Oscillatory entrainment of striatal neurons in freely moving rats

Oscillations and synchrony in basal ganglia circuits may play a key role in the organization of voluntary actions and habits. We recorded single units and local field potentials from multiple striatal and cortical locations simultaneously, over a range of behavioral states. We observed opposite gradients of oscillatory entrainment, with dorsal/lateral striatal neurons entrained to high-voltage spindle oscillations ("spike wave discharges") and ventral/medial striatal neurons entrained to the hippocampal theta rhythm. While the majority of units were likely medium-spiny projection neurons, a second neuronal population showed characteristic features of fast-spiking GABAergic interneurons, including tonic activity, brief waveforms, and high-frequency bursts. These fired at an earlier spindle phase than the main neuronal population, and their density within striatum corresponded closely to the intensity of spindle oscillations. The orchestration of oscillatory activity by networks of striatal interneurons may be an important mechanism in the pathophysiology of neurological disorders such as Parkinson's disease.     

Coupled oscillations mediate directed interactions between prefrontal cortex and hippocampus of the neonatal rat

The coactivation of prefrontal and hippocampal networks in oscillatory rhythms is critical for precise information flow in mnemonic and executive tasks, yet the mechanisms governing its development are still unknown. Here, we demonstrate that already in neonatal rats, patterns of discontinuous oscillatory activity precisely entrain the firing of prefrontal neurons and have distinct spatial and temporal organization over cingulate and prelimbic cortices. Moreover, we show that hippocampal theta bursts drive the generation of neonatal prefrontal oscillations by phase-locking the neuronal firing via axonal pathways. Consequently, functional impairment of the hippocampus reduces the prefrontal activity. With ongoing maturation continuous theta-gamma oscillations emerge and mutually entrain the prejuvenile prefrontal-hippocampal networks. Thus, theta-modulated communication within developing prefrontal-hippocampal networks may be relevant for circuitry refinement and maturation of functional units underlying information storage at adulthood.     

Communication through Resonance in Spiking Neuronal Networks

The cortex processes stimuli through a distributed network of specialized brain areas. This processing requires mechanisms that can route neuronal activity across weakly connected cortical regions. Routing models proposed thus far are either limited to propagation of spiking activity across strongly connected networks or require distinct mechanisms that create local oscillations and establish their coherence between distant cortical areas. Here, we propose a novel mechanism which explains how synchronous spiking activity propagates across weakly connected brain areas supported by oscillations. In our model, oscillatory activity unleashes network resonance that amplifies feeble synchronous signals and promotes their propagation along weak connections (“communication through resonance”). The emergence of coherent oscillations is a natural consequence of synchronous activity propagation and therefore the assumption of different mechanisms that create oscillations and provide coherence is not necessary. Moreover, the phase-locking of oscillations is a side effect of communication rather than its requirement. Finally, we show how the state of ongoing activity could affect the communication through resonance and propose that modulations of the ongoing activity state could influence information processing in distributed cortical networks.     

Prelimbic and infralimbic prefrontal cortex interact during fast network oscillations

Background

The medial prefrontal cortex has been implicated in a variety of cognitive and executive processes such as decision making and working memory. The medial prefrontal cortex of rodents consists of several areas including the prelimbic and infralimbic cortex that are thought to be involved in different aspects of cognitive performance. Despite the distinct roles in cognitive behavior that have been attributed to prelimbic and infralimbic cortex, little is known about neuronal network functioning of these areas, and whether these networks show any interaction during fast network oscillations.

Methodology/Principal Findings

Here we show that fast network oscillations in rat infralimbic cortex slices occur at higher frequencies and with higher power than oscillations in prelimbic cortex. The difference in oscillation frequency disappeared when prelimbic and infralimbic cortex were disconnected.

Conclusions/Significance

Our data indicate that neuronal networks of prelimbic and infralimbic cortex can sustain fast network oscillations independent of each other, but suggest that neuronal networks of prelimbic and infralimbic cortex are interacting during these oscillations.     

Pharmacological Characterization of Cultivated Neuronal Networks: Relevance to Synaptogenesis and Synaptic Connectivity

Mental disorders, such as schizophrenia or Alzheimer’s disease, are associated with impaired synaptogenesis and/or synaptic communication. During development, neurons assemble into neuronal networks, the primary supracellular mediators of information processing. In addition to the orchestrated activation of genetic programs, spontaneous electrical activity and associated calcium signaling have been shown to be critically involved in the maturation of such neuronal networks. We established an in vitro model that recapitulates the maturation of neuronal networks, including spontaneous electrical activity. Upon plating, mouse primary hippocampal neurons grow neurites and interconnect via synapses to form a dish-wide neuronal network. Via live cell calcium imaging, we identified a limited period of time in which the spontaneous activity synchronizes across neurons, indicative of the formation of a functional network. After establishment of network activity, the neurons grow dendritic spines, the density of which was used as a morphological readout for neuronal maturity and connectivity. Hence, quantification of neurite outgrowth, synapse density, spontaneous neuronal activity, and dendritic spine density allowed to study neuronal network maturation from the day of plating until the presence of mature neuronal networks. Via acute pharmacological intervention, we show that synchronized network activity is mediated by the NMDA-R. The balance between kynurenic and quinolinic acid, both neuro-active intermediates in the tryptophan/kynurenine pathway, was shown to be decisive for the maintenance of network activity. Chronic modulation of the neurotrophic support influenced the network formation and revealed the extreme sensitivity of calcium imaging to detect subtle alterations in neuronal physiology. Given the reproducible cultivation in a 96-well setup in combination with fully automated analysis of the calcium recordings, this approach can be used to build a high-content screening assay usable for neurotoxicity screening, target identification/validation, or phenotypic drug screening.     

Self-stabilization of neuronal networks

Between the extreme views concerning ontogenesis (genetic vs. environmental determination), we use a moderate approach: a somehow pre-established neuronal model network reacts to activity deviations (reflecting input to be compensated), and stabilizes itself during a complex feed-back process. Morphogenesis is based on an algorithm formalizing the compensation theory of synaptogenesis (Wolff and Wagner 1983). This algorithm is applied to randomly connected McCulloch-Pitts networks that are able to maintain oscillations of their activity patterns over time. The algorithm can lead to networks which are morphogenetically stable but preserve self-maintained oscillations in activity. This is in contrast to most of the current models of synaptogenesis and synaptic modification based on Hebbian rules of plasticity. Hebbian networks are morphogenetically unstable without additional assumptions. The effects of compensation on structural and functional properties of the networks are described. It is concluded that the compensation theory of synaptogenesis can account for the development of morphogenetically stable neuronal networks out of randomly connected networks via selective stabilization and elimination of synapses.The logic of the compensation algorithm is based on experimental results. The present paper shows that the compensation theory can not only predict the behavior of synaptic populations (Wagner and Wolff, in preparation), but it can also describe the behavior of neurons interconnected in a network, with the resulting additional system properties. The neuronal interactions-leading to equilibrium in certain cases-are a self-organizing process in the sense that all decisions are performed on the individual cell level without knowing the overall network situation or goal.     

Plasticity of recurring spatiotemporal activity patterns in cortical networks

How do neurons encode and store information for long periods of time? Recurring patterns of activity have been reported in various cortical structures and were suggested to play a role in information processing and memory. To study the potential role of bursts of action potentials in memory mechanisms, we investigated patterns of spontaneous multi-single-unit activity in dissociated rat cortical cultures in vitro. Spontaneous spikes were recorded from networks of approximately 50 000 neurons and glia cultured on a grid of 60 extracellular substrate- embedded electrodes (multi-electrode arrays). These networks expressed spontaneous culture- wide bursting from approximately one week in vitro. During bursts, a large portion of the active electrodes showed elevated levels of firing. Spatiotemporal activity patterns within spontaneous bursts were clustered using a correlation-based clustering algorithm, and the occurrences of these burst clusters were tracked over several hours. This analysis revealed spatiotemporally diverse bursts occurring in well-defined patterns, which remained stable for several hours. Activity evoked by strong local tetanic stimulation resulted in significant changes in the occurrences of spontaneous bursts belonging to different clusters, indicating that the dynamical flow of information in the neuronal network had been altered. The diversity of spatiotemporal structure and long-term stability of spontaneous bursts together with their plastic nature strongly suggests that such network patterns could be used as codes for information transfer and the expression of memories stored in cortical networks.     

Functional Calcium Imaging in Developing Cortical Networks

A hallmark pattern of activity in developing nervous systems is spontaneous, synchronized network activity. Synchronized activity has been observed in intact spinal cord, brainstem, retina, cortex and dissociated neuronal culture preparations. During periods of spontaneous activity, neurons depolarize to fire single or bursts of action potentials, activating many ion channels. Depolarization activates voltage-gated calcium channels on dendrites and spines that mediate calcium influx. Highly synchronized electrical activity has been measured from local neuronal networks using field electrodes. This technique enables high temporal sampling rates but lower spatial resolution due to integrated read-out of multiple neurons at one electrode. Single cell resolution of neuronal activity is possible using patch-clamp electrophysiology on single neurons to measure firing activity. However, the ability to measure from a network is limited to the number of neurons patched simultaneously, and typically is only one or two neurons. The use of calcium-dependent fluorescent indicator dyes has enabled the measurement of synchronized activity across a network of cells. This technique gives both high spatial resolution and sufficient temporal sampling to record spontaneous activity of the developing network.A key feature of newly-forming cortical and hippocampal networks during pre- and early postnatal development is spontaneous, synchronized neuronal activity (Katz & Shatz, 1996; Khaziphov & Luhmann, 2006). This correlated network activity is believed to be essential for the generation of functional circuits in the developing nervous system (Spitzer, 2006). In both primate and rodent brain, early electrical and calcium network waves are observed pre- and postnatally in vivo and in vitro (Adelsberger et al., 2005; Garaschuk et al., 2000; Lamblin et al., 1999). These early activity patterns, which are known to control several developmental processes including neuronal differentiation, synaptogenesis and plasticity (Rakic & Komuro, 1995; Spitzer et al., 2004) are of critical importance for the correct development and maturation of the cortical circuitry.In this JoVE video, we demonstrate the methods used to image spontaneous activity in developing cortical networks. Calcium-sensitive indicators, such as Fura 2-AM ester diffuse across the cell membrane where intracellular esterase activity cleaves the AM esters to leave the cell-impermeant form of indicator dye. The impermeant form of indicator has carboxylic acid groups which are able to then detect and bind calcium ions intracellularly.. The fluorescence of the calcium-sensitive dye is transiently altered upon binding to calcium. Single or multi-photon imaging techniques are used to measure the change in photons being emitted from the dye, and thus indicate an alteration in intracellular calcium. Furthermore, these calcium-dependent indicators can be combined with other fluorescent markers to investigate cell types within the active network.     

Inhibitory transmission, activity-dependent ionic changes and neuronal network oscillations

Oscillatory network activity arises from interactions between synaptic and intrinsic membrane properties of neurons. In this review, we summarize general mechanisms of synchronous neuronal oscillations. In addition, we focus on recent experimental and computational studies which suggest that activity-dependent changes of ionic environment can affect both the synaptic and intrinsic neuronal properties and influence the network behavior. GABA(A) receptor (GABA(A)R)-mediated signaling, that is based on Cl(-) and HCO(3)(-) permeability, is thought to be important for the oscillogenesis and synchronization in cortical networks. A remarkable feature of GABAergic synapses is that prolonged GABA(A)R activation may lead to switching from a hyperpolarizing to a depolarizing response. This is partly due to a positive shift of the GABA(A) R reversal potential (E(GABA)) that is generated by GABA-induced Cl(-) accumulation in neurons. Recent studies suggest that activity-dependent E(GABA) changes may have important implications for the mechanisms of gamma oscillations and seizure-like discharges. Thus, a better understanding of the impact of intracellular Cl(-) dynamics on network behavior may provide insights into the mechanisms of physiological and pathological brain rhythms. Combination of experiments and simulations is a promising approach for elucidating which properties of the time-varying ionic environment can shape the dynamics of a given circuit.     

Impaired electrical signaling disrupts gamma frequency oscillations in connexin 36-deficient mice

Neural processing occurs in parallel in distant cortical areas even for simple perceptual tasks. Associated cognitive binding is believed to occur through the interareal synchronization of rhythmic activity in the gamma (30-80 Hz) range. Such oscillations arise as an emergent property of the neuronal network and require conventional chemical neurotransmission. To test the potential role of gap junction-mediated electrical signaling in this network property, we generated mice lacking connexin 36, the major neuronal connexin. Here we show that the loss of this protein disrupts gamma frequency network oscillations in vitro but leaves high frequency (150 Hz) rhythms, which may involve gap junctions between principal cells (Schmitz et al., 2001), unaffected. Thus, specific connexins differentially deployed throughout cortical networks are likely to regulate different functional aspects of neuronal information processing in the mature brain.     

Innate synchronous oscillations in freely-organized small neuronal circuits

Background

Information processing in neuronal networks relies on the network''s ability to generate temporal patterns of action potentials. Although the nature of neuronal network activity has been intensively investigated in the past several decades at the individual neuron level, the underlying principles of the collective network activity, such as the synchronization and coordination between neurons, are largely unknown. Here we focus on isolated neuronal clusters in culture and address the following simple, yet fundamental questions: What is the minimal number of cells needed to exhibit collective dynamics? What are the internal temporal characteristics of such dynamics and how do the temporal features of network activity alternate upon crossover from minimal networks to large networks?

Methodology/Principal Findings

We used network engineering techniques to induce self-organization of cultured networks into neuronal clusters of different sizes. We found that small clusters made of as few as 40 cells already exhibit spontaneous collective events characterized by innate synchronous network oscillations in the range of 25 to 100 Hz. The oscillation frequency of each network appeared to be independent of cluster size. The duration and rate of the network events scale with cluster size but converge to that of large uniform networks. Finally, the investigation of two coupled clusters revealed clear activity propagation with master/slave asymmetry.

Conclusions/Significance

The nature of the activity patterns observed in small networks, namely the consistent emergence of similar activity across networks of different size and morphology, suggests that neuronal clusters self-regulate their activity to sustain network bursts with internal oscillatory features. We therefore suggest that clusters of as few as tens of cells can serve as a minimal but sufficient functional network, capable of sustaining oscillatory activity. Interestingly, the frequencies of these oscillations are similar those observed in vivo.     

The maturation of cortical interneuron diversity: how multiple developmental journeys shape the emergence of proper network function

If the classical functional attribute of cortical GABAergic interneurons is to mediate synaptic inhibition in the adult cortex, it is becoming evident that their major task is instead to shape the spatio-temporal dynamics of the network oscillations that support most brain functions. This complex function involves a division of labour between morpho-physiologically diverse interneuron subtypes. Both the central network function and the bewildering heterogeneity of the interneuron population are especially emphasized during cortical development: at early postnatal stages, a single GABAergic neuron can efficiently pace the activity of hundreds of other cells, whereas some interneuron subtypes are still poorly developed. Given the role of coherent activity in brain development, this confers to GABAergic interneurons a major role in the proper maturation of cortical networks.     

Coemergence of regularity and complexity during neural network development

With the growing recognition that rhythmic and oscillatory patterns are widespread in the brain and play important roles in all aspects of the function of our nervous system, there has been a resurgence of interest in neuronal synchronized bursting activity. Here, we were interested in understanding the development of synchronized bursts as information-bearing neuronal activity patterns. For that, we have monitored the morphological organization and spontaneous activity of neuronal networks cultured on multielectrode-arrays during their self-executed evolvement from a mixture of dissociated cells into an active network. Complex collective network electrical activity evolved from sporadic firing patterns of the single neurons. On the system (network) level, the activity was marked by bursting events with interneuronal synchronization and nonarbitrary temporal ordering. We quantified these individual-to-collective activity transitions using newly-developed system level quantitative measures of time series regularity and complexity. We found that individual neuronal activity before synchronization was characterized by high regularity and low complexity. During neuronal wiring, there was a transient period of reorganization marked by low regularity, which then leads to coemergence of elevated regularity and functional (nonstochastic) complexity. We further investigated the morphology-activity interplay by modeling artificial neuronal networks with different topological organizations and connectivity schemes. The simulations support our experimental results by showing increased levels of complexity of neuronal activity patterns when neurons are wired up and organized in clusters (similar to mature real networks), as well as network-level activity regulation once collective activity forms.     

The hypothesis of the cortical mechanisms of operative memory]

The investigation of neuronal activity of monkey cerebral cortex during delayed spatial choice performance allows to develop a hypothesis about the neuronal networks securing the operative memory. The work of one of them is based on the relay-race and reverberation principles of information transfer. Another neuronal network secures the reliability of the transfer phases of behavioural program. Both of these neuronal networks are represented differently in the prefrontal and parietal associative cortical areas.     

Phase-Coherence Transitions and Communication in the Gamma Range between Delay-Coupled Neuronal Populations

Synchronization between neuronal populations plays an important role in information transmission between brain areas. In particular, collective oscillations emerging from the synchronized activity of thousands of neurons can increase the functional connectivity between neural assemblies by coherently coordinating their phases. This synchrony of neuronal activity can take place within a cortical patch or between different cortical regions. While short-range interactions between neurons involve just a few milliseconds, communication through long-range projections between different regions could take up to tens of milliseconds. How these heterogeneous transmission delays affect communication between neuronal populations is not well known. To address this question, we have studied the dynamics of two bidirectionally delayed-coupled neuronal populations using conductance-based spiking models, examining how different synaptic delays give rise to in-phase/anti-phase transitions at particular frequencies within the gamma range, and how this behavior is related to the phase coherence between the two populations at different frequencies. We have used spectral analysis and information theory to quantify the information exchanged between the two networks. For different transmission delays between the two coupled populations, we analyze how the local field potential and multi-unit activity calculated from one population convey information in response to a set of external inputs applied to the other population. The results confirm that zero-lag synchronization maximizes information transmission, although out-of-phase synchronization allows for efficient communication provided the coupling delay, the phase lag between the populations, and the frequency of the oscillations are properly matched.     

Growth rules for the repair of Asynchronous Irregular neuronal networks after peripheral lesions

Several homeostatic mechanisms enable the brain to maintain desired levels of neuronal activity. One of these, homeostatic structural plasticity, has been reported to restore activity in networks disrupted by peripheral lesions by altering their neuronal connectivity. While multiple lesion experiments have studied the changes in neurite morphology that underlie modifications of synapses in these networks, the underlying mechanisms that drive these changes are yet to be explained. Evidence suggests that neuronal activity modulates neurite morphology and may stimulate neurites to selective sprout or retract to restore network activity levels. We developed a new spiking network model of peripheral lesioning and accurately reproduced the characteristics of network repair after deafferentation that are reported in experiments to study the activity dependent growth regimes of neurites. To ensure that our simulations closely resemble the behaviour of networks in the brain, we model deafferentation in a biologically realistic balanced network model that exhibits low frequency Asynchronous Irregular (AI) activity as observed in cerebral cortex. Our simulation results indicate that the re-establishment of activity in neurons both within and outside the deprived region, the Lesion Projection Zone (LPZ), requires opposite activity dependent growth rules for excitatory and inhibitory post-synaptic elements. Analysis of these growth regimes indicates that they also contribute to the maintenance of activity levels in individual neurons. Furthermore, in our model, the directional formation of synapses that is observed in experiments requires that pre-synaptic excitatory and inhibitory elements also follow opposite growth rules. Lastly, we observe that our proposed structural plasticity growth rules and the inhibitory synaptic plasticity mechanism that also balances our AI network both contribute to the restoration of the network to pre-deafferentation stable activity levels.     

fMRI Resting Slow Fluctuations Correlate with the Activity of Fast Cortico-Cortical Physiological Connections

Recording of slow spontaneous fluctuations at rest using functional magnetic resonance imaging (fMRI) allows distinct long-range cortical networks to be identified. The neuronal basis of connectivity as assessed by resting-state fMRI still needs to be fully clarified, considering that these signals are an indirect measure of neuronal activity, reflecting slow local variations in de-oxyhaemoglobin concentration. Here, we combined fMRI with multifocal transcranial magnetic stimulation (TMS), a technique that allows the investigation of the causal neurophysiological interactions occurring in specific cortico-cortical connections. We investigated whether the physiological properties of parieto-frontal circuits mapped with short-latency multifocal TMS at rest may have some relationship with the resting-state fMRI measures of specific resting-state functional networks (RSNs). Results showed that the activity of fast cortico-cortical physiological interactions occurring in the millisecond range correlated selectively with the coupling of fMRI slow oscillations within the same cortical areas that form part of the dorsal attention network, i.e., the attention system believed to be involved in reorientation of attention. We conclude that resting-state fMRI ongoing slow fluctuations likely reflect the interaction of underlying physiological cortico-cortical connections.     

An integrate-and-fire model for synchronized bursting in a network of cultured cortical neurons

It has been suggested that spontaneous synchronous neuronal activity is an essential step in the formation of functional networks in the central nervous system. The key features of this type of activity consist of bursts of action potentials with associated spikes of elevated cytoplasmic calcium. These features are also observed in networks of rat cortical neurons that have been formed in culture. Experimental studies of these cultured networks have led to several hypotheses for the mechanisms underlying the observed synchronized oscillations. In this paper, bursting integrate-and-fire type mathematical models for regular spiking (RS) and intrinsic bursting (IB) neurons are introduced and incorporated through a small-world connection scheme into a two-dimensional excitatory network similar to those in the cultured network. This computer model exhibits spontaneous synchronous activity through mechanisms similar to those hypothesized for the cultured experimental networks. Traces of the membrane potential and cytoplasmic calcium from the model closely match those obtained from experiments. We also consider the impact on network behavior of the IB neurons, the geometry and the small world connection scheme. Action Editor: David Golomb     

Periodicity, Mixed-Mode Oscillations, and Quasiperiodicityin a Rhythm-Generating Neural Network

We studied patterns of oscillatory neural activity in the network that generates respiratory rhythm in mammals. When isolated in vitro, this network spontaneously generates an inspiratory-related motor rhythm, with stable amplitude from cycle to cycle. We show that progressively elevating neuronal excitability in vitro causes periodic modulation of this inspiratory rhythm, evoking (in order): mixed-mode oscillations, quasiperiodicity, and ultimately disorganized aperiodic activity. Thus, the respiratory network oscillator follows a well defined sequence of behavioral states characterized by dynamical systems theory, which includes discrete stages of periodic and quasiperiodic amplitude modulation and progresses (according to theory) to aperiodic chaos-like behavior. We also observed periodic, mixed-mode periodic, and quasiperiodic breathing patterns in neonatal rodents and human infants in vivo, suggesting that breathing patterns generated by the intact nervous system reflect deterministic neural activity patterns in the underlying rhythm-generating network.     

Activity-dependent clustering of functional synaptic inputs on developing hippocampal dendrites

During brain development, before sensory systems become functional, neuronal networks spontaneously generate repetitive bursts of neuronal activity, which are typically synchronized across many neurons. Such activity patterns have been described on the level of networks and cells, but the fine-structure of inputs received by an individual neuron during spontaneous network activity has not been studied. Here, we used calcium imaging to record activity at many synapses of hippocampal pyramidal neurons simultaneously to establish the activity patterns in the majority of synapses of an entire cell. Analysis of the spatiotemporal patterns of synaptic activity revealed a fine-scale connectivity rule: neighboring synapses (<16?μm intersynapse distance) are more likely to be coactive than synapses that are farther away from each other. Blocking spiking activity or NMDA receptor activation revealed that the clustering of synaptic inputs required neuronal activity, demonstrating a role of developmentally expressed spontaneous activity for connecting neurons with subcellular precision.