scholarly journals Facilitating the propagation of spiking activity in feedforward networks by including feedback

2019 ◽  
Author(s):  
Hedyeh Rezaei ◽  
Ad Aertsen ◽  
Arvind Kumar ◽  
Alireza Valizadeh

AbstractTransient oscillations in the network activity upon sensory stimulation have been reported in different sensory areas. These evoked oscillations are the generic response of networks of excitatory and inhibitory neurons (EI-networks) to a transient external input. Recently, it has been shown that this resonance property of EI-networks can be exploited for communication in modular neuronal networks by enabling the transmission of sequences of synchronous spike volleys (‘pulse packets’), despite the sparse and weak connectivity between the modules. The condition for successful transmission is that the pulse packet (PP) intervals match the period of the modules’ resonance frequency. Hence, the mechanism was termed communication through resonance (CTR). This mechanism has three sever constraints, though. First, it needs periodic trains of PPs, whereas single PPs fail to propagate. Second, the inter-PP interval needs to match the network resonance. Third, transmission is very slow, because in each module, the network resonance needs to build-up over multiple oscillation cycles. Here, we show that, by adding appropriate feedback connections to the network, the CTR mechanism can be improved and the aforementioned constraints relaxed. Specifically, we show that adding feedback connections between two upstream modules, called the resonance pair, in an otherwise feedforward modular network can support successful propagation of a single PP throughout the entire network. The key condition for successful transmission is that the sum of the forward and backward delays in the resonance pair matches the resonance frequency of the network modules. The transmission is much faster, by more than a factor of two, than in the original CTR mechanism. Moreover, it distinctly lowers the threshold for successful communication by synchronous spiking in modular networks of weakly coupled networks. Thus, our results suggest a new functional role of bidirectional connectivity for the communication in cortical area networks.Author summaryThe cortex is organized as a modular system, with the modules (cortical areas) communicating via weak long-range connections. It has been suggested that the intrinsic resonance properties of population activities in these areas might contribute to enabling successful communication. A module’s intrinsic resonance appears in the damped oscillatory response to an incoming spike volley, enabling successful communication during the peaks of the oscillation. Such communication can be exploited in feedforward networks, provided the participating networks have similar resonance frequencies. This, however, is not necessarily true for cortical networks. Moreover, the communication is slow, as it takes several oscillation cycles to build up the response in the downstream network. Also, only periodic trains of spikes volleys (and not single volleys) with matching intervals can propagate. Here, we present a novel mechanism that alleviates these shortcomings and enables propagation of synchronous spiking across weakly connected networks with not necessarily identical resonance frequencies. In this framework, an individual spike volley can propagate by local amplification through reverberation in a loop between two successive networks, connected by feedforward and feedback connections: the resonance pair. This overcomes the need for activity build-up in downstream networks, causing the volley to propagate distinctly faster and more reliably.

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Chang-geng Song ◽  
Xin Kang ◽  
Fang Yang ◽  
Wan-qing Du ◽  
Jia-jia Zhang ◽  
...  

Abstract In mature mammalian brains, the endocannabinoid system (ECS) plays an important role in the regulation of synaptic plasticity and the functioning of neural networks. Besides, the ECS also contributes to the neurodevelopment of the central nervous system. Due to the increase in the medical and recreational use of cannabis, it is inevitable and essential to elaborate the roles of the ECS on neurodevelopment. GABAergic interneurons represent a group of inhibitory neurons that are vital in controlling neural network activity. However, the role of the ECS in the neurodevelopment of GABAergic interneurons remains to be fully elucidated. In this review, we provide a brief introduction of the ECS and interneuron diversity. We focus on the process of interneuron development and the role of ECS in the modulation of interneuron development, from the expansion of the neural stem/progenitor cells to the migration, specification and maturation of interneurons. We further discuss the potential implications of the ECS and interneurons in the pathogenesis of neurological and psychiatric disorders, including epilepsy, schizophrenia, major depressive disorder and autism spectrum disorder.


2017 ◽  
Vol 17 (6) ◽  
pp. 925-937 ◽  
Author(s):  
Andrej Gosar

Abstract. The town of Idrija is located in an area with an increased seismic hazard in W Slovenia and is partly built on alluvial sediments or artificial mining and smelting deposits which can amplify seismic ground motion. There is a need to prepare a comprehensive seismic microzonation in the near future to support seismic hazard and risk assessment. To study the applicability of the microtremor horizontal-to-vertical spectral ratio (HVSR) method for this purpose, 70 free-field microtremor measurements were performed in a town area of 0.8 km2 with 50–200 m spacing between the points. The HVSR analysis has shown that it is possible to derive the sediments' resonance frequency at 48 points. With the remaining one third of the measurements, nearly flat HVSR curves were obtained, indicating a small or negligible impedance contrast with the seismological bedrock. The isofrequency (a range of 2.5–19.5 Hz) and the HVSR peak amplitude (a range of 3–6, with a few larger values) maps were prepared using the natural neighbor interpolation algorithm and compared with the geological map and the map of artificial deposits. Surprisingly no clear correlation was found between the distribution of resonance frequencies or peak amplitudes and the known extent of the supposed soft sediments or deposits. This can be explained by relatively well-compacted and rather stiff deposits and the complex geometry of sedimentary bodies. However, at several individual locations it was possible to correlate the shape and amplitude of the HVSR curve with the known geological structure and prominent site effects were established in different places. In given conditions (very limited free space and a high level of noise) it would be difficult to perform an active seismic refraction or MASW measurements to investigate the S-wave velocity profiles and the thickness of sediments in detail, which would be representative enough for microzonation purposes. The importance of the microtremor method is therefore even greater, because it enables a direct estimation of the resonance frequency without knowing the internal structure and physical properties of the shallow subsurface. The results of this study can be directly used in analyses of the possible occurrence of soil–structure resonance of individual buildings, including important cultural heritage mining and other structures protected by UNESCO. Another application of the derived free-field isofrequency map is to support soil classification according to the recent trends in building codes and to calibrate Vs profiles obtained from the microtremor array or geophysical measurements.


2021 ◽  
Vol 15 ◽  
Author(s):  
Lea Fritschi ◽  
Johanna Hedlund Lindmar ◽  
Florian Scheidl ◽  
Kerstin Lenk

According to the tripartite synapse model, astrocytes have a modulatory effect on neuronal signal transmission. More recently, astrocyte malfunction has been associated with psychiatric diseases such as schizophrenia. Several hypotheses have been proposed on the pathological mechanisms of astrocytes in schizophrenia. For example, post-mortem examinations have revealed a reduced astrocytic density in patients with schizophrenia. Another hypothesis suggests that disease symptoms are linked to an abnormality of glutamate transmission, which is also regulated by astrocytes (glutamate hypothesis of schizophrenia). Electrophysiological findings indicate a dispute over whether the disorder causes an increase or a decrease in neuronal and astrocytic activity. Moreover, there is no consensus as to which molecular pathways and network mechanisms are altered in schizophrenia. Computational models can aid the process in finding the underlying pathological malfunctions. The effect of astrocytes on the activity of neuron-astrocyte networks has been analysed with computational models. These can reproduce experimentally observed phenomena, such as astrocytic modulation of spike and burst signalling in neuron-astrocyte networks. Using an established computational neuron-astrocyte network model, we simulate experimental data of healthy and pathological networks by using different neuronal and astrocytic parameter configurations. In our simulations, the reduction of neuronal or astrocytic cell densities yields decreased glutamate levels and a statistically significant reduction in the network activity. Amplifications of the astrocytic ATP release toward postsynaptic terminals also reduced the network activity and resulted in temporarily increased glutamate levels. In contrast, reducing either the glutamate release or re-uptake in astrocytes resulted in higher network activities. Similarly, an increase in synaptic weights of excitatory or inhibitory neurons raises the excitability of individual cells and elevates the activation level of the network. To conclude, our simulations suggest that the impairment of both neurons and astrocytes disturbs the neuronal network activity in schizophrenia.


Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2207 ◽  
Author(s):  
Hai Wang ◽  
Bin Li ◽  
Yan Liu ◽  
Min Zhang ◽  
Wei Zhao ◽  
...  

This paper presents a piezoelectric vibration energy harvester (PVEH) with resonance frequencies shifted down by elastically supported masses. The added elastic supporters can diminish the equivalent stiffness of the whole structure, leading to an evident decline in the resonance frequency of the cantilever body. Meantime, a new resonant peak is generated in the lower frequency range. The resonant frequency of the proposed PVEH can be easily adjusted by replacing the rubber band of the elastic support. The constructed configuration is theoretically investigated and experimentally verified. Compared with the conventional cantilever, the proposed device achieved a 46% decrease in resonance frequency and 87% enhancement in output power.


2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Siqi Li ◽  
Shenglei Tian ◽  
Wei Li ◽  
Tie Yan ◽  
Fuqing Bi

In order to study the resonance characteristics of rock under harmonic excitation, two vibration models have been presented to estimate the natural frequency of rock encountered during the drilling. The first one is a developed single-DOF model which considers the properties and dimensions of the rock. The second one is a multi-DOF model based on the principle of least action. Subsequently, the modal characteristics, as well as the influence of excitation frequency, the mechanical properties, and dimensions of the rock on its resonance frequency, are analyzed by using FEM. Finally, the ultrasonic test on artificial sandstones and materials of drill tools are carried out indoor, and the FFT transform method is adopted to obtain their resonance frequencies. Based on the analysis undertaken, it can be concluded that the natural frequency of the rock increases with the change of vibration mode. For the same kind of rock, the resonance frequency is inversely proportional to mass, while for the different kinds of rocks, the mechanical parameters, such as density, elastic modulus, and Poisson’s ratio, determine the resonance frequency of the rock together. Besides, the shape of the rock is also one of the main factors affecting its resonance frequency. At last, the theoretical research results are further verified by ultrasonic tests.


2020 ◽  
Vol 14 ◽  
Author(s):  
Fred Shaffer ◽  
Zachary M. Meehan

Heart rate variability (HRV) represents fluctuations in the time intervals between successive heartbeats, which are termed interbeat intervals. HRV is an emergent property of complex cardiac-brain interactions and non-linear autonomic nervous system (ANS) processes. A healthy heart is not a metronome because it exhibits complex non-linear oscillations characterized by mathematical chaos. HRV biofeedback displays both heart rate and frequently, respiration, to individuals who can then adjust their physiology to improve affective, cognitive, and cardiovascular functioning. The central premise of the HRV biofeedback resonance frequency model is that the adult cardiorespiratory system has a fixed resonance frequency. Stimulation at rates near the resonance frequency produces large-amplitude blood pressure oscillations that can increase baroreflex sensitivity over time. The authors explain the rationale for the resonance frequency model and provide detailed instructions on how to monitor and assess the resonance frequency. They caution that patterns of physiological change must be compared across several breathing rates to evaluate candidate resonance frequencies. They describe how to fine-tune the resonance frequency following an initial assessment. Furthermore, the authors critically assess the minimum epochs required to measure key HRV indices, resonance frequency test-retest reliability, and whether rhythmic skeletal muscle tension can replace slow paced breathing in resonance frequency assessment.


1993 ◽  
Vol 04 (04) ◽  
pp. 359-379 ◽  
Author(s):  
HOWARD CARD

Selected examples are presented of recent advances, primarily from the U.S. and Canada, in analog circuits for relaxation networks. Relaxation networks having feedback connections exhibit potentially greater computational power per neuron than feedforward networks. They are also more poorly understood especially with respect to learning algorithms. Examples are described of analog circuits for (i) supervised learning in deterministic Boltzmann machines, (ii) unsupervised competitive learning and feature maps and (iii) networks with resistive grids for vision and audition tasks. We also discuss recent progress on in-circuit learning and synaptic weight storage mechanisms.


2018 ◽  
Vol 115 (13) ◽  
pp. E3017-E3025 ◽  
Author(s):  
James P. Roach ◽  
Aleksandra Pidde ◽  
Eitan Katz ◽  
Jiaxing Wu ◽  
Nicolette Ognjanovski ◽  
...  

Network oscillations across and within brain areas are critical for learning and performance of memory tasks. While a large amount of work has focused on the generation of neural oscillations, their effect on neuronal populations’ spiking activity and information encoding is less known. Here, we use computational modeling to demonstrate that a shift in resonance responses can interact with oscillating input to ensure that networks of neurons properly encode new information represented in external inputs to the weights of recurrent synaptic connections. Using a neuronal network model, we find that due to an input current-dependent shift in their resonance response, individual neurons in a network will arrange their phases of firing to represent varying strengths of their respective inputs. As networks encode information, neurons fire more synchronously, and this effect limits the extent to which further “learning” (in the form of changes in synaptic strength) can occur. We also demonstrate that sequential patterns of neuronal firing can be accurately stored in the network; these sequences are later reproduced without external input (in the context of subthreshold oscillations) in both the forward and reverse directions (as has been observed following learning in vivo). To test whether a similar mechanism could act in vivo, we show that periodic stimulation of hippocampal neurons coordinates network activity and functional connectivity in a frequency-dependent manner. We conclude that resonance with subthreshold oscillations provides a plausible network-level mechanism to accurately encode and retrieve information without overstrengthening connections between neurons.


2018 ◽  
Vol 284 ◽  
pp. 587-592 ◽  
Author(s):  
I.R. Kuzeev ◽  
E.A. Naumkin ◽  
S.A. Pankratiev ◽  
R.R. Tlyasheva

It was shown that the forced vibrations of objects on resonance frequencies could significantly change resistance of these objects to cyclic loads in a low-cycle loading range and decrease critical compression load under axial compression. We carried out a procedure of fatigue testing performance with simultaneous application of high-frequency vibrations. We developed and produced a device allowing carrying out testing aimed to check shape stability of cylindrical shells and their resistance to forced vibrations. Dependence of fatigue life capability within the low-cycle range on the frequency of applied forced vibrations in four harmonics of resonance frequency was experimentally determined. Fatigue life capability decreased by 1,6 times. Decrease of life capability particularly occurs on frequencies which are presumably connected with minimum in size elements of hierarchy of polycrystalline material structures. It was found out that the forced vibrations on resonance frequency contribute the increase of a number of vibrations, that leads to decrease of critical axial compression force value. Decrease can be by up to 40%. Experimental determination of critical load during application of vibrations allowed obtaining formula for adjusting factor calculation in the formula for permitted compression force calculation.


1996 ◽  
Vol 18 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Wenkang Qi ◽  
Wenwu Cao

Finite element method (FEA) has been used to calculate the thickness resonance frequency and electromechanical coupling coefficient kt for 2–2 piezocomposite transducers. The results are compared with that of the effective medium theory and also verified by experiments. It is shown that the predicted resonance frequencies from the effective medium theory and the unit cell modeling using FEA deviate from the experimental observations for composite systems with a ceramic aspect ratio (width/length) more than 0.4. For such systems, full size FEA modeling is required which can provide accurate predictions of the resonance frequency and thickness coupling constant kt.


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