Attractor dynamics

…with standard paradigms with limited dynamics. In the present work, we applied Switching Linear Dynamical Systems (SLDS), a framework that estimates a generative model of the data with both states and transitions like HMMs, to uncover the dynamics of threat processing during a continuous threat-of-s

…is realized in the temporal dynamics of perceptual population responses. Here, we use latent-space modeling and dynamical systems analysis to characterize activity across populations of simultaneously recorded neurons in a secondary auditory forebrain region of songbirds (European starlings), engaged in an expectation-cued song-syllable categorization task. We

…circuits, much work has emphasized how attractor dynamics generate reliable behavior through the convergence of a network to specialized activity patterns for specific decisions and actions1. Other work has emphasized how cortical activity exhibits variability across trials of a behavior, which could in principle support flexibility in actions2. Here, through multi-area calcium imaging and recurrent neural network models, we propose that cortical activity f

…formation and recruitment or intrinsic attractor dynamics. Additionally, it has been shown that overall hippocampal population activity reflects environmental novelty. However, a common neural basis supporting these two processes remains unknown. Furthermore, many memories contain overlapping features, and it remains to be established how specific memories are retrieved without interference in the hippocampus. We propose that both engram and attractor models hinge on l

…can produce orderly collective dynamics. Focusing on continuous-attractor networks, which model representations of continuous variables such as head direction and spatial location, we address the discrepancy between the symmetry required by these models and its apparent absence in mammalian neural recordings. Analysis of mouse head-direction cell tuning curves reveals significant heterogeneity that violates basic assumptions of c

Attractor dynamics are essential components of neural computation— they have given rise to elegant, interpretable models of population coding and working memory. Frequently, attractors are classified based on whether their invariant manifolds can represent discrete/continuous variables, with point attractors being an example of the former and ‘continuous attractors’ of the latter. Here we highlight that ‘learnability’ is another quality that may serve to differentiate neural dynamics while offering novel insight. Counterintuitively, good working memory does not necessarily imply that a well-de

To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation (1,2), but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation (3), we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through c

Continuous attractor networks support various cognitive functions yet the neuronal dynamics and circuits supporting these dynamics in vivo remain unclear. The HD circuit is a canonical example of such network and HD cells each fire for a specific direction of the animal’s head. In the anterodorsal nucleus of the thalamus (ADn), HD cells maintain their mutual coordination during sleep, when sensory inputs are virtually absent, supporting the view of an attractor-driven system. The rigid organization of HD cell activity in the ADN begs the question of the origin of these structured patterns. Th

Attractors play a key role in a wide range of processes including learning, memory, decision making and navigation. Due to recent innovations in recording methods, there is increasing evidence for the existence of attractor dynamics in the brain. Yet, our understanding of how these attractors emerge or disappear in a biological system is lacking. In vitro cultured cortical neurons have been used extensively as a realistic experimental tool to understand the underlying mechanisms in neuronal assemblies. One of the main characteristics of the activity of such networks are the spontaneous synchro

…We discovered that attractor dynamics could explain an array of initially puzzling MEC responses to virtual reality manipulations. This theoretical framewo

Recent theoretical work has proposed that hippocampus acts as a binding site for sensory stimuli and a task coordinate system, each represented in the entorhinal cortex. Since this coordinate system path-integrates, incoming sensory observations can be inferred rather than learned. Here, we show that (1) a similar mechanism can learn representations that predict actions rather than stimuli. This mechanism supports zero-shot action prediction – a significant departure from current theoretical frameworks for action-learning. (2) The learned representations resemble object-vector and landmark cel

…on Hebbian plasticity for storage and attractor dynamics for recall. In contrast, memory-augmented neural networks in machine learning commonly use a key-value mechanism to store and read out memories in a single step. Such augmented networks achieve impressive feats of memory compared to traditional variants, yet it remains unclear whether they can be implemented by biological systems. In our work, we bridge this gap by proposing a set of of biologically plausible three-fact

While temporal control is crucial for the generation of a wide range of sensorimotor tasks, its underlying mechanisms remain unclear. Like human speech, birdsong relies on a tight muscle coordination, and songbirds have proved to be an outstanding model to study the sequential pattern of neuronal activity encoding action timing. In male zebra finches, the premotor nucleus HVC is responsible for the precise control of song tempo. Current computational models of HVC rely on synfire chains, a purely feedforward network model that can account for HVC sequential activity. Synfire chains are however

…of neural activity along a continuous attractor. In the first portion of the talk, I will discuss our efforts to dissect the circuit mechanisms underlying a neural integrator from a rich array of anatomical, physiological, and perturbation expe

Regulation of information flow in the brain is critical for many forms of behavior. In the process of sensory based decision-making, decisions about future actions are held in memory until enacted, making them potentially vulnerable to distracting sensory input. Therefore, gating of information flow from sensory to motor areas could protect memory from interference during decision-making, but the underlying network mechanisms are not understood. I will present our recent experimental and modeling work describing how information flow from the sensory cortex can be gated by state-dependent front

Cortical circuits receive multiple inputs from upstream populations with non-overlapping stimulus tuning preferences. Both the feedforward and recurrent architectures of the receiving cortical layer will reflect this diverse input tuning. We study how population-wide neuronal variability propagates through a hierarchical cortical network receiving multiple, independent, tuned inputs. We present new analysis of in vivo neural data from the primate visual system showing that the number of latent variables (dimension) needed to describe population shared variability is smaller in V4 populations c