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Attention-driven gating of sensory information operates through distributed networks, shaping perception and action. This evergreen overview reviews mechanisms, evidence, and practical implications for optimizing task performance across real-world settings.

Oscillatory brain rhythms organize the timing of synaptic changes, shaping how information is stored and communicated across neural networks. This article surveys mechanisms linking phase, plasticity, and transfer efficiency in healthy and disturbed brains.

Across sensory cortices, intricate neural microcircuits encode probabilistic beliefs, transform uncertain stimuli into refined interpretations, and update estimates through feedback, tune, and dynamic competition, revealing a Bayesian-like neural computation that guides perception.

Cortical circuits constantly adapt by coordinating synaptic changes and inhibitory controls, preserving functional stability while learning, ensuring memory retention, accuracy, and resilience against disruption through multi-layered, balanced plasticity dynamics.

This article explores how sensory experience reshapes thalamic input processing and cortical circuitry, detailing the molecular, cellular, and network dynamics that underlie learning-driven refinement of connections and receptive fields across developing and mature brains.

Dendritic signaling networks operate as finely tuned gates, discerning which synapses undergo plastic changes during learning, by coordinating local biochemical cascades with global network states and timing cues across neural circuits.

In neural circuits, inhibitory synaptic plasticity functions as a dynamic regulator, adjusting inhibitory strength to maintain balance, prevent escalating activity, and promote robust information processing across diverse brain states and learning tasks.

A comprehensive overview of how cellular quality control mechanisms preserve synapses, support neuronal resilience, and influence aging, by detailing the roles of chaperones, proteasomes, autophagy, and stress responses in neural circuits.

A concise examination of how brain chemical signals influence what draws us to certain experiences, how motivation shapes attention, and why some memories are selected for lasting storage over others.

Exploring how modular neural architectures shape learning pace, transfer, and the emergence of distinct cognitive roles, with implications for education, AI, and brain-inspired design.

Sensory prediction errors prompt brain circuits to adjust synaptic strengths, refining perceptual models through learning rules that balance stability and plasticity, ensuring adaptive responses to changing environments.

Rapid neural adaptation hinges on fast-acting signals and structural changes, enabling synapses to form and stabilize swiftly as new skills emerge, with glial support and local protein synthesis guiding plasticity.

Across diverse neural circuits, activity-dependent myelination emerges as a dynamic regulator of signal timing, linking experience and plasticity to the precise coordination required for complex behaviors, learning, and adaptation.

Neuromodulators operate on precise timing windows, and their phasic bursts synchronize neural circuits to reinforce specific learning rules. This article explores how timing, frequency, and sequence of neuromodulatory signals influence synaptic plasticity, shaping when and how memories are formed and updated in adaptive systems. By integrating theoretical models with experimental findings, we examine how timing deviations can redirect reinforcement signals, alter eligibility traces, and modify rule-based learning across brain regions. The goal is to illuminate the temporal logic that governs reinforcement, prediction error signaling, and the consolidation of experience into durable behavior. Understanding these dynamics offers insights for education, therapy, and artificial intelligence.

In the brain’s cortex, layered columns organize neurons to dissect intricate sensory inputs, enabling rapid recognition of patterns, textures, motion, and shape. This evergreen examination explores how microcircuits within cortical columns perform hierarchical feature extraction, integrate context, and support perceptual inference across modalities, while remaining resilient to noise and variation. By tracing connections from thalamic inputs through local interneurons and pyramidal cells, we reveal principles that unify perception, learning, and adaptive behavior under a common cortical framework that persists throughout life.

This evergreen examination reveals how the brain’s fast reflex circuits and slower, thoughtful planning collaborate through interconnected loops, enabling humans to react swiftly while still weighing options, goals, and consequences in real time.

This evergreen exploration surveys how neural networks orchestrate sequences of movement, revealing mechanisms that enable smooth, adaptive motor control and scalable performance across varied tasks and environments.

Across learning and memory, neural ensembles adapt their interactions to enable gradual skill acquisition, robust retention, and flexible retrieval of complex motor sequences, integrating sensory, cognitive, and motivational signals for coordinated action.

Dendritic processing reshapes traditional views of neuronal computation by revealing how individual branches implement localized learning rules, nonlinear integration, and context-dependent signaling, thereby enabling flexible, input-specific learning within single neurons.

This evergreen exploration delves into how individual synapses employ intrinsic regulatory processes to preserve relative strength patterns, ensuring stable signaling and reliable computation within neural networks over time.