The Touch and Zap method for in vivo whole-cell patch recording of intrinsic and visual responses of cortical neurons and glial cells

Analysis of Network Models with Neuron-Astrocyte Interactions

Neural networks, composed of many neurons and governed by complex interactions between them, are a widely accepted formalism for modeling and exploring global dynamics and emergent properties in brain systems. In the past decades, experimental evidence of computationally relevant neuron-astrocyte interactions, as well as the astrocytic modulation of global neural dynamics, have accumulated. These findings motivated advances in computational glioscience and inspired several models integrating mechanisms of neuron-astrocyte interactions into the standard neural network formalism. These models were developed to study, for example, synchronization, information transfer, synaptic plasticity, and hyperexcitability, as well as classification tasks and hardware implementations. We here focus on network models of at least two neurons interacting bidirectionally with at least two astrocytes that include explicitly modeled astrocytic calcium dynamics. In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to better integrate them in data-driven computational models. Broadening the discussion about theoretical approaches and expanding the computational tools is necessary to better understand astrocytes' roles in brain functions.

Cell-type-specific silence in thalamocortical circuits precedes hippocampal sharp-wave ripples

Evidence suggests that the hippocampus conveys memory-related neural patterns across distributed cortical circuits during high-frequency oscillations called sharp-wave ripples (SWRs). We investigate how circuit activity in the retrosplenial cortex (RSC), a primary hippocampal target, could aid in processing SWR-related input. Using patch-clamp recordings from awake mice, we find that SWR-aligned membrane potential modulation is widespread but weak, and that spiking responses are sparse. However, using cell-type-specific two-photon Ca²⁺ imaging and optogenetics, we show that, 1-2 s before SWRs, superficial inhibition and thalamocortical input in RSC is reduced. We propose that pyramidal dendrites experience decreased local inhibition and subcortical interference in a seconds-long time window preceding SWRs. This may aid communication of weak and sparse SWR-aligned excitation between the hippocampus and neocortex and promote the strengthening of memory-related connections.

In Vivo Whole-Cell Patch-Clamp Methods: Recent Technical Progress and Future Perspectives

Brain functions are fundamental for the survival of organisms, and they are supported by neural circuits consisting of a variety of neurons. To investigate the function of neurons at the single-cell level, researchers often use whole-cell patch-clamp recording techniques. These techniques enable us to record membrane potentials (including action potentials) of individual neurons of not only anesthetized but also actively behaving animals. This whole-cell recording method enables us to reveal how neuronal activities support brain function at the single-cell level. In this review, we introduce previous studies using in vivo patch-clamp recording techniques and recent findings primarily regarding neuronal activities in the hippocampus for behavioral function. We further discuss how we can bridge the gap between electrophysiology and biochemistry.

Identifying neuronal correlates of dying and resuscitation in a model of reversible brain anoxia

We developed a new rodent model of reversible brain anoxia and performed continuous electrocorticographic (ECoG) and intracellular recordings of neocortical neurons to identify in real-time the cellular and network dynamics that successively emerge throughout the dying-to-recovery process. Along with a global decrease in ECoG amplitude, deprivation of oxygen supply resulted in an early surge of beta-gamma activities, accompanied by rhythmic membrane depolarizations and regular firing in pyramidal neurons. ECoG and intracellular signals were then dominated by low-frequency activities which progressively declined towards isoelectric levels. Cortical neurons during the isoelectric state underwent a massive membrane potential depolarizing shift, captured in the ECoG as a large amplitude triphasic wave known as the "wave-of-death" (WoD). This neuronal anoxic depolarization, associated with a block of action potentials and a loss of cell integrative properties, could however be reversed if brain re-oxygenation was rapidly restored (within 2-3.5 min). The subsequent slow repolarization of neocortical neurons resulted in a second identifiable ECoG wave we termed "wave-of-resuscitation" since it inaugurated the progressive regaining of pre-anoxic synaptic and firing activities. These results demonstrate that the WoD is not a biomarker of an irremediable death and unveil the cellular correlates of a novel ECoG wave that may be predictive of a successful recovery. The identification of real-time biomarkers of onset and termination of cell anoxic insult could benefit research on interventional strategies to optimize resuscitation procedures.

Electrophysiological Profiling of Neocortical Neural Subtypes: A Semi-Supervised Method Applied to in vivo Whole-Cell Patch-Clamp Data

A lot of efforts have been made to understand the structure and function of neocortical circuits. In fact, a promising way to understand the functions of cortical circuits is the classification of the neural types, based on their different properties. Recent studies focused on applying modern computational methods to classify neurons based on molecular, morphological, physiological, or mixed of these criteria. Although there are studies in the literature on in vitro/vivo extracellular or in vitro intracellular recordings, a study on the classification of neuronal types using in vivo whole-cell patch-clamp recordings is still lacking. We thus proposed a novel semi-supervised classification method based on waveform shape of neurons' spikes using in vivo whole-cell patch-clamp recordings. We, first, detected spike candidates. Then discriminative features were extracted from the time samples of the spikes using discrete cosine transform. We then extracted the center of clusters using fuzzy c-mean clustering and finally, the neurons were classified using the minimum distance classifier. We distinguished three types of neurons: excitatory pyramidal cells (Pyr) and two types of inhibitory neurons: GABAergic- parvalbumin positive (PV), and somatostatin positive (SST) non-pyramidal cells in layer II/III of the mice primary visual cortex. We used 10-fold cross validation in our study. The classification accuracy for PV, Pyr, and SST was 91.59 ± 1.69, 97.47 ± 0.67, and 89.06 ± 1.99, respectively. Overall, the algorithm correctly classified 92.67 ± 0.54% of the cells, confirming the relative robustness of the discriminant functions. The performance of the method was further assessed on in vitro recordings by using a pool of 50 neurons from Allen institute Cell Types Database (5 major subtypes of neurons: Pyr, PV, SST, 5HT3a, and vasoactive intestinal peptide (VIP) cells). Its overall accuracy was 84.13 ± 0.81% on this data set using cross validation framework. The proposed algorithm is thus a promising new tool in recognizing cell's type with high accuracy in laboratories using in vivo/vitro whole-cell patch-clamp recording technique. The developed programs and the entire dataset are available online to interested readers.

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.

Current advances in cell electrophysiology: applications for the analysis of intercellular communications within the neurovascular unit

Patch clamp is a golden standard for studying (patho)physiological processes affecting membranes of excitable cells. This method is rather labor-intensive and requires well-trained professionals and long-lasting experimental procedures; therefore, accurate designing of the experiments with patch clamp methodology as well as collecting and analyzing the data obtained are essential for the widely spread implementation of this method into the routine research practice. Recently, the method became very prospective not only for the characterization of single excitable cells but also for the detailed assessment of intercellular communication, i.e. within the neurovascular unit. Here, we analyze the main advantages and disadvantages of patch clamp method, with special focus on the tendencies in clamping technique improvement with the help of patch electrodes for the assessment of intercellular communication in the brain.

Assembly and operation of the autopatcher for automated intracellular neural recording in vivo

Whole-cell patch clamping in vivo is an important neuroscience technique that uniquely provides access to both suprathreshold spiking and subthreshold synaptic events of single neurons in the brain. This article describes how to set up and use the autopatcher, which is a robot for automatically obtaining high-yield and high-quality whole-cell patch clamp recordings in vivo. By following this protocol, a functional experimental rig for automated whole-cell patch clamping can be set up in 1 week. High-quality surgical preparation of mice takes ∼1 h, and each autopatching experiment can be carried out over periods lasting several hours. Autopatching should enable in vivo intracellular investigations to be accessible by a substantial number of neuroscience laboratories, and it enables labs that are already doing in vivo patch clamping to scale up their efforts by reducing training time for new lab members and increasing experimental durations by handling mentally intensive tasks automatically.

Induction of an Isoelectric Brain State to Investigate the Impact of Endogenous Synaptic Activity on Neuronal Excitability In Vivo

The way neurons process information depends both on their intrinsic membrane properties and on the dynamics of the afferent synaptic network. In particular, endogenously-generated network activity, which strongly varies as a function of the state of vigilance, significantly modulates neuronal computation. To investigate how different spontaneous cerebral dynamics impact single neurons' integrative properties, we developed a new experimental strategy in the rat consisting in suppressing in vivo all cerebral activity by means of a systemic injection of a high dose of sodium pentobarbital. Cortical activities, continuously monitored by combined electrocorticogram (ECoG) and intracellular recordings are progressively slowed down, leading to a steady isoelectric profile. This extreme brain state, putting the rat into a deep comatose, was carefully monitored by measuring the physiological constants of the animal throughout the experiments. Intracellular recordings allowed us to characterize and compare the integrative properties of the same neuron embedded into physiologically relevant cortical dynamics, such as those encountered in the sleep-wake cycle, and when the brain was fully silent.

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.