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Inhibitory neurons innervating the perisomatic region of cortical excitatory principal cells are known to control the emergence of several physiological and pathological synchronous events, including epileptic interictal spikes. In humans, little is known about their role in synchrony generation, although their changes in epilepsy have been thoroughly investigated. This paper demonstraits how parvalbumin (PV)- and type 1 cannabinoid receptor (CB1R)-positive perisomatic interneurons innervate pyramidal cell bodies, and their role in synchronous population events spontaneously emerging in the human epileptic and non-epileptic neocortex, in vitro. Quantitative electron microscopy showed that the overall, PV+ and CB1R+ somatic inhibitory inputs remained unchanged in focal cortical epilepsy. On the contrary, the size of PV-stained synapses increased, and their number decreased in epileptic samples, in synchrony generating regions. Pharmacology demonstrated—in conjunction with the electron microscopy—that although both perisomatic cell types participate, PV+ cells have stronger influence on the generation of population activity in epileptic samples. The somatic inhibitory input of neocortical pyramidal cells remained almost intact in epilepsy, but the larger and consequently more efficient somatic synapses might account for a higher synchrony in this neuron population. This, together with epileptic hyperexcitability, might make a cortical region predisposed to generate or participate in hypersynchronous events.

A new computational method is introduced to calculate the unbiased current source density distribution on a single neuron with known morphology. The relationship between extracellular and intracellular electric potential is determined via mathematical formalism, and a novel reconstruction method is applied for revealing the full spatiotemporal distribution of the membrane potential as well as the resistive and capacitive current components. The novel reconstruction method was validated on simulations. Simultaneous and co-localized whole-cell patch-clamp and multi-channel silicon probe recordings were performed from the same pyramidal neuron in the rat hippocampal CA1 region, in vitro. The method was applied in experimental measurements and returned precise and distinctive characteristics of various intracellular phenomena, such as the action potential generation, signal back-propagation, as well as initial dendritic depolarization preceding the somatic action potential.Even though electrophysiologists have been routinely recording intracellular neural activity ever since the groundbreaking work of Hodgkin and Huxley and extracellular multi-channel electrodes have also been frequently and extensively used, a practical experimental method to track membrane potential changes along a complete single neuron is still lacking. Instead of obtaining multiple intracellular measurements on the same neuron, we propose an alternative method by combining single-channel somatic patch-clamp and multi-channel extracellular potential recordings. In this work, we show that it is possible to reconstruct the complete spatiotemporal distribution of the membrane potential of a single neuron with the spatial resolution of an extracellular probe during action potential generation. Moreover, the reconstruction of the membrane potential allows for distinguishing between the two major but previously hidden components of the current source density (CSD) distribution: the resistive and the capacitive currents. This distinction provides a clue to the clear interpretation of the CSD analysis, as the resistive component corresponds to transmembrane ionic currents: all the synaptic, voltage-sensitive, and passive currents; while capacitive currents are considered the main contributors of counter-currents. We validate our model-based reconstruction approach on simulations and demonstrate its application to experimental data obtained in vitro via paired extracellular and intracellular recordings from a single pyramidal cell of the rat hippocampus. In perspective, the estimation of the spatial distribution of resistive membrane currents makes the distinction possible between active and passive sinks and sources of the CSD map and the localization of the synaptic input currents, which make the neuron fire. Abstract figure legend In this work, we show that it is possible to reconstruct the complete spatiotemporal distribution of the membrane potential of a single neuron, with the spatial resolution of an extracellular probe, by combining single-channel somatic patch-clamp and multi-channel extracellular potential recordings during action potential generation. The model-based membrane potential reconstruction utilizes the detailed morphology of the neuron and allows for distinguishing between the two major but previously hidden components of the current source density (CSD) distribution: the resistive and the capacitive currents. This distinction provides a clue to the clear interpretation of the CSD analysis, as the resistive component corresponds to transmembrane ionic currents: all the synaptic, voltage-sensitive, and passive currents; while capacitive currents are considered the main contributors of counter-currents. In perspective, the estimation of the spatial distribution of resistive membrane currents makes possible the localization of the synaptic input currents, which make the neuron fire. This article is protected by copyright. All rights reserved.

Objective: Spiking activity of individual neurons can be separated from the acquired multi-unit activity with spike sorting methods. Processing the recorded high-dimensional neural data can take a large amount of time when performed on general-purpose computers. Methods: In this paper, an FPGA-based real-time spike sorting system is presented which takes into account the spatial correlation between the electrical signals recorded with closely-packed recording sites to cluster multi-channel neural data. The system uses a spatial window-based version of the Online Sorting algorithm, which uses unsupervised template-matching for clustering. Results: The test results show that the proposed system can reach an average accuracy of 86% using simulated data (16–32 neurons, 4–10 dB Signal-to-Noise Ratio), while the single-channel clustering version achieves only 74% average accuracy in the same cases on a 128-channel electrode array. The developed system was also tested on in vivo cortical recordings obtained from an anesthetized rat. Conclusion: The proposed FPGA-based spike sorting system can process more than 11000 spikes/second, so it can be used during in vivo experiments providing real-time feedback on the location and electrophysiological properties of well-separable single units. Significance: The proposed spike sorting system could be used to reduce the positioning error of the closely-packed recording site during a neural measurement.

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Objective:Describing intracortical laminar organization of high frequency oscillations (HFOs).Methods:We recorded potential gradients with laminar microelectrode arrays (LME) for current source density (CSD) and multi-unit activity (MUA) analysis of interictal discharges (IID) and HFOs in the neocortex and mesial temporal lobe of focal epilepsy patients. Results:Ripples were only observed in 9/29 patients, all within the seizure onset zone (SOZ). Ripples variably (≈50%) coincided with IIDs. CSD analysis revealed slow ripples (150Hz) were biased to the lower layers, tending to precede the superficial activity (10-30ms).Conclusion: Our findings suggest that cortical slow ripples are generated primarily in upper layers while fast ripples and associated MUA in deeper layers. The dissociation of macro- and microdomains suggests that microelectrode recordings may be more selective for SOZ-linked ripples.Significance:We found a complex interplay between neural activity in the neocortical laminae during ripple formation. We observed a potential leading role of cortical neurons in deeper layers, suggesting a refined utilization of LMEs in SOZ localization.

Background Mindset and communication barriers may hinder the acceptance of bariatric surgery (BS) by the eligible patient population. Objectives To improve the understanding of expectations, opinions, emotions, and attitudes toward weight loss among patients with obesity. Setting Switzerland, Germany, Austria. Methods Survey data collected from BS-related social media communities (n = 1482). Participants were asked to write 5 words that first came to their mind about “weight loss,” and to select 2 emotions, which best described their corresponding feelings. Demographic and obesity-related data were collected. Cognitive representations were constructed based on the co-occurrence network of associations, using validated data-driven methodology. Results Respondents were Caucasian (98%), female (94%), aged 42.5 ± 10.1 years, current/highest lifetime body mass index = 36.9 ± 9/50.7 ± 8.7 kg/m2. The association network analysis revealed the following 2 cognitive modules: benefit-focused (health, attractiveness, happiness, agility) and procedure-focused (effort, diet, sport, surgery). Patients willing to undergo BS were more benefit-focused (odds ratio [OR] = 2.4, P = .02) and expressed more “hope” (OR = 142, P Conclusion Patients with obesity in our study tend to think about weight loss along 2 cognitive schemes, either emphasizing its expected benefits or focusing on the process of achieving it. Benefit-focused respondents were more likely to consider BS, and to express hope rather than gratitude or pride. Novel communication strategies may increase the acceptance of BS by incorporating weight loss–related cognitive and emotional content stemming from patients’ free associations.

Despite advantage of neuroimaging measures in translational research frameworks, less is known about the psychometric properties thereof, especially in middle-late adolescents. Earlier, we examined evidence of convergent and incremental validity of reward anticipation and response event-related potentials (ERPs) and here we examined, in the same sample of 43 adolescents (M

Knowledge about the activity of single neurons is essential in understanding the mechanisms of synchrony generation, and particularly interesting if related to pathological conditions. The generation of interictal spikes—the hypersynchronous events between seizures—is linked to hyperexcitability and to bursting behaviour of neurons in animal models. To explore its cellular mechanisms in humans we investigated the activity of clustered single neurons in a human in vitro model generating both physiological and epileptiform synchronous events. We show that non-epileptic synchronous events resulted from the finely balanced firing of excitatory and inhibitory cells, which was shifted towards an enhanced excitability in epileptic tissue. In contrast, interictal-like spikes were characterised by an asymmetric overall neuronal discharge initiated by excitatory neurons with the presumptive leading role of bursting pyramidal cells, and possibly terminated by inhibitory interneurons. We found that the overall burstiness of human neocortical neurons is not necessarily related to epilepsy, but the bursting behaviour of excitatory cells comprising both intrinsic and synaptically driven bursting is clearly linked to the generation of epileptiform synchrony.

Sleep EEG reflects instantaneous voltage differences relative to a reference, while its spectrum reflects the degree to which it is comprised of oscillations at various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations at specific frequencies, and its spectrum reflects the rhythmicity of the occurrence of these oscillations. The ordinary sleep EEG and its spectrum have been extensively studied and its individual stability and relationship to various demographic characteristics, psychological traits and pathologies is well known. In contrast, the envelope spectrum has not been extensively studied before. In two studies, we explored the generating mechanisms and utility of studying the envelope of the sleep EEG. First, we used human invasive data from cortex-penetrating microelectrodes and subdural grids to demonstrate that the sleep EEG envelope spectrum reflects local neuronal firing. Second, we used a large database of healthy volunteers to demonstrate that the scalp EEG envelope spectrum is highly stable within individuals, especially in NREM sleep, and that it is affected by age and sex. Multivariate models based on a learning algorithm could predict both age (r=0.6) and sex (r=0.5) with considerable accuracy from the EEG envelope spectrum. With age, oscillations characteristically shifted from a 4-5 second rhythm to higher rhythms. The envelope spectrum was not associated with general cognitive ability (IQ). Our results demonstrate that the sleep envelope spectrum is a promising, neuronal firing-based biomarker of various demographic and disease-related phenotypes.

In this paper, we investigate the long-term adhesion strength and barrier property of our recently proposed encapsulation stack that includes PDMS-Parylene C and PECVD interlayers (SiO 2 and SiC) for adhesion improvement. To evaluate the adhesion strength of our proposed stack, the sample preparation consisted in depositing approximately 25 nm of SiC and 25 nm of SiO 2 on half wafers, previously coated with Parylene C. Next, $50 \mu \mathrm{m}$ PDMS was spin-coated on top. Finally, the samples were detached from the Si wafer and soaked in a PBS solution at 67°C to accelerate the aging process. Two samples were also implanted, subcutaneously, on the left and right subscapular regions of a rat. The optical inspection and peel tests performed after two months confirmed our preliminary findings and showed a significant improvement of the adhesion in our proposed encapsulation stack compared to the case of PDMS on Parylene C alone. In addition, the X-ray photoelectron spectroscopy(XPS) analysis at the interface between SiC and Parylene C showed different peaks for the interface compared to the reference spectra, which could be an indication of a chemical bond. Finally, water vapor transmission rate (WVTR) tests were performed to investigate the barrier property of our proposed encapsulation stack against water vapor transmission. The results demonstrated that the proposed stack acts as a significantly (two orders of magnitude) higher barrier against moisture compared to only Parylene C and PDMS encapsulation layers. The proposed method yields a fully transparent encapsulation stack over a broad wavelength spectrum that can be used for the conformal encapsulation of flexible devices and thus, making them compatible with techniques such as optical imaging and optogenetics.

Cortical dynamics obey a 1/f power law, exhibiting an exponential decay of spectral power with increasing frequency. The slope and offset of this 1/f decay reflect the timescale and magnitude of aperiodic neural activity, respectively. These properties are tightly linked to cellular and circuit mechanisms (e.g. excitation:inhibition balance and firing rates) as well as cognitive processes (e.g. perception, memory, and state). However, the physiology underlying the 1/f power law in cortical dynamics is not well understood. Here, we compared laminar recordings from human, macaque and mouse cortex to evaluate how 1/f aperiodic dynamics vary across cortical layers and species. We report that 1/f slope is steepest in superficial layers and flattest in deep layers in each species. Additionally, the magnitude of this 1/f decay is greatest in superficial cortex and decreases with depth. We could account for both of these findings with a simple model in which superficial cortical transmembrane currents had longer time constants and greater densities than those in deeper layers. Together, our results provide novel insight into the organization of cortical dynamics, suggesting that the amplitude and time constant of local currents control circuit processing as a function of laminar depth. This may represent a general mechanism to facilitate appropriate integration of fast sensory inputs (infragranular) with slow feedback-type inputs (supragranular) across cortical areas and species.

Publicly available neural recordings obtained with high spatial resolution are scarce. Here, we present an electrophysiological dataset recorded from the neocortex of twenty rats anesthetized with ketamine/xylazine. The wideband, spontaneous recordings were acquired with a single-shank silicon-based probe having 128 densely-packed recording sites arranged in a 32 × 4 array. The dataset contains the activity of a total of 7126 sorted single units extracted from all layers of the cortex. Here, we share raw neural recordings, as well as spike times, extracellular spike waveforms and several properties of units packaged in a standardized electrophysiological data format. For technical validation of our dataset, we provide the distributions of derived single unit properties along with various spike sorting quality metrics. This large collection of in vivo data enables the investigation of the high-resolution electrical footprint of cortical neurons which in turn may aid their electrophysiology-based classification. Furthermore, the dataset might be used to study the laminar-specific neuronal activity during slow oscillation, a brain rhythm strongly involved in neural mechanisms underlying memory consolidation and sleep., Measurement(s) cortical electrical activity Technology Type(s) electrophysiological method Sample Characteristic - Organism Rattus norvegicus Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14555421

The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

Background Sleep spindles are involved in memory consolidation and other cognitive functions. Numerous automated methods for detection of spindles have been proposed; most of these rely on spectral analysis in some form. However, none of these approaches are ideal, and novel approaches to the problem could provide additional insights. New method Here, we apply delay differential analysis (DDA), a time-domain technique based on nonlinear dynamics to detect sleep spindles in human intracranial sleep data, including laminar electrode, stereoelectroencephalogram (sEEG), and electrocorticogram (ECoG) recordings. Results We show that this approach is computationally fast, generalizable, requires minimal preprocessing, and provides excellent agreement with human scoring. Comparison with existing methods We compared the method with established methods on a set of intracranial recordings and this method provided the highest agreement with human expert scoring when evaluated with F1 score while being the second-fastest to run. We also compared the results on the DREAMS surface EEG data, where the method produced a higher average F1 score than all other tested methods except the automated detections published with the DREAMS data. Further, in addition to being a fast and reliable method for spindle detection, DDA also provides a novel characterization of spindle activity based on nonlinear dynamical content of the data. Conclusions This additional, non-frequency-based perspective could prove particularly useful for certain atypical spindles, or identifying spindles of different types.

Episodic learning and memory retrieval are dependent on hippocampal theta oscillation, thought to rely on the GABAergic network of the medial septum (MS). To test how this network achieves theta synchrony, we recorded MS neurons and hippocampal local field potential simultaneously in anesthetized and awake mice and rats. We show that MS pacemakers synchronize their individual rhythmicity frequencies, akin to coupled pendulum clocks as observed by Huygens. We optogenetically identified them as parvalbumin-expressing GABAergic neurons, while MS glutamatergic neurons provide tonic excitation sufficient to induce theta. In accordance, waxing and waning tonic excitation is sufficient to toggle between theta and non-theta states in a network model of single-compartment inhibitory pacemaker neurons. These results provide experimental and theoretical support to a frequency-synchronization mechanism for pacing hippocampal theta, which may serve as an inspirational prototype for synchronization processes in the central nervous system from Nematoda to Arthropoda to Chordate and Vertebrate phyla.

Episodic learning and memory retrieval are critically dependent on a hippocampal 4-12 Hz oscillatory ‘clock’ signal, the theta oscillation. This clock is largely externally paced, by a network of GABAergic neurons in the medial septum (MS). Theoretical studies suggested a range of hypotheses how this network may achieve theta synchrony; however, experimental evidence is still lacking. By recording multiple single MS neurons and hippocampal local field potential oscillations simultaneously, with both acute and chronically implanted silicon probes, we show that MS pacemaker units oscillate at individual frequencies within the theta range in rodents. Synchronization of MS neuron frequencies, accompanied by an elevation of firing rates, was found to parallel hippocampal theta formation in multiple rodent model systems. This suggests a general mechanism for theta synchronization, akin to the synchronization of weakly coupled pendulum clocks observed by Huygens in the 17thcentury. We optogenetically identified the MS pacemaker units as parvalbumin-expressing GABAergic neurons, while the previously enigmatic MS glutamatergic neurons were mostly theta-activated non-rhythmic cells. Our data were consistent with a network model of partially connected single-compartment inhibitory pacemaker neurons, in which synchronization and de-synchronization in the frequency domain upon waxing and waning tonic excitatory drive was sufficient to toggle MS network output between theta and non-theta states. These results provide experimental and theoretical support to a frequency-synchronization mechanism for pacing hippocampal theta, which may serve as an inspirational prototype for the countless examples of synchronization processes in the central nervous system from Nematoda to Anthropoda to Chordate and Vertebrate phyla.

Adolescence is a developmental period characterized by heightened reward sensitivity which, in turn, confers risk for pertinent negative outcomes, underscoring the need to better understand biological bases and behavioral correlates of reward responsiveness during this developmental phase. Our goals in the current study were to examine, in a sample of 43 typically developing adolescents (Mage = 15.67 years; SD = 1.01; 32.6% boys), (1) evidence of convergent validity between neural and self-report reward responsiveness, (2) associations between neural reward responsiveness and self-report dispositional affectivity and emotion dysregulation (ED) and (3) evidence of incremental validity of self-report beyond neural reward responsiveness in predicting affectivity and ED. During electroencephalography (EEG), adolescents completed two experimental paradigms probing event-related potential (ERP) indices of reward anticipation and initial responsiveness to reward attainment. Following EEG, they completed self-report measures of reward responsiveness, affectivity, and ED. Findings indicated some evidence of convergent validity between enhanced ERP indices of reward anticipation and initial response to reward and greater reinforcement sensitivity; that ERP indices of both reward responsiveness aspects predicted lower negative affectivity and less ED; and evidence of incremental validity of self-report beyond neural reward responsiveness in predicting outcomes. Results underscore the utility of a multi-method framework in assessing adolescent reward responsiveness and support the relevance of reward responsiveness in explaining individual differences in dispositional affectivity and ED.