Periodic Reporting for period 1 - NeuralFieldTheoriES (Towards a neural field theory for spiking neuron networks with electrical synapses)
Berichtszeitraum: 2022-01-17 bis 2024-01-16
The human brain is probably the most complex system we know. Tremendous efforts and progress in neuroscience research has been made since Hans Berger’s discovery of the alpha rhythm in 1924. But a central question remains unanswered: how do the billions of interacting neurons in our brain generate macroscopic phenomena such as the coherent steering of muscles in locomotion, grasping, pattern recognition, working memory or decision making? Experimental neuroscience has provided ample evidence that these brain functions—and their pathological dysfunction—come along with characteristic neural activity patterns and brain rhythms. Neuronal synchrony is at the heart of perceiving and processing information as well as exchanging it across brain regions, which requires a careful balance of excitation (E) and inhibition (I). Disturbing the E-I balance can critically alter communication pathways and lead to, e.g. excessive beta-band oscillations in Parkinson’s disease or spatially propagating epileptic seizures in form of traveling waves. An increasing number of recent experimental findings point out that electrical synapses are ubiquitous across brain regions and species. Electrical synapses are broadly present between inhibitory neurons and widely believed to promote synchrony. They are therefore immediately implicated in the generation of brain rhythms, they directly affect the E-I balance and are thus critical for the functioning of our brain. But their overall functional role remains elusive, and how exactly they interact with inhibitory synapses to generate oscillations is unknown. In this multidisciplinary project, we strive for providing a comprehensive picture how electrical synapses contribute to and shape large-scale brain dynamics. We will develop the mathematical mean-field theory that allows for a full mechanistic understanding of the neuronal and network mechanisms underlying the emergence of spatio-temporal structures in large networks of neurons with both chemical and electrical synapses. In particular, we will address three objectives: (a) Understand symmetry breaking in two populations of inhibitory neurons with electrical synapses. (b) Derive an exact neural field model for neurons with electrical synapses with realistic spatial connectivity. (c) Develop a novel canonical neural field model with excitation, inhibition and electrical synapses, and subsequently incorporate more degrees of biological realism.
Work was conducted via 6 work packages (WP):
WP1 focused on gaining a mechanistic understanding of how different spatial ranges of electrical and chemical synaptic connectivity shape neuronal activity patterns of integrate-and-fire neuron models. After an extensive literature review of neuroanatomic connectivity, the researcher performed numerical simulations and bifurcation analyses of various neuron models arranged in spatially-structured networks.
WP2 extended WP1 by studying pattern formation due to different spatial ranges of electrical and chemical connectivity. During a secondment at Vrije Universiteit Amsterdam, the researcher advanced numerical bifurcation analysis techniques to study emergent Turing patterns.
WP3 extended the Next-Generation Neural Field Model (NG-NFM) with electrical and chemical synapses, including additional degrees of biological realism. In various subprojects, the researcher established finite-dimensional descriptions for networks of spiking neurons, explored pulse shape-dependent synchronization, analyzed heterogeneous populations of Quadratic Integrate-and-Fire neurons, and incorporated spike-frequency adaptation.
WP4 centered on project management activities. The researcher executed the Career Development Plan, providing insights into career goals. Progress evaluations were conducted regularly, ensuring transparent reporting. Independently managing project finances, the researcher planned conferences and secondment stays efficiently. Active engagement in external collaborations expanded the project's scope. Administrative support facilitated integration into host and secondment institutions. The researcher showed collaborative and administrative prowess throughout WP4.
WP5 focused on training and career development. The researcher received individualized training on research objectives from host and secondment supervisors and by attending local seminars, scientific events, and tutorials. The researcher acted as an expert evaluator for scientific journals and organized scientific events, showcasing leadership and active public engagement.
WP6 centered on dissemination and communication. The researcher effectively disseminated research findings through 3 publications and 4 manuscripts in preparation, 9 talks at local seminars, and 14 presentations at international conferences and workshops, and engaged in social media and private websites.
The main results amount to:
1. The MSCA project identified and studied pattern formation mechanisms in neural networks, particularly focusing on the interplay between electrical and chemical synaptic connectivity.
2. The development of the NG-NFM extended the exact mean-field formalism for QIF neuron models, enabling a more systematic study of pattern formation in neural networks with structured chemical or electrical coupling.
3. The project successfully applied analytic and numerical bifurcation analysis to understand the dynamics of spiking neural networks, revealing mechanisms such as winner-take-all phenomena and spontaneous symmetry-breaking.
4. The results suggested potential implications for the role of electrical synapses in the brain, challenging existing assumptions and proposing novel targets for medical treatment in neurodegenerative disorders.
5. The Research Fellow actively engaged in training, evaluated scientific journals, organized conferences, and participated in ERC training sessions, contributing to personal and career development.
The MSCA project successfully advanced the understanding of neural network dynamics, proposed novel models, and engaged with the scientific community, while committing to transparency, open access, research integrity and accountability.
WP1 focused on gaining a mechanistic understanding of how different spatial ranges of electrical and chemical synaptic connectivity shape neuronal activity patterns of integrate-and-fire neuron models. After an extensive literature review of neuroanatomic connectivity, the researcher performed numerical simulations and bifurcation analyses of various neuron models arranged in spatially-structured networks.
WP2 extended WP1 by studying pattern formation due to different spatial ranges of electrical and chemical connectivity. During a secondment at Vrije Universiteit Amsterdam, the researcher advanced numerical bifurcation analysis techniques to study emergent Turing patterns.
WP3 extended the Next-Generation Neural Field Model (NG-NFM) with electrical and chemical synapses, including additional degrees of biological realism. In various subprojects, the researcher established finite-dimensional descriptions for networks of spiking neurons, explored pulse shape-dependent synchronization, analyzed heterogeneous populations of Quadratic Integrate-and-Fire neurons, and incorporated spike-frequency adaptation.
WP4 centered on project management activities. The researcher executed the Career Development Plan, providing insights into career goals. Progress evaluations were conducted regularly, ensuring transparent reporting. Independently managing project finances, the researcher planned conferences and secondment stays efficiently. Active engagement in external collaborations expanded the project's scope. Administrative support facilitated integration into host and secondment institutions. The researcher showed collaborative and administrative prowess throughout WP4.
WP5 focused on training and career development. The researcher received individualized training on research objectives from host and secondment supervisors and by attending local seminars, scientific events, and tutorials. The researcher acted as an expert evaluator for scientific journals and organized scientific events, showcasing leadership and active public engagement.
WP6 centered on dissemination and communication. The researcher effectively disseminated research findings through 3 publications and 4 manuscripts in preparation, 9 talks at local seminars, and 14 presentations at international conferences and workshops, and engaged in social media and private websites.
The main results amount to:
1. The MSCA project identified and studied pattern formation mechanisms in neural networks, particularly focusing on the interplay between electrical and chemical synaptic connectivity.
2. The development of the NG-NFM extended the exact mean-field formalism for QIF neuron models, enabling a more systematic study of pattern formation in neural networks with structured chemical or electrical coupling.
3. The project successfully applied analytic and numerical bifurcation analysis to understand the dynamics of spiking neural networks, revealing mechanisms such as winner-take-all phenomena and spontaneous symmetry-breaking.
4. The results suggested potential implications for the role of electrical synapses in the brain, challenging existing assumptions and proposing novel targets for medical treatment in neurodegenerative disorders.
5. The Research Fellow actively engaged in training, evaluated scientific journals, organized conferences, and participated in ERC training sessions, contributing to personal and career development.
The MSCA project successfully advanced the understanding of neural network dynamics, proposed novel models, and engaged with the scientific community, while committing to transparency, open access, research integrity and accountability.
The MSCA project has propelled neural field modeling into a new era by introducing the NG-NFM with structured synaptic connectivity. This groundbreaking approach surpasses conventional methods, promising unprecedented insights into the intricate dynamics of spiking neurons by exactly capturing the mean-field dynamics and pinpointing the role of electrical coupling for neural activity patterns.
Through analytic and numerical bifurcation analysis, the researcher identified the underlying mechanisms of pattern formation beyond Turing's ideas about long-range inhibition and short-range activation in reaction-diffusion systems. Electrical synapses as the microscopic substrate for diffusion, require a delicate balance between synaptic coupling strengths, external input, and heterogeneity (or noise) to provoke spontaneous symmetry breaking and induce spatially modulated activity patterns. The results promise a paradigm shift both in physics as well as in the neurosciences. As electrical synapses are expressed stronger in neurodegenerative diseases, they present a natural target for medical treatment to restore full functionality (e.g. for pattern, or action, selection) of critical inhibitory brain structures.
Through analytic and numerical bifurcation analysis, the researcher identified the underlying mechanisms of pattern formation beyond Turing's ideas about long-range inhibition and short-range activation in reaction-diffusion systems. Electrical synapses as the microscopic substrate for diffusion, require a delicate balance between synaptic coupling strengths, external input, and heterogeneity (or noise) to provoke spontaneous symmetry breaking and induce spatially modulated activity patterns. The results promise a paradigm shift both in physics as well as in the neurosciences. As electrical synapses are expressed stronger in neurodegenerative diseases, they present a natural target for medical treatment to restore full functionality (e.g. for pattern, or action, selection) of critical inhibitory brain structures.