scholarly journals DEVELOPMENT OF FUNCTIONAL STATES AND HIERARCHICAL NETWORKS OF THE BRAIN

Author(s):  
A.S. Bazyan ◽  
eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Arthur-Ervin Avramiea ◽  
Richard Hardstone ◽  
Jan-Matthis Lueckmann ◽  
Jan Bím ◽  
Huibert D Mansvelder ◽  
...  

Understanding why identical stimuli give differing neuronal responses and percepts is a central challenge in research on attention and consciousness. Ongoing oscillations reflect functional states that bias processing of incoming signals through amplitude and phase. It is not known, however, whether the effect of phase or amplitude on stimulus processing depends on the long-term global dynamics of the networks generating the oscillations. Here, we show, using a computational model, that the ability of networks to regulate stimulus response based on pre-stimulus activity requires near-critical dynamics—a dynamical state that emerges from networks with balanced excitation and inhibition, and that is characterized by scale-free fluctuations. We also find that networks exhibiting critical oscillations produce differing responses to the largest range of stimulus intensities. Thus, the brain may bring its dynamics close to the critical state whenever such network versatility is required.


Author(s):  
Sanjukta Krishnagopal ◽  
Judith Lehnert ◽  
Winnie Poel ◽  
Anna Zakharova ◽  
Eckehard Schöll

We investigate complex synchronization patterns such as cluster synchronization and partial amplitude death in networks of coupled Stuart–Landau oscillators with fractal connectivities. The study of fractal or self-similar topology is motivated by the network of neurons in the brain. This fractal property is well represented in hierarchical networks, for which we present three different models. In addition, we introduce an analytical eigensolution method and provide a comprehensive picture of the interplay of network topology and the corresponding network dynamics, thus allowing us to predict the dynamics of arbitrarily large hierarchical networks simply by analysing small network motifs. We also show that oscillation death can be induced in these networks, even if the coupling is symmetric, contrary to previous understanding of oscillation death. Our results show that there is a direct correlation between topology and dynamics: hierarchical networks exhibit the corresponding hierarchical dynamics. This helps bridge the gap between mesoscale motifs and macroscopic networks. This article is part of the themed issue ‘Horizons of cybernetical physics’.


2018 ◽  
Vol 10 (3) ◽  
pp. 191-201 ◽  
Author(s):  
Ralph Adolphs ◽  
Daniel Andler

We defend a functionalist approach to emotion that begins by focusing on emotions as central states with causal connections to behavior and to other cognitive states. The approach brackets the conscious experience of emotion, lists plausible features that emotions exhibit, and argues that alternative schemes (e.g., focusing on feelings or on neurobiology as the starting point) are unpromising candidates. We conclude with the benefits of our approach: one can study emotions in animals; one can look in the brain for the implementation of specific features; and one ends up with an architecture of the mind in which emotions are fully accommodated through their relations to the rest of cognition. Our article focuses on arguing for this general approach; as such, it is an essay in the philosophy of emotion rather than in the psychology or neuroscience of emotion.


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