EEG/ECoG/EMG publications

Introduction Benzodiazepines (BDZs) are commonly used to treat the symptoms of movement disorders; however, deep brain stimulation (DBS) has become a popular treatment for these disorders. Previous studies have investigated the effects of BDZ on cortical activity, no data are currently available on their effects on deep brain regions, nor on these regions’ responses to DBS. How the BDZ affects the thalamus and basal ganglia in dystonia patients remains unknown. Methods DBS recordings were performed in ventral oralis anterior/posterior (VoaVop), ventral intermediate (VIM) and ventral anterior (VA) thalamic subnuclei, as well as globus pallidus interna (GPi) and subthalamic nucleus (STN). Evoked potentials (EP) and frequency domain analysis were performed to determine the BDZ effect on neural activities compared to the control condition (off-BDZ). Three male pediatric patients with dystonia treated with BDZ and undergoing depth electrode evaluation for clinical targeting were recruited for the study. Stimulation was administered at 25 and 55 Hz frequencies and recordings were simultaneously gathered through pairs of externalized stereoelectroencephalography (sEEG) electrodes. EP amplitude and the effect of stimulation on the frequency spectrum of activity were compared at baseline and following clinical administration of BDZ. Results Frequency analysis showed consistent reductions in activity during BDZ treatment in all studied brain regions for all patients. Evoked potential (EP) analysis showed increased subthalamic nucleus (STN) EP amplitude and decreased ventral intermediate (VIM) and STN EP amplitude during BDZ treatment. Interpretation BDZs reduce thalamic and basal ganglia activity in multiple regions and alter the efficacy of transmission between these regions. While the mechanism is unknown our results confirm the known widespread effects of this class of medications and identify specific areas within the motor system that are directly affected.

The rate model of basal ganglia function predicts that muscle activity in dystonia is due to disinhibition of thalamus resulting from decreased inhibitory input from pallidum. We seek to test this hypothesis in children with dyskinetic cerebral palsy undergoing evaluation for deep brain stimulation (DBS) to analyze movement-related activity in different brain regions. The results revealed prominent beta-band frequency peaks in the globus pallidus interna (GPi), ventral oralis anterior/posterior (VoaVop) subnuclei of the thalamus, and subthalamic nucleus (STN) during movement but not at rest. Connectivity analysis indicated stronger coupling between STN-VoaVop and STN-GPi compared to GPi-STN. These findings contradict the hypothesis of decreased thalamic inhibition in dystonia, suggesting that abnormal patterns of inhibition and disinhibition, rather than reduced GPi activity, contribute to the disorder. Additionally, the study implies that correcting abnormalities in GPi function may explain the effectiveness of DBS targeting the STN and GPi in treating dystonia.

The perception of pitch is a fundamental percept, which is mediated by the auditory system, requiring the abstraction of stimulus properties related to the spectro-temporal structure of sound. Despite its importance, there is still debate as to the precise areas responsible for its encoding, which may be due to species differences or differences in the recording measures and choices of stimuli used in previous studies. Moreover, it was unknown whether the human brain contains pitch neurons and how distributed such neurons might be. Here, we present the first study to measure multiunit neural activity in response to pitch stimuli in the auditory cortex of intracranially implanted humans. The stimulus sets were regular-interval noise with a pitch strength that is related to the temporal regularity and a pitch value determined by the repetition rate and harmonic complexes. Specifically, we demonstrate reliable responses to these different pitch-inducing paradigms that are distributed throughout Heschl’s gyrus, rather than being localized to a particular region, and this finding was evident regardless of the stimulus presented. These data provide a bridge across animal and human studies and aid our understanding of the processing of a critical percept associated with acoustic stimuli.

The subthalamic nucleus (STN) is hypothesized to play a central role in neural processes that regulate self-control. Still uncertain, however, is how that brain structure participates in the dynamically evolving estimation of value that underlies the ability to delay gratification and wait patiently for a gain. To address that gap in knowledge, we studied the spiking activity of neurons in the STN of monkeys during a task in which animals were required to remain motionless for varying periods of time in order to obtain food reward. At the single-neuron and population levels, we found a cost–benefit integration between the desirability of the expected reward and the imposed delay to reward delivery, with STN signals that dynamically combined both attributes of the reward to form a single integrated estimate of value. This neural encoding of subjective value evolved dynamically across the waiting period that intervened after instruction cue. Moreover, this encoding was distributed inhomogeneously along the antero-posterior axis of the STN such that the most dorso-posterior-placed neurons represented the temporal discounted value most strongly. These findings highlight the selective involvement of the dorso-posterior STN in the representation of temporally discounted rewards. The combination of rewards and time delays into an integrated representation is essential for self-control, the promotion of goal pursuit, and the willingness to bear the costs of time delays.

Biocompatible and plastic neural interface devices allow for minimally invasive recording of brain activity. Increasing electrode density in such devices is essential for high-resolution neural recordings. Superimposing conductive leads in devices can help multiply the number of recording sites while keeping probes width small and suitable for implantation. However, because of leads' vertical proximity, this can create capacitive coupling (CC) between overlapping channels, which leads to crosstalk. Here, we present a thorough investigation of CC phenomenon in multi-gold layer thin-film multi-electrode arrays with a parylene C (PaC) insulation layer between superimposed leads. We also propose a guideline on the design, fabrication, and characterization of such type of neural interface devices for high spatial resolution recording. Our results demonstrate that the capacitance created through CC between superimposed tracks decreases non-linearly and then linearly with the increase of insulation thickness. We identify an optimal PaC insulation thickness that leads to a drastic reduction of CC between superimposed gold channels while not significantly increasing the overall device thickness. Finally, we show that double gold layer electrocorticography probes with the optimal insulation thickness exhibit similar performances in vivo when compared to single-layer devices. This confirms that these probes are adequate for high-quality neural recordings.

We report on the power spectral analysis of multiunit activity (MUA) of lumbar spinal interneurons during a locomotor task. In line with prior studies, we found evidence of greater power at the frequency of locomotion in high lumbar segments and during the flexion phase. Our results also confirm prior observations from our laboratory that the rhythmically active MUA behaves as a longitudinal standing wave of neural activation that is flexor dominant.

Application of closed-loop approaches in systems neuroscience and brain-computer interfaces holds great promise for revolutionizing our understanding of the brain and for developing novel neuromodulation strategies to restore lost function. The anterior forebrain mesocircuit (AFM) of the mammalian brain is hypothesized to underlie arousal regulation of the cortex and striatum, and support cognitive functions during wakefulness. Dysfunction of arousal regulation is hypothesized to contribute to cognitive dysfunctions in various neurological disorders, and most prominently in patients following traumatic brain injury (TBI). Several clinical studies have explored the use of daily central thalamic deep brain stimulation (CT-DBS) within the AFM to restore consciousness and executive attention in TBI patients. In this study, we explored the use of closed-loop CT-DBS in order to episodically regulate arousal of the AFM of a healthy non-human primate (NHP) with the goal of restoring behavioral performance. We used pupillometry and near real-time analysis of ECoG signals to episodically initiate closed-loop CT-DBS and here we report on our ability to enhance arousal and restore the animal's performance. The initial computer based approach was then experimentally validated using a customized clinical-grade DBS device, the DyNeuMo-X, a bi-directional research platform used for rapidly testing closed-loop DBS. The successful implementation of the DyNeuMo-X in a healthy NHP supports ongoing clinical trials employing the internal DyNeuMo system (NCT05437393, NCT05197816) and our goal of developing and accelerating the deployment of novel neuromodulation approaches to treat cognitive dysfunction in patients with structural brain injuries and other etiologies.

In bistable perception, observers experience alternations between two interpretations of an unchanging stimulus. Neurophysiological studies of bistable perception typically partition neural measurements into stimulus-based epochs and assess neuronal differences between epochs based on subjects' perceptual reports. Computational studies replicate statistical properties of percept durations with modeling principles like competitive attractors or Bayesian inference. However, bridging neuro-behavioral findings with modeling theory requires the analysis of single-trial dynamic data. Here, we propose an algorithm for extracting nonstationary timeseries features from single-trial electrocorticography (ECoG) data. We applied the proposed algorithm to 5-min ECoG recordings from human primary auditory cortex obtained during perceptual alternations in an auditory triplet streaming task (six subjects: four male, two female). We report two ensembles of emergent neuronal features in all trial blocks. One ensemble consists of periodic functions that encode a stereotypical response to the stimulus. The other comprises more transient features and encodes dynamics associated with bistable perception at multiple time scales: minutes (within-trial alternations), seconds (duration of individual percepts), and milliseconds (switches between percepts). Within the second ensemble, we identified a slowly drifting rhythm that correlates with the perceptual states and several oscillators with phase shifts near perceptual switches. Projections of single-trial ECoG data onto these features establish low-dimensional attractor-like geometric structures invariant across subjects and stimulus types. These findings provide supporting neural evidence for computational models with oscillatory-driven attractor-based principles. The feature extraction techniques described here generalize across recording modality and are appropriate when hypothesized low-dimensional dynamics characterize an underlying neural system. SIGNIFICANCE STATEMENT Irrespective of the sensory modality, neurophysiological studies of multistable perception have typically investigated events time-locked to the perceptual switching rather than the time course of the perceptual states per se. Here, we propose an algorithm that extracts neuronal features of bistable auditory perception from largescale single-trial data while remaining agnostic to the subject's perceptual reports. The algorithm captures the dynamics of perception at multiple timescales, minutes (within-trial alternations), seconds (durations of individual percepts), and milliseconds (timing of switches), and distinguishes attributes of neural encoding of the stimulus from those encoding the perceptual states. Finally, our analysis identifies a set of latent variables that exhibit alternating dynamics along a low-dimensional manifold, similar to trajectories in attractor-based models for perceptual bistability.

Sleep is ubiquitous and essential, but its mechanisms remain unclear. Studies in animals and humans have provided insights of sleep at vastly different spatiotemporal scales. However, challenges remain to integrate local and global information of sleep. Therefore, we developed sleep fMRI based on simultaneous electrophysiology at 9.4 T in male mice. Optimized un-anesthetized mouse fMRI setup allowed manifestation of NREM and REM sleep, and a large sleep fMRI dataset was collected and openly accessible. State dependent global patterns were revealed, and state transitions were found to be global, asymmetrical and sequential, which can be predicted up to 17.8 s using LSTM models. Importantly, sleep fMRI with hippocampal recording revealed potentiated sharp-wave ripple triggered global patterns during NREM than awake state, potentially attributable to co-occurrence of spindle events. To conclude, we established mouse sleep fMRI with simultaneous electrophysiology, and demonstrated its capability by revealing global dynamics of state transitions and neural events.

In humans, the level of consciousness is assessed by quantifying the spatiotemporal complexity of cortical responses using Perturbational Complexity Index (PCI) and related PCIst (st, state transitions). Here we validate PCIst in freely moving rats and mice by showing that it is lower in NREM sleep and slow wave anesthesia than in wake or REM sleep, as in humans. We then show that (1) low PCIst is associated with the occurrence of an OFF period of neuronal silence; (2) stimulation of deep, but not superficial, cortical layers leads to reliable PCIst changes across sleep/wake and anesthesia; (3) consistent PCIst changes are independent of which single area is being stimulated or recorded, except for recordings in mouse prefrontal cortex. These experiments show that PCIst can reliably measure vigilance states in unresponsive animals and support the hypothesis that it is low when an OFF period disrupts causal interactions in cortical networks.

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.

Although sleep and anesthesia are predicted to share common neural signatures of transitions into and out of unconsciousness, supportive evidence has been elusive. We identified these signatures using intracranial electroencephalography in neurosurgical patients. We applied diffusion map embedding to map cortical location into a space where proximity indicates functional similarity using a normalized connectivity (‘diffusion’) matrix, itself a rich source of information about network properties. During reduced consciousness, diffusion matrices exhibited decreased effective dimensionality, reflecting reduced network entropy. Furthermore, functional brain regions exhibited tighter clustering in embedding space with greater distances between regions, corresponding to decreased differentiation and functional integration. These changes were not region-specific, suggesting global network reorganization. These results strongly suggest common neural substrates for loss and recovery of consciousness during anesthesia and sleep, providing a systems-level mechanistic understanding within an intuitive geometric context and laying the foundation for evaluation of cortical state transitions in clinical settings.

The cerebral cortex is spontaneously active during sleep, yet it is unclear how this global cortical activity is spatiotemporally organized, and whether such activity not only reflects sleep states but also contributes to sleep state switching. Here we report that cortex-wide calcium imaging in mice revealed distinct sleep stage-dependent spatiotemporal patterns of global cortical activity, and modulation of such patterns could regulate sleep state switching. In particular, elevated activation in the occipital cortical regions (including the retrosplenial cortex and visual areas) became dominant during rapid-eye-movement (REM) sleep. Furthermore, such pontogeniculooccipital (PGO) wave-like activity was associated with transitions to REM sleep, and optogenetic inhibition of occipital activity strongly promoted deep sleep by suppressing the NREM-to-REM transition. Thus, whereas subcortical networks are critical for initiating and maintaining sleep and wakefulness states, distinct global cortical activity also plays an active role in controlling sleep states.

The contribution of different brain regions to movement abnormalities in children with dystonia is unknown. Three awake subjects undergoing depth electrode implantation for assessments of potential deep brain recording targets performed a rhythmic figure-8 drawing task. Two subjects had dystonia, one was undergoing testing for treatment of Tourette Syndrome and had neither dystonia nor abnormal movements during testing. Movement-related signals were evaluated by determining the magnitude of task-related frequency components. Brain signals were recorded in globus pallidus internus (GPi), the ventral oralis anterior/posterior (VoaVop) and the ventral intermediate (Vim) nuclei of the thalamus. In comparison to the subject without dystonia, both children with dystonia showed increased task-related activity in GPi and Vim. This finding is consistent with a role of both basal ganglia and cerebellar outputs in the pathogenesis of dystonia. Our results further suggest that frequency analysis of brain recordings during cyclic movements may be a useful tool for analysis of the presence of movement-related signals in various brain regions.

The primate amygdala is a complex consisting of over a dozen nuclei that have been implicated in a host of cognitive functions, individual differences, and psychiatric illnesses. These functions are implemented through distinct connectivity profiles, which have been documented in animals but remain largely unknown in humans. Here we present results from 25 neurosurgical patients who had concurrent electrical stimulation of the amygdala with intracranial electroencephalography (electrical stimulation tract-tracing; es-TT), or fMRI (electrical stimulation fMRI; es-fMRI), methods providing strong inferences about effective connectivity of amygdala subdivisions with the rest of the brain. We quantified functional connectivity with medial and lateral amygdala, the temporal order of these connections on the timescale of milliseconds, and also detail second-order effective connectivity among the key nodes. These findings provide a uniquely detailed characterization of human amygdala functional connectivity that will inform functional neuroimaging studies in healthy and clinical populations.

Background: Sensory impairments commonly occur in patients with autism or intellectual disability. Fragile X syndrome (FXS) is one form of intellectual disability that is often comorbid with autism. In electroencephalographic (EEG) recordings obtained from humans with FXS, the ability of cortical regions to consistently synchronize, or "phase-lock", to modulated auditory stimuli is reduced compared to that of typically developing individuals. At the same time, less time-locked, "non-phase-locked" power induced by sounds is higher. The same changes occur in the Fmr1 knockout (KO) mouse - an animal model of FXS. We determined if Fmr1 deletion in a subset of brainstem auditory neurons plays any role in these EEG changes in the mouse. Methods: We reinstated FMRP expression in a subpopulation of brainstem auditory neurons in an otherwise Fmr1 KO control (conditional on; cON Fmr1) mouse and used EEG recordings to determine if reinstatement normalized, or "rescued", the phase-locking phenotype observed in the cON Fmr1 mouse. In determining rescue, this also meant that Fmr1 deletion in the same neuron population was necessary for the phenotype to occur. Results: We find that Fmr1 reinstatement in a subset of brainstem neurons rescues certain aspects of the phase-locking phenotype but does not rescue the increase in non-phase-locked power. Unexpectedly, not all electrophysiological phenotypes observed in the Fmr1 KO were observed in the cON Fmr1 mouse used for the reinstatement experiments, and this was likely due to residual expression of FMRP in these Fmr1 KO controls. Conclusions: Fmr1 deletion in brainstem neurons is necessary for certain aspects of the decreased phase-locking phenotype in the Fmr1 KO, but not necessary for the increase in non-phase-locked power induced by a sound. The most likely brainstem structure underlying these results is the inferior colliculus. We also demonstrate that low levels of FMRP can rescue some EEG phenotypes but not others. This latter finding provides a foundation for how symptoms in FXS individuals may vary due to FMRP levels and that reinstatement of low FMRP levels may be sufficient to alleviate particular symptoms.

Fundamental to elucidating the functional organization of the brain is the assessment of causal interactions between different brain regions. Multivariate autoregressive (MVAR) modeling techniques applied to multisite electrophysiological recordings are a promising avenue for identifying such causal links. They estimate the degree to which past activity in one or more brain regions is predictive of another region's present activity, while simultaneously accounting for the mediating effects of other regions. Including as many mediating variables as possible in the model has the benefit of drastically reducing the odds of detecting spurious causal connectivity. However, effective bounds on the number of MVAR model coefficients that can be estimated reliably from limited data make exploiting the potential of MVAR models challenging for even modest numbers of recording sites. Here, we utilize well-established dimensionality-reduction techniques to fit MVAR models to human intracranial data from ∼100 - 200 recording sites spanning dozens of anatomically and functionally distinct cortical regions. First, we show that high-dimensional MVAR models can be successfully estimated from long segments of data and yield plausible connectivity profiles. Next, we use these models to generate synthetic data with known ground-truth connectivity to explore the utility of applying principal component analysis and group least absolute shrinkage and selection operator (gLASSO) to reduce the number of parameters (connections) during model fitting to shorter data segments. We show that gLASSO is highly effective for recovering ground-truth connectivity in the limited data regime, capturing important features of connectivity for high-dimensional models with as little as 10 seconds of data. The methods presented here have broad applicability to the analysis of high-dimensional time series data in neuroscience, facilitating the elucidation of the neural basis of sensation, cognition, and arousal.

Targeted therapies for epilepsies associated with the mTORC1 signaling negative regulator GATOR1 are lacking. NPRL2 is a subunit of the GATOR1 complex and mutations in GATOR1 subunits, including NPRL2, are associated with epilepsy. To delineate the mechanisms underlying NPRL2-related epilepsies, we created a mouse (Mus musculus) model with neocortical loss of Nprl2. Mutant mice have increased mTORC1 signaling and exhibit spontaneous seizures. They also display abnormal synaptic function characterized by increased evoked and spontaneous EPSC and decreased evoked and spontaneous IPSC frequencies, respectively. Proteomic and metabolomics studies of Nprl2 mutants revealed alterations in known epilepsy-implicated proteins and metabolic pathways, including increases in the neurotransmitter, glycine. Furthermore, glycine actions on the NMDA receptor contribute to the electrophysiological and survival phenotypes of these mice. Taken together, in this neuronal Nprl2 model, we delineate underlying molecular, metabolic, and electrophysiological mechanisms contributing to mTORC1-related epilepsy, providing potential therapeutic targets for epilepsy.

Spinal interneurons play a critical role in motor output. A given interneuron may receive convergent input from several different sensory modalities and descending centers and relay this information to just as many targets. Therefore, there is a critical need to quantify populations of spinal interneurons simultaneously. Here, we quantify the functional connectivity of spinal neurons through the concurrent recording of populations of lumbar interneurons and hindlimb motor units in the in vivo cat model during activation of either the ipsilateral sural nerve or contralateral tibial nerve. Two microelectrode arrays were placed into lamina VII, one at L3 and a second at L6/7, while an electrode array was placed on the surface of the exposed muscle. Stimulation of tibial and sural nerves elicited similar changes in the discharge rate of both interneurons and motor units. However, these same neurons showed highly significant differences in prevalence and magnitude of correlated activity underlying these two forms of afferent drive. Activation of the ipsilateral sural nerve resulted in highly correlated activity, particularly at the caudal array. In contrast, the contralateral tibial nerve resulted in less, but more widespread correlated activity at both arrays. These data suggest that the ipsilateral sural nerve has dense projections onto caudal lumbar spinal neurons, while contralateral tibial nerve has a sparse pattern of projections.

Over the last 15 years, optogenetics has changed fundamental research in neuroscience and is now reaching toward therapeutic applications. Vision restoration strategies using optogenetics are now at the forefront of these new clinical opportunities. But applications to human patients suffering from retinal diseases leading to blindness raise important concerns on the long-term functional expression of optogenes and the efficient signal transmission to higher visual centers. Here, we demonstrate in non-human primates continued expression and functionality at the retina level ∼20 months after delivery of our construct. We also performed in vivo recordings of visually evoked potentials in the primary visual cortex of anesthetized animals. Using synaptic blockers, we isolated the in vivo cortical activation resulting from the direct optogenetic stimulation of primate retina. In conclusion, our work indicates long-term transgene expression and transmission of the signal generated in the macaque retina to the visual cortex, two important features for future clinical applications.