scholarly journals Single synaptic inputs drive high-precision action potentials in parvalbumin expressing GABA-ergic cortical neurons in vivo

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Jean-Sébastien Jouhanneau ◽  
Jens Kremkow ◽  
James F. A. Poulet
Keyword(s):  
High Precision ◽  
Cortical Neurons ◽  
Action Potentials ◽  
Synaptic Inputs

scholarly journals How to build a grid cell

2014 ◽  
Vol 369 (1635) ◽  
pp. 20120520 ◽  
Author(s):  
Christoph Schmidt-Hieber ◽  
Michael Häusser
Keyword(s):  
Entorhinal Cortex ◽  
Action Potentials ◽  
Path Integration ◽  
Grid Cell ◽  
Medial Entorhinal Cortex ◽  
Synaptic Inputs ◽  
New Findings ◽  
Cell Firing

Neurons in the medial entorhinal cortex fire action potentials at regular spatial intervals, creating a striking grid-like pattern of spike rates spanning the whole environment of a navigating animal. This remarkable spatial code may represent a neural map for path integration. Recent advances using patch-clamp recordings from entorhinal cortex neurons in vitro and in vivo have revealed how the microcircuitry in the medial entorhinal cortex may contribute to grid cell firing patterns, and how grid cells may transform synaptic inputs into spike output during firing field crossings. These new findings provide key insights into the ingredients necessary to build a grid cell.

scholarly journals Temporally precise control of single-neuron spiking by juxtacellular nanostimulation

2017 ◽  
Vol 117 (3) ◽  
pp. 1363-1378 ◽  
Author(s):  
Maik C. Stüttgen ◽  
Lourens J. P. Nonkes ◽  
H. Rüdiger A. P. Geis ◽  
Paul H. Tiesinga ◽  
Arthur R. Houweling
Keyword(s):  
Short Duration ◽  
Cortical Neurons ◽  
Action Potentials ◽  
Neural Coding ◽  
Spike Trains ◽  
Precise Control ◽  
Neuronal Spike Trains ◽  
The Impact ◽  
Activity Dependent

Temporal patterns of action potentials influence a variety of activity-dependent intra- and intercellular processes and play an important role in theories of neural coding. Elucidating the mechanisms underlying these phenomena requires imposing spike trains with precisely defined patterns, but this has been challenging due to the limitations of existing stimulation techniques. Here we present a new nanostimulation method providing control over the action potential output of individual cortical neurons. Spikes are elicited through the juxtacellular application of short-duration fluctuating currents (“kurzpulses”), allowing for the sub-millisecond precise and reproducible induction of arbitrary patterns of action potentials at all physiologically relevant firing frequencies (<120 Hz), including minute-long spike trains recorded in freely moving animals. We systematically compared our method to whole cell current injection, as well as optogenetic stimulation, and show that nanostimulation performance compares favorably with these techniques. This new nanostimulation approach is easily applied, can be readily performed in awake behaving animals, and thus promises to be a powerful tool for systematic investigations into the temporal elements of neural codes, as well as the mechanisms underlying a wide variety of activity-dependent cellular processes. NEW & NOTEWORTHY Assessing the impact of temporal features of neuronal spike trains requires imposing arbitrary patterns of spiking on individual neurons during behavior, but this has been difficult to achieve due to limitations of existing stimulation methods. We present a technique that overcomes these limitations by using carefully designed short-duration fluctuating juxtacellular current injections, which allow for the precise and reliable evocation of arbitrary patterns of neuronal spikes in single neurons in vivo.

Monitoring the excitability of neocortical efferent neurons to direct activation by extracellular current pulses

1992 ◽  
Vol 68 (2) ◽  
pp. 605-619 ◽  
Author(s):  
H. A. Swadlow
Keyword(s):  
Cortical Neurons ◽  
Action Potentials ◽  
Short Latency ◽  
Gamma Aminobutyric Acid ◽  
Afferent Pathways ◽  
Synaptic Inputs ◽  
Direct Activation ◽  
Current Pulses ◽  
Efferent Neurons ◽  
Stimulation Of

1. Extracellular action potentials were recorded from antidromically activated efferent neurons in visual, somatosensory, and motor cortex of the awake rabbit using low-impedance metal microelectrodes. Efferent neurons were also activated by current pulses delivered near the soma [juxtasomal current pulses (JSCPs)] through the recording microelectrode. Action potentials generated by JSCPs were not directly observed (because of the stimulus artifact), but were inferred with the use of a collision paradigm. Efferent populations studied include callosal neurons [CC (n = 80)], ipsilateral corticocortical neurons [C-IC (n = 21)], corticothalamic neurons of layer 6 [CF-6 (n = 57)], and descending corticofugal neurons of layer 5 [CF-5, corticotectal neurons of the visual cortex (n = 48)]. 2. Most CC neurons (45/46) and all C-IC (8/8) and CF-6 neurons (39/39) were directly activated by JSCPs at near-threshold intensities. Some CF-5 neurons (9/38), however, showed evidence of indirect activation. All efferent classes had similar current thresholds (means 1.85-2.10 microA) to direct activation by JSCPs, and thresholds were inversely related to extracellular spike amplitude. For each neuron, the range of JSCP intensities that generated response probabilities of between 0.2 and 0.8 was measured, and this "range of uncertainty" was significantly greater in CF-5 neurons (mean 32.7% of threshold) than in CC (mean 19.0%) or CF-6 (mean 20.4%) neurons. 3. Several factors indicate that the threshold of efferent neurons to JSCPs is very sensitive to excitatory and inhibitory synaptic inputs. Iontophoretic applications of gamma-aminobutyric acid (GABA) increased the threshold to JSCPs, and glutamate reduced the threshold. Electrical stimulation of afferent pathways at intensities just below threshold for eliciting action potentials resulted in a dramatic decrease in JSCP threshold. This initial short-latency threshold decrease was specific to stimulation of particular afferent pathways and is thought to reflect excitability changes associated with EPSPs. Examination of such subliminal responses revealed subthreshold synaptic inputs that were not revealed by examination of all-or-none action potentials. In contrast to the specificity of the short-latency threshold decrease, a long-lasting increase in JSCP threshold was seen in virtually all neurons after stimulation of each of the afferent pathways tested. This increase in threshold usually began 20-40 ms after stimulation, lasted for 100-200 ms, and is thought to reflect excitability changes associated with a long-lasting inhibitory postsynaptic potential (IPSP) seen in many cortical neurons. 4. Many neurons in primary somatosensory cortex of rat, cat, and rabbit have no demonstrable receptive fields.(ABSTRACT TRUNCATED AT 400 WORDS)

Electrophysiological Classes of Cat Primary Visual Cortical Neurons In Vivo as Revealed by Quantitative Analyses

2003 ◽  
Vol 89 (3) ◽  
pp. 1541-1566 ◽  
Author(s):  
Lionel G. Nowak ◽  
Rony Azouz ◽  
Maria V. Sanchez-Vives ◽  
Charles M. Gray ◽  
David A. McCormick
Keyword(s):  
Short Duration ◽  
Cortical Neurons ◽  
Action Potentials ◽  
Low Frequency ◽  
Pyramidal Cells ◽  
Spike Frequency ◽  
Spike Frequency Adaptation ◽  
Frequency Adaptation ◽  
Layer 4

To facilitate the characterization of cortical neuronal function, the responses of cells in cat area 17 to intracellular injection of current pulses were quantitatively analyzed. A variety of response variables were used to separate the cells into subtypes using cluster analysis. Four main classes of neurons could be clearly distinguished: regular spiking (RS), fast spiking (FS), intrinsic bursting (IB), and chattering (CH). Each of these contained significant subclasses. RS neurons were characterized by trains of action potentials that exhibited spike frequency adaptation. Morphologically, these cells were spiny stellate cells in layer 4 and pyramidal cells in layers 2, 3, 5, and 6. FS neurons had short-duration action potentials (<0.5 ms at half height), little or no spike frequency adaptation, and a steep relationship between injected current intensity and spike discharge frequency. Morphologically, these cells were sparsely spiny or aspiny nonpyramidal cells. IB neurons typically generated a low frequency (<425 Hz) burst of spikes at the beginning of a depolarizing current pulse followed by a tonic train of action potentials for the remainder of the pulse. These cells were observed in all cortical layers, but were most abundant in layer 5. Finally, CH neurons generated repetitive, high-frequency (350–700 Hz) bursts of short-duration (<0.55 ms) action potentials. Morphologically, these cells were layer 2–4 (mainly layer 3) pyramidal or spiny stellate neurons. These results indicate that firing properties do not form a continuum and that cortical neurons are members of distinct electrophysiological classes and subclasses.

scholarly journals Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Balázs B Ujfalussy ◽  
Judit K Makara ◽  
Tiago Branco ◽  
Máté Lengyel
Keyword(s):  
Cortical Neurons ◽  
Activity Patterns ◽  
Pyramidal Cells ◽  
Cortical Circuits ◽  
Functional Link ◽  
Synaptic Inputs ◽  
Two Photon ◽  
Highly Nonlinear ◽  
Efficient Integration

Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.

scholarly journals 0017 Transmembrane TNF- Soluble TNF Receptor Reverse Signal to Induce a Wake-Like State in Vitro

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A7-A7
Author(s):  
C J Dykstra-Aiello ◽  
K Koh ◽  
J Nguyen ◽  
J M Krueger
Keyword(s):  
Cortical Neurons ◽  
Action Potentials ◽  
State Regulation ◽  
Electrode Arrays ◽  
Electrophysiological Properties ◽  
Reverse Signaling ◽  
Soluble Tnf Receptor ◽  
Induced Changes

Abstract Introduction Tumor necrosis factor (TNF) has sleep regulatory roles. Neuronal action potentials enhance TNF expression. Neuron/glia co-cultures exhibit more intense local sleep-like states after TNF administration in vitro. Both TNF and TNF receptors (Rs) are produced as transmembrane (tm) proteins that can subsequently be cleaved to produce soluble (s) forms. With immunocytes, sTNFR can bind tmTNF and induce reverse signaling within the cell expressing the tmTNF. This is opposite of conventional signaling induced by soluble ligands (e.g. sTNF) binding to transmembrane receptors. Having previously shown sleep inhibition after sTNFR administration in vivo, we hypothesized that tmTNF-sTNFR binding would induce wake-like states in vitro through reverse signaling. Methods Somatosensory cortical neurons/glia, from wildtype (WT) mice and mice lacking either TNF (TNF-KO) or both TNFRs (TNFR-KO), were co-cultured on multi-electrode arrays. Daily one-hour recordings were taken consecutively on incubation days 4 - 13 for development analyses. On day 14, a one-hour baseline was recorded prior to treatment with sTNFR (0.0 ng/μL-120 ng/μL). Immediately after treatment, recordings resumed for one hour. Synchronization of electrical activity (SYN), action potentials, slow wave power (SWP; 0.25–3.75 Hz), and burstiness index (measures used to define sleep in vivo) were used to characterize the ontological emergence of these electrophysiological properties and sTNFR-induced changes in vitro. Results Development rates were reduced in TNF-KO cells and increased in TNFR-KO cells relative to each other and to WT mice. Additionally, after sTNFR treatments, cells from TNFR-KO mice, which still express TNF, exhibited dose-dependent decreased SYN and SWP, indicative of a wake-like state. In contrast, cells from TNF-KO mice lacked a response to sTNFR treatment. Conclusion To our knowledge, this is the first demonstration of reverse TNF signaling with respect to sleep/wake states. As such, it provides a new way of viewing state regulation and associated potential clinical applications. Support This work was supported by grant NS096250 awarded to JK by NIH/NINDS.

scholarly journals Cortical neuron response selectivity derives from strength in numbers of synapses

2019 ◽  
Author(s):  
Benjamin Scholl ◽  
Connon I. Thomas ◽  
Melissa A. Ryan ◽  
Naomi Kamasawa ◽  
David Fitzpatrick
Keyword(s):  
Cortical Neuron ◽  
Cortical Neurons ◽  
Spatial Clustering ◽  
Supporting Evidence ◽  
Cortical Circuits ◽  
Synaptic Inputs ◽  
Synaptic Ultrastructure ◽  
Somatic Response ◽  
Neural Selectivity

AbstractSingle neocortical neurons are driven by populations of excitatory inputs, forming the basis of neural selectivity to features of sensory input. Excitatory connections are thought to mature during development through activity-dependent Hebbian plasticity1, whereby similarity between presynaptic and postsynaptic activity selectively strengthens some synapses and weakens others2. Evidence in support of this process ranges from measurements of synaptic ultrastructure to slice and in vivo physiology and imaging studies3,4,5,6,7,8. These corroborating lines of evidence lead to the prediction that a small number of strong synaptic inputs drive neural selectivity, while weak synaptic inputs are less correlated with the functional properties of somatic output and act to modulate activity overall6,7. Supporting evidence from cortical circuits, however, has been limited to measurements of neighboring, connected cell pairs, raising the question of whether this prediction holds for the full profile of synapses converging onto cortical neurons. Here we measure the strengths of functionally characterized excitatory inputs contacting single pyramidal neurons in ferret primary visual cortex (V1) by combining in vivo two-photon synaptic imaging and post hoc electron microscopy (EM). Using EM reconstruction of individual synapses as a metric of strength, we find no evidence that strong synapses play a predominant role in the selectivity of cortical neuron responses to visual stimuli. Instead, selectivity appears to arise from the total number of synapses activated by different stimuli. Moreover, spatial clustering of co-active inputs, thought to amplify synaptic drive, appears reserved for weaker synapses, further enhancing the contribution of the large number of weak synapses to somatic response. Our results challenge the role of Hebbian mechanisms in shaping neuronal selectivity in cortical circuits, and suggest that selectivity reflects the co-activation of large populations of presynaptic neurons with similar properties and a mixture of strengths.

scholarly journals Synaptic diversity naturally arises from neural decoding of heterogeneous populations

2021 ◽  
Author(s):  
Jacob L. Yates ◽  
Benjamin Scholl
Keyword(s):  
Dendritic Spines ◽  
Cortical Neurons ◽  
In Silico ◽  
Excitatory Synapses ◽  
Neural Decoding ◽  
Functional Heterogeneity ◽  
Synaptic Inputs ◽  
Population Codes ◽  
Optimal Decoding

Abstract The synaptic inputs to single cortical neurons exhibit substantial diversity in their sensory-driven activity. What this diversity reflects is unclear, and appears counter-productive in generating selective somatic responses to specific stimuli. We propose that synaptic diversity arises because neurons decode information from upstream populations. Focusing on a single sensory variable, orientation, we construct a probabilistic decoder that estimates the stimulus orientation from the responses of a realistic, hypothetical input population of neurons. We provide a straightforward mapping from the decoder weights to real excitatory synapses, and find that optimal decoding requires diverse input weights. Analytically derived weights exhibit diversity whenever upstream input populations consist of noisy, correlated, and heterogeneous neurons, as is typically found in vivo. In fact, in silico weight diversity was necessary to accurately decode orientation and matched the functional heterogeneity of dendritic spines imaged in vivo. Our results indicate that synaptic diversity is a necessary component of information transmission and reframes studies of connectivity through the lens of probabilistic population codes. These results suggest that the mapping from synaptic inputs to somatic selectivity may not be directly interpretable without considering input covariance and highlights the importance of population codes in pursuit of the cortical connectome.

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