A sensorimotor role for traveling waves in primate visual cortex

waveCSD: A method for estimating transmembrane currents originated from propagating neuronal activity in the neocortex: Application to study cortical spreading depression

BACKGROUND

Recent years have witnessed an upsurge in the development of methods for estimating current source densities (CSDs) in the neocortical tissue from their recorded local field potential (LFP) reflections using microelectrode arrays. Among these, methods utilizing linear arrays work under the assumption that CSDs vary as a function of cortical depth; whereas they are constant in the tangential direction, infinitely or in a confined cylinder. This assumption is violated in the analysis of neuronal activity propagating along the neocortical sheet, e.g. propagation of alpha waves or cortical spreading depression.

NEW METHOD

Here, we developed a novel mathematical method (waveCSD) for CSD analysis of LFPs associated with a planar wave of neocortical neuronal activity propagating at a constant velocity towards a linear probe.

RESULTS

Results show that the algorithm is robust to the presence of noise in LFP data and uncertainties in knowledge of propagation velocity. Also, results show high level of accuracy of the method in a wide range of electrode resolutions. Using in vivo experimental recordings from the rat neocortex, we employed waveCSD to characterize transmembrane currents associated with cortical spreading depressions.

COMPARISON WITH EXISTING METHOD(S)

Simulation results indicate that waveCSD has a significantly higher reconstruction accuracy compared to the widely-used inverse CSD method (iCSD), and the regularized kernel CSD method (kCSD), in the analysis of CSDs originating from propagating neuronal activity.

CONCLUSIONS

The waveCSD method provides a theoretical platform for estimation of transmembrane currents from their LFPs in experimental paradigms involving wave propagation.

Theta and Alpha Oscillations Are Traveling Waves in the Human Neocortex

Human cognition requires the coordination of neural activity across widespread brain networks. Here, we describe a new mechanism for large-scale coordination in the human brain: traveling waves of theta and alpha oscillations. Examining direct brain recordings from neurosurgical patients performing a memory task, we found contiguous clusters of cortex in individual patients with oscillations at specific frequencies within 2 to 15 Hz. These oscillatory clusters displayed spatial phase gradients, indicating that they formed traveling waves that propagated at ∼0.25-0.75 m/s. Traveling waves were relevant behaviorally because their propagation correlated with task events and was more consistent when subjects performed the task well. Human traveling theta and alpha waves can be modeled by a network of coupled oscillators because the direction of wave propagation correlated with the spatial orientation of local frequency gradients. Our findings suggest that oscillations support brain connectivity by organizing neural processes across space and time.

Classification of Spatiotemporal Neural Activity Patterns in Brain Imaging Data

Various patterns of neural activity are observed in dynamic cortical imaging data. Such patterns may reflect how neurons communicate using the underlying circuitry to perform appropriate functions; thus it is crucial to investigate the spatiotemporal characteristics of the observed neural activity patterns. In general, however, neural activities are highly nonlinear and complex, so it is a demanding job to analyze them quantitatively or to classify the patterns of observed activities in various types of imaging data. Here, we present our implementation of a novel method that successfully addresses the above issues for precise comparison and classification of neural activity patterns. Based on two-dimensional representations of the geometric structure and temporal evolution of activity patterns, our method successfully classified a number of computer-generated sample patterns created from combinations of various spatial and temporal patterns. In addition, we validated our method with voltage-sensitive dye imaging data of Alzheimer's disease (AD) model mice. Our analysis algorithm successfully distinguished the activity data of AD mice from that of wild type with significantly higher performance than previously suggested methods. Our result provides a pragmatic solution for precise analysis of spatiotemporal patterns of neural imaging data.

Identification of cytokine-specific sensory neural signals by decoding murine vagus nerve activity

The nervous system maintains physiological homeostasis through reflex pathways that modulate organ function. This process begins when changes in the internal milieu (e.g., blood pressure, temperature, or pH) activate visceral sensory neurons that transmit action potentials along the vagus nerve to the brainstem. IL-1β and TNF, inflammatory cytokines produced by immune cells during infection and injury, and other inflammatory mediators have been implicated in activating sensory action potentials in the vagus nerve. However, it remains unclear whether neural responses encode cytokine-specific information. Here we develop methods to isolate and decode specific neural signals to discriminate between two different cytokines. Nerve impulses recorded from the vagus nerve of mice exposed to IL-1β and TNF were sorted into groups based on their shape and amplitude, and their respective firing rates were computed. This revealed sensory neural groups responding specifically to TNF and IL-1β in a dose-dependent manner. These cytokine-mediated responses were subsequently decoded using a Naive Bayes algorithm that discriminated between no exposure and exposures to IL-1β and TNF (mean successful identification rate 82.9 ± 17.8%, chance level 33%). Recordings obtained in IL-1 receptor-KO mice were devoid of IL-1β-related signals but retained their responses to TNF. Genetic ablation of TRPV1 neurons attenuated the vagus neural signals mediated by IL-1β, and distal lidocaine nerve block attenuated all vagus neural signals recorded. The results obtained in this study using the methodological framework suggest that cytokine-specific information is present in sensory neural signals within the vagus nerve.

LFP beta amplitude is linked to mesoscopic spatio-temporal phase patterns

Beta oscillations observed in motor cortical local field potentials (LFPs) recorded on separate electrodes of a multi-electrode array have been shown to exhibit non-zero phase shifts that organize into planar waves. Here, we generalize this concept to additional classes of salient patterns that fully describe the spatial organization of beta oscillations. During a delayed reach-to-grasp task we distinguish planar, synchronized, random, circular, and radial phase patterns in monkey primary motor and dorsal premotor cortices. We observe that patterns correlate with the beta amplitude (envelope): Coherent planar/radial wave propagation accelerates with growing amplitude, and synchronized patterns are observed at largest amplitudes. In contrast, incoherent random or circular patterns are observed almost exclusively when beta is strongly attenuated. The occurrence probability of a particular pattern modulates with behavioral epochs in the same way as beta amplitude: Coherent patterns are more present during movement preparation where amplitudes are large, while incoherent phase patterns are dominant during movement execution where amplitudes are small. Thus, we uncover a trigonal link between the spatial arrangement of beta phases, beta amplitude, and behavior. Together with previous findings, we discuss predictions on the spatio-temporal organization of precisely coordinated spiking on the mesoscopic scale as a function of beta power.

Cortical travelling waves: mechanisms and computational principles

Multichannel recording technologies have revealed travelling waves of neural activity in multiple sensory, motor and cognitive systems. These waves can be spontaneously generated by recurrent circuits or evoked by external stimuli. They travel along brain networks at multiple scales, transiently modulating spiking and excitability as they pass. Here, we review recent experimental findings that have found evidence for travelling waves at single-area (mesoscopic) and whole-brain (macroscopic) scales. We place these findings in the context of the current theoretical understanding of wave generation and propagation in recurrent networks. During the large low-frequency rhythms of sleep or the relatively desynchronized state of the awake cortex, travelling waves may serve a variety of functions, from long-term memory consolidation to processing of dynamic visual stimuli. We explore new avenues for experimental and computational understanding of the role of spatiotemporal activity patterns in the cortex.

Developing a Nonstationary Computational Framework With Application to Modeling Dynamic Modulations in Neural Spiking Responses

OBJECTIVE

This paper aims to develop a computational model that incorporates the functional effects of modulatory covariates (such as context, task, or behavior), which dynamically alter the relationship between the stimulus and the neural response.

METHODS

We develop a general computational approach along with an efficient estimation procedure in the widely used generalized linear model (GLM) framework to characterize such nonstationary dynamics in spiking response and spatiotemporal characteristics of a neuron at the level of individual trials. The model employs a set of modulatory components, which nonlinearly interact with other stimulus-related signals to reproduce such nonstationary effects.

RESULTS

The model is tested for its ability to predict the responses of neurons in the middle temporal cortex of macaque monkeys during an eye movement task. The fitted model proves successful in capturing the fast temporal modulations in the response, reproducing the spike response temporal statistics, and accurately accounting for the neurons' dynamic spatiotemporal sensitivities, during eye movements.

CONCLUSION

The nonstationary GLM framework developed in this study can be used in cases where a time-varying behavioral or cognitive component makes GLM-based models insufficient to describe the dependencies of neural responses on the stimulus-related covariates.

SIGNIFICANCE

In addition to being quite powerful in encoding time-varying response modulations, this general framework also enables a readout of the neural code while dissociating the influence of other nonstimulus covariates. This framework will advance our ability to understand sensory processing in higher brain areas when modulated by several behavioral or cognitive variables.

Large-Scale Traveling Waves in EEG Activity Following Eye Movement

In spontaneous, stimulus-evoked, and eye-movement evoked EEG, the oscillatory signal shows large scale, dynamically organized patterns of phase. We investigated eye-movement evoked patterns in free-viewing conditions. Participants viewed photographs of natural scenes in anticipation of a memory test. From 200 ms intervals following saccades, we estimated the EEG phase gradient over the entire scalp, and the wave activity, i.e. the goodness of fit of a wave model involving a phase gradient assumed to be smooth over the scalp. In frequencies centered at 6.5 Hz, large-scale phase organization occurred, peaking around 70 ms after fixation onset and taking the form of a traveling wave. According to the wave gradient, most of the times the wave spreads from the posterior-inferior to anterior-superior direction. In these directions, the gradients depended on the size and direction of the saccade. Wave propagation velocity decreased in the course of the fixation, particularly in the interval from 50 to 150 ms after fixation onset. This interval corresponds to the fixation-related lambda activity, which reflects early perceptual processes following fixation onset. We conclude that lambda activity has a prominent traveling wave component. This component consists of a short-term whole-head phase pattern of specific direction and velocity, which may reflect feedforward propagation of visual information at fixation.

Neural field model of memory-guided search

Many organisms can remember locations they have previously visited during a search. Visual search experiments have shown exploration is guided away from these locations, reducing redundancies in the search path before finding a hidden target. We develop and analyze a two-layer neural field model that encodes positional information during a search task. A position-encoding layer sustains a bump attractor corresponding to the searching agent's current location, and search is modeled by velocity input that propagates the bump. A memory layer sustains persistent activity bounded by a wave front, whose edges expand in response to excitatory input from the position layer. Search can then be biased in response to remembered locations, influencing velocity inputs to the position layer. Asymptotic techniques are used to reduce the dynamics of our model to a low-dimensional system of equations that track the bump position and front boundary. Performance is compared for different target-finding tasks.

Transcranial Direct Current Stimulation Facilitates Associative Learning and Alters Functional Connectivity in the Primate Brain

There has been growing interest in transcranial direct current stimulation (tDCS), a non-invasive technique purported to modulate neural activity via weak, externally applied electric fields. Although some promising preliminary data have been reported for applications ranging from stroke rehabilitation to cognitive enhancement, little is known about how tDCS affects the human brain, and some studies have concluded that it may have no effect at all. Here, we describe a macaque model of tDCS that allows us to simultaneously examine the effects of tDCS on brain activity and behavior. We find that applying tDCS to right prefrontal cortex improves monkeys' performance on an associative learning task. While firing rates do not change within the targeted area, tDCS does induce large low-frequency oscillations in the underlying tissue. These oscillations alter functional connectivity, both locally and between distant brain areas, and these long-range changes correlate with tDCS's effects on behavior. Together, these results are consistent with the idea that tDCS leads to widespread changes in brain activity and suggest that it may be a valuable method for cheaply and non-invasively altering functional connectivity in humans.

Visual Motion Discrimination by Propagating Patterns in Primate Cerebral Cortex

Visual stimuli can evoke waves of neural activity that propagate across the surface of visual cortical areas. The relevance of these waves for visual processing is unknown. Here, we measured the phase and amplitude of local field potentials (LFPs) in electrode array recordings from the motion-processing medial temporal (MT) area of anesthetized male marmosets. Animals viewed grating or dot-field stimuli drifting in different directions. We found that, on individual trials, the direction of LFP wave propagation is sensitive to the direction of stimulus motion. Propagating LFP patterns are also detectable in trial-averaged activity, but the trial-averaged patterns exhibit different dynamics and behaviors from those in single trials and are similar across motion directions. We show that this difference arises because stimulus-sensitive propagating patterns are present in the phase of single-trial oscillations, whereas the trial-averaged signal is dominated by additive amplitude effects. Our results demonstrate that propagating LFP patterns can represent sensory inputs at timescales relevant to visually guided behaviors and raise the possibility that propagating activity patterns serve neural information processing in area MT and other cortical areas.SIGNIFICANCE STATEMENT Propagating wave patterns are widely observed in the cortex, but their functional relevance remains unknown. We show here that visual stimuli generate propagating wave patterns in local field potentials (LFPs) in a movement-sensitive area of the primate cortex and that the propagation direction of these patterns is sensitive to stimulus motion direction. We also show that averaging LFP signals across multiple stimulus presentations (trial averaging) yields propagating patterns that capture different dynamic properties of the LFP response and show negligible direction sensitivity. Our results demonstrate that sensory stimuli can modulate propagating wave patterns reliably in the cortex. The relevant dynamics are normally masked by trial averaging, which is a conventional step in LFP signal processing.

Mechanisms of Saccadic Suppression in Primate Cortical Area V4

Psychophysical studies have shown that subjects are often unaware of visual stimuli presented around the time of an eye movement. This saccadic suppression is thought to be a mechanism for maintaining perceptual stability. The brain might accomplish saccadic suppression by reducing the gain of visual responses to specific stimuli or by simply suppressing firing uniformly for all stimuli. Moreover, the suppression might be identical across the visual field or concentrated at specific points. To evaluate these possibilities, we recorded from individual neurons in cortical area V4 of nonhuman primates trained to execute saccadic eye movements. We found that both modes of suppression were evident in the visual responses of these neurons and that the two modes showed different spatial and temporal profiles: while gain changes started earlier and were more widely distributed across visual space, nonspecific suppression was found more often in the peripheral visual field, after the completion of the saccade. Peripheral suppression was also associated with increased noise correlations and stronger local field potential oscillations in the α frequency band. This pattern of results suggests that saccadic suppression shares some of the circuitry responsible for allocating voluntary attention.

SIGNIFICANCE STATEMENT

We explore our surroundings by looking at things, but each eye movement that we make causes an abrupt shift of the visual input. Why doesn't the world look like a film recorded on a shaky camera? The answer in part is a brain mechanism called saccadic suppression, which reduces the responses of visual neurons around the time of each eye movement. Here we reveal several new properties of the underlying mechanisms. First, the suppression operates differently in the central and peripheral visual fields. Second, it appears to be controlled by oscillations in the local field potentials at frequencies traditionally associated with attention. These results suggest that saccadic suppression shares the brain circuits responsible for actively ignoring irrelevant stimuli.

Sequential hemifield gating of α- and β-behavioral performance oscillations after microsaccades

Microsaccades are tiny saccades that occur during gaze fixation. Even though visual processing has been shown to be strongly modulated close to the time of microsaccades, both at central and peripheral eccentricities, it is not clear how these eye movements might influence longer term fluctuations in brain activity and behavior. Here we found that visual processing is significantly affected and, in a rhythmic manner, even several hundreds of milliseconds after a microsaccade. Human visual detection efficiency, as measured by reaction time, exhibited coherent rhythmic oscillations in the α- and β-frequency bands for up to ~650-700 ms after a microsaccade. Surprisingly, the oscillations were sequentially pulsed across visual hemifields relative to microsaccade direction, first occurring in the same hemifield as the movement vector for ~400 ms and then the opposite. Such pulsing also affected perceptual detection performance. Our results suggest that visual processing is subject to long-lasting oscillations that are phase locked to microsaccade generation, and that these oscillations are dependent on microsaccade direction.NEW & NOTEWORTHY We investigated long-term microsaccadic influences on visual processing and found rhythmic oscillations in behavioral performance at α- and β-frequencies (~8-20 Hz). These oscillations were pulsed at a much lower frequency across visual hemifields, first occurring in the same hemifield as the microsaccade direction vector for ~400 ms before switching to the opposite hemifield for a similar interval. Our results suggest that saccades temporally organize visual processing and that such organization can sequentially switch hemifields.

Task modulates functional connectivity networks in free viewing behavior

In free visual exploration, eye-movement is immediately followed by dynamic reconfiguration of brain functional connectivity. We studied the task-dependency of this process in a combined visual search-change detection experiment. Participants viewed two (nearly) same displays in succession. First time they had to find and remember multiple targets among distractors, so the ongoing task involved memory encoding. Second time they had to determine if a target had changed in orientation, so the ongoing task involved memory retrieval. From multichannel EEG recorded during 200 ms intervals time-locked to fixation onsets, we estimated the functional connectivity using a weighted phase lag index at the frequencies of theta, alpha, and beta bands, and derived global and local measures of the functional connectivity graphs. We found differences between both memory task conditions for several network measures, such as mean path length, radius, diameter, closeness and eccentricity, mainly in the alpha band. Both the local and the global measures indicated that encoding involved a more segregated mode of operation than retrieval. These differences arose immediately after fixation onset and persisted for the entire duration of the lambda complex, an evoked potential commonly associated with early visual perception. We concluded that encoding and retrieval differentially shape network configurations involved in early visual perception, affecting the way the visual input is processed at each fixation. These findings demonstrate that task requirements dynamically control the functional connectivity networks involved in early visual perception.

Rhythmic modulation of visual contrast discrimination triggered by action

Recent evidence suggests that ongoing brain oscillations may be instrumental in binding and integrating multisensory signals. In this experiment, we investigated the temporal dynamics of visual-motor integration processes. We show that action modulates sensitivity to visual contrast discrimination in a rhythmic fashion at frequencies of about 5 Hz (in the theta range), for up to 1 s after execution of action. To understand the origin of the oscillations, we measured oscillations in contrast sensitivity at different levels of luminance, which is known to affect the endogenous brain rhythms, boosting the power of alpha-frequencies. We found that the frequency of oscillation in sensitivity increased at low luminance, probably reflecting the shift in mean endogenous brain rhythm towards higher frequencies. Importantly, both at high and at low luminance, contrast discrimination showed a rhythmic motor-induced suppression effect, with the suppression occurring earlier at low luminance. We suggest that oscillations play a key role in sensory-motor integration, and that the motor-induced suppression may reflect the first manifestation of a rhythmic oscillation.

Coherent alpha oscillations link current and future receptive fields during saccades

Oscillations are ubiquitous in the brain, and they can powerfully influence neural coding. In particular, when oscillations at distinct sites are coherent, they provide a means of gating the flow of neural signals between different cortical regions. Coherent oscillations also occur within individual brain regions, although the purpose of this coherence is not well understood. Here, we report that within a single brain region, coherent alpha oscillations link stimulus representations as they change in space and time. Specifically, in primate cortical area V4, alpha coherence links sites that encode the retinal location of a visual stimulus before and after a saccade. These coherence changes exhibit properties similar to those of receptive field remapping, a phenomenon in which individual neurons change their receptive fields according to the metrics of each saccade. In particular, alpha coherence, like remapping, is highly dependent on the saccade vector and the spatial arrangement of current and future receptive fields. Moreover, although visual stimulation plays a modulatory role, it is neither necessary nor sufficient to elicit alpha coherence. Indeed, a similar pattern of coherence is observed even when saccades are made in darkness. Together, these results show that the pattern of alpha coherence across the retinotopic map in V4 matches many of the properties of receptive field remapping. Thus, oscillatory coherence might play a role in constructing the stable representation of visual space that is an essential aspect of conscious perception.

Dissociation of forward and convergent remapping in primate visual cortex

A fundamental concept in neuroscience is the receptive field, the area of space over which a neuron gathers information. Until about 25 years ago, visual receptive fields were thought to be determined entirely by the pattern of retinal inputs, so it was quite surprising to find neurons in primate cortex with receptive fields that changed position every time a saccade was executed [1]. Although this discovery has figured prominently into theories of visual perception, there is still much debate about the nature of the phenomenon: Some studies report forward remapping[1-3], in which receptive fields shift to their postsaccadic locations, and others report convergent remapping, in which receptive fields shift toward the saccade target [4]. These two possibilities can be difficult to distinguish, particularly when the two types of remapping lead to receptive field shifts in similar directions [5], as was the case in virtually all previous experiments. Here we report new data from neurons in primate cortical area V4, where both types of remapping have previously been reported [3,6]. Using an experimental configuration in which forward and convergent remapping would lead to receptive field shifts in opposite directions, we show that forward remapping is the dominant type of receptive field shift in V4.

Traveling waves and breathers in an excitatory-inhibitory neural field

We study existence and stability of traveling activity bump solutions in an excitatory-inhibitory (E-I) neural field with Heaviside firing rate functions by deriving existence conditions for traveling bumps and an Evans function to analyze their spectral stability. Subsequently, we show that these existence and stability results reduce, in the limit of wave speed c→0, to the equivalent conditions developed for the stationary bump case. Using the results for the stationary bump case, we show that drift bifurcations of stationary bumps serve as a mechanism for generating traveling bump solutions in the E-I neural field as parameters are varied. Furthermore, we explore the interrelations between stationary and traveling types of bumps and breathers (time-periodic oscillatory bumps) by bridging together analytical and simulation results for stationary and traveling bumps and their bifurcations in a region of parameter space. Interestingly, we find evidence for a codimension-2 drift-Hopf bifurcation occurring as two parameters, inhibitory time constant τ and I-to-I synaptic connection strength w[over ¯]_{ii}, are varied and show that the codimension-2 point serves as an organizing center for the dynamics of these four types of spatially localized solutions. Additionally, we describe a case involving subcritical bifurcations that lead to traveling waves and breathers as τ is varied.

Active sensing without efference copy: referent control of perception

Although action and perception are different behaviors, they are likely to be interrelated, as implied by the notions of perception-action coupling and active sensing. Traditionally, it has been assumed that the nervous system directly preprograms motor commands required for actions and uses a copy of them called efference copy (EC) to also influence our senses. This review offers a critical analysis of the EC concept by identifying its limitations. An alternative to the EC concept is based on the experimentally confirmed notion that sensory signals from receptors are perceived relative to referent signals specified by the brain. These referents also underlie the control of motor actions by predetermining where, in the spatial domain, muscles can work without preprogramming how they should work in terms of motor commands or EC. This approach helps solve several problems of action and explain several sensory experiences, including position sense and the sense that the world remains stationary despite changes in its retinal image during eye or body motion (visual space constancy). The phantom limb phenomenon and other kinesthetic illusions are also explained within this framework.

Inferring Cortical Variability from Local Field Potentials

The responses of sensory neurons can be quite different to repeated presentations of the same stimulus. Here, we demonstrate a direct link between the trial-to-trial variability of cortical neuron responses and network activity that is reflected in local field potentials (LFPs). Spikes and LFPs were recorded with a multielectrode array from the middle temporal (MT) area of the visual cortex of macaques during the presentation of continuous optic flow stimuli. A maximum likelihood-based modeling framework was used to predict single-neuron spiking responses using the stimulus, the LFPs, and the activity of other recorded neurons. MT neuron responses were strongly linked to gamma oscillations (maximum at 40 Hz) as well as to lower-frequency delta oscillations (1-4 Hz), with consistent phase preferences across neurons. The predicted modulation associated with the LFP was largely complementary to that driven by visual stimulation, as well as the activity of other neurons, and accounted for nearly half of the trial-to-trial variability in the spiking responses. Moreover, the LFP model predictions accurately captured the temporal structure of noise correlations between pairs of simultaneously recorded neurons, and explained the variation in correlation magnitudes observed across the population. These results therefore identify signatures of network activity related to the variability of cortical neuron responses, and suggest their central role in sensory cortical function.

SIGNIFICANCE STATEMENT

The function of sensory neurons is nearly always cast in terms of representing sensory stimuli. However, recordings from visual cortex in awake animals show that a large fraction of neural activity is not predictable from the stimulus. We show that this variability is predictable given the simultaneously recorded measures of network activity, local field potentials. A model that combines elements of these signals with the stimulus processing of the neuron can predict neural responses dramatically better than current models, and can predict the structure of correlations across the cortical population. In identifying ways to understand stimulus processing in the context of ongoing network activity, this work thus provides a foundation to understand the role of sensory cortex in combining sensory and cognitive variables.

Discrepancies between Multi-Electrode LFP and CSD Phase-Patterns: A Forward Modeling Study

Multi-electrode recordings of local field potentials (LFPs) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFPs allow studying the coordination of neural oscillations in time and space and to tie it to cognitive processing. Given the computational roles of LFP phases, it is important to know how they relate to the phases of the underlying current source densities (CSDs) that generate them. Although CSDs and LFPs are distinct physical quantities, they are often (implicitly) identified when interpreting experimental observations. That this identification is problematic is clear from the fact that LFP phases change when switching to different electrode montages, while the underlying CSD phases remain unchanged. In this study we use a volume-conductor model to characterize discrepancies between LFP and CSD phase-patterns, to identify the contributing factors, and to assess the effect of different electrode montages. Although we focus on cortical LFPs recorded with two-dimensional (Utah) arrays, our findings are also relevant for other electrode configurations. We found that the main factors that determine the discrepancy between CSD and LFP phase-patterns are the frequency of the neural oscillations and the extent to which the laminar CSD profile is balanced. Furthermore, the presence of laminar phase-differences in cortical oscillations, as commonly observed in experiments, precludes identifying LFP phases with those of the CSD oscillations at a given cortical depth. This observation potentially complicates the interpretation of spike-LFP coherence and spike-triggered LFP averages. With respect to reference strategies, we found that the average-reference montage leads to larger discrepancies between LFP and CSD phases as compared with the referential montage, while the Laplacian montage reduces these discrepancies. We therefore advice to conduct analysis of two-dimensional LFP recordings using the Laplacian montage.

Analytically tractable studies of traveling waves of activity in integrate-and-fire neural networks

In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration depends quadratically on the instantaneous speed of the activity propagation. We use this property to analytically compute the network spike dynamics and to highlight the emergence of a natural time scale for the evolution of the traveling waves. These results allow us to examine other applications of this model such as the effect that a nonconductive gap of tissue has on further activity propagation. Furthermore we show that activity propagation also depends on local conditions for other more general connectivity functions, by converting the evolution equations for network dynamics into a low-dimensional system of ordinary differential equations. This approach greatly enhances our intuition into the mechanisms of the traveling waves evolution and significantly reduces the simulation time for this class of models.

Perisaccadic Receptive Field Expansion in the Lateral Intraparietal Area

Humans and monkeys have access to an accurate representation of visual space despite a constantly moving eye. One mechanism by which the brain accomplishes this is by remapping visual receptive fields around the time of a saccade. In this process a neuron can be excited by a probe stimulus in the current receptive field, and also simultaneously by a probe stimulus in the location that will be brought into the neuron's receptive field by the saccade (the future receptive field), even before saccade begins. Here we show that perisaccadic neuronal excitability is not limited to the current and future receptive fields but encompasses the entire region of visual space across which the current receptive field will be swept by the saccade. A computational model shows that this receptive field expansion is consistent with the propagation of a wave of activity across the cerebral cortex as saccade planning and remapping proceed.

The ictal wavefront is the spatiotemporal source of discharges during spontaneous human seizures

The extensive distribution and simultaneous termination of seizures across cortical areas has led to the hypothesis that seizures are caused by large-scale coordinated networks spanning these areas. This view, however, is difficult to reconcile with most proposed mechanisms of seizure spread and termination, which operate on a cellular scale. We hypothesize that seizures evolve into self-organized structures wherein a small seizing territory projects high-intensity electrical signals over a broad cortical area. Here we investigate human seizures on both small and large electrophysiological scales. We show that the migrating edge of the seizing territory is the source of travelling waves of synaptic activity into adjacent cortical areas. As the seizure progresses, slow dynamics in induced activity from these waves indicate a weakening and eventual failure of their source. These observations support a parsimonious theory for how large-scale evolution and termination of seizures are driven from a small, migrating cortical area.

Epileptic brains display inhibitory restraint as manifested by the spread of synchronized activities being delayed in timing. Here, Elliot Smith and colleagues show fast-moving traveling wave that originates from the edge of ictal wavefront with subsequent depolarization and multiunit firing in the seizing brain regions in epileptic patients.

Two distinct types of remapping in primate cortical area V4

Visual neurons typically receive information from a limited portion of the retina, and such receptive fields are a key organizing principle for much of visual cortex. At the same time, there is strong evidence that receptive fields transiently shift around the time of saccades. The nature of the shift is controversial: Previous studies have found shifts consistent with a role for perceptual constancy; other studies suggest a role in the allocation of spatial attention. Here we present evidence that both the previously documented functions exist in individual neurons in primate cortical area V4. Remapping associated with perceptual constancy occurs for saccades in all directions, while attentional shifts mainly occur for neurons with receptive fields in the same hemifield as the saccade end point. The latter are relatively sluggish and can be observed even during saccade planning. Overall these results suggest a complex interplay of visual and extraretinal influences during the execution of saccades.

Visual receptive fields are known to change positions around the time of a saccade, but the nature of this remapping is unclear. Here Neupane and colleagues show that neurons in area V4 of the visual cortex exhibit two types of remapping, one consistent with a role in maintaining perceptual stability, and a second that seems to reflect shifts of attention.

Diverse Phase Relations among Neuronal Rhythms and Their Potential Function

Neuronal oscillations at nearby sites in the brain often show phase relations that are consistent across time, yet diverse across space. We discuss recent demonstrations of this phase relation diversity, and show that, contrary to earlier beliefs, this diversity is a general property of oscillations that is neither restricted to low-frequency oscillations nor to periods outside of stimulus processing. Arguing for the computational relevance of phase relation diversity, we discuss that it can be modulated by sensory and motor events, and put forward the idea that phase relation diversity may support effective neuronal communication by (i) enhancing selectivity and (ii) allowing for the concurrent segregation of multiple information streams.