Topic: behavioral states

Variations in brain states and behavioral profiles clearly influence neuronal activity in the visual cortex[1,2]. However, the mechanisms behind these influences and their consequent effect on sensory encoding remain to be determined. Here, we address this issue by analyzing simultaneous recordings of spiking activity and local field potentials (LFPs) from visual and subcortical regions of (N = 25) awake mice viewing a naturalistic movie. Applying a hidden Markov model (HMM) to cortical LFPs, we consistently identified three stable states in each mouse: a high-frequency state (dominated by gam

Recent studies in flies and rodents have shown that animals switch between a small number of ‘behavioral states’ during decision-making. However, the majority of studies infer these state switches only from behavioral measurements such as choices or movements. To provide greater insight into the internal processes that guide these switches, we developed a method for identifying state changes from behavioral measurements and neural responses. We applied this method to an evidence accumulation task studied in rats. Our method models trial-to-trial state switches with a hidden Markov model (HMM)

Recent technological advances allow us to measure large populations of neurons across multiple brain regions with millisecond precision and over extended periods while monitoring behavior. These data reveal that both behavior and neural dynamics change over minutes and hours, leading to different behavioral states at the level of single trials. However, many of the current methods and models for linking neural activity and behavior rely on trial-averaged data and often focus on one brain region, limiting our ability to causally link multiregional interactions to flexible behaviors that span sh

Comprehensive, continuous quantitative monitoring of intricately orchestrated physiological processes and behavioral states in living organisms provides an important tool for elucidating the function of neural circuits under healthy and diseased conditions, for defining the effects of potential drugs and treatments, and for monitoring disease progression and recovery. Here, we report a wireless, battery-free implantable device and a set of associated algorithms that enables continuous, multiparametric physio-behavioral monitoring in freely behaving small animals and interacting groups, through

Understanding the dynamic interplay between neuromodulatory systems and neuronal circuit dynamics is crucial for deciphering the underpinnings of complex behaviors. Noradrenergic signaling is widespread throughout the body and the brain and plays a pivotal role in the implementation of physiological processes and brain network configuration across arousal states. Yet, unraveling the causal relationship between norepinephrine release and concomitant neuronal dynamics poses a formidable challenge due to the intrinsic coupling of noradrenergic activity with behavioral changes.To resolve this conu

The ability to switch between different behaviors is essential to all animals’ survival. The selection of a behavior is guided by multiple factors, such as sensory inputs, internal states, and memory, which suggests that regions across the brain are involved in the decision to switch between them. While whole-brain information is necessary to investigate the neural basis of behavioral switching, brain-wide imaging in behaving mice has proved challenging so far. We employed functional Ultrasound imaging (fUS) to record large-scale neural dynamics in head-fixed mice while simultaneously tracking