All-Optical Electrophysiology Reveals the Role of Lateral Inhibition in Sensory Processing in Cortical Layer 1

Three dimensional (3D) and four dimensional (4D) live imaging to study mechanisms of progressive neurodegeneration

Neurodegenerative diseases are complex and progressive, posing challenges to their study and understanding. Recent advances in microscopy imaging technologies have enabled the exploration of neurons in three spatial dimensions (3D) over time (4D). When applied to 3D cultures, tissues or animals, these technologies can provide valuable insights into the dynamic and spatial nature of neurodegenerative diseases. This review focuses on the use of imaging techniques and neurodegenerative disease models to study neurodegeneration in 4D. Imaging techniques such as confocal microscopy, two-photon microscopy, miniscope imaging, light sheet microscopy, and robotic microscopy offer powerful tools to visualize and analyze neuronal changes over time in 3D tissue. Application of these technologies to in vitro models of neurodegeneration such as mouse organotypic culture systems and human organoid models provide versatile platforms to study neurodegeneration in a physiologically relevant context. Additionally, use of 4D imaging in vivo, including in mouse and zebrafish models of neurodegenerative diseases, allows for the investigation of early dysfunction and behavioral changes associated with neurodegeneration. We propose that these studies have the power to overcome the limitations of two-dimensional (2D) monolayer neuronal cultures, and pave the way for improved understanding of the dynamics of neurodegenerative diseases and the development of effective therapeutic strategies.

Functional diversities within neurons and astrocytes in the adult rat auditory cortex revealed by single-nucleus RNA sequencing

The mammalian cerebral cortex is composed of a rich diversity of cell types. Cortical cells are organized into networks that rely on their functional diversity to ultimately carry out a variety of sophisticated cognitive functions. To investigate the breadth of transcriptional diverse cell types in the sensory cortex, we have used single-nucleus RNA sequencing (snRNA-seq) in the auditory cortex of the adult rat. A variety of unique excitatory and inhibitory neuron types were identified. In addition, we report for the first time a diversity of astrocytes in the auditory cortex that may represent functionally unique subtypes. Together, these results pave the way for building models of how neurons in the sensory cortex work in concert with astrocytes at synapses to fulfill high-cognitive functions like learning and memory.

Characterization of two near-infrared genetically encoded voltage indicators

Significance

Efforts starting more than 20 years ago led to increasingly well performing genetically encoded voltage indicators (GEVIs) for optical imaging at wavelengths < 600    nm . Although optical imaging in the > 600    nm wavelength range has many advantages over shorter wavelength approaches for mesoscopic in vivo monitoring of neuronal activity in the mammalian brain, the availability and evaluation of well performing near-infrared GEVIs are still limited.

Aim

Here, we characterized two recent near-infrared GEVIs, Archon1 and nirButterfly, to support interested tool users in selecting a suitable near-infrared GEVI for their specific research question requirements.

Approach

We characterized side-by-side the brightness, sensitivity, and kinetics of both near-infrared GEVIs in a setting focused on population imaging.

Results

We found that nirButterfly shows seven-fold higher brightness than Archon1 under the same conditions and faster kinetics than Archon1 for population imaging without cellular resolution. But Archon1 showed larger signals than nirButterfly.

Conclusions

Neither GEVI characterized here surpasses in all three key parameters (brightness, kinetics, and sensitivity), so there is no unequivocal preference for one of the two. Our side-by-side characterization presented here provides new information for future in vitro and ex vivo experimental designs.

Electro-metabolic signaling

Precise matching of energy substrate delivery to local metabolic needs is essential for the health and function of all tissues. Here, we outline a mechanistic framework for understanding this critical process, which we refer to as electro-metabolic signaling (EMS). All tissues exhibit changes in metabolism over varying spatiotemporal scales and have widely varying energetic needs and reserves. We propose that across tissues, common signatures of elevated metabolism or increases in energy substrate usage that exceed key local thresholds rapidly engage mechanisms that generate hyperpolarizing electrical signals in capillaries that then relax contractile elements throughout the vasculature to quickly adjust blood flow to meet changing needs. The attendant increase in energy substrate delivery serves to meet local metabolic requirements and thus avoids a mismatch in supply and demand and prevents metabolic stress. We discuss in detail key examples of EMS that our laboratories have discovered in the brain and the heart, and we outline potential further EMS mechanisms operating in tissues such as skeletal muscle, pancreas, and kidney. We suggest that the energy imbalance evoked by EMS uncoupling may be central to cellular dysfunction from which the hallmarks of aging and metabolic diseases emerge and may lead to generalized organ failure states-such as diverse flavors of heart failure and dementia. Understanding and manipulating EMS may be key to preventing or reversing these dysfunctions.

Layer 1 neocortex: Gating and integrating multidimensional signals

Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.

Nanotechnology and Cancer Bioelectricity: Bridging the Gap Between Biology and Translational Medicine

Bioelectricity is the electrical activity that occurs within living cells and tissues. This activity is critical for regulating homeostatic cellular function and communication, and disruptions of the same can lead to a variety of conditions, including cancer. Cancer cells are known to exhibit abnormal electrical properties compared to their healthy counterparts, and this has driven researchers to investigate the potential of harnessing bioelectricity as a tool in cancer diagnosis, prognosis, and treatment. In parallel, bioelectricity represents one of the means to gain fundamental insights on how electrical signals and charges play a role in cancer insurgence, growth, and progression. This review provides a comprehensive analysis of the literature in this field, addressing the fundamentals of bioelectricity in single cancer cells, cancer cell cohorts, and cancerous tissues. The emerging role of bioelectricity in cancer proliferation and metastasis is introduced. Based on the acknowledgement that this biological information is still hard to access due to the existing gap between biological findings and translational medicine, the latest advancements in the field of nanotechnologies for cellular electrophysiology are examined, as well as the most recent developments in micro- and nano-devices for cancer diagnostics and therapy targeting bioelectricity.

Physiological features of parvalbumin-expressing GABAergic interneurons contributing to high-frequency oscillations in the cerebral cortex

Parvalbumin-expressing (PV+) inhibitory interneurons drive gamma oscillations (30-80 Hz), which underlie higher cognitive functions. In this review, we discuss two groups/aspects of fundamental properties of PV+ interneurons. In the first group (dubbed Before Axon), we list properties representing optimal synaptic integration in PV+ interneurons designed to support fast oscillations. For example: [i] Information can neither enter nor leave the neocortex without the engagement of fast PV+ -mediated inhibition; [ii] Voltage responses in PV+ interneuron dendrites integrate linearly to reduce impact of the fluctuations in the afferent drive; and [iii] Reversed somatodendritic Rm gradient accelerates the time courses of synaptic potentials arriving at the soma. In the second group (dubbed After Axon), we list morphological and biophysical properties responsible for (a) short synaptic delays, and (b) efficient postsynaptic outcomes. For example: [i] Fast-spiking ability that allows PV+ interneurons to outpace other cortical neurons (pyramidal neurons). [ii] Myelinated axon (which is only found in the PV+ subclass of interneurons) to secure fast-spiking at the initial axon segment; and [iii] Inhibitory autapses - autoinhibition, which assures brief biphasic voltage transients and supports postinhibitory rebounds. Recent advent of scientific tools, such as viral strategies to target PV cells and the ability to monitor PV cells via in vivo imaging during behavior, will aid in defining the role of PV cells in the CNS. Given the link between PV+ interneurons and cognition, in the future, it would be useful to carry out physiological recordings in the PV+ cell type selectively and characterize if and how psychiatric and neurological diseases affect initiation and propagation of electrical signals in this cortical sub-circuit. Voltage imaging may allow fast recordings of electrical signals from many PV+ interneurons simultaneously.

Lateral inhibition in V1 controls neural & perceptual contrast sensitivity

Lateral inhibition is a central principle for sensory system function. It is thought to operate by the activation of inhibitory neurons that restrict the spatial spread of sensory excitation. Much work on the role of inhibition in sensory systems has focused on visual cortex; however, the neurons, computations, and mechanisms underlying cortical lateral inhibition remain debated, and its importance for visual perception remains unknown. Here, we tested how lateral inhibition from PV or SST neurons in mouse primary visual cortex (V1) modulates neural and perceptual sensitivity to stimulus contrast. Lateral inhibition from PV neurons reduced neural and perceptual sensitivity to visual contrast in a uniform subtractive manner, whereas lateral inhibition from SST neurons more effectively changed the slope (or gain) of neural and perceptual contrast sensitivity. A neural circuit model identified spatially extensive lateral projections from SST neurons as the key factor, and we confirmed this with direct subthreshold measurements of a larger spatial footprint for SST versus PV lateral inhibition. Together, these results define cell-type specific computational roles for lateral inhibition in V1, and establish their unique consequences on sensitivity to contrast, a fundamental aspect of the visual world.

The storage capacity of a directed graph and nodewise autonomous, ubiquitous learning

The brain, an exceedingly intricate information processing system, poses a constant challenge to memory research, particularly in comprehending how it encodes, stores, and retrieves information. Cognitive psychology studies memory mechanism from behavioral experiment level and fMRI level, and neurobiology studies memory mechanism from anatomy and electrophysiology level. Current research findings are insufficient to provide a comprehensive, detailed explanation of memory processes within the brain. Numerous unknown details must be addressed to establish a complete information processing mechanism connecting micro molecular cellular levels with macro cognitive behavioral levels. Key issues include characterizing and distributing content within biological neural networks, coexisting information with varying content, and sharing limited resources and storage capacity. Compared with the hard disk of computer mass storage, it is very clear from the polarity of magnetic particles in the bottom layer, the division of tracks and sectors in the middle layer, to the directory tree and file management system in the high layer, but the understanding of memory is not sufficient. Biological neural networks are abstracted as directed graphs, and the encoding, storage, and retrieval of information within directed graphs at the cellular level are explored. A memory computational model based on active directed graphs and node-adaptive learning is proposed. First, based on neuronal local perspectives, autonomous initiative, limited resource competition, and other neurobiological characteristics, a resource-based adaptive learning algorithm for directed graph nodes is designed. To minimize resource consumption of memory content in directed graphs, two resource-occupancy optimization strategies-lateral inhibition and path pruning-are proposed. Second, this paper introduces a novel memory mechanism grounded in graph theory, which considers connected subgraphs as the physical manifestation of memory content in directed graphs. The encoding, storage, consolidation, and retrieval of the brain's memory system correspond to specific operations such as forming subgraphs, accommodating multiple subgraphs, strengthening connections and connectivity of subgraphs, and activating subgraphs. Lastly, a series of experiments were designed to simulate cognitive processes and evaluate the performance of the directed graph model. Experimental results reveal that the proposed adaptive connectivity learning algorithm for directed graphs in this paper possesses the following four features: (1) Demonstrating distributed, self-organizing, and self-adaptive properties, the algorithm achieves global-level functions through local node interactions; (2) Enabling incremental storage and supporting continuous learning capabilities; (3) Displaying stable memory performance, it surpasses the Hopfield network in memory accuracy, capacity, and diversity, as demonstrated in experimental comparisons. Moreover, it maintains high memory performance with large-scale datasets; (4) Exhibiting a degree of generalization ability, the algorithm's macroscopic performance remains unaffected by the topological structure of the directed graph. Large-scale, decentralized, and node-autonomous directed graphs are suitable simulation methods. Examining storage problems within directed graphs can reveal the essence of phenomena and uncover fundamental storage rules hidden within complex neuronal mechanisms, such as synaptic plasticity, ion channels, neurotransmitters, and electrochemical activities.

A bioelectrical phase transition patterns the first vertebrate heartbeats

A regular heartbeat is essential to vertebrate life. In the mature heart, this function is driven by an anatomically localized pacemaker. By contrast, pacemaking capability is broadly distributed in the early embryonic heart1-3, raising the question of how tissue-scale activity is first established and then maintained during embryonic development. The initial transition of the heart from silent to beating has never been characterized at the timescale of individual electrical events, and the structure in space and time of the early heartbeats remains poorly understood. Using all-optical electrophysiology, we captured the very first heartbeat of a zebrafish and analysed the development of cardiac excitability and conduction around this singular event. The first few beats appeared suddenly, had irregular interbeat intervals, propagated coherently across the primordial heart and emanated from loci that varied between animals and over time. The bioelectrical dynamics were well described by a noisy saddle-node on invariant circle bifurcation with action potential upstroke driven by CaV1.2. Our work shows how gradual and largely asynchronous development of single-cell bioelectrical properties produces a stereotyped and robust tissue-scale transition from quiescence to coordinated beating.

Aberration-free holographic microscope for simultaneous imaging and stimulation of neuronal populations

A technical challenge in neuroscience is to record and specifically manipulate the activity of neurons in living animals. This can be achieved in some preparations with two-photon calcium imaging and photostimulation. These methods can be extended to three dimensions by holographic light sculpting with spatial light modulators (SLMs). At the same time, performing simultaneous holographic imaging and photostimulation is still cumbersome, requiring two light paths with separate SLMs. Here we present an integrated optical design using a single SLM for simultaneous imaging and photostimulation. Furthermore, we applied axially dependent adaptive optics to make the system aberration-free, and developed software for calibrations and closed-loop neuroscience experiments. Finally, we demonstrate the performance of the system with simultaneous calcium imaging and optogenetics in mouse primary auditory cortex in vivo. Our integrated holographic system could facilitate the systematic investigation of neural circuit function in awake behaving animals.

Architectural organization of ∼1,500-neuron modular minicolumnar disinhibitory circuits in healthy and Alzheimer's cortices

Acquisition of neuronal circuit architectures, central to understanding brain function and dysfunction, remains prohibitively challenging. Here I report the development of a simultaneous and sequential octuple-sexdecuple whole-cell patch-clamp recording system that enables architectural reconstruction of complex cortical circuits. The method unveils the canonical layer 1 single bouquet cell (SBC)-led disinhibitory neuronal circuits across the mouse somatosensory, motor, prefrontal, and medial entorhinal cortices. The ∼1,500-neuron modular circuits feature the translaminar, unidirectional, minicolumnar, and independent disinhibition and optimize cortical complexity, subtlety, plasticity, variation, and redundancy. Moreover, architectural reconstruction uncovers age-dependent deficits at SBC-disinhibited synapses in the senescence-accelerated mouse prone 8, an animal model of Alzheimer's disease. The deficits exhibit the characteristic Alzheimer's-like cortical spread and correlation with cognitive impairments. These findings decrypt operations of the elementary processing units in healthy and Alzheimer's mouse cortices and validate the efficacy of octuple-sexdecuple patch-clamp recordings for architectural reconstruction of complex neuronal circuits.

Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation

Hippocampal CA1 neurons generate single spikes and stereotyped bursts of spikes. However, it is unclear how individual neurons dynamically switch between these output modes and whether these two spiking outputs relay distinct information. We performed extracellular recordings in spatially navigating rats and cellular voltage imaging and optogenetics in awake mice. We found that spike bursts are preferentially linked to cellular and network theta rhythms (3-12 Hz) and encode an animal's position via theta phase precession, particularly as animals are entering a place field. In contrast, single spikes exhibit additional coupling to gamma rhythms (30-100 Hz), particularly as animals leave a place field. Biophysical modeling suggests that intracellular properties alone are sufficient to explain the observed input frequency-dependent spike coding. Thus, hippocampal neurons regulate the generation of bursts and single spikes according to frequency-specific network and intracellular dynamics, suggesting that these spiking modes perform distinct computations to support spatial behavior.

Voltage Imaging with Engineered Proton-Pumping Rhodopsins: Insights from the Proton Transfer Pathway

Voltage imaging using genetically encoded voltage indicators (GEVIs) has taken the field of neuroscience by storm in the past decade. Its ability to create subcellular and network level readouts of electrical dynamics depends critically on the kinetics of the response to voltage of the indicator used. Engineered microbial rhodopsins form a GEVI subclass known for their high voltage sensitivity and fast response kinetics. Here we review the essential aspects of microbial rhodopsin photocycles that are critical to understanding the mechanisms of voltage sensitivity in these proteins and link them to insights from efforts to create faster, brighter and more sensitive microbial rhodopsin-based GEVIs.

Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy

Voltage imaging with cellular specificity has been made possible by the tremendous advances in genetically encoded voltage indicators (GEVIs). However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines signal-to-noise ratio (SNR) and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating, while also maximizing signal detection efficiency. The resulting benefits in SNR and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different GEVI classes.

Video-based pooled screening yields improved far-red genetically encoded voltage indicators

Video-based screening of pooled libraries is a powerful approach for directed evolution of biosensors because it enables selection along multiple dimensions simultaneously from large libraries. Here we develop a screening platform, Photopick, which achieves precise phenotype-activated photoselection over a large field of view (2.3 × 2.3 mm, containing >103 cells, per shot). We used the Photopick platform to evolve archaerhodopsin-derived genetically encoded voltage indicators (GEVIs) with improved signal-to-noise ratio (QuasAr6a) and kinetics (QuasAr6b). These GEVIs gave improved signals in cultured neurons and in live mouse brains. By combining targeted in vivo optogenetic stimulation with high-precision voltage imaging, we characterized inhibitory synaptic coupling between individual cortical NDNF (neuron-derived neurotrophic factor) interneurons, and excitatory electrical synapses between individual hippocampal parvalbumin neurons. The QuasAr6 GEVIs are powerful tools for all-optical electrophysiology and the Photopick approach could be adapted to evolve a broad range of biosensors.

Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies

The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research.

DIRECT, a low-cost system for high-speed, low-noise imaging of fluorescent bio-samples

A targeted imaging system has been developed for applications requiring recording from stationary samples at high spatiotemporal resolutions. It works by illuminating regions of interest in rapid sequence, and recording the signal from the whole field of view onto a single photodetector. It can be implemented at low cost on an existing microscope without compromising existing functionality. The system is characterized in terms of speed, spatial resolution, and tissue penetration depth, before being used to record individual action potentials from ASAP-3 expressing neurons in an ex vivo mouse brain slice preparation.

Multiplexed Volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and serial electron microscopy on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (GFP, GFAP, calbindin, parvalbumin, Kv1.2, VGluT1, PSD-95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with linear unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure and superimposition of the different fluorescence channels. We document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of ion channels. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable a wide range of connectomic studies.

Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator

The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

Expanding the family of genetically encoded voltage indicators with a candidate Heliorhodopsin exhibiting near-infrared fluorescence

Genetically encoded voltage indicators (GEVIs), particularly those based on microbial rhodopsins, are gaining traction in neuroscience as fluorescent sensors for imaging voltage dynamics with high-spatiotemporal precision. Here we establish a novel GEVI candidate based on the recently discovered subfamily of the microbial rhodopsin clade, termed heliorhodopsins. We discovered that upon excitation at 530-560nm, wild type heliorhodopsin exhibits near infra-red fluorescence which is sensitive to membrane voltage. We characterized the fluorescence brightness, photostability, voltage sensitivity and kinetics of wild type heliorhodopsin in HEK293T cells and further examined the impact of mutating key residues near the retinal chromophore. The S237A mutation significantly improved the fluorescence response of heliorhodopsin by 76% providing a highly promising starting point for further protein evolution.

All-optical closed-loop voltage clamp for precise control of muscles and neurons in live animals

Excitable cells can be stimulated or inhibited by optogenetics. Since optogenetic actuation regimes are often static, neurons and circuits can quickly adapt, allowing perturbation, but not true control. Hence, we established an optogenetic voltage-clamp (OVC). The voltage-indicator QuasAr2 provides information for fast, closed-loop optical feedback to the bidirectional optogenetic actuator BiPOLES. Voltage-dependent fluorescence is held within tight margins, thus clamping the cell to distinct potentials. We established the OVC in muscles and neurons of Caenorhabditis elegans, and transferred it to rat hippocampal neurons in slice culture. Fluorescence signals were calibrated to electrically measured potentials, and wavelengths to currents, enabling to determine optical I/V-relationships. The OVC reports on homeostatically altered cellular physiology in mutants and on Ca²⁺-channel properties, and can dynamically clamp spiking in C. elegans. Combining non-invasive imaging with control capabilities of electrophysiology, the OVC facilitates high-throughput, contact-less electrophysiology in individual cells and paves the way for true optogenetic control in behaving animals.

Potassium-selective channelrhodopsins

Since their discovery 21 years ago, channelrhodopsins have come of age and have become indispensable tools for optogenetic control of excitable cells such as neurons and myocytes. Potential therapeutic utility of channelrhodopsins has been proven by partial vision restoration in a human patient. Previously known channelrhodopsins are either proton channels, non-selective cation channels almost equally permeable to Na+ and K+ besides protons, or anion channels. Two years ago, we discovered a group of channelrhodopsins that exhibit over an order of magnitude higher selectivity for K+ than for Na+. These proteins, known as "kalium channelrhodopsins" or KCRs, lack the canonical tetrameric selectivity filter found in voltage- and ligand-gated K+ channels, and use a unique selectivity mechanism intrinsic to their individual protomers. Mutant analysis has revealed that the key residues responsible for K+ selectivity in KCRs are located at both ends of the putative cation conduction pathway, and their role has been confirmed by high-resolution KCR structures. Expression of KCRs in mouse neurons and human cardiomyocytes enabled optical inhibition of these cells' electrical activity. In this minireview we briefly discuss major results of KCR research obtained during the last two years and suggest some directions of future research.

Calcium imaging and analysis of the jugular-nodose ganglia enables identification of distinct vagal sensory neuron subsets

Objective.Sensory nerves of the peripheral nervous system (PNS) transmit afferent signals from the body to the brain. These peripheral nerves are composed of distinct subsets of fibers and associated cell bodies, which reside in peripheral ganglia distributed throughout the viscera and along the spinal cord. The vagus nerve (cranial nerve X) is a complex polymodal nerve that transmits a wide array of sensory information, including signals related to mechanical, chemical, and noxious stimuli. To understand how stimuli applied to the vagus nerve are encoded by vagal sensory neurons in the jugular-nodose ganglia, we developed a framework for micro-endoscopic calcium imaging and analysis.Approach.We developed novel methods forin vivoimaging of the intact jugular-nodose ganglion using a miniature microscope (Miniscope) in transgenic mice with the genetically-encoded calcium indicator GCaMP6f. We adapted the Python-based analysis package Calcium Imaging Analysis (CaImAn) to process the resulting one-photon fluorescence data into calcium transients for subsequent analysis. Random forest classification was then used to identify specific types of neuronal responders.Results.We demonstrate that recordings from the jugular-nodose ganglia can be accomplished through careful surgical dissection and ganglia stabilization. Using a customized acquisition and analysis pipeline, we show that subsets of vagal sensory neurons respond to different chemical stimuli applied to the vagus nerve. Successful classification of the responses with a random forest model indicates that certain calcium transient features, such as amplitude and duration, are important for encoding these stimuli by sensory neurons.Significance.This experimental approach presents a new framework for investigating how individual vagal sensory neurons encode various stimuli on the vagus nerve. Our surgical and analytical approach can be applied to other PNS ganglia in rodents and other small animal species to elucidate previously unexplored roles for peripheral neurons in a diverse set of physiological functions.

Detection of Membrane Potential-Dependent Rhodopsin Fluorescence Using Low-Intensity Light Emitting Diode for Long-Term Imaging

Microbial rhodopsin is a family of photoreceptive membrane proteins that commonly consist of a seven-transmembrane domain and a derivative of vitamin-A, retinal, as a chromophore. In 2011, archaeorhodopsin-3 (AR3) was shown to exhibit voltage-dependent fluorescence changes in mammalian cells. Since then, AR3 and its variants have been used as genetically encoded voltage indicators, in which mostly intense laser stimulation (1-1000 W/cm²) is used for the detection of dim fluorescence of rhodopsin, leading to high spatiotemporal resolution. However, intense laser stimulation potentially causes serious cell damage, particularly during long-term imaging over minutes. In this study, we present the successful detection of voltage-sensitive fluorescence of AR3 and its high fluorescence mutant Archon1 in a variety of mammalian cell lines using low-intensity light emitting diode stimulation (0.15 W/cm²) with long exposure time (500 ms). The detection system enables real-time imaging of drug-induced slow changes in voltage within the cells for minutes harmlessly and without fluorescence bleaching. Therefore, we demonstrate a method to quantitatively understand the dynamics of slow changes in membrane voltage on long time scales.

All-optical physiology resolves a synaptic basis for behavioral timescale plasticity

Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.

Adult-born neurons inhibit developmentally-born neurons during spatial learning

Ongoing neurogenesis in the dentate gyrus (DG) subregion of the hippocampus results in a heterogenous population of neurons. Immature adult-born neurons (ABNs) have physiological and anatomical properties that may give them a unique role in learning. For example, compared to older granule neurons, they have greater somatic excitability, which could facilitate their recruitment into memory traces. However, recruitment is also likely to depend on interactions with other DG neurons through processes such as lateral inhibition. Immature ABNs target inhibitory interneurons and, compared to older neurons, they receive less GABAergic inhibition. Thus, they may induce lateral inhibition of mature DG neurons while being less susceptible to inhibition themselves. To test this we used a chemogenetic approach to silence immature ABNs as rats learned a spatial water maze task, and measured activity (Fos expression) in ABNs and developmentally-born neurons (DBNs). A retrovirus expressing the inhibitory DREADD receptor, hM4Di, was injected into the dorsal DG of male rats at 6w to infect neurons born in adulthood. Animals were also injected with BrdU to label DBNs or ABNs. DBNs were significantly more active than immature 4-week-old ABNs. Silencing 4-week-old ABNs did not alter learning but it increased activity in DBNs. However, silencing ABNs did not affect activation in other ABNs within the DG. Silencing ABNs also did not alter Fos expression in parvalbumin- and somatostatin-expressing interneurons. Collectively, these results suggest that ABNs may directly inhibit DBN activity during hippocampal-dependent learning, which may be relevant for maintaining sparse hippocampal representations of experienced events.

Scanless two-photon voltage imaging

Parallel light-sculpting methods have been used to perform scanless two-photon photostimulation of multiple neurons simultaneously during all-optical neurophysiology experiments. We demonstrate that scanless two-photon excitation also enables high-resolution, high-contrast, voltage imaging by efficiently exciting fluorescence in a large fraction of the cellular soma. We present a thorough characterisation of scanless two-photon voltage imaging using existing parallel approaches and lasers with different repetition rates. We demonstrate voltage recordings of high frequency spike trains and sub-threshold depolarizations in intact brain tissue from neurons expressing the soma-targeted genetically encoded voltage indicator JEDI-2P-kv. Using a low repetition-rate laser, we perform recordings from up to ten neurons simultaneously. Finally, by co-expressing JEDI-2P-kv and the channelrhodopsin ChroME-ST in neurons of hippocampal organotypic slices, we perform single-beam, simultaneous, two-photon voltage imaging and photostimulation. This enables in-situ validation of the precise number and timing of light evoked action potentials and will pave the way for rapid and scalable identification of functional brain connections in intact neural circuits.

Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence

We present a computational protocol for the fast and automated screening of excited-state hybrid quantum mechanics/molecular mechanics (QM/MM) models of rhodopsins to be used as fluorescent probes based on the automatic rhodopsin modeling protocol (a-ARM). Such "a-ARM fluorescence screening protocol" is implemented through a general Python-based driver, PyARM, that is also proposed here. The implementation and performance of the protocol are benchmarked using different sets of rhodopsin variants whose absorption and, more relevantly, emission spectra have been experimentally measured. We show that, despite important limitations that make unsafe to use it as a black-box tool, the protocol reproduces the observed trends in fluorescence and it is capable of selecting novel potentially fluorescent rhodopsins. We also show that the protocol can be used in mechanistic investigations to discern fluorescence enhancement effects associated with a near degeneracy of the S₁/S₂ states or, alternatively, with a barrier generated via coupling of the S₀/S₁ wave functions.

Probing top-down information in neocortical layer 1

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally generated top-down information. Decades of work have elucidated how sensory neocortex processes physical stimulus features. By contrast, examining how top-down information is encoded and integrated with bottom-up signals has been challenging using traditional neuroscience methods. Recent technological advances in functional imaging of brain-wide afferents in behaving mice have enabled the direct measurement of top-down information. Here, we review the emerging literature on encoding of these internally generated signals by different projection systems enriched in neocortical layer 1 during defined brain functions, including memory, attention, and predictive coding. Moreover, we identify gaps in current knowledge and highlight future directions for this rapidly advancing field.

Deep brain stimulation creates informational lesion through membrane depolarization in mouse hippocampus

Deep brain stimulation (DBS) is a promising neuromodulation therapy, but the neurophysiological mechanisms of DBS remain unclear. In awake mice, we performed high-speed membrane voltage fluorescence imaging of individual hippocampal CA1 neurons during DBS delivered at 40 Hz or 140 Hz, free of electrical interference. DBS powerfully depolarized somatic membrane potentials without suppressing spike rate, especially at 140 Hz. Further, DBS paced membrane voltage and spike timing at the stimulation frequency and reduced timed spiking output in response to hippocampal network theta-rhythmic (3-12 Hz) activity patterns. To determine whether DBS directly impacts cellular processing of inputs, we optogenetically evoked theta-rhythmic membrane depolarization at the soma. We found that DBS-evoked membrane depolarization was correlated with DBS-mediated suppression of neuronal responses to optogenetic inputs. These results demonstrate that DBS produces powerful membrane depolarization that interferes with the ability of individual neurons to respond to inputs, creating an informational lesion.

In vitro neurons learn and exhibit sentience when embodied in a simulated game-world

Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game "Pong." Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.

Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types

Genetically encoded fluorescent voltage indicators are ideally suited to reveal the millisecond-scale interactions among and between targeted cell populations. However, current indicators lack the requisite sensitivity for in vivo multipopulation imaging. We describe next-generation green and red voltage sensors, Ace-mNeon2 and VARNAM2, and their reverse response-polarity variants pAce and pAceR. Our indicators enable 0.4- to 1-kilohertz voltage recordings from >50 spiking neurons per field of view in awake mice and ~30-minute continuous imaging in flies. Using dual-polarity multiplexed imaging, we uncovered brain state–dependent antagonism between neocortical somatostatin-expressing (SST + ) and vasoactive intestinal peptide–expressing (VIP + ) interneurons and contributions to hippocampal field potentials from cell ensembles with distinct axonal projections. By combining three mutually compatible indicators, we performed simultaneous triple-population imaging. These approaches will empower investigations of the dynamic interplay between neuronal subclasses at single-spike resolution.

A kinetic-optimized CoChR variant with enhanced high-frequency spiking fidelity

Channelrhodopsins are a promising toolset for noninvasive optical manipulation of genetically identifiable neuron populations. Existing channelrhodopsins have generally suffered from a trade-off between two desired properties: fast channel kinetics and large photocurrent. Such a trade-off hinders spatiotemporally precise optogenetic activation during both one-photon and two-photon photostimulation. Furthermore, the simultaneous use of spectrally separated genetically encoded indicators and channelrhodopsins has generally suffered from non-negligible crosstalk in photocurrent or fluorescence. These limitations have hindered crosstalk-free dual-channel experiments needed to establish relationships between multiple neural populations. Recent large-scale transcriptome sequencing revealed one potent optogenetic actuator, the channelrhodopsin from species Chloromonas oogama (CoChR), which possessed high cyan light-driven photocurrent but slow channel kinetics. We rationally designed and engineered a kinetic-optimized CoChR variant that was faster than native CoChR while maintaining large photocurrent amplitude. When expressed in cultured hippocampal pyramidal neurons, our CoChR variant improved high-frequency spiking fidelity under one-photon illumination. Our CoChR variant's blue-shifted excitation spectrum enabled simultaneous cyan photostimulation and red calcium imaging with negligible photocurrent crosstalk.

Dynamic Fluorescence Imaging in Experimental Epilepsy

The ability to develop effective new treatments for epilepsy may depend on improved understanding of seizure pathophysiology, about which many questions remain. Dynamic fluorescence imaging of activity at single-neuron resolution with fluorescent indicators in experimental model systems in vivo has revolutionized basic neuroscience and has the potential to do so for epilepsy research as well. Here, we review salient issues as they pertain to experimental imaging in basic epilepsy research, including commonly used imaging technologies, data processing and analysis, interpretation of results, and selected examples of how imaging-based approaches have revealed new insight into mechanisms of seizures and epilepsy.

Multiregion neuronal activity: the forest and the trees

The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.

Advances in approaches to study cell-type specific cortical circuits throughout development

Neurons in the neocortex and hippocampus are diverse and form synaptic connections that depend on their type. Recent work has improved our understanding of neuronal cell-types and how to target them for experiments. This is crucial for investigating cortical circuit architecture, as the current catalog of established cell-type specific circuit motifs is small relative to the diversity of neuronal subtypes. Some of these motifs are found throughout the cortex, suggesting they are canonical circuits necessary for basic computations. However, the extent to which circuit organization is stereotyped across the brain or varies by cortical region remains unclear. Cortical circuits are also plastic, and their organization evolves throughout each developmental stage. Thus, experimental access to neuronal subtypes with temporal control is essential for studying cortical structure and function. In this mini review, we highlight several recent advances to target specific neuronal subtypes and study their synaptic connectivity and physiology throughout development. We emphasize approaches that combine multiple techniques, provide examples of successful applications, and describe potential future applications of novel tools.

Cell-type-specific population dynamics of diverse reward computations

Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, and computational features), we identified encoding of reward-predictive cues and reward outcomes in distinct genetically defined neural populations, including TH+ cells and Tac1+ cells. Data from genetically targeted recordings were used to train an optimized nonlinear dynamical systems model and revealed activity dynamics consistent with a line attractor. High-density, cell-type-specific electrophysiological recordings and optogenetic perturbation provided supporting evidence for this model. Reverse-engineering predicted how Tac1+ cells might integrate reward history, which was complemented by in vivo experimentation. This integrated approach describes a process by which data-driven computational models of population activity can generate and frame actionable hypotheses for cell-type-specific investigation in biological systems.

All-optical inter-layers functional connectivity investigation in the mouse retina

We developed a multi-unit microscope for all-optical inter-layers circuits interrogation. The system performs two-photon (2P) functional imaging and 2P multiplexed holographic optogenetics at axially distinct planes. We demonstrated the capability of the system to map, in the mouse retina, the functional connectivity between rod bipolar cells (RBCs) and ganglion cells (GCs) by activating single or defined groups of RBCs while recording the evoked response in the GC layer with cell-type specificity and single-cell resolution. We then used a logistic model to probe the functional connectivity between cell types by deriving the "cellular receptive field" describing how RBCs impact each GC type. With the capability to simultaneously image and control neuronal activity at axially distinct planes, the system enables a precise interrogation of multi-layered circuits. Understanding this information transfer is a promising avenue to dissect complex neural circuits and understand the neural basis of computations.

A genetic tool for the longitudinal study of a subset of post-inflammatory reactive astrocytes

Astrocytes are vital support cells that ensure proper brain function. In brain disease, astrocytes reprogram into a reactive state that alters many of their cellular roles. A long-standing question in the field is whether downregulation of reactive astrocyte (RA) markers during resolution of inflammation is because these astrocytes revert back to a non-reactive state or die and are replaced. This has proven difficult to answer mainly because existing genetic tools cannot distinguish between healthy versus RAs. Here we describe the generation of an inducible genetic tool that can be used to specifically target and label a subset of RAs. Longitudinal analysis of an acute inflammation model using this tool revealed that the previously observed downregulation of RA markers after inflammation is likely due to changes in gene expression and not because of cell death. Our findings suggest that cellular changes associated with astrogliosis after acute inflammation are largely reversible.

Biophysical characterization of light-gated ion channels using planar automated patch clamp

Channelrhodopsins (ChRs) are proteins that guide phototaxis in protists and exhibit light-gated channel conductance when their genes are heterologously expressed in mammalian cells. ChRs are widely used as molecular tools to control neurons and cardiomyocytes with light (optogenetics). Cation- and anion-selective ChRs (CCRs and ACRs, respectively) enable stimulation and inhibition of neuronal activity by depolarization and hyperpolarization of the membrane, respectively. More than 400 natural ChR variants have been identified so far, and high-throughput polynucleotide sequencing projects add many more each year. However, electrophysiological characterization of new ChRs lags behind because it is mostly done by time-consuming manual patch clamp (MPC). Here we report using a high-throughput automated patch clamp (APC) platform, SyncroPatch 384i from Nanion Technologies, for ChR research. We find that this instrument can be used for determination of the light intensity dependence and current-voltage relationships in ChRs and discuss its advantages and limitations.

Automatic Multi-functional Integration Program (AMFIP) towards all-optical mechano-electrophysiology interrogation

Automatic operations of multi-functional and time-lapse live-cell imaging are necessary for the biomedical science community to study active, multi-faceted, and long-term biological phenomena. To achieve automatic control, most existing solutions often require the purchase of extra software programs and hardware that rely on the manufacturers’ own specifications. However, these software programs are usually non-user-programmable and unaffordable for many laboratories. To address this unmet need, we have developed a novel open-source software program, titled Automatic Multi-functional Integration Program (AMFIP), as a new Java-based and hardware-independent system that provides proven advantages over existing alternatives to the scientific community. Without extra hardware, AMFIP enables the functional synchronization of the μManager software platform, the Nikon NIS-Elements platform, and other 3rd party software to achieve automatic operations of most commercially available microscopy systems, including but not limited to those from Nikon. AMFIP provides a user-friendly and programmable graphical user interface (GUI), opening the door to expanding the customizability for myriad hardware and software systems according to user-specific experimental requirements and environments. To validate the intended purposes of developing AMFIP, we applied it to elucidate the question whether single cells, prior to their full spreading, can sense and respond to a soft solid substrate, and if so, how does the interaction depend on the cell spreading time and the stiffness of the substrate. Using a CRISPR/Cas9-engineered human epithelial Beas2B (B2B) cell line that expresses mNeonGreen2-tagged mechanosensitive Yes-associated protein (YAP), we show that single B2B cells develop distinct substrate-stiffness-dependent YAP expressions within 10 hours at most on the substrate, suggesting that cells are able to sense, distinguish, and respond to mechanical cues prior to the establishment of full cell spreading. In summary, AMFIP provides a reliable, open-source, and cost-free solution that has the validated long-term utility to satisfy the need of automatic imaging operations in the scientific community.

All-optical interrogation of neural circuits in behaving mice

Recent advances combining two-photon calcium imaging and two-photon optogenetics with computer-generated holography now allow us to read and write the activity of large populations of neurons in vivo at cellular resolution and with high temporal resolution. Such 'all-optical' techniques enable experimenters to probe the effects of functionally defined neurons on neural circuit function and behavioral output with new levels of precision. This greatly increases flexibility, resolution, targeting specificity and throughput compared with alternative approaches based on electrophysiology and/or one-photon optogenetics and can interrogate larger and more densely labeled populations of neurons than current voltage imaging-based implementations. This protocol describes the experimental workflow for all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system (~3 h), the preparation of an indicator and opsin-expressing and task-performing animal (~3-6 weeks), the characterization of functional and photostimulation responses (~2 h per field of view) and the design and implementation of an all-optical experiment (achievable within the timescale of a normal behavioral experiment; ~3-5 h per field of view). We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy in three brain areas by using different experimental setups. This approach can in principle be adapted to any brain area to probe functional connectivity in neural circuits and investigate the relationship between neural circuit activity and behavior.

Advantages, Pitfalls, and Developments of All Optical Interrogation Strategies of Microcircuits in vivo

The holy grail for every neurophysiologist is to conclude a causal relationship between an elementary behaviour and the function of a specific brain area or circuit. Our effort to map elementary behaviours to specific brain loci and to further manipulate neural activity while observing the alterations in behaviour is in essence the goal for neuroscientists. Recent advancements in the area of experimental brain imaging in the form of longer wavelength near infrared (NIR) pulsed lasers with the development of highly efficient optogenetic actuators and reporters of neural activity, has endowed us with unprecedented resolution in spatiotemporal precision both in imaging neural activity as well as manipulating it with multiphoton microscopy. This readily available toolbox has introduced a so called all-optical physiology and interrogation of circuits and has opened new horizons when it comes to precisely, fast and non-invasively map and manipulate anatomically, molecularly or functionally identified mesoscopic brain circuits. The purpose of this review is to describe the advantages and possible pitfalls of all-optical approaches in system neuroscience, where by all-optical we mean use of multiphoton microscopy to image the functional response of neuron(s) in the network so to attain flexible choice of the cells to be also optogenetically photostimulated by holography, in absence of electrophysiology. Spatio-temporal constraints will be compared toward the classical reference of electrophysiology methods. When appropriate, in relation to current limitations of current optical approaches, we will make reference to latest works aimed to overcome these limitations, in order to highlight the most recent developments. We will also provide examples of types of experiments uniquely approachable all-optically. Finally, although mechanically non-invasive, all-optical electrophysiology exhibits potential off-target effects which can ambiguate and complicate the interpretation of the results. In summary, this review is an effort to exemplify how an all-optical experiment can be designed, conducted and interpreted from the point of view of the integrative neurophysiologist.

The Mesencephalic Locomotor Region: Beyond Locomotor Control

The mesencephalic locomotor region (MLR) was discovered several decades ago in the cat. It was functionally defined based on the ability of low threshold electrical stimuli within a region comprising the cuneiform and pedunculopontine nucleus to evoke locomotion. Since then, similar regions have been found in diverse vertebrate species, including the lamprey, skate, rodent, pig, monkey, and human. The MLR, while often viewed under the lens of locomotion, is involved in diverse processes involving the autonomic nervous system, respiratory system, and the state-dependent activation of motor systems. This review will discuss the pedunculopontine nucleus and cuneiform nucleus that comprises the MLR and examine their respective connectomes from both an anatomical and functional angle. From a functional perspective, the MLR primes the cardiovascular and respiratory systems before the locomotor activity occurs. Inputs from a variety of higher structures, and direct outputs to the monoaminergic nuclei, allow the MLR to be able to respond appropriately to state-dependent locomotion. These state-dependent effects are roughly divided into escape and exploratory behavior, and the MLR also can reinforce the selection of these locomotor behaviors through projections to adjacent structures such as the periaqueductal gray or to limbic and cortical regions. Findings from the rat, mouse, pig, and cat will be discussed to highlight similarities and differences among diverse species.

Dynamic interplay between thalamic activity and Cajal-Retzius cells regulates the wiring of cortical layer 1

Cortical wiring relies on guidepost cells and activity-dependent processes that are thought to act sequentially. Here, we show that the construction of layer 1 (L1), a main site of top-down integration, is regulated by crosstalk between transient Cajal-Retzius cells (CRc) and spontaneous activity of the thalamus, a main driver of bottom-up information. While activity was known to regulate CRc migration and elimination, we found that prenatal spontaneous thalamic activity and NMDA receptors selectively control CRc early density, without affecting their demise. CRc density, in turn, regulates the distribution of upper layer interneurons and excitatory synapses, thereby drastically impairing the apical dendrite activity of output pyramidal neurons. In contrast, postnatal sensory-evoked activity had a limited impact on L1 and selectively perturbed basal dendrites synaptogenesis. Collectively, our study highlights a remarkable interplay between thalamic activity and CRc in L1 functional wiring, with major implications for our understanding of cortical development.

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Prenatal thalamic waves of activity regulate CRc density in L1

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Prenatal and postnatal CRc manipulations alter specific interneuron populations

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Postnatal CRc shape L5 apical dendrite structural and functional properties

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Early sensory activity selectively regulates L5 basal dendrite spine formation

The Role of Inhibitory Interneurons in Circuit Assembly and Refinement Across Sensory Cortices

Sensory information is transduced into electrical signals in the periphery by specialized sensory organs, which relay this information to the thalamus and subsequently to cortical primary sensory areas. In the cortex, microcircuits constituted by interconnected pyramidal cells and inhibitory interneurons, distributed throughout the cortical column, form the basic processing units of sensory information underlying sensation. In the mouse, these circuits mature shortly after birth. In the first postnatal week cortical activity is characterized by highly synchronized spontaneous activity. While by the second postnatal week, spontaneous activity desynchronizes and sensory influx increases drastically upon eye opening, as well as with the onset of hearing and active whisking. This influx of sensory stimuli is fundamental for the maturation of functional properties and connectivity in neurons allocated to sensory cortices. In the subsequent developmental period, spanning the first five postnatal weeks, sensory circuits are malleable in response to sensory stimulation in the so-called critical periods. During these critical periods, which vary in timing and duration across sensory areas, perturbations in sensory experience can alter cortical connectivity, leading to long-lasting modifications in sensory processing. The recent advent of intersectional genetics, in vivo calcium imaging and single cell transcriptomics has aided the identification of circuit components in emergent networks. Multiple studies in recent years have sought a better understanding of how genetically-defined neuronal subtypes regulate circuit plasticity and maturation during development. In this review, we discuss the current literature focused on postnatal development and critical periods in the primary auditory (A1), visual (V1), and somatosensory (S1) cortices. We compare the developmental trajectory among the three sensory areas with a particular emphasis on interneuron function and the role of inhibitory circuits in cortical development and function.

Voltage imaging identifies spinal circuits that modulate locomotor adaptation in zebrafish

Motor systems must continuously adapt their output to maintain a desired trajectory. While the spinal circuits underlying rhythmic locomotion are well described, little is known about how the network modulates its output strength. A major challenge has been the difficulty of recording from spinal neurons during behavior. Here, we use voltage imaging to map the membrane potential of large populations of glutamatergic neurons throughout the spinal cord of the larval zebrafish during fictive swimming in a virtual environment. We characterized a previously undescribed subpopulation of tonic-spiking ventral V3 neurons whose spike rate correlated with swimming strength and bout length. Optogenetic activation of V3 neurons led to stronger swimming and longer bouts but did not affect tail beat frequency. Genetic ablation of V3 neurons led to reduced locomotor adaptation. The power of voltage imaging allowed us to identify V3 neurons as a critical driver of locomotor adaptation in zebrafish.

Fast and slow feedforward inhibitory circuits for cortical odor processing

Feedforward inhibitory circuits are key contributors to the complex interplay between excitation and inhibition in the brain. Little is known about the function of feedforward inhibition in the primary olfactory (piriform) cortex. Using in vivo two-photon-targeted patch clamping and calcium imaging in mice, we find that odors evoke strong excitation in two classes of interneurons – neurogliaform (NG) cells and horizontal (HZ) cells – that provide feedforward inhibition in layer 1 of the piriform cortex. NG cells fire much earlier than HZ cells following odor onset, a difference that can be attributed to the faster odor-driven excitatory synaptic drive that NG cells receive from the olfactory bulb. As a result, NG cells strongly but transiently inhibit odor-evoked excitation in layer 2 principal cells, whereas HZ cells provide more diffuse and prolonged feedforward inhibition. Our findings reveal unexpected complexity in the operation of inhibition in the piriform cortex.