scholarly journals Did I imagine that? The functional role of paracingulate cortex in reality monitoring

2020 ◽  
Author(s):  
JR Garrison ◽  
F Saviola ◽  
E Morgenroth ◽  
H Barker ◽  
Michael Lührs ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Real Time ◽  
Brain Activity ◽  
Occipital Cortex ◽  
Reality Monitoring ◽  
Monitoring Networks ◽  
Healthy Individuals ◽  
Resting State Functional Connectivity ◽  
Monitoring Accuracy

AbstractReality monitoring describes our ability to distinguish between internally and externally generated experiences. Individuals show significant variation in this ability and impaired reality monitoring has been linked to the experience of hallucinations. We undertook two studies to investigate the association between reality monitoring and morphology of the paracingulate region of medial prefrontal cortex. In Study 1 we compared reality monitoring accuracy and functional connectivity within paracingulate cortex in groups of healthy controls (N=20) and patients with schizophrenia and hallucinations (N=19). Controls showed greater reality monitoring accuracy that was associated with resting-state functional connectivity between paracingulate, precuneus and occipital cortices, while reality monitoring in patients was associated with more lateral functional connectivity. In Study 2 we used real-time fMRI neurofeedback to obtain causal evidence for the role of the paracingulate cortex in reality monitoring. Healthy individuals received Active feedback from paracingulate cortex (N=21) or Sham feedback based on randomised signal (N=18). Active-group participants showed a specific behavioural effect of improved reality monitoring for Imagined items, as well as increases in both activity within the paracingulate region, and its posterior functional connectivity with precuneus and lateral parietal cortices, and occipital cortex.Our findings suggest reality monitoring in healthy individuals is causally supported by a paracingulate mediated flexible network including the precuneus. Network connectivity can be enhanced using neurofeedback and tracks with improved reality monitoring ability. In contrast, patients with schizophrenia may utilise a distinct and more lateral network which may explain observed sub-optimal reality monitoring accuracy, contributing to the experience of hallucinations.Significance StatementReality monitoring refers to our ability to distinguish imagination from our experiences in the outside world, and is linked both to hallucinations in schizophrenia as well as to the morphology of paracingulate cortex area of the brain. Here, we revealed less paracingulate involvement in the functional reality monitoring networks in patients with schizophrenia compared to healthy individuals. Thereafter, we used real-time fMRI neurofeedback to show that healthy individuals can learn to upregulate brain activity within the paracingulate cortex, with this resulting in both improved reality monitoring ability and changes in paracingulate functional connectivity. This suggests that paracingulate cortex activity and connectivity play a causal role in reality monitoring, with implications for both the understanding and treatment of hallucinations.

scholarly journals A distinctive neural nexus in blind individuals supports Braille reading

2021 ◽  
Author(s):  
Ruxue WANG ◽  
Jiangtao GONG ◽  
Chenying ZHAO ◽  
Yingqing XU ◽  
Bo HONG
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Frontal Cortex ◽  
Reading Proficiency ◽  
Occipital Cortex ◽  
Resting State Functional Connectivity ◽  
Crossmodal Plasticity ◽  
Blind Individuals ◽  
Language Areas

In the absence of visual input, occipital 'visual' cortex of blind people has been found to be engaged in non-visual higher cognitive tasks. Although the increased functional connectivity between 'visual' cortex and frontal cortex in the blind has been observed, the specific organization and functional role of this connectivity change remain to be elucidated. Here, we tested resting-state functional connectivity for primary 'visual' cortex (V1) and higher-tier lateral occipital cortex (LOC) in people with acquired blindness, and found an enhanced connectivity between the LOC but not V1 and typical frontal language areas - the inferior frontal cortex (IFC). In fact, the left-lateralized LOC-IFC connectivity strength predicted blind individuals' natural Braille reading proficiency. Furthermore, an increased bidirectional information flow between the left LOC and IFC was observed during a natural Braille reading task. In particular, the task-relevant modulation of the top-down communication from left IFC to LOC was significantly stronger than that of the bottom-up communication. Altogether, our study identified a distinctive neural nexus, LOC-IFC connection, and its behavioral significance in the acquired blind, revealing the neural correlates of the crossmodal plasticity in their 'visual' cortex underlying natural Braille reading.

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.

Correlations Between the DMN and the Smoking Cessation Outcome of a Real-Time fMRI Neurofeedback Supported Exploratory Therapy Approach: Descriptive Statistics on Tobacco-Dependent Patients

2021 ◽  
pp. 155005942110627
Author(s):  
Marco Paolini ◽  
Daniel Keeser ◽  
Boris-Stephan Rauchmann ◽  
Sarah Gschwendtner ◽  
Hannah Jeanty ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Functional Connectivity ◽  
Real Time ◽  
Smoking Status ◽  
Connectivity Pattern ◽  
Resting State Functional Connectivity ◽  
Correlation Pattern ◽  
Early Withdrawal ◽  
Seed Analysis ◽  
Negative Coupling

The aim of this study was to explore the potential of default mode network (DMN) functional connectivity for predicting the success of smoking cessation in patients with tobacco dependence in the context of a real-time function al MRI (RT-fMRI) neurofeedback (NF) supported therapy. Fifty-four tobacco-dependent patients underwent three RT-fMRI-NF sessions including resting-state functional connectivity (RSFC) runs over a period of 4 weeks during professionally assisted smoking cessation. Patients were randomized into two groups that performed either active NF of an addiction-related brain region or sham NF. After preprocessing, the RSFC baseline data were statistically evaluated using seed-based ROI (SBA) approaches taking into account the smoking status of patients after 3 months (abstinence/relapse). The results of the real study group showed a widespread functional connectivity in the relapse subgroup (n = 10) exceeding the DMN template and mainly low correlations and anticorrelations in the within-seed analysis. In contrast, the connectivity pattern of the abstinence subgroup (n = 8) primarily contained the core DMN in the seed-to-whole-brain analysis and a left lateralized correlation pattern in the within-seed analysis. Calculated Multi-Subject Dictionary Learning (MSDL) matrices showed anticorrelations between DMN regions and salience regions in the abstinence group. Concerning the sham group, results of the relapse subgroup (n = 4) and the abstinence subgroup (n = 6) showed similar trends only in the within-seed analysis. In the setting of a RT-fMRI-NF-assisted therapy, a widespread intrinsic DMN connectivity and a low negative coupling between the DMN and the salience network (SN) in patients with tobacco dependency during early withdrawal may be useful as an early indicator of later therapy nonresponse.

scholarly journals On the role of the corpus callosum in interhemispheric functional connectivity in humans

2017 ◽  
Vol 114 (50) ◽  
pp. 13278-13283 ◽  
Author(s):  
Jarod L. Roland ◽  
Abraham Z. Snyder ◽  
Carl D. Hacker ◽  
Anish Mitra ◽  
Joshua S. Shimony ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Corpus Callosum ◽  
Parietal Lobe ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Limited Sample ◽  
Temporal Correlations ◽  
Before And After

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity.

Role of local network oscillations in resting-state functional connectivity

NeuroImage ◽  
2011 ◽  
Vol 57 (1) ◽  
pp. 130-139 ◽  
Author(s):  
Joana Cabral ◽  
Etienne Hugues ◽  
Olaf Sporns ◽  
Gustavo Deco
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Local Network ◽  
Resting State Functional Connectivity ◽  
Network Oscillations

scholarly journals Predicting Individual Variability in Task-Evoked Brain Activity in Schizophrenia

2020 ◽  
Author(s):  
Niv Tik ◽  
Abigail Livny ◽  
Shachar Gal ◽  
Karny Gigi ◽  
Galia Tsarfaty ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Prediction Model ◽  
Resting State ◽  
Brain Activity ◽  
Strong Association ◽  
Brain Activation ◽  
Individual Variability ◽  
Resting State Functional Connectivity ◽  
Successful Prediction ◽  
And Task

AbstractBACKGROUNDPatients suffering from schizophrenia demonstrate abnormal brain activity, as well as alterations in patterns of functional connectivity assessed by functional magnetic resonance imaging (fMRI). Previous studies in healthy participants suggest a strong association between resting-state functional connectivity and task-evoked brain activity that could be detected at an individual level, and show that brain activation in various tasks could be predicted from task-free fMRI scans. In the current study we aimed to predict brain activity in patients diagnosed with schizophrenia, using a prediction model based on healthy individuals exclusively. This offers novel insights regarding the interrelations between brain connectivity and activity in schizophrenia.METHODSWe generated a prediction model using a group of 80 healthy controls that performed the well-validated N-back task, and used it to predict individual variability in task-evoked brain activation in 20 patients diagnosed with schizophrenia.RESULTSWe demonstrated a successful prediction of individual variability in the task-evoked brain activation based on resting-state functional connectivity. The predictions were highly sensitive, reflected by high correlations between predicted and actual activation maps (Median = 0.589, SD = 0.193) and specific, evaluated by a Kolomogrov-Smirnov test (D = 0.25, p < 0.0001).CONCLUSIONSA Successful prediction of brain activity from resting-state functional connectivity highlights the strong coupling between the two. Moreover, our results support the notion that even though resting-state functional connectivity and task-evoked brain activity are frequently reported to be altered in schizophrenia, the relations between them remains unaffected. This may allow to generate task activity maps for clinical populations without the need the actually perform the task.

scholarly journals Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity

2019 ◽  
Vol 3 (2) ◽  
pp. 427-454 ◽  
Author(s):  
David M. Lydon-Staley ◽  
Rastko Ciric ◽  
Theodore D. Satterthwaite ◽  
Danielle S. Bassett
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Systematic Evaluation ◽  
Resting State Functional Connectivity ◽  
Multilayer Network ◽  
Dynamic Functional Connectivity ◽  
Spontaneous Brain Activity ◽  
Global Signal ◽  
Health And Disease ◽  
Modularity Maximization

Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly used participant-level confound regression strategies designed to mitigate the effects of micromovements in a sample of 393 youths (ages 8–22 years). Each strategy was evaluated according to a number of benchmarks, including (a) the residual association between participant motion and edge dispersion, (b) distance-dependent effects of motion on edge dispersion, (c) the degree to which functional subnetworks could be identified by multilayer modularity maximization, and (d) measures of module reconfiguration, including node flexibility and node promiscuity. Results indicate variability in the effectiveness of the evaluated pipelines across benchmarks. Methods that included global signal regression were the most consistently effective de-noising strategies.

scholarly journals The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug-related and natural-reward stimuli

2020 ◽  
Author(s):  
Lauren D. Hill-Bowen ◽  
Michael C. Riedel ◽  
Ranjita Poudel ◽  
Taylor Salo ◽  
Jessica S. Flannery ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Activity ◽  
Cue Reactivity ◽  
Dorsal Striatum ◽  
Brain Regions ◽  
Reward Processing ◽  
Resting State Functional Connectivity ◽  
Addictive Disorders ◽  
Natural Reward ◽  
Elemental Nature

ABSTRACTBackgroundThe cue-reactivity paradigm is a widely adopted neuroimaging probe assessing brain activity linked to attention, memory, emotion, and reward processing associated with the presentation of appetitive stimuli. Lacking, is the apperception of more precise brain regions, neurocircuits, and mental operations comprising cue-reactivity’s multi-elemental nature. To resolve such complexities, we employed emergent meta-analytic techniques to enhance insight into drug and natural cue-reactivity in the brain.MethodsOperating from this perspective, we first conducted multiple coordinate-based meta-analyses to define common and distinct brain regions showing convergent activation across studies involving drug-related and natural-reward cue-reactivity paradigms. In addition, we examined the activation profiles of each convergent brain region linked to cue-reactivity as seeds in task-dependent and task-independent functional connectivity analyses. Using methods to cluster regions of interest, we categorized cue-reactivity into cliques, or sub-networks, based on the functional similarities between regions. Cliques were further classified with psychological constructs.ResultsWe identified a total of 164 peer-reviewed articles: 108 drug-related, and 56 natural-reward. When considering cue-reactivity collectively, across both drug and natural studies, activity convergence was observed in the dorsal striatum, limbic, insula, parietal, occipital, and temporal regions. Common convergent neural activity between drug and natural cue-reactivity was observed in the caudate, amygdala, thalamus, cingulate, and temporal regions. Drug distinct convergence was observed in the putamen, cingulate, and temporal regions, while natural distinct convergence was observed in the caudate, parietal, occipital, and frontal regions. We seeded identified cue-reactivity regions in meta-analytic connectivity modeling and resting-state functional connectivity analyses. Consensus hierarchical clustering of both connectivity analyses identified six distinct cliques that were further functionally characterized using the BrainMap and Neurosynth databases.ConclusionsWe examined the multifaceted nature of cue-reactivity and decomposed this construct into six elements of visual, executive function, sensorimotor, salience, emotion, and self-referential processing. Further, we demonstrated that these elements are supported by perceptual, sensorimotor, tripartite, and affective networks, which are essential to understanding the neural mechanisms involved in the development and or maintenance of addictive disorders.

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