Correlations In Spontaneous Activity Research Articles

Fluctuation-dissipation relations in the imbalanced Wilson-Cowan model.

The relation between spontaneous and stimulated brain activity is a fundamental question in neuroscience which has received wide attention in experimental studies. Recently, it has been suggested that the evoked response to external stimuli can be predicted from temporal correlations of spontaneous activity. Previous theoretical results, confirmed by the comparison with magnetoencephalography data for human brains, were obtained for the Wilson-Cowan model in the condition of balance of excitation and inhibition, a signature of a healthy brain. Here we extend previous studies to imbalanced conditions by examining a region of parameter space around the balanced fixed point. Analytical results are compared to numerical simulations of Wilson-Cowan networks. We evidence that in imbalanced conditions the functional form of the time correlation and response functions can show several behaviors, exhibiting also an oscillating regime caused by the emergence of complex eigenvalues. The analytical predictions are fully in agreement with numerical simulations, validating the role of cross-correlations in the response function. Furthermore, we identify the leading role of inhibitory neurons in controlling the overall activity of the system, tuning the level of excitability and imbalance.

Microstimulation of sensory cortex engages natural sensory representations

Cortical activity patterns occupy a small subset of possible network states. If this is due to intrinsic network properties, microstimulation of sensory cortex should evoke activity patterns resembling those observed during natural sensory input. Here, we use optical microstimulation of virally transfected layer 2/3 pyramidal neurons in the mouse primary vibrissal somatosensory cortex to compare artificially evoked activity with natural activity evoked by whisker touch and movement ("whisking"). We find that photostimulation engages touch- but not whisking-responsive neurons more than expected by chance. Neurons that respond to photostimulation and touch or to touch alone exhibit higher spontaneous pairwise correlations than purely photoresponsive neurons. Exposure to several days of simultaneous touch and optogenetic stimulation raises both overlap and spontaneous activity correlations among touch and photoresponsive neurons. We thus find that cortical microstimulation engages existing cortical representations and that repeated co-presentationof natural and artificial stimulation enhances this effect.

Network instability dynamics drive a transient bursting period in the developing hippocampus in vivo.

Spontaneous correlated activity is a universal hallmark of immature neural circuits. However, the cellular dynamics and intrinsic mechanisms underlying network burstiness in the intact developing brain are largely unknown. Here, we use two-photon Ca2+ imaging to comprehensively map the developmental trajectories of spontaneous network activity in the hippocampal area CA1 of mice in vivo. We unexpectedly find that network burstiness peaks after the developmental emergence of effective synaptic inhibition in the second postnatal week. We demonstrate that the enhanced network burstiness reflects an increased functional coupling of individual neurons to local population activity. However, pairwise neuronal correlations are low, and network bursts (NBs) recruit CA1 pyramidal cells in a virtually random manner. Using a dynamic systems modeling approach, we reconcile these experimental findings and identify network bi-stability as a potential regime underlying network burstiness at this age. Our analyses reveal an important role of synaptic input characteristics and network instability dynamics for NB generation. Collectively, our data suggest a mechanism, whereby developing CA1 performs extensive input-discrimination learning prior to the onset of environmental exploration.

NMDA Receptor Enhances Correlation of Spontaneous Activity in Neonatal Barrel Cortex.

Correlated spontaneous activity plays critical role in the organization of neocortical circuits during development. However, cortical mechanisms regulating activity correlation are still elusive. In this study, using two-photon calcium imaging of the barrel cortex layer 4 (L4) in living neonatal mice, we found that NMDA receptors (NMDARs) in L4 neurons are important for enhancement of spontaneous activity correlation. Disruption of GluN1 (Grin1), an obligatory NMDAR subunit, in a sparse population of L4 neurons reduced activity correlation between GluN1 knock-out (GluN1KO) neuron pairs within a barrel. This reduction in activity correlation was even detected in L4 neuron pairs in neighboring barrels and most evident when either or both of neurons are located on the barrel edge. Our results provide evidence for the involvement of L4 neuron NMDARs in spatial organization of the spontaneous firing activity of L4 neurons in the neonatal barrel cortex.SIGNIFICANCE STATEMENT Precise wiring of the thalamocortical circuits is necessary for proper sensory information processing, and thalamus-derived correlated spontaneous activity is important for thalamocortical circuit formation. The molecular mechanisms involved in the correlated activity transfer from the thalamus to the neocortex are largely unknown. In vivo two-photon calcium imaging of the neonatal barrel cortex revealed that correlated spontaneous activity between layer four neurons is reduced by mosaic knock-out (KO) of the NMDA receptor (NMDAR) obligatory subunit GluN1. Our results suggest that the function of NMDARs in layer four neurons is necessary for the communication between presynaptic and postsynaptic partners during thalamocortical circuit formation.

Purinergic Signaling Controls Spontaneous Activity in the Auditory System throughout Early Development.

Spontaneous bursts of electrical activity in the developing auditory system arise within the cochlea before hearing onset and propagate through future sound-processing circuits of the brain to promote maturation of auditory neurons. Studies in isolated cochleae revealed that this intrinsically generated activity is initiated by ATP release from inner supporting cells (ISCs), resulting in activation of purinergic autoreceptors, K+ efflux, and subsequent depolarization of inner hair cells. However, it is unknown when this activity emerges or whether different mechanisms induce activity during distinct stages of development. Here we show that spontaneous electrical activity in mouse cochlea from both sexes emerges within ISCs during the late embryonic period, preceding the onset of spontaneous correlated activity in inner hair cells and spiral ganglion neurons, which begins at birth and follows a base to apex developmental gradient. At all developmental ages, pharmacological inhibition of P2Y1 purinergic receptors dramatically reduced spontaneous activity in these three cell types. Moreover, in vivo imaging within the inferior colliculus revealed that auditory neurons within future isofrequency zones exhibit coordinated neural activity at birth. The frequency of these discrete bursts increased progressively during the postnatal prehearing period yet remained dependent on P2RY1. Analysis of mice with disrupted cholinergic signaling in the cochlea indicate that this efferent input modulates, rather than initiates, spontaneous activity before hearing onset. Thus, the auditory system uses a consistent mechanism involving ATP release from ISCs and activation of P2RY1 autoreceptors to elicit coordinated excitation of neurons that will process similar frequencies of sound.SIGNIFICANCE STATEMENT In developing sensory systems, groups of neurons that will process information from similar sensory space exhibit highly correlated electrical activity that is critical for proper maturation and circuit refinement. Defining the period when this activity is present, the mechanisms responsible and the features of this activity are crucial for understanding how spontaneous activity influences circuit development. We show that, from birth to hearing onset, the auditory system relies on a consistent mechanism to elicit correlate firing of neurons that will process similar frequencies of sound. Targeted disruption of this activity will increase our understanding of how these early circuits mature and may provide insight into processes responsible for developmental disorders of the auditory system.

Schrödinger filtering: a precise EEG despiking technique for EEG-fMRI gradient artifact

In EEG data acquired in the presence of fMRI, gradient-related spike artifacts contaminate the signal following the common preprocessing step of average artifact subtraction. Spike artifacts compromise EEG data quality since they overlap with the EEG signal in frequency, thereby confounding frequency-based inferences on activity. As well, spike artifacts can inflate or deflate correlations among time series, thereby confounding inferences on functional connectivity.We present Schrödinger filtering, which uses the Schrödinger equation to decompose the spike-containing input. The basis functions of the decomposition are localized and pulse-shaped, and selectively capture the various input peaks, with the spike components clustered at the beginning of the spectrum. Schrödinger filtering automatically subtracts the spike components from the data.On real and simulated data, we show that Schrödinger filtering (1) simultaneously accomplishes high spike removal and high signal preservation without affecting evoked activity, and (2) reduces spurious pairwise correlations in spontaneous activity. In these regards, Schrödinger filtering was significantly better than three other despiking techniques: median filtering, amplitude thresholding, and wavelet denoising.These results encourage the use of Schrödinger filtering in future EEG-fMRI pipelines, as well as in other spike-related applications (e.g., fMRI motion artifact removal or action potential extraction).

Predicting brain evoked response to external stimuli from temporal correlations of spontaneous activity

The relation between spontaneous and stimulated global brain activity is a fundamental problem in the understanding of brain functions. This question is investigated both theoretically and experimentally within the context of nonequilibrium fluctuation-dissipation relations. We consider the stochastic coarse-grained Wilson-Cowan model in the linear noise approximation and compare analytical results to experimental data from magnetoencephalography (MEG) of human brain. The short time behavior of the autocorrelation function for spontaneous activity is characterized by a double-exponential decay, with two characteristic times, differing by two orders of magnitude. Conversely, the response function exhibits a single exponential decay in agreement with experimental data for evoked activity under visual stimulation. Results suggest that the brain response to weak external stimuli can be predicted from the observation of spontaneous activity and pave the way to controlled experiments on the brain response under different external perturbations.

Correlation of Spontaneous Activity on Needle Electromyography with Pathological Changes on Muscle Biopsies (2535)

Correlation of Spontaneous Activity on Needle Electromyography with Pathological Changes on Muscle Biopsies (2535)

Slow-Wave Activity in the S1HL Cortex Is Contributed by Different Layer-Specific Field Potential Sources during Development.

Spontaneous correlated activity in cortical columns is critical for postnatal circuit refinement. We used spatial discrimination techniques to explore the late maturation of synaptic pathways through the laminar distribution of the field potential (FP) generators underlying spontaneous and evoked activities of the S1HL cortex in juvenile (P14–P16) and adult anesthetized rats. Juveniles exhibit an intermittent FP pattern resembling Up/Down states in adults, but with much reduced power and different laminar distribution. Whereas FPs in active periods are dominated by a layer VI generator in juveniles, in adults a developing multipart generator takes over, displaying current sinks in middle layers (III–V). The blockade of excitatory transmission in upper and middle layers of adults recovered the juvenile-like FP profiles. In addition to the layer VI generator, a gamma-specific generator in supragranular layers was the same in both age groups. While searching for dynamical coupling among generators in juveniles we found significant cross-correlation in ∼one-half of the tested pairs, whereas excessive coherence hindered their efficient separation in adults. Also, potentials evoked by tactile and electrical stimuli showed different short-latency dipoles between the two age groups, and the juveniles lacked the characteristic long latency UP state currents in middle layers. In addition, the mean firing rate of neurons was lower in juveniles. Thus, cortical FPs originate from different intra-columnar segments as they become active postnatally. We suggest that although some cortical segments are active early postnatally, a functional sensory-motor control relies on a delayed maturation and network integration of synaptic connections in middle layers.SIGNIFICANCE STATEMENT Early postnatal activity in the rodent cortex is mostly endogenous, whereas it becomes driven by peripheral input at later stages. The precise schedule for the maturation of synaptic pathways is largely unknown. We explored this in the somatosensory hindlimb cortex at an age when animals begin to use their limbs by uncovering the laminar distribution of the field potential generators underlying the dominant delta waves in juveniles and adults. Our results suggest that field potentials are mostly generated by a pathway in deep layers, whereas other pathways mature later in middle layers and take over in adults. We suggest that a functional sensory-motor control relies on a delayed maturation and network integration of synaptic connections in middle layers.

Spontaneous cognitive processes and the behavioral validation of time-varying brain connectivity.

In cognitive neuroscience, focus is commonly placed on associating brain function with changes in objectively measured external stimuli or with actively generated cognitive processes. In everyday life, however, many forms of cognitive processes are initiated spontaneously, without an individual’s active effort and without explicit manipulation of behavioral state. Recently, there has been increased emphasis, especially in functional neuroimaging research, on spontaneous correlated activity among spatially segregated brain regions (intrinsic functional connectivity) and, more specifically, on intraindividual fluctuations of such correlated activity on various time scales (time-varying functional connectivity). In this Perspective, we propose that certain subtypes of spontaneous cognitive processes are detectable in time-varying functional connectivity measurements. We define these subtypes of spontaneous cognitive processes and review evidence of their representations in time-varying functional connectivity from studies of attentional fluctuations, memory reactivation, and effects of baseline states on subsequent perception. Moreover, we describe how these studies are critical to validating the use of neuroimaging tools (e.g., fMRI) for assessing ongoing brain network dynamics. We conclude that continued investigation of the behavioral relevance of time-varying functional connectivity will be beneficial both in the development of comprehensive neural models of cognition, and in informing on best practices for studying brain network dynamics.

Super-wide-field two-photon imaging with a micro-optical device moving in post-objective space

Wide-field imaging of neural activity at a cellular resolution is a current challenge in neuroscience. To address this issue, wide-field two-photon microscopy has been developed; however, the field size is limited by the objective size. Here, we develop a micro-opto-mechanical device that rotates within the post-objective space between the objective and brain tissue. Two-photon microscopy with this device enables sub-second sequential calcium imaging of left and right mouse sensory forelimb areas 6 mm apart. When imaging the rostral and caudal motor forelimb areas (RFA and CFA) 2 mm apart, we found high pairwise correlations in spontaneous activity between RFA and CFA neurons and between an RFA neuron and its putative axons in CFA. While mice performed a sound-triggered forelimb-movement task, the population activity between RFA and CFA covaried across trials, although the field-averaged activity was similar across trials. The micro-opto-mechanical device in the post-objective space provides a novel and flexible design to clarify the correlation structure between distant brain areas at subcellular and population levels.

Functional Interactions between Newborn and Mature Neurons Leading to Integration into Established Neuronal Circuits

SummaryFrom development up to adulthood, the vertebrate brain is continuously supplied with newborn neurons that integrate into established mature circuits. However, how this process is coordinated during development remains unclear. Using two-photon imaging, GCaMP5 transgenic zebrafish larvae, and sparse electroporation in the larva’s optic tectum, we monitored spontaneous and induced activity of large neuronal populations containing newborn and functionally mature neurons. We observed that the maturation of newborn neurons is a 4-day process. Initially, newborn neurons showed undeveloped dendritic arbors, no neurotransmitter identity, and were unresponsive to visual stimulation, although they displayed spontaneous calcium transients. Later on, newborn-labeled neurons began to respond to visual stimuli but in a very variable manner. At the end of the maturation period, newborn-labeled neurons exhibited visual tuning curves (spatial receptive fields and direction selectivity) and spontaneous correlated activity with neighboring functionally mature neurons. At this developmental stage, newborn-labeled neurons presented complex dendritic arbors and neurotransmitter identity (excitatory or inhibitory). Removal of retinal inputs significantly perturbed the integration of newborn neurons into the functionally mature tectal network. Our results provide a comprehensive description of the maturation of newborn neurons during development and shed light on potential mechanisms underlying their integration into a functionally mature neuronal circuit.

Fine-scale structure in higher brain areas.

Neuroscience The prefrontal cortex of the brain is involved in higher-order cognitive processes, including attention, decision-making, and goal-directed action. At present, we do not know how abstract context is represented in the prefrontal cortex, whether there are subregions, and, if so, how they might be organized. Waskom and Wagner used high-resolution brain scanning while subjects performed tasks that demanded goal-directed behavior. Multivariate signal–decoding techniques and examination of spontaneous activity correlations demonstrated the existence of stable networks of subregions within this brain area. Abstract cognitive representations thus emerge from an intrinsic functional organization in the human prefrontal cortex. Proc. Natl. Acad. Sci. U.S.A. 114 , 230 (2017).

Brain connectivity and neurological disorders after stroke.

An important challenge in neurology is identifying the neural mechanisms underlying behavioral deficits after brain injury. Here, we review recent advances in understanding the effects of focal brain lesions on brain networks and behavior. Neuroimaging studies indicate that the human brain is organized in large-scale resting state networks (RSNs) defined via functional connectivity, that is the temporal correlation of spontaneous activity between different areas. Prior studies showed that focal brain lesion induced behaviorally relevant changes of functional connectivity beyond the site of damage. Recent work indicates that across domains, functional connectivity changes largely conform to two patterns: a reduction in interhemispheric functional connectivity and an increase in intrahemispheric functional connectivity between networks that are normally anticorrelated, for example dorsal attention and default networks. Abnormal functional connectivity can exhibit a high degree of behavioral specificity such that deficits in a given behavioral domain are selectively related to functional connectivity of the corresponding RSN, but some functional connectivity changes allow prediction across domains. Finally, as behavioral recovery proceeds, the prestroke pattern of functional connectivity is restored. Investigating changes in RSNs may shed light on the neural mechanisms underlying brain dysfunction after stroke. Therefore, resting state functional connectivity may represent an important tool for clinical diagnosis, tracking recovery and rehabilitation.

Is There a Nonadditive Interaction Between Spontaneous and Evoked Activity? Phase-Dependence and Its Relation to the Temporal Structure of Scale-Free Brain Activity.

The aim of our study was to use functional magnetic resonance imaging to investigate how spontaneous activity interacts with evoked activity, as well as how the temporal structure of spontaneous activity, that is, long-range temporal correlations, relate to this interaction. Using an extremely sparse event-related design (intertrial intervals: 52-60 s), a novel blood oxygen level-dependent signal correction approach (accounting for spontaneous fluctuations using pseudotrials) and phase analysis, we provided direct evidence for a nonadditive interaction between spontaneous and evoked activity. We demonstrated the discrepancy between the present and previous observations on why a linear superposition between spontaneous and evoked activity can be seen by using co-occurring signals from homologous brain regions. Importantly, we further demonstrated that the nonadditive interaction can be characterized by phase-dependent effects of spontaneous activity, which is closely related to the degree of long-range temporal correlations in spontaneous activity as indexed by both power-law exponent and phase-amplitude coupling. Our findings not only contribute to the understanding of spontaneous brain activity and its scale-free properties, but also bear important implications for our understanding of neural activity in general.

Effects of isoflurane anesthesia on ensemble patterns of Ca2+ activity in mouse v1: reduced direction selectivity independent of increased correlations in cellular activity.

Anesthesia affects brain activity at the molecular, neuronal and network level, but it is not well-understood how tuning properties of sensory neurons and network connectivity change under its influence. Using in vivo two-photon calcium imaging we matched neuron identity across episodes of wakefulness and anesthesia in the same mouse and recorded spontaneous and visually evoked activity patterns of neuronal ensembles in these two states. Correlations in spontaneous patterns of calcium activity between pairs of neurons were increased under anesthesia. While orientation selectivity remained unaffected by anesthesia, this treatment reduced direction selectivity, which was attributable to an increased response to the null-direction. As compared to anesthesia, populations of V1 neurons coded more mutual information on opposite stimulus directions during wakefulness, whereas information on stimulus orientation differences was lower. Increases in correlations of calcium activity during visual stimulation were correlated with poorer population coding, which raised the hypothesis that the anesthesia-induced increase in correlations may be causal to degrading directional coding. Visual stimulation under anesthesia, however, decorrelated ongoing activity patterns to a level comparable to wakefulness. Because visual stimulation thus appears to ‘break’ the strength of pairwise correlations normally found in spontaneous activity under anesthesia, the changes in correlational structure cannot explain the awake-anesthesia difference in direction coding. The population-wide decrease in coding for stimulus direction thus occurs independently of anesthesia-induced increments in correlations of spontaneous activity.

CA1 cell activity sequences emerge after reorganization of network correlation structure during associative learning

Animals can learn causal relationships between pairs of stimuli separated in time and this ability depends on the hippocampus. Such learning is believed to emerge from alterations in network connectivity, but large-scale connectivity is difficult to measure directly, especially during learning. Here, we show that area CA1 cells converge to time-locked firing sequences that bridge the two stimuli paired during training, and this phenomenon is coupled to a reorganization of network correlations. Using two-photon calcium imaging of mouse hippocampal neurons we find that co-time-tuned neurons exhibit enhanced spontaneous activity correlations that increase just prior to learning. While time-tuned cells are not spatially organized, spontaneously correlated cells do fall into distinct spatial clusters that change as a result of learning. We propose that the spatial re-organization of correlation clusters reflects global network connectivity changes that are responsible for the emergence of the sequentially-timed activity of cell-groups underlying the learned behavior. DOI: http://dx.doi.org/10.7554/eLife.01982.001.

Continuous theta burst transcranial magnetic stimulation reduces resting state connectivity between visual areas

Continuous theta burst stimulation (cTBS) is a technique that allows for altering of brain activity. Research to date has focused on the effect of cTBS on the target area, but less is known about its effects on the resting state functional connectivity between different brain regions. We investigated this issue by applying cTBS to the occipital cortex and probing its influence in retinotopically defined regions in early visual cortex using functional MRI. We found that occipital cTBS reliably decreased the resting state functional connectivity (i.e., the correlation of spontaneous activity) between regions of the early visual cortex. In the context of a perceptual task, such an effect could mean that cTBS affects the strength of the perceptual signal, its variability, or both. We investigated this issue in a second experiment in which subjects performed a perceptual discrimination task and indicated their level of certainty on each trial. The results showed that occipital cTBS decreased both subjects' accuracy and confidence. Signal detection modeling suggested that these impairments resulted primarily from a decreased strength of the perceptual signal, with a nonsignificant trend of a decrease in signal variability. We discuss the implications of these experiments for understanding the mechanisms by which cTBS influences brain activity and perceptual processes.

Increased neural correlations in primate auditory cortex during slow-wave sleep.

During sleep, changes in brain rhythms and neuromodulator levels in cortex modify the properties of individual neurons and the network as a whole. In principle, network-level interactions during sleep can be studied by observing covariation in spontaneous activity between neurons. Spontaneous activity, however, reflects only a portion of the effective functional connectivity that is activated by external and internal inputs (e.g., sensory stimulation, motor behavior, and mental activity), and it has been shown that neural responses are less correlated during external sensory stimulation than during spontaneous activity. Here, we took advantage of the unique property that the auditory cortex continues to respond to sounds during sleep and used external acoustic stimuli to activate cortical networks for studying neural interactions during sleep. We found that during slow-wave sleep (SWS), local (neuron-neuron) correlations are not reduced by acoustic stimulation remaining higher than in wakefulness and rapid eye movement sleep and remaining similar to spontaneous activity correlations. This high level of correlations during SWS complements previous work finding elevated global (local field potential-local field potential) correlations during sleep. Contrary to the prediction that slow oscillations in SWS would increase neural correlations during spontaneous activity, we found little change in neural correlations outside of periods of acoustic stimulation. Rather, these findings suggest that functional connections recruited in sound processing are modified during SWS and that slow rhythms, which in general are suppressed by sensory stimulation, are not the sole mechanism leading to elevated network correlations during sleep.

A NIRS–fMRI study of resting state network

Resting state functional connectivity, which is defined as temporal correlation of spontaneous activity between diverse brain regions, has been reported to form resting state networks (RSNs), consisting of a specific set of brain regions, based on functional magnetic resonance imaging (fMRI). Recently, studies using near-infrared spectroscopy (NIRS) reported that NIRS signals also show temporal correlation between different brain regions. The local relationship between NIRS and fMRI signals has been examined by simultaneously recording these signals when participants perform tasks or respond to stimuli. However, the NIRS-fMRI signal relationship during the resting state has been reported only between NIRS signals obtained within limited regions and whole brain fMRI signals. Therefore, it remains unclear whether NIRS signals obtained at diverse regions correlate with regional fMRI signals close to the NIRS measurement channels, especially in relation to the RSNs. In this study, we tested whether the signals measured by these different modalities during the resting state have the consistent characteristics of the RSNs. Specifically, NIRS signals during the resting state were acquired over the frontal, temporal, and occipital cortices while whole brain fMRI data was simultaneously recorded. First, by projecting the NIRS channel positions over the cerebral cortical surface, we identified the most likely anatomical locations of all NIRS channels used in the study. Next, to investigate the regional signal relationship between NIRS and fMRI, we calculated the cross-correlation between NIRS signals and fMRI signals in the brain regions adjacent to each NIRS channel. For each NIRS channel, we observed the local maxima of correlation coefficients between NIRS and fMRI signals within a radius of 2 voxels from the projection point. Furthermore, we also found that highly correlated voxels with the NIRS signal were mainly localized within brain tissues for all NIRS channels, with the exception of 2 frontal channels. Finally, by calculating the correlation between NIRS signals at a channel and whole brain fMRI signals, we observed that NIRS signals correlate with fMRI signals not only within brain regions adjacent to NIRS channels but also within distant brain regions constituting RSNs, such as the dorsal attention, fronto-parietal control, and default mode networks. These results support the idea that NIRS signals obtained at several cortical regions during the resting state mainly reflect regional spontaneous hemodynamic fluctuations that originate from spontaneous cortical activity, and include information that characterizes the RSNs. Because NIRS is relatively easy to use and a less physically demanding neuroimaging technique, our findings should facilitate a broad application of this technique to examine RSNs, especially for clinical populations and conditions unsuitable for fMRI.