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Arseny Finkelstein

Tel Aviv University

June 17, 2026

From microcircuits to cortex-wide networks: connectivity and information-flow underlying goal-directed behavior

Regulation of information flow in neuronal circuits is fundamental to flexible, goal-directed behavior. In this talk, I will discuss how cortical circuits organize neural activity and connectivity across spatial scales, from local microcircuits to distributed cortex-wide networks. Using naturalistic multidirectional reaching in mice, combined with large-scale calcium imaging and causal connectivity mapping of >20,000,000 neuronal pairs, we identified connectivity motifs and population dynamics underlying goal-directed behavior. I will first describe the organizational principles of the motor cortex, where neurons are arranged into functional mini-columns with recurrent connectivity motifs linked to task-related activity, and discuss the potential computational advantages of this architecture. I will then show how these principles extend to larger spatial scales. Imaging ~1,000,000 neurons across 10 cortical regions revealed high-dimensional local population activity patterns alongside coordinated cortex-wide dynamics mediated by synchronized inter-areal communication. These distributed network dynamics supported high-dimensional representations of short-term memory for target location.  Together, these findings reveal how cortical networks are organized across spatial scales to support cognition.

Idan Segev

ELSC, The Hebrew Universityof Jerusalem

June 24, 2026

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VVTNS Sixth Season Closing Lecture

From Cajal’s Spines to Digital Neurons:

Connectomics View on Dendritic Computations​​

Dendritic spines are among the smallest structures in the brain, yet they hold some of the deepest clues to how neurons compute and store memories. In this lecture, I will revisit the classical question of spine biophysics in the new age of connectomics, where nanometer-resolution electron microscopy allows us to reconstruct whole neurons with thousands of synapses and spines. I will show how spine density, spine-neck resistance, and the irregular geometry of individual spines can shape local synaptic signals, generate fast voltage dynamics, influence excitatory/inhibitory gating, and affect communication between neighboring spines. I will then discuss how automated reconstruction pipelines and biophysical modeling now make it possible to build digital neurons at spine and synapse resolution, and how AI-based approaches, such as our new AI-based TwinProp algorithm, allow us to ask - and get answer - to a fundamental question: what can a neuron compute? I will end by claiming that we now enter a new age of connectomics that provides an essential constraint on understanding how synapses, neurons, and circuits perform their computational functions.

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