Topic: spontaneous activity

Daniel Levenstein discusses spontaneous activity in the hippocampus and cortex, especially during sleep, and its relationship to learning, memory and navigation. He explains how AI models can help investigate these dynamics, alongside questions about model systems, cognitive maps and the relationship between neuroscience experiments and theory.

The internal and external world is thought to be represented by distributed patterns of cortical activity. The emergence of these cortical representations over the course of development remains an unresolved question. In this talk, I share results from a series of recent studies combining theory and experiments in the cortex of the ferret, a species with a well-defined columnar organization and modular network of orientation-selective responses in visual cortex. I show that prior to the onset of structured sensory experience, endogenous mechanisms set up a highly organized cortical network str

Modern electrophysiological recordings simultaneously capture single-unit spiking activities of hundreds of neurons. These neurons exhibit highly complex coordination patterns. Where does this complexity stem from? One candidate is the ubiquitous heterogeneity in connectivity of local neural circuits. Studying neural network dynamics in the linearized regime and using tools from statistical field theory of disordered systems, we derive relations between structure and dynamics that are readily applicable to subsampled recordings of neural circuits: Measuring the statistics of pairwise covarianc

Predictive modeling and dimensionality reduction of functional neuroimaging data have provided rich information about the representations and functional architectures of the human brain. While these approaches have been effective in many cases, we will discuss how neglecting the internal dynamics of the brain (e.g., spontaneous activity, global dynamics, effective connectivity) and its underlying computational principles may hinder our progress in understanding and modeling brain functions. By reexamining evidence from our previous and ongoing work, we will propose new hypotheses and direction

To generate brain circuits that are both flexible and stable requires the coordination of powerful developmental mechanisms acting at different scales, including activity-dependent synaptic plasticity and changes in single neuron properties. The brain prepares to efficiently compute information and reliably generate behavior during early development without any prior sensory experience but through patterned spontaneous activity. After the onset of sensory experience, ongoing activity continues to modify sensory circuits, and plays an important functional role in the mature brain. Using quantit

In our everyday lives, we form connections and build up social networks that allow us to function successfully as individuals and as a society. Our social networks tend to include well-connected individuals who link us to other groups of people that we might otherwise have limited access to. In addition, we are more likely to befriend individuals who a) live nearby and b) have mutual friends. Interestingly, neurons tend to do the same…until development is perturbed. Just like social networks, neuronal networks require highly connected hubs to elicit efficient communication at minimal cost (you

Establishment of precise neuronal connectivity in the neocortex relies on activity-dependent circuit reorganization during postnatal development. In the mouse somatosensory cortex layer 4, barrels are arranged in one-to-one correspondence to whiskers on the face. Thalamocortical axon termini are clustered in the center of each barrel. The layer 4 spiny stellate neurons are located around the barrel edge, extend their dendrites primarily toward the barrel center, and make synapses with thalamocortical axons corresponding to a single whisker. These organized circuits are established during th

Synaptic inputs on cortical dendrites are organized with remarkable subcellular precision at the micron level. This organization emerges during early postnatal development through patterned spontaneous activity and manifests both locally where synapses with similar functional properties are clustered, and globally along the axis from dendrite to soma. Recent experiments reveal species-specific differences in the local and global synaptic organization in mouse, ferret and macaque visual cortex. I will present a computational framework that implements functional and structural plasticity from sp

Interacting with the environment to process sensory information, generate perceptions, and shape goal-directed behavior engages neural networks in brain areas with highly varied representations, ranging from unimodal sensory cortices to higher-order association areas. These networks form and undergo considerable and potentially area-specific refinement over development. However, recent work suggests a much greater degree of commonality in the functional organization of networks across such diverse cortical areas during early development. It is currently unknown whether this initially common st

The emergence of spontaneous activity in the form of synchronized bursting events (SBE) is considered to play a crucial role in activity-dependent development of neuronal networks. As inhibition matures, the spatiotemporal structure of activity becomes increasingly influenced by the balance between excitation and inhibition (E/I). Moreover, intricate interactions between excitatory (ENs) and inhibitory (INs) neurons may arise during their activity-dependent structural differentiation. However, how the resulting spatial embedding of INs and ENs in a network impacts on the spatiotemporal structu

Spontaneous activity in young ferrets (p22) is organised into modular, low-dimensional patterns across multiple cortical areas [1]. In the following two weeks (p22-43), these activity patterns undergo a transition similar in all areas, and show a gradual increase in dimensionality in most areas, suggesting an expansion of representational capacity [2]. However, it is unclear what the functional role of having low-dimensional activity patterns at the initial stage of development is, since one would expect the limited dimensionality to restrict representational learning. In this work, we investi

Brain circuits in mouse pups develop and mature extensively during the first few weeks of life. During early postnatal development, sensory cortices experience patterned spontaneous activity which is known to refine neural connectivity, preparing the animal to engage in sensorimotor tasks immediately upon ear and eye opening (∼P4 and ∼P15, respectively). In primary visual cortex (V1), spontaneous activity originates from two sources, from the retina relayed by thalamus and intrinsically generated in the cortex. Spontaneous events from these two sources have different spatiotemporal properties:

Spontaneous activity of neuron populations is often characterized by unique network events, ranging from sharp-wave ripples to slow propagating waves. One of the prominent examples of such network events is population bursting (Fig. 1a), robustly emerging in networks of primary neurons in vitro [1]. Population bursting is believed to depend on the genetic, single neuron, and network features. Typically, the events are characterized via several summary statistics and compared between observations [2]. Although changes in the burst morphology are frequently observed, they are much harder to quan