scholarly journals Control of brain state transitions with light

2019 ◽  
Author(s):  
Almudena Barbero-Castillo ◽  
Fabio Riefolo ◽  
Carlo Matera ◽  
Sara Caldas-Martínez ◽  
Pedro Mateos-Aparicio ◽  
...  
Keyword(s):  
Genetic Manipulation ◽  
Oscillatory Activity ◽  
State Transitions ◽  
Brain State ◽  
Muscarinic Agonist ◽  
Frequency Pattern ◽  
Brain Rhythms ◽  
Brain States ◽  
And Control

ABSTRACTBehavior is driven by specific neuronal activity and can be directly associated with characteristic brain states. The oscillatory activity of neurons contains information about the mental state of an individual, and the transition between physiological brain states is largely controlled by neuromodulators. Manipulating neural activity, brain rhythms or synchronization is of significant therapeutic interest in several neurological disorders and can be achieved by different means such as transcranial current and magnetic stimulation techniques, and by light through optogenetics, although the clinical translation of the latter is hampered by the need of gene therapy. Here, we directly modulate brain rhythms with light using a novel photoswitchable muscarinic agonist. Synchronous slow wave activity is transformed into a higher frequency pattern in the cerebral cortex both in slices in vitro and in anesthetized mice. These results open the way to the study of the neuromodulation and control of spatiotemporal patterns of activity and pharmacology of brain states, their transitions, and their links to cognition and behavior, in different organisms without requiring any genetic manipulation.

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 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 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 Control of Brain State Transitions with a Photoswitchable Muscarinic Agonist

2021 ◽  
pp. 2005027
Author(s):  
Almudena Barbero‐Castillo ◽  
Fabio Riefolo ◽  
Carlo Matera ◽  
Sara Caldas‐Martínez ◽  
Pedro Mateos‐Aparicio ◽  
...  
Keyword(s):  
State Transitions ◽  
Brain State ◽  
Muscarinic Agonist

scholarly journals The discrete logic of the Brain - Explicit modelling of Brain State durations in EEG and MEG

2019 ◽  
Author(s):  
Nelson J. Trujillo-Barreto ◽  
David Araya ◽  
Wael El-Deredy
Keyword(s):  
Markov Models ◽  
Simulated Data ◽  
State Transitions ◽  
Brain State ◽  
Dynamical Regime ◽  
Stable Pattern ◽  
State Duration ◽  
Brain States ◽  
Generative Mechanisms ◽  
The Brain

AbstractWe consider the detection and characterisation of brain state transitions, based on ongoing Magneto and Electroencephalography (M/EEG). Here a brain state represents a specific brain dynamical regime or mode of operation, which produces a characteristic quasi-stable pattern of activity at topography, sources or network levels. These states and their transitions over time can reflect fundamental computational properties of the brain, shaping human behaviour and brain function. The Hidden Markov Model (HMM) has emerged as a useful model-based approach for uncovering the hidden dynamics of brain state transitions based on observed data. However, the Geometric distribution of state duration (dwell time) implicit in HMM places highest probability on very short durations, which makes it inappropriate for the accurate modelling of brain states in M/EEG. We propose using Hidden Semi Markov Models (HSMM), a generalisation of HMM that models the brain state duration distribution explicitly. We present a Bayesian formulation of HSMM and use the Variational Bayes framework to efficiently estimate the HSMM parameters, the number of brain states and select among alternative brain state duration distributions. We assess HSMM performance against HMM on simulated data and demonstrate that the accurate modelling of state duration is paramount for accurately and robustly modelling non-Markovian EEG brain state features. Finally, we used actual resting-state EEG data to demonstrate the approach in practice and conclude that it provides a flexible parameterised framework that permits closer interrogation of possible generative mechanisms.

scholarly journals Cortical responses to vagus nerve stimulation are modulated by ongoing oscillatory activity associated with different brain states in non-human primates

2021 ◽  
Author(s):  
Irene Rembado ◽  
David K. Su ◽  
Ariel Levari ◽  
Larry E. Shupe ◽  
Steve Perlmutter ◽  
...  
Keyword(s):  
Vagus Nerve ◽  
Nerve Stimulation ◽  
Vagus Nerve Stimulation ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Oscillatory Activity ◽  
Brain State ◽  
Cortical Areas ◽  
Cortical Responses ◽  
Brain States

AbstractVagus nerve stimulation (VNS) is tested as therapy for several brain disorders and as a means to modulate brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are dependent on oscillatory brain activity underling different brain states. In 2 freely behaving macaque monkeys, we delivered trains of left cervical VNS, at different pulsing frequencies (5-300 Hz), while recording local field potentials (LFP) from sites in contralateral prefrontal, sensorimotor and parietal cortical areas, continuously over 11-16 hours. Different brain states were inferred from oscillatory components of LFPs and the presence of overt movement: active awake, resting awake, REM sleep and NREM sleep. VNS elicited VEPs comprising early (<70 ms), intermediate (70-250 ms) and late (>250 ms) components in all sampled cortical areas. The magnitude of only the intermediate and late components was modulated by brain state and pulsing frequency. These findings have implications for the role of ongoing brain activity in shaping cortical responses to peripheral stimuli, for the modulation of vagal interoceptive signaling by cortical states, and for the calibration of VNS therapies.

Improvement of effectiveness in maize breeding

2006 ◽  
Vol 54 (3) ◽  
pp. 351-358 ◽  
Author(s):  
P. Pepó
Keyword(s):  
Recurrent Selection ◽  
Genetic Manipulation ◽  
Field Testing ◽  
Tissue Cultures ◽  
Maize Breeding ◽  
Breeding Programmes ◽  
Speed Up ◽  
Selection For

Plant regeneration via tissue culture is becoming increasingly more common in monocots such as maize (Zea mays L.). Pollen (gametophytic) selection for resistance to aflatoxin in maize can greatly facilitate recurrent selection and the screening of germplasm for resistance at much less cost and in a shorter time than field testing. In vivo and in vitro techniques have been integrated in maize breeding programmes to obtain desirable agronomic attributes, enhance the genes responsible for them and speed up the breeding process. The efficiency of anther and tissue cultures in maize and wheat has reached the stage where they can be used in breeding programmes to some extent and many new cultivars produced by genetic manipulation have now reached the market.

scholarly journals Stage-dependent effect of deferoxamine on growth of Plasmodium falciparum in vitro

Blood ◽  
1990 ◽  
Vol 76 (6) ◽  
pp. 1250-1255 ◽  
Author(s):  
S Whitehead ◽  
TE Peto
Keyword(s):  
Plasmodium Falciparum ◽  
Growth Inhibition ◽  
Antimalarial Activity ◽  
Clinical Malaria ◽  
Inhibitory Effect ◽  
Parasite Development ◽  
And Control ◽  
Speed Of Onset

Abstract Deferoxamine (DF) has antimalarial activity that can be demonstrated in vitro and in vivo. This study is designed to examine the speed of onset and stage dependency of growth inhibition by DF and to determine whether its antimalarial activity is cytostatic or cytocidal. Growth inhibition was assessed by suppression of hypoxanthine incorporation and differences in morphologic appearance between treated and control parasites. Using synchronized in vitro cultures of Plasmodium falciparum, growth inhibition by DF was detected within a single parasite cycle. Ring and nonpigmented trophozoite stages were sensitive to the inhibitory effect of DF but cytostatic antimalarial activity was suggested by evidence of parasite recovery in later cycles. However, profound growth inhibition, with no evidence of subsequent recovery, occurred when pigmented trophozoites and early schizonts were exposed to DF. At this stage in parasite development, the activity of DF was cytocidal and furthermore, the critical period of exposure may be as short as 6 hours. These observations suggest that iron chelators may have a role in the treatment of clinical malaria.

scholarly journals Rapid target validation in a Cas9-inducible hiPSC derived kidney model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yasaman Shamshirgaran ◽  
Anna Jonebring ◽  
Anna Svensson ◽  
Isabelle Leefa ◽  
Mohammad Bohlooly-Y ◽  
...  
Keyword(s):  
High Efficiency ◽  
Disease Modeling ◽  
Genetic Manipulation ◽  
Disease Model ◽  
Genetically Engineered ◽  
Model Systems ◽  
Target Validation ◽  
Direct Differentiation ◽  
Kidney Organoids

AbstractRecent advances in induced pluripotent stem cells (iPSCs), genome editing technologies and 3D organoid model systems highlight opportunities to develop new in vitro human disease models to serve drug discovery programs. An ideal disease model would accurately recapitulate the relevant disease phenotype and provide a scalable platform for drug and genetic screening studies. Kidney organoids offer a high cellular complexity that may provide greater insights than conventional single-cell type cell culture models. However, genetic manipulation of the kidney organoids requires prior generation of genetically modified clonal lines, which is a time and labor consuming procedure. Here, we present a methodology for direct differentiation of the CRISPR-targeted cell pools, using a doxycycline-inducible Cas9 expressing hiPSC line for high efficiency editing to eliminate the laborious clonal line generation steps. We demonstrate the versatile use of genetically engineered kidney organoids by targeting the autosomal dominant polycystic kidney disease (ADPKD) genes: PKD1 and PKD2. Direct differentiation of the respective knockout pool populations into kidney organoids resulted in the formation of cyst-like structures in the tubular compartment. Our findings demonstrated that we can achieve > 80% editing efficiency in the iPSC pool population which resulted in a reliable 3D organoid model of ADPKD. The described methodology may provide a platform for rapid target validation in the context of disease modeling.

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