scholarly journals Synaptic input sequence discrimination on behavioral time-scales mediated by reaction-diffusion chemistry in dendrites

2017 ◽  
Author(s):  
Upinder Singh Bhalla
Keyword(s):  
Time Scales ◽  
Synaptic Input ◽  
Input Sequence ◽  
Reaction Diffusion ◽  
Neuronal Firing ◽  
Time Range ◽  
Event Prediction ◽  
Sequence Recognition ◽  
Spatio Temporal ◽  
Important Time

AbstractSequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that this selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models. Again, sequences were recognized, and local channel modulation on the length-scale of sequence input could elicit changes in neuronal firing. We predict that dendritic sequence-recognition zones occupy 5 to 20 microns and recognize time-intervals of 0.2 to 5s. We suggest that this mechanism provides highly parallel and selective neural computation in a functionally important time range.

scholarly journals Synaptic input sequence discrimination on behavioral timescales mediated by reaction-diffusion chemistry in dendrites

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Upinder Singh Bhalla
Keyword(s):  
Synaptic Input ◽  
Input Sequence ◽  
Reaction Diffusion ◽  
Neuronal Firing ◽  
Time Range ◽  
Channel Modulation ◽  
Event Prediction ◽  
Sequence Recognition ◽  
Spatio Temporal ◽  
Important Time

Sequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here, we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs. We incorporated biological detail using sequential synaptic input onto spines in morphologically, electrically, and chemically detailed pyramidal neuronal models based on rat data. Again, sequences were recognized, and local channel modulation downstream of putative sequence-triggered signaling could elicit changes in neuronal firing. We predict that dendritic sequence-recognition zones occupy 5 to 30 microns and recognize time-intervals of 0.2 to 5 s. We suggest that this mechanism provides highly parallel and selective neural computation in a functionally important time range.

scholarly journals Low-rate firing limit for neurons with axon, soma and dendrites driven by spatially distributed stochastic synapses

2019 ◽  
Author(s):  
Robert P. Gowers ◽  
Yulia Timofeeva ◽  
Magnus J. E. Richardson
Keyword(s):  
Firing Rate ◽  
Cell Body ◽  
Synaptic Input ◽  
Pyramidal Cells ◽  
Neuronal Firing ◽  
Level Crossing ◽  
Spatially Distributed ◽  
Spatio Temporal ◽  
Low Rate ◽  
Synaptic Drive

AbstractAnalytical forms for neuronal firing rates are important theoretical tools for the analysis of network states. Since the 1960s, the majority of approaches have treated neurons as being electrically compact and therefore isopotential. These approaches have yielded considerable insight into how single-cell properties affect network activity; however, many neuronal classes, such as cortical pyramidal cells, are electrically extended objects. Calculation of the complex flow of electrical activity driven by stochastic spatio-temporal synaptic input streams in these structures has presented a significant analytical challenge. Here we demonstrate that an extension of the level-crossing method of Rice, previously used for compact cells, provides a general framework for approximating the firing rate of neurons with spatial structure. Even for simple models, the analytical approximations derived demonstrate a surprising richness including: independence of the firing rate to the electrotonic length for certain models, but with a form distinct to the point-like leaky integrate-and-fire model; a non-monotonic dependence of the firing rate on the number of dendrites receiving synaptic drive; a significant effect of the axonal and somatic load on the firing rate; and the role that the trigger position on the axon for spike initiation has on firing properties. The approach necessitates only calculating first and second moments of the non-thresholded voltage and its rate of change in neuronal structures subject to spatio-temporal synaptic fluctuations. The combination of simplicity and generality promises a framework that can be built upon to incorporate increasing levels of biophysical detail and extend beyond the low-rate firing limit treated in this paper.Author summaryNeurons are extended cells with multiple branching dendrites, a cell body and an axon. In an active neuronal network, neurons receive vast numbers of incoming synaptic pulses throughout their dendrites and cell body that each exhibit significant variability in amplitude and arrival time. The resulting synaptic input causes voltage fluctuations throughout their structure that evolve in space and time. The dynamics of how these signals are integrated and how they ultimately trigger outgoing spikes have been modelled extensively since the late 1960s. However, until relatively recently the ma jority of the mathematical formulae describing how fluctuating synaptic drive triggers action potentials have been applicable only for small neurons with the dendritic and axonal structure ignored. This has been largely due to the mathematical complexity of including the effects of spatially distributed synaptic input. Here we show that in a physiologically relevant, low-firing-rate regime, an approximate, level-crossing approach can be used to provide an estimate for the neuronal firing rate even when the dendrites and axons are included. We illustrate this approach using basic neuronal morphologies that capture the fundamentals of neuronal structure. Though the models are simple, these preliminary results show that it is possible to obtain useful formulae that capture the effects of spatially distributed synaptic drive. The generality of these results suggests they will provide a mathematical framework for future studies that might require the structure of neurons to be taken into account, such as the effect of electrical fields or multiple synaptic input streams that target distinct spatial domains of cortical pyramidal cells.

scholarly journals Depositional setting and limiting factors of early Late Cretaceous glaucony formation: implications from Cenomanian glauconitic strata (Elbtal Group, Germany)

Facies ◽  
2021 ◽  
Vol 67 (3) ◽  
Author(s):  
Markus Wilmsen ◽  
Udita Bansal
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Time Scales ◽  
Late Cretaceous ◽  
Limiting Factors ◽  
High Accumulation ◽  
Spatio Temporal ◽  
Facies Types ◽  
Facies Succession ◽  
Early Late

AbstractCenomanian strata of the Elbtal Group (Saxony, eastern Germany) reflect a major global sea-level rise and contain, in certain intervals, a green authigenic clay mineral in abundance. Based on the integrated study of five new core sections, the environmental background and spatio-temporal patterns of these glauconitic strata are reconstructed and some general preconditions allegedly needed for glaucony formation are critically questioned. XRD analyses of green grains extracted from selected samples confirm their glauconitic mineralogy. Based on field observations as well as on the careful evaluation of litho- and microfacies, 12 glauconitc facies types (GFTs), broadly reflecting a proximal–distal gradient, have been identified, containing granular and matrix glaucony of exclusively intrasequential origin. When observed in stratigraphic succession, GFT-1 to GFT-12 commonly occur superimposed in transgressive cycles starting with the glauconitic basal conglomerates, followed up-section by glauconitic sandstones, sandy glauconitites, fine-grained, bioturbated, argillaceous and/or marly glauconitic sandstones; glauconitic argillaceous marls, glauconitic marlstones, and glauconitic calcareous nodules continue the retrogradational fining-upward trend. The vertical facies succession with upwards decreasing glaucony content demonstrates that the center of production and deposition of glaucony in the Cenomanian of Saxony was the nearshore zone. This time-transgressive glaucony depocenter tracks the regional onlap patterns of the Elbtal Group, shifting southeastwards during the Cenomanian 2nd-order sea-level rise. The substantial development of glaucony in the thick (60 m) uppermost Cenomanian Pennrich Formation, reflecting a tidal, shallow-marine, nearshore siliciclastic depositional system and temporally corresponding to only ~ 400 kyr, shows that glaucony formation occurred under wet, warm-temperate conditions, high accumulation rates and on rather short-term time scales. Our new integrated data thus indicate that environmental factors such as great water depth, cool temperatures, long time scales, and sediment starvation had no impact on early Late Cretaceous glaucony formation in Saxony, suggesting that the determining factors of ancient glaucony may be fundamentally different from recent conditions and revealing certain limitations of the uniformitarian approach.

scholarly journals Motility at the Origin of Life: Its Characterization and a Model

2014 ◽  
Vol 20 (1) ◽  
pp. 55-76 ◽  
Author(s):  
Tom Froese ◽  
Nathaniel Virgo ◽  
Takashi Ikegami
Keyword(s):  
Origin Of Life ◽  
Time Scales ◽  
Morphological Changes ◽  
Reaction Diffusion ◽  
Dissipative Structures ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Inclusive Approach ◽  
Intermediate Time ◽  
The Origin Of Life

Due to recent advances in synthetic biology and artificial life, the origin of life is currently a hot topic of research. We review the literature and argue that the two traditionally competing replicator-first and metabolism-first approaches are merging into one integrated theory of individuation and evolution. We contribute to the maturation of this more inclusive approach by highlighting some problematic assumptions that still lead to an ximpoverished conception of the phenomenon of life. In particular, we argue that the new consensus has so far failed to consider the relevance of intermediate time scales. We propose that an adequate theory of life must account for the fact that all living beings are situated in at least four distinct time scales, which are typically associated with metabolism, motility, development, and evolution. In this view, self-movement, adaptive behavior, and morphological changes could have already been present at the origin of life. In order to illustrate this possibility, we analyze a minimal model of lifelike phenomena, namely, of precarious, individuated, dissipative structures that can be found in simple reaction-diffusion systems. Based on our analysis, we suggest that processes on intermediate time scales could have already been operative in prebiotic systems. They may have facilitated and constrained changes occurring in the faster- and slower-paced time scales of chemical self-individuation and evolution by natural selection, respectively.

Multi-Head Spatio-Temporal Attention Mechanism for Urban Anomaly Event Prediction

2021 ◽  
Vol 5 (3) ◽  
pp. 1-21
Author(s):  
Huiqun Huang ◽  
Xi Yang ◽  
Suining He
Keyword(s):  
New York ◽  
Experimental Studies ◽  
Attention Mechanism ◽  
City Management ◽  
Temporal Attention ◽  
Spatial Correlations ◽  
Time Step ◽  
Event Prediction ◽  
Spatio Temporal ◽  
Prediction Approach

Timely forecasting the urban anomaly events in advance is of great importance to the city management and planning. However, anomaly event prediction is highly challenging due to the sparseness of data, geographic heterogeneity (e.g., complex spatial correlation, skewed spatial distribution of anomaly events and crowd flows), and the dynamic temporal dependencies. In this study, we propose M-STAP, a novel Multi-head Spatio-Temporal Attention Prediction approach to address the problem of multi-region urban anomaly event prediction. Specifically, M-STAP considers the problem from three main aspects: (1) extracting the spatial characteristics of the anomaly events in different regions, and the spatial correlations between anomaly events and crowd flows; (2) modeling the impacts of crowd flow dynamic of the most relevant regions in each time step on the anomaly events; and (3) employing attention mechanism to analyze the varying impacts of the historical anomaly events on the predicted data. We have conducted extensive experimental studies on the crowd flows and anomaly events data of New York City, Melbourne and Chicago. Our proposed model shows higher accuracy (41.91% improvement on average) in predicting multi-region anomaly events compared with the state-of-the-arts.

scholarly journals Differential Modulation of Synaptic Strength and Timing Regulate Synaptic Efficacy in a Motor Network

2011 ◽  
Vol 105 (1) ◽  
pp. 293-304 ◽  
Author(s):  
Bruce R. Johnson ◽  
Jessica M. Brown ◽  
Mark D. Kvarta ◽  
Jay Y. J. Lu ◽  
Lauren R. Schneider ◽  
...  
Keyword(s):  
Synaptic Input ◽  
Synaptic Strength ◽  
Neuronal Firing ◽  
Cycle Period ◽  
Cycle Frequency ◽  
Pyloric Network ◽  
Motor Network ◽  
Pyloric Dilator ◽  
Network Output ◽  
Firing Properties

Neuromodulators modify network output by altering neuronal firing properties and synaptic strength at multiple sites; however, the functional importance of each site is often unclear. We determined the importance of monoamine modulation of a single synapse for regulation of network cycle frequency in the oscillatory pyloric network of the lobster. The pacemaker kernel of the pyloric network receives only one chemical synaptic feedback, an inhibitory synapse from the lateral pyloric (LP) neuron to the pyloric dilator (PD) neurons, which can limit cycle frequency. We measured the effects of dopamine (DA), octopamine (Oct), and serotonin (5HT) on the strength of the LP→PD synapse and the ability of the modified synapse to regulate pyloric cycle frequency. DA and Oct strengthened, whereas 5HT weakened, LP→PD inhibition. Surprisingly, the DA-strengthened LP→PD synapse lost its ability to slow the pyloric oscillations, whereas the 5HT-weakened LP→PD synapse gained a greater influence on the oscillations. These results are explained by monoamine modulation of factors that determine the firing phase of the LP neuron in each cycle. DA acts via multiple mechanisms to phase-advance the LP neuron into the pacemaker's refractory period, where the strengthened synapse has little effect. In contrast, 5HT phase-delays LP activity into a region of greater pacemaker sensitivity to LP synaptic input. Only Oct enhanced LP regulation of cycle period simply by enhancing LP→PD synaptic strength. These results show that modulation of the strength and timing of a synaptic input can differentially affect the synapse's efficacy in the network.

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