scholarly journals Activity Dynamics and Signal Representation in Striatal Network Model with Distance-dependent Connectivity

2016 ◽  
Author(s):  
Sebastian Spreizer ◽  
Martin Angelhuber ◽  
Jyotika Bahuguna ◽  
Ad Aertsen ◽  
Arvind Kumar
Keyword(s):  
Network Model ◽  
Large Scale ◽  
Functional Characterization ◽  
Normal Function ◽  
Network Activity ◽  
Spatially Homogeneous ◽  
Main Input ◽  
Network States ◽  
External Stimuli ◽  
Activity Dynamics

AbstractStriatum is predominantly inhibitory and the main input nucleus of the basal ganglia. A functional characterization of its activity dynamics is crucial for understanding the mechanisms underlying phenomenon such as action selection and initiation. Here, we investigated the effects of the spatial connectivity structure on the emergence and maintenance of localized bumps of activity in large-scale striatal networks (~10,000 neurons). We show that in striatal network model in which the distance-dependent connection probability varies in a Gaussian fashion (Gaussian networks), the activity remains asynchronous irregular (AI) and spatially homogeneous, independent of the background input. By contrast, when the distance-dependent connectivity varies according to a Gamma distribution (Gamma networks), with short-range connectivity suppressed, a repertoire of activity dynamics can be observed: While weak background inputs induce spatially homogeneous AI activity, stronger background inputs induce stable, spatially localized activity bumps as in ‘winner-take-all’ (WTA) dynamics. Interestingly, for intermediate background inputs, the networks exhibit spatially localized, but unstable activity bumps (Transition Activity, TA), resembling the experimentally observed neuronal assembly dynamics in the striatum.Among the three main regimes of network activity (AI, WTA, TA) we found that in the AI and TA regimes, network dynamics are flexible and can be easily modified by external stimuli. Moreover, the dynamical state of the network returns to the baseline after the stimulus is removed. By contrast, the dynamics in the WTA state are rigid and can only be changed by very strong external stimuli. These results support the hypothesis that the flexibility of the striatal network state in response to stimuli is important for its normal function and the ‘rigid’ network states (WTA) correspond to brain disorders such as Parkinson’s disease, where the striatum looses its repertoire of dynamic states and is only receptive to very strong inputs.

scholarly journals Memory Replay in Balanced Recurrent Networks

2016 ◽  
Author(s):  
Nikolay Chenkov ◽  
Henning Sprekeler ◽  
Richard Kempter
Keyword(s):  
Large Scale ◽  
Neuronal Excitability ◽  
Activity Patterns ◽  
Recurrent Network ◽  
Network Activity ◽  
Sharp Waves ◽  
Sequence Of Events ◽  
Up States ◽  
Plausible Model ◽  
Network States

AbstractComplex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global—potentially neuromodulatory—alterations of neuronal excitability can switch between network states that favor retrieval and consolidation.Author SummarySynaptic plasticity is the basis for learning and memory, and many experiments indicate that memories are imprinted in synaptic connections. However, basic mechanisms of how such memories are retrieved and consolidated remain unclear. In particular, how can one-shot learning of a sequence of events achieve a sufficiently strong synaptic footprint to retrieve or replay this sequence? Using both numerical simulations of spiking neural networks and an analytic approach, we provide a biologically plausible model for understanding how minute synaptic changes in a recurrent network can nevertheless be retrieved by small cues or even manifest themselves as activity patterns that emerge spontaneously. We show how the retrieval of exceedingly small changes in the connections across assemblies is robustly facilitated by recurrent connectivity within assemblies. This interaction between recurrent amplification within an assembly and the feed-forward propagation of activity across the network establishes a basis for the retrieval of memories.

scholarly journals Interplay between periodic stimulation and GABAergic inhibition in striatal network oscillations

2016 ◽  
Author(s):  
Jovana J. Belić ◽  
Arvind Kumar ◽  
Jeanette Hellgren Kotaleski
Keyword(s):  
Large Scale ◽  
Medium Spiny Neuron ◽  
Network Activity ◽  
Exact Nature ◽  
Striatal Neurons ◽  
Cortical Oscillations ◽  
Large Scale Network ◽  
Scale Network ◽  
Fast Spiking ◽  
External Stimuli

AbstractThe network oscillations are ubiquitous across many brain regions. In the basal ganglia, oscillations are also present at many levels and a wide range of characteristic frequencies have been reported to occur during both health and disease.The striatum is the input nucleus of the basal ganglia that receives massive glutamatergic inputs from the cortex and is highly susceptible to cortical oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, periodic external stimuli propagate through the striatal circuitry. Using a large-scale network model of the striatum and corticostriatal projections, here we try to elucidate the importance of specific GABAergic neurons and their interactions in shaping striatal oscillatory activity. Our results show that fast-spiking interneurons, despite their uncorrelated firing, might have a crucial role in the emergence of high-frequency oscillations in the medium spiny neuron population, even if their activity is kept low. Rather, what matters is the firing time relative to just a few other neurons within an oscillation cycle. Finally, we show how the state of ongoing activity, the strengths of different types of inhibitions, the density of outgoing projections, and the overall activity of striatal cells influence network activity. These results suggest that the propagation of oscillatory inputs into the medium spiny neuron population is efficient, if indirect, through fast-spiking interneurons. Therefore, pharmaceuticals that target fast-spiking interneurons may provide a novel treatment for regaining the spectral characteristics of striatal activity that correspond to the healthy state.Author SummaryThe striatum is the largest and primary gateway component of the BG, receiving glutamatergic inputs from all cortical areas and is highly susceptible to cortical oscillations. However, there is limited knowledge about the exact nature of this routing process and therefore, it is of key importance to understand how time-dependent, external stimuli propagate through the striatal circuitry. The vast majority of striatal neurons, at least 95% of them, are medium spiny neurons (MSNs) that are also the only source of output from the nucleus. Two of the most examined sources of GABAergic inhibition into MSNs are the feedback inhibition (FB) from the axon collaterals of the MSNs themselves, and the feedforward inhibition (FF) via the small population of fast-spiking interneurons (FSIs) comprising roughly 1-2% of striatal neurons. Using a large-scale network model of the striatum we systematically investigate the propagation of asynchronous periodic cortical inputs, throughout the physiologically relevant range, onto the striatal neurons and their influence on striatal network dynamics. Our results show that FSIs, despite their firing being uncorrelated, may play a crucial role in the efficient propagation of external oscillations onto MSNs. Finally, we show how the state of ongoing activity, the strengths of different types of inhibitions, the density of outgoing projections, and the overall activity of striatal cells influence network activity.

Brain stem – from general view to computational model based on switchboard rules of operation

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Włodzisław Duch ◽  
Dariusz Mikołajewski
Keyword(s):  
Brain Stem ◽  
Large Scale ◽  
Ionic Channels ◽  
General View ◽  
The Central Nervous System ◽  
Network States ◽  
Large Scale Simulations ◽  
Influence Of Noise ◽  
The Brain ◽  
Sufficient Precision

Abstract Despite great progress in understanding the functions and structures of the central nervous system (CNS) the brain stem remains one of the least understood systems. We know that the brain stem acts as a decision station preparing the organism to act in a specific way, but such functions are rather difficult to model with sufficient precision to replicate experimental data due to the scarcity of data and complexity of large-scale simulations of brain stem structures. The approach proposed in this article retains some ideas of previous models, and provides more precise computational realization that enables qualitative interpretation of the functions played by different network states. Simulations are aimed primarily at the investigation of general switching mechanisms which may be executed in brain stem neural networks, as far as studying how the aforementioned mechanisms depend on basic neural network features: basic ionic channels, accommodation, and the influence of noise.

Cytochrome P450 mono-oxygenases in conifer genomes: discovery of members of the terpenoid oxygenase superfamily in spruce and pine

2006 ◽  
Vol 34 (6) ◽  
pp. 1209-1214 ◽  
Author(s):  
B. Hamberger ◽  
J. Bohlmann
Keyword(s):  
Cytochrome P450 ◽  
Loblolly Pine ◽  
Large Scale ◽  
Expressed Sequence Tag ◽  
Resin Acid ◽  
Functional Characterization ◽  
Structural Diversity ◽  
Resin Acids ◽  
Full Length Sequence ◽  
Diterpene Resin Acids

Diterpene resin acids, together with monoterpenes and sesquiterpenes, are the most prominent defence chemicals in conifers. These compounds belong to the large group of structurally diverse terpenoids formed by enzymes known as terpenoid synthases. CYPs (cytochrome P450-dependent mono-oxygenases) can further increase the structural diversity of these terpenoids. While most terpenoids are characterized as specialized or secondary metabolites, some terpenoids, such as the phytohormones GA (gibberellic acid), BRs (brassinosteroids) and ABA (abscisic acid), have essential functions in plant growth and development. To date, very few CYP genes involved in conifer terpenoid metabolism have been functionally characterized and were limited to two systems, yew (Taxus) and loblolly pine (Pinus taeda). The characterized yew CYP genes are involved in taxol diterpene biosynthesis, while the only characterized pine terpenoid CYP gene is part of DRA (diterpene resin acid) biosynthesis. These CYPs from yew and pine are members of two apparently conifer-specific CYP families within the larger CYP85 clan, one of four plant CYP multifamily clans. Other CYP families within the CYP85 clan were characterized from a variety of angiosperms with functions in terpenoid phytohormone metabolism of GA, BR, and ABA. The recent development of EST (expressed sequence tag) and FLcDNA (where FL is full-length) sequence databases and cDNA collections for species of two conifers, spruce (Picea) and pine, allows for the discovery of new terpenoid CYPs in gymnosperms by means of large-scale sequence mining, phylogenetic analysis and functional characterization. Here, we present a snapshot of conifer CYP data mining, discovery of new conifer CYPs in all but one family within the CYP85 clan, and suggestions for their functional characterization. This paper will focus on the discovery of conifer CYPs associated with diterpene metabolism and CYP with possible functions in the formation of GA, BR, and ABA in conifers.

scholarly journals Identification and functional characterization of two bamboo FD gene homologs having contrasting effects on shoot growth and flowering

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Smritikana Dutta ◽  
Anwesha Deb ◽  
Prasun Biswas ◽  
Sukanya Chakraborty ◽  
Suman Guha ◽  
...  
Keyword(s):  
Large Scale ◽  
Forest Ecology ◽  
Phylogenetic Analyses ◽  
Functional Characterization ◽  
Constitutive Expression ◽  
Transcript Level ◽  
In Planta ◽  
Mobility Shift ◽  
Vegetative Development ◽  
Sequence Comparisons

AbstractBamboos, member of the family Poaceae, represent many interesting features with respect to their fast and extended vegetative growth, unusual, yet divergent flowering time across species, and impact of sudden, large scale flowering on forest ecology. However, not many studies have been conducted at the molecular level to characterize important genes that regulate vegetative and flowering habit in bamboo. In this study, two bamboo FD genes, BtFD1 and BtFD2, which are members of the florigen activation complex (FAC) have been identified by sequence and phylogenetic analyses. Sequence comparisons identified one important amino acid, which was located in the DNA-binding basic region and was altered between BtFD1 and BtFD2 (Ala146 of BtFD1 vs. Leu100 of BtFD2). Electrophoretic mobility shift assay revealed that this alteration had resulted into ten times higher binding efficiency of BtFD1 than BtFD2 to its target ACGT motif present at the promoter of the APETALA1 gene. Expression analyses in different tissues and seasons indicated the involvement of BtFD1 in flower and vegetative development, while BtFD2 was very lowly expressed throughout all the tissues and conditions studied. Finally, a tenfold increase of the AtAP1 transcript level by p35S::BtFD1 Arabidopsis plants compared to wild type confirms a positively regulatory role of BtFD1 towards flowering. However, constitutive expression of BtFD1 had led to dwarfisms and apparent reduction in the length of flowering stalk and numbers of flowers/plant, whereas no visible phenotype was observed for BtFD2 overexpression. This signifies that timely expression of BtFD1 may be critical to perform its programmed developmental role in planta.

scholarly journals Image Classification Using Transfer Learning and Deep Learning

2021 ◽  
Vol 10 (9) ◽  
pp. 25394-25398
Author(s):  
Chitra Desai
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Image Classification ◽  
Transfer Learning ◽  
Network Model ◽  
Neural Network Model ◽  
Large Scale ◽  
Deep Neural Network ◽  
Visual Recognition ◽  
Classification Of Images

Deep learning models have demonstrated improved efficacy in image classification since the ImageNet Large Scale Visual Recognition Challenge started since 2010. Classification of images has further augmented in the field of computer vision with the dawn of transfer learning. To train a model on huge dataset demands huge computational resources and add a lot of cost to learning. Transfer learning allows to reduce on cost of learning and also help avoid reinventing the wheel. There are several pretrained models like VGG16, VGG19, ResNet50, Inceptionv3, EfficientNet etc which are widely used.   This paper demonstrates image classification using pretrained deep neural network model VGG16 which is trained on images from ImageNet dataset. After obtaining the convolutional base model, a new deep neural network model is built on top of it for image classification based on fully connected network. This classifier will use features extracted from the convolutional base model.

scholarly journals An Asymmetric Mechanism in a Symmetric Molecular Machine

2020 ◽  
Author(s):  
Florian Blanc ◽  
Marco Cecchini
Keyword(s):  
Free Energy ◽  
Large Scale ◽  
Technological Development ◽  
Thermal Fluctuations ◽  
Free Energy Calculations ◽  
Molecular Machine ◽  
Free Energy Surface ◽  
Promising Area ◽  
Sequential Mechanism ◽  
External Stimuli

The design of molecular architectures exhibiting functional motions is a promising area for disruptive technological development. Towards this goal, rotaxanes and catenanes, which undergo relative motions of their sub-units in response to external stimuli, are prime candidates. Here, we report on the computational analysis of the contraction/extension of a bistable [c2]-daisy chain rotaxane. Using free energy calculations and transition path optimizations, we explore the free energy landscape governing the functional motions of a prototypical molecular machine with atomic resolution.<br>The calculations reveal a sequential mechanism for contraction/extension in which the asynchronous gliding of each ring is preferred over the concerted movement suggested by chemical intuition. Analysis of the underlying free energy surface indicates that dissymmetric gliding is favored because it entails crossings of much smaller barriers.<br>Our findings illustrate an important design principle for molecular machines, namely that efficient exploitation of thermal fluctuations may be realized by breaking down the large-scale functional motions into smaller steps.

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