Sensitive multicolor indicators for monitoring norepinephrine in vivo.

Genetically encoded indicators engineered from G-protein-coupled receptors are important tools that enable high-resolution in vivo neuromodulator imaging. Here, we introduce a family of sensitive multicolor norepinephrine (NE) indicators, which includes nLightG (green) and nLightR (red). These tools report endogenous NE release in vitro, ex vivo and in vivo with improved sensitivity, ligand selectivity and kinetics, as well as a distinct pharmacological profile compared with previous state-of-the-art GRABNE indicators. Using in vivo multisite fiber photometry recordings of nLightG, we could simultaneously monitor optogenetically evoked NE release in the mouse locus coeruleus and hippocampus. Two-photon imaging of nLightG revealed locomotion and reward-related NE transients in the dorsal CA1 area of the hippocampus. Thus, the sensitive NE indicators introduced here represent an important addition to the current repertoire of indicators and provide the means for a thorough investigation of the NE system.

A genetically encoded sensor for in vivo imaging of orexin neuropeptides.

Orexins (also called hypocretins) are hypothalamic neuropeptides that carry out essential functions in the central nervous system; however, little is known about their release and range of action in vivo owing to the limited resolution of current detection technologies. Here we developed a genetically encoded orexin sensor (OxLight1) based on the engineering of circularly permutated green fluorescent protein into the human type-2 orexin receptor. In mice OxLight1 detects optogenetically evoked release of endogenous orexins in vivo with high sensitivity. Photometry recordings of OxLight1 in mice show rapid orexin release associated with spontaneous running behavior, acute stress and sleep-to-wake transitions in different brain areas. Moreover, two-photon imaging of OxLight1 reveals orexin release in layer 2/3 of the mouse somatosensory cortex during emergence from anesthesia. Thus, OxLight1 enables sensitive and direct optical detection of orexin neuropeptides with high spatiotemporal resolution in living animals.

Complementary encoding of spatial information in hippocampal astrocytes.

Calcium dynamics into astrocytes influence the activity of nearby neuronal structures. However, because previous reports show that astrocytic calcium signals largely mirror neighboring neuronal activity, current information coding models neglect astrocytes. Using simultaneous two-photon calcium imaging of astrocytes and neurons in the hippocampus of mice navigating a virtual environment, we demonstrate that astrocytic calcium signals encode (i.e., statistically reflect) spatial information that could not be explained by visual cue information. Calcium events carrying spatial information occurred in topographically organized astrocytic subregions. Importantly, astrocytes encoded spatial information that was complementary and synergistic to that carried by neurons, improving spatial position decoding when astrocytic signals were considered alongside neuronal ones. These results suggest that the complementary place dependence of localized astrocytic calcium signals may regulate clusters of nearby synapses, enabling dynamic, context-dependent variations in population coding within brain circuits.

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

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

Computation of the electroencephalogram (EEG) from network models of point neurons.

The electroencephalogram (EEG) is a major tool for non-invasively studying brain function and dysfunction. Comparing experimentally recorded EEGs with neural network models is important to better interpret EEGs in terms of neural mechanisms. Most current neural network models use networks of simple point neurons. They capture important properties of cortical dynamics, and are numerically or analytically tractable. However, point neurons cannot generate an EEG, as EEG generation requires spatially separated transmembrane currents. Here, we explored how to compute an accurate approximation of a rodent's EEG with quantities defined in point-neuron network models. We constructed different approximations (or proxies) of the EEG signal that can be computed from networks of leaky integrate-and-fire (LIF) point neurons, such as firing rates, membrane potentials, and combinations of synaptic currents. We then evaluated how well each proxy reconstructed a ground-truth EEG obtained when the synaptic currents of the LIF model network were fed into a three-dimensional network model of multicompartmental neurons with realistic morphologies. Proxies based on linear combinations of AMPA and GABA currents performed better than proxies based on firing rates or membrane potentials. A new class of proxies, based on an optimized linear combination of time-shifted AMPA and GABA currents, provided the most accurate estimate of the EEG over a wide range of network states. The new linear proxies explained 85-95% of the variance of the ground-truth EEG for a wide range of network configurations including different cell morphologies, distributions of presynaptic inputs, positions of the recording electrode, and spatial extensions of the network. Non-linear EEG proxies using a convolutional neural network (CNN) on synaptic currents increased proxy performance by a further 2-8%. Our proxies can be used to easily calculate a biologically realistic EEG signal directly from point-neuron simulations thus facilitating a quantitative comparison between computational models and experimental EEG recordings.

Unaltered Network Activity and Interneuronal Firing During Spontaneous Cortical Dynamics In Vivo in a Mouse Model of Severe Myoclonic Epilepsy of Infancy.

Severe myoclonic epilepsy of infancy (SMEI) is associated with loss of function of the SCN1A gene encoding the NaV1.1 sodium channel isoform. Previous studies in Scn1a(-/+) mice during the pre-epileptic period reported selective reduction in interneuron excitability and proposed this as the main pathological mechanism underlying SMEI. Yet, the functional consequences of this interneuronal dysfunction at the circuit level in vivo are unknown. Here, we investigated whether Scn1a(-/+) mice showed alterations in cortical network function. We found that various forms of spontaneous network activity were similar in Scn1a(-/+) during the pre-epileptic period compared with wild-type (WT) in vivo. Importantly, in brain slices from Scn1a(-/+) mice, the excitability of parvalbumin (PV) and somatostatin (SST) interneurons was reduced, epileptiform activity propagated more rapidly, and complex synaptic changes were observed. However, in vivo, optogenetic reduction of firing in PV or SST cells in WT mice modified ongoing network activities, and juxtasomal recordings from identified PV and SST interneurons showed unaffected interneuronal firing during spontaneous cortical dynamics in Scn1a(-/+) compared with WT. These results demonstrate that interneuronal hypoexcitability is not observed in Scn1a(-/+) mice during spontaneous activities in vivo and suggest that additional mechanisms may contribute to homeostatic rearrangements and the pathogenesis of SMEI.

Parvalbumin-Positive Inhibitory Interneurons Oppose Propagation But Favor Generation of Focal Epileptiform Activity.

Parvalbumin (Pv)-positive inhibitory interneurons effectively control network excitability, and their optogenetic activation has been reported to block epileptic seizures. An intense activity in GABAergic interneurons, including Pv interneurons, before seizures has been described in different experimental models of epilepsy, raising the hypothesis that an increased GABAergic inhibitory signal may, under certain conditions, initiate seizures. It is therefore unclear whether the activity of Pv interneurons enhances or opposes epileptiform activities. Here we use a mouse cortical slice model of focal epilepsy in which the epileptogenic focus can be identified and the role of Pv interneurons in the generation and propagation of seizure-like ictal events is accurately analyzed by a combination of optogenetic, electrophysiological, and imaging techniques. We found that a selective activation of Pv interneurons at the focus failed to block ictal generation and induced postinhibitory rebound spiking in pyramidal neurons, enhancing neuronal synchrony and promoting ictal generation. In contrast, a selective activation of Pv interneurons distant from the focus blocked ictal propagation and shortened ictal duration at the focus. We revealed that the reduced ictal duration was a direct consequence of the ictal propagation block, probably by preventing newly generated afterdischarges to travel backwards to the original focus of ictal initiation. Similar results were obtained upon individual Pv interneuron activation by intracellular depolarizing current pulses. The functional dichotomy of Pv interneurons here described opens new perspectives to our understanding of how local inhibitory circuits govern generation and spread of focal epileptiform activities.

Sampling bias corrections for accurate neural measures of redundant, unique, and synergistic information.

Shannon Information theory has long been a tool of choice to measure empirically how populations of neurons in the brain encode information about cognitive variables. Recently, Partial Information Decomposition (PID) has emerged as principled way to break down this information into components identifying not only the unique information carried by each neuron, but also whether relationships between neurons generate synergistic or redundant information. While it has been long recognized that Shannon information measures on neural activity suffer from a (mostly upward) limited sampling estimation bias, this issue has largely been ignored in the burgeoning field of PID analysis of neural activity. We used simulations to investigate the limited sampling bias of PID computed from discrete probabilities (suited to describe neural spiking activity). We found that PID suffers from a large bias that is uneven across components, with synergy by far the most biased. Using approximate analytical expansions, we found that the bias of synergy increases quadratically with the number of discrete responses of each neuron, whereas the bias of unique and redundant information increase only linearly or sub-linearly. Based on the understanding of the PID bias properties, we developed simple yet effective procedures that correct for the bias effectively, and that improve greatly the PID estimation with respect to current state-of-the-art procedures. We apply these PID bias correction procedures to datasets of 53117 pairs neurons in auditory cortex, posterior parietal cortex and hippocampus of mice performing cognitive tasks, deriving precise estimates and bounds of how synergy and redundancy vary across these brain regions.

Cortico-cortical transfer of socially derived information gates emotion recognition.

Emotion recognition and the resulting responses are important for survival and social functioning. However, how socially derived information is processed for reliable emotion recognition is incompletely understood. Here, we reveal an evolutionarily conserved long-range inhibitory/excitatory brain network mediating these socio-cognitive processes. Anatomical tracing in mice revealed the existence of a subpopulation of somatostatin (SOM) GABAergic neurons projecting from the medial prefrontal cortex (mPFC) to the retrosplenial cortex (RSC). Through optogenetic manipulations and Ca2+ imaging fiber photometry in mice and functional imaging in humans, we demonstrate the specific participation of these long-range SOM projections from the mPFC to the RSC, and an excitatory feedback loop from the RSC to the mPFC, in emotion recognition. Notably, we show that mPFC-to-RSC SOM projections are dysfunctional in mouse models relevant to psychiatric vulnerability and can be targeted to rescue emotion recognition deficits in these mice. Our findings demonstrate a cortico-cortical circuit underlying emotion recognition.

Early IGF-1 receptor inhibition in mice mimics preterm human brain disorders and reveals a therapeutic target.

Besides recent advances in neonatal care, preterm newborns still develop sex-biased behavioral alterations. Preterms fail to receive placental insulin-like growth factor-1 (IGF-1), a major fetal growth hormone in utero, and low IGF-1 serum levels correlate with preterm poor neurodevelopmental outcomes. Here, we mimicked IGF-1 deficiency of preterm newborns in mice by perinatal administration of an IGF-1 receptor antagonist. This resulted in sex-biased brain microstructural, functional, and behavioral alterations, resembling those of ex-preterm children, which we characterized performing parallel mouse/human behavioral tests. Pharmacological enhancement of GABAergic tonic inhibition by the U.S. Food and Drug Administration-approved drug ganaxolone rescued functional/behavioral alterations in mice. Establishing an unprecedented mouse model of prematurity, our work dissects the mechanisms at the core of abnormal behaviors and identifies a readily translatable therapeutic strategy for preterm brain disorders.

A chemogenetic approach for dopamine imaging with tunable sensitivity.

Genetically-encoded dopamine (DA) sensors enable high-resolution imaging of DA release, but their ability to detect a wide range of extracellular DA levels, especially tonic versus phasic DA release, is limited by their intrinsic affinity. Here we show that a human-selective dopamine receptor positive allosteric modulator (PAM) can be used to boost sensor affinity on-demand. The PAM enhances DA detection sensitivity across experimental preparations (in vitro, ex vivo and in vivo) via one-photon or two-photon imaging. In vivo photometry-based detection of optogenetically-evoked DA release revealed that DETQ administration produces a stable 31 minutes window of potentiation without effects on animal behavior. The use of the PAM revealed region-specific and metabolic state-dependent differences in tonic DA levels and enhanced single-trial detection of behavior-evoked phasic DA release in cortex and striatum. Our chemogenetic strategy can potently and flexibly tune DA imaging sensitivity and reveal multi-modal (tonic/phasic) DA signaling across preparations and imaging approaches.

ASTRA: a deep learning algorithm for fast semantic segmentation of large-scale astrocytic networks.

Changes in the intracellular calcium concentration are a fundamental fingerprint of astrocytes, the main type of glial cell. Astrocyte calcium signals can be measured with two-photon microscopy, occur in anatomically restricted subcellular regions, and are coordinated across astrocytic networks. However, current analytical tools to identify the astrocytic subcellular regions where calcium signals occur are time-consuming and extensively rely on user-defined parameters. These limitations limit reproducibility and prevent scalability to large datasets and fields-of-view. Here, we present Astrocytic calcium Spatio-Temporal Rapid Analysis (ASTRA), a novel software combining deep learning with image feature engineering for fast and fully automated semantic segmentation of two-photon calcium imaging recordings of astrocytes. We applied ASTRA to several two-photon microscopy datasets and found that ASTRA performed rapid detection and segmentation of astrocytic cell somata and processes with performance close to that of human experts, outperformed state-of-the-art algorithms for the analysis of astrocytic and neuronal calcium data, and generalized across indicators and acquisition parameters. We also applied ASTRA to the first report of two-photon mesoscopic imaging of hundreds of astrocytes in awake mice, documenting large-scale redundant and synergistic interactions in extended astrocytic networks. ASTRA is a powerful tool enabling closed-loop and large-scale reproducible investigation of astrocytic morphology and function.

Engineering memory with an extrinsically disordered kinase.

Synaptic plasticity plays a crucial role in memory formation by regulating the communication between neurons. Although actin polymerization has been linked to synaptic plasticity and dendritic spine stability, the causal link between actin polymerization and memory encoding has not been identified yet. It is not clear whether actin polymerization and structural changes in dendritic spines are a driver or a consequence of learning and memory. Using an extrinsically disordered form of the protein kinase LIMK1, which rapidly and precisely acts on ADF/cofilin, a direct modifier of actin, we induced long-term enlargement of dendritic spines and enhancement of synaptic transmission in the hippocampus on command. The activation of extrinsically disordered LIMK1 in vivo improved memory encoding and slowed cognitive decline in aged mice exhibiting reduced cofilin phosphorylation. The engineered memory by an extrinsically disordered LIMK1 supports a direct causal link between actin-mediated synaptic transmission and memory.

Two-photon calcium imaging in the intact brain.

The calcium ion is a fundamental second messenger that plays crucial roles in the pathophysiology of brain cells. In this chapter, we will focus on the measurement of calcium fluctuations as a reporter of cellular excitability of both neurons and glial cells in the intact central nervous system. We will first describe the methodological aspects of in vivo two-photon fluorescence calcium imaging and then review recent data highlighting the ways in which this technique is revolutionizing our understanding of brain circuits at the cellular level. Finally, we will discuss recent technical advancements that promise to open new horizons in the optical investigation of brain function in awake, behaving animals.

Endogenous nonneuronal modulators of synaptic transmission control cortical slow oscillations in vivo.

Gliotransmission, the release of molecules from astrocytes, regulates neuronal excitability and synaptic transmission in situ. Whether this process affects neuronal network activity in vivo is not known. Using a combination of astrocyte-specific molecular genetics, with in vivo electrophysiology and pharmacology, we determined that gliotransmission modulates cortical slow oscillations, a rhythm characterizing nonrapid eye movement sleep. Inhibition of gliotransmission by the expression of a dominant negative SNARE domain in astrocytes affected cortical slow oscillations, reducing the duration of neuronal depolarizations and causing prolonged hyperpolarizations. These network effects result from the astrocytic modulation of intracortical synaptic transmission at two sites: a hypofunction of postsynaptic NMDA receptors, and by reducing extracellular adenosine, a loss of tonic A1 receptor-mediated inhibition. These results demonstrate that rhythmic brain activity is generated by the coordinated action of the neuronal and glial networks.

Network States Classification based on Local Field Potential Recordings in the Awake Mouse Neocortex.

Recent studies using intracellular recordings in awake behaving mice revealed that cortical network states, defined based on membrane potential features, modulate sensory responses and perceptual outcomes. Single-cell intracellular recordings are difficult and have low yield compared to extracellular recordings of population signals, such as local field potentials (LFPs). However, it is currently unclear how to identify these behaviorally-relevant network states from the LFP. We used simultaneous LFP and intracellular recordings in the somatosensory cortex of awake mice to design a network state classification from the LFP, the Network State Index (NSI). We used the NSI to analyze the relationship between single-cell (intracellular) and population (LFP) signals over different network states of wakefulness. We found that graded levels of population signal faithfully predicted the levels of single-cell depolarization in nonrhythmic regimes whereas, in δ ([2-4 Hz]) oscillatory regimes, the graded levels of rhythmicity in the LFP mapped into a stereotypical oscillatory pattern of membrane potential. Finally, we showed that the variability of network states, beyond the occurrence of slow oscillatory activity, critically shaped the average correlations between single-cell and population signals. Application of the LFP-based NSI to mouse visual cortex data showed that this index increased with pupil size and during locomotion and had a U-shaped dependence on population firing rates. NSI-based characterization provides a ready-to-use tool to understand from LFP recordings how the modulation of local network dynamics shapes the flexibility of sensory processing during behavior.

SmaRT2P: a software for generating and processing smart line recording trajectories for population two-photon calcium imaging.

Two-photon fluorescence calcium imaging allows recording the activity of large neural populations with subcellular spatial resolution, but it is typically characterized by low signal-to-noise ratio (SNR) and poor accuracy in detecting single or few action potentials when large number of neurons are imaged. We recently showed that implementing a smart line scanning approach using trajectories that optimally sample the regions of interest increases both the SNR fluorescence signals and the accuracy of single spike detection in population imaging in vivo. However, smart line scanning requires highly specialised software to design recording trajectories, interface with acquisition hardware, and efficiently process acquired data. Furthermore, smart line scanning needs optimized strategies to cope with movement artefacts and neuropil contamination. Here, we develop and validate SmaRT2P, an open-source, user-friendly and easy-to-interface Matlab-based software environment to perform optimized smart line scanning in two-photon calcium imaging experiments. SmaRT2P is designed to interface with popular acquisition software (e.g., ScanImage) and implements novel strategies to detect motion artefacts, estimate neuropil contamination, and minimize their impact on functional signals extracted from neuronal population imaging. SmaRT2P is structured in a modular way to allow flexibility in the processing pipeline, requiring minimal user intervention in parameter setting. The use of SmaRT2P for smart line scanning has the potential to facilitate the functional investigation of large neuronal populations with increased SNR and accuracy in detecting the discharge of single and few action potentials.

Paradoxical somatodendritic decoupling supports cortical plasticity during REM sleep.

Rapid eye movement (REM) sleep is associated with the consolidation of emotional memories. Yet, the underlying neocortical circuits and synaptic mechanisms remain unclear. We found that REM sleep is associated with a somatodendritic decoupling in pyramidal neurons of the prefrontal cortex. This decoupling reflects a shift of inhibitory balance between parvalbumin neuron-mediated somatic inhibition and vasoactive intestinal peptide-mediated dendritic disinhibition, mostly driven by neurons from the central medial thalamus. REM-specific optogenetic suppression of dendritic activity led to a loss of danger-versus-safety discrimination during associative learning and a lack of synaptic plasticity, whereas optogenetic release of somatic inhibition resulted in enhanced discrimination and synaptic potentiation. Somatodendritic decoupling during REM sleep promotes opposite synaptic plasticity mechanisms that optimize emotional responses to future behavioral stressors.

A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging.

In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-photon calcium imaging data is computationally intensive and time-consuming, making online frame-by-frame analysis challenging. This is especially true for large field-of-view (FOV) imaging. Here, we present CITE-On (Cell Identification and Trace Extraction Online), a convolutional neural network-based algorithm for fast automatic cell identification, segmentation, identity tracking, and trace extraction in two-photon calcium imaging data. CITE-On processes thousands of cells online, including during mesoscopic two-photon imaging, and extracts functional measurements from most neurons in the FOV. Applied to publicly available datasets, the offline version of CITE-On achieves performance similar to that of state-of-the-art methods for offline analysis. Moreover, CITE-On generalizes across calcium indicators, brain regions, and acquisition parameters in anesthetized and awake head-fixed mice. CITE-On represents a powerful tool to speed up image analysis and facilitate closed-loop approaches, for example in combined all-optical imaging and manipulation experiments.