High-level brain functions, such as motor and cognitive behavior, rely on the concerted activity of neurons in networks. Neuronal networks consist of a wide array of cells types, each having a distinct morphology and functionality. Neurons communicate among them through complex voltage signaling mechanisms called spikes, which may or may not exhibit regular behavior along time. Yet, from chaos rises structure: neuronal networks are able to exhibit periodic oscillations emerging from their collective spiking activity, and disruption of this activity may result in diseases of the nervous system. Prominent among these oscillations is the theta band (4-10 Hz) rhythm, which is believed to form a temporal framework for information processing and transmission. How these oscillations emerge is still an open question. Studies in reduced prEnvironmental Protection Agencyrations show that the so-called principal cells exhibit a preference for theta-frequency subthreshold oscillatory activity (resonance) when they are forced with periodic inputs. This might suggest that the network theta oscillations are 'inherited' from this resonance. However, we have recently found that in behaving animals, the resonance observed at the network level requires the interaction between single-neuron and circuit properties in ways that are more complex than previously thought. In this project, the investigators will study the mechanisms underlying network resonance using a two-pronged approach: The US team will carry out detailed computational modeling, and the Israel team will perform experiments with behaving mice. This research is expected to generate a framework for describing and understanding network resonance and to lay mechanistic foundations for understanding brain oscillations in general. Therefore, the results of this work are expected to have implications for cognitive and motor function in both health and disease. The central hypothesis of this project is that the resonant behavior of spiking neurons in the theta frequency band (4-10 Hz) can be generated locally in various areas of the brain, and crucially depends on the interplay of the intrinsic properties of the participating neurons and the network connectivity. The investigators will test this hypothesis in hippocampal areas CA1 and CA3 and in the neocortex, regions in which the theta rhythm is prominent. While resonance in single neurons has been studied for almost three decades, the effect of the subthreshold oscillatory properties of neurons on shaping the dynamics of oscillatory networks has only recently become the focus of increasing experimental and theoretical attention. One reason for the sub vs. suprathreshold gap in our understanding is the lack of a theoretical framework that could provide the basis for a systematic study, is described in terms of the biophysics of neuronal systems, and is grounded in experimental results. This research is aimed at filling this void. By combining biophysically constrained computational modeling and in vivo experiments using multi-site/multi-color optogenetic manipulations, the investigators will construct the various plausible scenarios linking the intrinsic oscillatory properties of neurons to circuits and test them experimentally. In this way, causal relations will be established by interrogating these neuronal circuits both theoretically and in practice. This will contribute to the understanding of the neuronal circuits that underlie the generation of rhythmic oscillations in the hippocampus and the neocortex, which have implications for cognition and motor behavior. In addition, this research will contribute to the development of a theory of resonance and to the understanding of the interplay of oscillatory networks. Furthermore, the innovative tools that will be used in this project will pave the way for the development of hybrid computational-in vivo experimental tools reminiscent of the use of the dynamic clamp in vitro. A companion project is being funded by the US-Israel Binational Science Foundation (BSF).
|Effective start/end date||9/15/16 → 8/31/20|
- National Science Foundation