EEG/ECoG/EMG publications

The ability to detect deviations from expected sensory input is fundamental for adaptive behavior. We recorded electrocorticographic activity from the auditory (AC) and prefrontal (PFC) cortices of behaving macaques during an auditory oddball task to probe the cortical dynamics of predictive processing. Repetition of standard stimuli evoked suppression and facilitation in AC and strong low-frequency (2 Hz) enhancement in PFC, accompanied by bidirectional delta-band GC-defined interactions indicative of a shared predictive state. Deviant stimuli triggered earlier AC responses followed by PFC activation and increased GC-defined directed interactions across theta, alpha, and conventional gamma bands. Behavioral engagement amplified both repetition-related and deviance-related ECoG responses, strengthening cortical network coordination. Together, these findings reveal behaviorally gated auditory–prefrontal dynamics that are consistent with hierarchical predictive-processing accounts, while also allowing for contributions from repetition-, novelty-, and salience-related mechanisms.

Brain function relies on coordinated activity across spatial and temporal scales. Single neurons integrate local and long-range connectivity and reflect activity across brain-wide networks. Understanding integrated brain function requires tools capable of recording from anatomically connected populations in distributed brain areas to bridge local and global dynamics. Here, we present high-density, micro-electrocorticography arrays that facilitate multi-scale studies of brain activity. The hybrid arrays integrate the desirable features of silicone elastomers and polyimide films: silicone provides optical transparency and permits repeated penetration with intracortical arrays, while polyimide enables fine photolithographic feature definition. This combination facilitates high-throughput functional mapping to identify targets and insertion of intracortical arrays for dense local sampling. We demonstrate functional mapping in rats, cats, and marmosets, showing how functional maps guide multi-area laminar recordings. Finally, we demonstrate local and feedforward optogenetic stimulation to investigate cortico-cortical interactions. These capabilities establish the hybrid μECoG as a compelling tool for systems neuroscience.

The non-rapid-eye movement (NREM) sleep power spectrum is composed of rhythmic and arrhythmic components, respectively associated with brain rhythms and scale-free dynamics. Both components are hypothesized to represent distinct processes underlying sleep-dependent memory consolidation as well as other brain complex processes. Recent advancements in spectral parametrization techniques and the use of multifractal models have enabled new insights into these components and their connection to brain networks. Aging impacts NREM sleep oscillations, but no animal studies considered the impact of age on rhythmic and arrhythmic components. In this study, we assessed the effects of age on the power spectrum and its two components using local field potential recordings in mice. We recorded across the cerebral cortex and within the hippocampus—a central brain hub involved in NREM sleep-dependent cognitive processing. Ten younger (7.6 months) and eleven older (15.7 months) C57BL/6 J male and female mice were continuously recorded over a 24-hour period. We extracted the NREM sleep standard and rhythmic spectra, controlled for scale-free activity, and estimated multifractal arrhythmic properties during NREM sleep using the Wavelet Leader and Bootstrap based MultiFractal analysis toolbox. Older mice showed specific alterations in both components compared to younger animals: reduced rhythmic gamma power in the anterior cortex, greater regional differentiation of scaling exponents, and higher multifractal dispersion of the arrhythmic component in the hippocampus. These findings demonstrate that aging alters rhythmic and arrhythmic properties of NREM sleep in distinct brain regions, suggesting that both contribute to age-related changes in sleep-dependent cognition.

Purpose: We aim to develop a robust method to improve the estimation accuracy of motor-evoked potential (MEP) recruitment curves (RCs), including motor threshold, in small-sample settings which typically involve fewer than 40 stimuli. Methods: We present a hierarchical Bayesian (HB) method to model MEP size as a rectified-logistic function of stimulation intensity. This method is designed to account for small samples, handle outliers without discarding data, quantify estimation uncertainty, and simulate synthetic data that closely matches real observations, useful for optimizing experimental design. We validate its performance on transcranial magnetic stimulation (TMS), epidural spinal cord stimulation (SCS), and synthetic TMS datasets, and provide an open-source library for Python, called hbMEP, for diverse applications. Results: The rectified-logistic outperformed sigmoidal functions in predictive accuracy on TMS and SCS datasets, as demonstrated through cross-validation. A mixture extension of the HB model improved robustness to outliers by further increasing its predictive accuracy. The HB model reduced threshold estimation error by up to 70% on sparse synthetic TMS data compared to non-hierarchical models. Bayesian estimation with the HB model reduced the required number of participants by at least 23% to detect a shift in threshold with 80% power, compared to frequentist testing. Empirical results on human SCS data further validated its applicability to real data. Conclusion: By improving accuracy on sparse data, our method minimizes the number of stimuli needed to probe each individual's neuromuscular parameters across multiple muscles simultaneously, thereby reducing session duration and the risk of inadvertent neuromodulation. Our approach provides a more statistically powerful and conclusive framework for inferring changes in threshold, and therefore corticospinal excitability. The hbMEP library streamlines and unifies the analysis of RCs across stimulation modalities and experimental paradigms.

Most spinal cord injuries (SCI) spare descending and sublesional circuits that can be targeted through motor cortex and spinal cord stimulation to mitigate locomotor deficits. However, the potential synergy between cortical and spinal stimulation remains unknown. Here, we first investigated the phase-locked electrical stimulation of the motor cortex and lumbar spinal cord at 40 Hz in a rat model of unilateral SCI. Combining cortical and lumbar stimulation around the anticipated lift synergistically enhanced leg movements. When integrated into rehabilitation training, cortical stimulation proved essential for the recovery of skilled locomotion. We next investigated the effects of high-frequency (330 Hz) lumbar and sacral stimulation combined with cortical stimulation. Timely integration during the swing phase showed that cortical and lumbar stimulations enhance the initial and mid-swing phases, while sacral stimulation improves extension velocity in the late swing. These findings indicate that supraspinal and sublesional neuromodulation offer complementary neuroprosthetic effects in targeted SCI gait rehabilitation.

The locus coeruleus–norepinephrine (LC-NE) system regulates arousal and awakening; however, it remains unclear whether the LC does this in a global or circuit-specific manner. We hypothesized that sensory-evoked awakenings are predominantly regulated by specific LC-NE efferent pathways. Anatomical, physiological, and functional modularities of LC-NE pathways involving the mouse basal forebrain (BF) and pontine reticular nucleus (PRN) were tested. We found partial anatomical segregation between the LC → PRN and LC → BF circuits. Extracellular NE dynamics in BF and PRN exhibited distinct sound-evoked activation during sleep, including a fast sound-evoked NE peak specific to PRN. Causal optogenetic interrogation of LC efferent pathways, by retro-channelrhodopsin (ChR2) activation or Platynereis dumerilii ciliary opsin (PdCO) silencing of synapses in target regions, revealed a role for early LC → PRN activity in driving arousal and sound-evoked awakenings. Together, our results uncover a role for early LC-NE PRN activity in connecting sensory and arousal pathways and establish LC heterogeneity in regulating arousal.

The ability to detect deviations from expected sensory input is fundamental for adaptive behavior. We recorded electrocorticographic activity from the auditory (AC) and prefrontal (PFC) cortices of behaving macaques during an auditory oddball task to probe the cortical dynamics of predictive processing. Repetition of standard stimuli evoked suppression and facilitation in AC and strong low-frequency (2 Hz) enhancement in PFC, accompanied by bidirectional delta-band coupling indicative of a shared predictive state. Deviant stimuli triggered early AC responses followed by PFC activation and increased feedforward and feedback connectivity across delta, theta, and gamma bands. Behavioral engagement amplified both prediction and prediction error signals, strengthening cortical network coordination. Together, these findings reveal a hierarchical predictive network in which the AC encodes sensory regularities and violations, while the PFC integrates predictive context in a behaviorally dependent manner.

Restoring upper limb function is critical in individuals with central paralysis, and hand control is a priority in patients with neurological impairments. Functional electrical stimulation with implantable electrodes targeting the peripheral nervous system has the potential to selectively recruit hand muscles and generate multiple functional hand movements. However, the implantation of electrodes in the forearm or elbow areas requires multiple incisions for surgery, and elbow joint movements cannot be performed. In this study, we designed and implanted two epineural cuffs on the median and radial nerves in the distal brachial plexus of a single Japanese macaque ( Macaca fuscata ) monkey. The cuffs were successfully placed via an axillary approach using a single incision. Electrical stimuli were applied to innervate the contraction patterns of the hand, forearm, and triceps muscles relevant to the median and radial nerves. The evoked potentials of the target muscles electrically stimulated the distal brachial plexus to reliably and selectively innervate the upper limb muscles at the functional group level. Our results demonstrated that the distal brachial plexus can be a useful stimulation site for upper limb muscle contraction and that the axillary approach enables electrode placement to peripheral nerves required for upper limb control.

The ability of the brain to process auditory information across multiple temporal scales is crucial for perception. This study introduces an innovative experimental approach using nonlinguistic structured stimuli composed of click trains that alternate at different rates to investigate auditory processing across 3 distinct temporal scales: individual clicks (tens of milliseconds), click trains forming auditory objects (hundreds of milliseconds), and higher-order click trains in neuronal novelty detection (seconds) in both rhesus monkeys and humans. Electrocorticography recordings in the auditory cortex of rhesus monkeys unveil the primate brain’s remarkable ability to process intricate auditory temporal patterns at timescales of tens and hundreds of milliseconds. Furthermore, extracellular recordings in monkeys demonstrate pronounced responsiveness to deviant click trains at longer temporal scales in the primary auditory cortex (A1), accompanied by synchronization with both individual clicks and click trains. By contrast, neurons in the auditory thalamus prefer individual clicks only. Notably, neurons in A1 exhibit the ability to synchronize with individual clicks while simultaneously integrating these clicks into cohesive train objects, a phenomenon we term “temporal integration during synchronization”. Additional human electroencephalography recordings complement and support these findings, highlighting the paradigm’s potential for clinical applications. Our research offers novel insights into the neural mechanisms underpinning auditory information processing across various temporal scales at the neuronal level.

Micro-electrocorticography (µECoG) electrodes have emerged to balance the trade-off between invasiveness and signal quality in brain recordings. However, its large-scale applicability is still hindered by a lack of comparative studies assessing the relationship between ECoG and traditional recording methods such as penetrating electrodes. This study aimed to compare somatosensory evoked potentials (SEPs) through the lenses of a µECoG and an intracortical microelectrode array (MEA). The electrodes were implanted in the pig’s primary somatosensory cortex, while SEPs were generated by applying electrical stimulation to the ulnar nerve. The SEP amplitude, signal-to-noise ratio (SNR), power spectral density (PSD), and correlation structure were analysed. Overall, SEPs resulting from MEA recordings had higher amplitudes and contained significantly more spectral power, especially at higher frequencies. However, the SNRs were similar between the interfaces. These results demonstrate the feasibility of using µECoG to decode SEPs with wide-range applications in physiology monitoring and brain–computer interfaces.

Offset responses are traditionally viewed as indicators of sound cessation. Here, we investigate offset responses to auditory click trains, examining how they are modulated by inter-click intervals (ICIs) and train duration. Using extracellular recordings and electrocorticography (ECoG) in non-human primates, alongside electroencephalography (EEG) in humans, we show that offset responses are significantly influenced by both ICI and train length, thereby establishing them as markers of temporal integration. We introduce the concept of the 'Neuronal Integrative Window' (NIW), defined as the temporal span during which neurons integrate stimuli to produce or modulate the temporal integration signal. Our data reveal that on the neuronal level, the auditory cortex (AC) exhibits a more expansive NIW than the medial geniculate body (MGB), integrating stimuli over longer durations and showing a preference for larger ICIs. Furthermore, our results indicate that offset responses could serve as potential biomarkers for neurological and psychiatric conditions, highlighted by their sensitivity to pharmacological modulation with ketamine. This study advances our understanding of auditory temporal processing and proposes a novel approach for assessing and monitoring brain health.

Effective neural stimulation requires adequate parametrization. Gaussian-process (GP)-based Bayesian optimization (BO) offers a framework to discover optimal stimulation parameters in real time. Here, we first provide a general protocol to deploy this framework in neurostimulation interventions and follow by exemplifying its use in detail. Specifically, we describe the steps to implant rats with multi-channel electrode arrays in the hindlimb motor cortex. We then detail how to utilize the GP-BO algorithm to maximize evoked target movements, measured as electromyographic responses. For complete details on the use and execution of this protocol, please refer to Bonizzato and colleagues (2023).1.

Deformable semi-solid liquid metal particles (LMP) have emerged as a promising substitute for rigid conductive fillers due to their excellent electrical properties and stable conductance under strain. However, achieving a compact and robust coating of LMP on fibers remains a persistent challenge, mainly due to the incompatibility of conventional coating techniques with LMP. Additionally, the limited durability and absence of initial electrical conductivity of LMP restrict their widespread application. In this study, we propose a solution process that robustly and compactly assembles mechanically durable and initially conductive LMP on fibers. Specifically, we present a shearing-based deposition of polymer-attached LMP followed by additional coating with CNT-attached LMP to create bi-layer LMP composite with exceptional durability, electrical conductivity, stretchability, and biocompatibility on various fibers. The versatility and reliability of this manufacturing strategy for 1D electronics are demonstrated through the development of sewn electrical circuits, smart clothes, stretchable biointerfaced fiber, and multifunctional fiber probes.

Background During non-rapid eye movement sleep (NREM), alternating periods of synchronised high (ON period) and low (OFF period) neuronal activity are associated with high amplitude delta band (0.5–4 Hz) oscillations in neocortical electrophysiological signals termed slow waves. As this oscillation is dependent crucially on hyperpolarisation of cortical cells, there is an interest in understanding how neuronal silencing during OFF periods leads to the generation of slow waves and whether this relationship changes between cortical layers. A formal, widely adopted definition of OFF periods is absent, complicating their detection. Here, we grouped segments of high frequency neural activity containing spikes, recorded as multiunit activity from the neocortex of freely behaving mice, on the basis of amplitude and asked whether the population of low amplitude (LA) segments displayed the expected characteristics of OFF periods. Results Average LA segment length was comparable to previous reports for OFF periods but varied considerably, from as short as 8 ms to > 1 s. LA segments were longer and occurred more frequently in NREM but shorter LA segments also occurred in half of rapid eye movement sleep (REM) epochs and occasionally during wakefulness. LA segments in all states were associated with a local field potential (LFP) slow wave that increased in amplitude with LA segment duration. We found that LA segments > 50 ms displayed a homeostatic rebound in incidence following sleep deprivation whereas short LA segments (< 50 ms) did not. The temporal organisation of LA segments was more coherent between channels located at a similar cortical depth. Conclusion We corroborate previous studies showing neural activity signals contain uniquely identifiable periods of low amplitude with distinct characteristics from the surrounding signal known as OFF periods and attribute the new characteristics of vigilance-state-dependent duration and duration-dependent homeostatic response to this phenomenon. This suggests that ON/OFF periods are currently underdefined and that their appearance is less binary than previously considered, instead representing a continuum.

This study implements the use of Danish Landrace pigs as subjects for the long-term potentiation (LTP)-like pain model. This is accomplished by analyzing changes in the primary somatosensory cortex (S1) in response to electrical stimulation on the ulnar nerve after applying high-frequency electrical stimulation (HFS) on the ulnar nerve. In this study, eight Danish Landrace pigs were electrically stimulated, through the ulnar nerve, to record the cortically evoked response in S1 by a 16-channel microelectrode array (MEA). Six of these pigs were subjected to HFS (four consecutive, 15 mA, 100 Hz, 1000 µs pulse duration) 45 min after the start of the experiment. Two pigs were used as control subjects to compare the cortical response to peripheral electrical stimulation without applying HFS. Low-frequency components of the intracortical signals (0.3-300 Hz) were analyzed using event-related potential (ERP) analysis, where the minimum peak during the first 30-50 ms (N1 component) in each channel was detected. The change in N1 was compared over time across the intervention and control groups. Spectral analysis was used to demonstrate the effect of the intervention on the evoked cortical oscillations computed between 75 ms and 200 ms after stimulus. ERP analysis showed an immediate increase in N1 amplitude that became statistically significant 45 mins after HFS (p < 0.01) for the intervention group. The normalized change in power in frequency oscillations showed a similar trend. The results show that the LTP-like pain model can be effectively implemented in pigs using HFS since the cortical responses are comparable to those described in humans.

The strength of cortical connectivity to the striatum influences the balance between behavioral variability and stability. Learning to consistently produce a skilled action requires plasticity in corticostriatal connectivity associated with repeated training of the action. However, it remains unknown whether such corticostriatal plasticity occurs during training itself or ‘offline’ during time away from training, such as sleep. Here, we monitor the corticostriatal network throughout long-term skill learning in rats and find that non-rapid-eye-movement (NREM) sleep is a relevant period for corticostriatal plasticity. We first show that the offline activation of striatal NMDA receptors is required for skill learning. We then show that corticostriatal functional connectivity increases offline, coupled to emerging consistent skilled movements, and coupled cross-area neural dynamics. We then identify NREM sleep spindles as uniquely poised to mediate corticostriatal plasticity, through interactions with slow oscillations. Our results provide evidence that sleep shapes cross-area coupling required for skill learning.

Background Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. Methods We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation. Results Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation. Conclusions Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies’ activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.

Sieve electrodes stand poised to deliver the selectivity required for driving advanced prosthetics but are considered inherently invasive and lack the stability required for a chronic solution. This proof of concept experiment investigates the potential for the housing and engagement of a sieve electrode within the medullary canal as part of an osseointegrated neural interface (ONI) for greater selectivity toward improving prosthetic control. The working hypotheses are that (A) the addition of a sieve interface to a cuff electrode housed within the medullary canal of the femur as part of an ONI would be capable of measuring efferent and afferent compound nerve action potentials (CNAPs) through a greater number of channels; (B) that signaling improves over time; and (C) that stimulation at this interface generates measurable cortical somatosensory evoked potentials through a greater number of channels. The modified ONI was tested in a rabbit ( n = 1) amputation model over 12 weeks, comparing the sieve component to the cuff, and subsequently compared to historical data. Efferent CNAPs were successfully recorded from the sieve demonstrating physiological improvements in CNAPs between weeks 3 and 5, and somatosensory cortical responses recorded at 12 weeks postoperatively. This demonstrates that sieve electrodes can be housed and function within the medullary canal, demonstrated by improved nerve engagement and distinct cortical sensory feedback. This data presents the conceptual framework for housing more sophisticated sieve electrodes in bone as part of an ONI for improving selectivity with percutaneous connectivity toward improved prosthetic control.

Background Electrical stimulation of residual afferent nerve fibers can evoke sensations from a missing limb after amputation, and bionic arms endowed with artificial sensory feedback have been shown to confer functional and psychological benefits. Here we explore the extent to which artificial sensations can be discriminated based on location, quality, and intensity. Methods We implanted Utah Slanted Electrode Arrays (USEAs) in the arm nerves of three transradial amputees and delivered electrical stimulation via different electrodes and frequencies to produce sensations on the missing hand with various locations, qualities, and intensities. Participants performed blind discrimination trials to discriminate among these artificial sensations. Results Participants successfully discriminated cutaneous and proprioceptive sensations ranging in location, quality and intensity. Performance was significantly greater than chance for all discrimination tasks, including discrimination among up to ten different cutaneous location-intensity combinations (15/30 successes, p < 0.0001) and seven different proprioceptive location-intensity combinations (21/40 successes, p < 0.0001). Variations in the site of stimulation within the nerve, via electrode selection, enabled discrimination among up to five locations and qualities (35/35 successes, p < 0.0001). Variations in the stimulation frequency enabled discrimination among four different intensities at the same location (13/20 successes, p < 0.0005). One participant also discriminated among individual stimulation of two different USEA electrodes, simultaneous stimulation on both electrodes, and interleaved stimulation on both electrodes (20/24 successes, p < 0.0001). Conclusion Electrode location, stimulation frequency, and stimulation pattern can be modulated to evoke functionally discriminable sensations with a range of locations, qualities, and intensities. This rich source of artificial sensory feedback may enhance functional performance and embodiment of bionic arms endowed with a sense of touch.

Glassy carbon (GC) has high potential to serve as a biomaterial in neural applications because it is biocompatible, electrochemically inert and can be incorporated in polyimide-based implantable devices. Miniaturization and applicability of GC is, however, thought to be partially limited by its electrical conductivity. For this study, ultra-conformable polyimide-based electrocorticography (ECoG) devices with different-diameter GC electrodes were fabricated and tested in vitro and in rat models. For achieving conformability to the rat brain, polyimide was patterned in a finger-like shape and its thickness was set to 8 µm. To investigate different electrode sizes, each ECoG device was assigned electrodes with diameters of 50, 100, 200 and 300 µm. They were electrochemically characterized and subjected to 10 million biphasic pulses—for achieving a steady-state—and to X-ray photoelectron spectroscopy, for examining their elemental composition. The electrodes were then implanted epidurally to evaluate the ability of each diameter to detect neural activity. Results show that their performance at low frequencies (up to 300 Hz) depends on the distance from the signal source rather than on the electrode diameter, while at high frequencies (above 200 Hz) small electrodes have higher background noises than large ones, unless they are coated with poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS).