in St. Louis, researchers led by Jose Moron tested whether enriching a rat’s environment can reduce fentanyl use and relapse. The researchers housed rats individually in either standard conditions or environments with new objects and measured fentanyl use across stages modeling human addiction: ongoing use, quitting, and relapse triggered by stress. Environmental enrichment reduced fentanyl intake over time and helped animals stop seeking the drug faster. Notably, when exposed to a stressful trigger, rats in enriched environments showed a much weaker relapse response compared to those in standard conditions. Rats in enriched environments also had lower levels of stress hormones, which were linked to relapse in those with standard conditions. According to the researchers, their work suggests that supplying rats with new objects in nonsocial environments can protect against fentanyl use and relapse. Says Jose Moron-Concepcion, “Because these strategies do not rely on social interaction, they may be easier to implement in real-world settings, including treatment programs and recovery environments. More broadly, this work highlights the powerful role of the environment and stress in addiction. Enrichment-based approaches could complement existing treatments and offer a scalable way to reduce opioid use and relapse risk.”
People who experience depression after long-term stress are more sensitive to unpleasant smells. Joseph Zak and colleagues, from the University of Illinois at Chicago, used mice to explore the mechanism for this change in the sense of smell. The researchers discovered cellular changes in brain areas related to smelling that were linked to increased sensitivity to unpleasant smells following long-term stress.
Most-Discussed Research Published in March and April
Below are five Early Release articles that generated the most online discussion in March and April of 2026, as measured by Altmetric. Altmetric data is available for all articles published in eNeuro on the Info & Metrics tab. Learn more about how the Altmetric score is calculated.
Neural and Behavioral Correlates of Evidence Accumulation in Human Click-Based Echolocation
Remarkably, some blind individuals navigate the world using echolocation, producing mouth clicks and interpreting returning echoes to perceive their surroundings. Yet how the brain combines successive echoes to build spatial representations remains poorly understood. Here, we show that expert blind echolocators localized echoes more accurately than sighted novices and that their performance improved as additional clicks provided more spatial information over time. Brain recordings revealed that neural activity distinguished sound location from the earliest echoes and evolved systematically across click sequences in parallel with behavioral improvements. These findings provide a detailed account of how the human brain transforms repeated acoustic information into stable spatial representations, supporting navigation in the absence of vision.
Artificial intelligence (AI)-generated voices are becoming increasingly indistinguishable from real human speech, raising serious concerns about fraud as scammers can convincingly impersonate trusted individuals. Our study shows that even when listeners cannot behaviorally distinguish AI-generated voices from real human voices, brief perceptual training enables their brains to detect subtle acoustic differences. Our findings thus reveal a dissociation between neural sensitivity and behavioral performance in recognizing AI-generated speech. By identifying this gap, we highlight an important opportunity: developing specialized training programs that guide listeners to recognize and utilize these subtle differences. Such targeted training could significantly enhance people's ability to identify synthetic voices, offering potential protection against the growing risks of scams and misinformation enabled by increasingly realistic AI speech technologies.
Representation Biases: Variance Is Not Always a Good Proxy for Importance
Computational neuroscientists often attempt to understand the brain by analyzing patterns of neural activity. These analyses frequently rely on the assumption that the strongest signals—those that explain the most variance—reflect the most important computations. This work challenges that core assumption. Using artificial neural networks where the computational “ground truth” is known, we demonstrate that learned representations are systematically biased toward some features over others. For example, simple linear features generate strong, distinct signals, while complex, nonlinear computations are frequently hidden in low-variance activity. Consequently, standard analytic tools may be biased toward identifying certain aspects of a system’s computation. Thus, these findings highlight challenges for achieving full understanding of a system's computations using common methods.
The Interaction between Sleep and Development on Wake EEG Oscillations
Most studies measuring EEG during wakefulness do not take into consideration prior sleep/wake history. Here, we show that wake EEG measures significantly differ when measured before or after sleep, and these effects are strongly dependent on age. Differences between pediatric populations may in fact be due to prior sleep quality or circadian rhythms rather than hypothesized group differences.
We show that reactive balance recovery in older adults with and without Parkinson's disease can be decomposed into distinct components that reflect hierarchical brainstem, cortical, and basal ganglia feedback loops. Using a neuromechanical model of delayed task-level feedback control, we link these components to perturbation difficulty and clinical balance ability in older adults. This framework connects specific features of agonist and antagonist muscle activity to underlying neural control processes without requiring direct brain recordings. Our findings provide a mechanistic basis for age- and disease-related changes in balance control that can inform individualized assessment and future rehabilitation strategies.
Stay updated on the latest research: Sign up and manage your Alerts to receive email alerts of table of contents, searching, and article citation alerts for both issues and Early Release.