The dorsal visual stream is a large retinotopic network in human visual cortex, involved in attentional and spatial aspects of vision critical for attending to, filtering, and interacting with the visual environment. The visual field maps which comprise the dorsal stream have not been characterized across development; a fundamental gap in human neuroscience given this pathway’s role in critical childhood behaviors. Here, we designed a gamified task to retinotopically map the dorsal stream in both adults and children for the first time. We found that the dorsal representations of visual space undergo protracted development, increasing the area over which they pool information across the visual field. Children show an asymmetry in the way that receptive fields of each cerebral hemisphere tile visual space, with protracted development predominantly in the right hemisphere serving to balance coverage across the left and right sides of space. This divergence between the hemispheres’ developmental trajectories has behavioral relevance, with individual variability in visuospatial attention biases correlating with receptive field properties from childhood into adulthood.

Increasing evidence suggests that higher-order thalamic nuclei are implicated in cognitive behavior. Unlike those in the first-order thalamus, higher-order thalamic neurons have a high propensity to switch from tonic spiking to rapid spike sequences termed bursts. Although bursts have been linked to the augmentation of information transfer in a manner that may support behavior, their role in cognition has never been tested. We show that bursts in the pulvinar, a thalamic node linked to cortical coordination during attention, are attention-modulated and predict behavior. Using neural data from the pulvinar and parietal cortex in macaques performing an attention task, we found that pulvinar bursts were predictive of target detection and reconfigured population codes of spatial location in cortex. Electrical microstimulation of the pulvinar triggered bursts that enhanced target detection and synchronized cortical spiking. These results establish pulvinar bursts as a causal driver of attention, revealing a mechanism by which the higher-order thalamus exerts control over cortical processing and behavior.

Modern high-density neural recordings demand spike-sorting algorithms that can handle diverse probe geometries and complex, neuron-specific drift, yet existing methods often rely on rigid geometric assumptions and one-dimensional drift models. Here, we introduce KIASORT (Knowledge-Integrated Automated Spike Sorting), a geometry-free approach for per-neuron drift tracking. KIASORT builds channel-specific sorting models from a hybrid linear–nonlinear sample-sorting stage, using representative template banks or supervised classifiers. These channel-specific models then sort spikes by independently tracking each neuron, unconstrained by probe layout. Biophysical simulations showed that even submicron probe displacements induce neuron-specific waveform distortions that standard drift models cannot correct. In ground-truth benchmarks with heterogeneous, neuron-specific drift, KIASORT outperformed Kilosort4 in recovering high-quality units while maintaining real-time performance on standard CPUs. Its robustness was further illustrated on both primate and mouse data. KIASORT combines automated sorting with manual curation in a unified graphical interface, offering a complete and user-friendly spike-sorting platform. The software is freely available at https://kiasort.com.

Spontaneous fluctuations in attention can impede adaptation to changing goals and environments. Endogenous control over attentional shifts, referred to as attentional flexibility, is prone to disruption in children with attention deficit disorders. Here we studied in vivo intracranial recordings in children with epilepsy to identify a reproducible neural signature of attentional control that could predict and prevent impending lapses in real time. Machine learning classifiers were trained on intracranial signals while each child performed an attentional set-shifting task and predicted delays in attention shifting over multiple days and across several pediatric populations. Intracranial electrical stimulation in response to impending delays rescued attention shifts indexed by eye tracking, reaction time and accuracy. Simultaneous electroencephalography identified corresponding scalp signatures that enabled noninvasive modulation of attention shifting in healthy participants. These findings provide insight into the neural basis of attentional shifts with implications for targeted neuromodulation and exogenous attentional control.

Brain-wide communication supporting flexible behavior requires coordination between sensory and associative regions but how brain networks route sensory information at fast timescales to guide action remains unclear. Using human intracranial electrophysiology and spiking neural networks during spatial attention tasks, where participants detected targets at cued locations, we show that high-frequency activity bursts (HFAbs) mark temporal windows of elevated population firing that enable fast, long-range communications. HFAbs were evoked by sensory cues and targets, dynamically coupled to low-frequency rhythms. Notably, both the strength of cue-evoked HFAbs and their decoupling from slow rhythms predicted behavioral accuracy. HFAbs synchronized across the brain, revealing distinct cue- and target-activated subnetworks. These subnetworks exhibited lead-lag dynamics following target onset, with cue-activated subnetworks preceding target-activated subnetworks when cues were informative. Computational modeling suggested that HFAbs reflect transitions to population spiking, denoting temporal windows for network communications supporting attentional performance. These findings establish HFAbs as signatures of population state transitions, supporting information routing across distributed brain networks.

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

Attention samples visual space sequentially to enhance behaviorally relevant sensory representations. While traditionally conceptualized as a static continuous spotlight, contemporary models of attention highlight its discrete nature. But which neural mechanisms govern the temporally precise allocation of attention? Periodic brain activity as exemplified by neuronal oscillations as well as aperiodic temporal structure in the form of intrinsic neural timescales have been proposed to orchestrate the attentional sampling process in space and time. However, both mechanisms have been largely studied in isolation. To date, it remains unclear whether periodic and aperiodic temporal structure reflect distinct neural mechanisms. Here, we combined computational simulations with a multimodal approach encompassing five experiments, and three different variants of classic spatial attention paradigms, to differentiate aperiodic from oscillatory-based sampling. Converging evidence across behavior as well as scalp and intracranial electroencephalography (EEG) revealed that periodic and aperiodic temporal regularities can theoretically and experimentally be distinguished. Our results extend the rhythmic sampling framework of attention by demonstrating that aperiodic neural timescales predict behavior in a spatially-, context-, and demand-dependent manner. Aperiodic timescales increased from sensory to association cortex, decreased during sensory processing or action execution, and were prolonged with increasing behavioral demands. These results reveal that multiple, concurrent temporal regularities govern attentional sampling.

Human brain evolution is marked by a disproportionate expansion of cortical regions associated with advanced perceptual and cognitive functions. While this expansion is often attributed to the emergence of novel specialized brain areas, modifications to evolutionarily conserved cortical regions also have been linked to species-specific behaviors. Distinguishing between these two evolutionary outcomes has been limited by the ability to make direct comparisons between species. Here, we addressed this limitation by examining the expansion of the human visual cortex relative to macaques using a common functional architecture: retinotopy. Our findings revealed that human visual cortex expansion is primarily driven by increases in the surface area of a visual map architecture present in macaques rather than an increase in the number of individual areas. This expansion was not uniform, with higher-order areas, particularly in the parietal cortex, exhibiting the largest growth. Comparisons between neonate and adult humans revealed that these relative areal size differences were already established at birth. A meta-analysis of neuroimaging studies indicated that the most expanded areas are associated with advanced cognitive functions beyond visual processing. These results suggest that human perceptual and cognitive adaptations may be rooted in the expansion of evolutionarily conserved cortical architecture, with modifications even in the sensory cortex contributing to the broader cognitive functions characteristic of human behavior.

Selective attention relies on neural mechanisms that facilitate processing of behaviorally relevant sensory information while suppressing irrelevant information, consistently linked to alpha-band oscillations in human M/EEG studies. We analyzed cortical alpha responses from intracranial electrodes implanted in eight epilepsy patients, who performed a visual spatial attention task. Electrocorticographic data revealed a spatiotemporal dissociation between attention-modulated alpha desynchronization, associated with the enhancement of sensory processing, and alpha synchronization, associated with the suppression of sensory processing, during the cue-target interval. Dorsal intraparietal areas contralateral to the attended hemifield primarily exhibited a delayed and sustained alpha desynchronization, while ventrolateral extrastriatal areas ipsilateral to the attended hemifield primarily exhibited an earlier and sustained alpha synchronization. Analyses of cross-frequency coupling between alpha phase and broadband high-frequency activity (HFA) further revealed cross-frequency interactions along the visual hierarchy contralateral to the attended locations. Directionality analyses indicate that alpha phase in early and extrastriatal visual areas modulated HFA power in downstream visual areas, thus potentially facilitating the feedforward processing of an upcoming, spatially predictable target. In contrast, in areas ipsilateral to the attended locations, HFA power modulated local alpha phase in early and extrastriatal visual areas, with suppressed interareal interactions, potentially attenuating the processing of distractors. Our findings reveal divergent alpha-mediated neural mechanisms underlying target enhancement and distractor suppression during the deployment of spatial attention, reflecting enhanced functional connectivity at attended locations, while suppressed functional connectivity at unattended locations. The collective dynamics of these alpha-mediated neural mechanisms play complementary roles in the efficient gating of sensory information.

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at α, β, and γ frequencies—rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by θ-rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

In vivo electrophysiology requires direct access to brain tissue, necessitating the development and refinement of surgical procedures and techniques that promote the health and well-being of animal subjects. Here, we report a series of findings noted on structural magnetic resonance imaging (MRI) scans in monkeys with MRI-compatible implants following small craniotomies that provide access for intracranial electrophysiology. We found distinct brain regions exhibiting hyperintensities in T2-weighted scans that were prominent underneath the sites at which craniotomies had been performed. We interpreted these hyperintensities as edema of the neural tissue and found that they were predominantly present following electric and piezoelectric drilling, but not when manual, hand-operated drills were used. Furthermore, the anomalies subsided within 2–3 wk following surgery. Our report highlights the utility of MRI-compatible implants that promote clinical examination of the animal’s brain, sometimes revealing findings that may go unnoticed when incompatible implants are used. We show replicable differences in outcome when using electric versus mechanical devices, both ubiquitous in the field. If electric drills are used, our report cautions against electrophysiological recordings from tissue directly underneath the craniotomy for the first 2–3 wk following the procedure due to putative edema.

Attention is fundamental to all cognition. In the primate brain, it is implemented by a large-scale network that consists of areas spanning across all major lobes, also including subcortical regions. Classical attention accounts assume that control over the selection process in this network is exerted by ‘top-down’ mechanisms in the fronto-parietal cortex that influence sensory representations via feedback signals. More recent studies have expanded this view of attentional control. In this review, we will start from a traditional top-down account of attention control, and then discuss more recent findings on feature-based attention, thalamic influences, temporal network dynamics, and behavioral dynamics that collectively lead to substantial modifications. We outline how the different emerging accounts can be reconciled and integrated into a unified theory.