Abstract Transient high-frequency activity (HFA) in local field potentials exhibits substantial variability across trials and behavioral states, yet its functional role in sensory representation remains poorly understood. Here, we tested whether transient HFA events carry stimulus-related information through their temporal, spectral, and phase-dependent properties. Using intracranial recordings from 21 human participants performing a visual localizer task, we extracted transient HFA events and quantified their features using information-theoretic and decoding analyses. Individual event features carried only modest information about stimulus identity, and response magnitude and morphology-related properties contributed minimally to decoding performance. Instead, decoding was dominated by temporal alignment and low-frequency phase. Critically, representing transient events as distributed low-frequency phase configurations across electrodes substantially improved cross-trial decoding performance, whereas disrupting distributed phase structure eliminated this decoding advantage. These findings indicate that stimulus-related structure in transient HFA does not primarily arise from isolated local event properties, but instead emerges through distributed, phase-dependent network dynamics. More broadly, the results provide a framework for understanding how transient high-frequency neural activity contributes to sensory representations across distributed cortical networks.

Hippocampal sharp-wave ripples (SWRs) are high-frequency events critical for memory consolidation, typically studied during sleep and quiet wakefulness. Emerging evidence suggests that SWRs also occur during active behavior, yet their role in awake cognition remains unclear. Here, we demonstrate that changes in sustained attention modulate both the occurrence of SWRs and their temporal alignment to ongoing hippocampal oscillations. Using intracranial EEG recordings from epilepsy patients performing a sustained attention to response task (SART), we first identified attentional states based on behavioral variability and subjective reports. Next, we observed that SWRs were more frequent during high-attention periods, despite the absence of memory demands. Importantly, SWRs during low-attention periods showed higher phase synchrony with low-frequency oscillations (theta to lower beta) indicating increased endogenous coordination of SWRs under low attentional focus. These findings show that SWRs are dynamically regulated by attentional engagement, supporting a broader role for ripples in active cognitive processing.

The mammalian neocortex, organized into six cellular layers or laminae, forms a cortical network within layers. Layer-specific computations are crucial for sensory processing of visual stimuli within the primary visual cortex. Laminar recordings of local field potentials (LFPs) are a powerful tool to study neural activity within cortical layers. Electric brain stimulation is widely used in basic neuroscience and in a large range of clinical applications. However, the layer-specific effects of electric stimulation on LFPs remain unclear. To address this gap, we recorded laminar LFP from capuchin monkeys' primary visual cortex while presenting a flash visual stimulus. Simultaneously, we applied a low-frequency sinusoidal current to the occipital lobe with an offset frequency to the flash stimulus repetition rate. We analyzed the modulation of visual-evoked potentials with respect to the phase of applied electric stimulation. Our results reveal that only the deeper layers, but not the superficial layers, show phase-dependent changes in LFP components with respect to the applied current. Employing a cortical column model, we show that these in vivo observations can be explained by phase-dependent changes in the driving force within neurons of deeper layers. Our findings offer crucial insight into the selective modulation of cortical layers through electrical stimulation, thus advancing approaches for more targeted neuromodulation.

Sensory stimulation of the brain reverberates in its recurrent neural networks. However, current computational models of brain activity do not separate immediate sensory responses from this intrinsic dynamic. We apply a vector-autoregressive model with external input (VARX), combining the concepts of 'functional connectivity' and 'encoding models', to intracranial recordings in humans. This model captures the extrinsic effect of the stimulus and separates that from the intrinsic effect of the recurrent brain dynamic. We find that the intrinsic dynamic enhances and prolongs the neural responses to scene cuts, eye movements, and sounds. Failing to account for these extrinsic inputs leads to spurious recurrent connections that govern the intrinsic dynamic. We also find that the recurrent connectivity during rest is reduced during movie watching. The model shows that an external stimulus can reduce intrinsic noise. It also shows that sensory areas have mostly outward, whereas higher-order brain areas have mostly incoming connections. We conclude that the response to an external audiovisual stimulus can largely be attributed to the intrinsic dynamic of the brain, already observed during rest.

This is a commentary on a recently published paper. Mendoza-Halliday, Major et al., 2024 (“The Paper”) advocates a local field potential (LFP)-based approach to functional identification of cortical layers during “laminar” multielectrode recordings in nonhuman primates (NHPs). The broader goal is to substantiate the hypothesis of a ubiquitous spectrolaminar motif in NHP neocortex: gamma range activity originates in the upper layers and reflects feedforward activity, while alpha-beta activity originates in the lower layers and reflects feedback activity. In an impressive scientific effort, the authors analyze “laminar” data (simultaneous recordings from all cortical layers) collected from 14 cortical areas in 2 prior macaque studies and compare them to marmoset, mouse, and human data. Despite This Paper’s strengths, and its potential for scientific impact, a series of concerns that are fundamental to the analysis and interpretation of field potential signals, question its scientific foundations. The Paper also overstates the strength and prevalence of the spectrolaminar motif it advocates, and it understates key strengths and nuances of prior work.

The discrete events of our narrative experience are organized by the neural substrate that underlies episodic memory. This narrative process is segmented into distinct units by event boundaries, which facilitate a replay process that acts to consolidate each event into a narrative memory. High-frequency oscillations (HFOs) may synchronize neural activity during these processes. We use intracranial recordings from participants viewing and freely recalling a continuous, audiovisual stimulus. We find that hippocampal HFOs increase following event boundaries and hippocampal-cortical coincident HFOs (co-HFOs) occur in cortical regions that underlie event segmentation (inferior parietal, precuneus, lateral occipital, and inferior frontal cortices). Event-specific co-HFO patterns that occur during event viewing reoccur following event boundaries for the subsequent three events and during recall. This is consistent with models that support replay as a mechanism for memory consolidation. Therefore, HFOs may coordinate activity across brain regions that facilitate event segmentation, encode memory of discrete events, and bind representations to assemble memory of a coherent, continuous experience.

Natural vision is an active sensing process that entails frequent eye movements to sample the environment. Nonetheless vision is often studied using passive viewing with eye position held constant. Using closed-loop eye-tracking, with saccade-contingent stimulation and simultaneous intracranial recordings in surgical epilepsy patients, we tested the critical role of eye movement signals during natural visual processing in the hippocampus and hippocampal-amygdala circuit. Prior work shows that saccades elicit phase reset of ongoing neural excitability fluctuations across a broad array of cortical and subcortical areas. Here we show that saccade-related phase reset systematically modulates neuronal ensemble responses to visual input, enables phase-coding of information across the saccade-fixation cycle and modulates network connectivity between hippocampus and amygdala. The saccade-fixation cycle thus emerges as a fundamental sampling unit, organizing a range of neural operations including input representation, network connectivity and information coding. SUMMARY: Saccade-fixation cycle: a fundamental sampling unit, organizing input representation, information coding and network coordination.

Humans live in an environment that contains rich auditory stimuli, which must be processed efficiently. The entrainment of neural oscillations to acoustic inputs may support the processing of simple and complex sounds. However, the characteristics of this entrainment process have been shown to be inconsistent across species and experimental paradigms. It is imperative to establish whether neural activity in response to speech is a result of combination of simple evoked responses or of entrainment of neural oscillations in human participants. In this study, 12 participants with intracranial electrodes listened to natural speech and neural entrainment as evidenced by oscillatory activity persisting beyond the evoked responses was assessed. Neural activity was recorded from 165 contacts in Heschl’s gyrus and superior temporal gyrus. First, acoustic edges in the speech envelope induced coherence between speech and auditory cortex activity. Further, entrainment in the theta-alpha band outlasted the acoustic stimulation. This activity exceeded what could be expected from a simple evoked response. These findings suggest that speech has the potential to entrain neural oscillations in the human auditory cortex.

The mammalian neocortex, organized into six cellular layers or laminae, forms a cortical network within layers. Layer specific computations are crucial for sensory processing of visual stimuli within primary visual cortex. Laminar recordings of local field potentials (LFPs) are a powerful tool to study neural activity within cortical layers. Electric brain stimulation is widely used in basic neuroscience and in a large range of clinical applications. However, the layer-specific effects of electric stimulation on LFPs remain unclear. To address this gap, we conducted laminar LFP recordings of the primary visual cortex in monkeys while presenting a flash visual stimulus. Simultaneously, we applied a low frequency sinusoidal current to the occipital lobe with offset frequency to the flash stimulus repetition rate. We analyzed the modulation of visual-evoked potentials with respect to the applied phase of the electric stimulation. Our results reveal that only the deeper layers, but not the superficial layers, show phase-dependent changes in LFP components with respect to the applied current. Employing a cortical column model, we demonstrate that these in vivo observations can be explained by phase-dependent changes in the driving force within neurons of deeper layers. Our findings offer crucial insight into the selective modulation of cortical layers through electric stimulation, thus advancing approaches for more targeted neuromodulation.

Corticostriatal connections are essential for motivation, cognition, and behavioral flexibility. There is broad interest in using resting-state functional magnetic resonance imaging (rs-fMRI) to link circuit dysfunction in these connections with neuropsychiatric disorders. In this paper, we used tract-tracing data from non-human primates (NHPs) to assess the likelihood of monosynaptic connections being represented in rs-fMRI data of NHPs and humans. We also demonstrated that existing hub locations in the anatomical data can be identified in the rs-fMRI data from both species. To characterize this in detail, we mapped the complete striatal projection zones from 27 tract-tracer injections located in the orbitofrontal cortex (OFC), dorsal anterior cingulate cortex (dACC), ventromedial prefrontal cortex (vmPFC), ventrolateral PFC (vlPFC), and dorsal PFC (dPFC) of macaque monkeys. Rs-fMRI seeds at the same regions of NHP and homologous regions of human brains showed connectivity maps in the striatum mostly consistent with those observed in the tracer data. We then examined the location of overlap in striatal projection zones. The medial rostral dorsal caudate connected with all five frontocortical regions evaluated in this study in both modalities (tract-tracing and rs-fMRI) and species (NHP and human). Other locations in the caudate also presented an overlap of four frontocortical regions, suggesting the existence of different locations with lower levels of input diversity. Small retrograde tracer injections and rs-fMRI seeds in the striatum confirmed these cortical input patterns. This study sets the ground for future studies evaluating rs-fMRI in clinical samples to measure anatomical corticostriatal circuit dysfunction and identify connectional hubs to provide more specific treatment targets for neurological and psychiatric disorders.

Audiovisual (AV) interaction has been shown in many studies of auditory cortex. However, the underlying processes and circuits are unclear because few studies have used methods that delineate the timing and laminar distribution of net excitatory and inhibitory processes within areas, much less across cortical levels. This study examined laminar profiles of neuronal activity in auditory core (AC) and parabelt (PB) cortices recorded from macaques during active discrimination of conspecific faces and vocalizations. We found modulation of multi-unit activity (MUA) in response to isolated visual stimulation, characterized by a brief deep MUA spike, putatively in white matter, followed by mid-layer MUA suppression in core auditory cortex; the later suppressive event had clear current source density concomitants, while the earlier MUA spike did not. We observed a similar facilitation-suppression sequence in the PB, with later onset latency. In combined AV stimulation, there was moderate reduction of responses to sound during the visual-evoked MUA suppression interval in both AC and PB. These data suggest a common sequence of afferent spikes, followed by synaptic inhibition; however, differences in timing and laminar location may reflect distinct visual projections to AC and PB.

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.

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation method that is rapidly growing in popularity for studying causal brain-behavior relationships. However, its dose-dependent centrally induced neural mechanisms and peripherally induced sensory costimulation effects remain debated. Understanding how TMS stimulation parameters affect brain responses is vital for the rational design of TMS protocols. Studying these mechanisms in humans is challenging because of the limited spatiotemporal resolution of available noninvasive neuroimaging methods. Here, we leverage invasive recordings of local field potentials in a male and a female nonhuman primate (rhesus macaque) to study TMS mesoscale responses. We demonstrate that early TMS-evoked potentials show a sigmoidal dose-response curve with stimulation intensity. We further show that stimulation responses are spatially specific. We use several control conditions to dissociate centrally induced neural responses from auditory and somatosensory coactivation. These results provide crucial evidence regarding TMS neural effects at the brain circuit level. Our findings are highly relevant for interpreting human TMS studies and biomarker developments for TMS target engagement in clinical applications.

Our continuous visual experience in daily life is dominated by change. Previous research has focused on visual change due to stimulus motion, eye movements or unfolding events, but not their combined impact across the brain, or their interactions with semantic novelty. We investigate the neural responses to these sources of novelty during film viewing. We analyzed intracranial recordings in humans across 6328 electrodes from 23 individuals. Responses associated with saccades and film cuts were dominant across the entire brain. Film cuts at semantic event boundaries were particularly effective in the temporal and medial temporal lobe. Saccades to visual targets with high visual novelty were also associated with strong neural responses. Specific locations in higher-order association areas showed selectivity to either high or low-novelty saccades. We conclude that neural activity associated with film cuts and eye movements is widespread across the brain and is modulated by semantic novelty.

Abstract Every waking moment, multiple signals are received from different sensory systems. These signals must be properly integrated to ensure accurate perception and contextually-appropriate behavioral responses. An obvious question is: How does the brain integrate these separate signals? Research over the past 50 years has provided evidence of multisensory and sensorimotor integration in the thalamus itself and has highlighted the fact that widespread thalamic connections allow for fast transfer of information to and between different sensory and/or motor cortical areas. In addition to reviewing anatomical connections of major thalamic nuclei, this chapter considers the evidence supporting the role of thalamic nuclei in multisensory/sensorimotor integration, focusing on the mechanisms that include cross-modal modulation of ongoing oscillations and cortico-thalamocortical transfer of information.

We developed a detailed model of macaque auditory thalamocortical circuits, including primary auditory cortex (A1), medial geniculate body (MGB), and thalamic reticular nucleus, utilizing the NEURON simulator and NetPyNE tool. The A1 model simulates a cortical column with over 12,000 neurons and 25 million synapses, incorporating data on cell-type-specific neuron densities, morphology, and connectivity across six cortical layers. It is reciprocally connected to the MGB thalamus, which includes interneurons and core and matrix-layer-specific projections to A1. The model simulates multiscale measures, including physiological firing rates, local field potentials (LFPs), current source densities (CSDs), and electroencephalography (EEG) signals. Laminar CSD patterns, during spontaneous activity and in response to broadband noise stimulus trains, mirror experimental findings. Physiological oscillations emerge spontaneously across frequency bands comparable to those recorded in vivo. We elucidate population-specific contributions to observed oscillation events and relate them to firing and presynaptic input patterns. The model offers a quantitative theoretical framework to integrate and interpret experimental data and predict its underlying cellular and circuit mechanisms.

Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. Neural oscillations exhibit phase-dependent associations with cognitive functions, and tools to manipulate local oscillatory phases can affect communication across remote brain regions. A recent study demonstrated that multi-channel tACS can generate electric fields with a phase gradient or traveling waves in the brain. Computational simulations using phasor algebra can predict the phase distribution inside the brain and aid in informing parameters in tACS experiments. However, experimental validation of computational models for multi-phase tACS is still lacking. Here, we develop such a framework for phasor simulation and evaluate its accuracy using in vivo recordings in nonhuman primates. We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models. Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues’ conductivity. Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments.

Background: Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. TACS experiments have been coupled with computational simulations to predict the electromagnetic fields within the brain. However, existing simulations are focused on the magnitude of the field. As the possibility of inducing the phase gradient in the brain using multiple tACS electrodes arises, a simulation framework is necessary to investigate and predict the phase gradient of electric fields during multi-channel tACS. Objective: Here, we develop such a framework for phasor simulation using phasor algebra and evaluate its accuracy using in vivo recordings in monkeys. Methods: We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models.Results: Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues' conductivity.Conclusions: Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments.