scholarly journals Mechanisms underlying sharpening of visual response dynamics with familiarity

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Sukbin Lim
Keyword(s):  
Synaptic Plasticity ◽  
Negative Feedback ◽  
Visual Learning ◽  
Dynamics Analysis ◽  
Visual Response ◽  
Synaptic Connections ◽  
Cortical Circuits ◽  
Response Dynamics ◽  
Network Patterns ◽  
Firing Rate Adaptation

Experience-dependent modifications of synaptic connections are thought to change patterns of network activities and stimulus tuning with learning. However, only a few studies explored how synaptic plasticity shapes the response dynamics of cortical circuits. Here, we investigated the mechanism underlying sharpening of both stimulus selectivity and response dynamics with familiarity observed in monkey inferotemporal cortex. Broadening the distribution of activities and stronger oscillations in the response dynamics after learning provide evidence for synaptic plasticity in recurrent connections modifying the strength of positive feedback. Its interplay with slow negative feedback via firing rate adaptation is critical in sharpening response dynamics. Analysis of changes in temporal patterns also enables us to disentangle recurrent and feedforward synaptic plasticity and provides a measure for the strengths of recurrent synaptic plasticity. Overall, this work highlights the importance of analyzing changes in dynamics as well as network patterns to further reveal the mechanisms of visual learning.

scholarly journals Redundancy in synaptic connections enables neurons to learn optimally

2017 ◽  
Author(s):  
Naoki Hiratani ◽  
Tomoki Fukai
Keyword(s):  
Synaptic Plasticity ◽  
Particle Filtering ◽  
Neuron Model ◽  
Experimental Studies ◽  
Dendritic Tree ◽  
Spike Timing ◽  
Mammalian Brain ◽  
Synaptic Connections ◽  
Synaptic Organization ◽  
Functional Benefit

AbstractRecent experimental studies suggest that, in cortical microcircuits of the mammalian brain, the majority of neuron-to-neuron connections are realized by multiple synapses. However, it is not known whether such redundant synaptic connections provide any functional benefit. Here, we show that redundant synaptic connections enable near-optimal learning in cooperation with synaptic rewiring. By constructing a simple dendritic neuron model, we demonstrate that with multisynaptic connections, synaptic plasticity approximates a sample-based Bayesian filtering algorithm known as particle filtering, and wiring plasticity implements its resampling process. Applying the proposed framework to a detailed single neuron model, we show that the model accounts for many experimental observations, including the dendritic position dependence of spike-timing-dependent plasticity, and the functional synaptic organization on the dendritic tree based on the stimulus selectivity of presynaptic neurons. Our study provides a novel conceptual framework for synaptic plasticity and rewiring.

scholarly journals Synaptic plasticity onto inhibitory neurons as a mechanism for ocular dominance plasticity

2018 ◽  
Author(s):  
Jacopo Bono ◽  
Claudia Clopath
Keyword(s):  
Synaptic Plasticity ◽  
Critical Period ◽  
Ocular Dominance ◽  
Visual Deprivation ◽  
Inhibitory Neurons ◽  
Cortical Circuits ◽  
Ocular Dominance Plasticity ◽  
Opening And Closing ◽  
Recent Experimental Work ◽  
Cortical Maturation

AbstractOcular dominance plasticity is a well-documented phenomenon allowing us to study properties of cortical maturation. Understanding this maturation might be an important step towards unravelling how cortical circuits function. However, it is still not fully understood which mechanisms are responsible for the opening and closing of the critical period for ocular dominance and how changes in cortical responsiveness arise after visual deprivation. In this article, we present a theory of ocular dominance plasticity. Following recent experimental work, we propose a framework where a reduction in inhibition is necessary for ocular dominance plasticity in both juvenile and adult animals. In this framework, two ingredients are crucial to observe ocular dominance shifts: a sufficient level of inhibition as well as excitatory-to-inhibitory synaptic plasticity. In our model, the former is responsible for the opening of the critical period, while the latter limits the plasticity in adult animals. Finally, we also provide a possible explanation for the variability in ocular dominance shifts observed in individual neurons and for the counter-intuitive shifts towards the closed eye.

scholarly journals A GPCR negative feedback loop underlies efficient coding of external stimuli

2020 ◽  
Author(s):  
Rotem Ruach ◽  
Shai Yellinek ◽  
Eyal Itskovits ◽  
Alon Zaslaver
Keyword(s):  
Sensory Neurons ◽  
Negative Feedback ◽  
Feedback Inhibition ◽  
Essential Feature ◽  
Relevant Information ◽  
Complex Stimulus ◽  
Response Dynamics ◽  
Calcium Dependent ◽  
Spatio Temporal ◽  
External Stimuli

AbstractEfficient navigation based on chemical cues is an essential feature shared by all animals. These cues may be encountered in complex spatio-temporal patterns and with orders of magnitude varying intensities. Nevertheless, sensory neurons accurately extract the relevant information from such perplexing signals. Here, we show how a single sensory neuron in C. elegans worms can cell-autonomously encode complex stimulus patterns composed of instantaneous sharp changes and of slowly-changing continuous gradients. This encoding relies on a simple negative feedback in the GPCR signaling pathway in which TAX-6/Calcineurin plays a key role in mediating the feedback inhibition. Crucially, this negative feedback pathway supports several important coding features that underlie an efficient navigation strategy, including exact adaptation and adaptation to the magnitude of the gradient’s first derivative. A simple mathematical model accurately captured the fine neural dynamics of both wt and tax-6 mutant animals, further highlighting how the calcium-dependent activity of TAX-6/Calcineurin dictates GPCR inhibition and response dynamics. As GPCRs are ubiquitously expressed in all sensory neurons, this mechanism may be a universal solution for efficient cell-autonomous coding of external stimuli.

Long-Term Potentiation and Long-Term Depression

2018 ◽  
Author(s):  
Arianna Maffei
Keyword(s):  
Synaptic Plasticity ◽  
Neural Circuit ◽  
Long Term Potentiation ◽  
Synaptic Connections ◽  
Long Term Depression ◽  
Term Potentiation ◽  
Functional Implications ◽  
The Brain

Synaptic connections in the brain can change their strength in response to patterned activity. This ability of synapses is defined as synaptic plasticity. Long lasting forms of synaptic plasticity, long-term potentiation (LTP), and long-term depression (LTD), are thought to mediate the storage of information about stimuli or features of stimuli in a neural circuit. Since its discovery in the early 1970s, synaptic plasticity became a central subject of neuroscience, and many studies centered on understanding its mechanisms, as well as its functional implications.

scholarly journals Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics

2020 ◽  
Author(s):  
Michaël E Belloy ◽  
Jacob Billings ◽  
Anzar Abbas ◽  
Amrit Kashyap ◽  
Wen-Ju Pan ◽  
...  
Keyword(s):  
Reticular Formation ◽  
Visual Stimulation ◽  
Activity Patterns ◽  
Brain Dynamics ◽  
Brain State ◽  
Visual Response ◽  
Response Dynamics ◽  
Sensory Stimuli ◽  
Prominent Component ◽  
Global Brain

Abstract How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

scholarly journals Self-Tuning of Neural Circuits Through Short-Term Synaptic Plasticity

2007 ◽  
Vol 97 (6) ◽  
pp. 4079-4095 ◽  
Author(s):  
David Sussillo ◽  
Taro Toyoizumi ◽  
Wolfgang Maass
Keyword(s):  
Synaptic Plasticity ◽  
Activity Level ◽  
Cortical Circuits ◽  
Short Term ◽  
Cortical Networks ◽  
Short Term Plasticity ◽  
Numerous Experimental Data ◽  
Self Tuning ◽  
Synaptic Dynamics ◽  
Low Activity

Numerous experimental data show that cortical networks of neurons are not silent in the absence of external inputs, but rather maintain a low spontaneous firing activity. This aspect of cortical networks is likely to be important for their computational function, but is hard to reproduce in models of cortical circuits of neurons because the low-activity regime is inherently unstable. Here we show—through theoretical analysis and extensive computer simulations—that short-term synaptic plasticity endows models of cortical circuits with a remarkable stability in the low-activity regime. This short-term plasticity works as a homeostatic mechanism that stabilizes the overall activity level in spite of drastic changes in external inputs and internal circuit properties, while preserving reliable transient responses to signals. The contribution of synaptic dynamics to this stability can be predicted on the basis of general principles from control theory.

scholarly journals Crosstalk between biochemical signaling and trafficking determines AMPAR dynamics in synaptic plasticity

2021 ◽  
Author(s):  
Miriam Bell ◽  
Padmini Rangamani
Keyword(s):  
Synaptic Plasticity ◽  
Differential Equations ◽  
Network Architecture ◽  
Synaptic Weight ◽  
Synaptic Connections ◽  
Number Density ◽  
Structural Components ◽  
Synaptic Site ◽  
Signaling Model ◽  
Signaling Dynamics

Synaptic plasticity involves the modification of both biochemical and structural components of neurons. Many studies have revealed that the change in the number density of the glutamatergic receptor AMPAR at the synapse is proportional to synaptic weight update; increase in AMPAR corresponds to strengthening of synapses while decrease in AMPAR density weakens synaptic connections. The dynamics of AMPAR are thought to be regulated by upstream signaling, primarily the calcium-CaMKII pathway, trafficking to and from the synapse, and influx from extrasynaptic sources. Here, we have developed a set of models using compartmental ordinary differential equations to systematically investigate contributions of signaling and trafficking variations on AMPAR dynamics at the synaptic site. We find that the model properties including network architecture and parameters significantly affect the integration of fast upstream species by slower downstream species. Furthermore, we predict that the model outcome, as determined by bound AMPAR at the synaptic site, depends on (a) the choice of signaling model (bistable CaMKII or monostable CaMKII dynamics), (b) trafficking versus influx contributions, and (c) frequency of stimulus. Therefore, AMPAR dynamics can have unexpected dependencies when upstream signaling dynamics (such as CaMKII and PP1) are coupled with trafficking modalities.

scholarly journals Overlaid positive and negative feedback loops shape dynamical properties of PhoPQ two-component system

2021 ◽  
Vol 17 (1) ◽  
pp. e1008130
Author(s):  
Satyajit D Rao ◽  
Oleg A Igoshin
Keyword(s):  
Steady State ◽  
Negative Feedback ◽  
Positive Feedback ◽  
Feedback Loops ◽  
General Mechanism ◽  
Response Dynamics ◽  
Negative Feedback Loops ◽  
Two Component ◽  
Positive And Negative Feedback ◽  
Dynamical Properties

Bacteria use two-component systems (TCSs) to sense environmental conditions and change gene expression in response to those conditions. To amplify cellular responses, many bacterial TCSs are under positive feedback control, i.e. increase their expression when activated. Escherichia coli Mg2+ -sensing TCS, PhoPQ, in addition to the positive feedback, includes a negative feedback loop via the upregulation of the MgrB protein that inhibits PhoQ. How the interplay of these feedback loops shapes steady-state and dynamical responses of PhoPQ TCS to change in Mg2+ remains poorly understood. In particular, how the presence of MgrB feedback affects the robustness of PhoPQ response to overexpression of TCS is unclear. It is also unclear why the steady-state response to decreasing Mg2+ is biphasic, i.e. plateaus over a range of Mg2+ concentrations, and then increases again at growth-limiting Mg2+. In this study, we use mathematical modeling to identify potential mechanisms behind these experimentally observed dynamical properties. The results make experimentally testable predictions for the regime with response robustness and propose a novel explanation of biphasic response constraining the mechanisms for modulation of PhoQ activity by Mg2+ and MgrB. Finally, we show how the interplay of positive and negative feedback loops affects the network’s steady-state sensitivity and response dynamics. In the absence of MgrB feedback, the model predicts oscillations thereby suggesting a general mechanism of oscillatory or pulsatile dynamics in autoregulated TCSs. These results improve the understanding of TCS signaling and other networks with overlaid positive and negative feedback.

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