The touch and zap method for in vivo whole-cell patch recording of intrinsic and visual responses of cortical neurons and Glial cells

Whole-cell patch recording is an essential tool for quantitatively establishing the biophysics of brain function, particularly in vivo. This method is of particular interest for studying the functional roles of cortical glial cells in the intact brain, which cannot be assessed with extracellular recordings. Nevertheless, a reasonable success rate remains a challenge because of stability, recording duration and electrical quality constraints, particularly for voltage clamp, dynamic clamp or conductance measurements. To address this, we describe "Touch and Zap", an alternative method for whole-cell patch clamp recordings, with the goal of being simpler, quicker and more gentle to brain tissue than previous approaches. Under current clamp mode with a continuous train of hyperpolarizing current pulses, seal formation is initiated immediately upon cell contact, thus the "Touch". By maintaining the current injection, whole-cell access is spontaneously achieved within seconds from the cell-attached configuration by a self-limited membrane electroporation, or "Zap", as seal resistance increases. We present examples of intrinsic and visual responses of neurons and putative glial cells obtained with the revised method from cat and rat cortices in vivo. Recording parameters and biophysical properties obtained with the Touch and Zap method compare favourably with those obtained with the traditional blind patch approach, demonstrating that the revised approach does not compromise the recorded cell. We find that the method is particularly well-suited for whole-cell patch recordings of cortical glial cells in vivo, targeting a wider population of this cell type than the standard method, with better access resistance. Overall, the gentler Touch and Zap method is promising for studying quantitative functional properties in the intact brain with minimal perturbation of the cell's intrinsic properties and local network. Because the Touch and Zap method is performed semi-automatically, this approach is more reproducible and less dependent on experimenter technique

Neuron

Ripples are high-frequency oscillations associated with population bursts in area CA1 of the hippocampus that play a prominent role in theories of memory consolidation. While spiking during ripples has been extensively studied, our understanding of the subthreshold behavior of hippocampal neurons during these events remains incomplete. Here, we combine in vivo whole-cell and multisite extracellular recordings to characterize the membrane potential dynamics of identified CA1 pyramidal neurons during ripples. We find that the subthreshold depolarization during ripples is uncorrelated with the net excitatory input to CA1, while the post-ripple hyperpolarization varies proportionately. This clarifies the circuit mechanism keeping most neurons silent during ripples. On a finer timescale, the phase delay between intracellular and extracellular ripple oscillations varies systematically with membrane potential. Such smoothly varying delays are inconsistent with models of intracellular ripple generation involving perisomatic inhibition alone. Instead, they suggest that ripple-frequency excitation leading inhibition shapes intracellular ripple oscillations.DP1 MH099907/MH/NIMH NIH HHS/United StatesDP1 OD008255/OD/NIH HHS/United States5DP1MH099907/DP/NCCDPHP CDC HHS/United StatesNIH 1DP1OD008255/OD/NIH HHS/United States2017-02-17T00:00:00Z26889811PMC516757

Brain State Dependence of Hippocampal Subthreshold Activity in Awake Mice

Monitoring the membrane potential of individual neurons has uncovered how single-cell properties contribute to network processing across different brain states in neocortex. In contrast, the subthreshold modulation of hippocampal neurons by brain state has not been systematically characterized. To address this, we combined whole-cell recordings from dentate granule cells and CA1 pyramidal neurons with multisite extracellular recordings and behavioral measurements in awake mice. We show that the average membrane potential, amplitude of subthreshold fluctuations, and distance to spike threshold are all modulated by brain state. Furthermore, even within individual states, rapid variations in arousal are reflected in membrane potential fluctuations. These factors produce depolarizing ramps in the membrane potential of hippocampal neurons that precede ripples and mirror transitions to a network regime conducive for ripple generation. These results suggest that there are coordinated shifts in the subthreshold dynamics of individual neurons that underlie the transitions between distinct modes of hippocampal processing

GABAergic synaptic protein dynamics measured by spectroscopic approaches.

The activity dependent adjustment of synaptic strength (synaptic plasticity) involves the reorganization of post-synaptic proteins. The fast diffusion of synaptic proteins has been shown to play an important role in such molecular rearrangements. Taking advantage of single particle tracking (SPT) and fluorescence recovery after photobleaching (FRAP) techniques, it has been demonstrated that during inhibitory long-term potentiation (iLTP) the scaffold protein gephyrin and GABAA receptors are accumulated and immobilized at post-synaptic inhibitory sites

Whole Brain Network Dynamics of Epileptic Seizures at Single Cell Resolution

Epileptic seizures are characterised by abnormal brain dynamics at multiple scales, engaging single neurons, neuronal ensembles and coarse brain regions. Key to understanding the cause of such emergent population dynamics, is capturing the collective behaviour of neuronal activity at multiple brain scales. In this thesis I make use of the larval zebrafish to capture single cell neuronal activity across the whole brain during epileptic seizures. Firstly, I make use of statistical physics methods to quantify the collective behaviour of single neuron dynamics during epileptic seizures. Here, I demonstrate a population mechanism through which single neuron dynamics organise into seizures: brain dynamics deviate from a phase transition. Secondly, I make use of single neuron network models to identify the synaptic mechanisms that actually cause this shift to occur. Here, I show that the density of neuronal connections in the network is key for driving generalised seizure dynamics. Interestingly, such changes also disrupt network response properties and flexible dynamics in brain networks, thus linking microscale neuronal changes with emergent brain dysfunction during seizures. Thirdly, I make use of non-linear causal inference methods to study the nature of the underlying neuronal interactions that enable seizures to occur. Here I show that seizures are driven by high synchrony but also by highly non-linear interactions between neurons. Interestingly, these non-linear signatures are filtered out at the macroscale, and therefore may represent a neuronal signature that could be used for microscale interventional strategies. This thesis demonstrates the utility of studying multi-scale dynamics in the larval zebrafish, to link neuronal activity at the microscale with emergent properties during seizures

Excitatory-Inhibitory Homeostasis and Diaschisis: Tying the Local and Global Scales in the Post-stroke Cortex

Maintaining a balance between excitatory and inhibitory activity is an essential feature of neural networks of the neocortex. In the face of perturbations in the levels of excitation to cortical neurons, synapses adjust to maintain excitatory-inhibitory (EI) balance. In this review, we summarize research on this EI homeostasis in the neocortex, using stroke as our case study, and in particular the loss of excitation to distant cortical regions after focal lesions. Widespread changes following a localized lesion, a phenomenon known as diaschisis, are not only related to excitability, but also observed with respect to functional connectivity. Here, we highlight the main findings regarding the evolution of excitability and functional cortical networks during the process of post-stroke recovery, and how both are related to functional recovery. We show that cortical reorganization at a global scale can be explained from the perspective of EI homeostasis. Indeed, recovery of functional networks is paralleled by increases in excitability across the cortex. These adaptive changes likely result from plasticity mechanisms such as synaptic scaling and are linked to EI homeostasis, providing a possible target for future therapeutic strategies in the process of rehabilitation. In addition, we address the difficulty of simultaneously studying these multiscale processes by presenting recent advances in large-scale modeling of the human cortex in the contexts of stroke and EI homeostasis, suggesting computational modeling as a powerful tool to tie the meso- and macro-scale processes of recovery in stroke patients. Copyright © 2022 Páscoa dos Santos and Verschure

Membrane Potential Dynamics of Hippocampal Neurons During Ripples in Awake Mice

During periods of slow wave sleep and quiet wakefulness, the hippocampal formation generates spontaneous population bursts that are organized as a high-frequency "ripple" oscillation. The neurons that participate in these bursts often replay previously experienced activity patterns encoded during alert behavior, and interfering with ripple generation produces deficits in learning and memory tasks. For these reasons, ripples play a prominent role in theories of memory consolidation and retrieval. While spiking during ripples has been extensively studied, our understanding of the subthreshold behavior of hippocampal neurons during these events remains incomplete. Here, we combine in vivo whole-cell recordings with multisite extracellular and behavioral measurements to study the membrane potential dynamics of hippocampal neurons during ripples in awake mice. We find that the subthreshold depolarization of CA1 pyramidal neurons is uncorrelated with net excitatory input, clarifying the circuit mechanism keeping most neurons silent during ripples. On a finer time scale, the phase delay between intracellular and extracellular ripple oscillations varies systematically with the membrane potential, which is inconsistent with models of intracellular ripple generation involving perisomatic inhibition alone. In addition, we find that membrane potential statistics (mean, variability, distance to threshold) of CA1 pyramidal neurons and dentate granule cells are systematically modulated across brain states, that rapid variations in pupil diameter are reflected in subthreshold fluctuations, and that many neurons begin depolarizing about one second before ripple onset. These results provide evidence that coordinated shifts in the subthreshold dynamics of individual neurons may contribute to the emergence of state-dependent hippocampal activity patterns. Finally, we present evidence that area CA3 provides the major excitatory input to dentate granule cells during ripples and that there are coordinated interactions between hippocampal ripples and population events in the dentate gyrus, both of which inform network-level models of ripple generation