A Pneumatic Vibrator Created Using Rapid Prototyping Technology for the fMRI Environment

2011 ◽  
Author(s):  
Joseph Soltys ◽  
Sara Wilson
Keyword(s):  
Magnetic Resonance Imaging ◽  
Motor Control ◽  
Muscle Length ◽  
Vibratory Stimulus ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Neuromotor System ◽  
The Brain ◽  
Pneumatic Vibrator

Functional Magnetic Resonance Imaging (fMRI) promises to grant motor control researchers opportunities to more directly explore neuromotor system dynamics including the role of proprioception. The effects of vibration on proprioception have been well documented including changes in perceived muscle length and lengthening velocity and altered muscle spindle organ firing [1–4]. As such, the combination of vibration of the muscle-tendon with fMRI of the brain can be used to better understand how proprioceptive signals are managed in the brain. However, the strength of the magnetic environment of the fMRI does not easily allow for traditional vibration technologies, such as a DC motor with offset mass, to be used to create the necessary vibratory stimulus to perturb the proprioceptive system. Several researchers have nonetheless successfully designed and implemented various vibration devices to probe the brain in the fMRI environment [5–7].

scholarly journals Perceiving actions before they happen: psychological dimensions scaffold neural action prediction

2020 ◽  
Author(s):  
Mark A Thornton ◽  
Diana I Tamir
Keyword(s):  
Magnetic Resonance Imaging ◽  
Functional Neuroimaging ◽  
Social World ◽  
Action Space ◽  
Action Prediction ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
The Social ◽  
Psychological Dimensions ◽  
The Brain

Abstract The social world buzzes with action. People constantly walk, talk, eat, work, play, snooze and so on. To interact with others successfully, we need to both understand their current actions and predict their future actions. Here we used functional neuroimaging to test the hypothesis that people do both at the same time: when the brain perceives an action, it simultaneously encodes likely future actions. Specifically, we hypothesized that the brain represents perceived actions using a map that encodes which actions will occur next: the six-dimensional Abstraction, Creation, Tradition, Food(-relevance), Animacy and Spiritualism Taxonomy (ACT-FAST) action space. Within this space, the closer two actions are, the more likely they are to precede or follow each other. To test this hypothesis, participants watched a video featuring naturalistic sequences of actions while undergoing functional magnetic resonance imaging (fMRI) scanning. We first use a decoding model to demonstrate that the brain uses ACT-FAST to represent current actions. We then successfully predicted as-yet unseen actions, up to three actions into the future, based on their proximity to the current action’s coordinates in ACT-FAST space. This finding suggests that the brain represents actions using a six-dimensional action space that gives people an automatic glimpse of future actions.

scholarly journals Integrating additional knowledge into the estimation of graphical models

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Yunqi Bu ◽  
Johannes Lederer
Keyword(s):  
Graphical Models ◽  
Tuning Parameter ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Graphical Modeling ◽  
Standard Methods ◽  
Neighborhood Selection ◽  
Selection For ◽  
The Brain

Abstract Graphical models such as brain connectomes derived from functional magnetic resonance imaging (fMRI) data are considered a prime gateway to understanding network-type processes. We show, however, that standard methods for graphical modeling can fail to provide accurate graph recovery even with optimal tuning and large sample sizes. We attempt to solve this problem by leveraging information that is often readily available in practice but neglected, such as the spatial positions of the measurements. This information is incorporated into the tuning parameter of neighborhood selection, for example, in the form of pairwise distances. Our approach is computationally convenient and efficient, carries a clear Bayesian interpretation, and improves standard methods in terms of statistical stability. Applied to data about Alzheimer’s disease, our approach allows us to highlight the central role of lobes in the connectivity structure of the brain and to identify an increased connectivity within the cerebellum for Alzheimer’s patients compared to other subjects.

scholarly journals Increased sensitivity to strong perturbations in a whole-brain model of LSD

2021 ◽  
Author(s):  
Beatrice M. Jobst ◽  
Selen Atasoy ◽  
Adrián Ponce-Alvarez ◽  
Ana Sanjuán ◽  
Leor Roseman ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
External Perturbation ◽  
Brain Regions ◽  
Lysergic Acid ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Whole Brain ◽  
Response Diversity ◽  
Brain States ◽  
The Brain

AbstractLysergic acid diethylamide (LSD) is a potent psychedelic drug, which has seen a revival in clinical and pharmacological research within recent years. Human neuroimaging studies have shown fundamental changes in brain-wide functional connectivity and an expansion of dynamical brain states, thus raising the question about a mechanistic explanation of the dynamics underlying these alterations. Here, we applied a novel perturbational approach based on a whole-brain computational model, which opens up the possibility to externally perturb different brain regions in silico and investigate differences in dynamical stability of different brain states, i.e. the dynamical response of a certain brain region to an external perturbation. After adjusting the whole-brain model parameters to reflect the dynamics of functional magnetic resonance imaging (fMRI) BOLD signals recorded under the influence of LSD or placebo, perturbations of different brain areas were simulated by either promoting or disrupting synchronization in the regarding brain region. After perturbation offset, we quantified the recovery characteristics of the brain area to its basal dynamical state with the Perturbational Integration Latency Index (PILI) and used this measure to distinguish between the two brain states. We found significant changes in dynamical complexity with consistently higher PILI values after LSD intake on a global level, which indicates a shift of the brain’s global working point further away from a stable equilibrium as compared to normal conditions. On a local level, we found that the largest differences were measured within the limbic network, the visual network and the default mode network. Additionally, we found a higher variability of PILI values across different brain regions after LSD intake, indicating higher response diversity under LSD after an external perturbation. Our results provide important new insights into the brain-wide dynamical changes underlying the psychedelic state - here provoked by LSD intake - and underline possible future clinical applications of psychedelic drugs in particular psychiatric disorders.HighlightsNovel offline perturbational method applied on functional magnetic resonance imaging (fMRI) data under the effect of lysergic acid diethylamide (LSD)Shift of brain’s global working point to more complex dynamics after LSD intakeConsistently longer recovery time after model perturbation under LSD influenceStrongest effects in resting state networks relevant for psychedelic experienceHigher response diversity across brain regions under LSD influence after an external in silico perturbation

Resting state functional magnetic resonance imaging processing techniques in stroke studies

2016 ◽  
Vol 27 (8) ◽  
pp. 871-885 ◽  
Author(s):  
Golrokh Mirzaei ◽  
Hojjat Adeli
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Connectivity ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Stroke Patients ◽  
Processing Techniques ◽  
The Brain

AbstractIn recent years, there has been considerable research interest in the study of brain connectivity using the resting state functional magnetic resonance imaging (rsfMRI). Studies have explored the brain networks and connection between different brain regions. These studies have revealed interesting new findings about the brain mapping as well as important new insights in the overall organization of functional communication in the brain network. In this paper, after a general discussion of brain networks and connectivity imaging, the brain connectivity and resting state networks are described with a focus on rsfMRI imaging in stroke studies. Then, techniques for preprocessing of the rsfMRI for stroke patients are reviewed, followed by brain connectivity processing techniques. Recent research on brain connectivity using rsfMRI is reviewed with an emphasis on stroke studies. The authors hope this paper generates further interest in this emerging area of computational neuroscience with potential applications in rehabilitation of stroke patients.

Sign in / Sign up

Export Citation Format

Share Document