Current Opinion in Neurobiology最新文献

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Statistical learning: A core mechanism in a developmental hierarchy 统计学习：发展层次中的核心机制

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-10-09 DOI: 10.1016/j.conb.2025.103124

Richard N. Aslin, Jenny R. Saffran

Over the past 30 years, studies of learning in humans and other animal species have revealed powerful mechanisms that extract structured information from exposure to stimuli without the need for immediate reward or feedback. These implicit learning mechanisms are referred to as statistical learning because they are sensitive to the distributional information present in the ambient environment. Here we review the historical roots of statistical learning research as it evolved from the psychological and linguistic literature, later incorporating computational and cognitive neuroscience methods with the goal of fleshing out underlying mechanisms. We emphasize that statistical learning must be constrained by evolutionary and/or learning biases to function effectively and efficiently in a given context. We also discuss the component processes involved in statistical learning and how they may be implemented in the brain. Finally, we highlight the utility of studying statistical learning in early development. Immature neural systems lend themselves to an examination of their underlying components, which are more difficult to tease apart once they are consolidated as parallel interactive circuits in the mature brain.

在过去的30年里，对人类和其他动物物种学习的研究已经揭示了从暴露于刺激中提取结构化信息的强大机制，而不需要立即的奖励或反馈。这些内隐学习机制被称为统计学习，因为它们对周围环境中的分布信息很敏感。在这里，我们回顾了统计学习研究的历史根源，因为它从心理学和语言学文献演变而来，后来结合了计算和认知神经科学方法，目的是充实潜在的机制。我们强调统计学习必须受到进化和/或学习偏差的约束，才能在给定的环境中有效地发挥作用。我们还讨论了统计学习的组成过程，以及它们如何在大脑中实现。最后，我们强调了在早期发展中研究统计学习的效用。不成熟的神经系统有助于研究其潜在的组成部分，一旦它们在成熟的大脑中被整合为平行的互动回路，就很难梳理出来。

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Curriculum effects in multitask learning through the lens of contextual inference 从语境推理看多任务学习中的课程效应

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-10-09 DOI: 10.1016/j.conb.2025.103123

Sabyasachi Shivkumar , Máté Lengyel , Daniel M. Wolpert

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.

当学习多个任务时，实践结构或课程会深刻影响跨领域的学习成果，包括运动学习、规则学习、感知学习和机器学习。在多任务学习环境中，习得速度和长期记忆之间往往存在权衡。例如，在运动学习中，与随机交错训练相比，闭塞训练的习得速度更快，但记忆能力却大大降低。在机器学习中，这种效应被称为灾难性遗忘。相比之下，知觉和认知学习受益于结构化的、可预测的课程，如阻塞训练。我们提出语境推理作为一个统一的框架来解释这些影响，强调任务转移动力学、语境线索和学习过程中的观察噪声的整合。从这个框架中获得的见解可以通过利用受生物学习启发的原理来减轻机器学习中的灾难性干扰。

引用次数: 0

Memorability reflects statistical regularities of the environment 可记忆性反映了环境的统计规律

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-10-01 Epub Date: 2025-08-16 DOI: 10.1016/j.conb.2025.103095

Cambria Revsine , Wilma A. Bainbridge

The field of statistical learning research has had great success in characterizing people's ability to extract regularities in time and space, but questions remain as to exactly what and how individuals learn over the lifetime. We propose that the field of stimulus memorability research can offer insight to these questions. Sensitivity to memorability, the consistencies in what people remember and forget, is intrinsically linked to statistical learning, as both reflect the prioritization of meaningful input in the environment. Parallels in behavioral responses, developmental trajectories, and neural substrates between the two cognitive processes are discussed. We also offer ways in which both fields can continue to evolve, primarily by using naturalistic, multisensory paradigms, which can lead to a more robust understanding of how statistical learning occurs in the real world.

统计学习研究领域在描述人们从时间和空间中提取规律的能力方面取得了巨大的成功，但人们在一生中究竟学习了什么以及如何学习的问题仍然存在。我们建议刺激记忆研究领域可以为这些问题提供见解。对记忆的敏感性，即人们记忆和遗忘的一致性，与统计学习有着内在的联系，因为两者都反映了环境中有意义输入的优先级。平行的行为反应，发展轨迹，和神经基质之间的两个认知过程进行了讨论。我们还提供了两个领域可以继续发展的方法，主要是通过使用自然主义的多感官范式，这可以导致对统计学习如何在现实世界中发生的更有力的理解。

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Turning back time: Aging plasticity and its rejuvenation 时光倒流：衰老的可塑性及其返老还童

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-10-01 Epub Date: 2025-08-18 DOI: 10.1016/j.conb.2025.103097

Carola I. Radulescu, Kjara S. Pilch, Xingjian Wang, Fontaine Gibbs, Samuel J. Barnes

As we age, our brain is influenced by experience and intrinsic biological changes. This combination of external and internal factors shapes the way in which our brain functions. Neuronal plasticity processes can store information about the sensory world and regulate neural-circuit activity levels to maintain stable neural-circuit function. These learning- and homeostasis-related plasticity processes exhibit age-related changes. Developing a better understanding of such age-related changes may open opportunities for rejuvenation strategies that promote plasticity and improve neurological health in later life. Here we review some of the latest work investigating age-related plasticity changes with a specific focus on sensory cortices. We propose that a better understanding of age-related tipping points in the context of plasticity could facilitate timed intervention strategies that may promote resilience during aging, by boosting the efficacy of endogenous plasticity mechanisms.

随着年龄的增长，我们的大脑受到经验和内在生物变化的影响。这种外部和内部因素的结合决定了我们大脑的运作方式。神经元可塑性过程可以存储感觉世界的信息，调节神经回路的活动水平，维持神经回路的稳定功能。这些与学习和体内平衡相关的可塑性过程表现出与年龄相关的变化。更好地了解这些与年龄相关的变化，可能会为促进可塑性和改善晚年神经健康的恢复策略提供机会。在这里，我们回顾了一些研究年龄相关可塑性变化的最新工作，特别关注感觉皮层。我们提出，在可塑性的背景下，更好地理解年龄相关的引爆点，可以通过提高内源性可塑性机制的功效，促进时间干预策略，从而提高衰老过程中的恢复力。

引用次数: 0

New insights into axonal regulators of dopamine transmission in health and disease 对健康和疾病中多巴胺传递轴突调节因子的新见解

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-10-01 Epub Date: 2025-08-16 DOI: 10.1016/j.conb.2025.103093

Kathryn L. Todd , Kaitlyn M.L. Cramb , Katherine R. Brimblecombe , Stephanie J. Cragg

Dopamine release in the striatum is credited with being critical to the selection and learning of motivated actions and outcomes. Dysregulation of striatal dopamine release underlies multiple disorders of action selection and reward-processing, such as Parkinson’s disease, schizophrenia and addiction disorders, and is a major target for therapeutic interventions. The axonal molecular and circuit mechanisms governing dopamine exocytosis are incompletely resolved, but accumulating evidence suggests some key points of divergence from canonical neurotransmitter synapses. In this review, we bring together recent insights into mechanisms shaping dopamine transmission in the striatum, spanning the molecular machinery regulating exocytosis, striatal modulators locally governing release probability, and the mechanisms regulating dopamine vesicle endocytosis. Together, these findings continue to support points of divergence from canonical presynaptic mechanisms, they inform principles of axonal neuromodulation, and point to potential contributions to the susceptibility to neurodegeneration in Parkinson’s disease.

纹状体中的多巴胺释放被认为对动机行为和结果的选择和学习至关重要。纹状体多巴胺释放失调是多种行为选择和奖励处理障碍的基础，如帕金森病、精神分裂症和成瘾障碍，是治疗干预的主要目标。控制多巴胺胞吐的轴突分子和电路机制尚不完全清楚，但越来越多的证据表明，与典型神经递质突触存在一些关键的分歧。在这篇综述中，我们汇集了最近对纹状体中多巴胺传递机制的见解，包括调节胞吐的分子机制，纹状体调节局部释放概率的机制，以及调节多巴胺囊泡内吞的机制。总之，这些发现继续支持与典型突触前机制的分歧点，它们为轴突神经调节的原理提供了信息，并指出了帕金森病神经变性易感性的潜在贡献。

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引用次数: 0

Interoception 2025 Interoception 2025。

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-09-30 DOI: 10.1016/j.conb.2025.103122

Zachary A. Knight, Stephen D. Liberles

引用次数: 0

Neural basis for parental behavioral transitions in mice 小鼠亲代行为转变的神经基础。

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-09-18 DOI: 10.1016/j.conb.2025.103113

Kazunari Miyamichi

Parental care is fundamental to the physical and mental well-being of mammalian offspring. Females undergo pregnancy, parturition, and lactation, with hormones pivotal to these processes—such as estrogen, prolactin, and oxytocin—also playing essential roles in mediating infant-directed caregiving behaviors. Although the extent of paternal involvement varies widely across species, the same hormones that regulate maternal transitions may be utilized to facilitate paternal behavioral adaptations. Recent advances in single-cell transcriptomics and cell-type-specific genetic manipulations have elucidated the mechanisms through which hormones interact with discrete cell types to drive structural and physiological plasticity within key regions of the brain governing parental behaviors. Furthermore, parental care serves as a valuable model for studying naturally occurring motivated behavioral learning, wherein higher-order cognitive regions and monoaminergic systems play an integrative role. This review highlights recent progress in this field, with a brief discussion on the potential sexually dimorphic engagement of specific hormonal systems.

亲代抚育对哺乳动物后代的身心健康至关重要。雌性动物经历怀孕、分娩和哺乳，在这些过程中至关重要的激素——如雌激素、催乳素和催产素——也在调节婴儿导向的照顾行为中起着重要作用。尽管不同物种中父亲的参与程度差异很大，但调节母亲转变的激素可能被用来促进父亲的行为适应。单细胞转录组学和细胞类型特异性遗传操作的最新进展已经阐明了激素与离散细胞类型相互作用的机制，从而驱动大脑中控制亲代行为的关键区域的结构和生理可塑性。此外，亲代抚育为研究自然发生的动机行为学习提供了一个有价值的模型，其中高阶认知区域和单胺能系统起着综合作用。本文综述了这一领域的最新进展，并简要讨论了特定激素系统潜在的两性二态参与。

引用次数: 0

Neural plasticity supporting parental behaviors 支持父母行为的神经可塑性

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-09-13 DOI: 10.1016/j.conb.2025.103111

Patrick T. O'Neill , Dayu Lin

Becoming a parent involves extraordinary changes that allow caregivers to attend to and nurture infants. Neural circuits must adapt to the demands of caregiving to orchestrate various complex nurturing behaviors. These changes occur between two opposing circuits: a circuit primed for the expression of parenting to execute caregiving, and a circuit that suppresses this behavioral expression when the timing is not appropriate. In this review, we provide an overview of the neural circuits supporting the positive and negative control of parental behaviors and discuss mechanisms by which these opposing circuits are altered to facilitate the onset of parental care.

为人父母会带来巨大的变化，使照顾者能够照顾和养育婴儿。神经回路必须适应照顾的需要，以协调各种复杂的养育行为。这些变化发生在两个相反的回路之间：一个回路准备表达父母的养育行为来执行照顾，另一个回路在时机不合适时抑制这种行为表达。在这篇综述中，我们概述了支持父母行为的积极和消极控制的神经回路，并讨论了这些相反的回路是如何改变以促进亲代照顾的发生的机制。

引用次数: 0

Activity-dependent splicing: A game changer for proteome remodeling in the brain 活动依赖剪接：大脑中蛋白质组重塑的游戏规则改变者

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-09-10 DOI: 10.1016/j.conb.2025.103110

Oriane Mauger

The brain’s intricate neuronal circuits are continuously refined by external and internal stimuli throughout life. These plasticity events rely on a major proteome remodeling. Activity-dependent splicing has an unparalleled potential to instruct this proteome remodeling, enabling precise spatial and temporal control. This review examines recent progress in understanding activity-dependent splicing and highlights promising areas for future research into its role in brain plasticity.

大脑错综复杂的神经回路在人的一生中不断受到外部和内部刺激的完善。这些可塑性事件依赖于主要的蛋白质组重塑。活性依赖剪接在指导蛋白质组重塑方面具有无与伦比的潜力，可以实现精确的空间和时间控制。本文回顾了最近在理解活动依赖性剪接方面的进展，并强调了其在大脑可塑性中的作用的未来研究的有希望的领域。

引用次数: 0

Statistical learning and representational drift: A dynamic substrate for memories 统计学习和表征漂移：记忆的动态基础

IF 5.2 2区医学 Q1 NEUROSCIENCES

Current Opinion in Neurobiology

Pub Date : 2025-09-02 DOI: 10.1016/j.conb.2025.103107

Jens-Bastian Eppler , Matthias Kaschube , Simon Rumpel

In many brain areas, neurons exhibit continuous changes in their tuning properties over days, even when supporting stable percepts and behaviors–a phenomenon termed representational drift. How do neuronal circuits maintain stable function when their constituent elements are in constant flux? Here, we review recent theoretical and experimental work on interconnected levels, ranging from perpetual changes in synapses driving drifts in tuning of individual neurons to emergent stability at the population level, preserving similarities of activity patterns associated to specific percepts or behaviors. We propose that statistical learning, beyond its well-established roles during development and adaptation to new contexts, is also essential under steady behavioral and environmental conditions to safeguard the stability of representational similarities. We discuss implications for learning, memory, and forgetting. This framework reconciles the apparent paradox between unstable neural activity and stable perception, suggesting that representations are maintained through dynamic processes rather than static neural codes.

在许多大脑区域，即使在支持稳定的感知和行为时，神经元也会在几天内表现出其调谐特性的持续变化——这种现象被称为表征漂移。当神经元回路的组成元素不断变化时，它们如何保持稳定的功能？在这里，我们回顾了最近在相互联系水平上的理论和实验工作，从驱动单个神经元调谐漂移的突触的永久变化到群体水平上的紧急稳定性，保持与特定感知或行为相关的活动模式的相似性。我们认为，统计学习不仅在发展和适应新环境中发挥着重要作用，而且在稳定的行为和环境条件下，对于维护表征相似性的稳定性也至关重要。我们讨论了学习、记忆和遗忘的含义。这个框架调和了不稳定的神经活动和稳定的感知之间的明显矛盾，表明表征是通过动态过程而不是静态神经编码来维持的。

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