Neural
neural communication
The functional connectome across temporal scales
The view of human brain function has drastically shifted over the last decade, owing to the observation that the majority of brain activity is intrinsic rather than driven by external stimuli or cognitive demands. Specifically, all brain regions continuously communicate in spatiotemporally organized patterns that constitute the functional connectome, with consequences for cognition and behavior. In this talk, I will argue that another shift is underway, driven by new insights from synergistic interrogation of the functional connectome using different acquisition methods. The human functional connectome is typically investigated with functional magnetic resonance imaging (fMRI) that relies on the indirect hemodynamic signal, thereby emphasizing very slow connectivity across brain regions. Conversely, more recent methodological advances demonstrate that fast connectivity within the whole-brain connectome can be studied with real-time methods such as electroencephalography (EEG). Our findings show that combining fMRI with scalp or intracranial EEG in humans, especially when recorded concurrently, paints a rich picture of neural communication across the connectome. Specifically, the connectome comprises both fast, oscillation-based connectivity observable with EEG, as well as extremely slow processes best captured by fMRI. While the fast and slow processes share an important degree of spatial organization, these processes unfold in a temporally independent manner. Our observations suggest that fMRI and EEG may be envisaged as capturing distinct aspects of functional connectivity, rather than intermodal measurements of the same phenomenon. Infraslow fluctuation-based and rapid oscillation-based connectivity of various frequency bands constitute multiple dynamic trajectories through a shared state space of discrete connectome configurations. The multitude of flexible trajectories may concurrently enable functional connectivity across multiple independent sets of distributed brain regions.
Prof. Humphries reads from "The Spike" 📖
We see the last cookie in the box and think, can I take that? We reach a hand out. In the 2.1 seconds that this impulse travels through our brain, billions of neurons communicate with one another, sending blips of voltage through our sensory and motor regions. Neuroscientists call these blips “spikes.” Spikes enable us to do everything: talk, eat, run, see, plan, and decide. In The Spike, Mark Humphries takes readers on the epic journey of a spike through a single, brief reaction. In vivid language, Humphries tells the story of what happens in our brain, what we know about spikes, and what we still have left to understand about them. Drawing on decades of research in neuroscience, Humphries explores how spikes are born, how they are transmitted, and how they lead us to action. He dives into previously unanswered mysteries: Why are most neurons silent? What causes neurons to fire spikes spontaneously, without input from other neurons or the outside world? Why do most spikes fail to reach any destination? Humphries presents a new vision of the brain, one where fundamental computations are carried out by spontaneous spikes that predict what will happen in the world, helping us to perceive, decide, and react quickly enough for our survival. Traversing neuroscience’s expansive terrain, The Spike follows a single electrical response to illuminate how our extraordinary brains work.
Exploring feedforward and feedback communication between visual cortical areas with DLAG
Technological advances have increased the availability of recordings from large populations of neurons across multiple brain areas. Coupling these recordings with dimensionality reduction techniques, recent work has led to new proposals for how populations of neurons can send and receive signals selectively and flexibly. Advancement of these proposals depends, however, on untangling the bidirectional, parallel communication between neuronal populations. Because our current data analytic tools struggle to achieve this task, we have recently validated and presented a novel dimensionality reduction framework: DLAG, or Delayed Latents Across Groups. DLAG decomposes the time-varying activity in each area into within- and across-area latent variables. Across-area variables can be decomposed further into feedforward and feedback components using automatically estimated time delays. In this talk, I will review the DLAG framework. Then I will discuss new insights into the moment-by-moment nature of feedforward and feedback communication between visual cortical areas V1 and V2 of macaque monkeys. Overall, this work lays the foundation for dissecting the dynamic flow of signals across populations of neurons, and how it might change across brain areas and behavioral contexts.
Modeling multi-region neural communication during decision making with recurrent switching dynamical systems
COSYNE 2022
Modeling multi-region neural communication during decision making with recurrent switching dynamical systems
COSYNE 2022