Neuronal cell-type and circuit basis for visual predictive processing

Bayesian Brain theory suggests brain utilises predictive processing framework to interpret the noisy world. Predictive processing is essential to perception, action, cognition and psychiatric disease, but underlying neural circuit mechanisms remain undelineated. Here we show the neuronal cell-type and circuit basis for visual predictive processing in awake, head-fixed mice during self-initiated running. Preceding running, vasoactive intestinal peptide (VIP)-expressing inhibitory interneurons (INs) in primary visual cortex (V1) are robustly activated in absence of structured visual stimuli. This pre-running activation is mediated via distal top-down projections from frontal, parietal and retrosplenial areas known for motion planning, but not local excitatory inputs associated with the bottom-up pathway. Somatostatin (SST) INs show pre-running suppression and post-running activation, indicating a VIP-SST motif. Differential VIP-SST peri-running dynamics anisotropically suppress neighbouring pyramidal (Pyr) neurons, preadapting Pyr neurons to the incoming running. Our data delineate key neuron types and circuit elements of predictive processing brain employs in action and perception.

A network model of the modulation of gamma oscillations by NMDA receptors in cerebral cortex

Psychotic drugs such as ketamine induce symptoms close to schizophrenia, and stimulates the production of gamma oscillations, as also seen in patients, but the underlying mechanisms are still unclear. Here, we have used computational models of cortical networks generating gamma oscillations, and have integrated the action of drugs such as ketamine to partially block n-methyl-d-Aspartate (NMDA) receptors. The model can reproduce the modulation of gamma oscillations by NMDA-receptor antagonists, assuming that antagonists affect NMDA receptors predominantly on inhibitory interneurons. We next used the model to compare the responsiveness of the network to external stimuli, and found that when NMDA channnels are blocked an increase of Gamma power is observed altogether with an increase of network responsiveness. However, this responsiveness increase applies not only to gamma states, but also to synchronous states with no apparent gamma. We conclude that NMDA antagonists induce increased excitability state, which may or may not produce gamma oscillations, but the response to external inputs is exacerbated, which may explain phenomena such as altered perception or hallucinations.

Supercritical dynamics at the edge-of-chaos underlies optimal decision-making

Critical dynamics, characterized by scale-free neuronal avalanches, is thought to underlie optimal function in the sensory cortices by maximizing information transmission, capacity, and dynamic range. In contrast, deviations from criticality have not yet been considered to support any cognitive processes. Nonetheless, neocortical areas related to working memory and decision-making seem to rely on long-lasting periods of ignition-like persistent firing. Such firing patterns are reminiscent of supercritical states where runaway excitation dominates the circuit dynamics. In addition, a macroscopic gradient of the relative density of Somatostatin (SST+) and Parvalbumin (PV+) inhibitory interneurons throughout the cortical hierarchy has been suggested to determine the functional specialization of low- versus high-order cortex. These observations thus raise the question of whether persistent activity in high-order areas results from the intrinsic features of the neocortical circuitry. We used an attractor model of the canonical cortical circuit performing a perceptual decision-making task to address this question. Our model reproduces the known saddle-node bifurcation where persistent activity emerges, merely by increasing the SST+/PV+ ratio while keeping the input and recurrent excitation constant. The regime beyond such a phase transition renders the circuit increasingly sensitive to random fluctuations of the inputs -i.e., chaotic-, defining an optimal SST+/PV+ ratio around the edge-of-chaos. Further, we show that both the optimal SST+/PV+ ratio and the region of the phase transition decrease monotonically with increasing input noise. This suggests that cortical circuits regulate their intrinsic dynamics via inhibitory interneurons to attain optimal sensitivity in the face of varying uncertainty. Hence, on the one hand, we link the emergence of supercritical dynamics at the edge-of-chaos to the gradient of the SST+/PV+ ratio along the cortical hierarchy, and, on the other hand, explain the behavioral effects of the differential regulation of SST+ and PV+ interneurons by neuromodulators like acetylcholine in the presence of input uncertainty.

Meta-Analysis of cortical inhibitory interneurons markers landscape and their performances in scRNA-seq studies.

The mammalian cortex contains a great variety of neuronal cells. In particular, GABAergic interneurons, which play a major role in neuronal circuit function, exhibit an extraordinary diversity of cell types. In this regard, single-cell RNA-seq analysis is crucial to study cellular heterogeneity. To identify and analyze rare cell types, it is necessary to reliably label cells through known markers. In this way, all the related studies are dependent on the quality of the employed marker genes. Therefore, in this work, we investigate how a set of chosen inhibitory interneurons markers perform. The gene set consists of both immunohistochemistry-derived genes and single-cell RNA-seq taxonomy ones. We employed various human and mouse datasets of the brain cortex, consequently processed with the Monocle3 pipeline. We defined metrics based on the relations between unsupervised cluster results and the marker expression. Specifically, we calculated the specificity, the fraction of cells expressing, and some metrics derived from decision tree analysis like entropy gain and impurity reduction. The results highlighted the strong reliability of some markers but also the low quality of others. More interestingly, though, a correlation emerges between the general performances of the genes set and the experimental quality of the datasets. Therefore, the proposed method allows evaluating the quality of a dataset in relation to its reliability regarding the inhibitory interneurons cellular heterogeneity study.

Btbd11 is an inhibitory interneuron specific synaptic scaffolding protein that supports excitatory synapse structure and function

Synapses in the brain exhibit cell–type–specific differences in basal synaptic transmission and plasticity. Here, we evaluated cell–type–specific differences in the composition of glutamatergic synapses, identifying Btbd11, as an inhibitory interneuron–specific synapse–enriched protein. Btbd11 is highly conserved across species and binds to core postsynaptic proteins including Psd–95. Intriguingly, we show that Btbd11 can undergo liquid–liquid phase separation when expressed with Psd–95, supporting the idea that the glutamatergic post synaptic density in synapses in inhibitory and excitatory neurons exist in a phase separated state. Knockout of Btbd11 from inhibitory interneurons decreased glutamatergic signaling onto parvalbumin–positive interneurons. Further, both in vitro and in vivo, we find that Btbd11 knockout disrupts network activity. At the behavioral level, Btbd11 knockout from interneurons sensitizes mice to pharmacologically induced hyperactivity following NMDA receptor antagonist challenge. Our findings identify a cell–type–specific protein that supports glutamatergic synapse function in inhibitory interneurons–with implication for circuit function and animal behavior.

Longitudinal functional imaging of VIP interneurons reveals sup-population specific effects of stroke that are rescued with chemogenetic therapy

Stroke profoundly disrupts cortical excitability which impedes recovery, but how it affects the function of specific inhibitory interneurons, or subpopulations therein, is poorly understood. Interneurons expressing vasoactive intestinal peptide (VIP) represent an intriguing stroke target because they can regulate cortical excitability through disinhibition. Here we chemogenetically augmented VIP interneuron excitability in a murine model of photothrombotic stroke and show that it enhances somatosensory responses and improves recovery of paw function. Using longitudinal calcium imaging, we discovered that stroke primarily disrupts the fidelity (fraction of responsive trials) and predictability of sensory responses within a subset of highly active VIP neurons. Partial recovery of responses occurred largely within these active neurons and was not accompanied by the recruitment of minimally active neurons. Importantly, chemogenetic stimulation preserved sensory response fidelity and predictability in highly active neurons. These findings provide a new depth of understanding into how stroke and prospective therapies (chemogenetics), can influence subpopulations of inhibitory interneurons.

Mosaic and non-mosaic pcdh19 mutation leads to neuronal hyperexcitability in zebrafish

Epilepsy is one of the most common neurological disorders. The X-linked gene PCDH19 is associated with sporadic and familial epilepsy in humans, typically with early-onset clustering seizures and intellectual disability in females but not in so-called carrier males, suggesting that mosaic PCDH19 expression is required to produce epilepsy. To characterize the role of loss of PCDH19 function in epilepsy, we generated zebrafish with truncating pcdh19 variants. We observed hyperexcitability phenotypes in both mosaic and non-mosaic pcdh19+/- and -/- mutant larvae, indicating that Pcdh19 cellular mosaicism is not required for network hyperexcitability in zebrafish. Further, zebrafish with non-mosaic pcdh19 mutation display reduced numbers of inhibitory interneurons and transcriptional down-regulation of key inhibitory synapse components, suggesting a potential cellular basis for the observed hyperexcitability. Our findings in both mosaic and non-mosaic pcdh19 mutant zebrafish challenge the prevailing theory that mosaicism governs all PCDH19-related phenotypes and point to interneuron-mediated mechanisms underlying these phenotypes.