Electrophysiology publications

The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks.

Segregation of images into figures and background is fundamental for visual perception. Cortical neurons respond more strongly to figural image elements than to background elements, but the mechanisms of figure-ground modulation (FGM) are only partially understood. It is unclear whether FGM in early and mid-level visual cortex is caused by an enhanced response to the figure, a suppressed response to the background, or both.We studied neuronal activity in areas V1 and V4 in monkeys performing a texture segregation task. We compared texture-defined figures with homogeneous textures and found an early enhancement of the figure representation, and a later suppression of the background. Across neurons, the strength of figure enhancement was independent of the strength of background suppression.We also examined activity in the different V1 layers. Both figure enhancement and ground suppression were strongest in superficial and deep layers and weaker in layer 4. The current-source density profiles suggested that figure enhancement was caused by stronger synaptic inputs in feedback-recipient layers 1, 2, and 5 and ground suppression by weaker inputs in these layers, suggesting an important role for feedback connections from higher level areas. These results provide new insights into the mechanisms for figure-ground organization.

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n -gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Nervous systems distinguish between self- and other-generated movements by monitoring discrepancies between planned and performed actions. To do so, corollary discharges are conveyed to sensory areas and gate expected reafference. Such gating is observed in neonatal rats during wake-related movements. In contrast, twitches, which are self-generated movements produced during active (or REM) sleep, differ from wake movements in that they reliably trigger robust neural activity. Accordingly, we hypothesized that the gating actions of corollary discharge are absent during twitching. Here, we identify the external cuneate nucleus (ECN), which processes sensory input from the forelimbs, as a site of movement-dependent sensory gating during wake. Whereas pharmacological disinhibition of the ECN unmasked wake-related reafference, twitch-related reafference was unaffected. This is the first demonstration of a neural comparator that is differentially engaged depending on the kind of movement produced. This mechanism explains how twitches, although self-generated, trigger abundant reafferent activation of sensorimotor circuits in the developing brain.

Maximizing the potential of optogenetic approaches in deep brain structures of intact animals requires optical manipulation of neurons at high spatial and temporal resolutions, while simultaneously recording electrical data from those neurons. Here, we present the first fiber-less optoelectrode with a monolithically integrated optical waveguide mixer that can deliver multicolor light at a common waveguide port to achieve multicolor modulation of the same neuronal population in vivo . We demonstrate successful device implementation by achieving efficient coupling between a side-emitting injection laser diode (ILD) and a dielectric optical waveguide mixer via a gradient-index (GRIN) lens. The use of GRIN lenses attains several design features, including high optical coupling and thermal isolation between ILDs and waveguides. We validated the packaged devices in the intact brain of anesthetized mice co-expressing Channelrhodopsin-2 and Archaerhodopsin in pyramidal cells in the hippocampal CA1 region, achieving high quality recording, activation and silencing of the exact same neurons in a given local region. This fully-integrated approach demonstrates the spatial precision and scalability needed to enable independent activation and silencing of the same or different groups of neurons in dense brain regions while simultaneously recording from them, thus considerably advancing the capabilities of currently available optogenetic toolsets.

We describe a technique to semichronically record the cortical extracellular neural activity in the behaving monkey employing commercial high-density electrodes. After the design and construction of low cost microdrives that allow varying the depth of the recording locations after the implantation surgery, we recorded the extracellular unit activity from pools of neurons at different depths in the presupplementary motor cortex (pre-SMA) of a rhesus monkey trained in a tapping task. The collected data were processed to classify cells as putative pyramidal cells or interneurons on the basis of their waveform features. We also demonstrate that short time cross-correlogram occasionally yields unit pairs with high short latency (<5 ms), narrow bin (<3 ms) peaks, indicative of monosynaptic spike transmission from pre- to postsynaptic neurons. These methods have been verified extensively in rodents. Finally, we observed that the pattern of population activity was repetitive over distinct trials of the tapping task. These results show that the semichronic technique is a viable option for the large-scale parallel recording of local circuit activity at different depths in the cortex of the macaque monkey and other large species.

Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals. We also find direction-distinguishing information up to 400ms before force onset in the pre-movement signals, captured by electrodes placed over the limb-ipsilateral dorsal premotor regions. This approach can contribute to more accurate decoding of higher-level movement goals, at earlier timescales, and inform sensor placement. Our results also contribute to further understanding of the spatiotemporal features of human motor planning.

The sense of touch and proprioception are critical to movement control. After spinal cord injury, these senses may be restored with direct, electrical microstimulation of the brain as part of a complete sensorimotor neuroprosthesis. The present study was designed to test, in part, the hypothesis that the cuneate nucleus (CN) of the brainstem is a suitable site to encode somatosensory information. Two rhesus macaques were implanted with microelectrode arrays providing chronic access to the CN. The monkeys were trained on an active touch oddity task to detect vibrotactile stimuli. When the vibrotactile stimuli were replaced with electrical stimuli delivered to the CN, initial detection probabilities were near chance. Detection performance improved over time, reaching a plateau after about 10 daily sessions. At plateau performance, the monkeys exhibited detection probabilities that were 68-80% higher than the chance probability. Finally, detection probability was quantified as a function of stimulus amplitude. The resulting psychometric curve showed a detection threshold of 45 μA for 100-Hz stimulus trains. These behavioral data are the first to show that artificial CN activation is sufficient for perception. The results are consistent with our hypothesis and motivate future tests of the CN as a somatosensory encoding site.

High-density electrocorticography (ECoG) arrays are promising interfaces for high-resolution neural recording from the cortical surface. Commercial options for high-density arrays are limited, and historically tradeoffs must be made between spatial coverage and electrode density. However, thin-film technology is a promising alternative for generating electrode arrays capable of large area coverage and high channel count, with resolution on the order of cortical columns in the functional surface unit of a human gyrus. Here, we evaluate the sensing performance of a high-density thin-film 128-electrode array designed specifically for recording the distributed neural activity of a single human cortical gyrus. We found robust field potential responses throughout the superior temporal gyrus evoked by speech sounds, and clear phonetic feature selectivity at the resolution of 2 mm inter-electrode distance. Decoding accuracy improved with increasing density of electrodes over all three patients tested. Thin-film ECoG has significant potential for high-density neural interface applications at the scale of a human gyrus.

Cardiac arrest (CA) is one of the most prominent causes of morbidity and mortality in adults. Therapeutic hypothermia (TH) is a recommended treatment to improve survival and functional outcome following CA, however, it is unclear what degree of TH is most beneficial. It has been suggested that TH of 33°C provides no survival or outcome benefits over TH of 36°C. Additionally, there is a lack of verified objective quantitative prognostic tools for comatose CA patients under TH. In this study, we calculated three quantitative markers of somatosensory evoked potentials (SSEP) to examine their potential to track recovery in the early period following CA under graded TH. A total of 16 rats were randomly divided among 4 temperature groups (n=4/group): normothermia (N0, 36.5-37.5°C), hypothermia 1 (H1, 30-32°C), hypothermia 2 (H2, 32-34°C) and hypothermia 3 (H3, 34-36°C). All rats underwent a 15min baseline SSEP recording followed by 9min asphyxial-CA, resulting in severe cerebral injury, and immediate temperature management following resuscitation for 6 hours. SSEP recordings were maintained in 15 min intervals from 30min-4hrs after resuscitation. The N10 amplitude, N10 latency and quantitative SSEP phase space area (qSSEP-PSA) were calculated for the early recovery period and normalized to their respective baselines. Functional recovery was determined by the neurological deficit scale (NDS). N10 amplitude was significantly larger in H1, H2 and H3 compared to N0. N10 latency was significantly longer in H1 than all temperature groups and all hypothermia groups had significantly longer latencies than N0. qSSEP-PSA had significantly better recovery in H1 and H2 than N0. Animals with good outcome (72hr NDS>50) had better recovery of all markers. N10 amplitude was significantly correlated with N10 latency and qSSEP-PSA. The results importantly demonstrate that quantified SSEPs have the potential to objectively track recovery following CA with graded TH.

A key computational principle for encoding time-varying signals in auditory and somatosensory cortices of monkeys is the opponent model of rate coding by two distinct populations of neurons. However, the subthreshold mechanisms that give rise to this computation have not been revealed. Because the rate-coding neurons are only observed in awake conditions, it is especially challenging to probe their underlying cellular mechanisms. Using a novel intracellular recording technique that we developed in awake marmosets, we found that the two types of rate-coding neurons in auditory cortex exhibited distinct subthreshold responses. While the positive-monotonic neurons (monotonically increasing firing rate with increasing stimulus repetition frequency) displayed sustained depolarization at high repetition frequency, the negative-monotonic neurons (opposite trend) instead exhibited hyperpolarization at high repetition frequency but sustained depolarization at low repetition frequency. The combination of excitatory and inhibitory subthreshold events allows the cortex to represent time-varying signals through these two opponent neuronal populations.

The ventral premotor cortex (PMv) is a key node in the neural network involved in grasping. One way PMv can carry out this function is by modulating the outputs of the primary motor cortex (M1) to intrinsic hand and forearm muscles. As many PMv neurons discharge when grasping with either arm, both PMv within the same hemisphere (ipsilateral; iPMv) and in the opposite hemisphere (contralateral; cPMv) could modulate M1 outputs. Our objective was to compare modulatory effects of iPMv and cPMv on M1 outputs to intrinsic hand and forearm muscles. We used paired-pulse protocols with intracortical microstimulations in capuchin monkeys. A conditioning stimulus was applied in either iPMv or cPMv simultaneously or prior to a test stimulus in M1 and the effects quantified in electromyographic signals. Modulatory effects from iPMv were predominantly facilitatory, and facilitation was much more common and powerful on intrinsic hand than forearm muscles. In contrast, while the conditioning of cPMv could elicit facilitatory effects, in particular to intrinsic hand muscles, it was much more likely to inhibit M1 outputs. These data show that iPMv and cPMv have very different modulatory effects on the outputs of M1 to intrinsic hand and forearm muscles.

Target speaker identification is essential for speech enhancement algorithms in assistive devices aimed toward helping the hearing impaired. Several recent studies have reported that target speaker identification is possible through electroencephalography (EEG) recordings. If the EEG system could be reduced to acceptable size while retaining the signal quality, hearing aids could benefit from the integration with concealed EEG. To compare the performance of a multichannel around-the-ear EEG system with high-density cap EEG recordings an envelope tracking algorithm was applied in a competitive speaker paradigm. The data from 20 normal hearing listeners were concurrently collected from the traditional state-of-the-art laboratory wired EEG system and a wireless mobile EEG system with two bilaterally-placed around-the-ear electrode arrays (cEEGrids). The results show that the cEEGrid ear-EEG technology captured neural signals that allowed the identification of the attended speaker above chance-level, with 69.3% accuracy, while cap-EEG signals resulted in the accuracy of 84.8%. Further analyses investigated the influence of ear-EEG signal quality and revealed that the envelope tracking procedure was unaffected by variability in channel impedances. We conclude that the quality of concealed ear-EEG recordings as acquired with the cEEGrid array has potential to be used in the brain-computer interface steering of hearing aids.

Significance We hear sounds varying in intensity over six orders of magnitude using spiral ganglion neurons (SGNs), each of which changes its firing rates over only a fraction of this range. Somehow, the SGNs with different dynamic ranges collectively encode the full range of sound levels represented in the receptor potential of the inner hair cell (IHC) in the mammalian cochlea. Our study, combining subcellular imaging, mouse genetics, and auditory systems physiology, offers a unifying synaptic hypothesis for wide dynamic range sound encoding in the spiral ganglion. We propose that IHCs, from one receptor potential but via presynaptic active zones that vary in the voltage dependence of Ca 2+ influx, generate complementary codes on sound pressure level in functionally distinct SGNs.

Grasping requires translating object geometries into appropriate hand shapes. How the brain computes these transformations is currently unclear. We investigated three key areas of the macaque cortical grasping circuit with microelectrode arrays and found cooperative but anatomically separated visual and motor processes. The parietal area AIP operated primarily in a visual mode. Its neuronal population revealed a specialization for shape processing, even for abstract geometries, and processed object features ultimately important for grasping. Premotor area F5 acted as a hub that shared the visual coding of AIP only temporarily and switched to highly dominant motor signals towards movement planning and execution. We visualize these non-discrete premotor signals that drive the primary motor cortex M1 to reflect the movement of the grasping hand. Our results reveal visual and motor features encoded in the grasping circuit and their communication to achieve transformation for grasping.

The transmembrane recognition complex (TRC40) pathway mediates the insertion of tail-anchored (TA) proteins into membranes. Here, we demonstrate that otoferlin, a TA protein essential for hair cell exocytosis, is inserted into the endoplasmic reticulum (ER) via the TRC40 pathway. We mutated the TRC40 receptor tryptophan-rich basic protein (Wrb) in hair cells of zebrafish and mice and studied the impact of defective TA protein insertion. Wrb disruption reduced otoferlin levels in hair cells and impaired hearing, which could be restored in zebrafish by transgenic Wrb rescue and otoferlin overexpression. Wrb-deficient mouse inner hair cells (IHCs) displayed normal numbers of afferent synapses, Ca2+ channels, and membrane-proximal vesicles, but contained fewer ribbon-associated vesicles. Patch-clamp of IHCs revealed impaired synaptic vesicle replenishment. In vivo recordings from postsynaptic spiral ganglion neurons showed a use-dependent reduction in sound-evoked spiking, corroborating the notion of impaired IHC vesicle replenishment. A human mutation affecting the transmembrane domain of otoferlin impaired its ER targeting and caused an auditory synaptopathy. We conclude that the TRC40 pathway is critical for hearing and propose that otoferlin is an essential substrate of this pathway in hair cells.

Emerging neural prosthetics require precise positional tuning and stable interfaces with single neurons for optimal function over a lifetime. In this study, we report an autonomous control to precisely navigate microscale electrodes in soft, viscoelastic brain tissue without visual feedback. The autonomous control optimizes signal-to-noise ratio (SNR) of single neuronal recordings in viscoelastic brain tissue while maintaining quasi-static mechanical stress conditions to improve stability of the implant-tissue interface. Force-displacement curves from microelectrodes in in vivo rodent experiments are used to estimate viscoelastic parameters of the brain. Using a combination of computational models and experiments, we determined an optimal movement for the microelectrodes with bidirectional displacements of 3:2 ratio between forward and backward displacements and a inter-movement interval of 40 s for minimizing mechanical stress in the surrounding brain tissue. A regulator with the above optimal bidirectional motion for the microelectrodes in in vivo experiments resulted in significant reduction in the number of microelectrode movements (0.23 movements/min) and longer periods of stable SNR (53 % of the time) compared to a regulator using a conventional linear, unidirectional microelectrode movement (with 1.48 movements/min and stable SNR 23 % of the time).

Unlabelled: Accurate sensory discrimination is commonly believed to require precise representations in the nervous system; however, neural stimulus responses can be highly variable, even to identical stimuli. Recent studies suggest that cortical response variability decreases during stimulus processing, but the implications of such effects on stimulus discrimination are unclear. To address this, we examined electrocorticographic cortical field potential recordings from the human nonprimary auditory cortex (superior temporal gyrus) while subjects listened to speech syllables. Compared with a prestimulus baseline, activation variability decreased upon stimulus onset, similar to findings from microelectrode recordings in animal studies. We found that this decrease was simultaneous with encoding and spatially specific for those electrodes that most strongly discriminated speech sounds. We also found that variability was predominantly reduced in a correlated subspace across electrodes. We then compared signal and variability (noise) correlations and found that noise correlations reduce more for electrodes with strong signal correlations. Furthermore, we found that this decrease in variability is strongest in the high gamma band, which correlates with firing rate response. Together, these findings indicate that the structure of single-trial response variability is shaped to enhance discriminability despite non-stimulus-related noise. Significance statement: Cortical responses can be highly variable to auditory speech sounds. Despite this, sensory perception can be remarkably stable. Here, we recorded from the human superior temporal gyrus, a high-order auditory cortex, and studied the changes in the cortical representation of speech stimuli across multiple repetitions. We found that neural variability is reduced upon stimulus onset across electrodes that encode speech sounds.

The analysis of cross-frequency coupling (CFC) has become popular in studies involving intracranial and scalp EEG recordings in humans. It has been argued that some cases where CFC is mathematically present may not reflect an interaction of two distinct yet functionally coupled neural sources with different frequencies. Here we provide two empirical examples from intracranial recordings where CFC can be shown to be driven by the shape of a periodic waveform rather than by a functional interaction between distinct sources. Using simulations, we also present a generalized and realistic scenario where such coupling may arise. This scenario, which we term waveform-dependent CFC, arises when sharp waveforms (e.g., cortical potentials) occur in a periodic manner throughout parts of the data. Since the waveforms are repeated periodically, they constitute a slow wave that is inherently phase-aligned with the high-frequency component carried by the same waveforms. We submit that such behavior of the data, which seems to be present in various cortical signals, cannot be interpreted as reflecting functional modulation between distinct neural sources without additional evidence. In addition, we show that even low amplitude periodic potentials that cannot be readily observed or controlled for, are sufficient for significant CFC to occur.

In the cochlea of the mustached bat, cochlear resonance produces extremely sharp frequency tuning to the dominant frequency of the echolocation calls, around 61 kHz. Such high frequency resolution in the cochlea is accomplished at the expense of losing temporal resolution because of cochlear ringing, an effect that is observable not only in the cochlea but also in the cochlear nucleus. In the midbrain, the duration of sounds is thought to be analyzed by duration-tuned neurons, which are selective to both stimulus duration and frequency. We recorded from 57 DTNs in the auditory midbrain of the mustached bat to assess if a spectral-temporal trade-off is present. Such spectral-temporal trade-off is known to occur as sharp tuning in the frequency domain which results in poorer resolution in the time domain, and vice versa. We found that a specialized sub-population of midbrain DTNs tuned to the bat’s mechanical cochlear resonance frequency escape the cochlear spectral-temporal trade-off. We also show evidence that points towards an underlying neuronal inhibition that appears to be specific only at the resonance frequency.