On the Role of Biophysical Properties of Cortical Neurons in Binding and Segmentation of Visual Scenes

1999 ◽  
Vol 11 (5) ◽  
pp. 1113-1138 ◽  
Author(s):  
Paul F. M. J. Verschure ◽  
Peter König
Keyword(s):  
Leakage Current ◽  
Cortical Neurons ◽  
Single Cells ◽  
Spatial Dimension ◽  
Differential Regulation ◽  
System Level ◽  
Biophysical Properties ◽  
Moving Stimulus ◽  
Context Dependent ◽  
Different Levels

Neuroscience is progressing vigorously, and knowledge at different levels of description is rapidly accumulating. To establish relationships between results found at these different levels is one of the central challenges. In this simulation study, we demonstrate how microscopic cellular properties, taking the example of the action of modulatory substances onto the membrane leakage current, can provide the basis for the perceptual functions reflected in the macroscopic behavior of a cortical network. In the first part, the action of the modulatory system on cortical dynamics is investigated. First, it is demonstrated that the inclusion of these biophysical properties in a model of the primary visual cortex leads to the dynamic formation of synchronously active neuronal assemblies reflecting a context-dependent binding and segmentation of image components. Second, it is shown that the differential regulation of the leakage current can be used to bias the interactions of multiple cortical modules. This allows the flexible use of different feature domains for scene segmentation. Third, we demonstrate how, within the proposed architecture, the mapping of a moving stimulus onto the spatial dimension of the network results in an increased speed of synchronization. In the second part, we demonstrate how the differential regulation of neuromodulatory activity can be achieved in a self-consistent system. Three different mechanisms are described and investigated. This study thus demonstrates how a modulatory system, affecting the biophysical properties of single cells, can be used to achieve context-dependent processing at the system level.

scholarly journals Aircraft Requirements for Sustainable Regional Aviation

Aerospace ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 61
Author(s):  
Dominik Eisenhut ◽  
Nicolas Moebs ◽  
Evert Windels ◽  
Dominique Bergmann ◽  
Ingmar Geiß ◽  
...  
Keyword(s):  
Systems Engineering ◽  
System Level ◽  
Policy Initiative ◽  
The European Union ◽  
Calculation Methods ◽  
Figures Of Merit ◽  
Performance Requirements ◽  
High Level ◽  
Different Levels ◽  
The Eu

Recently, the new Green Deal policy initiative was presented by the European Union. The EU aims to achieve a sustainable future and be the first climate-neutral continent by 2050. It targets all of the continent’s industries, meaning aviation must contribute to these changes as well. By employing a systems engineering approach, this high-level task can be split into different levels to get from the vision to the relevant system or product itself. Part of this iterative process involves the aircraft requirements, which make the goals more achievable on the system level and allow validation of whether the designed systems fulfill these requirements. Within this work, the top-level aircraft requirements (TLARs) for a hybrid-electric regional aircraft for up to 50 passengers are presented. Apart from performance requirements, other requirements, like environmental ones, are also included. To check whether these requirements are fulfilled, different reference missions were defined which challenge various extremes within the requirements. Furthermore, figures of merit are established, providing a way of validating and comparing different aircraft designs. The modular structure of these aircraft designs ensures the possibility of evaluating different architectures and adapting these figures if necessary. Moreover, different criteria can be accounted for, or their calculation methods or weighting can be changed.

scholarly journals Neural mechanisms of context-dependent segmentation tested on large-scale recording data

2021 ◽  
Author(s):  
Toshitake Asabuki ◽  
Tomoki Fukai
Keyword(s):  
Cortical Neurons ◽  
Large Scale ◽  
Neural Mechanism ◽  
Imaging Data ◽  
Unsupervised Segmentation ◽  
Spike Sequences ◽  
Multiple Cell ◽  
Context Dependent ◽  
Current Flows ◽  
The Given

The brain performs various cognitive functions by learning the spatiotemporal salient features of the environment. This learning likely requires unsupervised segmentation of hierarchically organized spike sequences, but the underlying neural mechanism is only poorly understood. Here, we show that a recurrent gated network of neurons with dendrites can context-dependently solve difficult segmentation tasks. Dendrites in this model learn to predict somatic responses in a self-supervising manner while recurrent connections learn a context-dependent gating of dendro-somatic current flows to minimize a prediction error. These connections select particular information suitable for the given context from input features redundantly learned by the dendrites. The model selectively learned salient segments in complex synthetic sequences. Furthermore, the model was also effective for detecting multiple cell assemblies repeating in large-scale calcium imaging data of more than 6,500 cortical neurons. Our results suggest that recurrent gating and dendrites are crucial for cortical learning of context-dependent segmentation tasks.

scholarly journals Electrophysiological and Transcriptomic Features Reveal a Circular Taxonomy of Cortical Neurons

2021 ◽  
Vol 15 ◽  
Author(s):  
Alejandro Rodríguez-Collado ◽  
Cristina Rueda
Keyword(s):  
Cortical Neurons ◽  
Cell Types ◽  
Mammalian Brain ◽  
Neuronal Dynamics ◽  
Electrophysiological Signals ◽  
Visual Cortex Neurons ◽  
Line Level ◽  
Mouse Visual Cortex ◽  
Different Levels

The complete understanding of the mammalian brain requires exact knowledge of the function of each neuron subpopulation composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological features is proposed. The approach is validated by analysing more than 1850 electrophysiological signals of different mouse visual cortex neurons proceeding from the Allen Cell Types database. The study is conducted on two different levels: neurons and their cell-type aggregation into Cre lines. At the neuronal level, electrophysiological features have been extracted with a promising model that has already proved its worth in neuronal dynamics. At the Cre line level, electrophysiological and transcriptomic features are joined on cell types with available genetic information. A taxonomy with a circular order is revealed by a simple transformation of the first two principal components that allow the characterization of the different Cre lines. Moreover, the proposed methodology locates other Cre lines in the taxonomy that do not have transcriptomic features available. Finally, the taxonomy is validated by Machine Learning methods which are able to discriminate the different neuron types with the proposed electrophysiological features.

scholarly journals Electrophysiological and Transcriptomic Features Reveal a Circular Taxonomy of Cortical Neurons

2021 ◽  
Author(s):  
Alejandro Rodríguez-Collado ◽  
Cristina Rueda
Keyword(s):  
Cortical Neurons ◽  
Cell Types ◽  
Mammalian Brain ◽  
Neuronal Dynamics ◽  
Electrophysiological Signals ◽  
Visual Cortex Neurons ◽  
Line Level ◽  
Mouse Visual Cortex ◽  
Different Levels

The complete understanding of the mammalian brain requires exact knowledge of the function of each of the neurons composing its parts. To achieve this goal, an exhaustive, precise, reproducible, and robust neuronal taxonomy should be defined. In this paper, a new circular taxonomy based on transcriptomic features and novel electrophysiological features is proposed. The approach is validated by analysing more than 1850 electrophysiological signals of different mouse visual cortex neurons proceeding from the Allen Cell Types Database. The study is conducted on two different levels: neurons and their cell-type aggregation into Cre Lines. At the neuronal level, electrophysiological features have been extracted with a promising model that has already proved its worth in neuronal dynamics. At the Cre Line level, electrophysiological and transcriptomic features are joined on cell types with available genetic information. A taxonomy with a circular order is revealed by a simple transformation of the first two principal components that allow the characterization of the different Cre Lines. Moreover, the proposed methodology locates other Cre Lines in the taxonomy that do not have transcriptomic features available. Finally, the taxonomy is validated by Machine Learning methods which are able to discriminate the different neuron types with the proposed electrophysiological features.

Buddhist Metaphors in the Diamond Sutra and the Heart Sutra

2018 ◽  
Author(s):  
Xiuping Gao ◽  
Chun Lan
Keyword(s):  
Cognitive Linguistics ◽  
Spatial Dimension ◽  
Space Time ◽  
Temporal Dimension ◽  
Buddhist Practice ◽  
Different Levels ◽  
Heart Sutra

This is a study of the metaphorical expressions in the Diamond Sutra and the Heart Sutra from the perspective of cognitive linguistics, with a special emphasis on five concepts, SPACE, TIME, LIFE, BUDDHIST PRACTICE and EMPTINESS. It is found that the Buddhist SPACE is AN UNSUBSTANTIAL EMPTINESS, structured along ten directions and filled with an immeasurable number of dusts, which in turn constitute an immeasurable number of SHI-JIE (WORLD) on four different levels. The Buddhist TIME follows the root TIME-AS-SPACE metaphor. The Buddhist LIFE, constrained along both the temporal dimension and the spatial dimension, is A CYCLIC JOURNEY IN THE WHEEL OF SIX PATHS. BUDDHIST PRACTICE is A JOURNEY FROM REINCARNATION TO NIRVANA. These metaphors help construct a Buddhist world which is distinct from but also related to the mundane world that we all dwell in.

Chaotic Balanced State in a Model of Cortical Circuits

1998 ◽  
Vol 10 (6) ◽  
pp. 1321-1371 ◽  
Author(s):  
C. van Vreeswijk ◽  
H. Sompolinsky
Keyword(s):  
Cortical Neurons ◽  
Initial Conditions ◽  
Single Cells ◽  
Network Size ◽  
Short Time Scale ◽  
Strong Nonlinearity ◽  
Large Network ◽  
Wide Range ◽  
The Mean

The nature and origin of the temporal irregularity in the electrical activity of cortical neurons in vivo are not well understood. We consider the hypothesis that this irregularity is due to a balance of excitatory and inhibitory currents into the cortical cells. We study a network model with excitatory and inhibitory populations of simple binary units. The internal feedback is mediated by relatively large synaptic strengths, so that the magnitude of the total excitatory and inhibitory feedback is much larger than the neuronal threshold. The connectivity is random and sparse. The mean number of connections per unit is large, though small compared to the total number of cells in the network. The network also receives a large, temporally regular input from external sources. We present an analytical solution of the mean-field theory of this model, which is exact in the limit of large network size. This theory reveals a new cooperative stationary state of large networks, which we term a balanced state. In this state, a balance between the excitatory and inhibitory inputs emerges dynamically for a wide range of parameters, resulting in a net input whose temporal fluctuations are of the same order as its mean. The internal synaptic inputs act as a strong negative feedback, which linearizes the population responses to the external drive despite the strong nonlinearity of the individual cells. This feedback also greatly stabilizes the system's state and enables it to track a time-dependent input on time scales much shorter than the time constant of a single cell. The spatiotemporal statistics of the balanced state are calculated. It is shown that the autocorrelations decay on a short time scale, yielding an approximate Poissonian temporal statistics. The activity levels of single cells are broadly distributed, and their distribution exhibits a skewed shape with a long power-law tail. The chaotic nature of the balanced state is revealed by showing that the evolution of the microscopic state of the network is extremely sensitive to small deviations in its initial conditions. The balanced state generated by the sparse, strong connections is an asynchronous chaotic state. It is accompanied by weak spatial cross-correlations, the strength of which vanishes in the limit of large network size. This is in contrast to the synchronized chaotic states exhibited by more conventional network models with high connectivity of weak synapses.

scholarly journals Anisomycin protects cortical neurons from prolonged hypoxia with differential regulation of p38 and ERK

2007 ◽  
Vol 1149 ◽  
pp. 76-86 ◽  
Author(s):  
Soon-Sun Hong ◽  
Hong Qian ◽  
Peng Zhao ◽  
Alia Bazzy-Asaad ◽  
Ying Xia
Keyword(s):  
Cortical Neurons ◽  
Differential Regulation

scholarly journals Comparing Cerebellar and Motor Cortical Activity in Reaching and Grasping

1993 ◽  
Vol 20 (S3) ◽  
pp. S53-S61 ◽  
Author(s):  
M. Smith Allan ◽  
Dugas Clause ◽  
Fortier Pierre ◽  
Kalasha John ◽  
Picard Nathalie
Keyword(s):  
Motor Cortex ◽  
Cortical Neurons ◽  
Grip Force ◽  
Single Cells ◽  
Receptive Fields ◽  
Movement Direction ◽  
Arm Reaching ◽  
Anticipatory Activity ◽  
Motor Strategies ◽  
Premotor Areas

ABSTRACT:The activity of single cells in the cerebellar and motor cortex of awake monkeys was recorded during separate studies of whole-arm reaching movements and during the application of force-pulse perturbations to handheld objects. Two general observations about the contribution of the cerebellum to the control of movement emerge from the data. The first, derived from the study of whole arm reaching, suggests that although both the motor cortex and cerebellum generate a signal related to movement direction, the cerebellar signal is less precise and varies from trial to trial even when the movement kinematics remain unchanged. The second observation, derived from the study of predictable perturbations of a hand-held object, indicates that cerebellar cortical neurons better reflect preparatory motor strategies formed from the anticipation of cutaneous and proprioceptive stimuli acquired by previous experience. In spite of strong relations to grip force and receptive fields stimulated by preparatory grip forces increase, the neurons of the percentral motor cortex showed very little anticipatory activity compared with either the premotor areas or the cerebellum.

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