The human experience is shaped by evolutionary adjustments that have endowed the human brain with advanced cognitive, physiological, and morphological adaptations, surpassing those of other anthropoid primates. Although comparative mammalian studies have provided valuable insights into our evolutionary history, identifying genomic variations underpinning uniquely human phenotypic traits remains challenging. Integration of multiomic modalities with noninvasive brain imaging allows evolutionary hypotheses to be tested in previously intractable ways. This convergence marks a new era, integral to deepening our understanding of what novel and conserved features steer human brain development. In this review, we highlight multimodal efforts to study human brain evolution. We argue that efforts to connect primate and human genotype-to-phenotype relationships will accelerate over the coming years but require careful interpretation when evaluating claims of human uniqueness. Finally, we underscore the importance of continued identification of conserved aspects of brain development and the use of rigorous study designs when evaluating proposed 'human-specific' features.

Neurodegenerative diseases are characterized by key pathological hallmarks, progressive loss of neuronal structure and function, and synaptic loss. Often, mild behavioral changes including subjective cognitive decline and neuropsychiatric symptoms precede the diagnosis and may be a harbinger of disease inception and progression. Despite the success of new treatments that attenuate pathological burden, the ability to translate clinical benefit for cognitive impairment and dementia-related behavioral syndromes remains challenging. While model systems are essential, the appropriate model must be carefully chosen for the specific research question, with complementary model systems necessary to capture multiple aspects of disease. This review will cover the emergence of model systems that provide more translationally relevant trajectories of the progression of pathological changes throughout brain aging, and the advancement of model systems that are able to better capture the spectrum of behavioral and cognitive changes that signal the early prodromal period prior to diagnosis.

Our brains make sense of the world on a moment-by-moment basis despite its enormous complexity, largely because its overall statistical structure can be detected, learned, and generalized across experiences. Exposure to specific regularities (e.g., in speech) results in an unsupervised, incidental, form of learning, commonly known as statistical learning (SL). SL is well-established from a cognitive perspective and often assumed to require high-level cortical or hippocampal processing. However, accumulating evidence suggests that SL emerges much earlier in ascending sensory pathways. Despite this, our understanding of the forms it might take in subcortical sensory centres is relatively limited. Here, we review neuronal sensitivity to statistics in early sensory regions and ask how this sensitivity relates to SL. We feature examples of adaptive responses elicited by stimulus repetitions, omissions, changes in stimulus distribution, and more complex patterning, highlighting the interplay between adaptive coding and SL as manifestations of sensitivity to environmental statistics.

The vast diversity of animal behaviors has long inspired ethologists and neuroscientists, but circuit mechanisms driving this variation remain elusive. Recent advances in genetic tools and comparative approaches have enabled unprecedented insights into how neural circuits evolve to produce behavioral novelty. Here we focus on the discoveries emerging from the study of courtship behaviors, which are particularly well poised to capitalize on these advances. Comparative studies of sensory and motor circuits have begun to demonstrate that evolution can act through diverse mechanisms. The modular organization of courtship-controlling circuits emerges as a key feature facilitating rapid evolutionary innovation while maintaining essential functions. Changes in the neuronal composition of circuits, by both cellular and subcellular mechanisms, represent common mechanisms. Organisms may even carry vestigial circuits with the latent potential to be repurposed for new behavioral paradigms. We highlight how understanding the 'extended nervous system' of a species has begun to provide these critical insights into courtship evolution and offers fertile ground for future discoveries. As comparative approaches expand beyond model organisms, evolutionary neuroscience is on the cusp of revealing the principles governing behavioral diversity in nature.

Parkinson's disease (PD) remains one of the most elusive, progressive neurological diseases to treat due to an incomplete understanding of its pathology. Current symptomatic therapies revolve around alleviating symptoms with dopamine replacement therapy; however, this mode of treatment does not always provide long-term relief or address the underlying cause. Thus, there is still a need to better understand the mechanisms of proteins implicated in neurodegeneration as the key to developing disease-modifying treatments. Here we discuss recent advances in our understanding of six protein targets for PD therapy: α-synuclein, LRRK2, GBA1, PARKIN, PINK1, and USP30. For each, we highlight novel structures that shine light both on pathogenic mechanisms as well as novel therapies. We discuss drugs targeting these proteins that are in clinical trials, and how structures are used to improve them.

Early-onset Parkinson's disease (EOPD) is usually defined as Parkinson's disease (PD) occurring before the age of 40-50 years. Unlike late-onset PD, EOPD is often due to pathogenic mutations in autosomal recessive genes. Two phenotypes can be distinguished: typical EOPD, which progresses slowly (PRKN, PINK1 and DJ-1), and atypical PD, often associated with additional symptoms (ATP13A2, FBXO7, DNAJC6, VPS13C, SYNJ1, PLA2G6). In this review, we will highlight recent advances and remaining challenges. The frequency of causal genetic mutations and the genotype-phenotype landscape of PRKN-associated PD has been refined. Long-read sequencing has solved several undiagnosed cases with a single PRKN mutation. Five new genes have been reported to contribute to EOPD associated with various neurological signs (PTPA, DAGLB, PSMF1, EPG5, SGIP1). Small molecules targeting PRKN dysfunctions are expected to enter clinical trials in the coming years, paving the way for targeted therapies in EOPD.

The human brain is adept at extracting regularities from our environment, allowing us to behave adaptively and make predictions. Research on the neural basis of this statistical learning has diverged in recent years based on the brain mechanism being investigated and the timing and modality of the regularities. One literature has focused on the entrainment of neural oscillations to rapid auditory sequences in cortical regions. The other literature has focused on changes in the similarity of neural representations for slower visual sequences in the hippocampus. By reuniting these literatures, we identify a potential role for the hippocampus in generalizing over temporal variability and suggest how hippocampal-cortical interactions could support statistical learning.

Animals exhibit appropriate social behaviors and physiological responses based on the opponent's sex. Mammals secrete sex-specific chemical cues, some of which act as pheromones and play crucial roles. Sex-specific pheromones are received by a largely sexually monomorphic detection system in the vomeronasal organ. Small populations of sensory neurons encode conspecific sex via sex-selective receptors, while complex traits are encoded by combinatorial neuronal activity. These signals are processed by sexually dimorphic dedicated neural circuits in the brain. Neural activity recording in these brain regions has revealed distributed neural encoding of sex and internal brain states associated with aggression and mating. Sex hormones play critical roles in establishing, remodeling, and modulating these systems across multiple levels, enabling adaptive responses. Emerging evidence in mice sheds light on how pheromonal information is transformed into the neural representation of sex and internal state through adaptive modulatory mechanisms, ultimately triggering appropriate sex-specific responses.

The careful regulation of the protein lifecycle is important for cellular function, particularly during times of change. In neurons, the specializations needed to maintain the steady-state proteome at multiple subcellular domains and respond rapidly to activity have brought about unique mechanisms in messenger RNA (mRNA) translation and protein degradation. Recent research continues to illuminate these critical mechanisms, giving us a deeper understanding of the nervous system and identifying new targets for the treatment of neurological disorders. In this review, we highlight the new research shedding light on the mechanisms of proteostasis in brain development and plasticity. These studies emphasize the extent to which protein synthesis and degradation participate in brain function and how disruptions of proteostasis lead to disorders of the nervous system.

When learning multiple tasks, the structure of practice, or curriculum, profoundly influences learning outcomes across domains, including motor learning, rule learning, perceptual learning, and machine learning. In multitask learning settings, there is often a trade-off between the speed of acquisition and long-term retention. For example, in motor learning, acquisition appears faster, but retention is substantially reduced with blocked training compared to randomly interleaved training. In machine learning, this effect is known as catastrophic forgetting. In contrast, perceptual and cognitive learning benefit from structured, predictable curricula such as blocked training. We propose contextual inference as a unifying framework to explain these effects, emphasizing the integration of task transition dynamics, contextual cues and observation noise during learning. Insights from this framework may allow mitigating catastrophic interference in machine learning by leveraging principles inspired by biological learning.

Traditional views in cellular neurobiology stipulate that neuropeptides, biologically active peptides cleaved from precursor proteins with substantial expression in the nervous system, modulate bidirectional synaptic neurotransmission in the adult brain by engaging mostly, if not exclusively, G protein-coupled receptors. Recent evidence also places neuropeptides into developmental processes, with both transient and permanent expression foci in the fetal nervous system contributing to neuronal fate choices, notably axonal growth and directional guidance. Neuropeptide receptors are partitioned within navigating growth cones, with the bulk of neuropeptides inducing steering decisions, at least in vitro. Thus, any developmental process that disrupts growth cone motility and biases guidance decisions might render neuropeptide signaling inadequate for neuronal circuit formation. We recognize maternal drug abuse during pregnancy as a major liability for neuropeptide signaling, because the most common psychoactive drugs alter neuropeptide levels, their molecular targets coexist with neuropeptide receptors in growth cones, and symptomatically, neuropeptide signaling is altered in neurodevelopmental disorders in children with either prenatal or adolescent drug exposure. Mechanistically, the epigenetic deregulation of neuropeptide expression is suggested. Thus, we propose that neuropeptide-sensitive developmental programs, chiefly neurogenesis and synaptogenesis, are susceptible to psychoactive drugs. Thus, any means to rescue or reinstate neuropeptide signaling could attenuate nervous system pathobiology in offspring passively subjected to substance abuse during pregnancy.

The decision to urinate relies on assessing bladder fullness and context to determine an appropriate time and place to go. Any disruption in this interoceptive process results in frequent and sometimes debilitating consequences in daily life. Recent work has uncovered key pathways and brain regions that contribute to the sense of bladder stretch and the control of urinary reflexes, but many open questions remain. Here, we review the known mechanisms that convey sensory information from the bladder to the brain and back down again, and we highlight the knowledge gaps and opportunities for better understanding this system, which will be critical to develop effective therapies for urinary dysfunction.

Ingestive behavior is orchestrated by a complex interplay of neural circuits that sense and integrate nutritional information from the external environment and the internal milieu. A dynamic interaction between these circuits unfolds over time and allows organisms to learn to associate the nutritional benefits of foods and drinks realized in the body with antecedent actions (e.g., reaching, chewing) and sensory experiences in the environment (e.g., sight, smell) and oral cavity (e.g., flavor). This process of sequential gut-to-brain association learning optimizes behavior and metabolism by enabling the value of foods to be learned and updated based on their physiological consequences. As a result, when cues are encountered in the future, they can support predictive coding, such as the simulation of potential future states to guide adaptive food decisions, and they can acquire the capacity to elicit conditioned responses in the body to optimize metabolism. Here, we review recent advances in gut-brain reinforcement learning and highlight outstanding questions and controversies.

The effect of stress on an organism can be diverse and systemic, impacting cell physiology, development and behaviour. Here, I review the molecular mechanisms by which stressors (noxious stimuli) negatively impact all these aspects of animal biology and some of the mechanisms employed by the organism to combat damage by such insults. I focus on research carried out in the nematode Caenorhabditis elegans and the stress response pathways that enhance the core proteostasis network, a collection of molecular chaperones and degradation factors that refold or remove damaged proteins. Insults are often sensed by the nervous system, which then triggers stress response pathways systemically in distal tissues. Inter-tissue communication for cell nonautonomous regulation of stress responses by the nervous system involves many different neurotransmitters and modulators in an insult-specific manner. Sex-specific differences in stress sensitivity and proteostasis strategies also exist, with males generally being more resilient than hermaphrodites. However, male reproductive development and behaviour remain particularly vulnerable to stress.

The MDGA family proteins, MDGA1 and MDGA2, are glycophosphatidylinositol (GPI)-anchored proteins with high expression in the central nervous system. Initially associated with neuronal migration, MDGAs also act as synaptic suppressors in postsynaptic neurons, where they interfere with functions of key synapse organizing proteins. Strikingly, the MDGAs act upon distinct extracellular binding proteins to negatively control different synaptic properties of diverse synapses and neural circuits. This review discusses recent research on MDGAs and highlights debates and unresolved questions to invigorate future research activities aimed at determining precisely how MDGAs modulate synaptic properties in the context of neural circuits. Given that MDGAs and their interacting proteins are strongly linked with various neurodevelopmental disorders, understanding how synaptic signaling pathways encompassing MDGA protein complexes will be instrumental for better understanding the pathophysiological mechanisms of associated brain disorders.

Parental behavior, like other instinctive behaviors, must strike a delicate balance between robustness and flexibility to ensure offspring survival in dynamic environments. While core features of parenting are genetically programmed, they can be modulated by the hormonal changes accompanying pregnancy and parturition, as well as by social experience. How such behavioral flexibility arises from plasticity within the underlying neural circuits is a topic of intense investigation. In this review, we summarize recent advances in understanding the multi-level plasticity of the parental brain in both males and females. We highlight emerging principles of hormone- and experience-driven circuit remodeling and discuss key challenges and opportunities for future research in this rapidly evolving field.

Since their discovery and development, human induced pluripotent stem cells (iPSCs) have brought about notable advances in biomedical science and have become an essential infrastructure for medical research and applications. This review discusses the current status of iPSC-based cell therapies, drug discovery, and therapeutic developments for neurodegenerative diseases with unmet medical needs. It also highlights research approaches employing cohorts of iPSCs derived from sporadic neurodegenerative diseases to advance prevention and diagnostic support. It further considers future directions for the use of iPSCs in the treatment of neurodegenerative disorders.

The remarkable complexity and diversity of acoustic signals used in social interactions across animal species offers a unique window into the neural basis of behavioral evolution. Among these, the Drosophila courtship song serves as a powerful system for investigating how context-dependent complex motor patterns are encoded and evolve over time. With the aid of advanced tools-including cell-type-specific manipulation and connectomics-researchers are beginning to uncover the circuit architecture responsible for song production. Comparative analyses of homologous neurons across species are further revealing how specific components of the song circuit contribute to the diversification of acoustic signals. In this review, we synthesize recent comparative studies in Drosophila with current knowledge of the courtship song circuit to discuss where and how neural circuits may have evolved to generate species-specific motor patterns and to highlight circuit principles and features that may underlie or shape the evolution of complex motor behaviors.