Noisy Juxtacellular Stimulation<i>In Vivo</i>Leads to Reliable Spiking and Reveals High-Frequency Coding in Single Neurons

Doose, Jens; Doron, Guy; Brecht, Michael; Lindner, Benjamin

doi:10.1523/jneurosci.0787-16.2016

Cited by 26 publications

(31 citation statements)

References 49 publications

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“…We used juxtacellular current pulses to induce spikes in PYRs (Figure 2B; median gain = 23.2 Hz, median percent increase: 470%, N = 18). The juxtacellular stimulation protocol approached the limits (Doose et al, 2016) of experimentally evoked spike-time precision in PYRs in vivo (mean/median standard deviation of first spike latency after pulse onset = 13.0 ms). To validate that evoked presynaptic spikes were indeed decoupled from network drive, we assessed the degree of synchrony between the evoked spikes and the activity of other pyramidal cells.…”

Section: Resultsmentioning

confidence: 90%

Pyramidal Cell-Interneuron Circuit Architecture and Dynamics in Hippocampal Networks

English

McKenzie

Evans

et al. 2017

Neuron

224

304

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Summary Excitatory control of inhibitory neurons is poorly understood due to the difficulty of studying synaptic connectivity in vivo. We inferred such connectivity through analysis of spike timing and validated this inference using juxtacellular and optogenetic control of presynaptic spikes in behaving mice. We observed that neighboring CA1 neurons had stronger connections, and that superficial pyramidal cells projected more to deep interneurons. Connection probability and strength were skewed, with a minority of highly connected hubs. Divergent presynaptic connections led to synchrony between interneurons. Synchrony of convergent presynaptic inputs boosted postsynaptic drive. Presynaptic firing frequency was read out by postsynaptic neurons through short-term depression and facilitation, with individual pyramidal cells and interneurons displaying a diversity of spike transmission filters. Additionally, spike transmission was strongly modulated by prior spike timing of the postsynaptic cell. These results bridge anatomical structure with physiological function.

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Section: Resultsmentioning

confidence: 90%

Pyramidal Cell-Interneuron Circuit Architecture and Dynamics in Hippocampal Networks

English

McKenzie

Evans

et al. 2017

Neuron

224

304

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“…The precision is considerably higher than in previous experiments on cortical neurons exposed to strong sensory stimulation (e.g., Burac˘as et al 1998;Gabernet et al 2005;Kayser et al 2010). Spike time precision is comparable to that observed in vitro using lowpass filtered white noise current injections (jitter 1-2 ms) inducing highly reliable spike trains (Mainen and Sejnowski 1995), which is surprising given the increased background synaptic activity and membrane potential variability in vivo (see Doose et al 2016 for a theoretical analysis of nanostimulation-induced high-frequency spiking). The high precision of action potential induction with kurzpuls nanostimulation (jitter Ϸ 0.5 ms) does not require extreme current injections.…”

Section: Discussionmentioning

confidence: 50%

Temporally precise control of single-neuron spiking by juxtacellular nanostimulation

Stüttgen

Nonkes

Geis

et al. 2017

Journal of Neurophysiology

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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. 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.

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“…The development of juxtacellular stimulation has brought remarkable experimental opportunities, ranging from reliably evoking prescribed spike trains [50][51][52] to probing the role of a single neuron in the perception of sensory inputs and motor responses [2][3][4][5][6]. Recently, first attempts were made to model the behavioral responses to the stimulation of a single cortical neuron in rodents [25,26].…”

Section: Discussionmentioning

confidence: 99%

A network model of the barrel cortex combined with a differentiator detector reproduces features of the behavioral response to single-neuron stimulation

Bernardi

Doron

Brecht

et al. 2020

Preprint

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The stimulation of a single neuron in the rat somatosensory cortex can elicit a behavioral response. The probability of a behavioral response does not depend appreciably on the duration or intensity of a constant stimulation, whereas the response probability increases significantly upon injection of an irregular current. Biological mechanisms that can potentially suppress a constant input signal are present in the dynamics of both neurons and synapses and seem ideal candidates to explain these experimental findings. Here, we study a large network of integrate-and-fire neurons with several salient features of neuronal populations in the rat barrel cortex. The model includes cellular spike-frequency adaptation, experimentally constrained numbers and types of chemical synapses endowed with short-term plasticity, and gap junctions. Numerical simulations of this model indicate that cellular and synaptic adaptation mechanisms alone may not be sufficient to account for the experimental results if the local network activity is read out by an integrator. However, a differentiator circuit can detect the single-cell stimulation with a reliability that barely depends on the length or intensity of the stimulus, but that increases when an irregular signal is used. This finding is in accordance with the experimental results obtained for the stimulation of a regularly-spiking excitatory cell. Author summaryIt is widely assumed that only a large group of neurons can encode a stimulus or control behavior. This tenet of neuroscience has been challenged by experiments in which stimulating a single cortical neuron has had a measurable effect on an animal's behavior. Recently, theoretical studies have explored how a single-neuron stimulation could be detected in a large recurrent network. However, these studies missed essential biological mechanisms of cortical networks and are unable to explain more recent experiments in the barrel cortex. Here, to describe the stimulated brain area, we propose and study a network model endowed with many important biological features of the barrel cortex. Importantly, we also investigate different readout mechanisms, i.e. ways in which the stimulation effects can propagate to other brain areas. We show that a readout network which tracks rapid variations in the local network activity is in agreement with the experiments. Our model demonstrates a possible mechanism for how the stimulation of March 25, 2020 1/35 a single neuron translates into a signal at the population level, which is taken as a proxy of the animal's response. Our results illustrate the power of spiking neural networks to properly describe the effects of a single neuron's activity. Both the enormity of cortical networks -tens of thousands of neurons in the case of the somatosensory cortex [7] -and the apparent randomness of single-neuron spiking [8,9] have classically been evoked as arguments for population coding. If single spikes are unpredictable and noisy how can a few externally induced spikes lead to changes in behavior? On the ...

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Noisy Juxtacellular StimulationIn VivoLeads to Reliable Spiking and Reveals High-Frequency Coding in Single Neurons

Cited by 26 publications

References 49 publications

Pyramidal Cell-Interneuron Circuit Architecture and Dynamics in Hippocampal Networks

Pyramidal Cell-Interneuron Circuit Architecture and Dynamics in Hippocampal Networks

Temporally precise control of single-neuron spiking by juxtacellular nanostimulation

A network model of the barrel cortex combined with a differentiator detector reproduces features of the behavioral response to single-neuron stimulation

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