Correlation Structure in Micro-ECoG Recordings is Described by Spatially Coherent Components

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.

Uncorrelated bilateral cortical input becomes timed across hippocampal subfields for long waves whereas gamma waves are largely ipsilateral

The role of interhemispheric connections along successive segments of cortico-hippocampal circuits is poorly understood. We aimed to obtain a global picture of spontaneous transfer of activity during non-theta states across several nodes of the bilateral circuit in anesthetized rats. Spatial discrimination techniques applied to bilateral laminar field potentials (FP) across the CA1/Dentate Gyrus provided simultaneous left and right readouts in five FP generators that reflect activity in specific hippocampal afferents and associative pathways. We used a battery of correlation and coherence analyses to extract complementary aspects at different time scales and frequency bands. FP generators exhibited varying bilateral correlation that was high in CA1 and low in the Dentate Gyrus. The submillisecond delays indicate coordination but not support for synaptic dependence of one side on another. The time and frequency characteristics of bilateral coupling were specific to each generator. The Schaffer generator was strongly bilaterally coherent for both sharp waves and gamma waves, although the latter maintained poor amplitude co-variation. The lacunosum-moleculare generator was composed of up to three spatially overlapping activities, and globally maintained high bilateral coherence for long but not short (gamma) waves. These two CA1 generators showed no ipsilateral relationship in any frequency band. In the Dentate Gyrus, strong bilateral coherence was observed only for input from the medial entorhinal areas, while those from the lateral entorhinal areas were largely asymmetric, for both alpha and gamma waves. Granger causality testing showed strong bidirectional relationships between all homonymous bilateral generators except the lateral entorhinal input and a local generator in the Dentate Gyrus. It also revealed few significant relationships between ipsilateral generators, most notably the anticipation of lateral entorhinal cortex toward all others. Thus, with the notable exception of the lateral entorhinal areas, there is a marked interhemispheric coherence primarily for slow envelopes of activity, but not for pulse-like gamma waves, except in the Schafer segment. The results are consistent with essentially different streams of activity entering from and returning to the cortex on each side, with slow waves reflecting times of increased activity exchange between hemispheres and fast waves generally reflecting ipsilateral processing.

Theoretical considerations and supporting evidence for the primary role of source geometry on field potential amplitude and spatial extent

Field potential (FP) recording is an accessible means to capture the shifts in the activity of neuron populations. However, the spatial and composite nature of these signals has largely been ignored, at least until it became technically possible to separate activities from co-activated sources in different structures or those that overlap in a volume. The pathway-specificity of mesoscopic sources has provided an anatomical reference that facilitates transcending from theoretical analysis to the exploration of real brain structures. We review computational and experimental findings that indicate how prioritizing the spatial geometry and density of sources, as opposed to the distance to the recording site, better defines the amplitudes and spatial reach of FPs. The role of geometry is enhanced by considering that zones of the active populations that act as sources or sinks of current may arrange differently with respect to each other, and have different geometry and densities. Thus, observations that seem counterintuitive in the scheme of distance-based logic alone can now be explained. For example, geometric factors explain why some structures produce FPs and others do not, why different FP motifs generated in the same structure extend far while others remain local, why factors like the size of an active population or the strong synchronicity of its neurons may fail to affect FPs, or why the rate of FP decay varies in different directions. These considerations are exemplified in large structures like the cortex and hippocampus, in which the role of geometrical elements and regional activation in shaping well-known FP oscillations generally go unnoticed. Discovering the geometry of the sources in play will decrease the risk of population or pathway misassignments based solely on the FP amplitude or temporal pattern.

Large-scale multimodal surface neural interfaces for primates

Deciphering the function of neural circuits can help with the understanding of brain function and treating neurological disorders. Progress toward this goal relies on the development of chronically stable neural interfaces capable of recording and modulating neural circuits with high spatial and temporal precision across large areas of the brain. Advanced innovations in designing high-density neural interfaces for small animal models have enabled breakthrough discoveries in neuroscience research. Developing similar neurotechnology for larger animal models such as nonhuman primates (NHPs) is critical to gain significant insights for translation to humans, yet still it remains elusive due to the challenges in design, fabrication, and system-level integration of such devices. This review focuses on implantable surface neural interfaces with electrical and optical functionalities with emphasis on the required technological features to realize scalable multimodal and chronically stable implants to address the unique challenges associated with nonhuman primate studies.

Site-dependent shaping of field potential waveforms

The activity of neuron populations gives rise to field potentials (FPs) that extend beyond the sources. Their mixing in the volume dilutes the original temporal motifs in a site-dependent manner, a fact that has received little attention. And yet, it potentially rids of physiological significance the time-frequency parameters of individual waves (amplitude, phase, duration). This is most likely to happen when a single source or a local origin is erroneously assumed. Recent studies using spatial treatment of these signals and anatomically realistic modeling of neuron aggregates provide convincing evidence for the multisource origin and site-dependent blend of FPs. Thus, FPs generated in primary structures like the neocortex and hippocampus reach far and cross-contaminate each other but also, they add and even impose their temporal traits on distant regions. Furthermore, both structures house neurons that act as spatially distinct (but overlapped) FP sources whose activation is state, region, and time dependent, making the composition of so-called local FPs highly volatile and strongly site dependent. Since the spatial reach cannot be predicted without source geometry, it is important to assess whether waveforms and temporal motifs arise from a single source; otherwise, those from each of the co-active sources should be sought.

On-scalp magnetocorticography with optically pumped magnetometers: Simulated performance in resolving simultaneous sources

Currently, the gold standard for high-resolution mapping of cortical electrophysiological activity is invasive electrocorticography (ECoG), a procedure that carries with it the risk of serious morbidity and mortality. Due to these risks, the use of ECoG is largely limited to pre-surgical mapping in intractable epilepsy. Nevertheless, many seminal studies in neuroscience have utilized ECoG to explore domains such as visual perception, attention, auditory processing, and sensorimotor behavior. Studies such as these, occurring in patients with epilepsy rather than healthy controls, may lack generalizability, and are limited by the placement of the electrode arrays over the presumed seizure focus. This manuscript explores the use of optically pumped magnetometers (OPMs) to create a non-invasive alternative to ECoG, which we refer to as magnetocorticography. Because prior ECoG studies reveal that most cognitive processes are driven by multiple, simultaneous independent neuronal assemblies, we characterize the ability of a theoretical 56-channel dense OPM array to resolve simultaneous independent sources, and compare it to currently available SQUID devices, as well as OPM arrays with inter-sensor spacings more typical of other systems in development. Our evaluation of this theoretical system assesses many potential sources of error, including errors of sensor calibration and position. In addition, we investigate the influence of geometrical and anatomical factors on array performance. Our simulations reveal the potential of high-density, on-scalp OPM MEG devices to localize electrophysiological brain responses at unprecedented resolution for a non-invasive device.

Transparent, Low-Impedance Inkjet-Printed PEDOT:PSS Microelectrodes for Multi-modal Neuroscience

Transparent microelectrodes that facilitate simultaneous optical and electrophysiological interfacing are desirable tools for neuroscience. Electrodes made from transparent conductors such as graphene and indium tin oxide (ITO) show promise but are often limited by poor interfacial charge-transfer properties. Here, microelectrodes are demonstrated that take advantage of the transparency and volumetric capacitance of the mixed ion-electron conductor Poly(3,4- ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). Ring-shaped microelectrodes are fabricated by inkjet-printing PEDOT:PSS, encapsulating with Parylene-C, and then exposing a contact site that is much smaller than the microelectrode outer diameter. This unique structure allows the encapsulated portion of the microelectrode volume surrounding the contact site to participate in signal transduction, which reduces impedance and enhances charge storage capacity. While using the same 100 μm diameter contact site, increasing the outer diameter of the encapsulated electrode from 300 to 550 μm reduces the impedance from 294±21 to 98±2 kΩ, respectively, at 1 Hz. Similarly, the charge storage capacity is enhanced from 6 to 21 mC cm-2. The PEDOT:PSS microelectrodes provide a low-haze, high-transmittance optical interface, demonstrating their suitability for optical neuroscience applications. They remain functional after a million 1 V stimulation cycles, up to 600 μA of stimulation current, and more than 1000 mechanical bending cycles.

Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation

Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces. To this end, sophisticated machine learning algorithms optimized for decoding of brain states from neural time-series must be developed. To support this venture, this review summarizes the current state of machine learning studies for invasive neurophysiology. After a brief introduction to the machine learning terminology, the transformation of brain recordings into meaningful features for decoding of symptoms and behavior is described. Commonly used machine learning models are explained and analyzed from the perspective of utility for aDBS. This is followed by a critical review on good practices for training and testing to ensure conceptual and practical generalizability for real-time adaptation in clinical settings. Finally, first studies combining machine learning with aDBS are highlighted. This review takes a glimpse into the promising future of intelligent adaptive DBS (iDBS) and concludes by identifying four key ingredients on the road for successful clinical adoption: i) multidisciplinary research teams, ii) publicly available datasets, iii) open-source algorithmic solutions and iv) strong world-wide research collaborations.

The size of via holes influence the amplitude and selectivity of neural signals in Micro-ECoG arrays

Background

Electrocorticography (ECoG) arrays are commonly used to record the brain activity both in animal and human subjects. There is a lack of guidelines in the literature as to how the array geometry, particularly the via holes in the substrate, affects the recorded signals. A finite element (FE) model was developed to simulate the electric field generated by neurons located at different depths in the rat brain cortex and a micro ECoG array (μECoG) was placed on the pia surface for recording the neural signal. The array design chosen was a typical array of 8 × 8 circular (100 μm in diam.) contacts with 500 μm pitch. The size of the via holes between the recording contacts was varied to see the effect.

Results

The results showed that recorded signal amplitudes were reduced if the substrate was smaller than about four times the depth of the neuron in the gray matter. The signal amplitude profiles had dips around the via holes and the amplitudes were also lower at the contact sites as compared to the design without the holes; an effect that increased with the hole size. Another noteworthy result is that the spatial selectivity of the multi-contact recordings could be improved or reduced by the selection of the via hole sizes, and the effect depended on the distance between the neuron pair targeted for selective recording and its depth.

Conclusions

The results suggest that the via-hole size clearly affects the recorded neural signal amplitudes and it can be leveraged as a parameter to reduce the inter-channel correlation and thus maximize the information content of neural signals with μECoG arrays.

Ultra-Sharp Nanowire Arrays Natively Permeate, Record, and Stimulate Intracellular Activity in Neuronal and Cardiac Networks

We report innovative scalable, vertical, ultra-sharp nanowire arrays that are individually addressable to enable long-term, native recordings of intracellular potentials. Stable amplitudes of intracellular potentials from 3D tissue-like networks of neurons and cardiomyocytes are obtained. Individual electrical addressability is necessary for high-fidelity intracellular electrophysiological recordings. This study paves the way toward predictive, high-throughput, and low-cost electrophysiological drug screening platforms.

The transcatheter arterial chemoembolization combined with targeted nanoparticle delivering sorafenib system for the treatment of microvascular invasion of hepatocellular carcinoma

to explore the value of transcatheter arterial chemoembolization (TACE) combined with targeted nanoparticle delivery system for sorafenib (SFB) to treat hepatocellular carcinoma (HCC) with microvascular invasion. 42 HCC patients with microvascular invasion after liver cancer surgery were selected from our hospital from December 2020 and February 2021. Patients were divided into experimental group and control group based on their willingness. Patients in experimental group (18 cases) were treated with combination therapy of TACE and Ab-SFB-NP system; while patients in control group (24 cases) took TACE and non-nano drug delivery system. There was no obvious difference in liver function and blood test results between two groups of patients before treatment and one month after treatment (P > 0.05). Three months after treatment, differences of alanine aminotransferase (ALT) were statistically significant (P < 0.05); while differences of other test results were not (P > 0.05). The disease control rate (DCR) of patients in experimental group was higher slightly (P > 0.05). The incidence of adverse reactions of patients in experimental group was lower than the control group and the differences were statistically significant (P < 0.05). After three months of TACE, the DCR in the experimental group was significantly higher compared to control group. The toxic reactions of taking SFB with Ab-SFB-NP nano-drug delivery system mainly included hand-foot syndrome, diarrhea, and bleeding, the toxic reactions were mainly at level 1 ~ 2. After symptomatic treatment, the toxicity was effectively controlled, so the security was high.

Decoding of cortex-wide brain activity from local recordings of neural potentials

Objective. Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions.Approach. To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings.Main results. The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials.Significance. These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.

Cross Laminar Traveling Components of Field Potentials due to Volume Conduction of Non-Traveling Neuronal Activity in Macaque Sensory Cortices

Field potentials (FPs) reflect neuronal activities in the brain, and often exhibit traveling peaks across recording sites. While traveling FPs are interpreted as propagation of neuronal activity, not all studies directly reveal such propagating patterns of neuronal activation. Neuronal activity is associated with transmembrane currents that form dipoles and produce negative and positive fields. Thereby, FP components reverse polarity between those fields and have minimal amplitudes at the center of dipoles. Although their amplitudes could be smaller, FPs are never flat even around these reversals. What occurs around the reversal has not been addressed explicitly, although those are rationally in the middle of active neurons. We show that sensory FPs around the reversal appeared with peaks traveling across cortical laminae in macaque sensory cortices. Interestingly, analyses of current source density did not depict traveling patterns but lamina-delimited current sinks and sources. We simulated FPs produced by volume conduction of a simplified 2 dipoles' model mimicking sensory cortical laminar current source density components. While FPs generated by single dipoles followed the temporal patterns of the dipole moments without traveling peaks, FPs generated by concurrently active dipole moments appeared with traveling components in the vicinity of dipoles by superimposition of individually non-traveling FPs generated by single dipoles. These results indicate that not all traveling FP are generated by traveling neuronal activity, and that recording positions need to be taken into account to describe FP peak components around active neuronal populations.SIGNIFICANCE STATEMENT Field potentials (FPs) generated by neuronal activity in the brain occur with fields of opposite polarity. Likewise, in the cerebral cortices, they have mirror-imaged waveforms in upper and lower layers. We show that FPs appear like traveling across the cortical layers. Interestingly, the traveling FPs occur without traveling components of current source density, which represents transmembrane currents associated with neuronal activity. These seemingly odd findings are explained using current source density models of multiple dipoles. Concurrently active, non-traveling dipoles produce FPs as mixtures of FPs produced by individual dipoles, and result in traveling FP waveforms as the mixing ratio depends on the distances from those dipoles. The results suggest that not all traveling FP components are associated with propagating neuronal activity.

Versatile Surface Electrodes for Combined Electrophysiology and Two-Photon Imaging of the Mouse Central Nervous System

Understanding and modulating CNS function in physiological as well as pathophysiological contexts remains a significant ambition in research and clinical applications. The investigation of the multifaceted CNS cell types including their interactions and contributions to neural function requires a combination of the state-of-the-art in vivo electrophysiology and imaging techniques. We developed a novel type of liquid crystal polymer (LCP) surface micro-electrode manufactured in three customized designs with up to 16 channels for recording and stimulation of brain activity. All designs include spare central spaces for simultaneous 2P-imaging. Nanoporous platinum-plated contact sites ensure a low impedance and high current transfer. The epidural implantation of the LCP micro-electrodes could be combined with standard cranial window surgery. The epidurally positioned electrodes did not only display long-term biocompatibility, but we also observed an additional stabilization of the underlying CNS tissue. We demonstrate the electrode’s versatility in combination with in vivo 2P-imaging by monitoring anesthesia-awake cycles of transgenic mice with GCaMP3 expression in neurons or astrocytes. Cortical stimulation and simultaneous 2P Ca²⁺ imaging in neurons or astrocytes highlighted the astrocytes’ integrative character in neuronal activity processing. Furthermore, we confirmed that spontaneous astroglial Ca²⁺ signals are dampened under anesthesia, while evoked signals in neurons and astrocytes showed stronger dependency on stimulation intensity rather than on various levels of anesthesia. Finally, we show that the electrodes provide recordings of the electrocorticogram (ECoG) with a high signal-to noise ratio and spatial signal differences which help to decipher brain activity states during experimental procedures. Summarizing, the novel LCP surface micro-electrode is a versatile, convenient, and reliable tool to investigate brain function in vivo.

Thin-film microfabrication and intraoperative testing ofµECoG and iEEG depth arrays for sense and stimulation

Objective.Intracranial neural recordings and electrical stimulation are tools used in an increasing range of applications, including intraoperative clinical mapping and monitoring, therapeutic neuromodulation, and brain computer interface control and feedback. However, many of these applications suffer from a lack of spatial specificity and localization, both in terms of sensed neural signal and applied stimulation. This stems from limited manufacturing processes of commercial-off-the-shelf (COTS) arrays unable to accommodate increased channel density, higher channel count, and smaller contact size.Approach.Here, we describe a manufacturing and assembly approach using thin-film microfabrication for 32-channel high density subdural micro-electrocorticography (µECoG) surface arrays (contacts 1.2 mm diameter, 2 mm pitch) and intracranial electroencephalography (iEEG) depth arrays (contacts 0.5 mm × 1.5 mm, pitch 0.8 mm × 2.5 mm). Crucially, we tackle the translational hurdle and test these arrays during intraoperative studies conducted in four humans under regulatory approval.Main results.We demonstrate that the higher-density contacts provide additional unique information across the recording span compared to the density of COTS arrays which typically have electrode pitch of 8 mm or greater; 4 mm in case of specially ordered arrays. Our intracranial stimulation study results reveal that refined spatial targeting of stimulation elicits evoked potentials with differing spatial spread.Significance.Thin-film,μECoG and iEEG depth arrays offer a promising substrate for advancing a number of clinical and research applications reliant on high-resolution neural sensing and intracranial stimulation.

Prediction of Speech Onset by Micro-Electrocorticography of the Human Brain

Recent technological advances show the feasibility of offline decoding speech from neuronal signals, paving the way to the development of chronically implanted speech brain computer interfaces (sBCI). Two key steps that still need to be addressed for the online deployment of sBCI are, on the one hand, the definition of relevant design parameters of the recording arrays, on the other hand, the identification of robust physiological markers of the patient's intention to speak, which can be used to online trigger the decoding process. To address these issues, we acutely recorded speech-related signals from the frontal cortex of two human patients undergoing awake neurosurgery for brain tumors using three different micro-electrocorticographic ([Formula: see text]ECoG) devices. First, we observed that, at the smallest investigated pitch (600[Formula: see text][Formula: see text]m), neighboring channels are highly correlated, suggesting that more closely spaced electrodes would provide some redundant information. Second, we trained a classifier to recognize speech-related motor preparation from high-gamma oscillations (70-150[Formula: see text]Hz), demonstrating that these neuronal signals can be used to reliably predict speech onset. Notably, our model generalized both across subjects and recording devices showing the robustness of its performance. These findings provide crucial information for the design of future online sBCI.

High-density mapping of primate digit representations with a 1152-channelµECoG array

Objective.Advances in brain-machine interfaces (BMIs) are expected to support patients with movement disorders. Electrocorticogram (ECoG) measures electrophysiological activities over a large area using a low-invasive flexible sheet placed on the cortex. ECoG has been considered as a feasible signal source of the clinical BMI device. To capture neural activities more precisely, the feasibility of higher-density arrays has been investigated. However, currently, the number of electrodes is limited to approximately 300 due to wiring difficulties, device size, and system costs.Approach.We developed a high-density recording system with a large coverage (14 × 7 mm²) and using 1152 electrodes by directly integrating dedicated flexible arrays with the neural-recording application-specific integrated circuits and their interposers.Main results.Comparative experiments with a 128-channel array demonstrated that the proposed device could delineate the entire digit representation of a nonhuman primate. Subsampling analysis revealed that higher-amplitude signals can be measured using higher-density arrays.Significance.We expect that the proposed system that simultaneously establishes large-scale sampling, high temporal-precision of electrophysiology, and high spatial resolution comparable to optical imaging will be suitable for next-generation brain-sensing technology.

Sufficient sampling for kriging prediction of cortical potential in rat, monkey, and human µECoG

Objective. Large channel count surface-based electrophysiology arrays (e.g. µECoG) are high-throughput neural interfaces with good chronic stability. Electrode spacing remains ad hoc due to redundancy and nonstationarity of field dynamics. Here, we establish a criterion for electrode spacing based on the expected accuracy of predicting unsampled field potential from sampled sites.Approach. We applied spatial covariance modeling and field prediction techniques based on geospatial kriging to quantify sufficient sampling for thousands of 500 ms µECoG snapshots in human, monkey, and rat. We calculated a probably approximately correct (PAC) spacing based on kriging that would be required to predict µECoG fields at≤10% error for most cases (95% of observations).Main results. Kriging theory accurately explained the competing effects of electrode density and noise on predicting field potential. Across five frequency bands from 4-7 to 75-300 Hz, PAC spacing was sub-millimeter for auditory cortex in anesthetized and awake rats, and posterior superior temporal gyrus in anesthetized human. At 75-300 Hz, sub-millimeter PAC spacing was required in all species and cortical areas.Significance. PAC spacing accounted for the effect of signal-to-noise on prediction quality and was sensitive to the full distribution of non-stationary covariance states. Our results show that µECoG arrays should sample at sub-millimeter resolution for applications in diverse cortical areas and for noise resilience.

Oscillation-Based Connectivity Architecture Is Dominated by an Intrinsic Spatial Organization, Not Cognitive State or Frequency

Functional connectivity of neural oscillations (oscillation-based FC) is thought to afford dynamic information exchange across task-relevant neural ensembles. Although oscillation-based FC is classically defined relative to a prestimulus baseline, giving rise to rapid, context-dependent changes in individual connections, studies of distributed spatial patterns show that oscillation-based FC is omnipresent, occurring even in the absence of explicit cognitive demands. Thus, the issue of whether oscillation-based FC is primarily shaped by cognitive state or is intrinsic in nature remains open. Accordingly, we sought to reconcile these observations by interrogating the ECoG recordings of 18 presurgical human patients (8 females) for state dependence of oscillation-based FC in five canonical frequency bands across an array of six task states. FC analysis of phase and amplitude coupling revealed a highly similar, largely state-invariant (i.e., intrinsic) spatial component across cognitive states. This spatial organization was shared across all frequency bands. Crucially, however, each band also exhibited temporally independent FC dynamics capable of supporting frequency-specific information exchange. In conclusion, the spatial organization of oscillation-based FC is largely stable over cognitive states (i.e., primarily intrinsic in nature) and shared across frequency bands. Together, our findings converge with previous observations of spatially invariant patterns of FC derived from extremely slow and aperiodic fluctuations in fMRI signals. Our observations indicate that "background" FC should be accounted for in conceptual frameworks of oscillation-based FC targeting task-related changes.SIGNIFICANCE STATEMENT A fundamental property of neural activity is that it is periodic, enabling functional connectivity (FC) between distant regions through coupling of their oscillations. According to task-based studies, such oscillation-based FC is rapid and malleable to meet cognitive task demands. Studying distributed FC patterns instead of FC in a few individual connections, we found that oscillation-based FC is largely stable across various cognitive states and shares a common layout across oscillation frequencies. This stable spatial organization of FC in fast oscillatory brain signals parallels the known stability of fMRI-based intrinsic FC architecture. Despite the observed spatial state and frequency invariance, FC of individual connections was temporally independent between frequency bands, suggesting a putative mechanism for malleable frequency-specific FC to support cognitive tasks.

Local and Volume-Conducted Contributions to Cortical Field Potentials

Brain field potentials (FPs) can reach far from their sources, making difficult to know which waves come from where. We show that modern algorithms efficiently segregate the local and remote contributions to cortical FPs by recovering the generator-specific spatial voltage profiles. We investigated experimentally and numerically the local and remote origin of FPs in different cortical areas in anesthetized rats. All cortices examined show significant state, layer, and region dependent contribution of remote activity, while the voltage profiles help identify their subcortical or remote cortical origin. Co-activation of different cortical modules can be discriminated by the distinctive spatial features of the corresponding profiles. All frequency bands contain remote activity, thus influencing the FP time course, in cases drastically. The reach of different FP patterns is boosted by spatial coherence and curved geometry of the sources. For instance, slow cortical oscillations reached the entire brain, while hippocampal theta reached only some portions of the cortex. In anterior cortices, most alpha oscillations have a remote origin, while in the visual cortex the remote theta and gamma even surpass the local contribution. The quantitative approach to local and distant FP contributions helps to refine functional connectivity among cortical regions, and their relation to behavior.

Conformable polyimide-based μECoGs: Bringing the electrodes closer to the signal source

Structural biocompatibility is a fundamental requirement for chronically stable bioelectronic devices. Newest neurotechnologies are increasingly focused on minimizing the foreign body response through the development of devices that match the mechanical properties of the implanted tissue and mimic its surface composition, often compromising on their robustness. In this study, an analytical approach is proposed to determine the threshold of conformability for polyimide-based electrocorticography devices. A finite element model was used to quantify the depression of the cortex following the application of devices mechanically above or below conformability threshold. Findings were validated in vivo on rat animal models. Impedance measurements were performed for 40 days after implantation to monitor the status of the biotic/abiotic interface with both conformable and non-conformable implants. Multi-unit activity was then recorded for 12 weeks after implantation using the most compliant device type. It can therefore be concluded that conformability is an essential prerequisite for steady and reliable implants which does not only depend on the Young's modulus of the device material: it strongly relies on the relation between tissue curvature at the implantation site and corresponding device's thickness and geometry, which eventually define the moment of inertia and the interactions at the material-tissue interface.

Power Modulations of ECoG Alpha/Beta and Gamma Bands Correlate With Time-Derivative of Force During Hand Grasp

It is well-known that motor cortical oscillatory components are modulated in their amplitude during voluntary and imagined movements. These patterns have been used to develop brain-machine interfaces (BMI) which focused mostly on movement kinematics. In contrast, there have been only a few studies on the relation between brain oscillatory activity and the control of force, in particular, grasping force, which is of primary importance for common daily activities. In this study, we recorded intraoperative high-density electrocorticography (ECoG) from the sensorimotor cortex of four patients while they executed a voluntary isometric hand grasp following verbal instruction. The grasp was held for 2 to 3 s before being instructed to relax. We studied the power modulations of neural oscillations during the whole time-course of the grasp (onset, hold, and offset phases). Phasic event-related desynchronization (ERD) in the low-frequency band (LFB) from 8 to 32 Hz and event-related synchronization (ERS) in the high-frequency band (HFB) from 60 to 200 Hz were observed at grasp onset and offset. However, during the grasp holding period, the magnitude of LFB-ERD and HFB-ERS decreased near or at the baseline level. Overall, LFB-ERD and HFB-ERS show phasic characteristics related to the changes of grasp force (onset/offset) in all four patients. More precisely, the fluctuations of HFB-ERS primarily, and of LFB-ERD to a lesser extent, correlated with the time-course of the first time-derivative of force (yank), rather than with force itself. To the best of our knowledge, this is the first study that establishes such a correlation. These results have fundamental implications for the decoding of grasp in brain oscillatory activity-based neuroprosthetics.

Volume-Conducted Origin of the Field Potential at the Lateral Habenula

Field potentials (FPs) are easily reached signals that provide information about the brain's processing. However, FP should be interpreted cautiously since their biophysical bases are complex. The lateral habenula (LHb) is a brain structure involved in the encoding of aversive motivational values. Previous work indicates that the activity of the LHb is relevant for hippocampal-dependent learning. Moreover, it has been proposed that the interaction of the LHb with the hippocampal network is evidenced by the synchronization of LHb and hippocampal FPs during theta rhythm. However, the origin of the habenular FP has not been analyzed. Hence, its validity as a measurement of LHb activity has not been proven. In this work, we used electrophysiological recordings in anesthetized rats and feed-forward modeling to investigate biophysical basis of the FP recorded in the LHb. Our results indicate that the FP in the LHb during theta rhythm is a volume-conducted signal from the hippocampus. This result highlight that FPs must be thoroughly analyzed before its biological interpretation and argues against the use of the habenular FP signal as a readout of the activity of the LHb.