A highly collateralized thalamic cell type with arousal-predicting activity serves as a key hub for graded state transitions in the forebrain

Mátyás, Ferenc; Komlósi, Gergely; Babiczky, Ákos; Kocsis, Kinga; Barthó, Péter; Barsy, Boglárka; Dávid, Csaba; Kanti, Vivien; Porrero, César; Magyar, Aletta; Szűcs, Iván; Clascá, Francisco; Acsády, László

doi:10.1038/s41593-018-0251-9

Cited by 59 publications

(48 citation statements)

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“…Scalp EEG is most sensitive to source activity in adjacent cortex. While sleep-related cortical reconfigurations are likely driven by subcortical structures 27 , our findings permit a non-invasive characterization of the cortical manifestations of these subcortical modulations. Moreover, these results relate whole-cortex dynamics to functional brain development.…”

Section: Discussionmentioning

confidence: 84%

Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms

et al. 2019

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Sleep architecture carries vital information about brain health across the lifespan. In particular, the ability to express distinct vigilance states is a key physiological marker of neurological wellbeing in the newborn infant although systems-level mechanisms remain elusive. Here, we demonstrate that the transition from quiet to active sleep in newborn infants is marked by a substantial reorganization of large-scale cortical activity and functional brain networks. This reorganization is attenuated in preterm infants and predicts visual performance at two years. We find a striking match between these empirical effects and a computational model of large-scale brain states which uncovers fundamental biophysical mechanisms not evident from inspection of the data. Active sleep is defined by reduced energy in a uniform mode of neural activity and increased energy in two more complex anteroposterior modes. Preterm-born infants show a deficit in this sleep-related reorganization of modal energy that carries novel prognostic information.

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Section: Discussionmentioning

confidence: 84%

Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms

et al. 2019

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“…The involvement of the thalamic drive in Au1 is debated (Zhou et al, 2014) but cholinergic inputs as well as top-down input from secondary motor cortex (M2) may play a stronger role (Schneider et al, 2014; Nelson and Mooney, 2016; Reimer et al, 2016). Overall, neurons in the central/dorsal medial thalamic nuclei could play an important role in initiating and maintaining general cortical arousal (Gent et al, 2018; Mátyás et al, 2018). Other sources of modulatory inputs including noradrenergic inputs from the brainstem (Constantinople and Bruno, 2011; Polack et al, 2013; Fazlali et al, 2016; Reimer et al, 2016) or top-down inputs from higher-cortical areas (Zhang et al, 2014) also alter cortical activity and it is likely that multiple parallel pathways contribute to cortical activation with different involvement depending on the behavioral state (i.e., cortical activation during QW, whisking, locomotion) or context (spontaneous behavior vs. engagement in a task).…”

Section: Cellular Mechanisms Controlling Cortical Statesmentioning

confidence: 99%

The Cortical States of Wakefulness

Poulet

Crochet

2019

Front. Syst. Neurosci.

104

159

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Cortical neurons process information on a background of spontaneous, ongoing activity with distinct spatiotemporal profiles defining different cortical states. During wakefulness, cortical states alter constantly in relation to behavioral context, attentional level or general motor activity. In this review article, we will discuss our current understanding of cortical states in awake rodents, how they are controlled, their impact on sensory processing, and highlight areas for future research. A common observation in awake rodents is the rapid change in spontaneous cortical activity from high-amplitude, low-frequency (LF) fluctuations, when animals are quiet, to faster and smaller fluctuations when animals are active. This transition is typically thought of as a change in global brain state but recent work has shown variation in cortical states across regions, indicating the presence of a fine spatial scale control system. In sensory areas, the cortical state change is mediated by at least two convergent inputs, one from the thalamus and the other from cholinergic inputs in the basal forebrain. Cortical states have a major impact on the balance of activity between specific subtypes of neurons, on the synchronization between nearby neurons, as well as the functional coupling between distant cortical areas. This reorganization of the activity of cortical networks strongly affects sensory processing. Thus cortical states provide a dynamic control system for the moment-by-moment regulation of cortical processing.

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“…For example, two genes that are highly important for feeding, calretinin, and glucose transporter 2, are highly expressed in PVT. Calretinin, also known as calbindin 2, serves as one of the best markers for PVT (Allen Brain Atlas; Matyas et al, 2018), with around 62% of PVT glutamate neurons expressing this gene (Hua et al, 2018) predominantly in the lateral ventral and posterior regions (Winsky et al, 1992). These neurons have highly non-selective efferent projections to NAc, BNST, CeA, and PFC (Hua et al, 2018), and yet how calretinin-expressing neurons in PVT may differ from non-calretinin neurons is largely unexplored.…”

Section: Heterogeneity Is Based On Anatomical Location Projection Prmentioning

confidence: 99%

Heterogeneity in the Paraventricular Thalamus: The Traffic Light of Motivated Behaviors

McGinty

Otis

2020

Front. Behav. Neurosci.

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The paraventricular thalamic nucleus (PVT) is highly interconnected with brain areas that control reward-seeking behavior. Despite this known connectivity, broad manipulations of PVT often lead to mixed, and even opposing, behavioral effects, clouding our understanding of how PVT precisely contributes to reward processing. Although the function of PVT in influencing reward-seeking is poorly understood, recent studies show that forebrain and hypothalamic inputs to, and nucleus accumbens (NAc) and amygdalar outputs from, PVT are strongly implicated in PVT responses to conditioned and appetitive or aversive stimuli that determine whether an animal will approach or avoid specific rewards. These studies, which have used an array of chemogenetic, optogenetic, and calcium imaging technologies, have shown that activity in PVT input and output circuits is highly heterogeneous, with mixed activity patterns that contribute to behavior in highly distinct manners. Thus, it is important to perform experiments in precisely defined cell types to elucidate how the PVT network contributes to reward-seeking behaviors. In this review, we describe the complex heterogeneity within PVT circuitry that appears to influence the decision to seek or avoid a reward and point out gaps in our understanding that should be investigated in future studies.

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A highly collateralized thalamic cell type with arousal-predicting activity serves as a key hub for graded state transitions in the forebrain

Cited by 59 publications

References 58 publications

Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms

Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms

The Cortical States of Wakefulness

Heterogeneity in the Paraventricular Thalamus: The Traffic Light of Motivated Behaviors

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