Dynamics of spontaneous activity in neocortical slices

Minimum neuron density for synchronized bursts in a rat cortical culture on multi-electrode arrays

To investigate the minimum neuron and neurite densities required for synchronized bursts, we cultured rat cortical neurons on planar multi-electrode arrays (MEAs) at five plating densities (2500, 1000, 500, 250, and 100 cells/mm(2)) using two culture media: Neuron Culture Medium and Dulbecco's Modified Eagle Medium supplemented with serum (DMEM/serum). Long-term recording of spontaneous electrical activity clarified that the cultures exhibiting synchronized bursts required an initial plating density of at least 250 cells/mm(2) for Neuron Culture Medium and 500 cells/mm(2) for DMEM/serum. Immediately after electrical recording, immunocytochemistry of microtubule-associated protein 2 (MAP2) and Neurofilament 200 kD (NF200) was performed directly on MEAs to investigate the actual densities of neurons and neurites forming the networks. Immunofluorescence observation revealed that the construction of complicated neuronal networks required the same initial plating density as for synchronized bursts, and that overly sparse cultures showed significant decreases of neurons and neurites. We also found that the final densities of surviving neurons at 1 month decreased greatly compared with the initial plating densities and became saturated in denser cultures. In addition, the area of neurites and the number of nuclei were saturated in denser cultures. By comparing both the results of electrophysiological recording and immunocytochemical observation, we revealed that there is a minimum threshold of neuron densities that must be met for the exhibition of synchronized bursts. Interestingly, these minimum densities of MAP2-positive final neurons did not differ between the two culture media; the density was approximately 50 neurons/mm(2). This value was obtained in the cultures with the initial plating densities of 250 cells/mm(2) for Neuron Culture Medium and 500 cells/mm(2) for DMEM/serum.

Cellular imaging of visual cortex reveals the spatial and functional organization of spontaneous activity

The cerebral cortex is never silent; even in primary sensory areas there is ongoing neural activity in the absence of sensory input. Correlations in spontaneous activity can provide clues about network structure, but it has been difficult to record from enough nearby neurons to sample these correlations well. We used in vivo two-photon calcium imaging to demonstrate sparse patterns of correlated spontaneous activity among groups of ∼150 simultaneously imaged cells. In cat visual cortex, correlations fell off sharply with distance, by 50% within ∼240 μm, but in the rat there was little dependence on spatial separation up to 400 μm. In both species, cells that responded best to visual contours of a specific orientation were spontaneously co-active, suggesting that functionally related cells are organized into distinct subnetworks. Although these subnetworks are clustered in the cat, they are intermingled in the rodent, arguing for specific connections within the local cortical network.

Optical recording of neuronal spiking activity from unbiased populations of neurons with high spike detection efficiency and high temporal precision

Activity in populations of neurons is essential for cortical function including signaling of information and signal transport. Previous methods have made advances in recording activity from many neurons but have both technical and analytical limitations. Here we present an optical method, dithered random-access functional calcium imaging, to record somatic calcium signals from up to 100 neurons, in vitro and in vivo. We further developed a maximum-likelihood deconvolution algorithm to detect spikes and precise spike timings from the recorded calcium fluorescence signals. Spike detection efficiency and spike timing detection was determined in acute slices of juvenile mice. The results indicate that the combination of the two methods detected precise spiking activity from unbiased and spatially distributed populations of neurons in acute slices with high efficiency of spike detection (>97%), low rate of false positives (0.0023 spikes/s), and high temporal precision. The results further indicate that there is only a small window of excitation intensities where high spike detection can be achieved consistently.

Fast nonnegative deconvolution for spike train inference from population calcium imaging

Fluorescent calcium indicators are becoming increasingly popular as a means for observing the spiking activity of large neuronal populations. Unfortunately, extracting the spike train of each neuron from a raw fluorescence movie is a nontrivial problem. This work presents a fast nonnegative deconvolution filter to infer the approximately most likely spike train of each neuron, given the fluorescence observations. This algorithm outperforms optimal linear deconvolution (Wiener filtering) on both simulated and biological data. The performance gains come from restricting the inferred spike trains to be positive (using an interior-point method), unlike the Wiener filter. The algorithm runs in linear time, and is fast enough that even when simultaneously imaging >100 neurons, inference can be performed on the set of all observed traces faster than real time. Performing optimal spatial filtering on the images further refines the inferred spike train estimates. Importantly, all the parameters required to perform the inference can be estimated using only the fluorescence data, obviating the need to perform joint electrophysiological and imaging calibration experiments.

Stochastic cellular automata model of neural networks

We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons.

Effect of network topology on neuronal encoding based on spatiotemporal patterns of spikes

Despite significant progress in our understanding of the brain at both microscopic and macroscopic scales, the mechanisms by which low-level neuronal behavior gives rise to high-level mental processes such as memory still remain unknown. In this paper, we assess the plausibility and quantify the performance of polychronization, a newly proposed mechanism of neuronal encoding, which has been suggested to underlie a wide range of cognitive phenomena. We then investigate the effect of network topology on the reliability with which input stimuli can be distinguished based on their encoding in the form of so-called polychronous groups or spatiotemporal patterns of spikes. We find that small-world networks perform an order of magnitude better than random ones, enabling reliable discrimination between inputs even when prompted by increasingly incomplete recall cues. Furthermore, we show that small-world architectures operate at significantly reduced energetic costs and that their memory capacity scales favorably with network size. Finally, we find that small-world topologies introduce biologically realistic constraints on the optimal input stimuli, favoring especially the topographic inputs known to exist in many cortical areas. Our results suggest that mammalian cortical networks, by virtue of being both small-world and topographically organized, seem particularly well-suited to information processing through polychronization. This article addresses the fundamental question of encoding in neuroscience. In particular, evidence is presented in support of an emerging model of neuronal encoding in the neocortex based on spatiotemporal patterns of spikes.

Role of pre- and postsynaptic activity in thalamocortical axon branching

Axonal branching is thought to be regulated not only by genetically defined programs but also by neural activity in the developing nervous system. Here we investigated the role of pre- and postsynaptic activity in axon branching in the thalamocortical (TC) projection using organotypic coculture preparations of the thalamus and cortex. Individual TC axons were labeled with enhanced yellow fluorescent protein by transfection into thalamic neurons. To manipulate firing activity, a vector encoding an inward rectifying potassium channel (Kir2.1) was introduced into either thalamic or cortical cells. Firing activity was monitored with multielectrode dishes during culturing. We found that axon branching was markedly suppressed in Kir2.1-overexpressing thalamic cells, in which neural activity was silenced. Similar suppression of TC axon branching was also found when cortical cell activity was reduced by expressing Kir2.1. These results indicate that both pre- and postsynaptic activity is required for TC axon branching during development.

Sequential Reinstatement of Neocortical Activity during Slow Oscillations Depends on Cells' Global Activity

During Slow Wave Sleep (SWS), cortical activity is dominated by endogenous processes modulated by slow oscillations (0.1–1 Hz): cell ensembles fluctuate between states of sustained activity (UP states) and silent epochs (DOWN states). We investigate here the temporal structure of ensemble activity during UP states by means of multiple single unit recordings in the prefrontal cortex of naturally sleeping rats. As previously shown, the firing rate of each PFC cell peaks at a distinct time lag after the DOWN/UP transition in a consistent order. We show here that, conversely, the latency of the first spike after the UP state onset depends primarily on the session-averaged firing rates of cells (which can be considered as an indirect measure of their intrinsic excitability). This latency can be explained by a simple homogeneous process (Poisson model) of cell firing, with sleep averaged firing rates employed as parameters. Thus, at DOWN/UP transitions, neurons are affected both by a slow process, possibly originating in the cortical network, modulating the time course of firing for each cell, and by a fast, relatively stereotyped reinstatement of activity, related mostly to global activity levels.

Activity correlation imaging: visualizing function and structure of neuronal populations

For the analysis of neuronal networks it is an important yet unresolved task to relate the neurons' activities to their morphology. Here we introduce activity correlation imaging to simultaneously visualize the activity and morphology of populations of neurons. To this end we first stain the network's neurons using a membrane-permeable [Ca(2+)] indicator (e.g., Fluo-4/AM) and record their activities. We then exploit the recorded temporal activity patterns as a means of intrinsic contrast to visualize individual neurons' dendritic morphology. The result is a high-contrast, multicolor visualization of the neuronal network. Taking the Xenopus olfactory bulb as an example we show the activities of the mitral/tufted cells of the olfactory bulb as well as their projections into the olfactory glomeruli. This method, yielding both functional and structural information of neuronal populations, will open up unprecedented possibilities for the investigation of neuronal networks.

Spontaneous events outline the realm of possible sensory responses in neocortical populations

Neocortical assemblies produce complex activity patterns both in response to sensory stimuli and spontaneously without sensory input. To investigate the structure of these patterns, we recorded from populations of 40-100 neurons in auditory and somatosensory cortices of anesthetized and awake rats using silicon microelectrodes. Population spike time patterns were broadly conserved across multiple sensory stimuli and spontaneous events. Although individual neurons showed timing variations between stimuli, these were not sufficient to disturb a generally conserved sequential organization observed at the population level, lasting for approximately 100 ms with spiking reliability decaying progressively after event onset. Preserved constraints were also seen in population firing rate vectors, with vectors evoked by individual stimuli occupying subspaces of a larger but still constrained space outlined by the set of spontaneous events. These results suggest that population spike patterns are drawn from a limited "vocabulary," sampled widely by spontaneous events but more narrowly by sensory responses.

Percolation transition at growing spatiotemporal fractal patterns in models of mesoscopic neural networks

Spike packet propagation is modeled in mesoscopic-scale networks, composed of locally and recurrently coupled neural pools, and embedded in a two-dimensional lattice. Site dynamics is governed by three key parameters--pool connectedness probability, synaptic strength (following the steady-state distribution of some realizations of spike-timing-dependent plasticity learning rule), and the neuron refractoriness. Formation of spatiotemporal patterns in our model, synfire chains, exhibits critical behavior, with the emerging percolation phase transition controlled by the probability for nonzero synaptic strength value. Applying the finite-size scaling method, we infer the critical probability dependence on synaptic strength and refractoriness and determine the effects of connection topology on the pertaining percolation clusters fractal dimensions. We find that the directed percolation and the pair contact process with diffusion constitute the relevant universality classes of phase transitions observed in a class of mesoscopic-scale network models, which may be related to recently reported data on in vitro cultures.

Muscarinic enhancement of persistent sodium current synchronizes striatal medium spiny neurons

Network dynamics denoted by synchronous firing of neuronal pools rely on synaptic interactions and intrinsic properties. In striatal medium spiny neurons, N-methyl-d-aspartate (NMDA) receptor activation endows neurons with nonlinear capabilities by inducing a negative-slope conductance region (NSCR) in the current-voltage relationship. Nonlinearities underlie associative learning, procedural memory, and the sequential organization of behavior in basal ganglia nuclei. The cholinergic system modulates the function of medium spiny projection neurons through the activation of muscarinic receptors, increasing the NMDA-induced NSCR. This enhancement is reflected as a change in the NMDA-induced network dynamics, making it more synchronous. Nevertheless, little is known about the contribution of intrinsic properties that promote this activity. To investigate the mechanisms underlying the cholinergic modulation of bistable behavior in the striatum, we used whole cell and calcium-imaging techniques. A persistent sodium current modulated by muscarinic receptor activation participated in the enhancement of the NSCR and the increased network synchrony. These experiments provide evidence that persistent sodium current generates bistable behavior in striatal neurons and contributes to the regulation of synchronous network activity. The neuromodulation of bistable properties could represent a cellular and network mechanism for cholinergic actions in the striatum.

Levels of spontaneous activity and spike responses of cortical neurons to local administration of excitatory amino acids to their dendrites and bodies

Studies of cortical cortex slices showed that spontaneous neuron activity depended on the conditions of transmission of excitation from dendrites to the body. Studies using a measure of the efficiency of dendrosomatic conduction showed that cortical neurons constituted a significantly heterogeneous population. Spike reactions to direct excitation of cell bodies were relatively stable in neurons with different levels of spontaneous activity.

Regional difference in stainability with calcium-sensitive acetoxymethyl-ester probes in mouse brain slices

Loading neurons with membrane permeable Ca2+ indicators is a core experimental procedure in functional multineuron Ca2+ imaging (fMCI), an optical technique for monitoring multiple neuronal activities. Although fMCI has been applied to several brain networks, including cerebral cortex, hippocampus, and cerebellum, no studies have systematically addressed the dye-loading efficiency in different brain regions. Here, we describe the stainability of Oregon Green 488 BAPTA-1AM in mouse acute brain slice preparations. The data are suggestive of the potential usability of fMCI in many brain regions, including olfactory bulb, thalamus, dentate gyrus, habenular nucleus, and pons.

Abnormal network activity in a targeted genetic model of human double cortex

In human patients, cortical dysplasia produced by Doublecortin (DCX) mutations lead to mental retardation and intractable infantile epilepsies, but the underlying mechanisms are not known. DCX(-/-) mice have been generated to investigate this issue. However, they display no neocortical abnormality, lessening their impact on the field. In contrast, in utero knockdown of DCX RNA produces a morphologically relevant cortical band heterotopia in rodents. On this preparation we have now compared the neuronal and network properties of ectopic, overlying, and control neurons in an effort to identify how ectopic neurons generate adverse patterns that will impact cortical activity. We combined dynamic calcium imaging and anatomical and electrophysiological techniques and report now that DCX(-/-)EGFP(+)-labeled ectopic neurons that fail to migrate develop extensive axonal subcortical projections and retain immature properties, and most of them display a delayed maturation of GABA-mediated signaling. Cortical neurons overlying the heterotopia, in contrast, exhibit a massive increase of ongoing glutamatergic synaptic currents reflecting a strong reactive plasticity. Neurons in both experimental fields are more frequently coactive in coherent synchronized oscillations than control cortical neurons. In addition, both fields displayed network-driven oscillations during evoked epileptiform burst. These results show that migration disorders produce major alterations not only in neurons that fail to migrate but also in their programmed target areas. We suggest that this duality play a major role in cortical dysfunction of DCX brains.

Activation of the Cholinergic System Endows Compositional Properties to Striatal Cell Assemblies

Striatal cell assemblies are thought to encode network states related to associative learning, procedural memory, and the sequential organization of behavior. Cholinergic neurotransmission modulates memory processes in the striatum and other brain structures. This work asks if the activity of striatal microcircuits observed in living nervous tissue, with attributes similar to cell assemblies, exhibit some of the properties proposed to be necessary to compose memory traces. Accordingly, we used whole cell and calcium-imaging techniques to investigate the cholinergic modulation of striatal neuron pools that have been reported to exhibit several properties expected from cell assemblies such as synchronous states of activity and the alternation of this activity among different neuron pools. We analyzed the cholinergic modulation of the activity of neuron pools with multidimensional reduction techniques and vectorization of network dynamics. It was found that the activation of the cholinergic system enables striatal cell assemblies with properties that have been posited for recurrent neural artificial networks with memory storage capabilities. Graph theory techniques applied to striatal network states revealed sequences of vectors with a recursive dynamics similar to closed reverberating cycles. The cycles exhibited a modular architecture and a hierarchical organization. It is then concluded that, under certain conditions, the cholinergic system enables the striatal microcircuit with the ability to compose complex sequences of activity. Neuronal recurrent networks with the characteristics encountered in the present experiments are proposed to allow repeated sequences of activity to become memories and repeated memories to compose learned motor procedures.

How does non-random spontaneous activity contribute to brain development?

Highly non-random forms of spontaneous activity are proposed to play an instrumental role in the early development of the visual system. However, both the fundamental properties of spontaneous activity required to drive map formation, as well as the exact role of this information remain largely unknown. Here, a realistic computational model of spontaneous retinal waves is employed to demonstrate that both the amplitude and frequency of waves may play determining roles in retinocollicular map formation. Furthermore, results obtained with different learning rules show that spike precision in the order of milliseconds may be instrumental to neural development: a rule based on precise spike interactions (spike-timing-dependent plasticity) reduced the density of aberrant projections to the SC to a markedly greater extent than a rule based on interactions at much broader time-scale (correlation-based plasticity). Taken together, these results argue for an important role of spontaneous yet highly non-random activity, along with temporally precise learning rules, in the formation of neural circuits.

Agent-based brain modeling by means of hierarchical cooperative coevolution

We address the development of brain-inspired models that will be embedded in robotic systems to support their cognitive abilities. We introduce a novel agent-based coevolutionary computational framework for modeling assemblies of brain areas. Specifically, self-organized agent structures are employed to represent brain areas. In order to support the design of agents, we introduce a hierarchical cooperative coevolutionary (HCCE) scheme that effectively specifies the structural details of autonomous, yet cooperating system components. The design process is facilitated by the capability of the HCCE-based design mechanism to investigate the performance of the model in lesion conditions. Interestingly, HCCE also provides a consistent mechanism to reconfigure (if necessary) the structure of agents, facilitating follow-up modeling efforts. Implemented models are embedded in a simulated robot to support its behavioral capabilities, also demonstrating the validity of the proposed computational framework.

Statistical significance of precisely repeated intracellular synaptic patterns

Can neuronal networks produce patterns of activity with millisecond accuracy? It may seem unlikely, considering the probabilistic nature of synaptic transmission. However, some theories of brain function predict that such precision is feasible and can emerge from the non-linearity of the action potential generation in circuits of connected neurons. Several studies have presented evidence for and against this hypothesis. Our earlier work supported the precision hypothesis, based on results demonstrating that precise patterns of synaptic inputs could be found in intracellular recordings from neurons in brain slices and in vivo. To test this hypothesis, we devised a method for finding precise repeats of activity and compared repeats found in the data to those found in surrogate datasets made by shuffling the original data. Because more repeats were found in the original data than in the surrogate data sets, we argued that repeats were not due to chance occurrence. Mokeichev et al. (2007) challenged these conclusions, arguing that the generation of surrogate data was insufficiently rigorous. We have now reanalyzed our previous data with the methods introduced from Mokeichev et al. (2007). Our reanalysis reveals that repeats are statistically significant, thus supporting our earlier conclusions, while also supporting many conclusions that Mokeichev et al. (2007) drew from their recent in vivo recordings. Moreover, we also show that the conditions under which the membrane potential is recorded contributes significantly to the ability to detect repeats and may explain conflicting results. In conclusion, our reevaluation resolves the methodological contradictions between Ikegaya et al. (2004) and Mokeichev et al. (2007), but demonstrates the validity of our previous conclusion that spontaneous network activity is non-randomly organized.

The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons

Calcium imaging of the spontaneous activity in cortical slices has revealed repeating spatiotemporal patterns of transitions between so-called down states and up states (Ikegaya et al., 2004). Here we fit a model network of stochastic binary neurons to data from these experiments, and in doing so reproduce the distributions of such patterns. We use two versions of this model: (1) an unconnected network in which neurons are activated as independent Poisson processes; and (2) a network with an interaction matrix, estimated from the data, representing effective interactions between the neurons. The unconnected model (model 1) is sufficient to account for the statistics of repeating patterns in 11 of the 15 datasets studied. Model 2, with interactions between neurons, is required to account for pattern statistics of the remaining four. Three of these four datasets are the ones that contain the largest number of transitions, suggesting that long datasets are in general necessary to render interactions statistically visible. We then study the topology of the matrix of interactions estimated for these four datasets. For three of the four datasets, we find sparse matrices with long-tailed degree distributions and an overrepresentation of certain network motifs. The remaining dataset exhibits a strongly interconnected, spatially localized subgroup of neurons. In all cases, we find that interactions between neurons facilitate the generation of long patterns that do not repeat exactly.

Imaging synaptic inhibition throughout the brain via genetically targeted Clomeleon

Here we survey a molecular genetic approach for imaging synaptic inhibition. This approach is based on measuring intracellular chloride concentration ([Cl⁻]_i) with the fluorescent chloride indicator protein, Clomeleon. We first describe several different ways to express Clomeleon in selected populations of neurons in the mouse brain. These methods include targeted viral gene transfer, conditional expression controlled by Cre recombination, and transgenesis based on the neuron-specific promoter, thy1. Next, we evaluate the feasibility of using different lines of thy1::Clomeleon transgenic mice to image synaptic inhibition in several different brain regions: the hippocampus, the deep cerebellar nuclei (DCN), the basolateral nucleus of the amygdala, and the superior colliculus (SC). Activation of hippocampal interneurons caused [Cl⁻]_i to rise transiently in individual postsynaptic CA1 pyramidal neurons. [Cl⁻]_i increased linearly with the number of electrical stimuli in a train, with peak changes as large as 4 mM. These responses were largely mediated by GABA receptors because they were blocked by antagonists of GABA receptors, such as GABAzine and bicuculline. Similar responses to synaptic activity were observed in DCN neurons, amygdalar principal cells, and collicular premotor neurons. However, in contrast to the hippocampus, the responses in these three regions were largely insensitive to antagonists of inhibitory neurotransmitter receptors. This indicates that synaptic activity can also cause Cl⁻ influx through alternate pathways that remain to be identified. We conclude that Clomeleon imaging permits non-invasive, spatiotemporally precise recordings of [Cl⁻]_i in a large variety of neurons, and provides new opportunities for imaging synaptic inhibition and other forms of neuronal chloride signaling.

Spontaneous plasticity of multineuronal activity patterns in activated hippocampal networks

Using functional multineuron imaging with single-cell resolution, we examined how hippocampal networks by themselves change the spatiotemporal patterns of spontaneous activity during the course of emitting spontaneous activity. When extracellular ionic concentrations were changed to those that mimicked in vivo conditions, spontaneous activity was increased in active cell number and activity frequency. When ionic compositions were restored to the control conditions, the activity level returned to baseline, but the weighted spatial dispersion of active cells, as assessed by entropy-based metrics, did not. Thus, the networks can modify themselves by altering the internal structure of their correlated activity, even though they as a whole maintained the same level of activity in space and time.

Of mice and men, and chandeliers

How does the human neocortex reliably propagate information through neural circuits? One mechanism appears to involve relying on strong connections from pyramidal neurons to interneurons and a depolarizing action of cortical chandelier cells.

Spontaneous neuronal burst discharges as dependent and independent variables in the maturation of cerebral cortex tissue cultured in vitro: a review of activity-dependent studies in live 'model' systems for the development of intrinsically generated bioelectric slow-wave sleep patterns

A survey is presented of recent experiments which utilize spontaneous neuronal spike trains as dependent and/or independent variables in developing cerebral cortex cultures when synaptic transmission is interfered with for varying periods of time. Special attention is given to current difficulties in selecting suitable preparations for carrying out biologically relevant developmental studies, and in applying spike-train analysis methods with sufficient resolution to detect activity-dependent age and treatment effects. A hierarchy of synchronized nested burst discharges which approximate early slow-wave sleep patterns in the intact organism is established as a stable basis for isolated cortex function. The complexity of reported long- and short-term homeostatic responses to experimental interference with synaptic transmission is reviewed, and the crucial role played by intrinsically generated bioelectric activity in the maturation of cortical networks is emphasized.

In vivo calcium imaging reveals functional rewiring of single somatosensory neurons after stroke

Functional mapping and microstimulation studies suggest that recovery after stroke damage can be attributed to surviving brain regions taking on the functional roles of lost tissues. Although this model is well supported by data, it is not clear how activity in single neurons is altered in relation to cortical functional maps. It is conceivable that individual surviving neurons could adopt new roles at the expense of their usual function. Alternatively, neurons that contribute to recovery may take on multiple functions and exhibit a wider repertoire of neuronal processing. In vivo two-photon calcium imaging was used in adult mice within reorganized forelimb and hindlimb somatosensory functional maps to determine how the response properties of individual neurons and glia were altered during recovery from ischemic damage over a period of 2-8 weeks. Single-cell calcium imaging revealed that the limb selectivity of individual neurons was altered during recovery from ischemia, such that neurons normally selective for a single contralateral limb processed information from multiple limbs. Altered limb selectivity was most prominent in border regions between stroke-altered forelimb and hindlimb macroscopic map representations, and peaked 1 month after the targeted insult. Two months after stroke, individual neurons near the center of reorganized functional areas became more selective for a preferred limb. These previously unreported forms of plasticity indicate that in adult animals, seemingly hardwired cortical neurons first adopt wider functional roles as they develop strategies to compensate for loss of specific sensory modalities after forms of brain damage such as stroke.

Fast and accurate detection of action potentials from somatic calcium fluctuations

Large-scale recording from a population of neurons is a promising strategy for approaching the study of complex brain functions. Taking advantage of the fact that action potentials reliably evoke transient calcium fluctuations in the cell body, functional multineuron calcium imaging (fMCI) monitors the suprathreshold activity of hundreds of neurons. However, a limitation of fMCI is its semi-manual procedure of spike extraction from somatic calcium fluctuations, which is not only time consuming but is also associated with human errors. Here we describe a novel automatic method that combines principal-component analysis and support vector machine. This simple algorithm determines the timings of the spikes in calcium fluorescence traces more rapidly and reliably than human operators.

Optical monitoring of neuronal activity at high frame rate with a digital random-access multiphoton (RAMP) microscope

Two-photon microscopy offers the promise of monitoring brain activity at multiple locations within intact tissue. However, serial sampling of voxels has been difficult to reconcile with millisecond timescales characteristic of neuronal activity. This is due to the conflicting constraints of scanning speed and signal amplitude. The recent use of acousto-optic deflector scanning to implement random-access multiphoton microscopy (RAMP) potentially allows to preserve long illumination dwell times while sampling multiple points-of-interest at high rates. However, the real-life abilities of RAMP microscopy regarding sensitivity and phototoxicity issues, which have so far impeded prolonged optical recordings at high frame rates, have not been assessed. Here, we describe the design, implementation and characterisation of an optimised RAMP microscope. We demonstrate the application of the microscope by monitoring calcium transients in Purkinje cells and cortical pyramidal cell dendrites and spines. We quantify the illumination constraints imposed by phototoxicity and show that stable continuous high-rate recordings can be obtained. During these recordings the fluorescence signal is large enough to detect spikes with a temporal resolution limited only by the calcium dye dynamics, improving upon previous techniques by at least an order of magnitude.

On how network architecture determines the dominant patterns of spontaneous neural activity

In the absence of sensory stimulation, neocortical circuits display complex patterns of neural activity. These patterns are thought to reflect relevant properties of the network, including anatomical features like its modularity. It is also assumed that the synaptic connections of the network constrain the repertoire of emergent, spontaneous patterns. Although the link between network architecture and network activity has been extensively investigated in the last few years from different perspectives, our understanding of the relationship between the network connectivity and the structure of its spontaneous activity is still incomplete. Using a general mathematical model of neural dynamics we have studied the link between spontaneous activity and the underlying network architecture. In particular, here we show mathematically how the synaptic connections between neurons determine the repertoire of spatial patterns displayed in the spontaneous activity. To test our theoretical result, we have also used the model to simulate spontaneous activity of a neural network, whose architecture is inspired by the patchy organization of horizontal connections between cortical columns in the neocortex of primates and other mammals. The dominant spatial patterns of the spontaneous activity, calculated as its principal components, coincide remarkably well with those patterns predicted from the network connectivity using our theory. The equivalence between the concept of dominant pattern and the concept of attractor of the network dynamics is also demonstrated. This in turn suggests new ways of investigating encoding and storage capabilities of neural networks.

Imaging synaptic inhibition in transgenic mice expressing the chloride indicator, Clomeleon

We describe here a molecular genetic approach for imaging synaptic inhibition. The thy-1 promoter was used to express high levels of Clomeleon, a ratiometric fluorescent indicator for chloride ions, in discrete populations of neurons in the brains of transgenic mice. Clomeleon was functional after chronic expression and provided non-invasive readouts of intracellular chloride concentration ([Cl(-)](i)) in brain slices, allowing us to quantify age-dependent declines in resting [Cl(-)](i) during neuronal development. Activation of hippocampal interneurons caused [Cl(-)](i) to rise transiently in individual postsynaptic pyramidal neurons. [Cl(-)](i) increased in direct proportion to the amount of inhibitory transmission, with peak changes as large as 4 mM. Integrating responses over populations of pyramidal neurons allowed sensitive detection of synaptic inhibition. Thus, Clomeleon imaging permits non-invasive, spatiotemporally resolved recordings of [Cl(-)](i) in a large variety of neurons, opening up new opportunities for imaging synaptic inhibition and other forms of chloride signaling.

Structure of spontaneous UP and DOWN transitions self-organizing in a cortical network model

Synaptic plasticity is considered to play a crucial role in the experience-dependent self-organization of local cortical networks. In the absence of sensory stimuli, cerebral cortex exhibits spontaneous membrane potential transitions between an UP and a DOWN state. To reveal how cortical networks develop spontaneous activity, or conversely, how spontaneous activity structures cortical networks, we analyze the self-organization of a recurrent network model of excitatory and inhibitory neurons, which is realistic enough to replicate UP-DOWN states, with spike-timing-dependent plasticity (STDP). The individual neurons in the self-organized network exhibit a variety of temporal patterns in the two-state transitions. In addition, the model develops a feed-forward network-like structure that produces a diverse repertoire of precise sequences of the UP state. Our model shows that the self-organized activity well resembles the spontaneous activity of cortical networks if STDP is accompanied by the pruning of weak synapses. These results suggest that the two-state membrane potential transitions play an active role in structuring local cortical circuits.

Encoding Network States by Striatal Cell Assemblies

Correlated activity in cortico-basal ganglia circuits plays a key role in the encoding of movement, associative learning and procedural memory. How correlated activity is assembled by striatal microcircuits is not understood. Calcium imaging of striatal neuronal populations, with single-cell resolution, reveals sporadic and asynchronous activity under control conditions. However, N-methyl-d-aspartate (NMDA) application induces bistability and correlated activity in striatal neurons. Widespread neurons within the field of observation present burst firing. Sets of neurons exhibit episodes of recurrent and synchronized bursting. Dimensionality reduction of network dynamics reveals functional states defined by cell assemblies that alternate their activity and display spatiotemporal pattern generation. Recurrent synchronous activity travels from one cell assembly to the other often returning to the original assembly; suggesting a robust structure. An initial search into the factors that sustain correlated activity of neuronal assemblies showed a critical dependence on both intrinsic and synaptic mechanisms: blockage of fast glutamatergic transmission annihilates all correlated firing, whereas blockage of GABAergic transmission locked the network into a single dominant state that eliminates assembly diversity. Reduction of L-type Ca2+-current restrains synchronization. Each cell assembly comprised different cells, but a small set of neurons was shared by different assemblies. A great proportion of the shared neurons was local interneurons with pacemaking properties. The network dynamics set into action by NMDA in the striatal network may reveal important properties of striatal microcircuits under normal and pathological conditions.

Active hippocampal networks undergo spontaneous synaptic modification

The brain is self-writable; as the brain voluntarily adapts itself to a changing environment, the neural circuitry rearranges its functional connectivity by referring to its own activity. How the internal activity modifies synaptic weights is largely unknown, however. Here we report that spontaneous activity causes complex reorganization of synaptic connectivity without any external (or artificial) stimuli. Under physiologically relevant ionic conditions, CA3 pyramidal cells in hippocampal slices displayed spontaneous spikes with bistable slow oscillations of membrane potential, alternating between the so-called UP and DOWN states. The generation of slow oscillations did not require fast synaptic transmission, but their patterns were coordinated by local circuit activity. In the course of generating spontaneous activity, individual neurons acquired bidirectional long-lasting synaptic modification. The spontaneous synaptic plasticity depended on a rise in intracellular calcium concentrations of postsynaptic cells, but not on NMDA receptor activity. The direction and amount of the plasticity varied depending on slow oscillation patterns and synapse locations, and thus, they were diverse in a network. Once this global synaptic refinement occurred, the same neurons now displayed different patterns of spontaneous activity, which in turn exhibited different levels of synaptic plasticity. Thus, active networks continuously update their internal states through ongoing synaptic plasticity. With computational simulations, we suggest that with this slow oscillation-induced plasticity, a recurrent network converges on a more specific state, compared to that with spike timing-dependent plasticity alone.

Network model of spontaneous activity exhibiting synchronous transitions between up and down States

Both in vivo and in vitro recordings indicate that neuronal membrane potentials can make spontaneous transitions between distinct up and down states. At the network level, populations of neurons have been observed to make these transitions synchronously. Although synaptic activity and intrinsic neuron properties play an important role, the precise nature of the processes responsible for these phenomena is not known. Using a computational model, we explore the interplay between intrinsic neuronal properties and synaptic fluctuations. Model neurons of the integrate-and-fire type were extended by adding a nonlinear membrane current. Networks of these neurons exhibit large amplitude synchronous spontaneous fluctuations that make the neurons jump between up and down states, thereby producing bimodal membrane potential distributions. The effect of sensory stimulation on network responses depends on whether the stimulus is applied during an up state or deeply inside a down state. External noise can be varied to modulate the network continuously between two extreme regimes in which it remains permanently in either the up or the down state.

Persistently active, pacemaker-like neurons in neocortex

The neocortex is spontaneously active, however, the origin of this self-generated, patterned activity remains unknown. To detect potential “pacemaker cells,” we use calcium imaging to directly identify neurons that discharge action potentials in the absence of synaptic transmissionin slices from juvenile mouse visual cortex. We characterize 60 of these neurons electrophysiologically and morphologically, finding that they belong to two classes of cells: one class composed of pyramidal neurons with a thin apical dendritic tree and a second class composed of ascending axon interneurons (Martinotti cells) located in layer 5. In both types of neurons, persistent sodium currents are necessary for the generation of the spontaneous activity. Our data demonstrate that subtypes of neocortical neurons have intrinsic mechanisms to generate persistent activity. Like in central pattern generators (CPGs), these neurons may act as “pacemakers” to initiate or pattern spontaneous activity in the neocortex.

Comparative roles of acetylcholine and noradrenaline in controlling the spontaneous activity of cortical neurons

The effects of acetylcholine and noradrenaline on the spike activity of neurons recorded in guinea pig parietal cortex slices were studied. Iontophoretic application of these two neurotransmitters to cortical neurons induced similar responses consisting of slowly developing and prolonged increases in spike activity. Differences in the temperature sensitivity of responses to acetylcholine and noradrenaline were identified. When the incubation medium temperature was increased from 32-34 degrees C to 35-36 degrees C, the effects of acetylcholine on neuron spike activity increased sharply, with the result that neurons which showed no spontaneous activity at 32-34 degrees C became sensitive to acetylcholine. The temperature-dependent increases in the extent of responses to acetylcholine were accompanied by stable increases in the level of spontaneous activity. Responses to application of noradrenaline showed no significant change when the temperature increased from 32-34 degrees C to 35-36 degrees C. Since neuron responses to the iontophoretic application of glutamate, the major excitatory neurotransmitter in the cortex, remained constant over this range of temperatures, the data obtained here lead to the conclusion that acetylcholine is the main regulator of the level of spontaneous activity of cortical neurons.

Variable Timescales of Repeated Spike Patterns in Synfire Chain with Mexican-Hat Connectivity

Repetitions of precise spike patterns observed both in vivo and in vitro have been reported for more than a decade. Studies on the spike volley (a pulse packet) propagating through a homogeneous feedforward network have demonstrated its capability of generating spike patterns with millisecond fidelity. This model is called the synfire chain and suggests a possible mechanism for generating repeated spike patterns (RSPs). The propagation speed of the pulse packet determines the temporal property of RSPs. However, the relationship between propagation speed and network structure is not well understood. We studied a feedforward network with Mexican-hat connectivity by using the leaky integrate-and-fire neuron model and analyzed the network dynamics with the Fokker-Planck equation. We examined the effect of the spatial pattern of pulse packets on RSPs in the network with multistability. Pulse packets can take spatially uniform or localized shapes in a multistable regime, and they propagate with different speeds. These distinct pulse packets generate RSPs with different timescales, but the order of spikes and the ratios between interspike intervals are preserved. This result indicates that the RSPs can be transformed into the same template pattern through the expanding or contracting operation of the timescale.

Homeostatic regulation of eye-specific responses in visual cortex during ocular dominance plasticity

Experience-dependent plasticity is crucial for the precise formation of neuronal connections during development. It is generally thought to depend on Hebbian forms of synaptic plasticity. In addition, neurons possess other, homeostatic means of compensating for changes in sensory input, but their role in cortical plasticity is unclear. We used two-photon calcium imaging to investigate whether homeostatic response regulation contributes to changes of eye-specific responsiveness after monocular deprivation (MD) in mouse visual cortex. Short MD durations decreased deprived-eye responses in neurons with binocular input. Longer MD periods strengthened open-eye responses, and surprisingly, also increased deprived-eye responses in neurons devoid of open-eye input. These bidirectional response adjustments effectively preserved the net visual drive for each neuron. Our finding that deprived-eye responses were either weaker or stronger after MD, depending on the amount of open-eye input a cell received, argues for both Hebbian and homeostatic mechanisms regulating neuronal responsiveness during experience-dependent plasticity.

Analyzing the activity of large populations of neurons: how tractable is the problem?

Understanding how the brain performs computations requires understanding neuronal firing patterns at successive levels of processing-a daunting and seemingly intractable task. Two recent studies have made dramatic progress on this problem by showing how its dimensionality can be reduced. Using the retina as a model system, they demonstrated that multineuronal firing patterns can be predicted by pairwise interactions.

Cortistatin promotes and negatively correlates with slow-wave sleep

Sleep need is characterized by the level of slow-wave activity (SWA) and increases with time spent awake. The molecular nature of this sleep homeostatic process is practically unknown. Here, we show that intracerebroventricular administration of the neuropeptide, cortistatin (CST-14), enhances EEG synchronization by selectively promoting deep slow-wave sleep (SWS) during both the light and dark period in rats. CST-14 also increases the level of slow-wave activity (SWA) within deep SWS during the first two hours following CST-14 administration. Steady-state levels of preprocortistatin mRNA oscillate during the light:dark cycle and are four-fold higher upon total 24-h sleep deprivation, returning progressively to normal levels after eight hours of sleep recovery. Preprocortistatin mRNA is expressed upon sleep deprivation in a particular subset of cortical interneurons that colocalize with c-fos. In contrast, the number of CST-positive cells coexpressing pERK1/2 decreases under sleep deprivation. The capacity of CST-14 to increase SWA, together with preprocortistatin's inverse correlation with time spent in SWS, suggests a potential role in sleep homeostatic processes.

Synchrony of spontaneous calcium activity in mouse neocortex before synaptogenesis

Spontaneous calcium activity can be detected in embryonic mouse cortical slices as fluorescence intensity variations, in the presence of a fluorescent calcium indicator. Current methods to detect and quantify these variations depend heavily on experimenters whose judgement may interfere with measurement. In the present work, we developed new software called CalSignal for automatic detection and tracking of cellular bodies and quantification of spontaneous calcium activity on time-series of confocal fluorescence images. Analysis of 28 neocortical slices revealed that 21.0% of detected cells displayed peaks of fluorescence corresponding to spontaneous activity, with a mean frequency of one peak per 4 min. This activity was blocked in the absence of extracellular calcium but was not modified after depletion of calcium stores with thapsigargin or blockade of voltage-gated calcium channels with Ni2+. Further, statistical analysis of calcium activity revealed concomitant activation of distant cells in 24 slices, and the existence of a significant network of synchrony based on such coactivations in 17 slices out of 28. These networks enclosed 84.3% of active cells, scattered throughout the neocortical wall (mean distance between cellular bodies, 111.7 microm). Finally, it was possible to identify specific cells which were synchronously active with more neighbouring cells than others. The identity of these nodal cells remains to be investigated to fully comprehend the role of spontaneous calcium activity, before synaptogenesis, in shaping cortical neurogenesis.

Thalamocortical Up states: differential effects of intrinsic and extrinsic cortical inputs on persistent activity

During behavioral quiescence, the neocortex generates spontaneous slow oscillations that consist of Up and Down states. Up states are short epochs of persistent activity that resemble the activated neocortex during arousal and cognition. Although Up states are generated within the cortex, the impact of extrinsic (thalamocortical) and intrinsic (intracortical) inputs on the persistent activity is not known. Using thalamocortical slices, we found that the persistent cortical activity during spontaneous Up states effectively drives thalamocortical relay cells through corticothalamic connections. However, thalamic activity can also precede the onset of cortical Up states, which suggests a role of thalamic activity in triggering cortical Up states through thalamocortical connections. In support of this hypothesis, we found that cutting the connections between thalamus and cortex reduced the incidence of spontaneous Up states in the cortex. Consistent with a facilitating role of thalamic activity on Up states, electrical or chemical stimulation of the thalamus triggered cortical Up states very effectively and enhanced those occurring spontaneously. In contrast, stimulation of the cortex triggered Up states only at very low intensities but otherwise had a suppressive effect on Up states. Moreover, cortical stimulation suppressed the facilitating effect of thalamic stimulation on Up states. In conclusion, thalamocortical inputs facilitate and intracortical inputs suppress cortical Up states. Thus, extrinsic and intrinsic cortical inputs differentially regulate persistent activity, which may serve to adjust the processing state of thalamocortical networks during behavior.

GABAergic neurons are less selective to stimulus orientation than excitatory neurons in layer II/III of visual cortex, as revealed by in vivo functional Ca2+ imaging in transgenic mice

Most neurons in the visual cortex are selectively responsive to visual stimulation of a narrow range of orientations, and GABAergic neurons are considered to play a role in the formation of such orientation selectivity. This suggests that response properties of GABAergic neurons may be different from those of excitatory neurons. This view remains unproved, however. To address this issue, we applied in vivo two-photon functional Ca2+ imaging to transgenic mice, in which GABAergic neurons express enhanced green fluorescent protein. Astroglia were stained by an astrocyte-specific dye. The three types of cells, GABAergic neurons, excitatory neurons, and astrocytes, in layer II/III of the visual cortex were differentially identified by using different wavelengths of excitation light and a dichroic mirror for emitted fluorescence, and their responses to moving visual stimuli at different orientations were measured with changes in the intensity of fluorescence of a Ca2+-sensitive dye. We found that almost all GABAergic neurons have orientation-insensitive responses, whereas most of excitatory neurons have orientation-selective responses.

Stochastic emergence of repeating cortical motifs in spontaneous membrane potential fluctuations in vivo

It was recently discovered that subthreshold membrane potential fluctuations of cortical neurons can precisely repeat during spontaneous activity, seconds to minutes apart, both in brain slices and in anesthetized animals. These repeats, also called cortical motifs, were suggested to reflect a replay of sequential neuronal firing patterns. We searched for motifs in spontaneous activity, recorded from the rat barrel cortex and from the cat striate cortex of anesthetized animals, and found numerous repeating patterns of high similarity and repetition rates. To test their significance, various statistics were compared between physiological data and three different types of stochastic surrogate data that preserve dynamical characteristics of the recorded data. We found no evidence for the existence of deterministically generated cortical motifs. Rather, the stochastic properties of cortical motifs suggest that they appear by chance, as a result of the constraints imposed by the coarse dynamics of subthreshold ongoing activity.

Watching neuronal circuit dynamics through functional multineuron calcium imaging (fMCI)

Functional multineuron calcium imaging (fMCI) is a large-scale optical recording technique that monitors the spatiotemporal pattern of action potentials, all at once, from large neuron populations. fMCI has unique advantages, including: (i) simultaneous recording from >1000 neurons in a wide area, (ii) single-cell resolution, (iii) identifiable location of neurons and (iv) detection of non-active neurons during the observation period. We review herein the principle, history, utility and limitations of fMCI.

Metastability of active CA3 networks

The brain is spontaneously active even in the absence of external input. This ongoing background activity impacts neural information processing. We used functional multineuron calcium imaging (fMCI) to analyze the net structure of spontaneous CA3 network activity in hippocampal slice cultures loaded with Oregon Green 488 BAPTA-1 using a spinning disk confocal microscope (10-30 frames/s). Principal component analysis revealed that network states, defined by active cell ensembles, were stable but heterogenous and discrete. These states were stabilized through synaptic activity and maintained against external perturbations. A few discrete states emerged during our observation period of up to 30 min. Networks tended to stay in a single state for tens of seconds and then suddenly jump to a new state. After a state transition, the old state was rarely, if ever, revisited by the network during our observation period. This temporal profile of state transitions could not be simulated by a hidden Markov model, indicating that the state dynamics is nonrandomly organized. Within each state, the pattern of network activity tended to stabilize in a specific configuration. Neither maintenance nor transition of the network states required NMDA receptor activity. These findings suggest that the network states are metastable, rather than multistable, and might be governed by local attractor-like dynamics. The fMCI data analyzed here are available at http://hippocampus.jp/data/

Sequential structure of neocortical spontaneous activity in vivo

Even in the absence of sensory stimulation, the neocortex shows complex spontaneous activity patterns, often consisting of alternating "DOWN" states of generalized neural silence and "UP" states of massive, persistent network activity. To investigate how this spontaneous activity propagates through neuronal assemblies in vivo, we simultaneously recorded populations of 50-200 cortical neurons in layer V of anesthetized and awake rats. Each neuron displayed a virtually unique spike pattern during UP states, with diversity seen amongst both putative pyramidal cells and interneurons, reflecting a complex but stereotypically organized sequential spread of activation through local cortical networks. Spike timing was most precise during the first approximately 100 ms after UP state onset, and decayed as UP states progressed. A subset of UP states propagated as traveling waves, but waves passing a given point in either direction initiated similar local sequences, suggesting local networks as the substrate of sequential firing patterns. A search for repeating motifs indicated that their occurrence and structure was predictable from neurons' individual latencies to UP state onset. We suggest that these stereotyped patterns arise from the interplay of intrinsic cellular conductances and local circuit properties.