Transcranial magnetic stimulation (TMS) is a powerful non-invasive tool for safely modulating neural activity in humans. In particular, the left dorsolateral prefrontal cortex (DLPFC) is a common target site for clinical interventions in disorders such as treatment-resistant depression. Yet, clinical trials investigating the efficacy of TMS often lack neural markers of target engagement of the DLPFC. Local field potentials (LFPs), such as prefrontal theta oscillations, have been implicated in the clinical symptoms of these disorders. However, non-invasive electroencephalography (EEG) recordings in humans are limited by their spatial resolution and challenges of interpreting EEG signals. In this study, we investigate the effects of single-pulse TMS applied to the left prefrontal cortex in non-human primates on LFPs recorded through intracranial EEG. Compared to sham TMS, the intensity of active TMS pulses scaled with LFP power changes in a 1-13 Hz range at contacts close to the stimulation site in the prefrontal cortex (e.g., caudate nucleus, anterior cingulate cortex, insular cortex) as well as contacts that were more distal (e.g., posterior cingulate cortex, temporal lobe). To test how TMS modulates connectivity between these regions, we conducted a phase-based connectivity analysis. TMS pulses initially enhanced and then disrupted connectivity at 1-13 Hz between the stimulation site and other contacts. Connectivity rebounded approximately 1500 ms post-stimulation. Only the initial enhancement in connectivity scaled with TMS intensity. Our results demonstrate a dose-dependent power modulation of low frequency LFPs across prefrontal, parietal and temporal cortical regions by single pulses. Furthermore, they show that TMS applied over the left prefrontal cortex can enhance and interrupt short- and long-range connectivity. Our study advances the understanding of the effects of TMS on brain oscillations and connectivity with direct relevance for clinical applications in neuromodulation therapies.

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.

Functional connectivity (FC) is commonly defined as the temporal coincidence of neurophysiological events, often quantified by the statistical dependency among signals from different brain regions and measured by Pearson's correlation coefficient in fMRI. However, Pearson's r captures only linear dependencies, potentially overlooking nonlinear interactions. Recently, Multiscale Graph Correlation (MGC) was introduced to measure statistical dependencies of both linear and nonlinear relationships across multiple scales, offering an "optimal scale" at which such dependencies can be inferred. In this study, we systematically compared FC measurements by Pearson's r and MGC across datasets, evaluating their reliability, sensitivity to data quantity, and ability to capture distinct experimental conditions (deeper anesthesia in macaques) and brain-behavior association. Results showed highly similar spatial connectivity patterns and strong alignment between Pearson's r and MGC for within-network FC, where optimal scales were frequently global. However, local optimal scales emerged between networks, suggesting the presence of nonlinear dependencies of FC. Reliability was higher for Pearson's r overall, but both measurements improved as the quantity of data increased. Notably, MGC revealed variability in the optimal scales under altered brain states in deeper anesthesia, highlighting its potential for detecting local-scale dependencies across states. Despite these advantages, MGC required greater computational resources and did not outperform Pearson's r in detecting brain-behavior associations. Consequently, Pearson's r remains a sufficient and reliable measure for many standard applications, whereas MGC can offer more nuanced insights in scenarios where nonlinear dynamics are of particular interest. Researchers should, therefore, balance the potential gains from MGC against its added complexity and computational cost when selecting methods to quantify FC.

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.

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.

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.

Three large-scale networks are considered essential to cognitive flexibility: the ventral and dorsal attention (VANet and DANet) and salience (SNet) networks. The ventrolateral prefrontal cortex (vlPFC) is a known component of the VANet and DANet, but there is a gap in the current knowledge regarding its involvement in the SNet. Herein, we used a translational and multimodal approach to demonstrate the existence of a SNet node within the vlPFC. First, we used tract-tracing methods in non-human primates (NHP) to quantify the anatomical connectivity strength between different vlPFC areas and the frontal and insular cortices. The strongest connections were with the dorsal anterior cingulate cortex (dACC) and anterior insula (AI) – the main cortical SNet nodes. These inputs converged in the caudal area 47/12, an area that has strong projections to subcortical structures associated with the SNet. Second, we used resting-state functional MRI (rsfMRI) in NHP data to validate this SNet node. Third, we used rsfMRI in the human to identify a homologous caudal 47/12 region that also showed strong connections with the SNet cortical nodes. Taken together, these data confirm a SNet node in the vlPFC, demonstrating that the vlPFC contains nodes for all three cognitive networks: VANet, DANet, and SNet. Thus, the vlPFC is in a position to switch between these three networks, pointing to its key role as an attentional hub. Its additional connections to the orbitofrontal, dorsolateral, and premotor cortices, place the vlPFC at the center for switching behaviors based on environmental stimuli, computing value, and cognitive control.

Cortical connectivity conforms to a series of organizing principles that are common across species. Spatial proximity, similar cortical type, and similar connectional profile all constitute factors for determining the connectivity between cortical regions. We previously demonstrated another principle of connectivity that is closely related to the spatial layout of the cerebral cortex. Using functional connectivity from resting-state fMRI in the human cortex, we found that the further a region is located from primary cortex, the more distant are its functional connections with the other areas of the cortex. However, it remains unknown whether this relationship between cortical layout and connectivity extends to other primate species. Here, we investigated this relationship using both resting-state functional connectivity as well as gold-standard tract-tracing connectivity in the macaque monkey cortex. For both measures of connectivity, we found a gradient of connectivity distance extending between primary and frontoparietal regions. In the human cortex, the further a region is located from primary areas, the stronger its connections to distant portions of the cortex, with connectivity distance highest in frontal and parietal regions. The similarity between the human and macaque findings provides evidence for a phylogenetically conserved relationship between the spatial layout of cortical areas and connectivity.

Neural oscillations play a crucial role in communication between remote brain areas. Transcranial electric stimulation with alternating currents (TACS) can manipulate these brain oscillations in a non-invasive manner. Recently, TACS using multiple electrodes with phase shifted stimulation currents were developed to alter long-range connectivity. Typically, an increase in coordination between two areas is assumed when they experience an in-phase stimulation and a disorganization through an anti-phase stimulation. However, the underlying biophysics of multi-electrode TACS has not been studied in detail. Here, we leverage direct invasive recordings from two non-human primates during multi-electrode TACS to characterize electric field magnitude and phase as a function of the phase of stimulation currents. Further, we report a novel "traveling wave" stimulation where the location of the electric field maximum changes over the stimulation cycle. Our results provide a mechanistic understanding of the biophysics of multi-electrode TACS and enable future developments of novel stimulation protocols.

Abstract: Transcranial magnetic stimulation (TMS) is a noninvasive neuromodulation method which enables in vivo perturbation of neural activity in humans through the application of electromagnetic fields to the brain. The repeated application of TMS (rTMS) to the dorsolateral prefrontal cortex (DLPFC) has been shown to be a non-invasive neuromodulation tool for the treatment of drug resistant depression and is FDA approved to be used clinically. However, significant variability in treatment outcomes across patients has been reported. Additionally, basic mechanisms underlying TMS effects on prefrontal neural circuitry is largely unknown. Therefore, it is necessary to improve current stimulation protocols by exploring the mechanism of such modulation. Several studies have investigated TMS effects using non-invasive imaging modalities such as electroencephalography (EEG). However, EEG suffers from low signal to noise ratio (SNR) and low spatial specify due to volume conduction. Therefore, in our study we investigate the effect of prefrontal TMS in a non-human primate model with implanted depth electrodes (32 electrode channels spanning the left hemisphere from frontal to occipital brain regions). This allows us to record high quality neural activity from the stimulation region as well as connected brain areas with a high spatiotemporal resolution. Several sessions of single-pulse TMS (100 pulses total per stimulation condition) to the prefrontal cortex were recorded while the monkey was under anesthesia. Data preprocessing involved TMS artifact removal including TMS artifacts and TMS induced muscle activity. Neural activity could be fully recovered at least 10 ms after stimulation. With further time-frequency analysis, we found decreased power mainly in low frequency oscillations, (2-4 Hz) shortly after the TMS stimulus followed by a recovery approximately one second after offset. This effect was strongest in prefrontal electrodes. We provide evidence that TMS is modulating intrinsic brain activity even under anesthesia through the suppression of low frequency oscillations. Future research will involve investigating the effect of changing TMS parameters (intensity, coil orientation) in further detail. Our research can provide a better understanding on how TMS affects neural activity in the prefrontal cortex and eventually can lead to more efficient treatment protocols to a variety of disorders such as depression.

Complementing long-standing traditions centered on histology, fMRI approaches are rapidly maturing in delineating brain areal organization at the macroscale. The non-human primate (NHP) provides the opportunity to overcome critical barriers in translational research. Here, we establish the data requirements for achieving reproducible and internally valid parcellations in individuals. We demonstrate that functional boundaries serve as a functional fingerprint of the individual animals and can be achieved under anesthesia or awake conditions (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher-order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHPs, provide insights into the impact of scan state, and motivate efforts toward harmonizing protocols.

A long history of postmortem studies has provided significant insight into human brain structure and organization. Cadavers have also proven instrumental for the measurement of artifacts and nonneural effects in functional imaging, and more recently, the study of biophysical properties critical to brain stimulation. However, death produces significant changes in the biophysical properties of brain tissues, making an ex vivo to in vivo comparison complex, and even questionable. This study directly compares biophysical properties of electric fields arising from transcranial electric stimulation (TES) in a nonhuman primate brain pre- and postmortem. We show that pre-vs. postmortem, TES-induced intracranial electric fields differ significantly in both strength and frequency response dynamics, even while controlling for confounding factors such as body temperature. Our results clearly indicate that ex vivo cadaver and in vivo measurements are not easily equitable. In vivo examinations remain essential to establishing an adequate understanding of even basic biophysical phenomena in vivo.

Transcranial electric stimulation (TES) is an emerging technique to non-invasively modulate brain function. However, the spatiotemporal distribution of electric fields during TES remains poorly understood. In this study we perform direct intracranial measurements of the electric field generated by transcranial alternating current (tACS) in epilepsy patients and cebus monkeys and evaluate the capacity of finite element method (FEM) models to predict the spatial distribution of measured electric fields. Two presurgical epilepsy patients, with ca. 100 intracranially implanted electrodes participated in a single TES session. Two sponge electrodes (25 cm2) were attached over the left and right temporal cortex and a current of 1 mA with a frequency of 1 Hz was applied for 2 min. In two cebus monkeys three electrodes, with a total of 32 contacts were permanently implanted with posterior-anterior orientation. In multiple sessions intracranial EEG was recorded during TES. We varied the frequency of stimulation from 1–150 Hz and computed amplitude and phase relationships of recorded voltages. We constructed FEM models with increasing anatomical complexity for one epilepsy patient and compared the measured and simulated electric fields. Voltage magnitude slightly decreased with stimulation frequency up to 10% and small phase differences between electrode contacts up to a few degrees were observed. Electric field strengths were strongest in superficial brain regions with maximum values of 0.5 mV/mm (Download : Download high-res image (1MB)Download : Download full-size imageFig. 1). Comparison of measured and simulated potentials and electric fields showed very high correlation values for the potentials (r = 0.95) and correlations of r = 0.7 for the electric fields. Evaluating the predictive value of increasingly complex FEM models highlighted the importance of accurate skull modeling especially in the vicinity of skull defects (Download : Download high-res image (746KB)Download : Download full-size imageFig. 2). We conducted a comprehensive evaluation of intracranial electric field during TES in both human patients and monkeys. Our results indicate that TES currents spread in a linear ohmic manner and capacitive effects are small indicating that the quasi-static approximation is well justified in the low frequency range. The spatial variation of the electric fields can be captured using realistic FEM models.

Cellular targets of transcranial electric stimulation (TES) are not well understood. Due to a number of factors including size, packing, myelination and orientation of predominant cell types and related variations in conductivity across layers, some cortical layers may be more susceptible to stimulation than others. Current biophysical models of TES do not account for laminar specific differences in the electric field distribution. In this study we systematically mapped the electric field distribution during TES across cortical layers as a function of electrode montage, stimulation frequency and cortical depth. Using laminar multielectrode recordings (100 μm spacing, 24 contacts, implanted in V1) in an anesthetized cebus monkey we recorded TES induced potentials for two montages: 1. Anterior-Posterior current direction, electrodes placed over V1 and forehead. 2. Left–Right current direction, electrodes placed over bilateral temples. Stimulation intensity was 100 μA applied through round (3.14 cm2) Ag/AgCl electrodes. Measurements were performed using alternating currents with frequencies from 1–150 Hz for different depths (from dura through GM and WM). Electric fields were computed as the first spatial derivative of recorded potentials. We found a marked influence of the laminar structure on the electric field distribution (Download : Download high-res image (624KB)Download : Download full-size imageFig. 1A) with locally increased field strengths (Layer IV/V). This effect was dependent on current direction (Fig. 1B). The amplitude and phase of recorded potentials varied in a frequency and spatially dependent manner (Download : Download high-res image (444KB)Download : Download full-size imageFig. 2). Our results highlight differential effects of electric field propagation across cortical layers. Locally enhanced electric fields are likely due to currents passing across conductivity mismatches between layers. This effect is dependent on current orientation. Magnitude and phase of recorded potentials varied across the depth of cortex demonstrating changes in local electric properties of brain tissue. Larger phase shifts in deeper WM regions could be related to stronger capacitive influences from myelinated axons. In summary our results show previously unreported laminar specific effects of TES electric fields making a first step in the identification of cell specific targets for TES.