scholarly journals The structured flow on the brain's resting state manifold

2022 ◽  
Author(s):  
Jan Fousek ◽  
Giovanni Rabuffo ◽  
Kashyap Gudibanda ◽  
Hiba Sheheitli ◽  
Viktor Jirsa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Activity Patterns ◽  
Predictive Coding ◽  
Network Connectivity ◽  
High Amplitude ◽  
Characteristic Functional ◽  
Spatio Temporal ◽  
Generative Mechanism ◽  
Task Conditions

Spontaneously fluctuating brain activity patterns emerge at rest and relate to brain functional networks involved in task conditions. Despite detailed descriptions of the spatio-temporal brain patterns, our understanding of their generative mechanism is still incomplete. Using a combination of computational modeling and dynamical systems analysis we provide a complete mechanistic description in terms of the constituent entities and the productive relation of their causal activities leading to the formation of a resting state manifold via the network connectivity. We demonstrate that the symmetry breaking by the connectivity creates a characteristic flow on the manifold, which produces the major empirical data features including spontaneous high amplitude co-activations, neuronal cascades, spectral cortical gradients, multistability and characteristic functional connectivity dynamics. The understanding of the brain's resting state manifold is fundamental for the construction of task-specific flows and manifolds used in theories of brain function such as predictive coding.

scholarly journals Beyond the low frequency fluctuations morning and evening differences in human brain

2019 ◽  
Author(s):  
Magdalena Fafrowicz ◽  
Bartosz Bohaterewicz ◽  
Anna Ceglarek ◽  
Monika Cichocka ◽  
Koryna Lewandowska ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Human Performance ◽  
Brain Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Basic Mechanism ◽  
Time Of Day ◽  
Resting State Functional Connectivity ◽  
Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

scholarly journals fMRI single trial discovery of spatio-temporal brain activity patterns

2016 ◽  
Vol 38 (3) ◽  
pp. 1421-1437 ◽  
Author(s):  
Michele Allegra ◽  
Shima Seyed-Allaei ◽  
Fabrizio Pizzagalli ◽  
Fahimeh Baftizadeh ◽  
Marta Maieron ◽  
...  
Keyword(s):  
Brain Activity ◽  
Activity Patterns ◽  
Single Trial ◽  
Spatio Temporal

scholarly journals High-amplitude cofluctuations in cortical activity drive functional connectivity

2020 ◽  
Vol 117 (45) ◽  
pp. 28393-28401
Author(s):  
Farnaz Zamani Esfahlani ◽  
Youngheun Jo ◽  
Joshua Faskowitz ◽  
Lisa Byrge ◽  
Daniel P. Kennedy ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Temporal Structure ◽  
Activity Patterns ◽  
High Amplitude ◽  
Network Activity ◽  
Connectivity Pattern ◽  
Future Research ◽  
Resting State Functional Connectivity ◽  
Brain Organization

Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network’s modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research.

scholarly journals On-scalp MEG SQUIDs are sensitive to early somatosensory activity unseen by conventional MEG

2019 ◽  
Author(s):  
Lau M. Andersen ◽  
Christoph Pfeiffer ◽  
Silvia Ruffieux ◽  
Bushra Riaz ◽  
Dag Winkler ◽  
...  
Keyword(s):  
Brain Activity ◽  
Activity Patterns ◽  
Signal Strength ◽  
Classification Performance ◽  
Discrimination Accuracy ◽  
Sensor Coverage ◽  
Non Invasive ◽  
Spatio Temporal ◽  
Sensor Density ◽  
The Right

AbstractMagnetoencephalography (MEG) has a unique capacity to resolve the spatio-temporal development of brain activity from non-invasive measurements. Conventional MEG, however, relies on sensors that sample from a distance (20-40 mm) to the head due to thermal insulation requirements (the MEG sensors function at 4 K in a helmet). A gain in signal strength and spatial resolution may be achieved if sensors are moved closer to the head. Here, we report a study comparing measurements from a seven-channel on-scalp SQUID MEG system to those from a conventional (in-helmet) SQUID MEG system.We compared spatio-temporal resolution between on-scalp and conventional MEG by comparing the discrimination accuracy for neural activity patterns resulting from stimulating five different phalanges of the right hand. Because of proximity and sensor density differences between on-scalp and conventional MEG, we hypothesized that on-scalp MEG would allow for a more high-resolved assessment of these activity patterns, and therefore also a better classification performance in discriminating between neural activations from the different phalanges.We observed that on-scalp MEG provided better classification performance during an early post-stimulus period (15-30 ms). This corresponded to electroencephalographic (EEG) response components N16 and P23, and was an unexpected observation as these components are usually not observed in conventional MEG. They indicate that on-scalp MEG opens up for a richer registration of the cortical signal, allowing for sensitivity to what are potentially sources in the thalamo-cortical radiation and to quasi-radial sources.We had originally expected that on-scalp MEG would provide better classification accuracy based on activity in proximity to the P60m component compared to conventional MEG. This component indeed allowed for the best classification performance for both MEG systems (60-75%, chance 50%). However, we did not find that on-scalp MEG allowed for better classification than conventional MEG at this latency. We believe this may be due to the limited sensor coverage in the recording, in combination with our strategy for positioning the on-scalp MEG sensors. We discuss how sensor density and coverage as well as between-phalange source field dissimilarities may influence our hypothesis testing, which we believe to be useful for future benchmarking measurements.

scholarly journals Latent functional connectivity underlying multiple brain states

2021 ◽  
Author(s):  
Ethan M McCormick ◽  
Katelyn L Arnemann ◽  
Takuya Ito ◽  
Stephen Jose Hanson ◽  
Michael W Cole
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Network Architecture ◽  
Brain Activity ◽  
Brain Network ◽  
Mathematical Framework ◽  
Human Connectome Project ◽  
Brain States ◽  
Task Conditions ◽  
Psychometric G

Functional connectivity (FC) studies have predominantly focused on resting state, where ongoing dynamics are thought to primarily reflect the brain's intrinsic network architecture, which is thought to be broadly relevant to brain function because it persists across brain states. However, it is unknown whether resting state is the optimal state for measuring intrinsic FC. We propose that latent FC, reflecting patterns of connectivity shared across many brain states, may better capture intrinsic FC relative to measures derived from resting state alone. We estimated latent FC in relation to 7 highly distinct task states (24 task conditions) and resting state using fMRI data from 352 participants from the Human Connectome Project. Latent FC was estimated independently for each connection by applying leave-one-task-out factor analysis on the state FC estimates. Compared to resting-state connectivity, we found that latent connectivity improves generalization to held-out brain states, better explaining patterns of both connectivity and task-evoked brain activity. We also found that latent connectivity improved prediction of behavior, measured by the general intelligence factor psychometric g. Our results suggest that patterns of FC shared across many brain states, rather than just resting state, better reflects general, state-independent connectivity. This affirms the notion of "intrinsic" brain network architecture as a set of connectivity properties persistent across brain states, providing an updated conceptual and mathematical framework of intrinsic connectivity as a latent factor.

scholarly journals Different brain networks mediate the effects of social and conditioned expectations on pain

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Leonie Koban ◽  
Marieke Jepma ◽  
Marina López-Solà ◽  
Tor D. Wager
Keyword(s):  
Large Scale ◽  
Brain Activity ◽  
Activity Patterns ◽  
Predictive Coding ◽  
Social Information ◽  
Functional Networks ◽  
Learning Effects ◽  
Pain Ratings ◽  
Classically Conditioned ◽  
The Brain

Abstract Information about others’ experiences can strongly influence our own feelings and decisions. But how does such social information affect the neural generation of affective experience, and are the brain mechanisms involved distinct from those that mediate other types of expectation effects? Here, we used fMRI to dissociate the brain mediators of social influence and associative learning effects on pain. Participants viewed symbolic depictions of other participants’ pain ratings (social information) and classically conditioned pain-predictive cues before experiencing painful heat. Social information and conditioned stimuli each had significant effects on pain ratings, and both effects were mediated by self-reported expectations. Yet, these effects were mediated by largely separable brain activity patterns, involving different large-scale functional networks. These results show that learned versus socially instructed expectations modulate pain via partially different mechanisms—a distinction that should be accounted for by theories of predictive coding and related top-down influences.

scholarly journals The sensory and motor components of the cortical hierarchy are coupled to the rhythm of the stomach during rest

2021 ◽  
Author(s):  
Ignacio Rebollo ◽  
Catherine Tallon-Baudry
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Piriform Cortex ◽  
Brain Regions ◽  
Cognitive Networks ◽  
Hierarchical Organization ◽  
Temporal Organization ◽  
Resting State Networks ◽  
Fine Grained ◽  
Spatio Temporal

Bodily rhythms appear as novel scaffolding mechanisms orchestrating the spatio-temporal organization of spontaneous brain activity. Here, we follow up on the discovery of the gastric resting-state network (Rebollo et al, 2018), composed of brain regions in which the fMRI signal is phase-synchronized to the slow (0.05 Hz) electrical rhythm of the stomach. Using a larger sample size (n=63 human participants), we further characterize the anatomy and effect sizes of gastric-brain coupling across resting-state networks, a fine grained cortical parcellation, as well as along the main gradients of cortical organization. Most (67%) of the gastric network is included in the somato-motor-auditory (38%) and visual (29%) resting state networks. Gastric brain coupling also occurs in the granular insula and, to a lesser extent, in the piriform cortex. Thus, all sensory and motor cortices corresponding to both exteroceptive and interoceptive modalities are coupled to the gastric rhythm during rest. Conversely, little gastric-brain coupling occurs in cognitive networks and transmodal regions. These results suggest not only that gastric rhythm and sensory-motor processes are likely to interact, but also that gastric-brain coupling might be a mechanism of sensory and motor integration that mostly bypasses cognition, complementing the classical hierarchical organization of the human brain.

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