Dynamics of spontaneous activity in neocortical slices

The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent "Heterosynaptic" LTD in the Dentate Gyrus In Vivo

Long-term potentiation (LTP) and long-term depression (LTD) are widely accepted to be synaptic mechanisms involved in learning and memory. It remains uncertain, however, which particular activity rules are utilized by hippocampal neurons to induce LTP and LTD in behaving animals. Recent experiments in the dentate gyrus of freely moving rats revealed an unexpected pattern of LTP and LTD from high-frequency perforant path stimulation. While 400 Hz theta-burst stimulation (400-TBS) and 400 Hz delta-burst stimulation (400-DBS) elicited substantial LTP of the tetanized medial path input and, concurrently, LTD of the non-tetanized lateral path input, 100 Hz theta-burst stimulation (100-TBS, a normally efficient LTP protocol for in vitro preparations) produced only weak LTP and concurrent LTD. Here we show in a biophysically realistic compartmental granule cell model that this pattern of results can be accounted for by a voltage-based spike-timing-dependent plasticity (STDP) rule combined with a relatively fast Bienenstock-Cooper-Munro (BCM)-like homeostatic metaplasticity rule, all on a background of ongoing spontaneous activity in the input fibers. Our results suggest that, at least for dentate granule cells, the interplay of STDP-BCM plasticity rules and ongoing pre- and postsynaptic background activity determines not only the degree of input-specific LTP elicited by various plasticity-inducing protocols, but also the degree of associated LTD in neighboring non-tetanized inputs, as generated by the ongoing constitutive activity at these synapses.

The vast majority of computational studies that model synaptic plasticity neglect the fact that in vivo neurons exhibit an ongoing spontaneous spiking which affects the dynamics of synaptic changes. Here we study how key components of learning mechanisms in the brain, namely spike timing-dependent plasticity and metaplasticity, interact with spontaneous activity in the input pathways of the neuron. Using biologically realistic simulations we show that ongoing background activity is a key determinant of the degree of long-term potentiation and long-term depression of synaptic transmission between nerve cells in the hippocampus of freely moving animals. This work helps better understand the computational rules which drive synaptic plasticity in vivo.

Endogenous sequential cortical activity evoked by visual stimuli

Although the functional properties of individual neurons in primary visual cortex have been studied intensely, little is known about how neuronal groups could encode changing visual stimuli using temporal activity patterns. To explore this, we used in vivo two-photon calcium imaging to record the activity of neuronal populations in primary visual cortex of awake mice in the presence and absence of visual stimulation. Multidimensional analysis of the network activity allowed us to identify neuronal ensembles defined as groups of cells firing in synchrony. These synchronous groups of neurons were themselves activated in sequential temporal patterns, which repeated at much higher proportions than chance and were triggered by specific visual stimuli such as natural visual scenes. Interestingly, sequential patterns were also present in recordings of spontaneous activity without any sensory stimulation and were accompanied by precise firing sequences at the single-cell level. Moreover, intrinsic dynamics could be used to predict the occurrence of future neuronal ensembles. Our data demonstrate that visual stimuli recruit similar sequential patterns to the ones observed spontaneously, consistent with the hypothesis that already existing Hebbian cell assemblies firing in predefined temporal sequences could be the microcircuit substrate that encodes visual percepts changing in time.

Breaking the millisecond barrier on SpiNNaker: implementing asynchronous event-based plastic models with microsecond resolution

Spike-based neuromorphic sensors such as retinas and cochleas, change the way in which the world is sampled. Instead of producing data sampled at a constant rate, these sensors output spikes that are asynchronous and event driven. The event-based nature of neuromorphic sensors implies a complete paradigm shift in current perception algorithms toward those that emphasize the importance of precise timing. The spikes produced by these sensors usually have a time resolution in the order of microseconds. This high temporal resolution is a crucial factor in learning tasks. It is also widely used in the field of biological neural networks. Sound localization for instance relies on detecting time lags between the two ears which, in the barn owl, reaches a temporal resolution of 5 μs. Current available neuromorphic computation platforms such as SpiNNaker often limit their users to a time resolution in the order of milliseconds that is not compatible with the asynchronous outputs of neuromorphic sensors. To overcome these limitations and allow for the exploration of new types of neuromorphic computing architectures, we introduce a novel software framework on the SpiNNaker platform. This framework allows for simulations of spiking networks and plasticity mechanisms using a completely asynchronous and event-based scheme running with a microsecond time resolution. Results on two example networks using this new implementation are presented.

Self-organization of synchronous activity propagation in neuronal networks driven by local excitation

Many experimental and theoretical studies have suggested that the reliable propagation of synchronous neural activity is crucial for neural information processing. The propagation of synchronous firing activity in so-called synfire chains has been studied extensively in feed-forward networks of spiking neurons. However, it remains unclear how such neural activity could emerge in recurrent neuronal networks through synaptic plasticity. In this study, we investigate whether local excitation, i.e., neurons that fire at a higher frequency than the other, spontaneously active neurons in the network, can shape a network to allow for synchronous activity propagation. We use two-dimensional, locally connected and heterogeneous neuronal networks with spike-timing dependent plasticity (STDP). We find that, in our model, local excitation drives profound network changes within seconds. In the emergent network, neural activity propagates synchronously through the network. This activity originates from the site of the local excitation and propagates through the network. The synchronous activity propagation persists, even when the local excitation is removed, since it derives from the synaptic weight matrix. Importantly, once this connectivity is established it remains stable even in the presence of spontaneous activity. Our results suggest that synfire-chain-like activity can emerge in a relatively simple way in realistic neural networks by locally exciting the desired origin of the neuronal sequence.

Cell Assembly Signatures Defined by Short-Term Synaptic Plasticity in Cortical Networks

The cell assembly (CA) hypothesis has been used as a conceptual framework to explain how groups of neurons form memories. CAs are defined as neuronal pools with synchronous, recurrent and sequential activity patterns. However, neuronal interactions and synaptic properties that define CAs signatures have been difficult to examine because identities and locations of assembly members are usually unknown. In order to study synaptic properties that define CAs, we used optical and electrophysiological approaches to record activity of identified neurons in mouse cortical cultures. Population analysis and graph theory techniques allowed us to find sequential patterns that represent repetitive transitions between network states. Whole cell pair recordings of neurons participating in repeated sequences demonstrated that synchrony is exhibited by groups of neurons with strong synaptic connectivity (concomitant firing) showing short-term synaptic depression (STD), whereas alternation (sequential firing) is seen in groups of neurons with weaker synaptic connections showing short-term synaptic facilitation (STF). Decreasing synaptic weights of a network promoted the generation of sequential activity patterns, whereas increasing synaptic weights restricted state transitions. Thus in simple cortical networks of real neurons, basic signatures of CAs, the properties that underlie perception and memory in Hebb's original description, are already present.

Rebuilding a realistic corticostriatal "social network" from dissociated cells

Many of the methods available for the study of cortical influences on striatal neurons have serious problems. In vivo the connectivity is so complex that the study of input from an individual cortical neuron to a single striatal cell is nearly impossible. Mixed corticostriatal cultures develop many connections from striatal cells to cortical cells, in striking contrast to the fact that only connections from cortical cells to striatal cells are present in vivo. Furthermore, interneuron populations are over-represented in organotypic cultures. For these reasons, we have developed a method for growing cortical and striatal neurons in separated compartments that allows cortical neurons to innervate striatal cells in culture. The method works equally well for acutely dissociated or cryopreserved neurons and allows a number of manipulations that are not otherwise possible. Either cortical or striatal compartments can be transfected with channel rhodopsins. The activity of both areas can be recorded in multielectrode arrays or individual patch recordings from pairs of cells. Finally, corticostriatal connections can be severed acutely. This procedure enables determination of the importance of corticostriatal interaction in the resting pattern of activity. These cultures also facilitate development of sensitive analytical network methods to track connectivity.

NMDA receptors are the basis for persistent network activity in neocortex slices

During behavioral quiescence the neocortex generates spontaneous slow oscillations that consist of Up and Down states. Up states are short epochs of persistent activity, but their underlying source is unclear. In neocortex slices of adult mice, we monitored several cellular and network variables during the transition between a traditional buffer, which does not cause Up states, and a lower-divalent cation buffer, which leads to the generation of Up states. We found that the resting membrane potential and input resistance of cortical cells did not change with the development of Up states. The synaptic efficacy of excitatory postsynaptic potentials mediated by non-NMDA receptors was slightly reduced, but this is unlikely to facilitate the generation of Up states. On the other hand, we identified two variables that are associated with the generation of Up states: an enhancement of the intrinsic firing excitability of cortical cells and an enhancement of NMDA-mediated responses evoked by electrical or optogenetic stimulation. The fact that blocking NMDA receptors abolishes Up states indicates that the enhancement in intrinsic firing excitability alone is insufficient to generate Up states. NMDA receptors have a crucial role in the generation of Up states in neocortex slices.

Quantitative differences in developmental profiles of spontaneous activity in cortical and hippocampal cultures

BACKGROUND

Neural circuits can spontaneously generate complex spatiotemporal firing patterns during development. This spontaneous activity is thought to help guide development of the nervous system. In this study, we had two aims. First, to characterise the changes in spontaneous activity in cultures of developing networks of either hippocampal or cortical neurons dissociated from mouse. Second, to assess whether there are any functional differences in the patterns of activity in hippocampal and cortical networks.

RESULTS

We used multielectrode arrays to record the development of spontaneous activity in cultured networks of either hippocampal or cortical neurons every 2 or 3 days for the first month after plating. Within a few days of culturing, networks exhibited spontaneous activity. This activity strengthened and then stabilised typically around 21 days in vitro. We quantified the activity patterns in hippocampal and cortical networks using 11 features. Three out of 11 features showed striking differences in activity between hippocampal and cortical networks: (1) interburst intervals are less variable in spike trains from hippocampal cultures; (2) hippocampal networks have higher correlations and (3) hippocampal networks generate more robust theta-bursting patterns. Machine-learning techniques confirmed that these differences in patterning are sufficient to classify recordings reliably at any given age as either hippocampal or cortical networks.

CONCLUSIONS

Although cultured networks of hippocampal and cortical networks both generate spontaneous activity that changes over time, at any given time we can reliably detect differences in the activity patterns. We anticipate that this quantitative framework could have applications in many areas, including neurotoxicity testing and for characterising the phenotype of different mutant mice. All code and data relating to this report are freely available for others to use.

Monitoring activity in neural circuits with genetically encoded indicators

Recent developments in genetically encoded indicators of neural activity (GINAs) have greatly advanced the field of systems neuroscience. As they are encoded by DNA, GINAs can be targeted to genetically defined cellular populations. Combined with fluorescence microscopy, most notably multi-photon imaging, GINAs allow chronic simultaneous optical recordings from large populations of neurons or glial cells in awake, behaving mammals, particularly rodents. This large-scale recording of neural activity at multiple temporal and spatial scales has greatly advanced our understanding of the dynamics of neural circuitry underlying behavior—a critical first step toward understanding the complexities of brain function, such as sensorimotor integration and learning. Here, we summarize the recent development and applications of the major classes of GINAs. In particular, we take an in-depth look at the design of available GINA families with a particular focus on genetically encoded calcium indicators (GCaMPs), sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the GCaMP as an example, we review established sensor optimization pipelines. We also discuss practical considerations for end users of GINAs about experimental methods including approaches for gene delivery, imaging system requirements, and data analysis techniques. With the growing toolbox of GINAs and with new microscopy techniques pushing beyond their current limits, the age of light can finally achieve the goal of broad and dense sampling of neuronal activity across time and brain structures to obtain a dynamic picture of brain function.

Dendritic function in vivo

Dendrites are the predominant entry site for excitatory synaptic potentials in most types of central neurons. There is increasing evidence that dendrites are not just passive transmitting devices but play active roles in synaptic integration through linear and non-linear mechanisms. Frequently, excitatory synapses are formed on dendritic spines. In addition to relaying incoming electrical signals, spines can play important roles in modifying these signals through complex biochemical processes and, thereby, determine learning and memory formation. Here, we review recent advances in our understanding of the function of spines and dendrites in central mammalian neurons in vivo by focusing particularly on insights obtained from Ca(2+) imaging studies.

Ex vivo cultured neuronal networks emit in vivo-like spontaneous activity

Spontaneous neuronal activity is present in virtually all brain regions, but neither its function nor spatiotemporal patterns are fully understood. Ex vivo organotypic slice cultures may offer an opportunity to investigate some aspects of spontaneous activity, because they self-restore their networks that collapsed during slicing procedures. In hippocampal networks, we compared the levels and patterns of in vivo spontaneous activity to those in acute and cultured slices. We found that the firing rates and excitatory synaptic activity in the in vivo hippocampus are more similar to those in slice cultures compared to acute slices. The soft confidence-weighted algorithm, a machine learning technique without human bias, also revealed that hippocampal slice cultures resemble the in vivo hippocampus in terms of the overall tendency of the parameters of spontaneous activity.

Dynamics of self-sustained asynchronous-irregular activity in random networks of spiking neurons with strong synapses

Random networks of integrate-and-fire neurons with strong current-based synapses can, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze the mechanisms underlying the emergence, lifetime and irregularity of such self-sustained activity states. We first demonstrate how the competition between the mean and the variance of the synaptic input leads to a non-monotonic firing-rate transfer in the network. Thus, by increasing the synaptic coupling strength, the system can become bistable: In addition to the quiescent state, a second stable fixed-point at moderate firing rates can emerge by a saddle-node bifurcation. Inherently generated fluctuations of the population firing rate around this non-trivial fixed-point can trigger transitions into the quiescent state. Hence, the trade-off between the magnitude of the population-rate fluctuations and the size of the basin of attraction of the non-trivial rate fixed-point determines the onset and the lifetime of self-sustained activity states. During self-sustained activity, individual neuronal activity is moreover highly irregular, switching between long periods of low firing rate to short burst-like states. We show that this is an effect of the strong synaptic weights and the finite time constant of synaptic and neuronal integration, and can actually serve to stabilize the self-sustained state.

Extrasynaptic glutamate NMDA receptors: key players in striatal function

N-methyl-D-aspartate receptors (NMDAR) are crucial for the function of excitatory neurotransmission and are present at the synapse and on the extrasynaptic membrane. The major nucleus of the basal ganglia, striatum, receives a large glutamatergic excitatory input carrying information about movements and associated sensory stimulation for its proper function. Such bombardment of glutamate synaptic release results in a large extracellular concentration of glutamate that can overcome the neuronal and glial uptake homeostatic systems therefore allowing the stimulation of extrasynaptic glutamate receptors. Here we have studied the participation of their extrasynaptic type in cortically evoked responses or in the presence of NMDARs stimulation. We report that extrasynaptic NMDAR blocker memantine, reduced in a dose-dependent manner cortically induced NMDA excitatory currents in striatal neurons (recorded in zero-Mg(++) plus DNQX 10 μM). Moreover, memantine (2-4 μM) significantly reduced the NMDAR-dependent membrane potential oscillations called up and down states. Recordings of neuronal striatal networks with a fluorescent calcium indicator or with multielectrode arrays (MEA) also showed that memantine reduced in a dose-dependent manner, NMDA-induced excitatory currents and network behavior. We used multielectrode arrays (MEA) to grow segregated cortical and striatal neurons. Once synaptic contacts were developed (>21DIV) recordings of extracellular activity confirmed the cortical drive of spontaneous synchronous discharges in both compartments. After severing connections between compartments, active striatal neurons in the presence of memantine (1 μM) and CNQX (10 μM) were predominantly fast spiking interneurons (FSI). The significance of extrasynaptic receptors in the regulation of striatal function and neuronal network activity is evident.

Visual stimuli recruit intrinsically generated cortical ensembles

The cortical microcircuit is built with recurrent excitatory connections, and it has long been suggested that the purpose of this design is to enable intrinsically driven reverberating activity. To understand the dynamics of neocortical intrinsic activity better, we performed two-photon calcium imaging of populations of neurons from the primary visual cortex of awake mice during visual stimulation and spontaneous activity. In both conditions, cortical activity is dominated by coactive groups of neurons, forming ensembles whose activation cannot be explained by the independent firing properties of their contributing neurons, considered in isolation. Moreover, individual neurons flexibly join multiple ensembles, vastly expanding the encoding potential of the circuit. Intriguingly, the same coactive ensembles can repeat spontaneously and in response to visual stimuli, indicating that stimulus-evoked responses arise from activating these intrinsic building blocks. Although the spatial properties of stimulus-driven and spontaneous ensembles are similar, spontaneous ensembles are active at random intervals, whereas visually evoked ensembles are time-locked to stimuli. We conclude that neuronal ensembles, built by the coactivation of flexible groups of neurons, are emergent functional units of cortical activity and propose that visual stimuli recruit intrinsically generated ensembles to represent visual attributes.

Robust development of synfire chains from multiple plasticity mechanisms

Biological neural networks are shaped by a large number of plasticity mechanisms operating at different time scales. How these mechanisms work together to sculpt such networks into effective information processing circuits is still poorly understood. Here we study the spontaneous development of synfire chains in a self-organizing recurrent neural network (SORN) model that combines a number of different plasticity mechanisms including spike-timing-dependent plasticity, structural plasticity, as well as homeostatic forms of plasticity. We find that the network develops an abundance of feed-forward motifs giving rise to synfire chains. The chains develop into ring-like structures, which we refer to as "synfire rings." These rings emerge spontaneously in the SORN network and allow for stable propagation of activity on a fast time scale. A single network can contain multiple non-overlapping rings suppressing each other. On a slower time scale activity switches from one synfire ring to another maintaining firing rate homeostasis. Overall, our results show how the interaction of multiple plasticity mechanisms might give rise to the robust formation of synfire chains in biological neural networks.

Transfer entropy reconstruction and labeling of neuronal connections from simulated calcium imaging

Neuronal dynamics are fundamentally constrained by the underlying structural network architecture, yet much of the details of this synaptic connectivity are still unknown even in neuronal cultures in vitro. Here we extend a previous approach based on information theory, the Generalized Transfer Entropy, to the reconstruction of connectivity of simulated neuronal networks of both excitatory and inhibitory neurons. We show that, due to the model-free nature of the developed measure, both kinds of connections can be reliably inferred if the average firing rate between synchronous burst events exceeds a small minimum frequency. Furthermore, we suggest, based on systematic simulations, that even lower spontaneous inter-burst rates could be raised to meet the requirements of our reconstruction algorithm by applying a weak spatially homogeneous stimulation to the entire network. By combining multiple recordings of the same in silico network before and after pharmacologically blocking inhibitory synaptic transmission, we show then how it becomes possible to infer with high confidence the excitatory or inhibitory nature of each individual neuron.

Early hypersynchrony in juvenile PINK1(-)/(-) motor cortex is rescued by antidromic stimulation

In Parkinson’s disease (PD), cortical networks show enhanced synchronized activity but whether this precedes motor signs is unknown. We investigated this question in PINK1⁻/⁻ mice, a genetic rodent model of the PARK6 variant of familial PD which shows impaired spontaneous locomotion at 16 months. We used two-photon calcium imaging and whole-cell patch clamp in slices from juvenile (P14–P21) wild-type or PINK1⁻/⁻ mice. We designed a horizontal tilted cortico-subthalamic slice where the only connection between cortex and subthalamic nucleus (STN) is the hyperdirect cortico-subthalamic pathway. We report excessive correlation and synchronization in PINK1⁻/⁻ M1 cortical networks 15 months before motor impairment. The percentage of correlated pairs of neurons and their strength of correlation were higher in the PINK1⁻/⁻ M1 than in the wild type network and the synchronized network events involved a higher percentage of neurons. Both features were independent of thalamo-cortical pathways, insensitive to chronic levodopa treatment of pups, but totally reversed by antidromic invasion of M1 pyramidal neurons by axonal spikes evoked by high frequency stimulation (HFS) of the STN. Our study describes an early excess of synchronization in the PINK1⁻/⁻ cortex and suggests a potential role of antidromic activation of cortical interneurons in network desynchronization. Such backward effect on interneurons activity may be of importance for HFS-induced network desynchronization.

Interneuron firing precedes sequential activation of neuronal ensembles in hippocampal slices

Neuronal firing sequences that occur during behavioral tasks are precisely reactivated in the neocortex and the hippocampus during rest and sleep. These precise firing sequences are likely to reflect latent memory traces, and their reactivation is believed to be essential for memory consolidation and working memory maintenance. However, how the organized repeating patterns emerge through the coordinated interplay of distinct types of neurons remains unclear. In this study, we monitored ongoing spatiotemporal firing patterns using a multi-neuron calcium imaging technique and examined how the activity of individual neurons is associated with repeated ensembles in hippocampal slice cultures. To determine the cell types of the imaged neurons, we applied an optical synapse mapping method that identifies network connectivity among dozens of neurons. We observed that inhibitory interneurons exhibited an increase in their firing rates prior to the onset of repeating sequences, while the overall activity level of excitatory neurons remained unchanged. A specific repeating sequence emerged preferentially after the firing of a specific interneuron that was located close to the neuron first activated in the sequence. The times of repeating sequences could be more precisely predicted based on the activity patterns of inhibitory cells than excitatory cells. In line with these observations, stimulation of a single interneuron could trigger the emergence of repeating sequences. These findings provide a conceptual framework that interneurons serve as a key regulator of initiating sequential spike activity.

Intrinsically active and pacemaker neurons in pluripotent stem cell-derived neuronal populations

Neurons generated from pluripotent stem cells (PSCs) self-organize into functional neuronal assemblies in vitro, generating synchronous network activities. Intriguingly, PSC-derived neuronal assemblies develop spontaneous activities that are independent of external stimulation, suggesting the presence of thus far undetected intrinsically active neurons (IANs). Here, by using mouse embryonic stem cells, we provide evidence for the existence of IANs in PSC-neuronal networks based on extracellular multielectrode array and intracellular patch-clamp recordings. IANs remain active after pharmacological inhibition of fast synaptic communication and possess intrinsic mechanisms required for autonomous neuronal activity. PSC-derived IANs are functionally integrated in PSC-neuronal populations, contribute to synchronous network bursting, and exhibit pacemaker properties. The intrinsic activity and pacemaker properties of the neuronal subpopulation identified herein may be particularly relevant for interventions involving transplantation of neural tissues. IANs may be a key element in the regulation of the functional activity of grafted as well as preexisting host neuronal networks.

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PSC-neuronal assemblies harbor intrinsically active neurons (IANs)

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IANs remain active after inhibition of fast glutamatergic synaptic transmission

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Autonomous activities of PSC IANs depend on persistent active sodium currents

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PSC IANs contribute to concerted network activity and have pacemaker properties

Laminar and Columnar Structure of Sensory-Evoked Multineuronal Spike Sequences in Adult Rat Barrel Cortex In Vivo

One of the most relevant questions regarding the function of the nervous system is how sensory information is represented in populations of cortical neurons. Despite its importance, the manner in which sensory-evoked activity propagates across neocortical layers and columns has yet not been fully characterized. In this study, we took advantage of the distinct organization of the rodent barrel cortex and recorded with multielectrode arrays simultaneously from up to 74 neurons localized in several functionally identified layers and columns of anesthetized adult Wistar rats in vivo. The flow of activity within neuronal populations was characterized by temporally precise spike sequences, which were repeatedly evoked by single-whisker stimulation. The majority of the spike sequences representing instantaneous responses were led by a subgroup of putative inhibitory neurons in the principal column at thalamo-recipient layers, thus revealing the presence of feedforward inhibition. However, later spike sequences were mainly led by infragranular excitatory neurons in neighboring columns. Although the starting point of the sequences was anatomically confined, their ending point was rather scattered, suggesting that the population responses are structurally dispersed. Our data show for the first time the simultaneous intra- and intercolumnar processing of information at high temporal resolution.

Both neurons and astrocytes exhibited tetrodotoxin-resistant metabotropic glutamate receptor-dependent spontaneous slow Ca2+ oscillations in striatum

The striatum plays an important role in linking cortical activity to basal ganglia outputs. Group I metabotropic glutamate receptors (mGluRs) are densely expressed in the medium spiny projection neurons and may be a therapeutic target for Parkinson's disease. The group I mGluRs are known to modulate the intracellular Ca²⁺ signaling. To characterize Ca²⁺ signaling in striatal cells, spontaneous cytoplasmic Ca²⁺ transients were examined in acute slice preparations from transgenic mice expressing green fluorescent protein (GFP) in the astrocytes. In both the GFP-negative cells (putative-neurons) and astrocytes of the striatum, spontaneous slow and long-lasting intracellular Ca²⁺ transients (referred to as slow Ca²⁺ oscillations), which lasted up to approximately 200 s, were found. Neither the inhibition of action potentials nor ionotropic glutamate receptors blocked the slow Ca²⁺ oscillation. Depletion of the intracellular Ca²⁺ store and the blockade of inositol 1,4,5-trisphosphate receptors greatly reduced the transient rate of the slow Ca²⁺ oscillation, and the application of an antagonist against mGluR5 also blocked the slow Ca²⁺ oscillation in both putative-neurons and astrocytes. Thus, the mGluR5-inositol 1,4,5-trisphosphate signal cascade is the primary contributor to the slow Ca²⁺ oscillation in both putative-neurons and astrocytes. The slow Ca²⁺ oscillation features multicellular synchrony, and both putative-neurons and astrocytes participate in the synchronous activity. Therefore, the mGluR5-dependent slow Ca²⁺ oscillation may involve in the neuron-glia interaction in the striatum.

Prefrontal cortex HCN1 channels enable intrinsic persistent neural firing and executive memory function

In many cortical neurons, HCN1 channels are the major contributors to Ih, the hyperpolarization-activated current, which regulates the intrinsic properties of neurons and shapes their integration of synaptic inputs, paces rhythmic activity, and regulates synaptic plasticity. Here, we examine the physiological role of Ih in deep layer pyramidal neurons in mouse prefrontal cortex (PFC), focusing on persistent activity, a form of sustained firing thought to be important for the behavioral function of the PFC during working memory tasks. We find that HCN1 contributes to the intrinsic persistent firing that is induced by a brief depolarizing current stimulus in the presence of muscarinic agonists. Deletion of HCN1 or acute pharmacological blockade of Ih decreases the fraction of neurons capable of generating persistent firing. The reduction in persistent firing is caused by the membrane hyperpolarization that results from the deletion of HCN1 or Ih blockade, rather than a specific role of the hyperpolarization-activated current in generating persistent activity. In vivo recordings show that deletion of HCN1 has no effect on up states, periods of enhanced synaptic network activity. Parallel behavioral studies demonstrate that HCN1 contributes to the PFC-dependent resolution of proactive interference during working memory. These results thus provide genetic evidence demonstrating the importance of HCN1 to intrinsic persistent firing and the behavioral output of the PFC. The causal role of intrinsic persistent firing in PFC-mediated behavior remains an open question.

Connectomics and epilepsy

PURPOSE OF REVIEW

Tremendous advances have occurred in recent years in elucidating basic mechanisms of epilepsy at the level of ion channels and neurotransmitters. Epilepsy, however, is ultimately a disease of functionally and/or structurally aberrant connections between neurons and groups of neurons at the systems level. Recent advances in neuroimaging and electrophysiology now make it possible to investigate structural and functional connectivity of the entire brain, and these techniques are currently being used to investigate diseases that manifest as global disturbances of brain function. Epilepsy is such a disease, and our understanding of the mechanisms underlying the development of epilepsy and the generation of epileptic seizures will undoubtedly benefit from research utilizing these connectomic approaches.

RECENT FINDINGS

MRI using diffusion tensor imaging provides structural information, whereas functional MRI and electroencephalography provide functional information about connectivity at the whole brain level. Optogenetics, tracers, electrophysiological approaches, and calcium imaging provide connectivity information at the level of local circuits. These approaches are revealing important neuronal network disturbances underlying epileptic abnormalities.

SUMMARY

An understanding of the fundamental mechanisms underlying the development of epilepsy and the generation of epileptic seizures will require delineation of the aberrant functional and structural connections of the whole brain. The field of connectomics now provides approaches to accomplish this.

Multineuronal spike sequences repeat with millisecond precision

Cortical microcircuits are nonrandomly wired by neurons. As a natural consequence, spikes emitted by microcircuits are also nonrandomly patterned in time and space. One of the prominent spike organizations is a repetition of fixed patterns of spike series across multiple neurons. However, several questions remain unsolved, including how precisely spike sequences repeat, how the sequences are spatially organized, how many neurons participate in sequences, and how different sequences are functionally linked. To address these questions, we monitored spontaneous spikes of hippocampal CA3 neurons ex vivo using a high-speed functional multineuron calcium imaging (fMCI) technique that allowed us to monitor spikes with millisecond resolution and to record the location of spiking and non-spiking neurons. Multineuronal spike sequences (MSSs) were overrepresented in spontaneous activity compared to the statistical chance level. Approximately 75% of neurons participated in at least one sequence during our observation period. The participants were sparsely dispersed and did not show specific spatial organization. The number of sequences relative to the chance level decreased when larger time frames were used to detect sequences. Thus, sequences were precise at the millisecond level. Sequences often shared common spikes with other sequences; parts of sequences were subsequently relayed by following sequences, generating complex chains of multiple sequences.

Gating of sensory input by spontaneous cortical activity

The activity of neural populations is determined not only by sensory inputs but also by internally generated patterns. During quiet wakefulness, the brain produces spontaneous firing events that can spread over large areas of cortex and have been suggested to underlie processes such as memory recall and consolidation. Here we demonstrate a different role for spontaneous activity in sensory cortex: gating of sensory inputs. We show that population activity in rat auditory cortex is composed of transient 50-100 ms packets of spiking activity that occur irregularly during silence and sustained tone stimuli, but reliably at tone onset. Population activity within these packets had broadly consistent spatiotemporal structure, but the rate and also precise relative timing of action potentials varied between stimuli. Packet frequency varied with cortical state, with desynchronized state activity consistent with superposition of multiple overlapping packets. We suggest that such packets reflect the sporadic opening of a "gate" that allows auditory cortex to broadcast a representation of external sounds to other brain regions.

Differentiation of serum-free embryoid bodies from human induced pluripotent stem cells into networks

Three-dimensional aggregation cultures allow for complex development of differentiated human induced pluripotent stem cells. However, this approach is not easily amenable to live-cell imaging and electrophysiological applications due to the thickness and the geometry of the tissue. Here, we present an improvement on the traditional aggregation method by combining the use of cell culture inserts with serum-free embryoid bodies (SFEBs). The use of this technique allows the structures to maintain their three-dimensional structure while thinning substantially. We demonstrate that this technique can be used for electrophysiological recodings as well as live-cell calcium imaging combined with electrical stimulation, akin to organotypic slice preparations. This provides an important experimental tool that can be used to bridge 3-D structures with traditional monolayer approaches used in stem cell applications.

Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity

Synfire chains have long been proposed to generate precisely timed sequences of neural activity. Such activity has been linked to numerous neural functions including sensory encoding, cognitive and motor responses. In particular, it has been argued that synfire chains underlie the precise spatiotemporal firing patterns that control song production in a variety of songbirds. Previous studies have suggested that the development of synfire chains requires either initial sparse connectivity or strong topological constraints, in addition to any synaptic learning rules. Here, we show that this necessity can be removed by using a previously reported but hitherto unconsidered spike-timing-dependent plasticity (STDP) rule and activity-dependent excitability. Under this rule the network develops stable synfire chains that possess a non-trivial, scalable multi-layer structure, in which relative layer sizes appear to follow a universal function. Using computational modeling and a coarse grained random walk model, we demonstrate the role of the STDP rule in growing, molding and stabilizing the chain, and link model parameters to the resulting structure.

Properties and fate of oligodendrocyte progenitor cells in the corpus callosum, motor cortex, and piriform cortex of the mouse

Oligodendrocyte progenitor cells (OPCs) in the postnatal mouse corpus callosum (CC) and motor cortex (Ctx) reportedly generate only oligodendrocytes (OLs), whereas those in the piriform cortex may also generate neurons. OPCs have also been subdivided based on their expression of voltage-gated ion channels, ability to respond to neuronal activity, and proliferative state. To determine whether OPCs in the piriform cortex have inherently different physiological properties from those in the CC and Ctx, we studied acute brain slices from postnatal transgenic mice in which GFP expression identifies OL lineage cells. We whole-cell patch clamped GFP-expressing (GFP(+)) cells within the CC, Ctx, and anterior piriform cortex (aPC) and used prelabeling with 5-ethynyl-2'-deoxyuridine (EdU) to assess cell proliferation. After recording, slices were immunolabeled and OPCs were defined by strong expression of NG2. NG2(+) OPCs in the white and gray matter proliferated and coexpressed PDGFRα and voltage-gated Na(+) channels (I(Na)). Approximately 70% of OPCs were capable of generating regenerative depolarizations. In addition to OLIG2(+) NG2(+) I(Na)(+) OPCs and OLIG2(+) NG2(neg) I(Na)(neg) OLs, we identified cells with low levels of NG2 limited to the soma or the base of some processes. These cells had a significantly reduced I(Na) and a reduced ability to incorporate EdU when compared with OPCs and probably correspond to early differentiating OLs. By combining EdU labeling and lineage tracing using Pdgfrα-CreER(T2) : R26R-YFP transgenic mice, we double labeled OPCs and traced their fate in the postnatal brain. These OPCs generated OLs but did not generate neurons in the aPC or elsewhere at any time that we examined.

Consistent sequential activity across diverse forms of UP states under ketamine anesthesia

During slow-wave sleep, the neocortex shows complex, self-organized spontaneous activity. Similar slow-wave oscillations are present under anesthesia where massive, persistent network activity (UP states) alternates with periods of generalized neural silence (DOWN states). To investigate the neuronal activity patterns occurring during UP states, we recorded simultaneously from populations of cells in neocortical layer V of ketamine/xylazine-anesthetized rats. UP states formed a diverse class. In particular, simultaneous-onset UP states were typically accompanied by sharp field potentials and 10-14 Hz modulation, and were often grouped in a 3 Hz ('delta') pattern. Longer, slow-onset UP states did not exhibit 10-14 Hz modulation, and showed a slow propagation across recording electrodes ('traveling waves'). Despite this diversity, the temporal patterns of spiking activity were similar across different UP state types. Analysis of cross-correlograms revealed conserved temporal relationships among neurons, with each neuron having specific timing during UP states. As a group, putative interneurons were most active at the beginning of UP states and putative pyramidal cells were active uniformly throughout the duration of UP states. These results show that UP states under ketamine anesthesia have a stable, fine-structured firing pattern despite a large variability in global structure.

Thalamic activation modulates the responses of neurons in rat primary auditory cortex: an in vivo intracellular recording study

Auditory cortical plasticity can be induced through various approaches. The medial geniculate body (MGB) of the auditory thalamus gates the ascending auditory inputs to the cortex. The thalamocortical system has been proposed to play a critical role in the responses of the auditory cortex (AC). In the present study, we investigated the cellular mechanism of the cortical activity, adopting an in vivo intracellular recording technique, recording from the primary auditory cortex (AI) while presenting an acoustic stimulus to the rat and electrically stimulating its MGB. We found that low-frequency stimuli enhanced the amplitudes of sound-evoked excitatory postsynaptic potentials (EPSPs) in AI neurons, whereas high-frequency stimuli depressed these auditory responses. The degree of this modulation depended on the intensities of the train stimuli as well as the intervals between the electrical stimulations and their paired sound stimulations. These findings may have implications regarding the basic mechanisms of MGB activation of auditory cortical plasticity and cortical signal processing.

Rhythmic intrinsic bursting neurons in human neocortex obtained from pediatric patients with epilepsy

Neocortical oscillations result from synchronized activity of a synaptically coupled network and can be strongly influenced by the intrinsic firing properties of individual neurons. As such, the intrinsic electroresponsive properties of individual neurons may have important implications for overall network function. Rhythmic intrinsic bursting (rIB) neurons are of particular interest, as they are poised to initiate and/or strongly influence network oscillations. Although neocortical rIB neurons have been recognized in multiple species, the current study is the first to identify and characterize rIB neurons in the human neocortex. Using whole-cell current-clamp recordings, rIB neurons (n = 12) are identified in human neocortical tissue resected from pediatric patients with intractable epilepsy. In contrast to human regular spiking neurons (n = 12), human rIB neurons exhibit rhythmic bursts of action potentials at frequencies of 0.1-4 Hz. These bursts persist after blockade of fast excitatory neurotransmission and voltage-gated calcium channels. However, bursting is eliminated by subsequent application of the persistent sodium current (I(NaP)) blocker, riluzole. In the presence of riluzole (either 10 or 20 μm), human rIB neurons no longer burst, but fire tonically like regular spiking neurons. These data demonstrate that I(NaP) plays a critical role in intrinsic oscillatory activity observed in rIB neurons in the human neocortex. It is hypothesized that aberrant changes in I(NaP) expression and/or function may ultimately contribute to neurological diseases that are linked to abnormal network activity, such as epilepsy.

Dopaminergic modulation of the striatal microcircuit: receptor-specific configuration of cell assemblies

Selection and inhibition of motor behaviors are related to the coordinated activity and compositional capabilities of striatal cell assemblies. Striatal network activity represents a main step in basal ganglia processing. The dopaminergic system differentially regulates distinct populations of striatal medium spiny neurons (MSNs) through the activation of D(1)- or D(2)-type receptors. Although postsynaptic and presynaptic actions of these receptors are clearly different in MSNs during cell-focused studies, their activation during network activity has shown inconsistent responses. Therefore, using electrophysiological techniques, functional multicell calcium imaging, and neuronal population analysis in rat corticostriatal slices, we describe the effect of selective dopaminergic receptor activation in the striatal network by observing cell assembly configurations. At the microcircuit level, during striatal network activity, the selective activation of either D(1)- or D(2)-type receptors is reflected as overall increases in neuronal synchronization. However, graph theory techniques applied to the transitions between network states revealed receptor-specific configurations of striatal cell assemblies: D(1) receptor activation generated closed trajectories with high recurrence and few alternate routes favoring the selection of specific sequences, whereas D(2) receptor activation created trajectories with low recurrence and more alternate pathways while promoting diverse transitions among neuronal pools. At the single-cell level, the activation of dopaminergic receptors enhanced the negative-slope conductance region (NSCR) in D(1)-type-responsive cells, whereas in neurons expressing D(2)-type receptors, the NSCR was decreased. Consequently, receptor-specific network dynamics most probably result from the interplay of postsynaptic and presynaptic dopaminergic actions.

Classifying heterogeneity of spontaneous up-states: a method for revealing variations in firing probability, engaged neurons and Fano factor

The dynamics of spontaneous and sensory-evoked up-states have been recently compared, in multi-site recordings in vivo and found to have similarities and differences. Also in vitro, this is evident because we here describe a novel computational method to classify into statistically different states the spontaneous reverberating activity recorded from long-term (12-18 days-in vitro) cultured cortical neurons (from 60-site multi-electrode arrays, MEA). State classification was performed by spike number time histograms (SNTH, or other burst features) of excitatory and inhibitory neuron clusters and revealed that in novel identified states the number of engaged neurons or up-state duration can change. To improve the characterization of each state we also computed the firing spike histograms (FSH) which revealed a new facet of the firing probability of clusters. In exemplary functional experiments we show that: (i) up to 6-7 states can be safely categorized during several hours of recordings without observing spike rate changes, (ii) they disappear after a short pharmacological stimulation being replaced with novel states active and living up to 6-8 h, (iii) antagonists in the nM range can split the activity of a homogeneous network into the chronological coexistence of 2 states, one completely different and one not significantly different from control state. In conclusion, we believe that this novel procedure better characterizes the number of functional states of a network and opens up the possibility of predicting the elementary "vocabulary" used by small networks of neurons.

Somatic calcium level reports integrated spiking activity of cerebellar interneurons in vitro and in vivo

We examined the relationship between somatic Ca²⁺ signals and spiking activity of cerebellar molecular layer interneurons (MLIs) in adult mice. Using two-photon microscopy in conjunction with cell-attached recordings in slices, we show that in tonically firing MLIs loaded with high-affinity Ca²⁺ probes, Ca²⁺-dependent fluorescence transients are absent. Spike-triggered averages of fluorescence traces for MLIs spiking at low rates revealed that the fluorescence change associated with an action potential is small (1% of the basal fluorescence). To uncover the relationship between intracellular Ca²⁺ concentration ([Ca²⁺](i)) and firing rates, spikes were transiently silenced with puffs of the GABA(A) receptor agonist muscimol. [Ca²⁺](i) relaxed toward basal levels following a single exponential whose amplitude correlated to the preceding spike frequency. The relaxation time constant was slow (2.5 s) and independent of the probe concentration. Data from parvalbumin (PV)-/- animals indicate that PV controls the amplitude and decay time of spike-triggered averages as well as the time course of [Ca²⁺](i) relaxations following spike silencing. The [Ca²⁺](i) signals were sensitive to the L-type Ca²⁺ channel blocker nimodipine and insensitive to ryanodine. In anesthetized mice, as in slices, fluorescence traces from most MLIs did not show spontaneous transients. They nonetheless responded to muscimol iontophoresis with relaxations similar to those obtained in vitro, suggesting a state of tonic firing with estimated spiking rates ranging from 2 to 30 Hz. Altogether, the [Ca²⁺](i) signal appears to reflect the integral of the spiking activity in MLIs. We propose that the muscimol silencing strategy can be extended to other tonically spiking neurons with similar [Ca²⁺](i) homeostasis.

Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing.

Effects of acoustic stimuli on neuronal activity in the auditory cortex of the rat

Spontaneous activity of cortical neurons exhibits alternative fluctuations of membrane potential consisting of phased depolarization called "up-state" and persistent hyperpolarization called "down-state" during slow wave sleep and anesthesia. Here, we examined the effects of sound stimuli (noise bursts) on neuronal activity by intracellular recording in vivo from the rat auditory cortex (AC). Noise bursts increased the average time in the up-state by 0.81+/-0.65 s (range, 0.27-1.74 s) related to a 10 s recording duration. The rise times of the spontaneous up-events averaged 69.41+/-18.04 ms (range, 40.10-119.21 ms), while those of the sound-evoked up-events were significantly shorter (p<0.001) averaging only 22.54+/-8.81 ms (range, 9.31-45.74 ms). Sound stimulation did not influence ongoing spontaneous up-events. Our data suggest that a sound stimulus does not interfere with ongoing spontaneous neuronal activity in auditory cortex but can evoke new depolarizations in addition to the spontaneous ones.

History-dependent excitability as a single-cell substrate of transient memory for information discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron "sees" through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types.

Investigating and modelling pituitary endocrine network function

Endocrine cells in the mammalian pituitary are arranged into three-dimensional homotypic networks that wire the gland and act to optimise hormone output by allowing the transmission of information between cell ensembles in a temporally precise manner. Despite this, the structure-function relationships that allow cells belonging to these networks to display coordinated activity remain relatively uncharacterised. This review discusses the recent technological advances that have allowed endocrine cell network structure and function to be probed and the mathematical models that can be used to analyse and present the resulting data. In particular, we focus on the mechanisms that allow endocrine cells to dynamically function as a population to drive hormone release as well as the experimental and theoretical methods that are used to track and model information flow through the network.

Dynamics of the Parkinsonian striatal microcircuit: entrainment into a dominant network state

Neuronal synchronization in basal ganglia circuits plays a key role in the encoding of movement, procedural memory storage and habit formation. Striatal dopamine (DA) depletion during Parkinsonism causes abnormal synchronization in corticobasal ganglia loops resulting in motor dysfunction. However, the dynamics of the striatal microcircuit underlying abnormal synchronization in Parkinsonism is poorly understood. Here we used targeted whole-cell recordings, calcium imaging allowing the recording from dozens of cells simultaneously and analytical approaches, to describe the striking alterations in network dynamics that the striatal microcircuit undergoes following DA depletion in a rat model of Parkinson disease (PD): In addition to a significant enhancement of basal neuronal activity frequent periods of spontaneous synchronization were observed. Multidimensional reduction techniques of vectorized network dynamics revealed that increased synchronization resulted from a dominant network state that absorbed most spontaneously active cells. Abnormal synchronous activity can be virtually abolished by glutamatergic antagonists, while blockade of GABAergic transmission facilitates the engagement of striatal cell assemblies in the dominant state. Finally, a dopaminergic receptor agonist was capable of uncoupling neurons from the dominant state. Abnormal synchronization and "locking" into a dominant state may represent the basic neuronal mechanism that underlies movement disorders at the microcircuit level.

Precise spatiotemporal patterns among visual cortical areas and their relation to visual stimulus processing

Visual processing shows a highly distributed organization in which the presentation of a visual stimulus simultaneously activates neurons in multiple columns across several cortical areas. It has been suggested that precise spatiotemporal activity patterns within and across cortical areas play a key role in higher cognitive, motor, and visual functions. In the visual system, these patterns have been proposed to take part in binding stimulus features into a coherent object, i.e., to be involved in perceptual grouping. Using voltage-sensitive dye imaging (VSDI) in behaving monkeys (Macaca fascicularis, males), we simultaneously measured neural population activity in the primary visual cortex (V1) and extrastriate cortex (V2, V4) at high spatial and temporal resolution. We detected time point population events (PEs) in the VSDI signal of each pixel and found that they reflect transient increased neural activation within local populations by establishing their relation to spiking and local field potential activity. Then, we searched for repeating space and time relations between the detected PEs. We demonstrate the following: (1) spatiotemporal patterns occurring within (horizontal) and across (vertical) early visual areas repeat significantly above chance level; (2) information carried in only a few patterns can be used to reliably discriminate between stimulus categories on a single-trial level; (3) the spatiotemporal patterns yielding high classification performance are characterized by late temporal occurrence and top-down propagation, which are consistent with cortical mechanisms involving perceptual grouping. The pattern characteristics and the robust relation between the patterns and the stimulus categories suggest that spatiotemporal activity patterns play an important role in cortical mechanisms of higher visual processing.