Parvalbumin-expressing interneurons can act solo while somatostatin-expressing interneurons act in chorus in most cases on cortical pyramidal cells

Interacting rhythms enhance sensitivity of target detection in a fronto-parietal computational model of visual attention

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at α, β, and γ frequencies-rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by θ-rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

Key role of neuronal diversity in structured reservoir computing

Chaotic time series have been captured by reservoir computing models composed of a recurrent neural network whose output weights are trained in a supervised manner. These models, however, are typically limited to randomly connected networks of homogeneous units. Here, we propose a new class of structured reservoir models that incorporates a diversity of cell types and their known connections. In a first version of the model, the reservoir was composed of mean-rate units separated into pyramidal, parvalbumin, and somatostatin cells. Stability analysis of this model revealed two distinct dynamical regimes, namely, (i) an inhibition-stabilized network (ISN) where strong recurrent excitation is balanced by strong inhibition and (ii) a non-ISN network with weak excitation. These results were extended to a leaky integrate-and-fire model that captured different cell types along with their network architecture. ISN and non-ISN reservoir networks were trained to relay and generate a chaotic Lorenz attractor. Despite their increased performance, ISN networks operate in a regime of activity near the limits of stability where external perturbations yield a rapid divergence in output. The proposed framework of structured reservoir computing opens avenues for exploring how neural microcircuits can balance performance and stability when representing time series through distinct dynamical regimes.

Somatostatin-Positive Interneurons Contribute to Seizures in SCN8A Epileptic Encephalopathy

SCN8A epileptic encephalopathy is a devastating epilepsy syndrome caused by mutant SCN8A, which encodes the voltage-gated sodium channel Na_V1.6. To date, it is unclear if and how inhibitory interneurons, which express Na_V1.6, influence disease pathology. Using both sexes of a transgenic mouse model of SCN8A epileptic encephalopathy, we found that selective expression of the R1872W SCN8A mutation in somatostatin (SST) interneurons was sufficient to convey susceptibility to audiogenic seizures. Patch-clamp electrophysiology experiments revealed that SST interneurons from mutant mice were hyperexcitable but hypersensitive to action potential failure via depolarization block under normal and seizure-like conditions. Remarkably, GqDREADD-mediated activation of WT SST interneurons resulted in prolonged electrographic seizures and was accompanied by SST hyperexcitability and depolarization block. Aberrantly large persistent sodium currents, a hallmark of SCN8A mutations, were observed and were found to contribute directly to aberrant SST physiology in computational modeling and pharmacological experiments. These novel findings demonstrate a critical and previously unidentified contribution of SST interneurons to seizure generation not only in SCN8A epileptic encephalopathy, but epilepsy in general.SIGNIFICANCE STATEMENT SCN8A epileptic encephalopathy is a devastating neurological disorder that results from de novo mutations in the sodium channel isoform Na_v1.6. Inhibitory neurons express Na_V1.6, yet their contribution to seizure generation in SCN8A epileptic encephalopathy has not been determined. We show that mice expressing a human-derived SCN8A variant (R1872W) selectively in somatostatin (SST) interneurons have audiogenic seizures. Physiological recordings from SST interneurons show that SCN8A mutations lead to an elevated persistent sodium current which drives initial hyperexcitability, followed by premature action potential failure because of depolarization block. Furthermore, chemogenetic activation of WT SST interneurons leads to audiogenic seizure activity. These findings provide new insight into the importance of SST inhibitory interneurons in seizure initiation, not only in SCN8A epileptic encephalopathy, but for epilepsy broadly.

Optogenetic Activation of Interneuron Subtypes Modulates Visual Contrast Responses of Mouse V1 Neurons

Interneurons are critical for information processing in the cortex. In vitro optogenetic studies in mouse primary visual cortex (V1) have sketched the connectivity of a local neural circuit comprising excitatory pyramidal neurons and distinct interneuron subtypes that express parvalbumin (Pvalb+), somatostatin (SOM+), or vasoactive intestinal peptide (VIP+). However, in vivo studies focusing on V1 orientation tuning have ascribed discrepant computational roles to specific interneuron subtypes. Here, we sought to clarify the differences between interneuron subtypes by examining the effects of optogenetic activation of Pvalb+, SOM+, or VIP+ interneurons on contrast tuning of V1 neurons while also accounting for cortical depth and photostimulation intensity. We found that illumination of the cortical surface produced a similar spectrum of saturating additive photostimulation effects in all 3 interneuron subtypes, which varied with cortical depth rather than light intensity in Pvalb+ and SOM+ cells. Pyramidal cell modulation was well explained by a conductance-based model that incorporated these interneuron photostimulation effects.

Information Capacity of a Stochastically Responding Neuron Assembly

In this work, certain aspects of the structure of the overlapping groups of neurons encoding specific signals are examined. Individual neurons are assumed to respond stochastically to input signal. Identification of a particular signal is assumed to result from the aggregate activity of a group of neurons, which we call information pathway. Conditions for definite response and for non-interference of pathways are derived. These conditions constrain the response properties of individual neurons and the allowed overlap among pathways. Under these constrains, and under the simplifying assumption that all pathways have similar structure, the information capacity of the system is derived. Furthermore, we show that there is a definite advantage in the information capacity if pathway neurons areinterspersed among the neuron assembly.

Flexible Frequency Switching in Adult Mouse Visual Cortex Is Mediated by Competition Between Parvalbumin and Somatostatin Expressing Interneurons

Neuronal networks in rodent primary visual cortex (V1) can generate oscillations in different frequency bands depending on the network state and the level of visual stimulation. High-frequency gamma rhythms, for example, dominate the network's spontaneous activity in adult mice but are attenuated upon visual stimulation, during which the network switches to the beta band instead. The spontaneous local field potential (LFP) of juvenile mouse V1, however, mainly contains beta rhythms and presenting a stimulus does not elicit drastic changes in network oscillations. We study, in a spiking neuron network model, the mechanism in adult mice allowing for flexible switches between multiple frequency bands and contrast this to the network structure in juvenile mice that lack this flexibility. The model comprises excitatory pyramidal cells (PCs) and two types of interneurons: the parvalbumin-expressing (PV) and the somatostatinexpressing (SOM) interneuron. In accordance with experimental findings, the pyramidal-PV and pyramidal-SOM cell subnetworks are associated with gamma and beta oscillations, respectively. In our model, they are both generated via a pyramidal-interneuron gamma (PING) mechanism, wherein the PCs drive the oscillations. Furthermore, we demonstrate that large but not small visual stimulation activates SOM cells, which shift the frequency of resting-state gamma oscillations produced by the pyramidal-PV cell subnetwork so that beta rhythms emerge. Finally, we show that this behavior is obtained for only a subset of PV and SOM interneuron projection strengths, indicating that their influence on the PCs should be balanced so that they can compete for oscillatory control of the PCs. In sum, we propose a mechanism by which visual beta rhythms can emerge from spontaneous gamma oscillations in a network model of the mouse V1; for this mechanism to reproduce V1 dynamics in adult mice, balance between the effective strengths of PV and SOM cells is required.

Chemogenetic Inhibition of Infralimbic Prefrontal Cortex GABAergic Parvalbumin Interneurons Attenuates the Impact of Chronic Stress in Male Mice

Hypofunction of the prefrontal cortex (PFC) contributes to stress-related neuropsychiatric illnesses. Mechanisms leading to prefrontal hypoactivity remain to be determined. Prior evidence suggests that chronic stress leads to an increase in activity of parvalbumin (PV) expressing GABAergic interneurons (INs) in the PFC. The purpose of the study was to determine whether reducing PV IN activity in the Infralimbic (IL) PFC would prevent stress-related phenotypes. We used a chemogenetic approach to inhibit IL PFC PV INs during stress. Mice were first tested in the tail suspension test (TST) to determine the impact of PV IN inhibition on behavioral responses to acute stress. The long-term impact of PV IN inhibition during a modified chronic variable stress (CVS) was tested in the forced swim test (FST). Acute PV IN inhibition reduced active (struggling) and increased passive coping behaviors (immobility) in the TST. In contrast, inhibition of PV INs during CVS increased active and reduced passive coping behaviors in the FST. Moreover, chronic inhibition of PV INs attenuated CVS-induced changes in Fos expression in the prelimbic cortex (PrL), basolateral amygdala (BLA), and ventrolateral periaqueductal gray (vlPAG) and also attenuated adrenal hypertrophy and body weight loss associated with chronic stress. Our results suggest differential roles of PV INs in acute versus chronic stress, indicative of distinct biological mechanisms underlying acute versus chronic stress responses. Our results also indicate a role for PV INs in driving chronic stress adaptation and support literature evidence suggesting cortical GABAergic INs as a therapeutic target in stress-related illnesses.

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.

Exciting Complexity: The Role of Motor Circuit Elements in ALS Pathophysiology

Amyotrophic lateral sclerosis (ALS) is a fatal disease, characterized by the degeneration of both upper and lower motor neurons. Despite decades of research, we still to date lack a cure or disease modifying treatment, emphasizing the need for a much-improved insight into disease mechanisms and cell type vulnerability. Altered neuronal excitability is a common phenomenon reported in ALS patients, as well as in animal models of the disease, but the cellular and circuit processes involved, as well as the causal relevance of those observations to molecular alterations and final cell death, remain poorly understood. Here, we review evidence from clinical studies, cell type-specific electrophysiology, genetic manipulations and molecular characterizations in animal models and culture experiments, which argue for a causal involvement of complex alterations of structure, function and connectivity of different neuronal subtypes within the cortical and spinal cord motor circuitries. We also summarize the current knowledge regarding the detrimental role of astrocytes and reassess the frequently proposed hypothesis of glutamate-mediated excitotoxicity with respect to changes in neuronal excitability. Together, these findings suggest multifaceted cell type-, brain area- and disease stage- specific disturbances of the excitation/inhibition balance as a cardinal aspect of ALS pathophysiology.

Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured with functional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here a putative mechanism reported in neurodevelopmental disorders, that is, excitation-to-inhibition ratio (E:I), was chemogenetically increased within cortical microcircuits of the mouse brain and measured via fMRI. Increased E:I caused a significant "reduction" of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin (PV) interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knockout mice, a model for autism with well-documented loss of parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

Cortical Microcircuit Mechanisms of Mismatch Negativity and Its Underlying Subcomponents

In the neocortex, neuronal processing of sensory events is significantly influenced by context. For instance, responses in sensory cortices are suppressed to repetitive or redundant stimuli, a phenomenon termed “stimulus-specific adaptation” (SSA). However, in a context in which that same stimulus is novel, or deviates from expectations, neuronal responses are augmented. This augmentation is termed “deviance detection” (DD). This contextual modulation of neural responses is fundamental for how the brain efficiently processes the sensory world to guide immediate and future behaviors. Notably, context modulation is deficient in some neuropsychiatric disorders such as schizophrenia (SZ), as quantified by reduced “mismatch negativity” (MMN), an electroencephalography waveform reflecting a combination of SSA and DD in sensory cortex. Although the role of NMDA-receptor function and other neuromodulatory systems on MMN is established, the precise microcircuit mechanisms of MMN and its underlying components, SSA and DD, remain unknown. When coupled with animal models, the development of powerful precision neurotechnologies over the past decade carries significant promise for making new progress into understanding the neurobiology of MMN with previously unreachable spatial resolution. Currently, rodent models represent the best tool for mechanistic study due to the vast genetic tools available. While quantifying human-like MMN waveforms in rodents is not straightforward, the “oddball” paradigms used to study it in humans and its underlying subcomponents (SSA/DD) are highly translatable across species. Here we summarize efforts published so far, with a focus on cortically measured SSA and DD in animals to maintain relevance to the classically measured MMN, which has cortical origins. While mechanistic studies that measure and contrast both components are sparse, we synthesize a potential set of microcircuit mechanisms from the existing rodent, primate, and human literature. While MMN and its subcomponents likely reflect several mechanisms across multiple brain regions, understanding fundamental microcircuit mechanisms is an important step to understand MMN as a whole. We hypothesize that SSA reflects adaptations occurring at synapses along the sensory-thalamocortical pathways, while DD depends on both SSA inherited from afferent inputs and resulting disinhibition of non-adapted neurons arising from the distinct physiology and wiring properties of local interneuronal subpopulations and NMDA-receptor function.

Prefrontal parvalbumin cells are sensitive to stress and mediate anxiety-related behaviors in female mice

Reduced activity of the prefrontal cortex (PFC) is seen in mood disorders including depression and anxiety. The mechanisms of this hypofrontality remain unclear. Because of their specific physiological properties, parvalbumin-expressing (PV⁺) inhibitory interneurons contribute to the overall activity of the PFC. Our recent work using a chronic stress mouse model showed that stress-induced increases in prefrontal PV expression correlates with increased anxiety-like behaviors in female mice. Our goal is now to provide a causal relationship between changes in prefrontal PV⁺ cells and changes in emotional behaviors in mice. We first show that, in addition to increasing overall level of PV expression, chronic stress increases the activity of prefrontal PV⁺ cells. We then used a chemogenetic approach to mimic the effects of chronic stress and specifically increase the activity of prefrontal PV⁺ cells. We observed that chemogenetic activation of PV⁺ cells caused an overall reduction in prefrontal activity, and that chronic activation of PV⁺ cells lead to increased anxiety-related behaviors in female mice only. These results demonstrate that activity of prefrontal PV⁺ cells could represent a novel sex-specific modulator of anxiety-related behaviors, potentially through changes in overall prefrontal activity. The findings also support the idea that prefrontal PV⁺ cells are worth further investigation to better understand mood disorders that are more prevalent in female populations.

Tsc1 represses parvalbumin expression and fast-spiking properties in somatostatin lineage cortical interneurons

Medial ganglionic eminence (MGE)-derived somatostatin (SST)+ and parvalbumin (PV)+ cortical interneurons (CINs), have characteristic molecular, anatomical and physiological properties. However, mechanisms regulating their diversity remain poorly understood. Here, we show that conditional loss of the Tuberous Sclerosis Complex (TSC) gene, Tsc1, which inhibits the mammalian target of rapamycin (MTOR), causes a subset of SST+ CINs, to express PV and adopt fast-spiking (FS) properties, characteristic of PV+ CINs. Milder intermediate phenotypes also occur when only one allele of Tsc1 is deleted. Notably, treatment of adult mice with rapamycin, which inhibits MTOR, reverses the phenotypes. These data reveal novel functions of MTOR signaling in regulating PV expression and FS properties, which may contribute to TSC neuropsychiatric symptoms. Moreover, they suggest that CINs can exhibit properties intermediate between those classically associated with PV+ or SST+ CINs, which may be dynamically regulated by the MTOR signaling.

Prefrontal excitatory/inhibitory balance in stress and emotional disorders: Evidence for over-inhibition

Chronic stress-induced emotional disorders like anxiety and depression involve imbalances between the excitatory glutamatergic system and the inhibitory GABAergic system in the prefrontal cortex (PFC). However, the precise nature and trajectory of excitatory/inhibitory (E/I) imbalances in these conditions is not clear, with the literature reporting glutamatergic and GABAergic findings that are at times contradictory and inconclusive. Here we propose and discuss the hypothesis that chronic stress-induced emotional dysfunction involves hypoactivity of the PFC due to increased inhibition. We will also discuss E/I imbalances in the context of sex differences. In this review, we will synthesize research about how glutamatergic and GABAergic systems are perturbed by chronic stress and in related emotional disorders like anxiety and depression and propose ideas for reconciling contradictory findings in support of the hypothesis of over-inhibition. We will also discuss evidence for how aspects of the GABAergic system such as parvalbumin (PV) cells can be targeted therapeutically for reinstating activity and plasticity in the PFC and treating stress-related disorders.

Inhibitory Units: An Organizing Nidus for Feature-Selective SubNetworks in Area V1

Neuronal circuits often display small-world network architecture characterized by neuronal cliques of dense local connectivity communicating with each other through a limited number of cells that participate in multiple cliques. The principles by which such cliques organize to encode information remain poorly understood. Similarly tuned pyramidal cells that preferentially target each other may form multicellular encoding units performing distinct computational tasks. The existence of such units can reflect upon both spontaneous and stimulus-driven population events.We applied two-photon calcium imaging to study spontaneous population bursts in layer 2/3 of area V1 in male C57BL/6 mice. To identify potential small-world cliques, we searched for pyramidal cells whose calcium events had a consistent temporal relationship with the events of local inhibitory interneurons. This was guided by the intuition that groups of neurons whose synchronous firing represents a temporally coherent computational unit should be inhibited together. Pyramidal members of these interneuron-centered clusters on average displayed stronger functional connectivity between each other than with nonmember pyramidal neurons. The structure of the clusters evolved during postnatal development: cluster size and overlap between clusters decreased with developmental maturation. Pyramidal neurons in a cluster showed higher than chance tuning function similarity between each other and with the linked interneuron. Thus, spontaneous population events in V1 are shaped by small-world subnetworks of pyramidal neurons that share functional properties and work as a coherent unit with a local interneuron. These interneuron-pyramidal cell partnerships may represent a fundamental neocortical unit of computation at the population level.SIGNIFICANCE STATEMENT Neuronal circuit in layer 2/3 of mouse area V1 possesses small-world network architecture, where cliques of densely interconnected neurons ("small worlds") communicate via restricted number of hub cells. We show that: (1) in mouse V1 individual small-world cliques preferably incorporate pyramidal neurons with similar visual feature tuning, and (2) ongoing population activity of such pyramidal neuron clique is temporally linked to the activity of the local interneuron sharing its feature tuning with the clique members. Functional grouping of similarly tuned interneurons and pyramidal cells into cliques may ensure that ensembles of functionally alike pyramidal cells recruited during perceptual tasks and spontaneous activity are also turned off together as a unit, with interneurons serving as organizers of linked pyramidal ensemble activity.

Electrophysiological Profiling of Neocortical Neural Subtypes: A Semi-Supervised Method Applied to in vivo Whole-Cell Patch-Clamp Data

A lot of efforts have been made to understand the structure and function of neocortical circuits. In fact, a promising way to understand the functions of cortical circuits is the classification of the neural types, based on their different properties. Recent studies focused on applying modern computational methods to classify neurons based on molecular, morphological, physiological, or mixed of these criteria. Although there are studies in the literature on in vitro/vivo extracellular or in vitro intracellular recordings, a study on the classification of neuronal types using in vivo whole-cell patch-clamp recordings is still lacking. We thus proposed a novel semi-supervised classification method based on waveform shape of neurons' spikes using in vivo whole-cell patch-clamp recordings. We, first, detected spike candidates. Then discriminative features were extracted from the time samples of the spikes using discrete cosine transform. We then extracted the center of clusters using fuzzy c-mean clustering and finally, the neurons were classified using the minimum distance classifier. We distinguished three types of neurons: excitatory pyramidal cells (Pyr) and two types of inhibitory neurons: GABAergic- parvalbumin positive (PV), and somatostatin positive (SST) non-pyramidal cells in layer II/III of the mice primary visual cortex. We used 10-fold cross validation in our study. The classification accuracy for PV, Pyr, and SST was 91.59 ± 1.69, 97.47 ± 0.67, and 89.06 ± 1.99, respectively. Overall, the algorithm correctly classified 92.67 ± 0.54% of the cells, confirming the relative robustness of the discriminant functions. The performance of the method was further assessed on in vitro recordings by using a pool of 50 neurons from Allen institute Cell Types Database (5 major subtypes of neurons: Pyr, PV, SST, 5HT3a, and vasoactive intestinal peptide (VIP) cells). Its overall accuracy was 84.13 ± 0.81% on this data set using cross validation framework. The proposed algorithm is thus a promising new tool in recognizing cell's type with high accuracy in laboratories using in vivo/vitro whole-cell patch-clamp recording technique. The developed programs and the entire dataset are available online to interested readers.

State-dependent cell-type-specific membrane potential dynamics and unitary synaptic inputs in awake mice

The cellular and synaptic mechanisms driving cell-type-specific function during various cortical network activities and behaviors are poorly understood. Here, we targeted whole-cell recordings to two classes of inhibitory GABAergic neurons in layer 2/3 of the barrel cortex of awake head-restrained mice and correlated spontaneous membrane potential dynamics with cortical state and whisking behavior. Using optogenetic stimulation of single layer 2/3 excitatory neurons we measured unitary excitatory postsynaptic potentials (uEPSPs) across states. During active states, characterized by whisking and reduced low-frequency activity in the local field potential, parvalbumin-expressing neurons depolarized and, albeit in a small number of recordings, received uEPSPs with increased amplitude. In contrast, somatostatin-expressing neurons hyperpolarized and reduced firing rates during active states without consistent change in uEPSP amplitude. These results further our understanding of neocortical inhibitory neuron function in awake mice and are consistent with the hypothesis that distinct genetically-defined cell classes have different state-dependent patterns of activity.