Linear-nonlinear cascades capture synaptic dynamics

Rossbroich, Julian; Trotter, Daniel; Beninger, John; Tóth, Katalin; Naud, Richard

doi:10.1371/journal.pcbi.1008013

Cited by 18 publications

(10 citation statements)

References 93 publications

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“…A wrong short-term plasticity model will therefore lead to a wrong connectivity in the circuit. Here, it will be interesting to see how a more expressive model of short-term plasticity [ 70 ] influences the optimal circuit structure. Finally, of course, our optimality assumption could be wrong to different degrees.…”

Section: Discussionmentioning

confidence: 99%

Optimizing interneuron circuits for compartment-specific feedback inhibition

Keijser

Sprekeler

2022

PLoS Comput Biol

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Cortical circuits process information by rich recurrent interactions between excitatory neurons and inhibitory interneurons. One of the prime functions of interneurons is to stabilize the circuit by feedback inhibition, but the level of specificity on which inhibitory feedback operates is not fully resolved. We hypothesized that inhibitory circuits could enable separate feedback control loops for different synaptic input streams, by means of specific feedback inhibition to different neuronal compartments. To investigate this hypothesis, we adopted an optimization approach. Leveraging recent advances in training spiking network models, we optimized the connectivity and short-term plasticity of interneuron circuits for compartment-specific feedback inhibition onto pyramidal neurons. Over the course of the optimization, the interneurons diversified into two classes that resembled parvalbumin (PV) and somatostatin (SST) expressing interneurons. Using simulations and mathematical analyses, we show that the resulting circuit can be understood as a neural decoder that inverts the nonlinear biophysical computations performed within the pyramidal cells. Our model provides a proof of concept for studying structure-function relations in cortical circuits by a combination of gradient-based optimization and biologically plausible phenomenological models.

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Section: Discussionmentioning

confidence: 99%

Optimizing interneuron circuits for compartment-specific feedback inhibition

Keijser

Sprekeler

2022

PLoS Comput Biol

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“…Therefore, these factors influence the interaction between the pre- and postsynaptic neurons which cannot be captured by the dynamics of STP solely. It was suggested that alternative models of plasticity with less biophysical constraints like generalized bilinear model [ 15 ] and linear-nonlinear cascade model [ 19 ] could provide more flexible representation of STP dynamics compared to the TM model. Despite such limitations, the conventional three-parameter TM model is sufficient to describe STP in many cases [ 12 ].…”

Section: Discussionmentioning

confidence: 99%

“…Ghanbari et al [ 15 , 18 ] also used a different GLM to directly estimate the STP dynamics, a model that can be considered as an alternative to the TM model. Rossbroich et al [ 19 ] introduced a new synaptic model which represents short-term dynamics by combining an exponential kernel with a non-linear readout function. The simplicity of this model enabled applying the concepts of STP in artificial neural networks to examine its role in learning.…”

Section: Introductionmentioning

confidence: 99%

Inferring stimulation induced short-term synaptic plasticity dynamics using novel dual optimization algorithm

et al. 2022

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Experimental evidence in both human and animal studies demonstrated that deep brain stimulation (DBS) can induce short-term synaptic plasticity (STP) in the stimulated nucleus. Given that DBS-induced STP may be connected to the therapeutic effects of DBS, we sought to develop a computational predictive model that infers the dynamics of STP in response to DBS at different frequencies. Existing methods for estimating STP–either model-based or model-free approaches–require access to pre-synaptic spiking activity. However, in the context of DBS, extracellular stimulation (e.g. DBS) can be used to elicit presynaptic activations directly. We present a model-based approach that integrates multiple individual frequencies of DBS-like electrical stimulation as pre-synaptic spikes and infers parameters of the Tsodyks-Markram (TM) model from post-synaptic currents of the stimulated nucleus. By distinguishing between the steady-state and transient responses of the TM model, we develop a novel dual optimization algorithm that infers the model parameters in two steps. First, the TM model parameters are calculated by integrating multiple frequencies of stimulation to estimate the steady state response of post-synaptic current through a closed-form analytical solution. The results of this step are utilized as the initial values for the second step in which a non-derivative optimization algorithm is used to track the transient response of the post-synaptic potential across different individual frequencies of stimulation. Moreover, in order to confirm the applicability of the method, we applied our algorithm–as a proof of concept–to empirical data recorded from acute rodent brain slices of the subthalamic nucleus (STN) during DBS-like stimulation to infer dynamics of STP for inhibitory synaptic inputs.

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“…These connections all show STF with frequency dependence (Milstein et al, 2015;Wierenga et al, 2005) arising from multi-vesicular release (Soares et al, 2019;Dürst et al, 2022). This suggests a preponderance of STF for inputs onto CA1, a trend that extends to other parts of the hippocampus (Salin et al, 1996;Toth et al, 2000;Rossbroich et al, 2021). CA1 pyramidal neurons then project to multiple targets, with many connections going to the subiculum.…”

Section: Differential Transmission Of Firing Patternsmentioning

confidence: 97%

Silences, spikes and bursts: Three‐part knot of the neural code

Friedenberger,

Harkin,

Tóth

et al. 2023

The Journal of Physiology

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When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym – bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high‐frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial. image

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Linear-nonlinear cascades capture synaptic dynamics

Cited by 18 publications

References 93 publications

Optimizing interneuron circuits for compartment-specific feedback inhibition

Optimizing interneuron circuits for compartment-specific feedback inhibition

Inferring stimulation induced short-term synaptic plasticity dynamics using novel dual optimization algorithm

Silences, spikes and bursts: Three‐part knot of the neural code

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