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Background: Notwithstanding advances with low-intensity transcranial electrical stimulation (tES), there remain questions about the efficacy of clinically realistic electric fields on neuronal function. Objective: To measure electric fields magnitude and their effects on neuronal firing rate of hippocampal neurons in freely moving rats, and to establish calibrated computational models of current flow. Methods: Current flow models were calibrated on electric field measures in the motor cortex (n = 2 anesthetized rats) and hippocampus. A Neuropixels 2.0 probe with 384 channels was used in an in-vivo rat model of tES (n = 4 freely moving and 2 urethane anesthetized rats) to detect effects of weak fields on neuronal firing rate. High-density field mapping and computational models verified field intensity (1 V/m in hippocampus per 50 μA of applied skull currents). Results: Electric fields of as low as 0.35 V/m (0.25–0.47) acutely modulated average firing rate in the hippocampus. At these intensities, firing rate effects increased monotonically with electric field intensity at a rate of 11.5 % per V/m (7.2–18.3). For the majority of excitatory neurons, firing increased for soma-depolarizing stimulation and diminished for soma-hyperpolarizing stimulation. While more diverse, the response of inhibitory neurons followed a similar pattern on average, likely as a result of excitatory drive. Conclusion: In awake animals, electric fields modulate spiking rate above levels previously observed in vitro. Firing rate effects are likely mediated by somatic polarization of pyramidal neurons. We recommend that all future rodent experiments directly measure electric fields to insure rigor and reproducibility.

Summary: Narratives can synchronize neural and physiological signals between individuals, but the relationship between these signals, and the underlying mechanism, is unclear. We hypothesized a top-down effect of cognition on arousal and predicted that auditory narratives will drive not only brain signals but also peripheral physiological signals. We find that auditory narratives entrained gaze variation, saccade initiation, pupil size, and heart rate. This is consistent with a top-down effect of cognition on autonomic function. We also hypothesized a bottom-up effect, whereby autonomic physiology affects arousal. Controlled breathing affected pupil size, and heart rate was entrained by controlled saccades. Additionally, fluctuations in heart rate preceded fluctuations of pupil size and brain signals. Gaze variation, pupil size, and heart rate were all associated with anterior-central brain signals. Together, these results suggest bidirectional causal effects between peripheral autonomic function and central brain circuits involved in the control of arousal.

Abstract In this work, we present a dataset that combines functional magnetic imaging (fMRI) and electroencephalography (EEG) to use as a resource for understanding human brain function in these two imaging modalities. The dataset can also be used for optimizing preprocessing methods for simultaneously collected imaging data. The dataset includes simultaneously collected recordings from 22 individuals (ages: 23–51) across various visual and naturalistic stimuli. In addition, physiological, eye tracking, electrocardiography, and cognitive and behavioral data were collected along with this neuroimaging data. Visual tasks include a flickering checkerboard collected outside and inside the MRI scanner (EEG-only) and simultaneous EEG-fMRI recordings. Simultaneous recordings include rest, the visual paradigm Inscapes, and several short video movies representing naturalistic stimuli. Raw and preprocessed data are openly available to download. We present this dataset as part of an effort to provide open-access data to increase the opportunity for discoveries and understanding of the human brain and evaluate the correlation between electrical brain activity and blood oxygen level-dependent (BOLD) signals.

Abstract 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.

Background and objectives: Motor learning experiments with transcranial direct current stimulation (tDCS) at 2 mA have produced mixed results. We hypothesize that tDCS boosts motor learning provided sufficiently high field intensity on the motor cortex. Methods: In a single-blinded design, 108 healthy participants received either anodal (N = 36) or cathodal (N = 36) tDCS at 4 mA total, or no stimulation (N = 36) while they practiced a 12-min sequence learning task. Anodal stimulation was delivered across four electrode pairs (1 mA each), with anodes above the right parietal lobe and cathodes above the right frontal lobe. Cathodal stimulation, with reversed polarities, served as an active control for sensation, while the no-stimulation condition established baseline performance. fMRI-localized targets on the primary motor cortex in 10 subjects were used in current flow models to optimize electrode placement for maximal field intensity. A single electrode montage was then selected for all participants. Results: We found a significant difference in performance with anodal vs. cathodal stimulation (Cohen's d = 0.71) and vs. no stimulation (d = 0.56). This effect persisted for at least 1 h, and subsequent learning for a new sequence and the opposite hand also improved. Sensation ratings were comparable in the active groups and did not exceed moderate levels. Current flow models suggest the new electrode montage can achieve stronger motor cortex polarization than alternative montages. Conclusion: The present paradigm shows a medium to large effect size and is well-tolerated. It may serve as a go-to experiment for future studies on motor learning and tDCS.

Background: Electric fields generated during direct current stimulation (DCS) are known to modulate activity-dependent synaptic plasticity in-vitro. This provides a mechanistic explanation for the lasting behavioral effects observed with transcranial direct current stimulation (tDCS) in human learning experiments. However, previous in-vitro synaptic plasticity experiments show relatively small effects despite using strong fields compared to what is expected with conventional tDCS in humans (20 V/m vs. 1 V/m). There is therefore a need to improve the effectiveness of tDCS at realistic field intensities. Here we leverage the observation that effects of learning are known to accumulate over multiple bouts of learning, known as spaced learning. Hypothesis: We propose that effects of DCS on synaptic long-term potentiation (LTP) accumulate over time in a spaced learning paradigm, thus revealing effects at more realistic field intensities. Methods: We leverage a standard model for spaced learning by inducing LTP with repeated bouts of theta burst stimulation (TBS) in hippocampal slice preparations. We studied the cumulative effects of DCS paired with TBS at various intensities applied during the induction of LTP in the CA1 region of rat hippocampal slices. Results: As predicted, DCS applied during repeated bouts of theta burst stimulation (TBS) resulted in an increase of LTP. This spaced learning effect is saturated quickly with strong TBS protocols and stronger fields. In contrast, weaker TBS and the weakest electric fields of 2.5 V/m resulted in the strongest relative efficacies (12% boost in LTP per 1 V/m applied). Conclusions: Weak DCS causes a relatively strong cumulative effect of spaced learning on synaptic plasticity. Staturarion may have masked stronger effects sizes in previous in-vitro studies. Relative effect sizes of DCS are now closer in line with human tDCS experiments.

Background: Transcranial direct current stimulation (DCS) has lasting effects that may be explained by a boost in synaptic long-term potentiation (LTP). We hypothesized that this boost is the result of a modulation of somatic spiking in the postsynaptic neuron, as opposed to indirect network effects. To test this directly we record somatic spiking in a postsynaptic neuron during LTP induction with concurrent DCS. Methods: We performed rodent in-vitro patch-clamp recordings at the soma of individual CA1 pyramidal neurons. LTP was induced with theta-burst stimulation (TBS) applied concurrently with DCS. To test the causal role of somatic polarization, we manipulated polarization via current injections. We also used a computational multi-compartment neuron model that captures the effect of electric fields on membrane polarization and activity-dependent synaptic plasticity. Results: TBS-induced LTP was enhanced when paired with anodal DCS as well as depolarizing current injections. In both cases, somatic spiking during the TBS was increased, suggesting that evoked somatic activity is the primary factor affecting LTP modulation. However, the boost of LTP with DCS was less than expected given the increase in spiking activity alone. In some cells, we also observed DCS-induced spiking, suggesting DCS also modulates LTP via induced network activity. The computational model reproduces these results and suggests that they are driven by both direct changes in postsynaptic spiking and indirect changes due to network activity. Conclusion: DCS enhances synaptic plasticity by increasing postsynaptic somatic spiking, but we also find that an increase in network activity may boost but also limit this enhancement.

Background: Skin sensation is the primary factor limiting the intensity of transcranial electrical stimulation (tES). It is well established that different waveforms generate different sensations, yet transcranial stimulation has been limited to a relatively small number of prototypical waveforms. Objective: We explore whether alternative stimulation waveforms could substantially reduce skin sensation and thus allow for stronger intensities in tES. Methods: We systematically tested a range of waveforms in a series of 6 exploratory experiments stimulating human adults on the forearm and in one instance on the head. Subjects were asked to rate skin sensation level on a numerical scale from “none” to “extreme”. Results: High frequency (>1 kHz) monophasic square wave stimulation was found to decrease in sensation with increasing duty cycle, baseline, and frequency, but the sensation was never lower than for constant current stimulation. For the purpose of injecting a net direct current (DC), a constant current is optimal. For stimulation with alternating current (AC), sensation decreased with increasing frequency, consistent with previous reports. Amplitude modulation did not reduce sensation below stimulation with constant AC amplitude, and biphasic square waveforms produced higher sensation levels than biphasic sinusoidal waveforms. Furthermore, for DC stimulation, sensation levels on the arm were similar to those reported on the head. Conclusion: Our comparisons of various waveforms for monophasic and biphasic stimulation indicate that conventional DC and AC waveforms may provide the lowest skin sensations levels for transcutaneous electrical stimulation. These results are likely generalizable to tES applications.

Background: Temporal interference (TI) stimulation of the brain generates amplitude-modulated electric fields oscillating in the kHz range with the goal of non-invasive targeted deep brain stimulation. Yet, the current intensities required in human (sensitivity) to modulate deep brain activity and if superficial brain region are spared (selectivity) at these intensities remains unclear. Objective: We developed an experimentally constrained theory for TI sensitivity to kHz electric field given the attenuation by membrane low-pass filtering property, and for TI selectivity to deep structures given the distribution of modulated and unmodulated electric fields in brain. Methods: The electric field threshold to modulate carbachol-induced gamma oscillations in rat hippocampal slices was determined for unmodulated 0.05–2 kHz sine waveforms, and 5 Hz amplitude-modulated waveforms with 0.1–2 kHz carrier frequencies. The neuronal effects are replicated with a computational network model to explore the underlying mechanisms, and then coupled to a validated current-flow model of the human head. Results: Amplitude-modulated electric fields are stronger in deep brain regions, while unmodulated electric fields are maximal at the cortical regions. Both experiment and model confirmed the hypothesis that spatial selectivity of temporal interference stimulation depends on the phasic modulation of neural oscillations only in deep brain regions. Adaptation mechanism (e.g. GABAb) enhanced sensitivity to amplitude modulated waveform in contrast to unmodulated kHz and produced selectivity in modulating gamma oscillation (i.e. Higher gamma modulation in amplitude modulated vs unmodulated kHz stimulation). Selection of carrier frequency strongly affected sensitivity to amplitude modulation stimulation. Amplitude modulated stimulation with 100 Hz carrier frequency required ∼5 V/m (corresponding to ∼13 mA at the scalp surface), whereas, 1 kHz carrier frequency ∼60 V/m (∼160 mA) and 2 kHz carrier frequency ∼80 V/m (∼220 mA) to significantly modulate gamma oscillation. Sensitivity is increased (scalp current required decreased) for theoretical neuronal membranes with faster time constants. Conclusion: The TI sensitivity (current required at the scalp) depends on the neuronal membrane time-constant (e.g. axons) approaching the kHz carrier frequency. TI selectivity is governed by network adaption (e.g. GABAb) that is faster than the amplitude-modulation frequency. Thus, we show neuronal and network oscillations time-constants determine the scalp current required and the selectivity achievable with TI in humans.

Background: There is evidence that transcranial direct current stimulation (tDCS) can improve learning performance. Arguably, this effect is related to long term potentiation (LTP), but the precise biophysical mechanisms remain unknown. Hypothesis: We propose that direct current stimulation (DCS) causes small changes in postsynaptic membrane potential during ongoing endogenous synaptic activity. The altered voltage dynamics in the postsynaptic neuron then modify synaptic strength via the machinery of endogenous voltage-dependent Hebbian plasticity. This hypothesis predicts that DCS should exhibit Hebbian properties, namely pathway specificity and associativity. Methods: We studied the effects of DCS applied during the induction of LTP in the CA1 region of rat hippocampal slices and using a biophysical computational model. Results: DCS enhanced LTP, but only at synapses that were undergoing plasticity, confirming that DCS respects Hebbian pathway specificity. When different synaptic pathways cooperated to produce LTP, DCS enhanced this cooperation, boosting Hebbian associativity. Further slice experiments and computer simulations support a model where polarization of postsynaptic pyramidal neurons drives these plasticity effects through endogenous Hebbian mechanisms. The model is able to reconcile several experimental results by capturing the complex interaction between the induced electric field, neuron morphology, and endogenous neural activity. Conclusions: These results suggest that tDCS can enhance associative learning. We propose that clinical tDCS should be applied during tasks that induce Hebbian plasticity to harness this phenomenon, and that the effects should be task specific through their interaction with endogenous plasticity mechanisms. Models that incorporate brain state and plasticity mechanisms may help to improve prediction of tDCS outcomes.

Summary: Heart rate has natural fluctuations that are typically ascribed to autonomic function. Recent evidence suggests that conscious processing can affect the timing of the heartbeat. We hypothesized that heart rate is modulated by conscious processing and therefore dependent on attentional focus. To test this, we leverage the observation that neural processes synchronize between subjects by presenting an identical narrative stimulus. As predicted, we find significant inter-subject correlation of heart rate (ISC-HR) when subjects are presented with an auditory or audiovisual narrative. Consistent with our hypothesis, we find that ISC-HR is reduced when subjects are distracted from the narrative, and higher ISC-HR predicts better recall of the narrative. Finally, patients with disorders of consciousness have lower ISC-HR, as compared to healthy individuals. We conclude that heart rate fluctuations are partially driven by conscious processing, depend on attentional state, and may represent a simple metric to assess conscious state in unresponsive patients.

A variety of psychiatric, behavioral and cognitive phenotypes have been linked to brain ‘’functional connectivity’’ -- the pattern of correlation observed between different brain regions. Most commonly assessed using functional magnetic resonance imaging (fMRI), here, we investigate the connectivity-phenotype associations with functional connectivity measured with electroencephalography (EEG), using phase-coupling. We analyzed data from the publicly available Healthy Brain Network Biobank. This database compiles a growing sample of children and adolescents, currently encompassing 1657 individuals. Among a variety of assessment instruments we focus on ten phenotypic and additional demographic measures that capture most of the variance in this sample. The largest effect sizes are found for age and sex for both fMRI and EEG. We replicate previous findings of an association of Intelligence Quotient (IQ) and Attention Deficit Hyperactivity Disorder (ADHD) with the pattern of fMRI functional connectivity. We also find an association with socioeconomic status, anxiety and the Child Behavior Checklist Score. For EEG we find a significant connectivity-phenotype relationship with IQ. The actual spatial patterns of functional connectivity are quite different between fMRI and source-space EEG. However, within EEG we observe clusters of functional connectivity that are consistent across frequency bands. Additionally we analyzed reproducibility of functional connectivity. We compare connectivity obtained with different tasks, including resting state, a video and a visual flicker task. For both EEG and fMRI the variation between tasks was smaller than the variability observed between subjects. We also found an increase of reliability with increasing frequency of the EEG, and increased sampling duration. We conclude that, while the patterns of functional connectivity are distinct between fMRI and phase-coupling of EEG, they are nonetheless similar in their robustness to the task, and similar in that idiosyncratic patterns of connectivity predict individual phenotypes.

Odors can be powerful stimulants. It is well-established that odors provide strong cues for recall of locations, people and events. The effects of specific scents on other cognitive functions are less well-established. We hypothesized that scents with different odor qualities will have a different effect on attention. To assess attention, we used Inter-Subject Correlation of the EEG because this metric is strongly modulated by attentional engagement with natural audiovisual stimuli. We predicted that scents known to be “energizing” would increase Inter-Subject Correlation during watching of videos as compared to “calming” scents. In a first experiment, we confirmed this for eucalyptol and linalool while participants watched animated autobiographical narratives. The result was replicated in a second experiment, but did not generalize to limonene, also considered an “energizing” odorant. In a third, double-blind experiment, we tested a battery of scents including single molecules, as well as mixtures, as participants watched various short video clips. We found a varying effect of odor on Inter-Subject Correlation across the various scents. This study provides a basis for reliably and reproducibly assessing effects of odors on brain activity. Future research is needed to further explore the effect of scent-based up-modulation in engagement on learning and memory performance. Educators, product developers and fragrance brands might also benefit from such objective neurophysiological measures.

Transcranial electrical stimulation techniques, such as tDCS and tACS, are popular tools for neuroscience and clinical therapy, but how low-intensity current might modulate brain activity remains unclear. In this review, the authors review the evidence on mechanisms of transcranial electrical stimulation.

Complex networks can be used to model brain networks. Here the authors identify the essential nodes in a model of a brain network and then validate these predictions by means of in vivo pharmacogenetic interventions. They find that the nucleus accumbens is a central region for brain integration.

Transcranial alternating current stimulation (tACS) has been proposed to enhance neural rhythms supporting memory. Here, the authors leverage human intracranial recordings to show that low-frequency tACS does not entrain key rhythms in non-REM sleep or resting wakefulness.

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4−7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation.

Abstract It is said that we lose track of time - that “time flies” - when we are engrossed in a story. How does engagement with the story cause this distorted perception of time, and what are its neural correlates? People commit both time and attentional resources to an engaging stimulus. For narrative videos, attentional engagement can be represented as the level of similarity between the electroencephalographic responses of different viewers. Here we show that this measure of neural engagement predicted the duration of time that viewers were willing to commit to narrative videos. Contrary to popular wisdom, engagement did not distort the average perception of time duration. Rather, more similar brain responses resulted in a more uniform perception of time across viewers. These findings suggest that by capturing the attention of an audience, narrative videos bring both neural processing and the subjective perception of time into synchrony.

It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Figure 11. The corrected figures are now properly calibrated to 1 mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section ‘Intensity ranged from 0.5 to 2.5 mA (current density 0.125–0.625 mA mA/cm2), which is stronger than in previous reports’, should have read ‘Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625–0.3125 mA/cm2), which is stronger than in previous reports.’ These errors do not affect any of the Article’s conclusions.

The original version of this Article contained an error in the last sentence of the first paragraph of the Introduction, which incorrectly read ‘Correlation of brain activity is typically measured using functional magnetic resonance imaging (fMRI), and the correlation structure is often referred to as “fu’. The correct version states ‘referred to as “functional connectivity”2–6’ in place of ‘referred to as “fu’. This has been corrected in both the PDF and HTML versions of the Article.

Music maintains a characteristic balance between repetition and novelty. Here, we report a similar balance in singing performances of free-living Australian pied butcherbirds. Their songs include many phrase types. The more phrase types in a bird's repertoire, the more diverse the singing performance can be. However, without sufficient temporal organization, avian listeners may find diverse singing performances difficult to perceive and memorize. We tested for a correlation between the complexity of song repertoire and the temporal regularity of singing performance. We found that different phrase types often share motifs (notes or stereotyped groups of notes). These shared motifs reappeared in strikingly regular temporal intervals across different phrase types, over hundreds of phrases produced without interruption by each bird. We developed a statistical estimate to quantify the degree to which phrase transition structure is optimized for maximizing the regularity of shared motifs. We found that transition probabilities between phrase types tend to maximize regularity in the repetition of shared motifs, but only in birds of high repertoire complexity. Conversely, in birds of low repertoire complexity, shared motifs were produced with less regularity. The strong correlation between repertoire complexity and motif regularity suggests that birds possess a mechanism that regulates the temporal placement of shared motifs in a manner that takes repertoire complexity into account. We discuss alternative musical, mechanistic and ecological explanations to this effect.

Rhythmic neuronal activity is ubiquitous in the human brain. These rhythms originate from a variety of different network mechanisms, which give rise to a wide-ranging spectrum of oscillation frequencies. In the last few years an increasing number of clinical research studies have explored transcranial alternating current stimulation (tACS) with weak current as a tool for affecting brain function. The premise of these interventions is that tACS will interact with ongoing brain oscillations. However, the exact mechanisms by which weak currents could affect neuronal oscillations at different frequency bands are not well known and this, in turn, limits the rational optimization of human experiments. Here we review the available in vitro and in vivo animal studies that attempt to provide mechanistic explanations. The findings can be summarized into a few generic principles, such as periodic modulation of excitability, shifts in spike timing, modulation of firing rate, and shifts in the balance of excitation and inhibition. These effects result from weak but simultaneous polarization of a large number of neurons. Whether this can lead to an entrainment or a modulation of brain oscillations, or whether AC currents have no effect at all, depends entirely on the specific dynamic that gives rise to the different brain rhythms, as discussed here for slow wave oscillations (~1 Hz) and gamma oscillations (~30 Hz). We conclude with suggestions for further experiments to investigate the role of AC stimulation for other physiologically relevant brain rhythms.

Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta-band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing, and that naturalistic brain states such as engagement may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.