Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology

Annecchino, Luca; Morris, Alexander R.; Copeland, Caroline S.; Agabi, Oshiorenoya E.; Chadderton, Paul; Schultz, Simon R.

doi:10.1016/j.neuron.2017.08.018

Cited by 54 publications

(73 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With recent advancements in in vivo electrophysiology ( Kodandaramaiah et al, 2012 ; Annecchino et al, 2017 ) and volume electron microscopy ( Briggman and Denk, 2006 ; Briggman and Bock, 2012 ; Denk et al, 2012 ; Helmstaedter, 2013 ), the understanding of neuronal microcircuits has become more obtainable. However, neither of these techniques alone can provide sufficient information to build effective models of circuit function.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Association of Anatomical and Functional Classes of Olfactory Bulb Neurons

et al. 2018

View full text Add to dashboard Cite

Juxtaglomerular cells (JGCs) of the olfactory bulb (OB) glomerular layer (GL) play a fundamental role in olfactory information processing. Their variability in morphology, physiology, and connectivity suggests distinct functions. The quantitative understanding of population-wise morphological and physiological properties and a comprehensive classification based on quantitative parameters, however, is still lacking, impeding the analysis of microcircuits. Here, we provide multivariate clustering of 95 in vitro sampled cells from the GL of the mouse (male or female C57BL/6) OB and perform detailed morphological and physiological characterization for the seven computed JGC types. Using a classifier based on a subselection of parameters, we identified the neuron types in paired recordings to characterize their functional connectivity. We found that 4 of the 7 clusters comply with prevailing concepts of GL cell types, whereas the other 3 represent own distinct entities. We have labeled these entities horizontal superficial tufted cell (hSTC), vertical superficial tufted cell, and microglomerular cell (MGC): The hSTC is a tufted cell with a lateral dendrite that much like mitral cells and tufted cells receives excitatory inputs from the external tufted cell but likewise serves as an excitatory element for glomerular interneurons. The vertical superficial tufted cell, on the other hand, represents a tufted cell type with vertically projecting basal dendrites. We further define the MGC, characterized by a small dendritic tree and plateau action potentials. In addition to olfactory nerve-driven and external tufted cell driven interneurons, these MGCs represent a third functionally distinct type, the hSTC-driven interneurons. The presented correlative analysis helps to bridge the gap between branching patterns and cellular functional properties, permitting the integration of results from in vivo recordings, advanced morphological tools, and connectomics.SIGNIFICANCE STATEMENT The variance of neuron properties is a feature across mammalian cerebral circuits, contributing to signal processing and adding computational robustness to the networks. It is particularly noticeable in the glomerular layer of the olfactory bulb, the first site of olfactory information processing. We provide the first unbiased population-wise multivariate analysis to correlate morphological and physiological parameters of juxtaglomerular cells. We identify seven cell types, including four previously described neuron types, and identify further three distinct classes. The presented correlative analysis of morphological and physiological parameters gives an opportunity to predict morphological classes from physiological measurements or the functional properties of neurons from morphology and opens the way to integrate results from in vivo recordings, advanced morphological tools, and connectomics.

show abstract

Section: Discussionmentioning

confidence: 99%

Quantitative Association of Anatomical and Functional Classes of Olfactory Bulb Neurons

et al. 2018

View full text Add to dashboard Cite

show abstract

“…This allowed the reuse of the same pipettes with no degradation in signal fidelity both in vitro and in vivo. Robotic assistance to move the pipettes also may help speed up this process and has recently been implemented for the entire visualised patching process (Annecchino et al, 2017; Suk et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Multiple two-photon targeted whole-cell patch-clamp recordings from monosynaptically connected neurons in vivo

Jouhanneau

Poulet

2019

Preprint

View full text Add to dashboard Cite

28Although we know a great deal about monosynaptic connectivity, transmission and integration 29 in the mammalian nervous system from in vitro studies, very little is known in vivo. This is partly 30 because it is technically difficult to evoke action potentials and simultaneously record small 31 amplitude subthreshold responses in closely (< 150 µm) located pairs of neurons. To address 32 this, we have developed in vivo two-photon targeted multiple (2 -4) whole-cell patch clamp 33 recordings of nearby neurons in superficial layers 1 to 3 of primary somatosensory cortex. 34Here we describe a step-by-step guide to this approach in the anesthetised mouse, including: 35 the design of the setup, surgery, preparation of pipettes, targeting and acquisition of multiple 36 whole-cell recordings, as well as in vivo and post-hoc histology. The procedure takes ~ 4 hours 37 from start of surgery to end of recording and allows examinations both into the 38 electrophysiological features of unitary excitatory and inhibitory monosynaptic inputs and the 39 synaptic mechanisms of correlated neuronal activity.45 properties of synapses. In the intact brain, however, synapses function during different 46 behavioural and network states as well fluctuating levels of neuromodulators and far less is 47 known about monosynaptic transmission and the activity of connected neurons in vivo. 48In vivo approaches to identify connected pairs of neurons in the mammalian nervous system 49 have typically performed electrophysiological recordings of multiple single neurons and 50 examined the average response of one neuron to spontaneously occurring action potentials in 51 another neuron. "Spike triggered averaging" of cortical neurons has been performed both with 52 multiple extracellular recordings (Bartho, 2004; Csicsvari et al., 1998; English et al., 2017; 53 Fujisawa et al., 2008; Reid and Alonso, 1995; Swadlow and Gusev, 2002) and a combination 54 of extracellular and intracellular membrane potential recordings (Bruno, 2006; Crochet et al., 55 2005; London et al., 2010; Matsumura et al., 1996; Yu and Ferster, 2013). However, because 56 it is not yet possible to record the activity of all neurons presynaptic to the cells of interest and 57 cortical neurons can fire simultaneously, it is difficult to confirm whether correlated activity is 58 the result of a direct synaptic connection between the two recorded neurons or input from a 59 third, unrecorded, neuron with similar firing dynamics. One approach to get around the problem 60 of synchronous input is to have experimental control of action potential timing using single cell 61 stimulation, while simultaneously recording the evoked membrane potential response from a 62 second neuron. While, care has to be taken in concluding that any synaptic response is the 63 result of a monosynaptic rather than polysynaptic input (Berry and Pentreath, 1976; Parker, 64 2010), this approach has been used in vivo to characterise the wiring and functional properties

show abstract

“…Combined with surgical robotics advances that allow precisely defined access to brain ( Pak et al, 2015 ), high density robotically guided patch clamping arrays that simultaneously target and record from neurons distributed locally in microcircuits or in multiple brain regions could be developed. Imaging could be used for closed-loop control of multiple pipettes, as has already been done for single patch pipettes ( Suk et al, 2017 ; Annecchino et al, 2017 ). Three or four fold increases in the number of simultaneously controlled pipettes could be achieved by using miniaturized micromanipulators, and increasing the number of pneumatic valve banks in the multipatcher control box—–both of which are possible using existing off-the-shelf hardware.…”

Section: Discussionmentioning

confidence: 99%

Multi-neuron intracellular recording in vivo via interacting autopatching robots

Kodandaramaiah

Flores

Holst

et al. 2018

eLife

View full text Add to dashboard Cite

The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known about the intracellular processes that lead to spiking activity. We present a robotic system, the multipatcher, capable of automatically obtaining blind whole-cell patch clamp recordings from multiple neurons simultaneously. The multipatcher significantly extends automated patch clamping, or 'autopatching’, to guide four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain. We demonstrate its performance in the cortex of anesthetized and awake mice. A multipatcher with four electrodes took an average of 10 min to obtain dual or triple recordings in 29% of trials in anesthetized mice, and in 18% of the trials in awake mice, thus illustrating practical yield and throughput to obtain multiple, simultaneous whole-cell recordings in vivo.

show abstract

Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology

Cited by 54 publications

References 31 publications

Quantitative Association of Anatomical and Functional Classes of Olfactory Bulb Neurons

Quantitative Association of Anatomical and Functional Classes of Olfactory Bulb Neurons

Multiple two-photon targeted whole-cell patch-clamp recordings from monosynaptically connected neurons in vivo

Multi-neuron intracellular recording in vivo via interacting autopatching robots

Contact Info

Product

Resources

About