scholarly journals Satiety, Thermosensation and Mechanosensation Regulate a Spontaneous C. elegans Sleep State

2019 ◽  
Author(s):  
Daniel L. Gonzales ◽  
Jasmine Zhou ◽  
Jacob T. Robinson
Keyword(s):  
Neural Activity ◽  
Neural Circuits ◽  
Brain Activity ◽  
External Environment ◽  
State Transitions ◽  
Brain State ◽  
Behavioral State ◽  
Chemical Signaling ◽  
Whole Brain ◽  
C Elegans

AbstractOne remarkable feature of the nervous system is its ability to rapidly and spontaneously switch between activity states. In the extreme example of sleep, animals arrest locomotion, reduce their sensitivity to sensory stimuli, and dramatically alter their neural activity. Small organisms are useful models to better understand these sudden changes in neural states because we can simultaneously observe whole-brain activity, monitor behavior and precisely regulate the external environment. Here, we show a spontaneous sleep-like behavior in C. elegans that is associated with a distinct global-brain state and regulated by both the animal’s internal physiological state and input from multiple sensory circuits. Specifically, we found that when confined in microfluidic chambers, adult worms spontaneously transition between periods of normal activity and short quiescent bouts, with behavioral state transitions occurring every few minutes. This quiescent state, which we call μSleep, meets the behavioral requirements of C. elegans sleep, is dependent on known sleep-promoting neurons ALA and RIS, and is associated with a global down-regulation of neural activity. Consistent with prior studies of C. elegans sleep, we found that μSleep is regulated by satiety and temperature. In addition, we show for the first time that quiescence can be either driven or suppressed by thermosensory input, and that animal restraint induces quiescence through mechanosensory pathways. Together, these results establish a rich model system for studying how neural and behavioral state transitions are influenced by multiple physiological and environmental conditions.Significance StatementUnique brain states govern animal behaviors like sleep and wakefulness; however, how the brain regulates these dramatic state transitions is not well understood. Brain activity can be influenced by a complex interaction between sensory circuits that monitor the external environment, neural circuits that control behavior, and internal chemical signaling. Here, we describe a platform to study behavioral states in a context that allows us to record whole-brain activity while controlling the environment and monitoring animal behavior. Specifically, we identify a pattern of sleep bouts in the roundworm C. elegans that occur when they are confined to microscopic fluidic chambers. This behavior platform provides a powerful system to study how neural circuits interact with chemical signaling to drive brain state transitions.

scholarly journals Neuron ID dataset facilitates neuronal annotation for whole-brain activity imaging of C. elegans

BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Yu Toyoshima ◽  
Stephen Wu ◽  
Manami Kanamori ◽  
Hirofumi Sato ◽  
Moon Sun Jang ◽  
...  
Keyword(s):  
Brain Activity ◽  
Whole Brain ◽  
C Elegans

scholarly journals Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness

2021 ◽  
Vol 17 (7) ◽  
pp. e1009139
Author(s):  
Yonatan Sanz Perl ◽  
Carla Pallavicini ◽  
Ignacio Pérez Ipiña ◽  
Athena Demertzi ◽  
Vincent Bonhomme ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Relevant Information ◽  
Complete Characterization ◽  
Brain State ◽  
Whole Brain ◽  
Brain Injured ◽  
Level Of Consciousness ◽  
The Stability ◽  
Injured Patients

Consciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness. While the level of consciousness can be taken to describe the actual brain state, a complete characterization should also include its potential behavior against external perturbations. We developed and analyzed whole-brain computational models to show that the stability of conscious states provides information complementary to their similarity to conscious wakefulness. Our work leads to a novel methodological framework to sort out different brain states by their stability and reversibility, and illustrates its usefulness to dissociate between physiological (sleep), pathological (brain-injured patients), and pharmacologically-induced (anesthesia) loss of consciousness.

The Temporal Dynamics of Spontaneous Emotional Brain States and Their Implications for Mental Health

2021 ◽  
pp. 1-14
Author(s):  
Philip A. Kragel ◽  
Ahmad R. Hariri ◽  
Kevin S. LaBar
Keyword(s):  
Mental Health ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Resting State Fmri ◽  
State Transitions ◽  
Brain State ◽  
Emotional States ◽  
Affective States ◽  
Emotional Responding ◽  
Brain States

Abstract Temporal processes play an important role in elaborating and regulating emotional responding during routine mind wandering. However, it is unknown whether the human brain reliably transitions among multiple emotional states at rest and how psychopathology alters these affect dynamics. Here, we combined pattern classification and stochastic process modeling to investigate the chronometry of spontaneous brain activity indicative of six emotions (anger, contentment, fear, happiness, sadness, and surprise) and a neutral state. We modeled the dynamic emergence of these brain states during resting-state fMRI and validated the results across two population cohorts—the Duke Neurogenetics Study and the Nathan Kline Institute Rockland Sample. Our findings indicate that intrinsic emotional brain dynamics are effectively characterized as a discrete-time Markov process, with affective states organized around a neutral hub. The centrality of this network hub is disrupted in individuals with psychopathology, whose brain state transitions exhibit greater inertia and less frequent resetting from emotional to neutral states. These results yield novel insights into how the brain signals spontaneous emotions and how alterations in their temporal dynamics contribute to compromised mental health.

scholarly journals Characterizing pupil dynamics coupling to brain state fluctuation based on lateral hypothalamic activity

2021 ◽  
Author(s):  
Kengo Takahashi ◽  
Filip Sobczak ◽  
Patricia Pais-Roldán ◽  
Xin Yu
Keyword(s):  
Brain Activity ◽  
Field Potential ◽  
Neuronal Cell ◽  
Cell Types ◽  
State Regulation ◽  
Anterior Cingulate ◽  
Brain State ◽  
Dependent Manner ◽  
Whole Brain ◽  
Brain Fmri

AbstractPupil dynamics presents varied correlation features with brain activity under different vigilant levels. The modulation of brain state changes can arise from the lateral hypothalamus (LH), where diverse neuronal cell types contribute to arousal regulation in opposite directions via the anterior cingulate cortex (ACC). However, the relationship of the LH and pupil dynamics has seldom been investigated. Here, we performed local field potential (LFP) recordings at the LH and ACC, and the whole brain fMRI with simultaneous fiber photometry Ca2+ recording in the ACC, to evaluate their correlation with brain state-dependent pupil dynamics. Both LFP and functional MRI (fMRI) data showed opposite correlation features to pupil dynamics, demonstrating an LH activity-dependent manner. Our results demonstrate that the correlation of pupil dynamics with ACC LFP and whole-brain fMRI signals depends on LH activity, indicating a role of the latter in brain state regulation.

scholarly journals Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness

2020 ◽  
Author(s):  
Yonatan Sanz Perl ◽  
Carla Pallavicini ◽  
Ignacio Pérez Ipiña ◽  
Athena Demertzi ◽  
Vincent Bonhomme ◽  
...  
Keyword(s):  
Computational Models ◽  
Brain Activity ◽  
Relevant Information ◽  
Complete Characterization ◽  
Brain State ◽  
Whole Brain ◽  
Brain Injured ◽  
Level Of Consciousness ◽  
The Stability ◽  
Injured Patients

AbstractConsciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness. While the level of consciousness can be taken to describe the actual brain state, a complete characterization should also include its potential behavior against external perturbations. We developed and analyzed whole-brain computational models to show that the stability of conscious states provides information complementary to their similarity to conscious wakefulness. Our work leads to a novel methodological framework to sort out different brain states by their stability and reversibility, and illustrates its usefulness to dissociate between physiological (sleep), pathological (brain-injured patients), and pharmacologically-induced (anesthesia) loss of consciousness.

scholarly journals Simultaneous optogenetic manipulation and calcium imaging in freely movingC. elegans

2013 ◽  
Author(s):  
Frederick B. Shipley ◽  
Christopher M. Clark ◽  
Mark J. Alkema ◽  
Andrew M. Leifer
Keyword(s):  
Neural Activity ◽  
Calcium Imaging ◽  
Neural Circuits ◽  
Neural Response ◽  
Sensory Stimuli ◽  
Systems Neuroscience ◽  
C Elegans ◽  
Fundamental Goal ◽  
Freely Moving ◽  
Interneuron Activity

A fundamental goal of systems neuroscience is to probe the dynamics of neural activity that drive behavior. Here we present an instrument to simultaneously manipulate neural activity via Channelrhodopsin, monitor neural response via GCaMP3, and observes behavior in freely moving C. elegans. We use the instrument to directly observe the relation between sensory stimuli, interneuron activity and locomotion in the mechanosensory circuit. Now published as: Front Neural Circuits 8:28, doi:10.3389/fncir.2014.00028

scholarly journals A neural circuit for flexible control of persistent behavioral states

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Ni Ji ◽  
Gurrein K Madan ◽  
Guadalupe I Fabre ◽  
Alyssa Dayan ◽  
Casey M Baker ◽  
...  
Keyword(s):  
Neural Activity ◽  
Neural Circuit ◽  
Activity Patterns ◽  
State Transitions ◽  
Flexible Control ◽  
C Elegans ◽  
Food Odors ◽  
Long Time ◽  
Behavioral States ◽  
Learning Analysis

To adapt to their environments, animals must generate behaviors that are closely aligned to a rapidly changing sensory world. However, behavioral states such as foraging or courtship typically persist over long time scales to ensure proper execution. It remains unclear how neural circuits generate persistent behavioral states while maintaining the flexibility to select among alternative states when the sensory context changes. Here, we elucidate the functional architecture of a neural circuit controlling the choice between roaming and dwelling states, which underlie exploration and exploitation during foraging in C. elegans. By imaging ensemble-level neural activity in freely-moving animals, we identify stereotyped changes in circuit activity corresponding to each behavioral state. Combining circuit-wide imaging with genetic analysis, we find that mutual inhibition between two antagonistic neuromodulatory systems underlies the persistence and mutual exclusivity of the neural activity patterns observed in each state. Through machine learning analysis and circuit perturbations, we identify a sensory processing neuron that can transmit information about food odors to both the roaming and dwelling circuits and bias the animal towards different states in different sensory contexts, giving rise to context-appropriate state transitions. Our findings reveal a potentially general circuit architecture that enables flexible, sensory-driven control of persistent behavioral states.

scholarly journals LSD flattens the brain′s energy landscape: evidence from receptor-informed network control theory

2021 ◽  
Author(s):  
S. Parker Singleton ◽  
Andrea I Luppi ◽  
Robin L. Carhart-Harris ◽  
Josephine Cruzat ◽  
Leor Roseman ◽  
...  
Keyword(s):  
Control Theory ◽  
Subjective Experience ◽  
Brain Activity ◽  
Energy Landscape ◽  
Network Control ◽  
State Transitions ◽  
Brain State ◽  
Control Analysis ◽  
Brain States ◽  
The Brain

Psychedelics like lysergic acid diethylamide (LSD) offer a powerful window into the function of the human brain and mind, by temporarily altering subjective experience through their neurochemical effects. The RElaxed Beliefs Under Psychedelics (REBUS) model postulates that 5-HT2a receptor agonism allows the brain to explore its dynamic landscape more readily, as suggested by more diverse (entropic) brain activity. Formally, this effect is theorized to correspond to a reduction in the energy required to transition between different brain-states, i.e. a ″flattening of the energy landscape.″ However, this hypothesis remains thus far untested. Here, we leverage network control theory to map the brain′s energy landscape, by quantifying the energy required to transition between recurrent brain states. In accordance with the REBUS model, we show that LSD reduces the energy required for brain-state transitions, and, furthermore, that this reduction in energy correlates with more frequent state transitions and increased entropy of brain-state dynamics. Through network control analysis that incorporates the spatial distribution of 5-HT2a receptors, we demonstrate the specific role of this receptor in flattening the brain′s energy landscape. Also, in accordance with REBUS, we show that the occupancy of bottom-up states is increased by LSD. In addition to validating fundamental predictions of the REBUS model of psychedelic action, this work highlights the potential of receptor-informed network control theory to provide mechanistic insights into pharmacological modulation of brain dynamics.

scholarly journals Movie viewing elicits rich and reliable brain state dynamics

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Johan N. van der Meer ◽  
Michael Breakspear ◽  
Luke J. Chang ◽  
Saurabh Sonkusare ◽  
Luca Cocchi
Keyword(s):  
Resting State ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
State Transitions ◽  
Brain State ◽  
The Social ◽  
Brain States ◽  
Functional States ◽  
Intrinsic Brain Activity

Abstract Adaptive brain function requires that sensory impressions of the social and natural milieu are dynamically incorporated into intrinsic brain activity. While dynamic switches between brain states have been well characterised in resting state acquisitions, the remodelling of these state transitions by engagement in naturalistic stimuli remains poorly understood. Here, we show that the temporal dynamics of brain states, as measured in fMRI, are reshaped from predominantly bistable transitions between two relatively indistinct states at rest, toward a sequence of well-defined functional states during movie viewing whose transitions are temporally aligned to specific features of the movie. The expression of these brain states covaries with different physiological states and reflects subjectively rated engagement in the movie. In sum, a data-driven decoding of brain states reveals the distinct reshaping of functional network expression and reliable state transitions that accompany the switch from resting state to perceptual immersion in an ecologically valid sensory experience.

scholarly journals An annotation dataset facilitates automatic annotation of whole-brain activity imaging of C. elegans

2019 ◽  
Author(s):  
Yu Toyoshima ◽  
Stephen Wu ◽  
Manami Kanamori ◽  
Hirofumi Sato ◽  
Moon Sun Jang ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Brain Activity ◽  
Expression Patterns ◽  
Human Interaction ◽  
Automatic Annotation ◽  
Head Region ◽  
Whole Brain ◽  
C Elegans ◽  
Annotation Method ◽  
Neural Activities

AbstractAnnotation of cell identity is an essential process in neuroscience that allows for comparing neural activities across different animals. In C. elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal is limited in practice and comprehensive methods for cell annotation are required. Here we propose an efficient annotation method that can be integrated with the whole-brain imaging technique. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. The large positional variations illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters to tackle this problem. We also developed an automatic annotation method with human interaction functionality that facilitates annotation for whole-brain imaging.

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