Neural Circuit Dynamics
September 13-20, 2025
Director: Gyorgy Buzsaki
New York University, USA
Co-Director: Michael Hausser
University College London, UK
Faculty:
Sonja Hofer, University College, London, UK
Itzhak Fried, University of California, Los Angeles, USA
Kenneth Harris, University College, London, UK
Massimo Scanziani, University of California, San Francisco, USA
Rosa Cossart, INSERM, Marseille, France
Gyorgy Buzsaki, New York University, USA
Michael Hausser, University College, London, UK
The Decade of the Brain, and subsequently the Brain Initiative, were primarily devoted to developing novel tools and providing new windows on brain function and disease. Spectacular progress has been made in various fields of neurotechnologies, and the movement recruited experts from different disciplines, from chemistry to math to AI. At the same time, there is growing recognition that science is not just the art of measuring the world and that cutting-edge techniques are necessary but not sufficient for a deeper understanding in neuroscience. Observations must be organized into coherent theories to allow further progress. Hence, a forum is needed to address overarching views and offer new theoretical frameworks to synthesize current knowledge and advance our thinking in new directions.
This Advanced Course will address novel directions in systems neuroscience research. While plenty of data will be discussed, the main emphasis will be on overarching hypotheses and theories, the relationship between experimentation and theory, and between fundamental neuroscience and treatments for disease. Accordingly, the faculty is drawn from a range of neuroscience fields, from action to perception, development to preconfigured and plastic adult brain, experimental design to mathematical frameworks, and animal experiments to clinical testing.
Overall, the Advanced Course will allow students and scholars to familiarize themselves with novel directions that should guide experimental design and interpretation of observations.
Gyorgy Buzsaki
Preconfigured brain dynamics
Communication in any system requires an ‘agreement’ (or cipher) between the sender and the receiver. Messages are discretized (such as words in a language) and separated by agreed symbols (e.g., punctuation). In the brain, such discretization is supported by the numerous network rhythms because most rhythms involve inhibition, which is a natural punctuation/separation mechanism. Message packaging and deciphering in the brain evolve not only in time but in neuronal space, due mainly to the slow propagation of spikes from structure to structure. These rhythm-based syntactical operations are well preserved throughout evolution and provide the basis for communication among brain systems and between brains, such as human language. Rhythm-supported communication mechanisms are preconfigured and, in principle, allow for generating infinite messages from preexisting cell assembly sequences. Thus, as an alternative to acquiring everything from scratch and increasing the complexity of neuronal dynamics with cumulative new learning, ‘matching’ between preexisting ‘lego-like’ neuronal sequence patterns and experience may be a better option for neuronal learning. AI-based on similar preconfigured dynamics may yield alternative solutions to the current limitations of artificial networks.
Sonja Hofer
Understanding local and distributed neural dynamics during neocortical information processing
Recent advances in imaging and recording techniques have revolutionized our ability to observe neural circuit dynamics during behaviour, yet translating these observations into coherent theoretical frameworks remains challenging. We use large-scale recordings of cell-type-specific neural population activity within and across neocortical areas together with targeted circuit manipulations, behavioural analysis, and different modelling approaches to extract fundamental principles of neocortical circuit function. The endeavour is to understand how sensory information is represented and processed in local and distributed neocortical neural circuits and this will be a major focus of presentation and discussion. Also, attention will be devoted to how information processing is shaped by experience, learning, our internal models of the world, and our expectations. How these experimental insights inform theoretical frameworks for understanding neural circuit dynamics and plasticity and how these processes support adaptive behaviour will also be topics of presentation and debate.
Kenneth Harris
Multidimensional structure of activity in identified cortical cell types
The cerebral cortex is comprised of hundreds of distinct cell types connected into a network that underpins cognition. To characterize the structure of activity in these cells, recordings from thousands of neurons simultaneously in the mouse visual cortex, followed by molecular analysis, have been used to characterize their fine subtypes. The findings will be the main focus of discussion: they have revealed that cortical cells differed in their coupling to three dominant modes of population activity. The first mode correlated with behavioural alertness, the second with a spontaneous sleep-like oscillation, and the third with the bursting of a particular inhibitory neuron class (Somatostatin-positive cells). Visual responses correlated primarily with the oscillatory dimension. Interestingly, a cell’s coupling to these dimensions could be predicted from its transcriptome in inhibitory but not excitatory neurons.
Rosa Cossart
Rewinding brain development to dissect cortical circuits
Development shapes adult cortical circuits in many ways, from the constraint of genetic programs to establishing the interaction between self-referenced representations and environmental signals in support of adaptive behaviour. The adaptation of cortical circuits to the external world results from the modifications of self-organized circuits constrained by genetic programs in response to activity-dependent adjustments that occur at critical turning points throughout the developmental trajectories of individual animals.
Central to this process is the cortical circuit’s ability to differentiate between internally generated and externally driven inputs, a function mediated by distinct circuits. We posit that these dedicated circuits emerge through a developmental process in which the brain learns to segregate self and non-self signals via its interactions with the body and the environment. Disruptions to this developmental trajectory, we argue, may underlie disorders like autism and schizophrenia, characterized by distorted world models. The presentations aim to unravel the emergence of functional cortical circuits during development. Through a synthesis of published and unpublished data, we highlight the dual influence of early developmental programming and ongoing interaction with environmental signals.
Michael Hausser
Illuminating causal links between neural circuit activity and behaviour.
Understanding the causal relationship between activity patterns in neural circuits and behaviour is one of the fundamental questions in systems neuroscience. Addressing this problem requires performing rapid and targeted interventions in ongoing neuronal activity at cellular resolution and with millisecond precision. I will describe the results of experiments using a powerful new “all-optical” strategy for interrogating neural circuits, which combines simultaneous two-photon imaging and two-photon optogenetics. This enables the activity of functionally characterized and genetically defined ensembles of neurons to be manipulated with sufficient temporal and spatial resolution to enable physiological patterns of network activity to be reproduced. We have used this approach to identify the lower bound for the perception of cortical activity, probe how the brain state influences the role of the cortex in perception, and provide causal tests of the role of hippocampal place cells in spatial navigation.