Portraits of Communication in Neuronal Networks | Under which conditions can messages be exchanged?
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Researchers from the Bernstein Center Freiburg, and colleagues from Spain and Sweden, are proposing a new framework that combines three prominent explanatory models that have been proposed in recent years: synfire communication, communication through coherence, and communication through resonance. In particular, their study takes into account how the activity state of the networks these neuron groups are embedded in may influence the communication. Their conclusions have now been published in Nature Reviews Neuroscience .
Gerald Hahn at the Pompeu Fabra University, Barcelona, Ad Aertsen and Arvind Kumar from the Bernstein Center Freiburg, the latter now at the KTH Royal Institute of Technology, Stockholm, and colleagues have now reviewed these seemingly different mechanisms and proposed to join them into a single coherent framework, rooted in the theory of dynamical systems. "We think that our explanatory model can help us gain a better understanding as to how neuron populations interact, depending on their network activity state, and whether messages from a neuron group in Brain Area A can reach a neuron group in Brain Area B, or not," concludes Ad Aertsen.
Their central approach: „Communication within and across networks can be described by trajectories in a two-dimensional state space, spanned by the properties of the neuronal input activity. Such `state space portraits describe how this activity evolves as it propagates from one neuron group (the ´sender´) to the next (the ´receiver´)”, explains Arvind Kumar (see Figure above), before going into more detail. In this state space, a dividing line (the ´separatrix´) separates the space into two different regimes of neuronal inputs: those that can and those that cannot propagate from one group to the next. “Thus, the separatrix is the critical boundary, which decides whether communication will be successful or not,” summarizes Arvind Kumar.
The course of the separatrix is determined, amongst other things, by the size of the neuron groups, the numbers and strengths of synaptic connections between them, and other structural properties of the networks involved. “Now we considered how the activity states of the neuron groups influence the separatrix. Specifically, we considered the case when the neuron groups are rhythmically modulated by brain oscillations.” Such oscillations typically involve large populations of neurons, up to entire brain areas, and may be either slow (alpha or theta rhythms) or fast (gamma rhythm). The new approach also takes these network dynamics into account. It focuses on the question: How do different brain rhythms interact with each other and modify the separatrix and, hence, the communication between the networks?
"We looked into different cases. How does message transmission work when one network oscillates and the other does not, and vice versa? And what happens when both networks oscillate, either at the same frequency, or at different frequencies, and so on," explains Ad Aertsen. "We discovered that the oscillations result in a rhythmic shifting of the separatrix. If it shifts down, the area in which messages are transmitted grows and, hence, communication improves. If, by contrast, it shifts upwards, the area diminishes and communication is weakened", continues Arvind Kumar. “And the temporal pattern of the shifting is determined by the frequencies of the network oscillations and the phase relation between them.”
Importantly, the new synthesis sheds light on the complementary role of fast gamma oscillations and non-oscillatory but synchronized spike patterns in neuronal network communication. The framework also considers nested oscillations to be an important control mechanism for flexibly routing spiking signals in both allowing and preventing communication between specific networks. In these nested oscillations, a low-frequency rhythm modulates the power of high-frequency oscillations. Under certain conditions, slow oscillations can modulate the time required to establish faster oscillations, thereby regulating the communication between specific networks.
"Whether communication between networks is possible or not depends on many factors: whether the oscillations are fast or slow, the frequencies are similar or different, how the phases relate to one another, and so on. Our approach now allows us to make specific predictions in each of these cases", explains Arvind Kumar. And Ad Aertsen adds: "In a next step, these predictions could be tested experimentally. For example, optogenetic stimulation could be used to impose certain oscillations onto groups of neurons in different brain areas and, by using our model, we could predict if a message from one area could reach the other, or not".
Figure Legend
Summary phase portrait of neuronal communication. Phase portrait representation of different communication strategies, incorporating potential top-down mechanisms to control the flow of spiking activity through slow modulations and changes of excitability, and including the effect of synaptic plasticity, triggered by gamma oscillations.
Original publication
Hahn G, Ponce-Alvarez A, Deco G, Aertsen A, Kumar A (2018) Portraits of communication in neuronal networks. Nature Rev Neurosci.
Press release
Press release University of Freiburg (English)
Press release University of Freiburg (German)
Contact
Prof. em. Dr. Ad Aertsen
Faculty of Biology
Bernstein Center Freiburg
University Freiburg
Hansastraße 9a
D - 79104 Freiburg
Tel: +49 (761) 203 9550
E-mail: aertsen@biologie.uni-freiburg.de
Prof. Dr. Arvind Kumar
KTH Royal Institute of Technology
Dept. of Computational Science and Technology
Lindstedtsvagen 5
Stockholm, Sweden
Tel: +46 (8) 790 62 24
E-mail: arvkumar@kth.se