An extended toolkit for production and use of RVdG-CVS-N2c rabies viral vectors uncovers hidden hippocampal connections

From the large collection of molecular tools used to investigate neuronal connectivity, envA-pseudotyped rabies viral vectors (RVdGenvA) uniquely enable cell-type specific, trans-synaptic retrograde labeling. However, widespread use of the powerful and flexible method is to date hindered by low-yield and cumbersome production pipelines. Here, we report the development of new cell lines, which significantly reduce production time while increasing viral titer and eliminating background contamination from native-coat particles. We further show that RVdGenvA-CVS-N2c vectors produced using this system retain their enhanced retrograde-trafficking when compared with SAD-B19 vectors, allowing us to uncover undescribed cortico-hippocampal connections and to monitor activity in a cortical microcircuit of behaving animals. Along with new suites of AAV and RVdG-CVS-N2c vectors, developed to enable retrograde labeling from a wide range of neuronal populations and tailored for diverse experimental requirements, we present here an optimal system for mapping, manipulating and imaging of neuronal circuits.

Analysis of the computational strategy of a detailed laminar cortical microcircuit model for solving the image-change-detection task

The neocortex can be viewed as a tapestry consisting of variations of rather stereotypical local cortical microcircuits. Hence understanding how these microcircuits compute holds the key to understanding brain function. Intense research efforts over several decades have culminated in a detailed model of a generic cortical microcircuit in the primary visual cortex from the Allen Institute. We are presenting here methods and first results for understanding computational properties of this large-scale data-based model. We show that it can solve a standard image-change-detection task almost as well as the living brain. Furthermore, we unravel the computational strategy of the model and elucidate the computational role of diverse subtypes of neurons. Altogether this work demonstrates the feasibility and scientific potential of a methodology based on close interaction of detailed data and large-scale computer modelling for understanding brain function.

Mitochondrial, exosomal miR137-COX6A2 and gamma synchrony as biomarkers of parvalbumin interneurons, psychopathology, and neurocognition in schizophrenia

Early detection and intervention in schizophrenia requires mechanism-based biomarkers that capture neural circuitry dysfunction, allowing better patient stratification, monitoring of disease progression and treatment. In prefrontal cortex and blood of redox dysregulated mice (Gclm-KO ± GBR), oxidative stress induces miR-137 upregulation, leading to decreased COX6A2 and mitophagy markers (NIX, Fundc1, and LC3B) and to accumulation of damaged mitochondria, further exacerbating oxidative stress and parvalbumin interneurons (PVI) impairment. MitoQ, a mitochondria-targeted antioxidant, rescued all these processes. Translating to early psychosis patients (EPP), blood exosomal miR-137 increases and COX6A2 decreases, combined with mitophagy markers alterations, suggest that observations made centrally and peripherally in animal model were reflected in patients’ blood. Higher exosomal miR-137 and lower COX6A2 levels were associated with a reduction of ASSR gamma oscillations in EEG. As ASSR requires proper PVI-related networks, alterations in miR-137/COX6A2 plasma exosome levels may represent a proxy marker of PVI cortical microcircuit impairment. EPP can be stratified in two subgroups: (a) a patients’ group with mitochondrial dysfunction “Psy-D”, having high miR-137 and low COX6A2 levels in exosomes, and (b) a “Psy-ND” subgroup with no/low mitochondrial impairment, including patients having miR-137 and COX6A2 levels in the range of controls. Psy-D patients exhibited more impaired ASSR responses in association with worse psychopathological status, neurocognitive performance, and global and social functioning, suggesting that impairment of PVI mitochondria leads to more severe disease profiles. This stratification would allow, with high selectivity and specificity, the selection of patients for treatments targeting brain mitochondria dysregulation and capture the clinical and functional efficacy of future clinical trials.

Myelin speeds cortical oscillations by consolidating phasic parvalbumin-mediated inhibition

Parvalbumin-positive (PV+) γ-aminobutyric acid (GABA) interneurons are critically involved in producing rapid network oscillations and cortical microcircuit computations but the significance of PV+ axon myelination to the temporal features of inhibition remains elusive. Here using toxic and genetic models of demyelination and dysmyelination, respectively, we find that loss of compact myelin reduces PV+ interneuron presynaptic terminals, increases failures and the weak phasic inhibition of pyramidal neurons abolishes optogenetically driven gamma oscillations in vivo. Strikingly, during periods of quiet wakefulness selectively theta rhythms are amplified and accompanied by highly synchronized interictal epileptic discharges. In support of a causal role of impaired PV-mediated inhibition, optogenetic activation of myelin-deficient PV+ interneurons attenuated the power of slow theta rhythms and limited interictal spike occurrence. Thus, myelination of PV+ axons is required to consolidate fast inhibition of pyramidal neurons and enable behavioral state-dependent modulation of local circuit synchronization.

High-frequency burst spiking in layer 5 thick-tufted pyramids of rat primary somatosensory cortex encodes exploratory touch

Diversity of cell-types that collectively shape the cortical microcircuit ensures the necessary computational richness to orchestrate a wide variety of behaviors. The information content embedded in spiking activity of identified cell-types remain unclear to a large extent. Here, we recorded spike responses upon whisker touch of anatomically identified excitatory cell-types in primary somatosensory cortex in naive, untrained rats. We find major differences across layers and cell-types. The temporal structure of spontaneous spiking contains high-frequency bursts (≥100 Hz) in all morphological cell-types but a significant increase upon whisker touch is restricted to layer L5 thick-tufted pyramids (L5tts) and thus provides a distinct neurophysiological signature. We find that whisker touch can also be decoded from L5tt bursting, but not from other cell-types. We observed high-frequency bursts in L5tts projecting to different subcortical regions, including thalamus, midbrain and brainstem. We conclude that bursts in L5tts allow accurate coding and decoding of exploratory whisker touch.

NetPyNE Implementation and Scaling of the Potjans-Diesmann Cortical Microcircuit Model

The Potjans-Diesmann cortical microcircuit model is a widely used model originally implemented in NEST. Here, we reimplemented the model using NetPyNE, a high-level Python interface to the NEURON simulator, and reproduced the findings of the original publication. We also implemented a method for scaling the network size that preserves first- and second-order statistics, building on existing work on network theory. Our new implementation enabled the use of more detailed neuron models with multicompartmental morphologies and multiple biophysically realistic ion channels. This opens the model to new research, including the study of dendritic processing, the influence of individual channel parameters, the relation to local field potentials, and other multiscale interactions. The scaling method we used provides flexibility to increase or decrease the network size as needed when running these CPU-intensive detailed simulations. Finally, NetPyNE facilitates modifying or extending the model using its declarative language; optimizing model parameters; running efficient, large-scale parallelized simulations; and analyzing the model through built-in methods, including local field potential calculation and information flow measures.

Antagonistic inhibitory subnetworks control cooperation and competition across cortical space

The cortical microcircuit can dynamically adjust to dramatic changes in the strength, scale, and complexity of its input. In the primary visual cortex (V1), pyramidal cells (PCs) integrate widely across space when signals are weak, but integrate narrowly when signals are strong, a phenomenon known as contrast-dependent surround suppression. Theoretical work has proposed that local interneurons could mediate a shift from cooperation to competition of PCs across cortical space, underlying this computation. We combine calcium imaging and electrophysiology to constrain a stabilized superlinear network model that explains how the four principal cell types in layer 2/3 (L2/3) of mouse V1– somatostatin (SST), parvalbumin (PV), and vasoactive intestinal peptide (VIP) interneurons, and PCs transform inputs from layer 4 (L4) PCs to encode drifting gratings of varying size and contrast. Using bidirectional optogenetic perturbations, we confirm key predictions of the model. Our data and modeling show that network nonlinearities set up by recurrent amplification mediate a shift from a positive PC-VIP feedback loop at small size and low contrast to a negative PC-SST feedback loop at large size and high contrast to support this flexible computation. This may represent a widespread mechanism for gating competition across cortical space to optimally meet task demands.