Cross-correlation Histograms Research Articles

The role of the dorsolateral prefrontal cortex in control of skin sympathetic nerve activity in humans.

The dorsolateral prefrontal cortex (dlPFC) is primarily involved in higher order executive functions, with there being evidence of lateralization. Brain imaging studies have revealed its link to the generation of skin sympathetic nerve activity (SSNA), which is elevated in states of emotional arousal or anxiety. However, no studies have directly explored dlPFC influences on SSNA. Transcranial alternating current stimulation (-2 to 2mA, 0.08Hz, 100cycles) was applied between the left or right dlPFC and nasion via surface electrodes. Spontaneous bursts of SSNA were recorded from the common peroneal nerve via a tungsten microelectrode in 21 healthy participants. The modulation index was calculated for each stimulation paradigm by constructing cross-correlation histograms between SSNA and the sinusoidal stimulus. Stimulation of the dlPFC caused significant modulation of SSNA, but there was no significant difference in the median modulation index across sides. Stimulation also caused cyclic modulation of skin blood flow and sweat release. We have shown for the first time that stimulation of the dlPFC causes modulation of SSNA, also reflected in the effector-organ responses. This supports a role for the dlPFC in the control of SSNA, which likely contributes to the ability of emotions to bring about cutaneous vasoconstriction and sweat release.

Quantification of cardiac and respiratory modulation of axonal activity in the human vagus nerve.

We recently documented the first microelectrode recordings from the cervical vagus nerve in awake humans. Here we aimed to quantify cardiac and respiratory modulation of vagal activity to assess the feasibility of targeting axons supplying the heart and airways. Multi-unit activity was recorded from 43 sites in 19 healthy participants in the left (n=10) and right (n=9) vagus nerves with ECG, continuous non-invasive blood pressure and respiration. Cross-correlation histograms were constructed between axonal spikes and the R-waves or the peaks of inspiration. The latencies for the peak in cardiac modulation showed a bimodal distribution: while the majority of sites (72%) had peak latencies that preceded the R-wave by up to 550ms (mean±SD, -300±178ms), 12 sites had latencies of up to 250ms following the R-wave (64±87ms). Interestingly, the majority of sites with negative latencies (68%) were found in the left nerve whereas most of those with positive latencies (75%) were found in the right. Conversely, on average the peak of respiratory modulation straddled the peak of inspiration. Sites showing respiratory modulation were more prevalent and showed stronger modulation than those with cardiac modulation: calculated for sites with modulation indices ≥15%, the median cardiac and respiratory modulation indices were 23.4% (n=17) and 44.5% (n=35), respectively. We conclude that, despite the fact that much of the vagus nerve supplies the gut, cardiac and respiratory modulation of vagal nerve activity can be identified through invasive recordings in awake humans. KEY POINTS: Intraneural recordings from the cervical vagus were obtained in awake humans via tungsten microelectrodes inserted into the nerve through ultrasound guidance. Cross-correlation analysis of multi-unit vagal activity revealed cardiac and respiratory modulation, from which the amplitude and latency of the peaks could be computed. The magnitude of the cardiac modulation (23%) was weaker than that of the respiratory modulation (45%). The latencies for the peak in cardiac modulation showed a bimodal distribution: the majority of sites (72%) had peak latencies that preceded the R-wave, while the remainder had latencies that followed the R-wave. The majority of sites with negative latencies (68%) were found in the left nerve whereas most of those with positive latencies (75%) were found in the right. On average the peak of respiratory modulation coincided with the peak of inspiration.

Effects of Intra‐arterial Fentanyl and Codeine on Medullary Respiratory Network Organization

The actions of mu‐opioid agonists to depress breathing are currently controversial, encompassing several proposed mechanisms that are focused on preferential effects in specific locations in the brainstem. We hypothesized that opioids have multiple actions at the respiratory network scale which include loss of synchrony and/or network dynamics. Experiments were conducted in 4 anesthetized, spontaneously breathing and 11 decerebrated, artificially ventilated, paralyzed and vagal intact cats. In spontaneously breathing animals, EMGs were recorded from diaphragm, parasternal, abdominal and upper airway muscles. In paralyzed animals, neurograms were recorded from phrenic and abdominal nerves. Fentanyl or codeine were administered via the vertebral artery (i.a.; fentanyl, 1‐10 ng/kg, codeine 1‐3000 μg/kg) while simultaneously recording from multiple medullary neurons. Analyses included assessment of autocorrelation histograms (ACH), significant features in cross correlation histograms (CCHs), and discharge identity (phenotype of firing frequency of a neuron during the breathing cycle). Qualitatively similar opioid‐induced changes in neuron firing rates, ACHs, CCHs, and discharge identity were observed during either fentanyl or codeine dose responses. Some neurons lost or gained excitability during the dose responses. ACHs of some neurons exhibited changes in spiking periodicity. Features in CCHs changed during administration of opioids including loss of some central or offset peaks. Detectability index (a metric of the magnitude of significant functional interactions) in some neuron pairs increased during opioid administration. Further, the discharge identity of many neurons changed during the dose responses with most of these changes occurring in neurons with tonic discharge during breathing. The extent of these changes strongly suggest that opioids induce significant changes in network organization including reduced synchrony and altered discharge identity of network members. These changes can occur at low doses of opioids that do not profoundly alter the breathing pattern.

A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age.

The objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T clinical MRI scanner in 227 healthy adult volunteers (N = 227, aged 18–76 years old, male/female = 99/128). With the proposed QDA framework we derived two types of voxel-wise RFC metrics: the connectivity strength index and connectivity density index utilizing the convolutions of the cross-correlation histogram with different kernels. Furthermore, we assessed the negative and positive portions of these metrics separately. With the QDA framework we found age-related declines of RFC metrics in the superior and middle frontal gyri, posterior cingulate cortex (PCC), right insula and inferior parietal lobule of the default mode network (DMN), which resembles previously reported results using other types of RFC data processing methods. Importantly, our new findings complement previously undocumented results in the following aspects: (1) the PCC and right insula are anti-correlated and tend to manifest simultaneously declines of both the negative and positive connectivity strength with subjects’ age; (2) separate assessment of the negative and positive RFC metrics provides enhanced sensitivity to the aging effect; and (3) the sensorimotor network depicts enhanced negative connectivity strength with the adult age. The proposed QDA framework can produce threshold-free and voxel-wise RFC metrics from R-fMRI data. The detected adult age effect is largely consistent with previously reported studies using different R-fMRI analysis approaches. Moreover, the separate assessment of the negative and positive contributions to the RFC metrics can enhance the RFC sensitivity and clarify some of the mixed results in the literature regarding to the DMN and sensorimotor network involvement in adult aging.

Sex Differences in the Effect of Acute Intermittent Hypoxia on Respiratory‐Sympathetic Coupling in Humans

Background Sex-related differences in respiratory-sympathetic coupling have been described in preclinical models of intermittent hypoxia (IH) and have been implicated in the development of neurogenic hypertension. Based on sex disparities in the respiratory and blood pressure response to acute IH in humans as well as changes in respiratory-sympathetic coupling in clinical sleep apnea, we examined sex-related differences in respiratory modulation of muscle sympathetic nerve activity (MSNA) following acute IH in healthy humans. We hypothesized the magnitude of respiratory-sympathetic coupling would increase in both men and women following IH; however, the respiratory patterning of MSNA following IH would be sex-specific. Methods Heart rate, MSNA, and respiration were assessed in 21 healthy young men (30±1 yrs) and 10 healthy young women (28±1 yrs) during normoxic rest prior to and following IH. IH was achieved by alternating between a hypercapnic hypoxic (3% carbon dioxide, 5% oxygen) gas cylinder and room air (21% oxygen) to target 15 hypoxic events over 30-min. Respiratory modulation of MSNA was assessed by fitting polynomials to cross-correlation histograms constructed between sympathetic spikes and respiration. Results MSNA was elevated following IH in both men (34±2 to 41±3 bursts/100 heart beats) and women (30±4 to 35±5 bursts/100 heart beats) (p<0.01). When examining the normalized temporal profile of MSNA, both men and women exhibited changes in respiratory patterning of MSNA following IH; however, the pattern of MSNA differed by sex. Following IH, women exhibited more sympathetic activity during late expiration and less during post-inspiration (interaction of IH and time, p<0.01). In contrast, men exhibited greater sympathetic activity during post-inspiration following IH (interaction of IH and time, p<0.01). Conclusions Both men and women exhibit changes in respiratory patterning of MSNA following acute IH; however, this pattern differs by sex. These data support sex disparities in respiratory-sympathetic coupling and advance our understanding of sex-specific changes in sympathetic activation following IH which may have important implications for the development of neurogenic hypertension.

Secured image steganography based on Catalan transform

Transform domain steganography methods are always preferable than spatial domain methods to the research community due to following advantages: better feature identification, improved security and higher robustness. In this paper, an integer sequence named Catalan Transform (CT) has been exploited in the image steganography domain. At the outset, the cover image is decomposed into 2 × 2 non-overlapping blocks in row major order. Then, each such block i.e., 4-pixel group is converted into transform domain using CT. Secret bits are embedded into the transformed components in varying proportions which facilitates us to achieve a payload in the range of 1 to 4 bpp. Inverse Catalan Transform (ICT) is applied over transformed cum embedded quadruples to generate the stego-pixels in spatial domain. Successive embedding operation over an entire image ensures the formation of stego-image. Experimental results confirm that the Peak Signal to Noise Ratio (PSNR) values obtained by the proposed method are always above the acceptable level (i.e., 30 dB) and at the same time, it outperforms many state-of-the-art methods. Other metrics such as Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), Normalized Cross Correlation (NCC) and Global histograms with similarity measure have also been computed which prove the effectiveness of the proposed scheme. The robustness of the stego-images has further been tested using the StegExpose tool and it is found that the tool is unable to detect the presence of secret data. The code of this work is available at: https://github.com/Souradeep150/Catalan-based-Steganography .

Motoneurone synchronization for intercostal and abdominal muscles: interneurone influences in two different species

The contribution of branched-axon monosynaptic inputs in the generation of short-term synchronization of motoneurones remains uncertain. Here, synchronization was measured for intercostal and abdominal motoneurones supplying the lower thorax and upper abdomen, mostly showing expiratory discharges. Synchronization in the anaesthetized cat, where the motoneurones receive a strong direct descending drive, is compared with that in anaesthetized or decerebrate rats, where the direct descending drive is much weaker. In the cat, some examples could be explained by branched-axon monosynaptic inputs, but many others could not, by virtue of peaks in cross-correlation histograms whose widths (relatively wide) and timing indicated common inputs with more complex linkages, e.g., disynaptic excitatory. In contrast, in the rat, correlations for pairs of internal intercostal nerves were dominated by very narrow peaks, indicative of branched-axon monosynaptic inputs. However, the presence of activity in both inspiration and expiration in many of the nerves allowed additional synchronization measurements between internal and external intercostal nerves. Time courses of synchronization for these often consisted of combinations of peaks and troughs, which have never been previously described for motoneurone synchronization and which we interpret as indicating combinations of inputs, excitation of one group of motoneurones being common with either excitation or inhibition of the other. Significant species differences in the circuits controlling the motoneurones are indicated, but in both cases, the roles of spinal interneurones are emphasised. The results demonstrate the potential of motoneurone synchronization for investigating inhibition and have important general implications for the interpretation of neural connectivity measurements by cross-correlation.

Optical Stepped Thermography of Defects in Photovoltaic Panels

Defects in photovoltaic panels can reduce the effective working area, and decrease the performance of the photovoltaic panels. Therefore, it is significant to identify such defects and to feed the fault information up to the production chain. Active infrared thermographic non-destructive testing has the advantages of non-contact, fast speed and large imaging area, and has been widely used in the detection of defects in various materials. In this article, a stepped thermography of the defects, which result in degradation of energy conversion efficiency of cells in photovoltaic panels, was proposed. The front surface of the photovoltaic panel was optically stimulated by halogen lamps in step heating way, while an infrared camera was employed to monitor the temperature evolution of the front surface and to capture infrared image sequences. The thermal image sequences were processed using data processing algorithms, focusing on enhancing the defect signatures. The techniques of background subtraction, discrete Fourier transform, polynomial fitting, first-order derivative, cross correlation coefficient and histogram equalization were mainly used. Compared to the raw thermal images, the reconstructed images using suitable algorithms are more helpful to evaluate the defects. The results show that the optical stepped thermography combined with suitable post data processing is a fast and effective technique to identify the defects in photovoltaic panels.

MotoRneuron: an open-source R toolbox for time-domain motor unit analyses

Motor unit synchronization is the tendency of motor neurons and their associated muscle fibers to discharge near-simultaneously. It has been theorized as a control mechanism for force generation by common excitatory inputs to these motor neurons. Magnitude of synchronization is calculated from peaks in cross-correlation histograms between motor unit discharge trains. However, there are many different methods for detecting these peaks and even more indices for calculating synchronization from them. Methodology is diverse, typically laboratory-specific and requires expensive software, like Matlab or LabView. This lack of standardization makes it difficult to draw definitive conclusions about motor unit synchronization. A free, open-source toolbox, “motoRneuron”, for the R programming language, has been developed which contains functions for calculating time domain synchronization using different methods found in the literature. The objective of this paper is to detail the toolbox’s functionality and present a case study showing how the same synchronization index can differ when different methods are used to compute it. A pair of motor unit action potential trains were collected from the forearm during a isometric finger flexion task using fine wire electromyography. The motoRneuron package was used to analyze the discharge time of the motor units for time-domain synchronization. The primary function “mu_synch” automatically performed the cross-correlation analysis using three different peak detection methods, the cumulative sum method, the z-score method, and a subjective visual method. As function parameters defined by the user, only first order recurrence intervals were calculated and a 1 ms bin width was used to create the cross correlation histogram. Output from the function were six common synchronization indices, the common input strength (CIS), k′, k′ − 1, E, S, and Synch Index. In general, there was a high degree of synchronization between the two motor units. However, there was a varying degree of synchronization between methods. For example, the widely used CIS index, which represents a rate of synchronized discharges, shows a 45% difference between the visual and z-score methods. This singular example demonstrates how a lack of consensus in motor unit synchronization methodologies may lead to substantially differing results between studies. The motoRneuron toolbox provides researchers with a standard interface and software to examine time-domain motor unit synchronization.

Hold Your Methods! How Multineuronal Firing Ensembles Can Be Studied Using Classical Spike-Train Analysis Techniques.

Responses of neuronal populations play an important role in the encoding of stimulus related information. However, the inherent multidimensionality required to describe population activity has imposed significant challenges and has limited the applicability of classical spike train analysis techniques. Here, we show that these limitations can be overcome. We first quantify the collective activity of neurons as multidimensional vectors (patterns). Then we characterize the behavior of these patterns by applying classical spike train analysis techniques: peri-stimulus time histograms, tuning curves and auto- and cross-correlation histograms. We find that patterns can exhibit a broad spectrum of properties, some resembling and others substantially differing from those of their component neurons. We show that in some cases pattern behavior cannot be intuitively inferred from the activity of component neurons. Importantly, silent neurons play a critical role in shaping pattern expression. By correlating pattern timing with local-field potentials, we show that the method can reveal fine temporal coordination of cortical circuits at the mesoscale. Because of its simplicity and reliance on well understood classical analysis methods the proposed approach is valuable for the study of neuronal population dynamics.

Comparison of filter banks of DWT in recovery of image using one dimensional signal vector

Digital filter bank of DWT (discrete wavelet transform) provides the approximate and detail components of a signal, whereas the perfection of the filter bank depends on recovery of the signal. In this paper, we convert an image into a one dimensional signal vector then the perfection of the filter bank is observed on recovery of signal vector hence the image. Here orthogonal FIR (finite impulse response), FIR under window method, IIR (infinite impulse response) Butterworth, Chebyshev type-I, type-II and synchrosqueezed transform are compared in context of image recovery under statistical parameters: mean error, variance of error, difference of skewness and kurtosis, cross-correlation coefficient, PSNR (peak signal to noise ratio) and histogram. The orthogonal FIR combination gives the best results and synchrosqueezed transform is the worst case for reconstruction of image.

Total spiking probability edges: A cross-correlation based method for effective connectivity estimation of cortical spiking neurons

BackgroundConnectivity is a relevant parameter for the information flow within neuronal networks. Network connectivity can be reconstructed from recorded spike train data. Various methods have been developed to estimate connectivity from spike trains. New methodIn this work, a novel effective connectivity estimation algorithm called Total Spiking Probability Edges (TSPE) is proposed and evaluated. First, a cross-correlation between pairs of spike trains is calculated. Second, to distinguish between excitatory and inhibitory connections, edge filters are applied on the resulting cross-correlogram. ResultsTSPE was evaluated with large scale in silico networks and enables almost perfect reconstructions (true positive rate of approx. 99% at a false positive rate of 1% for low density random networks) depending on the network topology and the spike train duration. A distinction between excitatory and inhibitory connections was possible. TSPE is computational effective and takes less than 3 min on a high-performance computer to estimate the connectivity of an 1 h dataset of 1000 spike trains. Comparison of existing methodsTSPE was compared with connectivity estimation algorithms like Transfer Entropy based methods, Filtered and Normalized Cross-Correlation Histogram and Normalized Cross-Correlation. In all test cases, TSPE outperformed the compared methods in the connectivity reconstruction accuracy. ConclusionsThe results show that the accuracy of functional connectivity estimation of large scale neuronal networks has been enhanced by TSPE compared to state of the art methods. Furthermore, TSPE enables the classification of excitatory and inhibitory synaptic effects.

Cardiac modulation of alpha motoneuron discharges.

Recordings of alpha motoneuron discharges from branches of the intercostal and abdominal nerves in anesthetized cats were analyzed for modulation during the cardiac cycle. Cardiac modulation was assessed by the construction of cross-correlation histograms between the R-wave of the ECG and the largest amplitude efferent spikes. In all but two recordings (which were believed to have either no or few alpha spikes), the histograms showed relatively short duration peaks and/or troughs (widths at half amplitude 4-50 ms) at lags of 10-150 ms. These observations were deduced to result from activity in oligosynaptic pathways, probably from muscle spindle afferents, whose discharges are known to be synchronized to the cardiac pulse. The results suggest that onward transmission of the cardiac signal from thoracic muscle afferents (and possibly from other dynamically sensitive afferents) to other parts of the central nervous system is highly likely and that therefore these afferents could contribute to cardiac interoception. NEW & NOTEWORTHY It has been recognized since 1933 that muscle spindles respond to the cardiac pulse, but it is unknown whether this cardiac signal is transmitted to other levels in the nervous system. Here we show that a cardiac signal, likely arising from muscle spindles, is present in the efferent activities of thoracic and abdominal muscle nerves, suggesting probable onward transmission of this signal to higher levels and therefore that muscle spindles could contribute to cardiac interoception.

A multivariate extension of mutual information for growing neural networks

Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data derived from such recordings can be used to infer effects of compounds or disease states on a variety of important neural functions, including network synchrony. Historically, synchrony of networks in vitro has been assessed either by determination of correlation coefficients (e.g. Pearson’s correlation), by statistics estimated from cross-correlation histograms between pairs of active electrodes, and/or by pairwise mutual information and related measures. The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size. Theoretical simulations are designed to investigate NMI as a measure of complexity and synchrony in a developing network relative to several alternative approaches. The NMI approach is applied to these simulations and also to data collected during exposure of in vitro neural networks to neuroactive compounds during the first 12 days in vitro, and compared to other common measures, including correlation coefficients and mean firing rates of neurons. NMI is shown to be more sensitive to developmental effects than first order synchronous and nonsynchronous measures of network complexity. Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches.

Intermittent Hypoxia Enhances Connectivity between Cervical Spinal Interneurons

Intermittent hypoxia is a potent initiator of spinal plasticity and a promising rehabilitative modality to enhance respiratory and non‐respiratory motor function in certain cases of neurologic dysfunction. Current models of intermittent hypoxia‐induced spinal plasticity have focused exclusively on motoneurons, and nothing is known about how cervical spinal interneurons are impacted by intermittent hypoxia. Prior work has established that most cervical spinal interneurons alter discharge rates during acute hypoxia, and that some spinal interneurons are synaptically coupled with phrenic motoneurons. We hypothesize that acute intermittent hypoxia triggers “network level” spinal plasticity which manifests as an increase in the prevalence of temporally related discharge of spinal interneurons. To test this hypothesis, bilateral phrenic motor output was recorded in N=12 anesthetized and ventilated adult rats and a 16‐channel multi‐electrode array was used to record mid‐cervical neuron activity during and following three, 5‐min episodes of hypoxia (11% O2). To evaluate “functional connectivity” among spinal interneurons, cross‐correlation histograms were constructed for all possible pairs of simultaneously recorded neurons. A positive correlogram “peak” &gt; 3 stdev above the mean was taken to indicate an excitatory connection. The current analysis focused on post‐hypoxia discharge, and data were included for 319 neuronal pairs in which a correlogram peak was detected during any post‐hypoxia period. A correlogram peak was present in 24% of neuronal pairs during the pre‐hypoxia baseline. This value tended to increase during hypoxia (Hypoxia‐1: 34%; Hypoxia‐2: 30%; Hypoxia‐3: 34%), but this did not reach statistical significance (all P&gt;0.05 vs. baseline). In contrast, the number of excitatory connections, as reflected by positive correlogram peaks, were significantly increased following each bout of hypoxia (Hypoxia‐1: 60%; Hypoxia‐2: 53%; Hypoxia‐3: 50%) (all P&lt;0.05 vs. baseline). This is the first demonstration that intermittent hypoxia alters the connectivity of spinal networks and we therefore conclude that the spinal impact of intermittent hypoxia extends beyond phrenic motoneurons. These data support the hypothesis that neuroplasticity in spinal networks contributes to sustained changes in respiratory and/or autonomic output following intermittent hypoxia.Support or Funding InformationNIH: 1F32NS095620‐01 (KS); 1R01NS080180‐01A1 (DF); and T32‐ND043730 (MS). Department of Defense W81XWH‐14‐1‐0625 (PR).

Coupling multielectrode array recordings with silver labeling of recording sites to study cervical spinal network connectivity.

Midcervical spinal interneurons form a complex and diffuse network and may be involved in modulating phrenic motor output. The intent of the current work was to enable a better understanding of midcervical "network-level" connectivity by pairing the neurophysiological multielectrode array (MEA) data with histological verification of the recording locations. We first developed a method to deliver 100-nA currents to electroplate silver onto and subsequently deposit silver from electrode tips after obtaining midcervical (C3-C5) recordings using an MEA in anesthetized and ventilated adult rats. Spinal tissue was then fixed, harvested, and histologically processed to "develop" the deposited silver. Histological studies verified that the silver deposition method discretely labeled (50-μm resolution) spinal recording locations between laminae IV and X in cervical segments C3-C5. Using correlative techniques, we next tested the hypothesis that midcervical neuronal discharge patterns are temporally linked. Cross-correlation histograms produced few positive peaks (5.3%) in the range of 0-0.4 ms, but 21.4% of neuronal pairs had correlogram peaks with a lag of ≥0.6 ms. These results are consistent with synchronous discharge involving mono- and polysynaptic connections among midcervical neurons. We conclude that there is a high degree of synaptic connectivity in the midcervical spinal cord and that the silver-labeling method can reliably mark metal electrode recording sites and "map" interneuron populations, thereby providing a low-cost and effective tool for use in MEA experiments. We suggest that this method will be useful for further exploration of midcervical network connectivity.NEW & NOTEWORTHY We describe a method that reliably identifies the locations of multielectrode array (MEA) recording sites while preserving the surrounding tissue for immunohistochemistry. To our knowledge, this is the first cost-effective method to identify the anatomic locations of neuronal ensembles recorded with a MEA during acute preparations without the requirement of specialized array electrodes. In addition, evaluation of activity recorded from silver-labeled sites revealed a previously unappreciated degree of connectivity between midcervical interneurons.

Using Computational Neuroscience to Define Common Input to Spinal Motor Neurons.

Common input is a widely used concept in motor neurophysiology. It embodies the notion that inputs to individual spinal motor neurons (MNs) are not unique, but partly shared across MNs, and is considered the main explanation for synchronized activity of MNs (Bremner et al., 1991; Farmer et al., 1993; Boonstra and Breakspear, 2012; Farina and Negro, 2015). Motor-unit synchronization was first observed in the time domain using cross-correlation histograms from pairs of MNs (Sears and Stagg, 1976). This was later extended to the frequency domain by estimating coherence between spike trains to reveal the frequency content of common input (Farmer et al., 1993). In addition to measurements of individual MNs, coherence can also be estimated between the surface EMG of different muscles—referred to as intermuscular coherence—to assess common input shared across motor-unit pools (Boonstra and Breakspear, 2012). Common input is considered relevant for motor control as it may provide a mechanism to reduce the dimensionality of the control signal, thereby simplifying motor control (Farmer, 1998).

DCE-MRI and IVIM-MRI of rabbit Vx2 tumors treated with MR-HIFU-induced mild hyperthermia.

BackgroundThe purpose of this study is to investigate whether changes could be detected in dynamic contrast-enhanced (DCE) and intra-voxel incoherent motion (IVIM) MR parameters upon MR-guided high-intensity focused ultrasound (MR-HIFU)-induced hyperthermia in a rabbit Vx2 tumor model.MethodsFive Vx2 tumor-bearing New Zealand white rabbits were treated with hyperthermia using a clinical MR-HIFU system. Data were acquired before and after hyperthermia. For the DCE analysis, the extended Tofts model was used. For the IVIM analysis, a Bayesian approach was used. Maps were reconstructed of the DCE parameters (Ktrans, kep, and vp) and IVIM parameters (Dt, fp, and Dp). Individual parameter histograms and two-dimensional cross-correlation histograms were constructed to analyze changes in the parameters after hyperthermia. Changes in median values were tested for statistical significance with the Mann-Whitney U test.ResultsThe MR temperature measurements confirmed that mild hyperthermia (40 to 42 °C) was successfully achieved in all rabbits. One rabbit died during treatment and was excluded from the analysis. In the remaining four rabbits, an increase in Dt was observed. In three rabbits, an increase in Ktrans was observed, while in the other rabbits, all three DCE parameter values decreased. Mixed changes were seen for vp and fp.ConclusionsChanges in DCE and IVIM parameters were detected after hyperthermia and were variable between the rabbits. DCE- and IVIM-MRI may be promising tools to assess tumor responses to hyperthermia. Further research in a larger number of subjects is necessary in order to assess their value for treatment response monitoring.

Skin Sympathetic Nerve Activity is Modulated during Slow Sinusoidal Linear Displacements in Supine Humans.

Low-frequency sinusoidal linear acceleration (0.08 Hz, ±4 mG) modulates skin sympathetic nerve activity (SSNA) in seated subjects (head vertical), suggesting that activation of the utricle in the peripheral vestibular labyrinth modulates SSNA. The aim of the current study was to determine whether SSNA is also modulated by input from the saccule. Tungsten microelectrodes were inserted into the common peroneal nerve to record oligounitary SSNA in 8 subjects laying supine on a motorized platform with the head aligned with the longitudinal axis of the body. Slow sinusoidal (0.08 Hz, 100 cycles) linear acceleration-decelerations (peak ±4 mG) were applied rostrocaudally to predominately activate the saccules, or mediolaterally to predominately activate the utricles. Cross-correlation histograms were constructed between the negative-going sympathetic spikes and the positive peaks of the sinusoidal stimuli. Sinusoidal linear acceleration along the rostrocaudal axis or mediolateral axis both resulted in sinusoidal modulation of SSNA (Median, IQR 27.0, 22–33% and 24.8, 17–39%, respectively). This suggests that both otolith organs act on sympathetic outflow to skin and muscle in a similar manner during supine displacements.

Dynamics of the Assimilation of Rhythms of Electrocutaneous Stimulation by Sensorimotor Cortex Neurons in the Rabbit Brain

A dominant focus is a zone with stably increased neuron excitability in the cerebral cortex arising as a result of prolonged stimulation of some kind of effector (in our case the animal’s forepaw) or the direct cortical representation of this effector. Apart from increased excitability and stable excitation of the neurons within the zone, the dominant focus has two further very important properties – the ability of its neurons to sum excitation arriving in the cortex and propagating across cortical neural networks and inertia. This latter property is manifest as activation of the reaction in response to test stimuli (previously indifferent for the animal), leading to action by the effector even several days after cessation of the stimulation which formed the dominant. Stimulation of the paws in rabbits with rhythmic current impulses of threshold strength formed a rhythmic defensive dominant. The interaction (linkage) of sensorimotor cortex neuron activity in rabbits in the dominant focus was studied. The time sequences of the accumulation of intervals between linked spikes were analyzed as peaks on cross-correlation histograms (CCH). The frequencies of linked spikes or the intervals between them in the CCH peak during the 1-min analysis period were determined using “secondary” autocorrelation histograms (ACH). Further analysis was performed using selected peaks on secondary ACH, which dominated over the mean histogram level with significance p < 0.05. Formation of a rhythmic defensive dominant in the cerebral cortex was associated with the appearance of linked spikes not only at the stimulation rhythm (2 sec), but also at rhythms which were multiples of this (4, 6, and 8 sec). Neuron activity was recorded and analyzed after creation of a rhythmic dominant. At the beginning of each experiment (i.e., before presentation of test stimulation), linked spikes were dominated by the 2-sec rhythm. Repeated peaks on secondary ACH, providing evidence that linked activity was dominated by rhythms of 4, 6, and 8 sec, were absent or rare. Presentation of test stimuli showed a significant increase in the number of repeated peaks. It is suggested that subsequent exposure to test stimuli during the experiment enhanced the previously created latent focus of excitation, which became apparent as an increase in the complexity of the rhythm.