Energy landscape and dynamics of brain activity during human bistable perception.
Ontology highlight
ABSTRACT:
SUBMITTER: Watanabe T
PROVIDER: S-EPMC4174295 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The neural mechanisms underlying conscious visual perception have been extensively investigated using bistable perception paradigms. Previous functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) studies suggest that the right anterior superior parietal (r-aSPL) and the right posterior superior parietal lobule (r-pSPL) have opposite roles in triggering perceptual reversals. It has been proposed that these two areas are part of a hierarchical network whose dynamics determine perceptual switches. However, how these two parietal regions interact with each other and with the rest of the brain during bistable perception is not known. Here, we investigated such a model by recording brain activity using fMRI while participants viewed a bistable structure-from-motion stimulus. Using dynamic causal modeling (DCM), we found that resolving such perceptual ambiguity was specifically associated with reciprocal interactions between these parietal regions and V5/MT. Strikingly, the strength of bottom-up coupling between V5/MT to r-pSPL and from r-pSPL to r-aSPL predicted individual mean dominance duration. Our findings are consistent with a hierarchical predictive coding model of parietal involvement in bistable perception and suggest that visual information processing underlying spontaneous perceptual switches can be described as changes in connectivity strength between parietal and visual cortical regions.
| S-EPMC4306523 | biostudies-literature
Project description:When faced with ambiguous sensory inputs, subjective perception alternates between the different interpretations in a stochastic manner. Such multistable perception phenomena have intrigued scientists and laymen alike for over a century. Despite rigorous investigations, the underlying mechanisms of multistable perception remain elusive. Recent studies using multivariate pattern analysis revealed that activity patterns in posterior visual areas correlate with fluctuating percepts. However, increasing evidence suggests that vision--and perception at large--is an active inferential process involving hierarchical brain systems. We applied searchlight multivariate pattern analysis to functional magnetic resonance imaging signals across the human brain to decode perceptual content during bistable perception and simple unambiguous perception. Although perceptually reflective activity patterns during simple perception localized predominantly to posterior visual regions, bistable perception involved additionally many higher-order frontoparietal and temporal regions. Moreover, compared with simple perception, both top-down and bottom-up influences were dramatically enhanced during bistable perception. We further studied the intermittent presentation of ambiguous images--a condition that is known to elicit perceptual memory. Compared with continuous presentation, intermittent presentation recruited even more higher-order regions and was accompanied by further strengthened top-down influences but relatively weakened bottom-up influences. Taken together, these results strongly support an active top-down inferential process in perception.
| S-EPMC3761598 | biostudies-literature
Project description:Human brain dynamics can be viewed through the lens of statistical mechanics, where neurophysiological activity evolves around and between local attractors representing mental states. Many physically-inspired models of these dynamics define brain states based on instantaneous measurements of regional activity. Yet, recent work in network neuroscience has provided evidence that the brain might also be well-characterized by time-varying states composed of locally coherent activity or functional modules. We study this network-based notion of brain state to understand how functional modules dynamically interact with one another to perform cognitive functions. We estimate the functional relationships between regions of interest (ROIs) by fitting a pair-wise maximum entropy model to each ROI's pattern of allegiance to functional modules. This process uses an information theoretic notion of energy (as opposed to a metabolic one) to produce an energy landscape in which local minima represent attractor states characterized by specific patterns of modular structure. The clustering of local minima highlights three classes of ROIs with similar patterns of allegiance to community states. Visual, attention, sensorimotor, and subcortical ROIs are well-characterized by a single functional community. The remaining ROIs affiliate with a putative executive control community or a putative default mode and salience community. We simulate the brain's dynamic transitions between these community states using a random walk process. We observe that simulated transition probabilities between basins are statistically consistent with empirically observed transitions in resting state fMRI data. These results offer a view of the brain as a dynamical system that transitions between basins of attraction characterized by coherent activity in groups of brain regions, and that the strength of these attractors depends on the ongoing cognitive computations.
| S-EPMC5600845 | biostudies-literature
Project description:Our current understanding of melancholic depression is shaped by its position in the depression spectrum. The lack of consensus on how it should be treated-whether as a subtype of depression, or as a distinct disorder altogethe-interferes with the recovery of suffering patients. In this study, we analyzed brain state energy landscape models of melancholic depression, in contrast to healthy and non-melancholic energy landscapes. Our analyses showed significant group differences on basin energy, basin frequency, and transition dynamics in several functional brain networks such as basal ganglia, dorsal default mode, and left executive control networks. Furthermore, we found evidences suggesting the connection between energy landscape characteristics (basin characteristics) and depressive symptom scores (BDI-II and SHAPS). These results indicate that melancholic depression is distinguishable from its non-melancholic counterpart, not only in terms of depression severity, but also in brain dynamics.
| S-EPMC8656401 | biostudies-literature
Project description:Femtosecond to nanosecond dynamics of O(2) rebinding to human WT myoglobin and its mutants, V68F and I107F, have been studied by using transient absorption. The results are compared with NO rebinding. Even though the immediate environment around the heme binding site is changed by the mutations, the picosecond geminate rebinding of oxygen is at most minimally affected. On the other hand, the V68F (E11) mutation causes drastic differences in rebinding on the nanosecond time scale, whereas the effect of the I107F (G8) mutation remains relatively small within our 10-ns time window. Unlike traditional homogeneous kinetics and molecular dynamics collisional simulations, we propose a "bifurcation model" for populations of directed and undirected dynamics on the ultrafast time scale, reflecting the distribution of initial protein conformations. The major mutation effect occurs on the time scale on which global protein conformational change is possible, consistent with transitions between the conformations of directed and undirected population playing a role in the O(2) binding. We discuss the relevance of these findings to the bimolecular function of the protein.
| S-EPMC539810 | biostudies-literature
Project description:Characterizing anesthesia-induced alterations to brain network dynamics provides a powerful framework to understand the neural mechanisms of unconsciousness. To this end, increased attention has been directed at how anesthetic drugs alter the functional connectivity between brain regions as defined through neuroimaging. However, the effects of anesthesia on temporal dynamics at functional network scales is less well understood. Here, we examine such dynamics in view of the free-energy principle, which postulates that brain dynamics tend to promote lower energy (more organized) states. We specifically engaged the hypothesis that such low-energy states play an important role in maintaining conscious awareness. To investigate this hypothesis, we analyzed resting-state BOLD fMRI data from human volunteers during wakefulness and under sevoflurane general anesthesia. Our approach, which extends an idea previously used in the characterization of neuron-scale populations, involves thresholding the BOLD time series and using a normalized Hamiltonian energy function derived from the Ising model. Our major finding is that the brain spends significantly more time in lower energy states during eyes-closed wakefulness than during general anesthesia. This effect is especially pronounced in networks thought to be critical for maintaining awareness, suggesting a crucial cognitive role for both the structure and the dynamical landscape of these networks.
| S-EPMC6063715 | biostudies-literature
Project description:The human brain's executive systems have a vital role in deciding and selecting among actions. Selection among alternatives also occurs in the perceptual domain; for instance, when perception switches between interpretations during perceptual bistability. Whether executive systems also underlie this functionality remains debated, with known fronto-parietal concomitants of perceptual switches being variously interpreted as reflecting the switches' cause or as reflecting their consequences. We developed a procedure in which the two eyes receive different inputs and perception demonstrably switches between these inputs, yet the switches themselves are so inconspicuous as to become unreportable, minimizing their executive consequences. Fronto-parietal fMRI BOLD responses that accompanied perceptual switches were similarly minimized in this procedure, indicating that these reflect the switches' consequences rather than their cause. We conclude that perceptual switches do not always rely on executive brain areas and that processes responsible for selection among alternatives may operate outside the brain's executive systems.
| S-EPMC4603386 | biostudies-literature
Project description:A critical mystery in neuroscience lies in determining how anatomical structure impacts the complex functional dynamics of the brain. How does large-scale brain circuitry constrain states of neuronal activity and transitions between those states? We address these questions using a maximum entropy model of brain dynamics informed by white matter tractography. We demonstrate that the most probable brain states - characterized by minimal energy - display common activation profiles across brain areas: local spatially-contiguous sets of brain regions reminiscent of cognitive systems are co-activated frequently. The predicted activation rate of these systems is highly correlated with the observed activation rate measured in a separate resting state fMRI data set, validating the utility of the maximum entropy model in describing neurophysiological dynamics. This approach also offers a formal notion of the energy of activity within a system, and the energy of activity shared between systems. We observe that within- and between-system energies cleanly separate cognitive systems into distinct categories, optimized for differential contributions to integrated versus segregated function. These results support the notion that energetic and structural constraints circumscribe brain dynamics, offering insights into the roles that cognitive systems play in driving whole-brain activation patterns.
| S-EPMC5802783 | biostudies-literature
Project description:When facing ambiguous images, the brain switches between mutually exclusive interpretations, a phenomenon known as bistable perception. Despite years of research, a consensus on whether bistability is driven primarily by bottom-up or top-down mechanisms has not been achieved. Here, we adopted a Bayesian approach to reconcile these two theories. Fifty-five healthy participants were exposed to an adaptation of the Necker cube paradigm, in which we manipulated sensory evidence and prior knowledge. Manipulations of both sensory evidence and priors significantly affected the way participants perceived the Necker cube. However, we observed an interaction between the effect of the cue and the effect of the instructions, a finding that is incompatible with Bayes-optimal integration. In contrast, the data were well predicted by a circular inference model. In this model, ambiguous sensory evidence is systematically biased in the direction of current expectations, ultimately resulting in a bistable percept.
| S-EPMC7405786 | biostudies-literature
Project description:Behavioural engagement can enhance sensory perception. However, the neuronal mechanisms by which behavioural states affect stimulus perception remain poorly understood. Here we record from single units in auditory cortex of rats performing a self-initiated go/no-go auditory task. Self-initiation transforms cortical tuning curves and bidirectionally modulates stimulus-evoked activity patterns and improves auditory detection and recognition. Trial self-initiation decreases the rate of spontaneous activity in the majority of recorded cells. Optogenetic disruption of cortical activity before and during tone presentation shows that these changes in evoked and spontaneous activity are important for sound perception. Thus, behavioural engagement can prepare cortical circuits for sensory processing by dynamically changing sound representation and by controlling the pattern of spontaneous activity.
| S-EPMC5309852 | biostudies-other