Browse Articles

The latent circuit model identifies low-dimensional mechanisms of task execution from heterogenous neural responses. This approach reveals a latent inhibitory mechanism for context-dependent decisions in neural network models and the prefrontal cortex.

Animals must distinguish between signals from sensory stimuli and action-generated signals. This paper shows that the ventral lateral geniculate nucleus acts as a corollary discharge center to suppress motion-induced visual signals, orchestrating accurate perception and motor control.

Using a novel method for isolating cognitive and motor neural dynamics, the authors show that dynamics often attributed to cognitive processes were corrupted by movements and that distinct populations of neurons encode cognitive and motor variables.

Sensory experience transforms endogenously structured cortical networks with diverse and unreliable visual responses into reliable representations. This process is proposed to involve the alignment of feedforward and recurrent networks.

Using the AstroLight system, the authors reveal that astrocytic ensembles in the nucleus accumbens regulate cue-motivated reward behavior, demonstrating that selective manipulation of tagged astrocytes can influence specific behavioral choices.

Lynn T. Landmesser, professor emerita of the Department of Neurosciences, School of Medicine at Case Western Reserve University, died on 29 November 2024 at the age of 80. In an illustrious and influential career that spanned more than four decades, she established central principles by which the complex and specific wiring of the vertebrate nervous system is established.

Emerging evidence highlights the dual role of oligodendrocytes in Alzheimer’s disease, both providing protective mechanisms against the pathology and contributing to its progression.

The default mode network (DMN) is implicated in cognition and behavior. Here, the authors show that the DMN is cytoarchitecturally heterogeneous, it contains regions receptive to input from the sensory cortex and a core relatively insulated from environmental input, and it uniquely balances its output across sensory hierarchies.

The authors show that a bidirectional circuit connecting the anterior and posterior (aIC–pIC) insula mediates the conditioned immune response in male mice, illustrating a mechanism by which sensory experience affects immune function.

During the pathogenesis of Parkinson’s disease (PD), α-synuclein pathology may originate in peripheral organs and spread to the CNS. Using human tissue samples and multiple approaches in mouse models of renal failure, we demonstrated that the kidney serves as an origin of pathological α-synuclein in PD.

Yuan et al. find that the kidney can serve as a site of initiation for the spread of pathological α-synuclein to the brain, contributing to the development of Parkinson’s disease (PD) and providing a mechanistic link between PD and renal dysfunction.

Duncan and colleagues link specific human brain cell types to schizophrenia and other complex brain phenotypes, providing mechanistic insights and a cellular taxonomy for psychiatric disorders.

Our brains evolved to help us rapidly learn new things. But anyone who has put in hours of practice to perfect their tennis serve, only to reach a plateau, can attest that our brains aren’t infinitely flexible. New work shows that patterns of neural activity over time — the temporal dynamics of neural populations — cannot change rapidly, suggesting that neural activity dynamics may both reflect and constrain how the brain performs computations.

Neuronal micronuclei are transferred to microglia during the early postnatal period, which leads to altered microglial morphology and transcriptomic signatures, suggesting that these micronuclei may act as mediators that control microglial characteristics.

Oby, Degenhart, Grigsby and colleagues used a brain–computer interface to challenge monkeys to override their natural time courses of neural activity. They found the time courses to be highly robust, suggestive of network-level computational mechanisms.

Using a metalearning approach to model relational learning, Miconi and Kay show neural mechanisms for structured generalization and rapid learning.