Seeing beyond the spikes: reconstructing the complete spatiotemporal membrane potential distribution from paired intra- and extracellular recordings.

Although electrophysiologists have been recording intracellular neural activity routinely ever since the ground-breaking work of Hodgkin and Huxley, and extracellular multichannel electrodes have also been used frequently and extensively, a practical experimental method to track changes in membrane potential 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 multichannel 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 us to distinguish 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, because the resistive component corresponds to transmembrane ionic currents (all the synaptic, voltage-sensitive and passive currents), whereas capacitive currents are considered to be 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 it possible to distiguish between active and passive sinks and sources of the CSD map and the localization of the synaptic input currents, which make the neuron fire. KEY POINTS: 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 new reconstruction method is applied to reveal the full spatiotemporal distribution of the membrane potential and the resistive and capacitive current components. The new reconstruction method was validated on simulations. Simultaneous and colocalized whole-cell patch-clamp and multichannel 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 action potential generation, signal back-propagation and the initial dendritic depolarization preceding the somatic action potential.

Manifold-adaptive dimension estimation revisited.

Data dimensionality informs us about data complexity and sets limit on the structure of successful signal processing pipelines. In this work we revisit and improve the manifold adaptive Farahmand-Szepesvári-Audibert (FSA) dimension estimator, making it one of the best nearest neighbor-based dimension estimators available. We compute the probability density function of local FSA estimates, if the local manifold density is uniform. Based on the probability density function, we propose to use the median of local estimates as a basic global measure of intrinsic dimensionality, and we demonstrate the advantages of this asymptotically unbiased estimator over the previously proposed statistics: the mode and the mean. Additionally, from the probability density function, we derive the maximum likelihood formula for global intrinsic dimensionality, if i.i.d. holds. We tackle edge and finite-sample effects with an exponential correction formula, calibrated on hypercube datasets. We compare the performance of the corrected median-FSA estimator with kNN estimators: maximum likelihood (Levina-Bickel), the 2NN and two implementations of DANCo (R and MATLAB). We show that corrected median-FSA estimator beats the maximum likelihood estimator and it is on equal footing with DANCo for standard synthetic benchmarks according to mean percentage error and error rate metrics. With the median-FSA algorithm, we reveal diverse changes in the neural dynamics while resting state and during epileptic seizures. We identify brain areas with lower-dimensional dynamics that are possible causal sources and candidates for being seizure onset zones.

Model-free detection of unique events in time series.

Recognition of anomalous events is a challenging but critical task in many scientific and industrial fields, especially when the properties of anomalies are unknown. In this paper, we introduce a new anomaly concept called "unicorn" or unique event and present a new, model-free, unsupervised detection algorithm to detect unicorns. The key component of the new algorithm is the Temporal Outlier Factor (TOF) to measure the uniqueness of events in continuous data sets from dynamic systems. The concept of unique events differs significantly from traditional outliers in many aspects: while repetitive outliers are no longer unique events, a unique event is not necessarily an outlier; it does not necessarily fall out from the distribution of normal activity. The performance of our algorithm was examined in recognizing unique events on different types of simulated data sets with anomalies and it was compared with the Local Outlier Factor (LOF) and discord discovery algorithms. TOF had superior performance compared to LOF and discord detection algorithms even in recognizing traditional outliers and it also detected unique events that those did not. The benefits of the unicorn concept and the new detection method were illustrated by example data sets from very different scientific fields. Our algorithm successfully retrieved unique events in those cases where they were already known such as the gravitational waves of a binary black hole merger on LIGO detector data and the signs of respiratory failure on ECG data series. Furthermore, unique events were found on the LIBOR data set of the last 30 years.

Relaxation of Some Confusions about Confounders.

This work is about observational causal discovery for deterministic and stochastic dynamic systems. We explore what additional knowledge can be gained by the usage of standard conditional independence tests and if the interacting systems are located in a geodesic space.

Do not waste your electrodes-principles of optimal electrode geometry for spike sorting.

Objective. This study examines how the geometrical arrangement of electrodes influences spike sorting efficiency, and attempts to formalise principles for the design of electrode systems enabling optimal spike sorting performance.Approach. The clustering performance of KlustaKwik, a popular toolbox, was evaluated using semi-artificial multi-channel data, generated from a library of real spike waveforms recorded in the CA1 region of mouse Hippocampusin vivo.Main results. Based on spike sorting results under various channel configurations and signal levels, a simple model was established to describe the efficiency of different electrode geometries. Model parameters can be inferred from existing spike waveform recordings, which allowed quantifying both the cooperative effect between channels and the noise dependence of clustering performance.Significance. Based on the model, analytical and numerical results can be derived for the optimal spacing and arrangement of electrodes for one- and two-dimensional electrode systems, targeting specific brain areas.

Network Path Convergence Shapes Low-Level Processing in the Visual Cortex.

Hierarchical counterstream via feedforward and feedback interactions is a major organizing principle of the cerebral cortex. The counterstream, as a topological feature of the network of cortical areas, is captured by the convergence and divergence of paths through directed links. So defined, the convergence degree (CD) reveals the reciprocal nature of forward and backward connections, and also hierarchically relevant integrative properties of areas through their inward and outward connections. We asked if topology shapes large-scale cortical functioning by studying the role of CD in network resilience and Granger causal coupling in a model of hierarchical network dynamics. Our results indicate that topological synchronizability is highly vulnerable to attacking edges based on CD, while global network efficiency depends mostly on edge betweenness, a measure of the connectedness of a link. Furthermore, similar to anatomical hierarchy determined by the laminar distribution of connections, CD highly correlated with causal coupling in feedforward gamma, and feedback alpha-beta band synchronizations in a well-studied subnetwork, including low-level visual cortical areas. In contrast, causal coupling did not correlate with edge betweenness. Considering the entire network, the CD-based hierarchy correlated well with both the anatomical and functional hierarchy for low-level areas that are far apart in the hierarchy. Conversely, in a large part of the anatomical network where hierarchical distances are small between the areas, the correlations were not significant. These findings suggest that CD-based and functional hierarchies are interrelated in low-level processing in the visual cortex. Our results are consistent with the idea that the interplay of multiple hierarchical features forms the basis of flexible functional cortical interactions.

Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings.

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.

Laminar distribution of electrically evoked hippocampal short latency ripple activity highlights the importance of the subiculum in vivo in human epilepsy, an intraoperative study.

OBJECTIVE: The goal of this study was to define the pathology and anesthesia dependency of single pulse electrical stimulation (SPES) dependent high-frequency oscillations (HFOs, ripples, fast ripples) in the hippocampal formation. METHODS: Laminar profile of electrically evoked short latency (<100 ms) high-frequency oscillations (80-500 Hz) was examined in the hippocampus of therapy-resistant epileptic patients (6 female, 2 male) in vivo, under general anesthesia. RESULTS: Parahippocampal SPES evoked HFOs in all recorded hippocampal subregions (Cornu Ammonis 2-3, dentate gyrus, and subiculum) were not uniform, rather the combination of ripples, fast ripples, sharp transients, and multiple unit activities. Mild and severe hippocampal sclerosis (HS) differed in the probability to evoke fast ripples: it decreased with the severity of sclerosis in CA2-3 but increased in the subiculum. Modulation in the ripple spectrum was observed only in the subiculum with increased fast HFO rate and frequency in severe HS. Inhalational anesthetics (isoflurane) suppressed the chance to evoke HFOs compared to propofol. CONCLUSION: The presence of early HFOs in the dentate gyrus and early fast HFOs (>250 Hz) in the other subregions indicate the pathological nature of these evoked oscillations. Subiculum was found to be active producing HFOs in parallel with the cell loss in the hippocampus proper, which emphasize the role of this region in the generation of epileptic activity.

Mental and emotional representations of "weight loss": free-word association networks in members of bariatric surgery-related social media communities.

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 < .001). History of BS was associated with higher adherence to the procedure-focused module (OR = 2.3, P < .001), and with increased use of the emotions "gratitude" (OR = 107, P < .001), "pride" (OR = 15, P < .001), and decreased mention of "hope" (OR = .03, P < .001). 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.

Causal relationship between local field potential and intrinsic optical signal in epileptiform activity in vitro.

The directed causal relationship were examined between the local field potential (LFP) and the intrinsic optical signal (IOS) during induced epileptiform activity in in vitro cortical slices by the convergent cross-mapping causality analysis method. Two components of the IOS signal have been distinguished: a faster, activity dependent component (IOSh) which changes its sign between transmitted and reflected measurement, thus it is related to the reflectance or the scattering of the tissue and a slower component (IOSl), which is negative in both cases, thus it is resulted by the increase of the absorption of the tissue. We have found a strong, unidirectional, delayed causal effect from LFP to IOSh with 0.5-1s delay, without signs of feedback from the IOSh to the LFP, while the correlation was small and the peaks of the cross correlation function did not reflect the actual causal dependency. Based on these observations, a model has been set up to describe the dependency of the IOSh on the LFP power and IOSh was reconstructed, based on the LFP signal. This study demonstrates that causality analysis can lead to better understanding the physiological interactions, even in case of two data series with drastically different time scales.

Strategic Positioning of Connexin36 Gap Junctions Across Human Retinal Ganglion Cell Dendritic Arbors.

Connexin36 (Cx36) subunits form gap junctions (GJ) between neurons throughout the central nervous system. Such GJs of the mammalian retina serve the transmission, averaging and correlation of signals prior to conveying visual information to the brain. Retinal GJs have been exhaustively studied in various animal species, however, there is still a perplexing paucity of information regarding the presence and function of human retinal GJs. Particularly little is known about GJ formation of human retinal ganglion cells (hRGCs) due to the limited number of suitable experimental approaches. Compared to the neuronal coupling studies in animal models, where GJ permeable tracer injection is the gold standard method, the post-mortem nature of scarcely available human retinal samples leaves immunohistochemistry as a sole approach to obtain information on hRGC GJs. In this study Lucifer Yellow (LY) dye injections and Cx36 immunohistochemistry were performed in fixed short-post-mortem samples to stain hRGCs with complete dendritic arbors and locate dendritic Cx36 GJs. Subsequent neuronal reconstructions and morphometric analyses revealed that Cx36 plaques had a clear tendency to form clusters and particularly favored terminal dendritic segments.

Revealing the distribution of transmembrane currents along the dendritic tree of a neuron from extracellular recordings.

Revealing the current source distribution along the neuronal membrane is a key step on the way to understanding neural computations; however, the experimental and theoretical tools to achieve sufficient spatiotemporal resolution for the estimation remain to be established. Here, we address this problem using extracellularly recorded potentials with arbitrarily distributed electrodes for a neuron of known morphology. We use simulations of models with varying complexity to validate the proposed method and to give recommendations for experimental applications. The method is applied to in vitro data from rat hippocampus.

Calcium buffer proteins are specific markers of human retinal neurons.

Ca(2+)-buffer proteins (CaBPs) modulate the temporal and spatial characteristics of transient intracellular Ca(2+)-concentration changes in neurons in order to fine-tune the strength and duration of the output signal. CaBPs have been used as neurochemical markers to identify and trace neurons of several brain loci including the mammalian retina. The CaBP content of retinal neurons, however, varies between species and, thus, the results inferred from animal models cannot be utilised directly by clinical ophthalmologists. Moreover, the shortage of well-preserved human samples greatly impedes human retina studies at the cellular and network level. Our purpose has therefore been to examine the distribution of major CaBPs, including calretinin, calbindin-D28, parvalbumin and the recently discovered secretagogin in exceptionally well-preserved human retinal samples. Based on a combination of immunohistochemistry, Neurolucida tracing and Lucifer yellow injections, we have established a database in which the CaBP marker composition can be defined for morphologically identified cell types of the human retina. Hence, we describe the full CaBP make-up for a number of human retinal neurons, including HII horizontal cells, AII amacrine cells, type-1 tyrosine-hydroxylase-expressing amacrine cells and other lesser known neurons. We have also found a number of unidentified cells whose morphology remains to be characterised. We present several examples of the colocalisation of two or three CaBPs with slightly different subcellular distributions in the same cell strongly suggesting a compartment-specific division of labour of Ca(2+)-buffering by CaBPs. Our work thus provides a neurochemical framework for future ophthalmological studies and renders new information concerning the cellular and subcellular distribution of CaBPs for experimental neuroscience.

The Retinal TNAP.

Accumulating evidence from recent literature underline the important roles of tissue non specific alkaline phosphatase (TNAP) in diverse functions as well as diseases of the nervous system. Exploration of TNAP in well characterized neural circuits such as the retina, might significantly advance our understanding regarding neural TNAP's roles. This chapter reviews the scarce literature as well as our findings on retinal TNAP. We found that retinal TNAP activity was preserved and followed diverse patterns throughout vertebrate evolution. We have consistently observed TNAP activity (1) in retinal vessels, (2) in photoreceptors and (3) in the majority of the studied species in the outer (OPL) and inner plexiform layers (IPL), where synaptic transmission occurs. Importantly, in some species the IPL exhibits several TNAP positive strata. These strata exactly corresponded those seen after quadruple immunohistochemistry with four canonical IPL markers (tyrosine hydroxylase, choline acetyltransferase, calretinin, protein kinase C α). Diabetes results in diminishing retinal TNAP activity before changes in canonical markers could be observed in a rat model. The presence of TNAP activity at critical sites of neurotransmission suggests its important and evolutionary conserved role in vision. In diabetes, the decreased TNAP activity indicates neurological alterations adding further evidence for the role of TNAP in brain diseases.

Stratified organization and disorganization of inner plexiform layer revealed by TNAP activity in healthy and diabetic rat retina.

Tissue non-specific alkaline phosphatase (TNAP), an abundant ectophosphatase, is present in various organs including the brain and retina of several vertebrate species. Evidence is emerging that TNAP influences neural functions in multiple ways. In rat, strong TNAP activity has been found in retinal vessels, photoreceptors, and both synaptic layers. In the present study, we identified eleven strata of the inner plexiform layer (IPL) by using TNAP histochemistry alone. The TNAP strata corresponded exactly to the strata seen after combined immunohistochemistry with four canonical IPL markers (TH-ChAT-CR-PKCα). Therefore, as described in other mammalian species, our data support the existence of multiple morphologically and functionally discernible IPL strata in rats. Remarkably, the stratification pattern of the IPL was severely disrupted in a diabetic rat model, even before changes in the canonical IPL markers were detectable. These findings indicate that TNAP histochemistry offers a more straightforward, but also more sensitive, method for investigating retinal strata and their diabetes-induced degeneration.

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals.

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function.

In vitro intrinsic optical imaging can be used for source determination in cortical slices.

In the last decades intrinsic optical imaging has become a widely used technique for monitoring activity in vivo and in vitro. It is assumed that in brain slices the source of intrinsic optical signals (IOSs) is the change in light scattering caused by cell swelling or shrinkage. The aim of the present study was to find a correlation between electrical activity and parallel optical characteristics, elicited by 4-aminopyridine-containing or Mg(2+) -free medium in rat cortical brain slices. Electrophysiological signals and reflected light alterations were recorded during spontaneous seizure activity. Current source density (CSD) analysis was performed on the electrophysiological records. Direct correlation analysis of IOS to CSD was made, and source distribution provided by IOS and CSD methods was compared by determining Matthews correlation coefficient. The gradual development of seizure-like activity elicited the reduction of light reflectance. The main findings of our experiments are that long-term epileptiform activity resulted in persistent alteration in IOSs of brain slices. The observed IOS pattern remained stable after 1 h incubation in convulsants. The pattern of IOS shows good correlation with the data obtained from the CSD analysis. Persistent IOS changes provide information about the area-specific changes of basic excitability, which can serve as a background for ictal and interictal-like epileptiform activity. We can conclude that changes in IOSs correlate well with electrophysiological recordings under different conditions. Our experiments provide evidence that underlying synchronised neuronal processes produce parallel alterations in IOSs and electrophysiological activity.

Localization of single-cell current sources based on extracellular potential patterns: the spike CSD method.

Traditional current source density (tCSD) calculation method calculates neural current source distribution of extracellular (EC) potential patterns, thus providing important neurophysiological information. While the tCSD method is based on physical principles, it adopts some assumptions, which can not hold for single-cell activity. Consequently, tCSD method gives false results for single-cell activity. A new, spike CSD (sCSD) method has been developed, specifically designed to reveal CSD distribution of single cells during action potential generation. This method is based on the inverse solution of the Poisson-equation. The efficiency of the method is tested and demonstrated with simulations, and showed, that the sCSD method reconstructed the original CSD more precisely than the tCSD. The sCSD method is applied to EC spatial potential patterns of spikes, measured in cat primary auditory cortex with a 16-channel chronically implanted linear probe in vivo. Using our method, the cell-electrode distances were estimated and the spatio-temporal CSD distributions were reconstructed. The results suggested, that the new method is potentially useful in determining fine details of the spatio-temporal dynamics of spikes.

Distance coding strategies based on the entorhinal grid cell system.

Estimating and keeping track of the distance from salient points of the environment are important constituents of the spatial awareness and navigation. In rodents, the majority of principal cells in the hippocampus are known to be correlated with the position of the animal. However, the lack of topography in the hippocampal cognitive map does not support the assumption that connections between these cells are able to store and recall distances between coded positions. In contrast, the firing fields of the grid cells in the medial entorhinal cortex form triangular grids and are organized on metrical principles. We suggest a model in which a hypothesized 'distance cell' population is able to extract metrics from the activity of grid cells. We show that storing the momentary activity pattern of the grid cell system in a freely chosen position by one-shot learning and comparing it to the actual grid activity at other positions results in a distance dependent activity of these cells. The actual distance of the animal from the origin can be decoded directly by selecting the distance cell receiving the largest excitation or indirectly via transmission of local interneurons. We found that direct decoding works up to the longest grid spacing, but fails on smaller scales, while the indirect way provides precise distance determination up to the half of the longest grid spacing. In both cases, simulated distance cells have a multi-peaked, patchy spatial activity pattern consistent with the experimentally observed behavior of granule cells in the dentate gyrus.