Surface-printed microdot array chips for the quantification of axonal collateral branching of a single neuron in vitro

Lab on a Chip ◽  
2014 ◽  
Vol 14 (4) ◽  
pp. 799-805 ◽  
Author(s):  
Woon Ryoung Kim ◽  
Min Jee Jang ◽  
Sunghoon Joo ◽  
Woong Sun ◽  
Yoonkey Nam
Keyword(s):  
Single Neuron ◽  
Axonal Collateral

Safety of Hybrid Electrodes for Single-Neuron Recordings in Humans

Neurosurgery ◽  
2013 ◽  
Vol 73 (1) ◽  
pp. 78-85 ◽  
Author(s):  
Stefan Hefft ◽  
Armin Brandt ◽  
Stefan Zwick ◽  
Dominik von Elverfeldt ◽  
Irina Mader ◽  
...  
Keyword(s):  
Single Neuron ◽  
Electrode Implantation ◽  
Intraoperative Computed Tomography ◽  
Postoperative Mri ◽  
Depth Electrodes ◽  
Magnetic Resonance Imaging Mri ◽  
Clinical Mri

Abstract BACKGROUND: Intracranial in vivo recordings of individual neurons in humans are increasingly performed for a better understanding of the mechanisms of epileptogenesis and of the neurobiological basis of cognition. So far, information about the safety of stereotactic implantations and of magnetic resonance imaging (MRI) with hybrid depth electrodes is scarce. OBJECTIVE: The aim of this study was to assess neurosurgical safety of implantations, recordings, and imaging using hybrid electrodes in humans. METHODS: Perioperative and long-term safety of implantation of a total of 88 hybrid depth electrodes with integrated microwires was assessed retrospectively in 25 consecutive epilepsy patients who underwent implantation of electrodes from 2007 to 2011 based on electronically stored charts. Safety aspects of MRI are reported from both in vitro and in vivo investigations. Precision of electrode implantation is evaluated based on intraoperative computed tomography and pre- and postoperative MRI. RESULTS: There was no clinically relevant morbidity associated with the use of hybrid electrodes in any of the patients. Precision of recordings from the targets aimed at was similar to that of standard depth electrodes. In vitro studies demonstrated the absence of relevant heating of hybrid electrodes with newly designed connectors with MRI at 1.5 T, corresponding to well-tolerated clinical MRI in patients. CONCLUSION: Given the technical approach described here, precise targeting and safe use are possible with hybrid electrodes containing microwires for in vivo recording of human neuronal units.

scholarly journals Single-Neuron Discharge Properties and Network Activity in Dissociated Cultures of Neocortex

2004 ◽  
Vol 92 (2) ◽  
pp. 977-996 ◽  
Author(s):  
M. Giugliano ◽  
P. Darbon ◽  
M. Arsiero ◽  
H.-R. Lüscher ◽  
J. Streit
Keyword(s):  
Single Cell ◽  
Single Neuron ◽  
Neuronal Response ◽  
Mean Field ◽  
Network Activity ◽  
Model Parameters ◽  
Cell Discharge ◽  
Collective Activity ◽  
The Mean

Cultures of neurons from rat neocortex exhibit spontaneous, temporally patterned, network activity. Such a distributed activity in vitro constitutes a possible framework for combining theoretical and experimental approaches, linking the single-neuron discharge properties to network phenomena. In this work, we addressed the issue of closing the loop, from the identification of the single-cell discharge properties to the prediction of collective network phenomena. Thus, we compared these predictions with the spontaneously emerging network activity in vitro, detected by substrate arrays of microelectrodes. Therefore, we characterized the single-cell discharge properties to Gauss-distributed noisy currents, under pharmacological blockade of the synaptic transmission. Such stochastic currents emulate a realistic input from the network. The mean ( m) and variance ( s2) of the injected current were varied independently, reminiscent of the extended mean-field description of a variety of possible presynaptic network organizations and mean activity levels, and the neuronal response was evaluated in terms of the steady-state mean firing rate ( f). Experimental current-to-spike–rate responses f( m, s2) were similar to those of neurons in brain slices, and could be quantitatively described by leaky integrate-and-fire (IF) point neurons. The identified model parameters were then used in numerical simulations of a network of IF neurons. Such a network reproduced a collective activity, matching the spontaneous irregular population bursting, observed in cultured networks. We finally interpret such a collective activity and its link with model details by the mean-field theory. We conclude that the IF model is an adequate minimal description of synaptic integration and neuronal excitability, when collective network activities are considered in vitro.

scholarly journals Single-neuron models linking electrophysiology, morphology and transcriptomics across cortical cell types

2020 ◽  
Author(s):  
Anirban Nandi ◽  
Tom Chartrand ◽  
Werner Van Geit ◽  
Anatoly Buchin ◽  
Zizhen Yao ◽  
...  
Keyword(s):  
Ion Channel ◽  
Single Cell ◽  
Single Neuron ◽  
Cell Types ◽  
Cell Models ◽  
Cell Type ◽  
Channel Conductance ◽  
Neuron Models ◽  
Inhibitory Cell

AbstractIdentifying the cell types constituting brain circuits is a fundamental question in neuroscience and motivates the generation of taxonomies based on electrophysiological, morphological and molecular single cell properties. Establishing the correspondence across data modalities and understanding the underlying principles has proven challenging. Bio-realistic computational models offer the ability to probe cause-and-effect and have historically been used to explore phenomena at the single-neuron level. Here we introduce a computational optimization workflow used for the generation and evaluation of more than 130 million single neuron models with active conductances. These models were based on 230 in vitro electrophysiological experiments followed by morphological reconstruction from the mouse visual cortex. We show that distinct ion channel conductance vectors exist that distinguish between major cortical classes with passive and h-channel conductances emerging as particularly important for classification. Next, using models of genetically defined classes, we show that differences in specific conductances predicted from the models reflect differences in gene expression in excitatory and inhibitory cell types as experimentally validated by single-cell RNA-sequencing. The differences in these conductances, in turn, explain many of the electrophysiological differences observed between cell types. Finally, we show the robustness of the herein generated single-cell models as representations and realizations of specific cell types in face of biological variability and optimization complexity. Our computational effort generated models that reconcile major single-cell data modalities that define cell types allowing for causal relationships to be examined.HighlightsGeneration and evaluation of more than 130 million single-cell models with active conductances along the reconstructed morphology faithfully recapitulate the electrophysiology of 230 in vitro experiments.Optimized ion channel conductances along the cellular morphology (‘all-active’) are characteristic of model complexity and offer enhanced biophysical realism.Ion channel conductance vectors of all-active models classify transcriptomically defined cell-types.Cell type differences in ion channel conductances predicted by the models correlate with experimentally measured single-cell gene expression differences in inhibitory (Pvalb, Sst, Htr3a) and excitatory (Nr5a1, Rbp4) classes.A set of ion channel conductances identified by comparing between cell type model populations explain electrophysiology differences between these types in simulations and brain slice experiments.All-active models recapitulate multimodal properties of excitatory and inhibitory cell types offering a systematic and causal way of linking differences between them.

scholarly journals Predicting Single-Neuron Activity in Locally Connected Networks

2012 ◽  
Vol 24 (10) ◽  
pp. 2655-2677 ◽  
Author(s):  
Feraz Azhar ◽  
William S. Anderson
Keyword(s):  
Process Model ◽  
Single Neuron ◽  
Neuron Activity ◽  
Neuronal Populations ◽  
Behaving Monkeys ◽  
External Stimuli ◽  
Multiple Units

The characterization of coordinated activity in neuronal populations has received renewed interest in the light of advancing experimental techniques that allow recordings from multiple units simultaneously. Across both in vitro and in vivo preparations, nearby neurons show coordinated responses when spontaneously active and when subject to external stimuli. Recent work (Truccolo, Hochberg, & Donoghue, 2010 ) has connected these coordinated responses to behavior, showing that small ensembles of neurons in arm-related areas of sensorimotor cortex can reliably predict single-neuron spikes in behaving monkeys and humans. We investigate this phenomenon using an analogous point process model, showing that in the case of a computational model of cortex responding to random background inputs, one is similarly able to predict the future state of a single neuron by considering its own spiking history, together with the spiking histories of randomly sampled ensembles of nearby neurons. This model exhibits realistic cortical architecture and displays bursting episodes in the two distinct connectivity schemes studied. We conjecture that the baseline predictability we find in these instances is characteristic of locally connected networks more broadly considered.

Interactions between network synchrony and the dynamics of neuronal threshold

2012 ◽  
Vol 107 (11) ◽  
pp. 2926-2936 ◽  
Author(s):  
Avner Wallach ◽  
Shimon Marom
Keyword(s):  
Single Neuron ◽  
Cellular Level ◽  
Network Activity ◽  
Threshold Dynamics ◽  
Synchronous Activity ◽  
Interactive Nature ◽  
Synchronous Network ◽  
Health And Disease ◽  
The Impact

Synchronous activity impacts on a range of functional brain capacities in health and disease. To address the interrelations between cellular level activity and network-wide synchronous events, we implemented in vitro a recently introduced technique, the response clamp, which enables online monitoring of single neuron threshold dynamics while ongoing network synchronous activity continues uninterrupted. We show that the occurrence of a synchronous network event causes a significant biphasic change in the single neuron threshold. These threshold dynamics are correlated across the neurons constituting the network and are entailed by the input to the neurons rather than by their own spiking (i.e., output) activity. The magnitude of network activity during a synchronous event is correlated with the threshold state of individual neurons at the event's onset. Recovery from the impact of a given synchronous event on the neuronal threshold lasts several seconds and seems to be a key determinant of the time to the next spontaneously occurring synchronous event. Moreover, the neuronal threshold is shown to be correlated with the excitability dynamics of the entire network. We conclude that the relations between the two levels (network activity and the single neuron threshold) should be thought of in terms that emphasize their interactive nature.

scholarly journals M-type potassium conductance controls the emergence of neural phase codes: a combined experimental and neuron modelling study

2014 ◽  
Vol 11 (99) ◽  
pp. 20140604 ◽  
Author(s):  
Jeehyun Kwag ◽  
Hyun Jae Jang ◽  
Mincheol Kim ◽  
Sujeong Lee
Keyword(s):  
Information Processing ◽  
Single Neuron ◽  
Pyramidal Neurons ◽  
Spatial Information ◽  
Potassium Conductance ◽  
Place Cells ◽  
Intrinsic Mechanism ◽  
Phase Precession

Rate and phase codes are believed to be important in neural information processing. Hippocampal place cells provide a good example where both coding schemes coexist during spatial information processing. Spike rate increases in the place field, whereas spike phase precesses relative to the ongoing theta oscillation. However, what intrinsic mechanism allows for a single neuron to generate spike output patterns that contain both neural codes is unknown. Using dynamic clamp, we simulate an in vivo -like subthreshold dynamics of place cells to in vitro CA1 pyramidal neurons to establish an in vitro model of spike phase precession. Using this in vitro model, we show that membrane potential oscillation (MPO) dynamics is important in the emergence of spike phase codes: blocking the slowly activating, non-inactivating K + current ( I M ), which is known to control subthreshold MPO, disrupts MPO and abolishes spike phase precession. We verify the importance of adaptive I M in the generation of phase codes using both an adaptive integrate-and-fire and a Hodgkin–Huxley (HH) neuron model. Especially, using the HH model, we further show that it is the perisomatically located I M with slow activation kinetics that is crucial for the generation of phase codes. These results suggest an important functional role of I M in single neuron computation, where I M serves as an intrinsic mechanism allowing for dual rate and phase coding in single neurons.

Ultrastructural Investigations of the Contractile Filaments of Amoebae

1974 ◽  
Vol 32 ◽  
pp. 188-189
Author(s):  
P.L. Moore
Keyword(s):  
Cytoplasmic Streaming ◽  
Three Dimensional ◽  
Freeze Fracture ◽  
Amoeboid Movement ◽  
Different Types ◽  
Chemical Conditions ◽  
Complete Interpretation

Previous freeze fracture results on the intact giant, amoeba Chaos carolinensis indicated the presence of a fibrillar arrangement of filaments within the cytoplasm. A complete interpretation of the three dimensional ultrastructure of these structures, and their possible role in amoeboid movement was not possible, since comparable results could not be obtained with conventional fixation of intact amoebae. Progress in interpreting the freeze fracture images of amoebae required a more thorough understanding of the different types of filaments present in amoebae, and of the ways in which they could be organized while remaining functional.The recent development of a calcium sensitive, demembranated, amoeboid model of Chaos carolinensis has made it possible to achieve a better understanding of such functional arrangements of amoeboid filaments. In these models the motility of demembranated cytoplasm can be controlled in vitro, and the chemical conditions necessary for contractility, and cytoplasmic streaming can be investigated. It is clear from these studies that “fibrils” exist in amoeboid models, and that they are capable of contracting along their length under conditions similar to those which cause contraction in vertebrate muscles.

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