Time-lapse electrical recordings of single neurons from the mouse neocortex

Linking brain activity across scales with simultaneous opto- and electrophysiology

The brain enables adaptive behavior via the dynamic coordination of diverse neuronal signals across spatial and temporal scales: from fast action potential patterns in microcircuits to slower patterns of distributed activity in brain-wide networks. Understanding principles of multiscale dynamics requires simultaneous monitoring of signals in multiple, distributed network nodes. Combining optical and electrical recordings of brain activity is promising for collecting data across multiple scales and can reveal aspects of coordinated dynamics invisible to standard, single-modality approaches. We review recent progress in combining opto- and electrophysiology, focusing on mouse studies that shed new light on the function of single neurons by embedding their activity in the context of brain-wide activity patterns. Optical and electrical readouts can be tailored to desired scales to tackle specific questions. For example, fast dynamics in single cells or local populations recorded with multi-electrode arrays can be related to simultaneously acquired optical signals that report activity in specified subpopulations of neurons, in non-neuronal cells, or in neuromodulatory pathways. Conversely, two-photon imaging can be used to densely monitor activity in local circuits while sampling electrical activity in distant brain areas at the same time. The refinement of combined approaches will continue to reveal previously inaccessible and under-appreciated aspects of coordinated brain activity.

Learning in a sensory cortical microstimulation task is associated with elevated representational stability

Sensory cortical representations can be highly dynamic, raising the question of how representational stability impacts learning. We train mice to discriminate the number of photostimulation pulses delivered to opsin-expressing pyramidal neurons in layer 2/3 of primary vibrissal somatosensory cortex. We simultaneously track evoked neural activity across learning using volumetric two-photon calcium imaging. In well-trained animals, trial-to-trial fluctuations in the amount of photostimulus-evoked activity predicted animal choice. Population activity levels declined rapidly across training, with the most active neurons showing the largest declines in responsiveness. Mice learned at varied rates, with some failing to learn the task in the time provided. The photoresponsive population showed greater instability both within and across behavioral sessions among animals that failed to learn. Animals that failed to learn also exhibited a faster deterioration in stimulus decoding. Thus, greater stability in the stimulus response is associated with learning in a sensory cortical microstimulation task.

Syngap1 regulates experience-dependent cortical ensemble plasticity by promoting in vivo excitatory synapse strengthening

A significant proportion of autism risk genes regulate synapse function, including plasticity, which is believed to contribute to behavioral abnormalities. However, it remains unclear how impaired synapse plasticity contributes to network-level processes linked to adaptive behaviors, such as experience-dependent ensemble plasticity. We found that Syngap1, a major autism risk gene, promoted measures of experience-dependent excitatory synapse strengthening in the mouse cortex, including spike-timing-dependent glutamatergic synaptic potentiation and presynaptic bouton formation. Synaptic depression and bouton elimination were normal in Syngap1 mice. Within cortical networks, Syngap1 promoted experience-dependent increases in somatic neural activity in weakly active neurons. In contrast, plastic changes to highly active neurons from the same ensemble that paradoxically weaken with experience were unaffected. Thus, experience-dependent excitatory synapse strengthening mediated by Syngap1 shapes neuron-specific plasticity within cortical ensembles. We propose that other genes regulate neuron-specific weakening within ensembles, and together, these processes function to redistribute activity within cortical networks during experience.

In vivo genome editing in single mammalian brain neurons through CRISPR-Cas9 and cytosine base editors

Gene manipulation is a useful approach for understanding functions of genes and is important for investigating basic mechanisms of brain function on the level of single neurons and circuits. Despite the development and the wide range of applications of CRISPR-Cas9 and base editors (BEs), their implementation for an analysis of individual neurons in vivo remained limited. In fact, conventional gene manipulations are generally achieved only on the population level. Here, we combined either CRISPR-Cas9 or BEs with the targeted single-cell electroporation technique as a proof-of-concept test for gene manipulation in single neurons in vivo. Our assay consisted of CRISPR-Cas9- or BEs-induced gene knockout in single Purkinje cells in the cerebellum. Our results demonstrate the feasibility of both gene editing and base editing in single cells in the intact brain, providing a tool through which molecular perturbations of individual neurons can be used for analysis of circuits and, ultimately, behaviors.

A Single-Neuron: Current Trends and Future Prospects

The brain is an intricate network with complex organizational principles facilitating a concerted communication between single-neurons, distinct neuron populations, and remote brain areas. The communication, technically referred to as connectivity, between single-neurons, is the center of many investigations aimed at elucidating pathophysiology, anatomical differences, and structural and functional features. In comparison with bulk analysis, single-neuron analysis can provide precise information about neurons or even sub-neuron level electrophysiology, anatomical differences, pathophysiology, structural and functional features, in addition to their communications with other neurons, and can promote essential information to understand the brain and its activity. This review highlights various single-neuron models and their behaviors, followed by different analysis methods. Again, to elucidate cellular dynamics in terms of electrophysiology at the single-neuron level, we emphasize in detail the role of single-neuron mapping and electrophysiological recording. We also elaborate on the recent development of single-neuron isolation, manipulation, and therapeutic progress using advanced micro/nanofluidic devices, as well as microinjection, electroporation, microelectrode array, optical transfection, optogenetic techniques. Further, the development in the field of artificial intelligence in relation to single-neurons is highlighted. The review concludes with between limitations and future prospects of single-neuron analyses.

Methods for single-cell recording and labeling in vivo

Targeting individual neurons in vivo is a key method to study the role of single cell types within local and brain-wide microcircuits. While novel technological developments now permit assessing activity from large number of cells simultaneously, there is currently no better solution than glass micropipettes to relate the physiology and morphology of single-cells. Sharp intracellular, juxtacellular, loose-patch and whole-cell approaches are some of the configurations used to record and label individual neurons. Here, we review procedures to establish successful electrophysiological recordings in vivo followed by appropriate labeling for post hoc morphological analysis. We provide operational recommendations for optimizing each configuration and a generic framework for functional, neurochemical and morphological identification of the different cell-types in a given region. Finally, we highlight emerging approaches that are challenging our current paradigms for single-cell recording and labeling in the living brain.

Method for labeling and reconstruction of single neurons using Sindbis virus vectors

Neuronal dendrites and axons are key substrates for the input and output of information, respectively, so establishing the precise and complete morphological description of dendritic and axonal processes of a single neuron is essential for understanding the neuron's functional role in the neuronal circuits. The whole structure of single neurons was originally revealed using Golgi staining, and later the intracellular labeling method was developed, although this is technically too difficult to stain entire neurons in vivo. Since the late 1980s, molecular biology techniques have been applied to neuroscience research, leading to the development of various virus vectors, such as the Sindbis and adeno-associated virus vectors, which have facilitated the reconstruction of neurons at a single cell level. In the present review, we focus on a method for labeling and reconstruction of single neurons using Sindbis virus vectors that express membrane-targeted fluorescent proteins. We describe in detail a protocol for single-neuron labeling using Sindbis virus vectors, and we provide an example of a recent project at our laboratory in which we successfully applied these methods to study thalamocortical projection neurons. Further, we discuss the strengths and limitations of Sindbis virus vectors for single neuron reconstruction, comparing them with adeno-associated virus vectors.

Quantifying How Staining Methods Bias Measurements of Neuron Morphologies

The process through which neurons are labeled is a key methodological choice in measuring neuron morphology. However, little is known about how this choice may bias measurements. To quantify this bias we compare the extracted morphology of neurons collected from the same rodent species, experimental condition, gender distribution, age distribution, brain region and putative cell type, but obtained with 19 distinct staining methods. We found strong biases on measured features of morphology. These were largest in features related to the coverage of the dendritic tree (e.g., the total dendritic tree length). Understanding measurement biases is crucial for interpreting morphological data.

Plasticity of population coding in primary sensory cortex

That experience shapes sensory tuning in primary sensory cortex is well understood. But effective neural population codes depend on more than just sensory tuning. Recent population imaging and recording studies have characterized population codes in sensory cortex, and tracked how they change with sensory manipulations and training on perceptual learning tasks. These studies confirm sensory tuning changes, but also reveal other features of plasticity, including sensory gain modulation, restructuring of firing correlations, and differential routing of information to output pathways. Unexpectedly strong day-to-day variation exists in single-neuron sensory tuning, which stabilizes during learning. These are novel dimensions of plasticity in sensory cortex, which refine population codes during learning, but whose mechanisms are unknown.

New Frontiers and Challenges for Single-Cell Electrochemical Analysis

Previous measurements of cell populations might obscure many important cellular differences, and new strategies for single-cell analyses are urgently needed to re-examine these fundamental biological principles for better diagnosis and treatment of diseases. Electrochemistry is a robust technique for the analysis of single living cells that has the advantages of minor interruption of cellular activity and provides the capability of high spatiotemporal resolution. The achievements of the past 30 years have revealed significant information about the exocytotic events of single cells to elucidate the mechanisms of cellular activity. Currently, the rapid developments of micro/nanofabrication and optoelectronic technologies drive the development of multifunctional electrodes and novel electrochemical approaches with higher resolution for single cells. In this Perspective, three new frontiers in this field, namely, electrochemical microscopy, intracellular analysis, and single-cell analysis in a biological system (i.e., neocortex and retina), are reviewed. The unique features and remaining challenges of these techniques are discussed.

Variance and invariance of neuronal long-term representations

The brain extracts behaviourally relevant sensory input to produce appropriate motor output. On the one hand, our constantly changing environment requires this transformation to be plastic. On the other hand, plasticity is thought to be balanced by mechanisms ensuring constancy of neuronal representations in order to achieve stable behavioural performance. Yet, prominent changes in synaptic strength and connectivity also occur during normal sensory experience, indicating a certain degree of constitutive plasticity. This raises the question of how stable neuronal representations are on the population level and also on the single neuron level. Here, we review recent data from longitudinal electrophysiological and optical recordings of single-cell activity that assess the long-term stability of neuronal stimulus selectivities under conditions of constant sensory experience, during learning, and after reversible modification of sensory input. The emerging picture is that neuronal representations are stabilized by behavioural relevance and that the degree of long-term tuning stability and perturbation resistance directly relates to the functional role of the respective neurons, cell types and circuits. Using a 'toy' model, we show that stable baseline representations and precise recovery from perturbations in visual cortex could arise from a 'backbone' of strong recurrent connectivity between similarly tuned cells together with a small number of 'anchor' neurons exempt from plastic changes.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'.

A stable brain from unstable components: Emerging concepts and implications for neural computation

Neuroscientists have often described the adult brain in similar terms to an electronic circuit board- dependent on fixed, precise connectivity. However, with the advent of technologies allowing chronic measurements of neural structure and function, the emerging picture is that neural networks undergo significant remodeling over multiple timescales, even in the absence of experimenter-induced learning or sensory perturbation. Here, we attempt to reconcile the parallel observations that critical brain functions are stably maintained, while synapse- and single-cell properties appear to be reformatted regularly throughout adult life. In this review, we discuss experimental evidence at multiple levels ranging from synapses to neuronal ensembles, suggesting that many parameters are maintained in a dynamic equilibrium. We highlight emerging hypotheses that could explain how stable brain functions may be generated from dynamic elements. Furthermore, we discuss the impact of dynamic circuit elements on neural computations, and how they could provide living neural circuits with computational abilities a fixed structure cannot offer. Taken together, recent evidence indicates that continuous dynamics are a fundamental property of neural circuits compatible with macroscopically stable behaviors. In addition, they may be a unique advantage imparting robustness and flexibility throughout life.

A robot for high yield electrophysiology and morphology of single neurons in vivo

Single-cell characterization and perturbation of neurons provides knowledge critical to addressing fundamental neuroscience questions including the structure–function relationship and neuronal cell-type classification. Here we report a robot for efficiently performing in vivo single-cell experiments in deep brain tissues optically difficult to access. This robot automates blind (non-visually guided) single-cell electroporation (SCE) and extracellular electrophysiology, and can be used to characterize neuronal morphological and physiological properties of, and/or manipulate genetic/chemical contents via delivering extraneous materials (for example, genes) into single neurons in vivo. Tested in the mouse brain, our robot successfully reveals the full morphology of single-infragranular neurons recorded in multiple neocortical regions, as well as deep brain structures such as hippocampal CA3, with high efficiency. Our robot thus can greatly facilitate the study of in vivo full morphology and electrophysiology of single neurons in the brain.

Single-cell characterization and perturbation of neurons is critical for revealing the structure-function relationship of brain cells. Here the authors develop a robot that performs single-cell electroporation and extracellular electrophysiology and can be used for performing in vivo single-cell experiments in deep brain tissues optically difficult to access.

3D Image-Guided Automatic Pipette Positioning for Single Cell Experiments in vivo

We report a method to facilitate single cell, image-guided experiments including in vivo electrophysiology and electroporation. Our method combines 3D image data acquisition, visualization and on-line image analysis with precise control of physical probes such as electrophysiology microelectrodes in brain tissue in vivo. Adaptive pipette positioning provides a platform for future advances in automated, single cell in vivo experiments.

Sparse, reliable, and long-term stable representation of periodic whisker deflections in the mouse barrel cortex

The rodent whisker system is a preferred model for studying plasticity in the somatosensory cortex (barrel cortex). Contrarily, only a small amount of research has been conducted to characterize the stability of neuronal population activity in the barrel cortex. We used the mouse whisker system to address the neuronal basis of stable perception in the somatosensory cortex. Cortical representation of periodic whisker deflections was studied in populations of neurons in supragranular layers over extended time periods (up to 3 months) with long-term two-photon Ca(2+) imaging in anesthetized mice. We found that in most of the neurons (87%), Ca(2+) responses increased sublinearly with increasing number of contralateral whisker deflections. The imaged population of neurons was activated in a stereotypic way over days and for different deflection rates (pulse frequencies). Thus, pulse frequencies are coded by response strength rather than by distinct neuronal sub-populations. A small population of highly responsive neurons (~3%) was sufficient to decode the whisker stimulus. This conserved functional map, led by a small set of highly responsive neurons, might form the foundation of stable sensory percepts.

Plasticity during motherhood: changes in excitatory and inhibitory layer 2/3 neurons in auditory cortex

Maternal behavior can be triggered by auditory and olfactory cues originating from the newborn. Here we report how the transition to motherhood affects excitatory and inhibitory neurons in layer 2/3 (L2/3) of the mouse primary auditory cortex. We used in vivo two-photon targeted cell-attached recording to compare the response properties of parvalbumin-expressing neurons (PVNs) and pyramidal glutamatergic neurons (PyrNs). The transition to motherhood shifts the average best frequency of PVNs to higher frequency by a full octave, with no significant effect on average best frequency of PyrNs. The presence of pup odors significantly reduced the spontaneous and evoked activity of PVN. This reduction of feedforward inhibition coincides with a complimentary increase in spontaneous and evoked activity of PyrNs. The selective shift of PVN frequency tuning should render pup odor-induced disinhibition more effective for high-frequency stimuli, such as ultrasonic vocalizations. Indeed, pup odors increased neuronal responses of PyrNs to pup ultrasonic vocalizations. We conclude that plasticity in the mothers is mediated, at least in part, via modulation of the feedforward inhibition circuitry in the auditory cortex.

Recording, labeling, and transfection of single neurons in deep brain structures

Genetic tools that permit functional or connectomic analysis of neuronal circuits are rapidly transforming neuroscience. The key to deployment of such tools is selective transfection of target neurons, but to date this has largely been achieved using transgenic animals or viral vectors that transduce subpopulations of cells chosen according to anatomical rather than functional criteria. Here, we combine single‐cell transfection with conventional electrophysiological recording techniques, resulting in three novel protocols that can be used for reliable delivery of conventional dyes or genetic material in vitro and in vivo. We report that techniques based on single cell electroporation yield reproducible transfection in vitro, and offer a simple, rapid and reliable alternative to established dye‐labeling techniques in vivo, but are incompatible with targeted transfection in deep brain structures. In contrast, we show that intracellular electrophoresis of plasmid DNA transfects brainstem neurons recorded up to 9 mm deep in the anesthetized rat. The protocols presented here require minimal, if any, modification to recording hardware, take seconds to deploy, and yield high recovery rates in vitro (dye labeling: 89%, plasmid transfection: 49%) and in vivo (dye labeling: 66%, plasmid transfection: 27%). They offer improved simplicity compared to the juxtacellular labeling technique and for the first time offer genetic manipulation of functionally characterized neurons in previously inaccessible brain regions.

The ability to label individual neurons after electrophysiological characterization of their functional properties is a foundational technique in neuroscience. A number of approaches that achieve this goal have been described, but all are technically challenging. Here, we describe a simple approach that is rapid, reliable, and compatible with delivery of conventional dyes or large plasmid DNA molecules.

Presynaptic and Postsynaptic Scaffolds

The development of methods to follow the dynamics of synaptic molecules in living neurons has radically altered our view of the synapse, from that of a generally static structure to that of a dynamic molecular assembly at steady state. This view holds not only for relatively labile synaptic components, such as synaptic vesicles, cytoskeletal elements, and neurotransmitter receptors, but also for the numerous synaptic molecules known as scaffolding molecules, a generic name for a diverse class of molecules that organize synaptic function in time and space. Recent studies reveal that these molecules, which confer a degree of stability to synaptic assemblies over time scales of hours and days, are themselves subject to significant dynamics. Furthermore, these dynamics are probably not without effect; wherever studied, these seem to be associated with spontaneous changes in scaffold molecule content, synaptic size, and possibly synaptic function. This review describes the dynamics exhibited by synaptic scaffold molecules, their typical time scales, and the potential implications to our understanding of synaptic function.

In vivo electroporation to physiologically identified deep brain regions in postnatal mammals

Genetic manipulation is widely used to research the central nervous system (CNS). The manipulation of molecular expression in a small number of neurons permits the detailed investigation of the role of specific molecules on the function and morphology of the neurons. Electroporation is a broadly used technique for gene transfer in the CNS. However, the targeting of gene transfer using electroporation in postnatal animals was restricted to the cortex, hippocampus, or the region facing the ventricle in previous reports. Electroporation targeting of deep brain structures, such as the thalamus, has been difficult. We introduce a novel electroporation technique that enables gene transfer to a physiologically identified deep brain region using a glass pipette. We recorded neural activity in young-adult mice to identify the location of the lateral geniculate nucleus (LGN) of the thalamus, using a glass pipette electrode containing the plasmid DNA encoding enhanced green fluorescent protein (EGFP). The location of the LGN was confirmed by monitoring visual responses, and the plasmid solution was pressure-injected into the recording site. Voltage pulses were delivered through the glass pipette electrode. Several EGFP-labeled somata and dendrites were observed in the LGN after a few weeks, and labeled axons were found in the visual cortex. The EGFP-expressing structures were observed in detail sufficient to reconstruct their morphology in three dimensions. We further confirmed the applicability of this technique in cats. This method should be useful for the transfer of various genes into cells in physiologically identified brain regions in rodents and gyrencephalic mammals.

Microcircuit dynamics of map plasticity in barrel cortex

Functional reorganization of the whisker map in rodent barrel cortex has long served as a model for cortical plasticity following changes in sensory experience. Given the heterogeneity of neuronal response properties in neocortex, it has remained unclear how individual neurons in the cortical microcircuit are affected. Novel in vivo imaging and electrophysiology methods allow longitudinal recording of the same neurons' functional properties and therefore have the critical ability to resolve the direction and dynamics of change as plasticity progresses. Tracking sensory responsiveness before and after whisker trimming has uncovered diverse effects in individual neurons, suggesting that longitudinal recording will be essential for elucidating plasticity mechanisms within cortical microcircuits.

Steady or changing? Long-term monitoring of neuronal population activity

Stability and flexibility are both hallmarks of brain function that allow animals to thrive in ever-changing environments. Investigating how a balance between these opposing features is achieved with a dynamic array of cellular and molecular constituents requires long-term tracking of activity from individual neurons. Here, we review in vivo chronic extracellular recording studies and recent long-term two-photon calcium-imaging investigations that address the question of stability and plasticity of neuronal population activity in the mammalian brain. Overall, spiking activity is heterogeneously distributed among neurons in local populations and largely remains stable for individual cells over time. Tuning properties appear more flexible and may be adaptively stabilized, possibly by neuromodulators, to encode reliably and specifically salient stimuli or behaviors.