Local and thalamic origins of correlated ongoing and sensory-evoked cortical activities

Modular architecture facilitates noise-driven control of synchrony in neuronal networks

High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.

Circuit-selective cell-autonomous regulation of inhibition in pyramidal neurons by Ste20-like kinase

Maintaining an appropriate balance between excitation and inhibition is critical for neuronal information processing. Cortical neurons can cell-autonomously adjust the inhibition they receive to individual levels of excitatory input, but the underlying mechanisms are unclear. We describe that Ste20-like kinase (SLK) mediates cell-autonomous regulation of excitation-inhibition balance in the thalamocortical feedforward circuit, but not in the feedback circuit. This effect is due to regulation of inhibition originating from parvalbumin-expressing interneurons, while inhibition via somatostatin-expressing interneurons is unaffected. Computational modeling shows that this mechanism promotes stable excitatory-inhibitory ratios across pyramidal cells and ensures robust and sparse coding. Patch-clamp RNA sequencing yields genes differentially regulated by SLK knockdown, as well as genes associated with excitation-inhibition balance participating in transsynaptic communication and cytoskeletal dynamics. These data identify a mechanism for cell-autonomous regulation of a specific inhibitory circuit that is critical to ensure that a majority of cortical pyramidal cells participate in information coding.

Dissection of brain-wide resting-state and functional somatosensory circuits by fMRI with optogenetic silencing

To further advance functional MRI (fMRI)-based brain science, it is critical to dissect fMRI activity at the circuit level. To achieve this goal, we combined brain-wide fMRI with neuronal silencing in well-defined regions. Since focal inactivation suppresses excitatory output to downstream pathways, intact input and suppressed output circuits can be separated. Highly specific cerebral blood volume-weighted fMRI was performed with optogenetic stimulation of local GABAergic neurons in mouse somatosensory regions. Brain-wide spontaneous somatosensory networks were found mostly in ipsilateral cortical and subcortical areas, which differed from the bilateral homotopic connections commonly observed in resting-state fMRI data. The evoked fMRI responses to somatosensory stimulation in regions of the somatosensory network were successfully dissected, allowing the relative contributions of spinothalamic (ST), thalamocortical (TC), corticothalamic (CT), corticocortical (CC) inputs, and local intracortical circuits to be determined. The ventral posterior thalamic nucleus receives ST inputs, while the posterior medial thalamic nucleus receives CT inputs from the primary somatosensory cortex (S1) with TC inputs. The secondary somatosensory cortex (S2) receives mostly direct CC inputs from S1 and a few TC inputs from the ventral posterolateral nucleus. The TC and CC input layers in cortical regions were identified by laminar-specific fMRI responses with a full width at half maximum of <150 µm. Long-range synaptic inputs in cortical areas were amplified approximately twofold by local intracortical circuits, which is consistent with electrophysiological recordings. Overall, whole-brain fMRI with optogenetic inactivation revealed brain-wide, population-based, long-range circuits, which could complement data typically collected in conventional microscopic functional circuit studies.

Feedforward mechanisms of cross-orientation interactions in mouse V1

Sensory neurons are modulated by context. For example, in mouse primary visual cortex (V1), neuronal responses to the preferred orientation are modulated by the presence of superimposed orientations ("plaids"). The effects of this modulation are diverse; some neurons are suppressed, while others have larger responses to a plaid than its components. We investigated whether this diversity could be explained by a unified circuit mechanism. We report that this masking is maintained during suppression of cortical activity, arguing against cortical mechanisms. Instead, the heterogeneity of plaid responses is explained by an interaction between stimulus geometry and orientation tuning. Highly selective neurons are uniformly suppressed by plaids, whereas the effects in weakly selective neurons depend on the spatial configuration of the stimulus, transitioning systematically between suppression and facilitation. Thus, the diverse responses emerge as a consequence of the spatial structure of feedforward inputs, with no need to invoke cortical interactions.

Short-Term Facilitation of Long-Range Corticocortical Synapses Revealed by Selective Optical Stimulation

Short-term plasticity regulates the strength of central synapses as a function of previous activity. In the neocortex, direct synaptic interactions between areas play a central role in cognitive function, but the activity-dependent regulation of these long-range corticocortical connections and their impact on a postsynaptic target neuron is unclear. Here, we use an optogenetic strategy to study the connections between mouse primary somatosensory and motor cortex. We found that short-term facilitation was strong in both corticocortical synapses, resulting in far more sustained responses than local intracortical and thalamocortical connections. A major difference between pathways was that the synaptic strength and magnitude of facilitation were distinct for individual excitatory cells located across all cortical layers and specific subtypes of GABAergic neurons. Facilitation was dependent on the presynaptic calcium sensor synaptotagmin-7 and altered by several optogenetic approaches. Current-clamp recordings revealed that during repetitive activation, the short-term dynamics of corticocortical synapses enhanced the excitability of layer 2/3 pyramidal neurons, increasing the probability of spiking with activity. Furthermore, the properties of the connections linking primary with secondary somatosensory cortex resemble those between somatosensory-motor areas. These short-term changes in transmission properties suggest long-range corticocortical synapses are specialized for conveying information over relatively extended periods.

Stimulus Feature-Specific Control of Layer 2/3 Subthreshold Whisker Responses by Layer 4 in the Mouse Primary Somatosensory Cortex

In the barrel field of the rodent primary somatosensory cortex (S1bf), excitatory cells in layer 2/3 (L2/3) display sparse firing but reliable subthreshold response during whisker stimulation. Subthreshold responses encode specific features of the sensory stimulus, for example, the direction of whisker deflection. According to the canonical model for the flow of sensory information across cortical layers, activity in L2/3 is driven by layer 4 (L4). However, L2/3 cells receive excitatory inputs from other regions, raising the possibility that L4 partially drives L2/3 during whisker stimulation. To test this hypothesis, we combined patch-clamp recordings from L2/3 pyramidal neurons in S1bf with selective optogenetic inhibition of L4 during passive whisker stimulation in both anesthetized and awake head-restrained mice. We found that L4 optogenetic inhibition did not abolish the subthreshold whisker-evoked response nor it affected spontaneous membrane potential fluctuations of L2/3 neurons. However, L4 optogenetic inhibition decreased L2/3 subthreshold responses to whisker deflections in the preferred direction, and it increased L2/3 responses to stimuli in the nonpreferred direction, leading to a change in the direction tuning. Our results contribute to reveal the circuit mechanisms underlying the processing of sensory information in the rodent S1bf.

NDNF interneurons in layer 1 gain-modulate whole cortical columns according to an animal's behavioral state

Processing of sensory information in neural circuits is modulated by an animal's behavioral state, but the underlying cellular mechanisms are not well understood. Focusing on the mouse visual cortex, here we analyze the role of GABAergic interneurons that are located in layer 1 and express Ndnf (L1 NDNF INs) in the state-dependent control over sensory processing. We find that the ongoing and sensory-evoked activity of L1 NDNF INs is strongly enhanced when an animal is aroused and that L1 NDNF INs gain-modulate local excitatory neurons selectively during high-arousal states by inhibiting their apical dendrites while disinhibiting their somata via Parvalbumin-expressing interneurons. Because active NDNF INs are evenly spread in L1 and can affect excitatory neurons across all cortical layers, this indicates that the state-dependent activation of L1 NDNF INs and the subsequent shift of inhibition in excitatory neurons toward their apical dendrites gain-modulate sensory processing in whole cortical columns.

Reduction of corpus callosum activity during whisking leads to interhemispheric decorrelation

Interhemispheric correlation between homotopic areas is a major hallmark of cortical physiology and is believed to emerge through the corpus callosum. However, how interhemispheric correlations and corpus callosum activity are affected by behavioral states remains unknown. We performed laminar extracellular and intracellular recordings simultaneously from both barrel cortices in awake mice. We find robust interhemispheric correlations of both spiking and synaptic activities that are reduced during whisking compared to quiet wakefulness. Accordingly, optogenetic inactivation of one hemisphere reveals that interhemispheric coupling occurs only during quiet wakefulness, and chemogenetic inactivation of callosal terminals reduces interhemispheric correlation especially during quiet wakefulness. Moreover, in contrast to the generally elevated firing rate observed during whisking epochs, we find a marked decrease in the activity of imaged callosal fibers. Our results indicate that the reduction in interhemispheric coupling and correlations during active behavior reflects the specific reduction in the activity of callosal neurons.

Functional and Structural Properties of Highly Responsive Somatosensory Neurons in Mouse Barrel Cortex

Sparse population activity is a well-known feature of supragranular sensory neurons in neocortex. The mechanisms underlying sparseness are not well understood because a direct link between the neurons activated in vivo, and their cellular properties investigated in vitro has been missing. We used two-photon calcium imaging to identify a subset of neurons in layer L2/3 (L2/3) of mouse primary somatosensory cortex that are highly active following principal whisker vibrotactile stimulation. These high responders (HRs) were then tagged using photoconvertible green fluorescent protein for subsequent targeting in the brain slice using intracellular patch-clamp recordings and biocytin staining. This approach allowed us to investigate the structural and functional properties of HRs that distinguish them from less active control cells. Compared to less responsive L2/3 neurons, HRs displayed increased levels of stimulus-evoked and spontaneous activity, elevated noise and spontaneous pairwise correlations, and stronger coupling to the population response. Intrinsic excitability was reduced in HRs, while we found no evidence for differences in other electrophysiological and morphological parameters. Thus, the choice of which neurons participate in stimulus encoding may be determined largely by network connectivity rather than by cellular structure and function.

Reversible Block of Cerebellar Outflow Reveals Cortical Circuitry for Motor Coordination

Coordinated movements are achieved by well-timed activation of selected muscles. This process relies on intact cerebellar circuitry, as demonstrated by motor impairments following cerebellar lesions. Based on anatomical connectivity and symptoms observed in cerebellar patients, we hypothesized that cerebellar dysfunction should disrupt the temporal patterns of motor cortical activity, but not the selected motor plan. To test this hypothesis, we reversibly blocked cerebellar outflow in primates while monitoring motor behavior and neural activity. This manipulation replicated the impaired motor timing and coordination characteristic of cerebellar ataxia. We found extensive changes in motor cortical activity, including loss of response transients at movement onset and decoupling of task-related activity. Nonetheless, the spatial tuning of cells was unaffected, and their early preparatory activity was mostly intact. These results indicate that the timing of actions, but not the selection of muscles, is regulated through cerebellar control of motor cortical activity.

Pathway-, layer- and cell-type-specific thalamic input to mouse barrel cortex

Mouse primary somatosensory barrel cortex (wS1) processes whisker sensory information, receiving input from two distinct thalamic nuclei. The first-order ventral posterior medial (VPM) somatosensory thalamic nucleus most densely innervates layer 4 (L4) barrels, whereas the higher-order posterior thalamic nucleus (medial part, POm) most densely innervates L1 and L5A. We optogenetically stimulated VPM or POm axons, and recorded evoked excitatory postsynaptic potentials (EPSPs) in different cell-types across cortical layers in wS1. We found that excitatory neurons and parvalbumin-expressing inhibitory neurons received the largest EPSPs, dominated by VPM input to L4 and POm input to L5A. In contrast, somatostatin-expressing inhibitory neurons received very little input from either pathway in any layer. Vasoactive intestinal peptide-expressing inhibitory neurons received an intermediate level of excitatory input with less apparent layer-specificity. Our data help understand how wS1 neocortical microcircuits might process and integrate sensory and higher-order inputs.

Dynamics and sources of response variability and its coordination in visual cortex

The trial-to-trial response variability in sensory cortices and the extent to which this variability can be coordinated among cortical units have strong implications for cortical signal processing. Yet, little is known about the relative contributions and dynamics of defined sources to the cortical response variability and their correlations across cortical units. To fill this knowledge gap, here we obtained and analyzed multisite local field potential (LFP) recordings from visual cortex of turtles in response to repeated naturalistic movie clips and decomposed cortical across-trial LFP response variability into three defined sources, namely, input, network, and local fluctuations. We found that input fluctuations dominate cortical response variability immediately following stimulus onset, whereas network fluctuations dominate the response variability in the steady state during continued visual stimulation. Concurrently, we found that the network fluctuations dominate the correlations of the variability during the ongoing and steady-state epochs, but not immediately following stimulus onset. Furthermore, simulations of various model networks indicated that (i) synaptic time constants, leading to oscillatory activity, and (ii) synaptic clustering and synaptic depression, leading to spatially constrained pockets of coherent activity, are both essential features of cortical circuits to mediate the observed relative contributions and dynamics of input, network, and local fluctuations to the cortical LFP response variability and their correlations across recording sites. In conclusion, these results show how a mélange of multiscale thalamocortical circuit features mediate a complex stimulus-modulated cortical activity that, when naively related to the visual stimulus alone, appears disguised as high and coordinated across-trial response variability.

Cortical Output Is Gated by Horizontally Projecting Neurons in the Deep Layers

Pyramidal tract neurons (PTs) represent the major output cell type of the mammalian neocortex. Here, we report the origins of the PTs’ ability to respond to a broad range of stimuli with onset latencies that rival or even precede those of their intracortical input neurons. We find that neurons with extensive horizontally projecting axons cluster around the deep-layer terminal fields of primary thalamocortical axons. The strategic location of these corticocortical neurons results in high convergence of thalamocortical inputs, which drive reliable sensory-evoked responses that precede those in other excitatory cell types. The resultant fast and horizontal stream of excitation provides PTs throughout the cortical area with input that acts to amplify additional inputs from thalamocortical and other intracortical populations. The fast onsets and broadly tuned characteristics of PT responses hence reflect a gating mechanism in the deep layers, which assures that sensory-evoked input can be reliably transformed into cortical output.

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Simulations predict in vivo responses for major output cell type of the neocortex

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Simulations reveal strategy how to test the origins of cortical output empirically

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Manipulations confirm that deep-layer corticocortical neurons gate cortical output

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Gating of cortical output originates from deep-layer thalamocortical input stratum

The Dynamical Regime of Sensory Cortex: Stable Dynamics around a Single Stimulus-Tuned Attractor Account for Patterns of Noise Variability

Correlated variability in cortical activity is ubiquitously quenched following stimulus onset, in a stimulus-dependent manner. These modulations have been attributed to circuit dynamics involving either multiple stable states (“attractors”) or chaotic activity. Here we show that a qualitatively different dynamical regime, involving fluctuations about a single, stimulus-driven attractor in a loosely balanced excitatory-inhibitory network (the stochastic “stabilized supralinear network”), best explains these modulations. Given the supralinear input/output functions of cortical neurons, increased stimulus drive strengthens effective network connectivity. This shifts the balance from interactions that amplify variability to suppressive inhibitory feedback, quenching correlated variability around more strongly driven steady states. Comparing to previously published and original data analyses, we show that this mechanism, unlike previous proposals, uniquely accounts for the spatial patterns and fast temporal dynamics of variability suppression. Specifying the cortical operating regime is key to understanding the computations underlying perception.

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A simple network model explains stimulus-tuning of cortical variability suppression

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Inhibition stabilizes recurrently interacting neurons with supralinear I/O functions

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Stimuli strengthen inhibitory stabilization around a stable state, quenching variability

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Single-trial V1 data are compatible with this model and rules out competing proposals

Stereotactic system for accurately targeting deep brain structures in awake head-fixed mice

Deep brain nuclei, such as the amygdala, nucleus basalis, and locus coeruleus, play a crucial role in cognition and behavior. Nonetheless, acutely recording electrical activity from these structures in head-fixed awake rodents has been very challenging due to the fact that head-fixed preparations are not designed for stereotactic accuracy. We overcome this issue by designing the DeepTarget, a system for stereotactic head fixation and recording, which allows for accurately directing recording electrodes or other probes into any desired location in the brain. We then validated it by performing intracellular recordings from optogenetically tagged amygdalar neurons followed by histological reconstruction, which revealed that it is accurate and precise to within ~100 μm. Moreover, in another group of mice we were able to target both the mammillothalamic tract and subthalamic nucleus. This approach can be adapted to any type of extracellular electrode, fiber optic, or other probe in cases where high accuracy is needed in awake, head-fixed rodents.NEW & NOTEWORTHY Accurate targeting of recording electrodes in awake head-restrained rodents is currently beyond our reach. We developed a device for stereotactic implantation of a custom head bar and a recording system that together allow the accurate and precise targeting of any brain structure, including deep and small nuclei. We demonstrated this by performing histology and intracellular recordings in the amygdala of awake mice. The system enables the targeting of any probe to any location in the awake brain.

Thalamus exhibits less sensory variability quenching than cortex

Spiking activity exhibits a large degree of variability across identical trials, which has been shown to be significantly reduced by stimulus onset in a wide range of cortical areas. Whether similar dynamics apply to the thalamus and in particular to the pulvinar is largely unknown. Here, we examined electrophysiological recordings from two adult rhesus macaques performing a perceptual task and comparatively investigated trial-to-trial variability in higher-order thalamus (ventral and dorsal pulvinar), the lateral geniculate nucleus (LGN) and visual cortex (area V4) prior to and following the presentation of a visual stimulus. We found spiking variability during stable fixation prior to stimulus onset to be considerably lower in both pulvinar and the LGN as compared to area V4. In contrast to the prominent variability reduction in V4 upon stimulus onset, variability in the thalamic nuclei was largely unaffected by visual stimulation. There was a small but significant variability decrease in the dorsal pulvinar, but not in the ventral portion of the pulvinar, which is closely connected to visual cortices and would thus have been expected to reflect cortical response properties. This dissociation did not stem from differences in response strength or mean firing rates and indicates fundamental differences in variability quenching between thalamus and cortex.

Correlated states in balanced neuronal networks

Understanding the magnitude and structure of interneuronal correlations and their relationship to synaptic connectivity structure is an important and difficult problem in computational neuroscience. Early studies show that neuronal network models with excitatory-inhibitory balance naturally create very weak spike train correlations, defining the "asynchronous state." Later work showed that, under some connectivity structures, balanced networks can produce larger correlations between some neuron pairs, even when the average correlation is very small. All of these previous studies assume that the local network receives feedforward synaptic input from a population of uncorrelated spike trains. We show that when spike trains providing feedforward input are correlated, the downstream recurrent network produces much larger correlations. We provide an in-depth analysis of the resulting "correlated state" in balanced networks and show that, unlike the asynchronous state, it produces a tight excitatory-inhibitory balance consistent with in vivo cortical recordings.

Single-Cell Membrane Potential Fluctuations Evince Network Scale-Freeness and Quasicriticality

What information single neurons receive about general neural circuit activity is a fundamental question for neuroscience. Somatic membrane potential (V _m) fluctuations are driven by the convergence of synaptic inputs from a diverse cross-section of upstream neurons. Furthermore, neural activity is often scale-free, implying that some measurements should be the same, whether taken at large or small scales. Together, convergence and scale-freeness support the hypothesis that single V _m recordings carry useful information about high-dimensional cortical activity. Conveniently, the theory of "critical branching networks" (one purported explanation for scale-freeness) provides testable predictions about scale-free measurements that are readily applied to V _m fluctuations. To investigate, we obtained whole-cell current-clamp recordings of pyramidal neurons in visual cortex of turtles with unknown genders. We isolated fluctuations in V _m below the firing threshold and analyzed them by adapting the definition of "neuronal avalanches" (i.e., spurts of population spiking). The V _m fluctuations which we analyzed were scale-free and consistent with critical branching. These findings recapitulated results from large-scale cortical population data obtained separately in complementary experiments using microelectrode arrays described previously (Shew et al., 2015). Simultaneously recorded single-unit local field potential did not provide a good match, demonstrating the specific utility of V _m Modeling shows that estimation of dynamical network properties from neuronal inputs is most accurate when networks are structured as critical branching networks. In conclusion, these findings extend evidence of critical phenomena while also establishing subthreshold pyramidal neuron V _m fluctuations as an informative gauge of high-dimensional cortical population activity.SIGNIFICANCE STATEMENT The relationship between membrane potential (V _m) dynamics of single neurons and population dynamics is indispensable to understanding cortical circuits. Just as important to the biophysics of computation are emergent properties such as scale-freeness, where critical branching networks offer insight. This report makes progress on both fronts by comparing statistics from single-neuron whole-cell recordings with population statistics obtained with microelectrode arrays. Not only are fluctuations of somatic V _m scale-free, they match fluctuations of population activity. Thus, our results demonstrate appropriation of the brain's own subsampling method (convergence of synaptic inputs) while extending the range of fundamental evidence for critical phenomena in neural systems from the previously observed mesoscale (fMRI, LFP, population spiking) to the microscale, namely, V _m fluctuations.

Membrane Potential Correlates of Network Decorrelation and Improved SNR by Cholinergic Activation in the Somatosensory Cortex

The nucleus basalis (NB) projects cholinergic axons to the cortex, where they play a major role in arousal, attention, and learning. Cholinergic inputs shift cortical dynamics from synchronous to asynchronous and improve the signal-to-noise ratio (SNR) of sensory responses. However, the underlying mechanisms of these changes remain unclear. Using simultaneous extracellular and whole-cell patch recordings in layer 4 of the mouse barrel cortex, we show that electrical or optogenetic activation of the cholinergic system has a differential effect on ongoing and sensory evoked activities. Cholinergic activation profoundly reduced the large spontaneous fluctuations in membrane potential and decorrelated ongoing activity. However, NB stimulation had no effect on the response to whisker stimulation or on signal correlations. These effects of cholinergic activation provide a unified explanation for the increased SNR of sensory response and for the reduction in noise correlations and explain the shift into the desynchronized cortical state, which are the hallmarks of arousal and attention.SIGNIFICANCE STATEMENT Attention increases the signal-to-noise ratio (SNR) of cortical sensory response, which may reflect either reduction in background firing rate or increased sensory response. Extracellular recordings showed that attention also reduces the correlation in network activity. These effects are partially mediated by cholinergic axons from the nucleus basalis projecting to the entire cortex. To reveal the cellular and synaptic correlates of these cholinergic effects, we performed simultaneous intracellular and LFP recordings in the somatosensory cortex. Global or local cholinergic activation increased the SNR of sensory response mainly by reducing the rate and amplitude of background synaptic activity and also reduced network correlations. Therefore, coding of sensory information is enhanced by the cholinergic system mainly due to a reduction in spontaneous activity.

Correlation of Synaptic Inputs in the Visual Cortex of Awake, Behaving Mice

The subthreshold mechanisms that underlie neuronal correlations in awake animals are poorly understood. Here, we perform dual whole-cell recordings in the visual cortex (V1) of awake mice to investigate membrane potential (Vm) correlations between upper-layer sensory neurons. We find that the membrane potentials of neighboring neurons display large, correlated fluctuations during quiet wakefulness, including pairs of cells with disparate tuning properties. These fluctuations are driven by correlated barrages of excitation followed closely by inhibition (∼5-ms lag). During visual stimulation, low-frequency activity is diminished, and coherent high-frequency oscillations appear, even for non-preferred stimuli. These oscillations are generated by alternating excitatory and inhibitory inputs at a similar lag. The temporal sequence of depolarization for pairs of neurons is conserved during both spontaneous- and visually-evoked activity, suggesting a stereotyped flow of activation that may function to produce temporally precise "windows of opportunity" for additional synaptic inputs.

Volume Conduction Coupling of Whisker-Evoked Cortical LFP in the Mouse Olfactory Bulb

Local field potentials (LFPs) are an important measure of brain activity and have been used to address various mechanistic and behavioral questions. We revealed a prominent whisker-evoked LFP signal in the olfactory bulb and investigated its physiology. This signal, dependent on barrel cortex activation and highly correlated with its local activity, represented a pure volume conduction signal that was sourced back to the activity in the ventro-lateral orbitofrontal cortex, located a few millimeters away. Thus, we suggest that special care should be taken when acquiring and interpreting LFP data.

Does layer 4 in the barrel cortex function as a balanced circuit when responding to whisker movements?

Neurons in one barrel in layer 4 (L4) in the mouse vibrissa somatosensory cortex are innervated mostly by neurons from the VPM nucleus and by other neurons within the same barrel. During quiet wakefulness or whisking in air, thalamic inputs vary slowly in time, and excitatory neurons rarely fire. A barrel in L4 contains a modest amount of neurons; the synaptic conductances are not very strong and connections are not sparse. Are the dynamical properties of the L4 circuit similar to those expected from fluctuation-dominated, balanced networks observed for large, strongly coupled and sparse cortical circuits? To resolve this question, we analyze a network of 150 inhibitory parvalbumin-expressing fast-spiking inhibitory interneurons innervated by the VPM thalamus with random connectivity, without or with 1600 low-firing excitatory neurons. Above threshold, the population-average firing rate of inhibitory cortical neurons increases linearly with the thalamic firing rate. The coefficient of variation CV is somewhat less than 1. Moderate levels of synchrony are induced by converging VPM inputs and by inhibitory interaction among neurons. The strengths of excitatory and inhibitory currents during whisking are about three times larger than threshold. We identify values of numbers of presynaptic neurons, synaptic delays between inhibitory neurons, and electrical coupling within the experimentally plausible ranges for which spike synchrony levels are low. Heterogeneity in in-degrees increases the width of the firing rate distribution to the experimentally observed value. We conclude that an L4 circuit in the low-synchrony regime exhibits qualitative dynamical properties similar to those of balanced networks.

Adaptation modulates correlated subthreshold response variability in visual cortex

Cortical sensory responses are highly variable across stimulus presentations. This variability can be correlated across neurons (due to some combination of dense intracortical connectivity, cortical activity level, and cortical state), with fundamental implications for population coding. Yet the interpretation of correlated response variability (or "noise correlation") has remained fraught with difficulty, in part because of the restriction to extracellular neuronal spike recordings. Here, we measured response variability and its correlation at the most microscopic level of electrical neural activity, the membrane potential, by obtaining dual whole cell recordings from pairs of cortical pyramidal neurons during visual processing in the turtle whole brain ex vivo preparation. We found that during visual stimulation, correlated variability adapts toward an intermediate level and that this correlation dynamic is likely mediated by intracortical mechanisms. A model network with external inputs, synaptic depression, and structure reproduced the observed dynamics of correlated variability. These results suggest that intracortical adaptation self-organizes cortical circuits toward a balanced regime at which correlated variability is maintained at an intermediate level.NEW & NOTEWORTHY Correlated response variability has profound implications for stimulus encoding, yet our understanding of this phenomenon is based largely on spike data. Here, we investigate the dynamics and mechanisms of membrane potential-correlated variability (CC) in visual cortex with a combined experimental and computational approach. We observe a visually evoked increase in CC, followed by a fast return to baseline. Our results further suggest a link between this observation and the adaptation-mediated dynamics of emergent network phenomena.

Inhibitory control of correlated intrinsic variability in cortical networks

Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different rodent species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the diverse activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations.

DOI:http://dx.doi.org/10.7554/eLife.19695.001

Our brains contain billions of neurons, which are continually producing electrical signals to relay information around the brain. Yet most of our knowledge of how the brain works comes from studying the activity of one neuron at a time. Recently, studies of multiple neurons have shown that they tend to be active together in short bursts called “up” states, which are followed by periods in which they are less active called “down” states. When we are sleeping or under a general anesthetic, the neurons may be completely silent during down states, but when we are awake the difference in activity between the two states is usually less extreme. However, it is still not clear how the neurons generate these patterns of activity.

To address this question, Stringer et al. studied the activity of neurons in the brains of awake and anesthetized rats, mice and gerbils. The experiments recorded electrical activity from many neurons at the same time and found a wide range of different activity patterns. A computational model based on these data suggests that differences in the degree to which some neurons suppress the activity of other neurons may account for this variety. Increasing the strength of these inhibitory signals in the model decreased the fluctuations in electrical activity across entire areas of the brain. Further analysis of the experimental data supported the model’s predictions by showing that inhibitory neurons – which act to reduce electrical activity in other neurons – were more active when there were fewer fluctuations in activity across the brain.

The next step following on from this work would be to develop ways to build computer models that can mimic the activity of many more neurons at the same time. The models could then be used to interpret the electrical activity produced by many different kinds of neuron. This will enable researchers to test more sophisticated hypotheses about how the brain works.

DOI:http://dx.doi.org/10.7554/eLife.19695.002

Neuronal activity controls the development of interneurons in the somatosensory cortex

BACKGROUND

Neuronal activity in cortical areas regulates neurodevelopment by interacting with defined genetic programs to shape the mature central nervous system. Electrical activity is conveyed to sensory cortical areas via intracortical and thalamocortical neurons, and includes oscillatory patterns that have been measured across cortical regions.

OBJECTIVE

In this work, we review the most recent findings about how electrical activity shapes the developmental assembly of functional circuitry in the somatosensory cortex, with an emphasis on interneuron maturation and integration. We include studies on the effect of various neurotransmitters and on the influence of thalamocortical afferent activity on circuit development. We additionally reviewed studies describing network activity patterns.

METHODS

We conducted an extensive literature search using both the PubMed and Google Scholar search engines. The following keywords were used in various iterations: "interneuron", "somatosensory", "development", "activity", "network patterns", "thalamocortical", "NMDA receptor", "plasticity". We additionally selected papers known to us from past reading, and those recommended to us by reviewers and members of our lab.

RESULTS

We reviewed a total of 132 articles that focused on the role of activity in interneuronal migration, maturation, and circuit development, as well as the source of electrical inputs and patterns of cortical activity in the somatosensory cortex. 79 of these papers included in this timely review were written between 2007 and 2016.

CONCLUSIONS

Neuronal activity shapes the developmental assembly of functional circuitry in the somatosensory cortical interneurons. This activity impacts nearly every aspect of development and acquisition of mature neuronal characteristics, and may contribute to changing phenotypes, altered transmitter expression, and plasticity in the adult. Progressively changing oscillatory network patterns contribute to this activity in the early postnatal period, although a direct requirement for specific patterns and origins of activity remains to be demonstrated.

The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks

Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits.

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Structural heterogeneity threatens the dynamic balance of excitation and inhibition

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Reconstruction of cortical networks reveals significant structural heterogeneity

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Spike-frequency adaptation can act locally to facilitate global balance

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Inhibitory homeostatic plasticity can compensate for structural imbalance