Decorrelating action of inhibition in neocortical networks

Luminance invariant encoding in mouse primary visual cortex

The visual system adapts to maintain sensitivity and selectivity over a large range of luminance intensities. One way that the retina maintains sensitivity across night and day is by switching between rod and cone photoreceptors, which alters the receptive fields and interneuronal correlations of retinal ganglion cells (RGCs). While these adaptations allow the retina to transmit visual information to the brain across environmental conditions, the code used for that transmission varies. To determine how downstream targets encode visual scenes across light levels, we measured the effects of luminance adaptation on thalamic and cortical population activity. While changes in the retinal output are evident in the lateral geniculate nucleus (LGN), selectivity in the primary visual cortex (V1) is largely invariant to the changes in luminance. We show that the visual system could maintain sensitivity across environmental conditions without altering cortical selectivity through the convergence of parallel functional pathways from the thalamus to the cortex.

The short-term plasticity of VIP interneurons in motor cortex

Short-term plasticity is an important feature in the brain for shaping neural dynamics and for information processing. Short-term plasticity is known to depend on many factors including brain region, cortical layer, and cell type. Here we focus on vasoactive-intestinal peptide (VIP) interneurons (INs). VIP INs play a key disinhibitory role in cortical circuits by inhibiting other IN types, including Martinotti cells (MCs) and basket cells (BCs). Despite this prominent role, short-term plasticity at synapses to and from VIP INs is not well described. In this study, we therefore characterized the short-term plasticity at inputs and outputs of genetically targeted VIP INs in mouse motor cortex. To explore inhibitory to inhibitory (I → I) short-term plasticity at layer 2/3 (L2/3) VIP IN outputs onto L5 MCs and BCs, we relied on a combination of whole-cell recording, 2-photon microscopy, and optogenetics, which revealed that VIP IN→MC/BC synapses were consistently short-term depressing. To explore excitatory (E) → I short-term plasticity at inputs to VIP INs, we used extracellular stimulation. Surprisingly, unlike VIP IN outputs, E → VIP IN synapses exhibited heterogeneous short-term dynamics, which we attributed to the target VIP IN cell rather than the input. Computational modeling furthermore linked the diversity in short-term dynamics at VIP IN inputs to a wide variability in probability of release. Taken together, our findings highlight how short-term plasticity at VIP IN inputs and outputs is specific to synapse type. We propose that the broad diversity in short-term plasticity of VIP IN inputs forms a basis to code for a broad range of contrasting signal dynamics.

Egocentric neural representation of geometric vertex in the retrosplenial cortex

Egocentric neural representations of environmental features, such as edges and vertices, are important for constructing a geometrically detailed egocentric cognitive map for goal-directed navigation and episodic memory. While egocentric neural representations of edges like egocentric boundary/border cells exist, those that selectively represent vertices egocentrically are yet unknown. Here we report that granular retrosplenial cortex (RSC) neurons in male mice generate spatial receptive fields exclusively near the vertices of environmental geometries during free exploration, termed vertex cells. Their spatial receptive fields occurred at a specific orientation and distance relative to the heading direction of mice, indicating egocentric vector coding of vertex. Removing physical boundaries defining the environmental geometry abolished the egocentric vector coding of vertex, and goal-directed navigation strengthened the egocentric vector coding at the goal-located vertex. Our findings suggest that egocentric vector coding of vertex by granular RSC neurons helps construct an egocentric cognitive map that guides goal-directed navigation.

The spike-timing-dependent plasticity of VIP interneurons in motor cortex

The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.

Memory encoding and retrieval by retrosplenial parvalbumin interneurons are impaired in Alzheimer's disease model mice

Memory deficits in Alzheimer's disease (AD) show a strong link with GABAergic interneuron dysfunctions.1,2,3,4,5,6,7 The ensemble dynamics of GABAergic interneurons represent memory encoding and retrieval,8,9,10,11,12 but how GABAergic interneuron dysfunction affects inhibitory ensemble dynamics in AD is unknown. As the retrosplenial cortex (RSC) is critical for episodic memory13,14,15,16 and is affected by β-amyloid accumulation in early AD,17,18,19,20,21 we address this question by performing Ca2+ imaging in RSC parvalbumin (PV)-expressing interneurons during a contextual fear memory task in healthy control mice and the 5XFAD mouse model of AD. We found that populations of PV interneurons responsive to aversive electric foot shocks during contextual fear conditioning (shock-responsive) significantly decreased in the 5XFAD mice, indicating dysfunctions in the recruitment of memory-encoding PV interneurons. In the control mice, ensemble activities of shock-responsive PV interneurons were selectively upregulated during the freezing epoch of the contextual fear memory retrieval, manifested by synaptic potentiation of PV interneuron-mediated inhibition. However, such changes in ensemble dynamics during memory retrieval and synaptic plasticity were both absent in the 5XFAD mice. Optogenetic silencing of PV interneurons during contextual fear conditioning in the control mice mimicked the memory deficits in the 5XFAD mice, while optogenetic activation of PV interneurons in the 5XFAD mice restored memory retrieval. These results demonstrate the critical roles of contextual fear memory-encoding PV interneurons for memory retrieval. Furthermore, synaptic dysfunction of PV interneurons may disrupt the recruitment of PV interneurons and their ensemble dynamics underlying contextual fear memory retrieval, subsequently leading to memory deficits in AD.

Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column

Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their "paradoxical response", where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation-inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation-inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.

Maturation of GABAergic Synaptic Transmission From Neocortical Parvalbumin Interneurons Involves N-methyl-D-aspartate Receptor Recruitment of Cav2.1 Channels

N-methyl-D-aspartate receptor (NMDAR) hypofunction during brain development is likely to contribute to the manifestation of schizophrenia (SCZ) in young adulthood. The cellular targets of NMDAR hypofunction appear to be at least in part corticolimbic fast-spiking (FS) interneurons. However, functional alterations in parvalbumin (PV)-positive FS interneurons following NMDAR hypofunction are poorly understood. Paired patch-clamp recordings from murine cortical PV interneurons and pyramidal neurons revealed that genetic deletion of NMDAR subunit Grin1 in prospective PV interneurons before the second postnatal week impaired evoked- and synchronized-GABA release. Whereas intrinsic excitability and spiking characteristics were also disturbed by Grin1 deletion, neither restoring their excitability by K⁺ channel blockade nor increasing extracellular Ca²⁺ rescued the GABA release. GABA release was also insensitive to the Cav2.1 channel antagonist ω-agatoxin IVA. Heterozygous deletion of Cacna1a gene (encoding Cav2.1) in PV interneurons produced a similar GABA release phenotype as the Grin1 mutants. Treatment with the Cav2.1/2.2 channel agonist GV-58 augmented somatic Ca²⁺ currents and GABA release in Cacna1a-haploinsufficient PV interneurons, but failed to enhance GABA release in the Grin1-deleted PV interneurons. Taken together, our results suggest that Grin1 deletion in prospective PV interneurons impairs proper maturation of membrane excitability and Cav2.1-recruited evoked GABA release. This may increase synaptic excitatory/inhibitory ratio in principal neurons, contributing to the emergence of SCZ-like phenotypes.

Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation

Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.

Disrupted-in-schizophrenia-1 is required for normal pyramidal cell-interneuron communication and assembly dynamics in the prefrontal cortex

We interrogated prefrontal circuit function in mice lacking Disrupted-in-schizophrenia-1 (Disc1-mutant mice), a risk factor for psychiatric disorders. Single-unit recordings in awake mice revealed reduced average firing rates of fast-spiking interneurons (INTs), including optogenetically identified parvalbumin-positive cells, and a lower proportion of INTs phase-coupled to ongoing gamma oscillations. Moreover, we observed decreased spike transmission efficacy at local pyramidal cell (PYR)-INT connections in vivo, suggesting a reduced excitatory effect of local glutamatergic inputs as a potential mechanism of lower INT rates. On the network level, impaired INT function resulted in altered activation of PYR assemblies: While assembly activations defined as coactivations within 25 ms were observed equally often, the expression strength of individual assembly patterns was significantly higher in Disc1-mutant mice. Our data, thus, reveal a role of Disc1 in shaping the properties of prefrontal assembly patterns by setting INT responsiveness to glutamatergic drive.

Loss of neuronal heterogeneity in epileptogenic human tissue impairs network resilience to sudden changes in synchrony

A myriad of pathological changes associated with epilepsy can be recast as decreases in cell and circuit heterogeneity. We thus propose recontextualizing epileptogenesis as a process where reduction in cellular heterogeneity, in part, renders neural circuits less resilient to seizure. By comparing patch clamp recordings from human layer 5 (L5) cortical pyramidal neurons from epileptogenic and non-epileptogenic tissue, we demonstrate significantly decreased biophysical heterogeneity in seizure-generating areas. Implemented computationally, this renders model neural circuits prone to sudden transitions into synchronous states with increased firing activity, paralleling ictogenesis. This computational work also explains the surprising finding of significantly decreased excitability in the population-activation functions of neurons from epileptogenic tissue. Finally, mathematical analyses reveal a bifurcation structure arising only with low heterogeneity and associated with seizure-like dynamics. Taken together, this work provides experimental, computational, and mathematical support for the theory that ictogenic dynamics accompany a reduction in biophysical heterogeneity.

Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity

Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results suggest that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. We show that inhibitory feedback (random and specific) increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight that (1) interneuron plasticity is key to the development of tuning diversity and (2) that efficient sensory representations are an emergent property of the resulting network.

Synaptic plasticity is crucial for the development of efficient input representation in the different sensory cortices, such as the primary visual cortex. Efficient visual representation is determined by two factors: representational efficiency, i.e. how many different input features can be represented, and metabolic efficiency, i.e. how many spikes are required to represent a specific feature. Previous research has pointed out the importance of plasticity at excitatory synapses to achieve high representational efficiency and feedback inhibition as a gain control mechanism for controlling metabolic efficiency. However, it is only partially understood how the influence of inhibitory plasticity on excitatory plasticity can lead to an efficient representation. Using a spiking neural network, we show that plasticity at feed-forward and feedback inhibitory synapses is necessary for the emergence of well-distributed neuronal selectivity to improve representational efficiency. Further, the emergent balance between excitatory and inhibitory currents improves the metabolic efficiency, and leads to contrast-invariant tuning as an inherent network property. Extending previous work, our simulation results highlight the importance of plasticity at inhibitory synapses.

Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States

Up states are the best studied example of an emergent neural dynamic regime. Computational models based on a single class of inhibitory neurons indicate that Up states reflect bistable dynamic systems in which positive feedback is stabilized by strong inhibition and predict a paradoxical effect in which increased drive to inhibitory neurons results in decreased inhibitory activity. To date, however, computational models have not incorporated empirically defined properties of parvalbumin (PV) and somatostatin (SST) neurons. Here we first experimentally characterized the frequency-current (F-I) curves of pyramidal (Pyr), PV, and SST neurons from mice of either sex, and confirmed a sharp difference between the threshold and slopes of PV and SST neurons. The empirically defined F-I curves were incorporated into a three-population computational model that simulated the empirically derived firing rates of pyramidal, PV, and SST neurons. Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states. Simulations and analytical methods demonstrated that while the paradoxical effect is not obligatory in a model with two classes of inhibitory neurons, it is present in most regimes. Finally, experimental tests validated predictions of the model that the Pyr ↔ PV inhibitory loop is stronger than the Pyr ↔ SST loop.SIGNIFICANCE STATEMENT Many cortical computations, such as working memory, rely on the local recurrent excitatory connections that define cortical circuit motifs. Up states are among the best studied examples of neural dynamic regimes that rely on recurrent excitatory excitation. However, this positive feedback must be held in check by inhibition. To address the relative contribution of PV and SST neurons, we characterized the intrinsic input-output differences between these classes of inhibitory neurons and, using experimental and theoretical methods, show that the higher threshold and gain of PV leads to a dominant role in network stabilization.

Kcns3 deficiency disrupts Parvalbumin neuron physiology in mouse prefrontal cortex: Implications for the pathophysiology of schizophrenia

The unique fast spiking (FS) phenotype of cortical parvalbumin-positive (PV) neurons depends on the expression of multiple subtypes of voltage-gated potassium channels (Kv). PV neurons selectively express Kcns3, the gene encoding Kv9.3 subunits, suggesting that Kcns3 expression is critical for the FS phenotype. KCNS3 expression is lower in PV neurons in the neocortex of subjects with schizophrenia, but the effects of this alteration are unclear, because Kv9.3 subunit function is poorly understood. Therefore, to assess the role of Kv9.3 subunits in PV neuron function, we combined gene expression analyses, computational modeling, and electrophysiology in acute slices from the cortex of Kcns3-deficient mice. Kcns3 mRNA levels were ~ 50% lower in cortical PV neurons from Kcns3-deficient relative to wildtype mice. While silent per se, Kv9.3 subunits are believed to amplify the Kv2.1 current in Kv2.1-Kv9.3 channel complexes. Hence, to assess the consequences of reducing Kv9.3 levels, we simulated the effects of decreasing the Kv2.1-mediated current in a computational model. The FS cell model with reduced Kv2.1 produced spike trains with irregular inter-spike intervals, or stuttering, and greater Na+ channel inactivation. As in the computational model, PV basket cells (PVBCs) from Kcns3-deficient mice displayed spike trains with strong stuttering, which depressed PVBC firing. Moreover, Kcns3 deficiency impaired the recruitment of PVBC firing at gamma frequency by stimuli mimicking synaptic input observed during cortical UP states. Our data indicate that Kv9.3 subunits are critical for PVBC physiology and suggest that KCNS3 deficiency in schizophrenia could impair PV neuron firing, possibly contributing to deficits in cortical gamma oscillations in the illness.

Somatostatin interneurons activated by 5-HT2A receptor suppress slow oscillations in medial entorhinal cortex

Serotonin (5-HT) is one of the major neuromodulators present in the mammalian brain and has been shown to play a role in multiple physiological processes. The mechanisms by which 5-HT modulates cortical network activity, however, are not yet fully understood. We investigated the effects of 5-HT on slow oscillations (SOs), a synchronized cortical network activity universally present across species. SOs are observed during anesthesia and are considered to be the default cortical activity pattern. We discovered that (±)3,4-methylenedioxymethamphetamine (MDMA) and fenfluramine, two potent 5-HT releasers, inhibit SOs within the entorhinal cortex (EC) in anesthetized mice. Combining opto- and pharmacogenetic manipulations with in vitro electrophysiological recordings, we uncovered that somatostatin-expressing (Sst) interneurons activated by the 5-HT_2A receptor (5-HT_2AR) play an important role in the suppression of SOs. Since 5-HT_2AR signaling is involved in the etiology of different psychiatric disorders and mediates the psychological effects of many psychoactive serotonergic drugs, we propose that the newly discovered link between Sst interneurons and 5-HT will contribute to our understanding of these complex topics.

Inhibitory stabilization and cortical computation

Neuronal networks with strong recurrent connectivity provide the brain with a powerful means to perform complex computational tasks. However, high-gain excitatory networks are susceptible to instability, which can lead to runaway activity, as manifested in pathological regimes such as epilepsy. Inhibitory stabilization offers a dynamic, fast and flexible compensatory mechanism to balance otherwise unstable networks, thus enabling the brain to operate in its most efficient regimes. Here we review recent experimental evidence for the presence of such inhibition-stabilized dynamics in the brain and discuss their consequences for cortical computation. We show how the study of inhibition-stabilized networks in the brain has been facilitated by recent advances in the technological toolbox and perturbative techniques, as well as a concomitant development of biologically realistic computational models. By outlining future avenues, we suggest that inhibitory stabilization can offer an exemplary case of how experimental neuroscience can progress in tandem with technology and theory to advance our understanding of the brain.

Endocannabinoid Signaling Contributes to Experience-Induced Increase of Synaptic Release Sites From Parvalbumin Interneurons in Mouse Visual Cortex

During postnatal development of the visual cortex between eye-opening to puberty, visual experience promotes a gradual increase in the strength of inhibitory synaptic connections from parvalbumin-positive interneurons (PV-INs) onto layer 2/3 pyramidal cells. However, the detailed connectivity properties and molecular mechanisms underlying these developmental changes are not well understood. Using dual-patch clamp in brain slices from G42 mice, we revealed that both connection probability and the number of synaptic release sites contributed to the enhancement of synaptic strength. The increase of release site number was hindered by dark rearing from eye-opening and rescued by 3-days re-exposure to the normal visual environment. The effect of light re-exposure on restoring synaptic release sites in dark reared mice was mimicked by the agonist of cannabinoid-1 (CB1) receptors and blocked by an antagonist of these receptors, suggesting a role for endocannabinoid signaling in light-induced maturation of inhibitory connectivity from PV-INs to pyramidal cells during postnatal development.

Jensen's force and the statistical mechanics of cortical asynchronous states

Cortical networks are shaped by the combined action of excitatory and inhibitory interactions. Among other important functions, inhibition solves the problem of the all-or-none type of response that comes about in purely excitatory networks, allowing the network to operate in regimes of moderate or low activity, between quiescent and saturated regimes. Here, we elucidate a noise-induced effect that we call “Jensen’s force” –stemming from the combined effect of excitation/inhibition balance and network sparsity– which is responsible for generating a phase of self-sustained low activity in excitation-inhibition networks. The uncovered phase reproduces the main empirically-observed features of cortical networks in the so-called asynchronous state, characterized by low, un-correlated and highly-irregular activity. The parsimonious model analyzed here allows us to resolve a number of long-standing issues, such as proving that activity can be self-sustained even in the complete absence of external stimuli or driving. The simplicity of our approach allows for a deep understanding of asynchronous states and of the phase transitions to other standard phases it exhibits, opening the door to reconcile, asynchronous-state and critical-state hypotheses, putting them within a unified framework. We argue that Jensen’s forces are measurable experimentally and might be relevant in contexts beyond neuroscience.

Parvalbumin-Positive Interneurons Regulate Neuronal Ensembles in Visual Cortex

For efficient cortical processing, neural circuit dynamics must be spatially and temporally regulated with great precision. Although parvalbumin-positive (PV) interneurons can control network synchrony, it remains unclear how they contribute to spatio-temporal patterning of activity. We investigated this by optogenetic inactivation of PV cells with simultaneous two-photon Ca2+ imaging from populations of neurons in mouse visual cortex in vivo. For both spontaneous and visually evoked activity, PV interneuron inactivation decreased network synchrony. But, interestingly, the response reliability and spatial extent of coactive neuronal ensembles during visual stimulation were also disrupted by PV-cell suppression, which reduced the functional repertoire of ensembles. Thus, PV interneurons can control the spatio-temporal dynamics of multineuronal activity by functionally sculpting neuronal ensembles and making them more different from each other. In doing so, inhibitory circuits could help to orthogonalize multicellular patterns of activity, enabling neural circuits to more efficiently occupy a higher dimensional space of potential dynamics.

Correlation Transfer by Layer 5 Cortical Neurons Under Recreated Synaptic Inputs In Vitro

Correlated electrical activity in neurons is a prominent characteristic of cortical microcircuits. Despite a growing amount of evidence concerning both spike-count and subthreshold membrane potential pairwise correlations, little is known about how different types of cortical neurons convert correlated inputs into correlated outputs. We studied pyramidal neurons and two classes of GABAergic interneurons of layer 5 in neocortical brain slices obtained from rats of both sexes, and we stimulated them with biophysically realistic correlated inputs, generated using dynamic clamp. We found that the physiological differences between cell types manifested unique features in their capacity to transfer correlated inputs. We used linear response theory and computational modeling to gain clear insights into how cellular properties determine both the gain and timescale of correlation transfer, thus tying single-cell features with network interactions. Our results provide further ground for the functionally distinct roles played by various types of neuronal cells in the cortical microcircuit.SIGNIFICANCE STATEMENT No matter how we probe the brain, we find correlated neuronal activity over a variety of spatial and temporal scales. For the cerebral cortex, significant evidence has accumulated on trial-to-trial covariability in synaptic inputs activation, subthreshold membrane potential fluctuations, and output spike trains. Although we do not yet fully understand their origin and whether they are detrimental or beneficial for information processing, we believe that clarifying how correlations emerge is pivotal for understanding large-scale neuronal network dynamics and computation. Here, we report quantitative differences between excitatory and inhibitory cells, as they relay input correlations into output correlations. We explain this heterogeneity by simple biophysical models and provide the most experimentally validated test of a theory for the emergence of correlations.

Decoupling of timescales reveals sparse convergent CPG network in the adult spinal cord

During the generation of rhythmic movements, most spinal neurons receive an oscillatory synaptic drive. The neuronal architecture underlying this drive is unknown, and the corresponding network size and sparseness have not yet been addressed. If the input originates from a small central pattern generator (CPG) with dense divergent connectivity, it will induce correlated input to all receiving neurons, while sparse convergent wiring will induce a weak correlation, if any. Here, we use pairwise recordings of spinal neurons to measure synaptic correlations and thus infer the wiring architecture qualitatively. A strong correlation on a slow timescale implies functional relatedness and a common source, which will also cause correlation on fast timescale due to shared synaptic connections. However, we consistently find marginal coupling between slow and fast correlations regardless of neuronal identity. This suggests either sparse convergent connectivity or a CPG network with recurrent inhibition that actively decorrelates common input.

Inhibitory Interneurons Regulate Temporal Precision and Correlations in Cortical Circuits

GABAergic interneurons, which are highly diverse, have long been thought to contribute to the timing of neural activity as well as to the generation and shaping of brain rhythms. GABAergic activity is crucial not only for entrainment of oscillatory activity across a neural population, but also for precise regulation of the timing of action potentials and the suppression of slow-timescale correlations. The diversity of inhibition provides the potential for flexible regulation of patterned activity, but also poses a challenge to identifying the elements of excitatory-inhibitory interactions underlying network engagement. This review highlights the key roles of inhibitory interneurons in spike correlations and brain rhythms, describes several scales on which GABAergic inhibition regulates timing in neural networks, and identifies potential consequences of inhibitory dysfunction.

Presynaptic Effects of N-Methyl-D-Aspartate Receptors Enhance Parvalbumin Cell-Mediated Inhibition of Pyramidal Cells in Mouse Prefrontal Cortex

BACKGROUND

Testing hypotheses regarding the role of N-methyl-D-aspartate receptor (NMDAR) hypofunction in schizophrenia requires understanding the mechanisms of NMDAR regulation of prefrontal cortex (PFC) circuit function. NMDAR antagonists are thought to produce pyramidal cell (PC) disinhibition. However, inhibitory parvalbumin-positive basket cells (PVBCs) have modest NMDAR-mediated excitatory drive and thus are unlikely to participate in NMDAR antagonist-mediated disinhibition. Interestingly, recent studies demonstrated that presynaptic NMDARs enhance transmitter release at central synapses. Thus, if presynaptic NMDARs enhance gamma-aminobutyric acid release at PVBC-to-PC synapses, they could participate in NMDAR-dependent PC disinhibition. Here, we examined whether presynaptic NMDAR effects could modulate gamma-aminobutyric acid release at PVBC-to-PC synapses in mouse PFC.

METHODS

Using whole-cell recordings from synaptically connected pairs in mouse PFC, we determined whether NMDA or NMDAR antagonist application affects PVBC-to-PC inhibition in a manner consistent with a presynaptic mechanism.

RESULTS

NMDAR activation enhanced by ∼40% the synaptic current at PVBC-to-PC pairs. This effect was consistent with a presynaptic mechanism given that it was 1) observed with postsynaptic NMDARs blocked by intracellular MK801, 2) associated with a lower rate of transmission failures and a higher transmitter release probability, and 3) blocked by intracellular MK801 in the PVBC. NMDAR antagonist application did not affect the synaptic currents in PVBC-to-PC pairs, but it reduced the inhibitory currents elicited in PCs with simultaneous glutamate release by extracellular stimulation.

CONCLUSIONS

We demonstrate that NMDAR activation enhances PVBC-to-PC inhibition in a manner consistent with presynaptic mechanisms, and we suggest that the functional impact of this presynaptic effect depends on the activity state of the PFC network.

Cell Type- and Layer-Specific Muscarinic Potentiation of Excitatory Synaptic Drive onto Parvalbumin Neurons in Mouse Prefrontal Cortex

Cholinergic neuromodulation is thought to shape network activity in the PFC, and thus PFC-dependent cognitive functions. ACh may modulate the activity of parvalbumin-positive (PV+) neurons, which critically regulate cortical network function. However, the mechanisms of cholinergic regulation of PV+ neuron activity, and particularly of the basket cell (BC) versus chandelier cell (ChC) subtypes, are unclear. Using patch clamp recordings in acute slices, we examined the effects of the ACh receptor (AChR) agonist carbachol on the excitatory synaptic drive onto BCs or ChCs in layers 2 to 6 of mouse PFC. Carbachol increased the frequency and amplitude of spontaneous EPSCs (sEPSCs) recorded from PV+ BCs in layers 3-6, but not in BCs from layer 2. Moreover, carbachol did not change the sEPSCs in ChCs, which were located exclusively in layer 2. The potentiation of sEPSCs in layers 3-6 BCs was prevented by the Na+ channel blocker tetrodotoxin and was abolished by the M1-selective muscarinic AChR antagonist pirenzepine. Thus, carbachol potentiates the activity-dependent excitatory drive onto PV+ neurons via M1-muscarinic AChR activation in a cell type- and layer-specific manner. In current clamp recordings with synaptic transmission blocked, carbachol directly evoked firing in deep layer pyramidal neurons (PNs). In contrast, carbachol elicited deep layer BC firing indirectly, via glutamate-mediated synaptic drive. Our data suggest that ACh powerfully regulates PFC microcircuit function by facilitating the firing of PNs that synaptically recruit deep layer PV+ BC activity, possibly shaping the patterns of network activity that contribute to cognitive function.

Altered Cortical Ensembles in Mouse Models of Schizophrenia

In schizophrenia, brain-wide alterations have been identified at the molecular and cellular levels, yet how these phenomena affect cortical circuit activity remains unclear. We studied two mouse models of schizophrenia-relevant disease processes: chronic ketamine (KET) administration and Df(16)A^+/-, modeling 22q11.2 microdeletions, a genetic variant highly penetrant for schizophrenia. Local field potential recordings in visual cortex confirmed gamma-band abnormalities similar to patient studies. Two-photon calcium imaging of local cortical populations revealed in both models a deficit in the reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altered single-neuron activity. This effect was present in ongoing and sensory-evoked activity and was not replicated by acute ketamine administration or pharmacogenetic parvalbumin-interneuron suppression. These results are consistent with the hypothesis that schizophrenia is an "attractor" disease and demonstrate that degraded neuronal ensembles are a common consequence of diverse genetic, cellular, and synaptic alterations seen in chronic schizophrenia.

Sex differences in endogenous cortical network activity: spontaneously recurring Up/Down states

BACKGROUND

Several molecular and cellular processes in the vertebrate brain exhibit differences between males and females, leading to sexual dimorphism in the formation of neural circuits and brain organization. While studies on large-scale brain networks provide ample evidence for both structural and functional sex differences, smaller-scale local networks have remained largely unexplored. In the current study, we investigate sexual dimorphism in cortical dynamics by means of spontaneous Up/Down states, a type of network activity that is exhibited during slow-wave sleep, quiet wakefulness, and anesthesia and is thought to represent the default activity of the cortex.

METHODS

Up state activity was monitored by local field potential recordings in coronal brain slices of male and female mice across three ages with distinct secretion profiles of sex hormones: (i) pre-puberty (17-21 days old), (ii) 3-9 adult (months old), and (iii) old (19-24 months old).

RESULTS

Female mice of all ages exhibited longer and more frequent Up states compared to aged-matched male mice. Power spectrum analysis revealed sex differences in the relative power of Up state events, with female mice showing reduced power in the delta range (1-4 Hz) and increased power in the theta range (4-8 Hz) compared to male mice. No sex differences were found in the characteristics of Up state peak voltage and latency.

CONCLUSIONS

The present study revealed for the first time sex differences in intracortical network activity, using an ex vivo paradigm of spontaneously occurring Up/Down states. We report significant sex differences in Up state properties that are already present in pre-puberty animals and are maintained through adulthood and old age.

Distinct Physiological Maturation of Parvalbumin-Positive Neuron Subtypes in Mouse Prefrontal Cortex

Parvalbumin-positive (PV⁺) neurons control the timing of pyramidal cell output in cortical neuron networks. In the prefrontal cortex (PFC), PV⁺ neuron activity is involved in cognitive function, suggesting that PV⁺ neuron maturation is critical for cognitive development. The two major PV⁺ neuron subtypes found in the PFC, chandelier cells (ChCs) and basket cells (BCs), are thought to play different roles in cortical circuits, but the trajectories of their physiological maturation have not been compared. Using two separate mouse lines, we found that in the mature PFC, both ChCs and BCs are abundant in superficial layer 2, but only BCs are present in deeper laminar locations. This distinctive laminar distribution was observed by postnatal day 12 (P12), when we first identified ChCs by the presence of axon cartridges. Electrophysiology analysis of excitatory synapse development, starting at P12, showed that excitatory drive remains low throughout development in ChCs, but increases rapidly before puberty in BCs, with an earlier time course in deeper-layer BCs. Consistent with a role of excitatory synaptic drive in the maturation of PV⁺ neuron firing properties, the fast-spiking phenotype showed different maturation trajectories between ChCs and BCs, and between superficial versus deep-layer BCs. ChC and BC maturation was nearly completed, via different trajectories, before the onset of puberty. These findings suggest that ChC and BC maturation may contribute differentially to the emergence of cognitive function, primarily during prepubertal development.SIGNIFICANCE STATEMENT Parvalbumin-positive (PV⁺) neurons tightly control pyramidal cell output. Thus PV⁺ neuron maturation in the prefrontal cortex (PFC) is crucial for cognitive development. However, the relative physiological maturation of the two major subtypes of PV⁺ neurons, chandelier cells (ChCs) and basket cells (BCs), has not been determined. We assessed the maturation of ChCs and BCs in different layers of the mouse PFC, and found that, from early postnatal age, ChCs and BCs differ in laminar location. Excitatory synapses and fast-spiking properties matured before the onset of puberty in both cell types, but following cell type-specific developmental trajectories. Hence, the physiological maturation of ChCs and BCs may contribute to the emergence of cognitive function differentially, and predominantly during prepubertal development.

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.

Synchronized gamma-frequency inhibition in neocortex depends on excitatory-inhibitory interactions but not electrical synapses

Synaptic inhibition plays a crucial role in the precise timing of spiking activity in the cerebral cortex. Synchronized, rhythmic inhibitory activity in the gamma (30-80 Hz) range is thought to be especially important for the active, information-processing neocortex, but the circuit mechanisms that give rise to synchronized inhibition are uncertain. In particular, the relative contributions of reciprocal inhibitory connections, excitatory-inhibitory interactions, and electrical synapses to precise spike synchrony among inhibitory interneurons are not well understood. Here we describe experiments on mouse barrel cortex in vitro as it spontaneously generates slow (<1 Hz) oscillations (Up and Down states). During Up states, inhibitory postsynaptic currents (IPSCs) are generated at gamma frequencies and are more synchronized than excitatory postsynaptic currents (EPSCs) among neighboring pyramidal cells. Furthermore, spikes in homotypic pairs of interneurons are more synchronized than in pairs of pyramidal cells. Comparing connexin36 knockout and wild-type animals, we found that electrical synapses make a minimal contribution to synchronized inhibition during Up states. Estimations of the delays between EPSCs and IPSCs in single pyramidal cells showed that excitation often preceded inhibition by a few milliseconds. Finally, tonic optogenetic activation of different interneuron subtypes in the absence of excitation led to only weak synchrony of IPSCs in pairs of pyramidal neurons. Our results suggest that phasic excitatory inputs are indispensable for synchronized spiking in inhibitory interneurons during Up states and that electrical synapses play a minimal role.

Auditory Golgi cells are interconnected predominantly by electrical synapses

The mossy fiber-granule cell-parallel fiber system conveys proprioceptive and corollary discharge information to principal cells in cerebellum-like systems. In the dorsal cochlear nucleus (DCN), Golgi cells inhibit granule cells and thus regulate information transfer along the mossy fiber-granule cell-parallel fiber pathway. Whereas excitatory synaptic inputs to Golgi cells are well understood, inhibitory and electrical synaptic inputs to Golgi cells have not been examined. Using paired recordings in a mouse brain slice preparation, we find that Golgi cells of the cochlear nucleus reliably form electrical synapses onto one another. Golgi cells were only rarely electrically coupled to superficial stellate cells, which form a separate network of electrically coupled interneurons in the DCN. Spikelets had a biphasic effect on the excitability of postjunctional Golgi cells, with a brief excitatory phase and a prolonged inhibitory phase due to the propagation of the prejunctional afterhyperpolarization through gap junctions. Golgi cells and stellate cells made weak inhibitory chemical synapses onto Golgi cells with low probability. Electrical synapses are therefore the predominant form of synaptic communication between auditory Golgi cells. We propose that electrical synapses between Golgi cells may function to regulate the synchrony of Golgi cell firing when electrically coupled Golgi cells receive temporally correlated excitatory synaptic input.

Inhibition Controls Asynchronous States of Neuronal Networks

Computations in cortical circuits require action potentials from excitatory and inhibitory neurons. In this mini-review, I first provide a quick overview of findings that indicate that GABAergic neurons play a fundamental role in coordinating spikes and generating synchronized network activity. Next, I argue that these observations helped popularize the notion that network oscillations require a high degree of spike correlations among interneurons which, in turn, produce synchronous inhibition of the local microcircuit. The aim of this text is to discuss some recent experimental and computational findings that support a complementary view: one in which interneurons participate actively in producing asynchronous states in cortical networks. This requires a proper mixture of shared excitation and inhibition leading to asynchronous activity between neighboring cells. Such contribution from interneurons would be extremely important because it would tend to reduce the spike correlation between neighboring pyramidal cells, a drop in redundancy that could enhance the information-processing capacity of neural networks.

Cooperative Subnetworks of Molecularly Similar Interneurons in Mouse Neocortex

Simultaneous co-activation of neocortical neurons is likely critical for brain computations ranging from perception and motor control to memory and cognition. While co-activation of excitatory principal cells (PCs) during ongoing activity has been extensively studied, that of inhibitory interneurons (INs) has received little attention. Here, we show in vivo and in vitro that members of two non-overlapping neocortical IN populations, expressing somatostatin (SOM) or vasoactive intestinal peptide (VIP), are active as populations rather than individually. We demonstrate a variety of synergistic mechanisms, involving population-specific local excitation, GABAergic disinhibition and excitation through electrical coupling, which likely underlie IN population co-activity. Firing of a few SOM or VIP INs recruits additional members within the cell type via GABAergic and cholinergic mechanisms, thereby amplifying the output of the population as a whole. Our data suggest that IN populations work as cooperative units, thus generating an amplifying nonlinearity in their circuit output.

Modulation of synchronous sympathetic firing behaviors by endogenous GABA(A) and glycine receptor-mediated activities in the neonatal rat spinal cord in vitro

Delivering effective commands in the nervous systems require a temporal integration of neural activities such as synchronous firing. Although sympathetic nerve discharges are characterized by synchronous firing, its temporal structures and how it is modulated are largely unknown. This study used a collagenase-dissociated splanchnic sympathetic nerve-thoracic spinal cord preparation of neonatal rats in vitro as an experimental model. Several single-fiber activities were recorded simultaneously and verified by rigorous computational algorithms. Among 3763 fiber pairs that had spontaneous fiber activities, 382 fiber pairs had firing positively correlated. Their temporal relationship was quantitatively evaluated by cross-correlogram. On average, correlated firing in a fiber pair occurred in scales of ∼40ms lasting for ∼11ms. The relative frequency distribution curves of correlogram parametrical values pertinent to the temporal features were best described by trimodal Gaussians, suggesting a correlated firing originated from three or less sources. Applications of bicuculline or gabazine (noncompetitive or competitive GABA(A) receptor antagonist) and/or strychnine (noncompetitive glycine receptor antagonist) increased, decreased, or did not change individual fiber activities. Antagonist-induced enhancement and attenuation of correlated firing were demonstrated by a respective increase and decrease of the peak probability of the cross-correlograms. Heterogeneity in antagonistic responses suggests that the inhibitory neurotransmission mediated by GABA(A) and glycine receptors is not essential for but can serve as a neural substrate to modulate synchronous firing behaviors. Plausible neural mechanisms were proposed to explain the temporal structures of correlated firing between sympathetic fibers.

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

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

Synaptic Mechanisms of Tight Spike Synchrony at Gamma Frequency in Cerebral Cortex

During the generation of higher-frequency (e.g., gamma) oscillations, cortical neurons can exhibit pairwise tight (<10 ms) spike synchrony. To understand how synaptic currents contribute to rhythmic activity and spike synchrony, we performed dual whole-cell recordings in mouse entorhinal cortical slices generating periodic activity (the slow oscillation). This preparation exhibited a significant amount of gamma-coherent spike synchrony during the active phase of the slow oscillation (Up state), particularly among fast-spiking inhibitory interneurons. IPSCs arriving in pairs of either pyramidal or fast-spiking neurons during the Up state were highly synchronized and exhibited significant coherence at frequencies from 10 to 100 Hz, peaking at ∼40 Hz, suggesting both synchronous discharge of, and synaptic divergence from, nearby inhibitory neurons. By inferring synaptic currents related to spike generation in simultaneously recorded pyramidal or fast-spiking neurons, we detected a decay of inhibition ∼20 ms before spiking. In fast-spiking interneurons, this was followed by an even larger excitatory input immediately before spike generation. Consistent with an important role for phasic excitation in driving spiking, we found that the correlation of excitatory inputs was highly predictive of spike synchrony in pairs of fast-spiking interneurons. Interestingly, spike synchrony in fast-spiking interneurons was not related to the strength of gap junctional coupling, and was still prevalent in connexin 36 knock-out animals. Our results support the pyramidal-interneuron gamma model of fast rhythmic oscillation in the cerebral cortex and suggest that spike synchrony and phase preference arises from the precise interaction of excitatory-inhibitory postsynaptic currents.

SIGNIFICANCE STATEMENT

We dissected the cellular and synaptic basis of spike synchrony occurring at gamma frequency (30-80 Hz). We used simultaneous targeted whole-cell recordings in an active slice preparation and analyzed the relationships between synaptic inputs and spike generation. We found that both pyramidal and fast-spiking neurons receive large, coherent inhibitory synaptic inputs at gamma frequency. In addition, we found that fast-spiking interneurons receive large, phasic excitatory synaptic inputs immediately before spike generation followed shortly by synaptic inhibition. These data support the principal-interneuron gamma generation model, and reveal how the synaptic connectivity between excitatory and inhibitory neurons supports the generation of gamma oscillations and spike synchrony.

High Stimulus-Related Information in Barrel Cortex Inhibitory Interneurons

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminate better between restricted sets of stimuli (≤6 stimulus classes) than EXC neurons in granular and infra-granular layers. We also demonstrate that ensembles of INH cells jointly provide as much information about such stimuli as comparable ensembles containing the ~20% most informative EXC neurons, however presenting less information redundancy – a result which was consistent when applying both theoretical information measurements and linear discriminant analysis classifiers. These results suggest that a consortium of INH neurons dominates the information conveyed to the neocortical network, thereby efficiently processing incoming sensory activity. This conclusion extends our view on the role of the inhibitory system to orchestrate cortical activity.

Perception of the environment relies on neuronal computation in the cerebral cortex. However, the exact algorithms by which cortical neuronal networks process relevant information from the inputs of sensory organs are only poorly understood. To address this problem we stimulated distinct whiskers and recorded the neuronal responses from identified cortical whisker representations of the rat using multi-site electrodes. For rodents the whisker system is one main sensory input channel, offering the unique property that for each whisker an identified cortical area ("barrel-related column") represents its main cortical input station. In the present study we were able to demonstrate that the action potential firing of single inhibitory neurons provides more information about behaviorally relevant qualities of whisker stimulation (identity of the stimulated whisker and frequency of stimulation) than excitatory neurons. In addition, information about stimulation qualities was encoded with less redundancy in inhibitory neurons. In summary, the results of our study suggest that inhibitory neurons carry substantial information about the sensory environment and can thereby adequately orchestrate neuronal activity in sensory cortices.

An acetylcholine-activated microcircuit drives temporal dynamics of cortical activity

Cholinergic modulation of cortex powerfully influences information processing and brain states, causing robust desynchronization of local field potentials and strong decorrelation of responses between neurons. We found that intracortical cholinergic inputs to mouse visual cortex specifically and differentially drive a defined cortical microcircuit: they facilitate somatostatin-expressing (SOM) inhibitory neurons that in turn inhibit parvalbumin-expressing inhibitory neurons and pyramidal neurons. Selective optogenetic inhibition of SOM responses blocked desynchronization and decorrelation, demonstrating that direct cholinergic activation of SOM neurons is necessary for this phenomenon. Optogenetic inhibition of vasoactive intestinal peptide-expressing neurons did not block desynchronization, despite these neurons being activated at high levels of cholinergic drive. Direct optogenetic SOM activation, independent of cholinergic modulation, was sufficient to induce desynchronization. Together, these findings demonstrate a mechanistic basis for temporal structure in cortical populations and the crucial role of neuromodulatory drive in specific inhibitory-excitatory circuits in actively shaping the dynamics of neuronal activity.

Columnar architecture improves noise robustness in a model cortical network

Cortical columnar architecture was discovered decades ago yet there is no agreed upon explanation for its function. Indeed, some have suggested that it has no function, it is simply an epiphenomenon of developmental processes. To investigate this problem we have constructed a computer model of one square millimeter of layer 2/3 of the primary visual cortex (V1) of the cat. Model cells are connected according to data from recent paired cell studies, in particular the connection probability between pyramidal cells is inversely proportional both to the distance separating the cells and to the distance between the preferred parameters (features) of the cells. We find that these constraints, together with a columnar architecture, produce more tightly clustered populations of cells when compared to the random architecture seen in, for example, rodents. This causes the columnar network to converge more quickly and accurately on the pattern representing a particular stimulus in the presence of noise, suggesting that columnar connectivity functions to improve pattern recognition in cortical circuits. The model also suggests that synaptic failure, a phenomenon exhibited by weak synapses, may conserve metabolic resources by reducing transmitter release at these connections that do not contribute to network function.

Independent theta phase coding accounts for CA1 population sequences and enables flexible remapping

Hippocampal place cells encode an animal's past, current, and future location through sequences of action potentials generated within each cycle of the network theta rhythm. These sequential representations have been suggested to result from temporally coordinated synaptic interactions within and between cell assemblies. Instead, we find through simulations and analysis of experimental data that rate and phase coding in independent neurons is sufficient to explain the organization of CA1 population activity during theta states. We show that CA1 population activity can be described as an evolving traveling wave that exhibits phase coding, rate coding, spike sequences and that generates an emergent population theta rhythm. We identify measures of global remapping and intracellular theta dynamics as critical for distinguishing mechanisms for pacemaking and coordination of sequential population activity. Our analysis suggests that, unlike synaptically coupled assemblies, independent neurons flexibly generate sequential population activity within the duration of a single theta cycle.

DOI:http://dx.doi.org/10.7554/eLife.03542.001

When we explore a new place, we naturally create a mental map of the location as we go. This mental map is stored in a region of the brain called the hippocampus, which contains cells called place cells. These cells can carry information about our past, present, and future location in the form of electrical signals. They connect to each other to form networks and it has been proposed that these connections can store the information needed for the mental maps.

Real-time maps are represented in the information carried by the electrical signals themselves. A physical location is specified by the individual place cell that is activated, and by the timing of the electrical signal it produces relative to a ‘brain wave’ called the theta rhythm. Brain waves are patterns of electrical signals activated in sets of brain cells and the theta rhythm is produced in the hippocampus of an animal as it explores its surroundings.

Previous experiments suggested that when a rat explores an area, several sets of brain cells in the hippocampus are activated in sequence within each cycle of the theta rhythm. As the rat moves forward, the sequence shifts to different sets of cells to reflect the upcoming locations ahead of the rat. It has been thought that these sequences are triggered by the individual connections between the place cells.

Here, Chadwick et al. developed mathematical models of the electrical activity in the brains of rats as they explored. They used these models to analyze data from previous experiments and found that the sequences of electrical activity arise from the timing of each cell's activity relative to the theta rhythm, rather than from the connections between the cells.

Chadwick et al.'s findings suggest that the mental map may be highly flexible, allowing vast numbers of distinct memories to be stored within the same network of place cells without interference. Future studies will involve investigating the role of brain waves in the forming new mental maps and creating new memories.

DOI:http://dx.doi.org/10.7554/eLife.03542.002

Distinct lineage-dependent structural and functional organization of the hippocampus

The hippocampus, as part of the cerebral cortex, is essential for memory formation and spatial navigation. Although it has been extensively studied, especially as a model system for neurophysiology, the cellular processes involved in constructing and organizing the hippocampus remain largely unclear. Here, we show that clonally related excitatory neurons in the developing hippocampus are progressively organized into discrete horizontal, but not vertical, clusters in the stratum pyramidale, as revealed by both cell-type-specific retroviral labeling and mosaic analysis with double markers (MADM). Moreover, distinct from those in the neocortex, sister excitatory neurons in the cornu ammonis 1 region of the hippocampus rarely develop electrical or chemical synapses with each other. Instead, they preferentially receive common synaptic input from nearby fast-spiking (FS), but not non-FS, interneurons and exhibit synchronous synaptic activity. These results suggest that shared inhibitory input may specify horizontally clustered sister excitatory neurons as functional units in the hippocampus.

Acetylcholine functionally reorganizes neocortical microcircuits

Sensory information is processed and transmitted through the synaptic structure of local cortical circuits, but it is unclear how modulation of this architecture influences the cortical representation of sensory stimuli. Acetylcholine (ACh) promotes attention and arousal and is thought to increase the signal-to-noise ratio of sensory input in primary sensory cortices. Using high-speed two-photon calcium imaging in a thalamocortical somatosensory slice preparation, we recorded action potential activity of up to 900 neurons simultaneously and compared local cortical circuit activations with and without bath presence of ACh. We found that ACh reduced weak pairwise relationships and excluded neurons that were already unreliable during circuit activity. Using action potential activity from the imaged population, we generated functional wiring diagrams based on the statistical dependencies of activity between neurons. ACh pruned weak functional connections from spontaneous circuit activations and yielded a more modular and hierarchical circuit structure, which biased activity to flow in a more feedforward fashion. Neurons that were active in response to thalamic input had reduced pairwise dependencies overall, but strong correlations were conserved. This coincided with a prolonged period during which neurons showed temporally precise responses to thalamic input. Our results demonstrate that ACh reorganizes functional circuit structure in a manner that may enhance the integration and discriminability of thalamic afferent input within local neocortical circuitry.

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

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

Structured connectivity in cerebellar inhibitory networks

Defining the rules governing synaptic connectivity is key to formulating theories of neural circuit function. Interneurons can be connected by both electrical and chemical synapses, but the organization and interaction of these two complementary microcircuits is unknown. By recording from multiple molecular layer interneurons in the cerebellar cortex, we reveal specific, nonrandom connectivity patterns in both GABAergic chemical and electrical interneuron networks. Both networks contain clustered motifs and show specific overlap between them. Chemical connections exhibit a preference for transitive patterns, such as feedforward triplet motifs. This structured connectivity is supported by a characteristic spatial organization: transitivity of chemical connectivity is directed vertically in the sagittal plane, and electrical synapses appear strictly confined to the sagittal plane. The specific, highly structured connectivity rules suggest that these motifs are essential for the function of the cerebellar network.

Cannabinoid neuromodulation in the adult early visual cortex

Sensory processing is an active process involving the interaction of ongoing cortical activity with incoming stimulus information. However, the modulators and circuits involved in this interaction are incompletely understood. One potential candidate is the cannabinoid-signaling system, which is known to modulate the dynamics of cortical networks. Here, we show that in the primate primary and secondary visual cortices, the cannabinoid CP55940 modulates not only population dynamics but also influences the dynamics of the stimulus-response relationship of individual neurons. At the population level, CP55940 decreases EEG power, LFP power, and LFP coherence. At the single-neuron level, intrinsic spike train dynamics appear relatively unchanged, but visual receptive fields are altered: CP55940 induced an overall delay and broadening of the temporal component of V1 and V2 spatiotemporal receptive fields. Our findings provide neurophysiologic evidence for a link between cannabinoid-signaling, network dynamics and the function of a canonical cortical circuit.

A blanket of inhibition: functional inferences from dense inhibitory connectivity

The function of neocortical interneurons is still unclear, and, as often happens, one may be able to draw functional insights from considering the structure. In this spirit we describe recent structural results and discuss their potential functional implications. Most GABAergic interneurons innervate nearby pyramidal neurons very densely and without any apparent specificity, as if they were extending a 'blanket of inhibition', contacting pyramidal neurons often in an overlapping fashion. While subtypes of interneurons specifically target subcellular compartments of pyramidal cells, and they also target different layers selectively, they appear to treat all neighboring pyramidal cells the same and innervate them massively. We explore the functional implications and temporal properties of dense, overlapping inhibition by four interneuron populations.

Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex

Mouse visual cortex is subdivided into multiple distinct, hierarchically organized areas that are interconnected through feedforward (FF) and feedback (FB) pathways. The principal synaptic targets of FF and FB axons that reciprocally interconnect primary visual cortex (V1) with the higher lateromedial extrastriate area (LM) are pyramidal cells (Pyr) and parvalbumin (PV)-expressing GABAergic interneurons. Recordings in slices of mouse visual cortex have shown that layer 2/3 Pyr cells receive excitatory monosynaptic FF and FB inputs, which are opposed by disynaptic inhibition. Most notably, inhibition is stronger in the FF than FB pathway, suggesting pathway-specific organization of feedforward inhibition (FFI). To explore the hypothesis that this difference is due to diverse pathway-specific strengths of the inputs to PV neurons we have performed subcellular Channelrhodopsin-2-assisted circuit mapping in slices of mouse visual cortex. Whole-cell patch-clamp recordings were obtained from retrobead-labeled FF(V1→LM)- and FB(LM→V1)-projecting Pyr cells, as well as from tdTomato-expressing PV neurons. The results show that the FF(V1→LM) pathway provides on average 3.7-fold stronger depolarizing input to layer 2/3 inhibitory PV neurons than to neighboring excitatory Pyr cells. In the FB(LM→V1) pathway, depolarizing inputs to layer 2/3 PV neurons and Pyr cells were balanced. Balanced inputs were also found in the FF(V1→LM) pathway to layer 5 PV neurons and Pyr cells, whereas FB(LM→V1) inputs to layer 5 were biased toward Pyr cells. The findings indicate that FFI in FF(V1→LM) and FB(LM→V1) circuits are organized in a pathway- and lamina-specific fashion.