Simultaneous Electrophysiological Recordings Research Articles

A 1024-Channel Simultaneous Electrophysiological and Electrochemical Neural Recording System with In-Pixel Digitization and Crosstalk Compensation.

Simultaneous electrophysiological and chemical recording allows for multi-modal neural instrumentation and provides insights into chemical synapses and ion channels across the cell membrane. However, intermodal interference can hinder highly synchronized recording in large-scale systems with high temporal and spatial resolution. In this work, we propose a 1024-channel lab-on-CMOS system for dual-modal neural recording with in-pixel digitization and interference suppression. A foreground calibration scheme with tunable capacitance is implemented in-pixel to compensate for the crosstalk between electrical and chemical recording. Active pixels for both electrical and chemical modalities are designed based on a pulse width modulation (PWM) analog-to-digital conversion scheme. CMOS-compatible post-processing is implemented to realize in-pixel electrodes and chemical sensing membranes. The prototype, implemented in a 180nm CMOS technology, occupies a total area of 33mm2 with 1024 pixels, and each unit pixel includes one electrical recording site and two chemical recording sites, with dimensions of 150μm×130 μm. The total system power consumption is 19.68mW at a frame rate of 9k and 3k for electrical and chemical imaging respectively. The in-vitro experiment demonstrated the concurrent high density electrophysilogical and electrochemical recording with sub millisecond temporal resolution.

Cortical plasticity is associated with blood-brain barrier modulation.

Brain microvessels possess the unique properties of a blood-brain barrier (BBB), tightly regulating the passage of molecules from the blood to the brain neuropil and vice versa. In models of brain injury, BBB dysfunction and the associated leakage of serum albumin to the neuropil have been shown to induce pathological plasticity, neuronal hyper-excitability, and seizures. The effect of neuronal activity on BBB function and whether it plays a role in plasticity in the healthy brain remain unclear. Here we show that neuronal activity induces modulation of microvascular permeability in the healthy brain and that it has a role in local network reorganization. Combining simultaneous electrophysiological recording and vascular imaging with transcriptomic analysis in rats, and functional and BBB-mapping MRI in human subjects, we show that prolonged stimulation of the limb induces a focal increase in BBB permeability in the corresponding somatosensory cortex that is associated with long-term synaptic plasticity. We further show that the increased microvascular permeability depends on neuronal activity and involves caveolae-mediated transcytosis and transforming growth factor β signaling. Our results reveal a role of BBB modulation in cortical plasticity in the healthy brain, highlighting the importance of neurovascular interactions for sensory experience and learning.

Spatial localization of hippocampal replay requires dopamine signaling.

Sequenced reactivations of hippocampal neurons called replays, concomitant with sharp-wave ripples in the local field potential, are critical for the consolidation of episodic memory, but whether replays depend on the brain's reward or novelty signals is unknown. Here we combined chemogenetic silencing of dopamine neurons in ventral tegmental area (VTA) and simultaneous electrophysiological recordings in dorsal hippocampal CA1, in freely behaving rats experiencing changes to reward magnitude and environmental novelty. Surprisingly, VTA silencing did not prevent ripple increases where reward was increased, but caused dramatic, aberrant ripple increases where reward was unchanged. These increases were associated with increased reverse-ordered replays. On familiar tracks this effect disappeared, and ripples tracked reward prediction error, indicating that non-VTA reward signals were sufficient to direct replay. Our results reveal a novel dependence of hippocampal replay on dopamine, and a role for a VTA-independent reward prediction error signal that is reliable only in familiar environments.

Fenobam modulates distinct electrophysiological mechanisms for regulating excessive gamma oscillations in the striatum of dyskinetic rats

Gamma oscillations have been frequently observed in levodopa-induced dyskinesia (LID), manifest as broadband (60-120 Hz) and narrowband (80-110 Hz) gamma activity in cortico-striatal projection. We investigated the electrophysiological mechanisms and correlation of gamma oscillations with dyskinesia severity, while assessing the administration of fenobam, a selective metabotropic glutamate receptor 5 (mGluR5) antagonist, in regulating dyskinesia-associated gamma activity. We conducted simultaneous electrophysiological recordings in Striatum (Str) and primary motor cortex (M1), together with Abnormal Involuntary Movement Scale scoring (AIMs). Phase-amplitude coupling (PAC), power, coherence, and Granger causality analyses were conducted for electrophysiological data. The findings demonstrated increased beta oscillations with directionality from M1 to Str in parkinsonian state. During on-state dyskinesia, elevated broadband gamma activity was modulated by the phase of theta activity in Str, while M1 → Str gamma causality mediated narrowband gamma oscillations in Str. Striatal gamma power (both periodic and aperiodic power), periodic power, peak frequency, and PAC at 80 min (corresponding to the peak dyskinesia) after repeated levodopa injections across recording days (day 30, 33, 36, 39, and 42) increased progressively, correlating with total AIMs. Additionally, a time-dependent parabolic trend of PAC, peak frequency and gamma power was observed after levodopa injection on day 42 from 20 to 120 min, which also correlated with corresponding AIMs. Fenobam effectively alleviates dyskinesia, suppresses enhanced gamma oscillations in the M1-Str directionality, and reduces PAC in Str. The temporal characteristics of gamma oscillations provide parameters for classifying LID severity. Antagonizing striatal mGluR5, a promising therapeutic target for dyskinesia, exerts its effects by modulating gamma activity.

Fully bioresorbable hybrid opto-electronic neural implant system for simultaneous electrophysiological recording and optogenetic stimulation

Bioresorbable neural implants based on emerging classes of biodegradable materials offer a promising solution to the challenges of secondary surgeries for removal of implanted devices required for existing neural implants. In this study, we introduce a fully bioresorbable flexible hybrid opto-electronic system for simultaneous electrophysiological recording and optogenetic stimulation. The flexible and soft device, composed of biodegradable materials, has a direct optical and electrical interface with the curved cerebral cortex surface while exhibiting excellent biocompatibility. Optimized to minimize light transmission losses and photoelectric artifact interference, the device was chronically implanted in the brain of transgenic mice and performed to photo-stimulate the somatosensory area while recording local field potentials. Thus, the presented hybrid neural implant system, comprising biodegradable materials, promises to provide monitoring and therapy modalities for versatile applications in biomedicine.

High-density transparent graphene arrays for predicting cellular calcium activity at depth from surface potential recordings.

Optically transparent neural microelectrodes have facilitated simultaneous electrophysiological recordings from the brain surface with the optical imaging and stimulation of neural activity. A remaining challenge is to scale down the electrode dimensions to the single-cell size and increase the density to record neural activity with high spatial resolution across large areas to capture nonlinear neural dynamics. Here we developed transparent graphene microelectrodes with ultrasmall openings and a large, transparent recording area without any gold extensions in the field of view with high-density microelectrode arrays up to 256 channels. We used platinum nanoparticles to overcome the quantum capacitance limit of graphene and to scale down the microelectrode diameter to 20 µm. An interlayer-doped double-layer graphene was introduced to prevent open-circuit failures. We conducted multimodal experiments, combining the recordings of cortical potentials of microelectrode arrays with two-photon calcium imaging of the mouse visual cortex. Our results revealed that visually evoked responses are spatially localized for high-frequency bands, particularly for the multiunit activity band. The multiunit activity power was found to be correlated with cellular calcium activity. Leveraging this, we employed dimensionality reduction techniques and neural networks to demonstrate that single-cell and average calcium activities can be decoded from surface potentials recorded by high-density transparent graphene arrays.

3D architecture and a bicellular mechanism of touch detection in mechanosensory corpuscle.

Mechanosensory corpuscles detect transient touch and vibration in the skin of vertebrates, enabling precise sensation of the physical environment. The corpuscle contains a mechanoreceptor afferent surrounded by lamellar cells (LCs), but corpuscular ultrastructure and the role of LCs in touch detection are unknown. We report the three-dimensional architecture of the avian Meissner (Grandry) corpuscle acquired using enhanced focused ion beam scanning electron microscopy and machine learning-based segmentation. The corpuscle comprises a stack of LCs interdigitated with terminal endings from two afferents. Simultaneous electrophysiological recordings from both cell types revealed that mechanosensitive LCs use calcium influx to trigger action potentials in the afferent and thus serve as physiological touch sensors in the skin. The elaborate architecture and bicellular sensory mechanism in the corpuscles, which comprises the afferents and LCs, create the capacity for nuanced encoding of the submodalities of touch.

An automated, low-latency environment for studying the neural basis of behavior in freely moving rats

BackgroundBehavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes).ResultsTo overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding areas, multiple sound sources, high-resolution behavioral tracking, and simultaneous electrophysiological recordings. The paper provides detailed information about the construction of the RIFF and the software used to control it. To illustrate the flexibility of the RIFF, we describe two complex tasks implemented in the RIFF, a foraging task and a sound localization task. Rats quickly learned to obtain rewards in both tasks. Neurons in the auditory cortex as well as neurons in the auditory field in the posterior insula had sound-driven activity during behavior. Remarkably, neurons in both structures also showed sensitivity to non-auditory parameters such as location in the arena and head-to-body angle.ConclusionsThe RIFF provides insights into the cognitive capabilities and learning mechanisms of rats and opens the way to a better understanding of how brains control behavior. The ability to do so depends crucially on the combination of wireless electrophysiology and detailed behavioral documentation available in the RIFF.

Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy.

Due to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the Anterior Nucleus of the Thalamus (ANT) has been proposed as a key Deep Brain Stimulation (DBS) target in drug-resistant epilepsy (DRE). However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy, remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 DRE (N = 6 males, age = ) patients underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG oscillations, higher power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with DRE.

Live Cell Light Sheet Imaging with Low- and High-Spatial-Coherence Detection Approaches Reveals Spatiotemporal Aspects of Neuronal Signaling

Light sheet microscopy in live cells requires minimal excitation intensity and resolves three-dimensional (3D) information rapidly. Lattice light sheet microscopy (LLSM) works similarly but uses a lattice configuration of Bessel beams to generate a flatter, diffraction-limited z-axis sheet suitable for investigating subcellular compartments, with better tissue penetration. We developed a LLSM method for investigating cellular properties of tissue in situ. Neural structures provide an important target. Neurons are complex 3D structures, and signaling between cells and subcellular structures requires high resolution imaging. We developed an LLSM configuration based on the Janelia Research Campus design or in situ recording that allows simultaneous electrophysiological recording. We give examples of using LLSM to assess synaptic function in situ. In presynapses, evoked Ca2+ entry causes vesicle fusion and neurotransmitter release. We demonstrate the use of LLSM to measure stimulus-evoked localized presynaptic Ca2+ entry and track synaptic vesicle recycling. We also demonstrate the resolution of postsynaptic Ca2+ signaling in single synapses. A challenge in 3D imaging is the need to move the emission objective to maintain focus. We have developed an incoherent holographic lattice light-sheet (IHLLS) technique to replace the LLS tube lens with a dual diffractive lens to obtain 3D images of spatially incoherent light diffracted from an object as incoherent holograms. The 3D structure is reproduced within the scanned volume without moving the emission objective. This eliminates mechanical artifacts and improves temporal resolution. We focus on LLS and IHLLS applications and data obtained in neuroscience and emphasize increases in temporal and spatial resolution using these approaches.

Electrodeposited NaYF4:Yb3+, Er3+ up-conversion films for flexible neural device construction and near-infrared optogenetics.

Near-infrared optogenetics based on up-conversion materials provides a promising tool for the dissection of neural circuit functions in deep brain regions. However, it remains a challenge to combine near-infrared up-conversion optogenetic stimulation with high-density electrophysiological recording in a minimally invasive manner. Here, we develop a flexible device for simultaneous electrophysiological recording and near-infrared optogenetics. The flexible device is constructed by integrating polymer-based flexible recording microelectrodes with electrodeposited NaYF4:Yb3+, Er3+ up-conversion films that can convert deep-tissue-penetrating near-infrared light into visible light for optogenetic activation of C1V1-expressing neurons. The emission properties of the up-conversion films are optimized for green light emission to stimulate C1V1 opsins. Owing to their minimized surgical footprint and high mechanical compliance, chronically implanted devices enable simultaneous electrophysiological recording and near-infrared optogenetic modulation of neuronal activities in the brain.

Bilayer-Nanomesh Transparent Neuroelectrodes on 10μm-Thick PDMS.

Transparent electrode arrays have emerged as promising platforms for neural interfacing by enabling simultaneous electrophysiological recording and optical measurements. Soft and thin devices also have compelling advantages due to their less mechanical mismatch with the brain tissue. Here we demonstrate a bilayer-nanomesh-based transparent microelectrode array (MEA) on ultrathin Polydimethylsiloxane (PDMS) substrate. We have successfully fabricated 32-channel, bilayer-nanomesh microelectrodes on PDMS with total device thickness down to only 10μm. In addition to excellent electrode performance, device reliability, and optical transparency, we have also demonstrated successful hydrophilic surface modification and great sterilization compatibility.

Multimodal Characterization of Cardiac Organoids Using Integrations of Pressure-Sensitive Transistor Arrays with Three-Dimensional Liquid Metal Electrodes.

Herein, we present an unconventional method for multimodal characterization of three-dimensional cardiac organoids. This method can monitor and control the mechanophysiological parameters of organoids within a single device. In this method, local pressure distributions of human-induced pluripotent stem-cell-derived cardiac organoids are visualized spatiotemporally by an active-matrix array of pressure-sensitive transistors. This array is integrated with three-dimensional electrodes formed by the high-resolution printing of liquid metal. These liquid-metal electrodes are inserted inside an organoid to form the intraorganoid interface for simultaneous electrophysiological recording and stimulation. The low mechanical modulus and low impedance of the liquid-metal electrodes are compatible with organoids’ soft biological tissue, which enables stable electric pacing at low thresholds. In contrast to conventional electrophysiological methods, this measurement of a cardiac organoid’s beating pressures enabled simultaneous treatment of electrical therapeutics using a single device without any interference between the pressure signals and electrical pulses from pacing electrodes, even in wet organoid conditions.

Honeycomb: a template for reproducible psychophysiological tasks for clinic, laboratory, and home use.

Objective:To improve the ability of psychiatry researchers to build, deploy, maintain, reproduce, and share their own psychophysiological tasks. Psychophysiological tasks are a useful tool for studying human behavior driven by mental processes such as cognitive control, reward evaluation, and learning. Neural mechanisms during behavioral tasks are often studied via simultaneous electrophysiological recordings. Popular online platforms such as Amazon Mechanical Turk (MTurk) and Prolific enable deployment of tasks to numerous participants simultaneously. However, there is currently no task-creation framework available for flexibly deploying tasks both online and during simultaneous electrophysiology.Methods:We developed a task creation template, termed Honeycomb, that standardizes best practices for building jsPsych-based tasks. Honeycomb offers continuous deployment configurations for seamless transition between use in research settings and at home. Further, we have curated a public library, termed BeeHive, of ready-to-use tasks.Results:We demonstrate the benefits of using Honeycomb tasks with a participant in an ongoing study of deep brain stimulation for obsessive compulsive disorder, who completed repeated tasks both in the clinic and at home.Conclusion:Honeycomb enables researchers to deploy tasks online, in clinic, and at home in more ecologically valid environments and during concurrent electrophysiology.

Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography

Social interactions powerfully impact the brain and the body, but high-resolution descriptions of these important physical interactions and their neural correlates are lacking. Currently, most studies rely on labor-intensive methods such as manual annotation. Scalable and objective tracking methods are required to understand the neural circuits underlying social behavior. Here we describe a hardware/software system and analysis pipeline that combines 3D videography, deep learning, physical modeling, and GPU-accelerated robust optimization, with automatic analysis of neuronal receptive fields recorded in interacting mice. Our system (“3DDD Social Mouse Tracker”) is capable of fully automatic multi-animal tracking with minimal errors (including in complete darkness) during complex, spontaneous social encounters, together with simultaneous electrophysiological recordings. We capture posture dynamics of multiple unmarked mice with high spatiotemporal precision (~2 mm, 60 frames/s). A statistical model that relates 3D behavior and neural activity reveals multiplexed ‘social receptive fields’ of neurons in barrel cortex. Our approach could be broadly useful for neurobehavioral studies of multiple animals interacting in complex low-light environments.

Effects of Ketamine and Midazolam on Simultaneous EEG/fMRI Data During Working Memory Processes

Reliable measures of cognitive brain activity from functional neuroimaging techniques may provide early indications of efficacy in clinical trials. Functional magnetic resonance imaging and electroencephalography provide complementary spatiotemporal information and simultaneous recording of these two modalities can remove inter-session drug response and environment variability. We sought to assess the effects of ketamine and midazolam on simultaneous electrophysiological and hemodynamic recordings during working memory (WM) processes. Thirty participants were included in a placebo-controlled, three-way crossover design with ketamine and midazolam. Compared to placebo, ketamine administration attenuated theta power increases and alpha power decreases and midazolam attenuated low beta band decreases to increasing WM load. Additionally, ketamine caused larger blood-oxygen-dependent (BOLD) signal increases in the supplementary motor area and angular gyrus, and weaker deactivations of the default mode network (DMN), whereas no difference was found between midazolam and placebo. Ketamine administration caused positive temporal correlations between frontal-midline theta (fm-theta) power and the BOLD signal to disappear and attenuated negative correlations. However, the relationship between fm-theta and the BOLD signal from DMN areas was maintained in some participants during ketamine administration, as increasing theta strength was associated with stronger BOLD signal reductions in these areas. The presence of, and ability to manipulate, both positive and negative associations between the BOLD signal and fm-theta suggest the presence of multiple fm-theta components involved in WM processes, with ketamine administration disrupting one or more of these theta-linked WM strategies.

A causal role for the pulvinar in coordinating task-independent cortico-cortical interactions.

The pulvinar is the largest nucleus in the primate thalamus and has topographically organized connections with multiple cortical areas, thereby forming extensive cortico-pulvino-cortical input-output loops. Neurophysiological studies have suggested a role for these transthalamic pathways in regulating information transmission between cortical areas. However, evidence for a causal role of the pulvinar in regulating cortico-cortical interactions is sparse and it is not known whether pulvinar's influences on cortical networks are task-dependent or, alternatively, reflect more basic large-scale network properties that maintain functional connectivity across networks regardless of active task demands. In the current study, under passive viewing conditions, we conducted simultaneous electrophysiological recordings from ventral (area V4) and dorsal (lateral intraparietal area [LIP]) nodes of macaque visual system, while reversibly inactivating the dorsal part of the lateral pulvinar (dPL), which shares common anatomical connectivity with V4 and LIP, to probe a causal role of the pulvinar. Our results show a significant reduction in local field potential phase coherence between LIP and V4 in low frequencies (4-15 Hz) following muscimol injection into dPL. At the local level, no significant changes in firing rates or LFP power were observed in LIP or in V4 following dPL inactivation. Synchronization between pulvinar spikes and cortical LFP phase decreased in low frequencies (4-15 Hz) both in LIP and V4, while the low frequency synchronization between LIP spikes and pulvinar phase increased. These results indicate a causal role for pulvinar in synchronizing neural activity between interconnected cortical nodes of a large-scale network, even in the absence of an active task state.

A non-invasive multimodal foetal ECG\u2013Doppler dataset for antenatal cardiology research

Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. In this work, we present the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA), the first open-access multimodal early-pregnancy dataset in the field that features simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler (PWD). The dataset is mainly conceived for researchers working on fECG signal processing algorithms. The dataset includes 60 entries from 39 pregnant women, between the 21st and 27th week of gestation. Each dataset entry comprises 27 electrophysiological channels (2048 Hz, 22 bits), a maternal respiration signal, synchronised foetal trans-abdominal PWD and clinical annotations provided by expert clinicians during signal acquisition. MATLAB snippets for data processing are also provided.

A Data-Driven Biophysical Computational Model of Parkinson’s Disease Based on Marmoset Monkeys

In this work we propose a new biophysical computational model of brain regions relevant to Parkinson's Disease based on local field potential data collected from the brain of marmoset monkeys. Parkinson's disease is a neurodegenerative disorder, linked to the death of dopaminergic neurons at the substantia nigra pars compacta, which affects the normal dynamics of the basal ganglia-thalamus-cortex neuronal circuit of the brain. Although there are multiple mechanisms underlying the disease, a complete description of those mechanisms and molecular pathogenesis are still missing, and there is still no cure. To address this gap, computational models that resemble neurobiological aspects found in animal models have been proposed. In our model, we performed a data-driven approach in which a set of biologically constrained parameters is optimised using differential evolution. Evolved models successfully resembled single-neuron mean firing rates and spectral signatures of local field potentials from healthy and parkinsonian marmoset brain data. As far as we are concerned, this is the first computational model of Parkinson's Disease based on simultaneous electrophysiological recordings from seven brain regions of Marmoset monkeys. Results show that the proposed model could facilitate the investigation of the mechanisms of PD and support the development of techniques that can indicate new therapies. It could also be applied to other computational neuroscience problems in which biological data could be used to fit multi-scale models of brain circuits.

Phase‐amplitude coupling profiles differ in frontal and auditory cortices of bats

Neural oscillations are at the core of important computations in the mammalian brain. Interactions between oscillatory activities in different frequency bands, such as delta (1-4Hz), theta (4-8Hz) or gamma (>30Hz), are a powerful mechanism for binding fundamentally distinct spatiotemporal scales of neural processing. Phase-amplitude coupling (PAC) is one such plausible and well-described interaction, but much is yet to be uncovered regarding how PAC dynamics contribute to sensory representations. In particular, although PAC appears to have a major role in audition, the characteristics of coupling profiles in sensory and integration (i.e. frontal) cortical areas remain obscure. Here, we address this question by studying PAC dynamics in the frontal-auditory field (FAF; an auditory area in the bat frontal cortex) and the auditory cortex (AC) of the bat Carollia perspicillata. By means of simultaneous electrophysiological recordings in frontal and auditory cortices examining local-field potentials (LFPs), we show that the amplitude of gamma-band activity couples with the phase of low-frequency LFPs in both structures. Our results demonstrate that the coupling in FAF occurs most prominently in delta/high-gamma frequencies (1-4/75-100Hz), whereas in the AC the coupling is strongest in the delta-theta/low-gamma (2-8/25-55Hz) range. We argue that distinct PAC profiles may represent different mechanisms for neuronal processing in frontal and auditory cortices, and might complement oscillatory interactions for sensory processing in the frontal-auditory cortex network.