Browsing by Subject "Functional magnetic resonance imaging"

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Open Access
BRAPH: A graph theory software for the analysis of brain connectivity
(Public Library of Science, 2017) Mijalkov, M.; Kakaei, E.; Pereira, J. B.; Westman, E.; Volpe, G.
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. © 2017 Mijalkov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
Effect of Covid-19 infection on the developing brain: psychosis proneness and working memory activation
(2022-08) Sozan, Sara Sinem
Researchers have been investigating the effects of Covid-19 infection since late 2019. Symptoms caused by the SARS-Cov-2 virus varied from respiratory system failure to fatigue, brain fog and headaches. Studies showed that the infection leads to cognitive impairment and psychotic-like symptoms even after recovery. Literature has focused on hospitalized adult patients, and there is less information on how the developing brain exposed to the virus is affected. To address these gaps in the literature we investigated whether Covid-19 can be a risk factor for psychosis in adolescents and young adults. Forty individuals who were infected with Covid-19 and recovered at least two and at most four months before and 36 demographically matched controls were recruited in the study. Positive PCR test results confirmed the infection status of the participants. Subclinical psychosis was assessed using the Community Assessment of Psychic Experience (CAPE-42) questionnaire and the Structured Interview of Schizotypy - Revised (SIS-R) was used to assess psychotic-like symptoms. A functional magnetic resonance imaging was conducted during a well-known working memory task to investigate activation patterns. The working memory task involved seven tasks and a control motor task. Verbal fluency performance was assessed in both phonetic and semantic categories. In order to control for the confounding effects of additional environmental risk factors for psychosis, paternal age, years of urban upbringing, cannabis exposure, and ethnicity were also considered. The findings revealed that although the two groups did not differ across different dimensions of the CAPE-42, the infected group had higher restricted affect and referential thoughts of being watched. Individuals infected with SARS-Cov-2 performed worse in both categories of the verbal fluency task. fMRI analysis revealed that individuals infected with the SARS-Cov-2 virus showed activation differences in the prefrontal cortex, medial temporal gyrus, middle frontal gyrus, and inferior parietal gyrus. Higher performance in the verbal fluency task predicted greater activation during the working memory task. These results suggest that exposure to the Covid-19 infection during brain development can be an environmental risk factor for psychosis.
Open Access
Functional changes in the human cortex over the course of visual perceptual learning
(2020-03) Akkoyunlu, Beyza
In this study we assessed functional changes through visual perceptual learning with bisection discrimination task. Before learning, after third session of learning and after learning ended, behavioral threshold and fMRI data has been collected. Our results showed that while participants showed threshold decrease in the midlearning session, the post-learning thresholds are turned to pre-learning levels. These results might be due to fatigue which caused by our experiment. Besides to training condition, we also tested location and task speciﬁcity. The results showed that only 150◦polar angle location showed signiﬁcant change between sessions. Along with the behavioral data, we collected task-based fMRI data while participants performing training and control conditions in the scanner. The analysis showed task-based BOLD response changed with session. However, post-hoc tests did not reveal signiﬁcant results. The resting-state functional connectivity analysis showed that the functional connectivity between V1 and V2 regions is signiﬁcantly increased. The Post Hoc analysis showed signiﬁcant change in the 210◦and 150◦polar angle conditions. The changes in the behavioral and functional connectivity measurements at 150◦polar angle conditions, these results might indicate the eﬀect of the inter-hemispheric connections. Moreover, our analysis on resting state data also revealed that, while there is no change between pre-learning and mid-learning sessions, connectivity changes signiﬁcantly in the post-learning session compared to other sessions. This ﬁnding supports the idea that functional connectivity changes related to perceptual learning might be occurring at the late phases of the learning. Overall, to rule out the confounds in the behavioral measurements and to link the behavioral data with the neural data, additional measurements should be taken in the future.
Open Access
It’s not the rule! rule-decodability is not limited to cognitive control-related frontoparietal regions
(2023-07) Gezici, Tamer
Performing tasks require us to abide and apply the relevant rules to the task (ie., do not wash white clothes with coloured clothes). As we perform tasks, these rules are maintained through cognitive control processes. Functional magnetic resonance imaging (fMRI) studies have shown that rule representations are decodable in a set of regions called the multiple demands (MD) network. Another set of regions called the default mode network (DMN) decorrelate with task-related networks. However, recent studies show that rule representations are decodable in tasknegative networks such as DMN as well. The present study investigated rule decodability using multivariate fMRI analysis methods. Subjects performed an event-related rule switch fMRI experiment in which there were two rules: categorizing numbers as even/odd (parity rule) or greater/smaller (value rule) than 10. In our first analysis, these two rules were modelled based on the switch or repeat status of the specific trial. We found that on switch trials, rules were decodable across the whole brain. In contrast, on repeat trials rules could not be decoded from any brain region. Curiously, repeat trials rule classification was significantly below chance, suggesting that training the classifier on one set of patterns made them worse than chance in classifying on the remaining set. This would happen if different instances of the same rule on repeat trials may have been accompanied by very different patterns of activity. In our second analysis we investigated if rule-related patterns changed with the number of consecutive repetitions or the number of consecutive switches, e.g., if the activity-pattern related to the parity rule on the first instance of a repeat trial was different from the pattern when this rule repeated again. We found that this was indeed the case. While the same rule could not be classified much across two consecutive switch trials, the same rule could be classified nearly everywhere across two consecutive repeat trials.
Open Access
Neural correlates of distorted body images in adolescent girls with anorexia nervosa: how is it different from major depressive disorder?
(John Wiley and Sons Ltd, 2023-06-28) Karakuş Aydos, Y.; Dövencioğlu, D.; Karlı Oğuz, Kader; Özdemir, P.; Pehlivantürk Kızılkan, M.; Kanbur, N.; Ünal, D.; Nalbant, K.; Çetin Çuhadaroğlu, F.; Akdemir, D.
Body image disturbance is closely linked to eating disorders including anorexia nervosa (AN). Distorted body image perception, dissatisfaction and preoccupation with weight and shape are often key factors in the development and maintenance of these disorders. Although the pathophysiological mechanism of body image disorder is not yet fully understood, aberrant biological processes may interfere with perceptive, cognitive and emotional aspects of body image. This study focuses on the neurobiological aspects of body image disturbance. The sample consisted of 12 adolescent girls diagnosed with AN, nine girls with major depressive disorder (MDD) and 10 without psychiatric diagnoses (HC, the healthy control group). We applied a block-design task in functional magnetic resonance imaging using participants' original and distorted overweight and underweight images. After imaging, the participants scored the images for resemblance, satisfaction and anxiety levels. The findings of this study demonstrate that overweight images elicited dissatisfaction and increased occipitotemporal activations across all participants. However, no difference was found between the groups. Furthermore, the MDD and HC groups showed increased activations in the prefrontal cortex and insula in response to underweight images compared to their original counterparts, whereas the AN group exhibited increased activations in the parietal cortex, cingulate gyrus and parahippocampal cortex in response to the same stimuli.
Open Access
Voxel-based state space modeling recovers task-related cognitive states in naturalistic fMRI experiments
(Frontiers Media S.A., 2021-05-06) Zhang, T.; Gao, J. S.; Çukur, Tolga; Gallant, J. L.
Complex natural tasks likely recruit many different functional brain networks, but it is difficult to predict how such tasks will be represented across cortical areas and networks. Previous electrophysiology studies suggest that task variables are represented in a low-dimensional subspace within the activity space of neural populations. Here we develop a voxel-based state space modeling method for recovering task-related state spaces from human fMRI data. We apply this method to data acquired in a controlled visual attention task and a video game task. We find that each task induces distinct brain states that can be embedded in a low-dimensional state space that reflects task parameters, and that attention increases state separation in the task-related subspace. Our results demonstrate that the state space framework offers a powerful approach for modeling human brain activity elicited by complex natural tasks.