Compression and reflection of visually evoked cortical waves

Distinct functional properties of primary and posteromedial visual area of mouse neocortex

Visual input provides important landmarks for navigating in the environment, information that in mammals is processed by specialized areas in the visual cortex. In rodents, the posteromedial area (PM) mediates visual information between primary visual cortex (V1) and the retrosplenial cortex, which further projects to the hippocampus. To understand the functional role of area PM requires a detailed analysis of its spatial frequency (SF) and temporal frequency (TF) tuning. Here, we applied two-photon calcium imaging to map neuronal tuning for orientation, direction, SF and TF, and speed in response to drifting gratings in V1 and PM of anesthetized mice. The distributions of orientation and direction tuning were similar in V1 and PM. Notably, in both areas we found a preference for cardinal compared to oblique orientations. The overrepresentation of cardinal tuned neurons was particularly strong in PM showing narrow tuning bandwidths for horizontal and vertical orientations. A detailed analysis of SF and TF tuning revealed a broad range of highly tuned neurons in V1. On the contrary, PM contained one subpopulation of neurons with high spatial acuity and a second subpopulation broadly tuned for low SFs. Furthermore, ∼20% of the responding neurons in V1 and only 12% in PM were tuned to the speed of drifting gratings with PM preferring slower drift rates compared to V1. Together, PM is tuned for cardinal orientations, high SFs, and low speed and is further located between V1 and the retrosplenial cortex consistent with a role in processing natural scenes during spatial navigation.

Genetically encoded optical indicators for the analysis of neuronal circuits

In a departure from previous top-down or bottom-up strategies used to understand neuronal circuits, many forward-looking research programs now place the circuit itself at their centre. This has led to an emphasis on the dissection and elucidation of neuronal circuit elements and mechanisms, and on studies that ask how these circuits generate behavioural outputs. This movement towards circuit-centric strategies is progressing rapidly as a result of technological advances that combine genetic manipulation with light-based methods. The core tools of these new approaches are genetically encoded optical indicators and actuators that enable non-destructive interrogation and manipulation of neuronal circuits in behaving animals with cellular-level precision. This Review examines genetically encoded reporters of neuronal function and assesses their value for circuit-oriented neuroscientific investigations.

Spontaneous high-gamma band activity reflects functional organization of auditory cortex in the awake macaque

In the absence of sensory stimuli, spontaneous activity in the brain has been shown to exhibit organization at multiple spatiotemporal scales. In the macaque auditory cortex, responses to acoustic stimuli are tonotopically organized within multiple, adjacent frequency maps aligned in a caudorostral direction on the supratemporal plane (STP) of the lateral sulcus. Here, we used chronic microelectrocorticography to investigate the correspondence between sensory maps and spontaneous neural fluctuations in the auditory cortex. We first mapped tonotopic organization across 96 electrodes spanning approximately two centimeters along the primary and higher auditory cortex. In separate sessions, we then observed that spontaneous activity at the same sites exhibited spatial covariation that reflected the tonotopic map of the STP. This observation demonstrates a close relationship between functional organization and spontaneous neural activity in the sensory cortex of the awake monkey.

Propagating waves in thalamus, cortex and the thalamocortical system: Experiments and models

Propagating waves of activity have been recorded in many species, in various brain states, brain areas, and under various stimulation conditions. Here, we review the experimental literature on propagating activity in thalamus and neocortex across various levels of anesthesia and stimulation conditions. We also review computational models of propagating waves in networks of thalamic cells, cortical cells and of the thalamocortical system. Some discrepancies between experiments can be explained by the "network state", which differs vastly between anesthetized and awake conditions. We introduce a network model displaying different states and investigate their effect on the spatial structure of self-sustained and externally driven activity. This approach is a step towards understanding how the intrinsically-generated ongoing activity of the network affects its ability to process and propagate extrinsic input.

Stimulus-entrained oscillatory activity propagates as waves from area 18 to 17 in cat visual cortex

Previous studies in cat visual cortex reported that area 18 can actively drive neurons in area 17 through cortico-cortical projections. However, the dynamics of such cortico-cortical interaction remains unclear. Here we used multielectrode arrays to examine the spatiotemporal pattern of neuronal activity in cat visual cortex across the 17/18 border. We found that full-field contrast reversal gratings evoked oscillatory wave activity propagating from area 18 to 17. The wave direction was independent of the grating orientation, and could not be accounted for by the spatial distribution of receptive field latencies, suggesting that the waves are largely mediated by intrinsic connections in the cortex. Different from the evoked waves, spontaneous waves propagated along both directions across the 17/18 border. Together, our results suggest that visual stimulation may enhance the flow of information from area 18 to 17.

Imaging neural circuit dynamics with a voltage-sensitive fluorescent protein

Population signals from neuronal ensembles in cortex during behavior are commonly measured with EEG, local field potential (LFP), and voltage-sensitive dyes. A genetically encoded voltage indicator would be useful for detection of such signals in specific cell types. Here we describe how this goal can be achieved with Butterfly, a voltage-sensitive fluorescent protein (VSFP) with a subthreshold detection range and enhancements designed for voltage imaging from single neurons to brain in vivo. VSFP-Butterfly showed reliable membrane targeting, maximum response gain around standard neuronal resting membrane potential, fast kinetics for single-cell synaptic responses, and a high signal-to-noise ratio. Butterfly reports excitatory postsynaptic potentials (EPSPs) in cortical neurons, whisker-evoked responses in barrel cortex, 25-Hz gamma oscillations in hippocampal slices, and 2- to 12-Hz slow waves during brain state modulation in vivo. Our findings demonstrate that cell class-specific voltage imaging is practical with VSFP-Butterfly, and expand the genetic toolbox for the detection of neuronal population dynamics.

Surround suppression and sparse coding in visual and barrel cortices

During natural vision the entire retina is stimulated. Likewise, during natural tactile behaviors, spatially extensive regions of the somatosensory surface are co-activated. The large spatial extent of naturalistic stimulation means that surround suppression, a phenomenon whose neural mechanisms remain a matter of debate, must arise during natural behavior. To identify common neural motifs that might instantiate surround suppression across modalities, we review models of surround suppression and compare the evidence supporting the competing ideas that surround suppression has either cortical or sub-cortical origins in visual and barrel cortex. In the visual system there is general agreement lateral inhibitory mechanisms contribute to surround suppression, but little direct experimental evidence that intracortical inhibition plays a major role. Two intracellular recording studies of V1, one using naturalistic stimuli (Haider et al., 2010), the other sinusoidal gratings (Ozeki et al., 2009), sought to identify the causes of reduced activity in V1 with increasing stimulus size, a hallmark of surround suppression. The former attributed this effect to increased inhibition, the latter to largely balanced withdrawal of excitation and inhibition. In rodent primary somatosensory barrel cortex, multi-whisker responses are generally weaker than single whisker responses, suggesting multi-whisker stimulation engages similar surround suppressive mechanisms. The origins of suppression in S1 remain elusive: studies have implicated brainstem lateral/internuclear interactions and both thalamic and cortical inhibition. Although the anatomical organization and instantiation of surround suppression in the visual and somatosensory systems differ, we consider the idea that one common function of surround suppression, in both modalities, is to remove the statistical redundancies associated with natural stimuli by increasing the sparseness or selectivity of sensory responses.

Human cortical traveling waves: dynamical properties and correlations with responses

The spatiotemporal behavior of human EEG oscillations is investigated. Traveling waves in the alpha and theta ranges are found to be common in both prestimulus and poststimulus EEG activity. The dynamical properties of these waves, including their speeds, directions, and durations, are systematically characterized for the first time, and the results show that there are significant changes of prestimulus spontaneous waves in the presence of an external stimulus. Furthermore, the functional relevance of these waves is examined by studying how they are correlated with reaction times on a single trial basis; prestimulus alpha waves traveling in the frontal-to-occipital direction are found to be most correlated to reaction speeds. These findings suggest that propagating waves of brain oscillations might be involved in mediating long-range interactions between widely distributed parts of human cortex.

Neural field theory with variance dynamics

Previous neural field models have mostly been concerned with prediction of mean neural activity and with second order quantities such as its variance, but without feedback of second order quantities on the dynamics. Here the effects of feedback of the variance on the steady states and adiabatic dynamics of neural systems are calculated using linear neural field theory to estimate the neural voltage variance, then including this quantity in the total variance parameter of the nonlinear firing rate-voltage response function, and thus into determination of the fixed points and the variance itself. The general results further clarify the limits of validity of approaches with and without inclusion of variance dynamics. Specific applications show that stability against a saddle-node bifurcation is reduced in a purely cortical system, but can be either increased or decreased in the corticothalamic case, depending on the initial state. Estimates of critical variance scalings near saddle-node bifurcation are also found, including physiologically based normalizations and new scalings for mean firing rate and the position of the bifurcation.

Interactions between two propagating waves in rat visual cortex

Sensory-evoked propagating waves are frequently observed in sensory cortex. However, it is largely unknown how an evoked propagating wave affects the activity evoked by subsequent sensory inputs, or how two propagating waves interact when evoked by simultaneous sensory inputs. Using voltage-sensitive dye imaging, we investigated the interactions between two evoked waves in rat visual cortex, and the spatiotemporal patterns of depolarization in the neuronal population due to wave-to-wave interactions. We have found that visually-evoked propagating waves have a refractory period of about 300 ms, within which the response to a subsequent visual stimulus is suppressed. Simultaneous presentation of two visual stimuli at different locations can evoke two waves propagating toward each other, and these two waves fuse. Fusion significantly shortens the latency and half-width of the response, leading to changes in the spatial profile of evoked population activity. The visually-evoked propagating wave may also be suppressed by a preceding spontaneous wave. The refractory period following a propagating wave and the fusion between two waves may contribute to visual sensory processing by modifying the spatiotemporal profile of population neuronal activity evoked by sensory events.

From invasion to extinction in heterogeneous neural fields

In this paper, we analyze the invasion and extinction of activity in heterogeneous neural fields. We first consider the effects of spatial heterogeneities on the propagation of an invasive activity front. In contrast to previous studies of front propagation in neural media, we assume that the front propagates into an unstable rather than a metastable zero-activity state. For sufficiently localized initial conditions, the asymptotic velocity of the resulting pulled front is given by the linear spreading velocity, which is determined by linearizing about the unstable state within the leading edge of the front. One of the characteristic features of these so-called pulled fronts is their sensitivity to perturbations inside the leading edge. This means that standard perturbation methods for studying the effects of spatial heterogeneities or external noise fluctuations break down. We show how to extend a partial differential equation method for analyzing pulled fronts in slowly modulated environments to the case of neural fields with slowly modulated synaptic weights. The basic idea is to rescale space and time so that the front becomes a sharp interface whose location can be determined by solving a corresponding local Hamilton-Jacobi equation. We use steepest descents to derive the Hamilton-Jacobi equation from the original nonlocal neural field equation. In the case of weak synaptic heterogenities, we then use perturbation theory to solve the corresponding Hamilton equations and thus determine the time-dependent wave speed. In the second part of the paper, we investigate how time-dependent heterogenities in the form of extrinsic multiplicative noise can induce rare noise-driven transitions to the zero-activity state, which now acts as an absorbing state signaling the extinction of all activity. In this case, the most probable path to extinction can be obtained by solving the classical equations of motion that dominate a path integral representation of the stochastic neural field in the weak noise limit. These equations take the form of nonlocal Hamilton equations in an infinite-dimensional phase space.

Hemodynamic traveling waves in human visual cortex

Functional MRI (fMRI) experiments rely on precise characterization of the blood oxygen level dependent (BOLD) signal. As the spatial resolution of fMRI reaches the sub-millimeter range, the need for quantitative modelling of spatiotemporal properties of this hemodynamic signal has become pressing. Here, we find that a detailed physiologically-based model of spatiotemporal BOLD responses predicts traveling waves with velocities and spatial ranges in empirically observable ranges. Two measurable parameters, related to physiology, characterize these waves: wave velocity and damping rate. To test these predictions, high-resolution fMRI data are acquired from subjects viewing discrete visual stimuli. Predictions and experiment show strong agreement, in particular confirming BOLD waves propagating for at least 5–10 mm across the cortical surface at speeds of 2–12 mm s-1. These observations enable fundamentally new approaches to fMRI analysis, crucial for fMRI data acquired at high spatial resolution.

Functional magnetic resonance imaging (fMRI) experiments have advanced our understanding of the structure and function of the human brain. Dynamic changes in the flow and concentration of oxygen in blood are observed experimentally in fMRI data via the blood oxygen level dependent (BOLD) signal. Since neuronal activity induces this hemodynamic response, the BOLD signal provides a noninvasive measure of neuronal activity. Understanding the mechanisms that drive this BOLD response is fundamental for accurately inferring the underlying neuronal activity. The goal of this study is to systematically predict spatiotemporal hemodynamics from a biophysical model, then test these in a high resolution fMRI study of the visual cortex. Using this theory, we predict and empirically confirm the existence of hemodynamic waves in cortex – a striking and novel finding.

Response of traveling waves to transient inputs in neural fields

We analyze the effects of transient stimulation on traveling waves in neural field equations. Neural fields are modeled as integro-differential equations whose convolution term represents the synaptic connections of a spatially extended neuronal network. The adjoint of the linearized wave equation can be used to identify how a particular input will shift the location of a traveling wave. This wave response function is analogous to the phase response curve of limit cycle oscillators. For traveling fronts in an excitatory network, the sign of the shift depends solely on the sign of the transient input. A complementary estimate of the effective shift is derived using an equation for the time-dependent speed of the perturbed front. Traveling pulses are analyzed in an asymmetric lateral inhibitory network and they can be advanced or delayed, depending on the position of spatially localized transient inputs. We also develop bounds on the amplitude of transient input necessary to terminate traveling pulses, based on the global bifurcation structure of the neural field.

Effect of high velocity, large amplitude stimuli on the spread of depolarization in S1 "barrel" cortex

We examined the effect of large, controlled whisker movements, delivered at a high speed, on the amplitude and spread of depolarization in the anesthetized mouse barrel cortex. The stimulus speed was varied between 1500 and 6000°/s and the extent of movement was varied between 4° and 16°. The rate of rise of the response was linearly related to the rate of rise of the stimulus. The initial spatial extent of cortical activation was also related to the rate of rise of the stimulus: that is, the faster the stimulus onset, the faster the rate of rise of the response, the larger the extent of cortex activated initially. The spatial extent of the response and the rate of rise of the response were not correlated with changes in the deflection amplitude. However, slower, longer lasting stimuli produced an Off response, making the actual extent of activation larger for the slowest rising stimuli. These results indicate that the spread of cortical activation depends on stimulus features.

Sound-evoked network calcium transients in mouse auditory cortex in vivo

Population calcium signals generated by the action potential activity of local clusters of neurons have been recorded in the auditory cortex of mice using an optical fibre-based approach. These network calcium transients (NCaTs) occurred spontaneously as well as in response to sound stimulation. Two-photon calcium imaging experiments suggest that neurons and neuropil contribute about equally to the NCaT. Sound-evoked calcium signals had two components: an early, fast increase in calcium concentration, which corresponds to the short-latency spiking responses observed in electrophysiological experiments, and a late, slow calcium transient which lasted for at least 1 s. The slow calcium transients evoked by sound were essentially identical to spontaneous NCaTs. Their sizes were dependent on the spontaneous activity level at sound onset, suggesting that spontaneous and sensory-evoked NCaTs excluded each other. When using pure tones as stimulus, the early evoked calcium transients were more narrowly tuned than the slow NCaTs. The slow NCaTs were correlated with global ‘up states' recorded with epidural potentials, and sound presented during an epidural ‘down state' triggered a calcium transient that was associated with an epidural ‘up state'. Essentially indistinguishable calcium transients were evoked by optogenetic activation of local clusters of layer 5 pyramidal neurons in the auditory cortex, indicating that these neurons play an important role in the generation of the calcium signal. Taken together, our results identify sound-evoked slow NCaTs as an integral component of neuronal signalling in the mouse auditory cortex, reflecting the prolonged neuronal activity of local clusters of neurons that can be activated even by brief stimuli.

Visualization and manipulation of neural activity in the developing vertebrate nervous system

Neural activity during vertebrate development has been unambiguously shown to play a critical role in sculpting circuit formation and function. Patterned neural activity in various parts of the developing nervous system is thought to modulate neurite outgrowth, axon targeting, and synapse refinement. The nature and role of patterned neural activity during development has been classically studied with in vitro preparations using pharmacological manipulations. In this review we discuss newly available and developing molecular-genetic tools for the visualization and manipulation of neural activity patterns specifically during development.

Stereotypical spatiotemporal activity patterns during slow-wave activity in the neocortex

Alternating epochs of activity and silence are a characteristic feature of neocortical networks during certain sleep cycles and deep states of anesthesia. The mechanism and functional role of these slow oscillations (<1 Hz) have not yet been fully characterized. Experimental and theoretical studies show that slow-wave oscillations can be generated autonomously by neocortical tissue but become more regular through a thalamo-cortical feedback loop. Evidence for a functional role of slow-wave activity comes from EEG recordings in humans during sleep, which show that activity travels as stereotypical waves over the entire brain, thought to play a role in memory consolidation. We used an animal model to investigate activity wave propagation on a smaller scale, namely within the rat somatosensory cortex. Signals from multiple extracellular microelectrodes in combination with one intracellular recording in the anesthetized animal in vivo were utilized to monitor the spreading of activity. We found that activity propagation in most animals showed a clear preferred direction, suggesting that it often originated from a similar location in the cortex. In addition, the breakdown of active states followed a similar pattern with slightly weaker direction preference but a clear correlation to the direction of activity spreading, supporting the notion of a wave-like phenomenon similar to that observed after strong sensory stimulation in sensory areas. Taken together, our findings support the idea that activity waves during slow-wave sleep do not occur spontaneously at random locations within the network, as was suggested previously, but follow preferred synaptic pathways on a small spatial scale.

Flow detection of propagating waves with temporospatial correlation of activity

Voltage-sensitive dye imaging (VSDI) allows population patterns of cortical activity to be recorded with high temporal resolution, and recent findings ascribe potential significance to these spatial propagation patterns--both for normal cortical processing and in pathologies such as epilepsy. However, analysis of these spatiotemporal patterns has been mostly qualitative to date. In this report, we describe an algorithm to quantify fast local flow patterns of cortical population activation, as measured with VSDI. The algorithm uses correlation of temporal features across space, and therefore differs from conventional optical flow algorithms which use correlation of spatial features over time. This alternative approach allows us to take advantage of the characteristics of fast optical imaging data, which have very high temporal resolution but less spatial resolution. We verify the method both on artificial and biological data, and demonstrate its use.

Generalization of learning by synchronous waves: from perceptual organization to invariant organization

From a few presentations of an object, perceptual systems are able to extract invariant properties such that novel presentations are immediately recognized. This may be enabled by inferring the set of all representations equivalent under certain transformations. We implemented this principle in a neurodynamic model that stores activity patterns representing transformed versions of the same object in a distributed fashion within maps, such that translation across the map corresponds to the relevant transformation. When a pattern on the map is activated, this causes activity to spread out as a wave across the map, activating all the transformed versions represented. Computational studies illustrate the efficacy of the proposed mechanism. The model rapidly learns and successfully recognizes rotated and scaled versions of a visual representation from a few prior presentations. For topographical maps such as primary visual cortex, the mechanism simultaneously represents identity and variation of visual percepts whose features change through time.

Propagating waves in human motor cortex

Previous studies in non-human primates (NHPs) have shown that beta oscillations (15–30 Hz) of local field potentials (LFPs) in the arm/hand areas of primary motor cortex (MI) propagate as traveling waves across the cortex. These waves exhibited two stereotypical features across animals and tasks: (1) The waves propagated in two dominant modal directions roughly 180° apart, and (2) their propagation speed ranged from 10 to 35 cm/s. It is, however, unknown if such cortical waves occur in the human motor cortex. This study shows that the two properties of propagating beta waves are present in MI of a tetraplegic human patient while he was instructed to perform an instruction delay center-out task using a cursor controlled by the chin. Moreover, we show that beta waves are sustained and have similar properties whether the subject was engaged in the task or at rest. The directions of the successive sustained waves both in the human subject and a NHP subject tended to switch from one dominant mode to the other, and at least in the NHP subject the estimated distance traveled between successive waves traveling into and out of the central sulcus is consistent with the hypothesis of wave reflection between the border of motor and somatosensory cortices. Further, we show that the occurrence of the beta waves is not uniquely tied to periods of increased power in the beta frequency band. These results demonstrate that traveling beta waves in MI are a general phenomenon occurring in human as well as NHPs. Consistent with the NHP data, the dominant directions of the beta LFP waves in human aligned to the proximal to distal gradient of joint representations in MI somatotopy. This consistent finding of wave propagation may imply the existence of a hardwired organization of motor cortex that mediates this spatiotemporal pattern.

Spatiotemporal scales and links between electrical neuroimaging modalities

Recordings of brain electrophysiological activity provide the most direct reflect of neural function. Information contained in these signals varies as a function of the spatial scale at which recordings are done: from single cell recording to large scale macroscopic fields, e.g., scalp EEG. Microscopic and macroscopic measurements and models in Neuroscience are often in conflict. Solving this conflict might require the developments of a sort of bio-statistical physics, a framework for relating the microscopic properties of individual cells to the macroscopic or bulk properties of neural circuits. Such a framework can only emerge in Neuroscience from the systematic analysis and modeling of the diverse recording scales from simultaneous measurements. In this article we briefly review the different measurement scales and models in modern neuroscience to try to identify the sources of conflict that might ultimately help to create a unified theory of brain electromagnetic fields. We argue that seen the different recording scales, from the single cell to the large scale fields measured by the scalp electroencephalogram, as derived from a unique physical magnitude--the electric potential that is measured in all cases--might help to conciliate microscopic and macroscopic models of neural function as well as the animal and human neuroscience literature.

Propagation of epileptiform activity on a submillimeter scale

Microseizures are highly focal low-frequency epileptiform-appearing events recorded from the neocortex of epilepsy patients. Because of their tiny, often submillimeter distribution, they may be regarded as a high-resolution window into the epileptic process, providing an excellent opportunity to study the fine temporal structure of their origin and spread. A 16 mm² 96-microelectrode array with 400-μm interelectrode spacing was implanted in seven patients undergoing invasive EEG monitoring for medically refractory epilepsy. Seven microdischarge populations were tested for a substantial contribution by volume conduction to the observed waveform amplitudes. Single-unit activity was examined for specific evidence of neural activity at multiple sites within the microdischarge fields. We found that microdischarges appear to originate at a highly focal source location, likely within a single cortical macrocolumn, and spread to local and more distant sites via neural propagation.

Lateral Spread of Orientation Selectivity in V1 is Controlled by Intracortical Cooperativity

Neurons in the primary visual cortex receive subliminal information originating from the periphery of their receptive fields (RF) through a variety of cortical connections. In the cat primary visual cortex, long-range horizontal axons have been reported to preferentially bind to distant columns of similar orientation preferences, whereas feedback connections from higher visual areas provide a more diverse functional input. To understand the role of these lateral interactions, it is crucial to characterize their effective functional connectivity and tuning properties. However, the overall functional impact of cortical lateral connections, whatever their anatomical origin, is unknown since it has never been directly characterized. Using direct measurements of postsynaptic integration in cat areas 17 and 18, we performed multi-scale assessments of the functional impact of visually driven lateral networks. Voltage-sensitive dye imaging showed that local oriented stimuli evoke an orientation-selective activity that remains confined to the cortical feedforward imprint of the stimulus. Beyond a distance of one hypercolumn, the lateral spread of cortical activity gradually lost its orientation preference approximated as an exponential with a space constant of about 1 mm. Intracellular recordings showed that this loss of orientation selectivity arises from the diversity of converging synaptic input patterns originating from outside the classical RF. In contrast, when the stimulus size was increased, we observed orientation-selective spread of activation beyond the feedforward imprint. We conclude that stimulus-induced cooperativity enhances the long-range orientation-selective spread.

Spiral wave dynamics in neocortex

Although spiral waves are ubiquitous features of nature and have been observed in many biological systems, their existence and potential function in mammalian cerebral cortex remain uncertain. Using voltage-sensitive dye imaging, we found that spiral waves occur frequently in the neocortex in vivo, both during pharmacologically induced oscillations and during sleep-like states. While their life span is limited, spiral waves can modify ongoing cortical activity by influencing oscillation frequencies and spatial coherence and by reducing amplitude in the area surrounding the spiral phase singularity. During sleep-like states, the rate of occurrence of spiral waves varies greatly depending on brain states. These results support the hypothesis that spiral waves, as an emergent activity pattern, can organize and modulate cortical population activity on the mesoscopic scale and may contribute to both normal cortical processing and to pathological patterns of activity such as those found in epilepsy.

A self-calibrating, camera-based eye tracker for the recording of rodent eye movements

Much of neurophysiology and vision science relies on careful measurement of a human or animal subject's gaze direction. Video-based eye trackers have emerged as an especially popular option for gaze tracking, because they are easy to use and are completely non-invasive. However, video eye trackers typically require a calibration procedure in which the subject must look at a series of points at known gaze angles. While it is possible to rely on innate orienting behaviors for calibration in some non-human species, other species, such as rodents, do not reliably saccade to visual targets, making this form of calibration impossible. To overcome this problem, we developed a fully automated infrared video eye-tracking system that is able to quickly and accurately calibrate itself without requiring co-operation from the subject. This technique relies on the optical geometry of the cornea and uses computer-controlled motorized stages to rapidly estimate the geometry of the eye relative to the camera. The accuracy and precision of our system was carefully measured using an artificial eye, and its capability to monitor the gaze of rodents was verified by tracking spontaneous saccades and evoked oculomotor reflexes in head-fixed rats (in both cases, we obtained measurements that are consistent with those found in the literature). Overall, given its fully automated nature and its intrinsic robustness against operator errors, we believe that our eye-tracking system enhances the utility of existing approaches to gaze-tracking in rodents and represents a valid tool for rodent vision studies.

Neurophysiological and computational principles of cortical rhythms in cognition

Synchronous rhythms represent a core mechanism for sculpting temporal coordination of neural activity in the brain-wide network. This review focuses on oscillations in the cerebral cortex that occur during cognition, in alert behaving conditions. Over the last two decades, experimental and modeling work has made great strides in elucidating the detailed cellular and circuit basis of these rhythms, particularly gamma and theta rhythms. The underlying physiological mechanisms are diverse (ranging from resonance and pacemaker properties of single cells to multiple scenarios for population synchronization and wave propagation), but also exhibit unifying principles. A major conceptual advance was the realization that synaptic inhibition plays a fundamental role in rhythmogenesis, either in an interneuronal network or in a reciprocal excitatory-inhibitory loop. Computational functions of synchronous oscillations in cognition are still a matter of debate among systems neuroscientists, in part because the notion of regular oscillation seems to contradict the common observation that spiking discharges of individual neurons in the cortex are highly stochastic and far from being clocklike. However, recent findings have led to a framework that goes beyond the conventional theory of coupled oscillators and reconciles the apparent dichotomy between irregular single neuron activity and field potential oscillations. From this perspective, a plethora of studies will be reviewed on the involvement of long-distance neuronal coherence in cognitive functions such as multisensory integration, working memory, and selective attention. Finally, implications of abnormal neural synchronization are discussed as they relate to mental disorders like schizophrenia and autism.

Neuronal avalanches in spontaneous activity in vivo

Many complex systems give rise to events that are clustered in space and time, thereby establishing a correlation structure that is governed by power law statistics. In the cortex, such clusters of activity, called "neuronal avalanches," were recently found in local field potentials (LFPs) of spontaneous activity in acute cortex slices, slice cultures, the developing cortex of the anesthetized rat, and premotor and motor cortex of awake monkeys. At present, it is unclear whether neuronal avalanches also exist in the spontaneous LFPs and spike activity in vivo in sensory areas of the mature brain. To address this question, we recorded spontaneous LFPs and extracellular spiking activity with multiple 4 × 4 microelectrode arrays (Michigan Probes) in area 17 of adult cats under anesthesia. A cluster of events was defined as a consecutive sequence of time bins Δt (1-32 ms), each containing at least one LFP event or spike anywhere on the array. LFP cluster sizes consistently distributed according to a power law with a slope largely above -1.5. In two thirds of the corresponding experiments, spike clusters also displayed a power law that displayed a slightly steeper slope of -1.8 and was destroyed by subsampling operations. The power law in spike clusters was accompanied with stronger temporal correlations between spiking activities of neurons that spanned longer time periods compared with spike clusters lacking power law statistics. The results suggest that spontaneous activity of the visual cortex under anesthesia has the properties of neuronal avalanches.

Six principles of visual cortical dynamics

A fundamental goal in vision science is to determine how many neurons in how many areas are required to compute a coherent interpretation of the visual scene. Here I propose six principles of cortical dynamics of visual processing in the first 150 ms following the appearance of a visual stimulus. Fast synaptic communication between neurons depends on the driving neurons and the biophysical history and driving forces of the target neurons. Under these constraints, the retina communicates changes in the field of view driving large populations of neurons in visual areas into a dynamic sequence of feed-forward communication and integration of the inward current of the change signal into the dendrites of higher order area neurons (30-70 ms). Simultaneously an even larger number of neurons within each area receiving feed-forward input are pre-excited to sub-threshold levels. The higher order area neurons communicate the results of their computations as feedback adding inward current to the excited and pre-excited neurons in lower areas. This feedback reconciles computational differences between higher and lower areas (75-120 ms). This brings the lower area neurons into a new dynamic regime characterized by reduced driving forces and sparse firing reflecting the visual areas interpretation of the current scene (140 ms). The population membrane potentials and net-inward/outward currents and firing are well behaved at the mesoscopic scale, such that the decoding in retinotopic cortical space shows the visual areas' interpretation of the current scene. These dynamics have plausible biophysical explanations. The principles are theoretical, predictive, supported by recent experiments and easily lend themselves to experimental tests or computational modeling.

Emergent complexity in simple neural systems

The ornate and diverse patterns of seashells testify to the complexity of living systems. Provocative computational explorations have shown that similarly complex patterns may arise from the collective interaction of a small number of rules. This suggests that, although a system may appear complex, it may still be understood in terms of simple principles. It is still debatable whether shell patterns emerge from some undiscovered simple principles, or are the consequence of an irreducibly complex interaction of many effects. Recent work by Boettiger, Ermentrout and Oster on the biological mechanisms of shell patterning has provided compelling evidence that, at least for this system, simplicity produces diversity and complexity.

Fast propagating waves within the rodent auditory cortex

Central processing of acoustic signals is assumed to take place in a stereotypical spatial and temporal pattern involving different fields of auditory cortex. So far, cortical propagating waves representing such patterns have mainly been demonstrated by optical imaging, repeatedly in the visual and somatosensory cortex. In this study, the surface of rat auditory cortex was mapped by recording local field potentials (LFPs) in response to a broadband acoustic stimulus. From the peak amplitudes of LFPs, cortical activation maps were constructed over 4 cortical auditory fields. Whereas response onset had same latencies across primary auditory field (A1), anterior auditory field (AAF), and ventral auditory field and longer latencies in posterior auditory field, activation maps revealed a reproducible wavelike pattern of activity propagating for ∼45 ms poststimulus through all cortical fields. The movement observed started with 2 waves within the primary auditory fields A1 and AAF moving from ventral to dorsal followed by a motion from rostral to caudal, passing continuously through higher-order fields. The pattern of propagating waves was well reproducible and showed only minor changes if different anesthetics were used. The results question the classical "hierarchical" model of cortical areas and demonstrate that the different fields process incoming information as a functional unit.

Kalman meets neuron: the emerging intersection of control theory with neuroscience

Since the 1950s, we have developed mature theories of modern control theory and computational neuroscience with almost no interaction between these disciplines. With the advent of computationally efficient nonlinear Kalman filtering techniques, along with improved neuroscience models that provide increasingly accurate reconstruction of dynamics in a variety of important normal and disease states in the brain, the prospects for a synergistic interaction between these fields are now strong. I show recent examples of the use of nonlinear control theory for the assimilation and control of single neuron dynamics, the modulation of oscillatory wave dynamics in brain cortex, a control framework for Parkinsonian dynamics and seizures, and the use of optimized parameter model networks to assimilate complex network data - the 'consensus set'.

Mapping of contextual modulation in the population response of primary visual cortex

We review the evidence of long-range contextual modulation in V1. Populations of neurons in V1 are activated by a wide variety of stimuli outside of their classical receptive fields (RF), well beyond their surround region. These effects generally involve extra-RF features with an orientation component. The population mapping of orientation preferences to the upper layers of V1 is well understood, as far as the classical RF properties are concerned, and involves organization into pinwheel-like structures. We introduce a novel hypothesis regarding the organization of V1's contextual response. We show that RF and extra-RF orientation preferences are mapped in related ways. Orientation pinwheels are the foci of both types of features. The mapping of contextual features onto the orientation pinwheel has a form that recapitulates the organization of the visual field: an iso-orientation patch within the pinwheel also responds to extra-RF stimuli of the same orientation. We hypothesize that the same form of mapping applies to other stimulus properties that are mapped out in V1, such as colour and contrast selectivity. A specific consequence is that fovea-like properties will be mapped in a systematic way to orientation pinwheels. We review the evidence that cytochrome oxidase blobs comprise the foci of this contextual remapping for colour and low contrasts. Neurodynamics and motion in the visual field are argued to play an important role in the shaping and maintenance of this type of mapping in V1.

Coherence potentials: loss-less, all-or-none network events in the cortex

Transient associations among neurons are thought to underlie memory and behavior. However, little is known about how such associations occur or how they can be identified. Here we recorded ongoing local field potential (LFP) activity at multiple sites within the cortex of awake monkeys and organotypic cultures of cortex. We show that when the composite activity of a local neuronal group exceeds a threshold, its activity pattern, as reflected in the LFP, occurs without distortion at other cortex sites via fast synaptic transmission. These large-amplitude LFPs, which we call coherence potentials, extend up to hundreds of milliseconds and mark periods of loss-less spread of temporal and amplitude information much like action potentials at the single-cell level. However, coherence potentials have an additional degree of freedom in the diversity of their waveforms, which provides a high-dimensional parameter for encoding information and allows identification of particular associations. Such nonlinear behavior is analogous to the spread of ideas and behaviors in social networks.

Distributed dynamical computation in neural circuits with propagating coherent activity patterns

Activity in neural circuits is spatiotemporally organized. Its spatial organization consists of multiple, localized coherent patterns, or patchy clusters. These patterns propagate across the circuits over time. This type of collective behavior has ubiquitously been observed, both in spontaneous activity and evoked responses; its function, however, has remained unclear. We construct a spatially extended, spiking neural circuit that generates emergent spatiotemporal activity patterns, thereby capturing some of the complexities of the patterns observed empirically. We elucidate what kind of fundamental function these patterns can serve by showing how they process information. As self-sustained objects, localized coherent patterns can signal information by propagating across the neural circuit. Computational operations occur when these emergent patterns interact, or collide with each other. The ongoing behaviors of these patterns naturally embody both distributed, parallel computation and cascaded logical operations. Such distributed computations enable the system to work in an inherently flexible and efficient way. Our work leads us to propose that propagating coherent activity patterns are the underlying primitives with which neural circuits carry out distributed dynamical computation.

The brain processes information with extraordinary efficiency, and can perform feats such as effortlessly recognizing objects from among thousands of possibilities within a fraction of a second. This is accomplished because the brain represents and processes information in a distributed fashion and in a dynamical way. This processing is manifested in spatiotemporal neural activity patterns of great complexities within the brain. Here, we construct a spiking neural circuit that can reproduce some of the complexities, which are evident in terms of multiple wave patterns with interactions between each other. We show that their dynamics can support propagating pattern-based computation; spiking wave patterns signal information by propagating across neural circuits, and computational operations occur when they collide with each other. Such dynamical computation contrasts sharply with that done by static and physically fixed logic gates operating in other computing machines such as computers. Moreover, we elucidate that the collective dynamics of multiple, interacting wave patterns enable computation processing implemented in a fundamentally distributed and parallel manner in the neural circuit.

Voltage-sensitive dye imaging: Technique review and models

In this review, we present the voltage-sensitive dye imaging (VSDI) method. The possibility offered for in vivo (and in vitro) brain imaging is unprecedented in terms of spatial and temporal resolution. However, the unresolved multi-component origin of the optical signal encourages us to perform a detailed analysis of the method limitation and the existing models. We propose a biophysical model at a mesoscopic scale in order to understand and interpret this signal.

Neurophysiological changes with age probed by inverse modeling of EEG spectra

OBJECTIVE

To investigate age-associated changes in physiologically-based EEG spectral parameters in the healthy population.

METHODS

Eyes-closed EEG spectra of 1498 healthy subjects aged 6-86 years were fitted to a mean-field model of thalamocortical dynamics in a cross-sectional study. Parameters were synaptodendritic rates, cortical wave decay rates, connection strengths (gains), axonal delays for thalamocortical loops, and power normalizations. Age trends were approximated using smooth asymptotically linear functions with a single turning point. We also considered sex differences and relationships between model parameters and traditional quantitative EEG measures.

RESULTS

The cross-sectional data suggest that changes tend to be most rapid in childhood, generally leveling off at age 15-20 years. Most gains decrease in magnitude with age, as does power normalization. Axonal and dendritic delays decrease in childhood and then increase. Axonal delays and gains show small but significant sex differences.

CONCLUSIONS

Mean-field brain modeling allows interpretation of age-associated EEG trends in terms of physiological processes, including the growth and regression of white matter, influencing axonal delays, and the establishment and pruning of synaptic connections, influencing gains.

SIGNIFICANCE

This study demonstrates the feasibility of inverse modeling of EEG spectra as a noninvasive method for investigating large-scale corticothalamic dynamics, and provides a basis for future comparisons.

Imaging nervous system activity

This unit describes methods for loading ion- and voltage-sensitive dyes into neurons, with a particular focus on the spinal cord as a model system. In addition, we describe the use of these dyes to visualize neural activity. Although the protocols described here concern spinal networks in culture or an intact in vitro preparation, they can be, and have been, widely used in other parts of the nervous system.

Correlations and brain states: from electrophysiology to functional imaging

Neural activity in cortex is correlated, an observation that has traditionally been attributed to neurons receiving input from a shared and limited presynaptic pool. Recent studies have shown that correlations are also strongly influenced by network fluctuations that operate over a range of spatial and temporal scales, extending in some cases across cortical areas. These fluctuations are sensitive to internal states and external drive, so that correlations themselves depend strongly on cognitive state and stimulus properties. Given the potential impact on population coding, this modulation of correlations may play an important role in sensory processing.

Spatiotemporal patterns of cortical activity with bilateral cochlear implants in congenital deafness

Congenital deafness affects developmental processes in the auditory cortex. In this study, local field potentials (LFPs) were mapped at the cortical surface with microelectrodes in response to cochlear implant stimulation. LFPs were compared between hearing controls and congenitally deaf cats (CDCs). Pulsatile electrical stimulation initially evoked cortical activity in the rostral parts of the primary auditory field (A1). This progressed both in the approximate dorsoventral direction (along the isofrequency stripe) and in the rostrocaudal direction. The dorsal branch of the wavefront split into a caudal branch (propagating in A1) and another smaller one propagating rostrally into the AAF (anterior auditory field). After the front reached the caudal border of A1, a "reflection wave" appeared, propagating back rostrally. In total, the waves took approximately 13-15 ms to propagate along A1 and return back. In CDCs, the propagation pattern was significantly disturbed, with a more synchronous activation of distant cortical regions. The maps obtained from contralateral and ipsilateral stimulation overlapped in both groups of animals. Although controls showed differences in the latency-amplitude patterns, cortical waves evoked by contralateral and ipsilateral stimulation were more similar in CDCs. Additionally, in controls, LFPs with contralateral and ipsilateral stimulation were more similar in caudal A1 than in rostral A1. This dichotomy was lost in deaf animals. In conclusion, propagating cortical waves are specific for the contralateral ear, they are affected by auditory deprivation, and the specificity of the cortex for stimulation of the contralateral ear is reduced by deprivation.

The neural origins of shell structure and pattern in aquatic mollusks

We present a model to explain how the neurosecretory system of aquatic mollusks generates their diversity of shell structures and pigmentation patterns. The anatomical and physiological basis of this model sets it apart from other models used to explain shape and pattern. The model reproduces most known shell shapes and patterns and accurately predicts how the pattern alters in response to environmental disruption and subsequent repair. Finally, we connect the model to a larger class of neural models.

Rapid and sensitive mapping of long-range connections in vitro using flavoprotein autofluorescence imaging combined with laser photostimulation

We investigated the use of flavoprotein autofluorescence (FA) as a tool to map long-range neural connections and combined FA with laser-uncaging of glutamate to facilitate rapid long-range mapping in vitro. Using the somatosensory thalamocortical slice, we determined that the spatial resolution of FA is >or=100-200 microm and that the sensitivity for detecting thalamocortical synaptic activity approximates that of whole cell recording. Blockade of ionotropic glutamate receptors with DNQX and AP5 abolished cortical responses to electrical thalamic stimulation. The combination of FA with photostimulation using caged glutamate revealed robust long-distance connectivity patterns that could be readily assessed in slices from the somatosensory, auditory, and visual systems that contained thalamocortical, corticothalamic, or corticocortical connections. We mapped the projection from the ventral posterior nucleus of thalamus (VPM) to the primary somatosensory cortex-barrel field and confirmed topography that had been previously described using more laborious methods. We also produced a novel map of the projections from the VPM to the thalamic reticular nucleus, showing precise topography along the dorsoventral axis. Importantly, only about 30 s were needed to generate the connectivity map (six stimulus locations). These data suggest that FA is a sensitive tool for exploring and measuring connectivity and, when coupled with glutamate photostimulation, can rapidly map long-range projections in a single animal.

Propagating waves of activity in the neocortex: what they are, what they do

The development of voltage-sensitive dyes (VSD) and fast optical imaging techniques have brought us a new tool for examining spatiotemporal patterns of population neuronal activity in the neocortex. Propagating waves have been observed during almost every type of cortical processing examined by VSD imaging or electrode arrays. These waves provide subthreshold depolarization to individual neurons and increase their spiking probability. Therefore, the propagation of the waves sets up a spatiotemporal framework for increased excitability in neuronal populations, which can help to determine when and where the neurons are likely to fire. In this review, first discussed is propagating waves observed in various systems and possible mechanisms for generating and sustaining these waves. Then discussed are wave dynamics as an emergent behavior of the population activity that can, in turn, influence the activity of individual neurons. The functions of spontaneous and sensory-evoked waves remain to be explored. An important next step will be to examine the interaction between dynamics of propagating waves and functions in the cortex, and to verify if cortical processing can be modified when these waves are altered.

Mean-field modeling of the basal ganglia-thalamocortical system. I Firing rates in healthy and parkinsonian states

Parkinsonism leads to various electrophysiological changes in the basal ganglia-thalamocortical system (BGTCS), often including elevated discharge rates of the subthalamic nucleus (STN) and the output nuclei, and reduced activity of the globus pallidus external (GPe) segment. These rate changes have been explained qualitatively in terms of the direct/indirect pathway model, involving projections of distinct striatal populations to the output nuclei and GPe. Although these populations partly overlap, evidence suggests dopamine depletion differentially affects cortico-striato-pallidal connection strengths to the two pallidal segments. Dopamine loss may also decrease the striatal signal-to-noise ratio, reducing both corticostriatal coupling and striatal firing thresholds. Additionally, nigrostriatal degeneration may cause secondary changes including weakened lateral inhibition in the GPe, and mesocortical dopamine loss may decrease intracortical excitation and especially inhibition. Here a mean-field model of the BGTCS is presented with structure and parameter estimates closely based on physiology and anatomy. Changes in model rates due to the possible effects of dopamine loss listed above are compared with experiment. Our results suggest that a stronger indirect pathway, possibly combined with a weakened direct pathway, is compatible with empirical evidence. However, altered corticostriatal connection strengths are probably not solely responsible for substantially increased STN activity often found. A lower STN firing threshold, weaker intracortical inhibition, and stronger striato-GPe inhibition help explain the relatively large increase in STN rate. Reduced GPe-GPe inhibition and a lower GPe firing threshold can account for the comparatively small decrease in GPe rate frequently observed. Changes in cortex, GPe, and STN help normalize the cortical rate, also in accord with experiments. The model integrates the basal ganglia into a unified framework along with an existing thalamocortical model that already accounts for a wide range of electrophysiological phenomena. A companion paper discusses the dynamics and oscillations of this combined system.

Normalization of voltage-sensitive dye signal with functional activity measures

In general, signal amplitude in optical imaging is normalized using the well-established DeltaF/F method, where functional activity is divided by the total fluorescent light flux. This measure is used both directly, as a measure of population activity, and indirectly, to quantify spatial and spatiotemporal activity patterns. Despite its ubiquitous use, the stability and accuracy of this measure has not been validated for voltage-sensitive dye imaging of mammalian neocortex in vivo. In this report, we find that this normalization can introduce dynamic biases. In particular, the DeltaF/F is influenced by dye staining quality, and the ratio is also unstable over the course of experiments. As methods to record and analyze optical imaging signals become more precise, such biases can have an increasingly pernicious impact on the accuracy of findings, especially in the comparison of cytoarchitechtonic areas, in area-of-activation measurements, and in plasticity or developmental experiments. These dynamic biases of the DeltaF/F method may, to an extent, be mitigated by a novel method of normalization, DeltaF/DeltaF(epileptiform). This normalization uses as a reference the measured activity of epileptiform spikes elicited by global disinhibition with bicuculline methiodide. Since this normalization is based on a functional measure, i.e. the signal amplitude of "hypersynchronized" bursts of activity in the cortical network, it is less influenced by staining of non-functional elements. We demonstrate that such a functional measure can better represent the amplitude of population mass action, and discuss alternative functional normalizations based on the amplitude of synchronized spontaneous sleep-like activity. These findings demonstrate that the traditional DeltaF/F normalization of voltage-sensitive dye signals can introduce pernicious inaccuracies in the quantification of neural population activity. They further suggest that normalization-independent metrics such as waveform propagation patterns, oscillations in single detectors, and phase relationships between detector pairs may better capture the biological information which is obtained by high-sensitivity imaging.

Mean-field modeling of the basal ganglia-thalamocortical system. II Dynamics of parkinsonian oscillations

Neuronal correlates of Parkinson's disease (PD) include a shift to lower frequencies in the electroencephalogram (EEG) and enhanced synchronized oscillations at 3-7 and 7-30 Hz in the basal ganglia, thalamus, and cortex. This study describes the dynamics of a recent physiologically based mean-field model of the basal ganglia-thalamocortical system, and shows how it accounts for many key electrophysiological correlates of PD. Its detailed functional connectivity comprises partially segregated direct and indirect pathways through two populations of striatal neurons, a hyperdirect pathway involving a corticosubthalamic projection, thalamostriatal feedback, and local inhibition in striatum and external pallidum (GPe). In a companion paper, realistic steady-state firing rates were obtained for the healthy state, and after dopamine loss modeled by weaker direct and stronger indirect pathways, reduced intrapallidal inhibition, lower firing thresholds of the GPe and subthalamic nucleus (STN), a stronger projection from striatum to GPe, and weaker cortical interactions. Here it is shown that oscillations around 5 and 20 Hz can arise with a strong indirect pathway, which also causes increased synchronization throughout the basal ganglia. Furthermore, increased theta power with progressive nigrostriatal degeneration is correlated with reduced alpha power and peak frequency, in agreement with empirical results. Unlike the hyperdirect pathway, the indirect pathway sustains oscillations with phase relationships that coincide with those found experimentally. Alterations in the responses of basal ganglia to transient stimuli accord with experimental observations. Reduced cortical gains due to both nigrostriatal and mesocortical dopamine loss lead to slower changes in cortical activity and may be related to bradykinesia. Finally, increased EEG power found in some studies may be partly explained by a lower effective GPe firing threshold, reduced GPe-GPe inhibition, and/or weaker intracortical connections in parkinsonian patients. Strict separation of the direct and indirect pathways is not necessary to obtain these results.