scholarly journals Anxiety attenuates learning advantages conferred by statistical stability and induces loss of volatility-attuning in brain activity

2021 ◽  
Author(s):  
Elise G Rowe ◽  
Clare Harris ◽  
Ilvana Dzafic ◽  
Marta Garrido
Keyword(s):  
Neural Activity ◽  
Brain Activity ◽  
Stable Condition ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Environmental Stability ◽  
Statistical Stability ◽  
Behavioural Adaptation ◽  
Threat Of Shock

Anxiety can alter an individual's perception of their external sensory environment. Previous studies suggest that anxiety can increase the magnitude of neural responses to unexpected (or surprising) stimuli. Additionally, surprise responses are reported to be boosted during stable compared to volatile environments. Few studies, however, have examined how learning is impacted by both threat and volatility. To investigate these effects, we used threat-of-shock to transiently increase subjective anxiety in healthy adults during an auditory oddball task, in which the regularity could be stable or volatile, while undergoing functional Magnetic Resonance Imaging (fMRI) scanning. We then used Bayesian Model Selection (BMS) mapping to pinpoint the brain areas where different models of anxiety displayed the highest evidence. Behaviourally, we found that threat-of-shock eliminated the accuracy advantage conferred by environmental stability over volatility in the task at hand. Neurally, we found that threat-of-shock led to both attenuation and loss of volatility-attuning of neural activity evoked by surprising sounds across most subcortical and limbic brain regions including the thalamus, basal ganglia, claustrum, insula, anterior cingulate, hippocampal gyrus and also the superior temporal gyrus. Conversely, within two small clusters in the left medial frontal gyrus and extrastriate area, threat-of-shock boosted the neural activity (relative to the safe and volatile condition) to the levels observed during the safe and stable condition, while also inducing a loss of volatility-attuning. Taken together, our findings suggest that threat eliminates the learning advantage conferred by statistical stability compared to volatility. Thus, we propose that anxiety disrupts behavioural adaptation to environmental statistics, and that multiple subcortical and limbic regions are implicated in this process.

Abstract WMP117: Regional Homogeneity Changes In Patients With Transient Ischemic Attack: A Resting-state Functional Magnetic Resonance Imaging Study

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jian Guo ◽  
Ning Chen ◽  
Muke Zhou ◽  
Pian Wang ◽  
Li He
Keyword(s):  
Transient Ischemic Attack ◽  
Neural Activity ◽  
Resting State ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Imaging Study ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Anterior Cingulate ◽  
Ischemic Attack

Background: Transient ischemic attack (TIA) can increase the risk of some neurologic dysfunctions, of which the mechanism remains unclear. Resting-state functional MRI (rfMRI) is suggested to be a valuable tool to study the relation between spontaneous brain activity and behavioral performance. However, little is known about whether the local synchronization of spontaneous neural activity is altered in TIA patients. The purpose of this study is to detect differences in regional spontaneous activities throughout the whole brain between TIAs and normal controls. Methods: Twenty one TIA patients suffered an ischemic event in the right hemisphere and 21 healthy volunteers were enrolled in the study. All subjects were investigated using cognitive tests and rfMRI. The regional homogeneity (ReHo) was calculate and compared between two groups. Then a correlation analysis was performed to explore the relationship between ReHo values of brain regions showing abnormal resting-state properties and clinical variables in TIA group. Results: Compared with controls, TIA patients exhibited decreased ReHo in right dorsolateral prefrontal cortex (DLPFC), right inferior prefrontal gyrus, right ventral anterior cingulate cortex and right dorsal posterior cingular cortex. Moreover, the mean ReHo in right DLPFC and right inferior prefrontal gyrus were significantly correlated with MoCA in TIA patients. Conclusions: Neural activity in the resting state is changed in patients with TIA. The positive correlation between regional homogeneity of rfMRI and cognition suggests that ReHo may be a promising tool to better our understanding of the neurobiological consequences of TIA.

scholarly journals Peripheral arterial stiffness during electrocutaneous stimulation is positively correlated with pain-related brain activity and subjective pain intensity: an fMRI study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Toshio Tsuji ◽  
Fumiya Arikuni ◽  
Takafumi Sasaoka ◽  
Shin Suyama ◽  
Takashi Akiyoshi ◽  
...  
Keyword(s):  
Arterial Stiffness ◽  
Pain Intensity ◽  
Brain Activity ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Electrocutaneous Stimulation ◽  
Pain Matrix ◽  
Fmri Study ◽  
Subjective Pain ◽  
Peripheral Arterial

AbstractBrain activity associated with pain perception has been revealed by numerous PET and fMRI studies over the past few decades. These findings helped to establish the concept of the pain matrix, which is the distributed brain networks that demonstrate pain-specific cortical activities. We previously found that peripheral arterial stiffness $${\beta }_{\text{art}}$$ β art responds to pain intensity, which is estimated from electrocardiography, continuous sphygmomanometer, and photo-plethysmography. However, it remains unclear whether and to what extent $${\beta }_{\text{art}}$$ β art aligns with pain matrix brain activity. In this fMRI study, 22 participants received different intensities of pain stimuli. We identified brain regions in which the blood oxygen level-dependent signal covaried with $${\beta }_{\text{art}}$$ β art using parametric modulation analysis. Among the identified brain regions, the lateral and medial prefrontal cortex and ventral and dorsal anterior cingulate cortex were consistent with the pain matrix. We found moderate correlations between the average activities in these regions and $${\beta }_{\text{art}}$$ β art (r = 0.47, p < 0.001). $${\beta }_{\text{art}}$$ β art was also significantly correlated with self-reported pain intensity (r = 0.44, p < 0.001) and applied pain intensity (r = 0.43, p < 0.001). Our results indicate that $${\beta }_{\text{art}}$$ β art is positively correlated with pain-related brain activity and subjective pain intensity. This study may thus represent a basis for adopting peripheral arterial stiffness as an objective pain evaluation metric.

Acetaminophen Reduces Social Pain

2010 ◽  
Vol 21 (7) ◽  
pp. 931-937 ◽  
Author(s):  
C. Nathan DeWall ◽  
Geoff MacDonald ◽  
Gregory D. Webster ◽  
Carrie L. Masten ◽  
Roy F. Baumeister ◽  
...  
Keyword(s):  
Brain Activity ◽  
Brain Regions ◽  
Daily Basis ◽  
Social Rejection ◽  
Neural Mechanisms ◽  
Anterior Cingulate ◽  
Neural Responses ◽  
Physical Pain ◽  
Social Pain ◽  
Dorsal Anterior Cingulate Cortex

Pain, whether caused by physical injury or social rejection, is an inevitable part of life. These two types of pain—physical and social—may rely on some of the same behavioral and neural mechanisms that register pain-related affect. To the extent that these pain processes overlap, acetaminophen, a physical pain suppressant that acts through central (rather than peripheral) neural mechanisms, may also reduce behavioral and neural responses to social rejection. In two experiments, participants took acetaminophen or placebo daily for 3 weeks. Doses of acetaminophen reduced reports of social pain on a daily basis (Experiment 1). We used functional magnetic resonance imaging to measure participants’ brain activity (Experiment 2), and found that acetaminophen reduced neural responses to social rejection in brain regions previously associated with distress caused by social pain and the affective component of physical pain (dorsal anterior cingulate cortex, anterior insula). Thus, acetaminophen reduces behavioral and neural responses associated with the pain of social rejection, demonstrating substantial overlap between social and physical pain.

scholarly journals Neuronal Substrates Underlying Performance Variability in Well-Trained Skillful Motor Task in Humans

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Nobuaki Mizuguchi ◽  
Shintaro Uehara ◽  
Satoshi Hirose ◽  
Shinji Yamamoto ◽  
Eiichi Naito
Keyword(s):  
Task Performance ◽  
Motor Skill ◽  
Brain Activity ◽  
Motor Task ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Cerebellar Hemisphere ◽  
Intensive Training ◽  
Performance Variability ◽  
The Right

Motor performance fluctuates trial by trial even in a well-trained motor skill. Here we show neural substrates underlying such behavioral fluctuation in humans. We first scanned brain activity with functional magnetic resonance imaging while healthy participants repeatedly performed a 10 s skillful sequential finger-tapping task. Before starting the experiment, the participants had completed intensive training. We evaluated task performance per trial (number of correct sequences in 10 s) and depicted brain regions where the activity changes in association with the fluctuation of the task performance across trials. We found that the activity in a broader range of frontoparietocerebellar network, including the bilateral dorsolateral prefrontal cortex (DLPFC), anterior cingulate and anterior insular cortices, and left cerebellar hemisphere, was negatively correlated with the task performance. We further showed in another transcranial direct current stimulation (tDCS) experiment that task performance deteriorated, when we applied anodal tDCS to the right DLPFC. These results indicate that fluctuation of brain activity in the nonmotor frontoparietocerebellar network may underlie trial-by-trial performance variability even in a well-trained motor skill, and its neuromodulation with tDCS may affect the task performance.

Reconstruction of Neural Activity from EEG Data Using Dynamic Spatiotemporal Constraints

2016 ◽  
Vol 26 (07) ◽  
pp. 1650026 ◽  
Author(s):  
E. Giraldo-Suarez ◽  
J. D. Martinez-Vargas ◽  
G. Castellanos-Dominguez
Keyword(s):  
Spatial Resolution ◽  
Neural Activity ◽  
Focal Epilepsy ◽  
Experimental Testing ◽  
Brain Activity ◽  
Brain Regions ◽  
Basis Set ◽  
Eeg Signals ◽  
Reconstruction Performance ◽  
Eeg Data

We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period. Moreover, to deal with applications that have either distributed or localized neural activity, the spatiotemporal constraints are expressed through [Formula: see text] and [Formula: see text] norms, respectively. For the purpose of validation, we estimate the neural reconstruction performance in time and space separately. Experimental testing is carried out on artificial data, simulating stationary and non-stationary EEG signals. Also, validation is accomplished on two real-world databases, one holding Evoked Potentials and another with EEG data of focal epilepsy. Moreover, responses of functional magnetic resonance imaging for the former EEG data have been measured in advance, allowing to contrast our findings. Obtained results show that the [Formula: see text]-based IRA produces a spatial resolution that is comparable to the one achieved by some widely used sparse-based estimators of brain activity. At the same time, the [Formula: see text]-based IRA outperforms other similar smooth solutions, providing a spatial resolution that is lower than the sparse [Formula: see text]-based solution. As a result, the proposed IRA is a promising method for improving the accuracy of brain activity reconstruction.

scholarly journals Meta-analysis of resting-state fMRI in depression: generating spatial hypotheses for potential clinical applications

2014 ◽  
Author(s):  
Benedikt Sundermann ◽  
Mona Olde lütke Beverborg ◽  
Bettina Pfleiderer
Keyword(s):  
Resting State ◽  
Spatial Information ◽  
Brain Activity ◽  
Meta Analysis ◽  
Likelihood Estimation ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Diagnostic Classification Models ◽  
Spontaneous Brain Activity

Information derived from functional magnetic resonance imaging (fMRI) during wakeful rest has been introduced as a candidate diagnostic biomarker in unipolar major depressive disorder (MDD). Multiple reports of resting state fMRI in MDD describe group effects. Such prior knowledge can be adopted to pre-select potentially discriminating features, for example for diagnostic classification models with the aim to improve diagnostic accuracy. Purpose of this analysis was to consolidate spatial information about alterations of spontaneous brain activity in MDD to serve such feature selection and as a secondary aim to improve understanding of disease mechanisms. 32 studies were included in final analyses. Coordinates extracted from the original reports were assigned to two categories based on directionality of findings. Meta-analyses were calculated using the non-additive activation likelihood estimation approach with coordinates organized by subject group to account for non-independent samples. Results were compared with established resting state networks (RSNs) and spatial representations of recently introduced temporally independent functional modes (TFMs) of spontaneous brain activity. Converging evidence revealed a distributed pattern of brain regions with increased or decreased spontaneous activity in MDD. The most distinct finding was hyperactivity/ hyperconnectivity presumably reflecting the interaction of cortical midline structures (posterior default mode network components associated with self-referential processing and the subgenual anterior cingulate cortex) with lateral frontal areas related to externally-directed cognition. One particular TFM seems to better comprehend the findings than classical RSNs. Alterations that can be captured by resting state fMRI show considerable overlap with those identifiable with other neuroimaging modalities though differing in some aspects.

scholarly journals Mapping Pavlovian Conditioning Effects on the Brain: Blocking, Contiguity, and Excitatory Effects

2001 ◽  
Vol 86 (2) ◽  
pp. 809-823 ◽  
Author(s):  
Dirk Jones ◽  
F. Gonzalez-Lima
Keyword(s):  
Pavlovian Conditioning ◽  
Large Scale ◽  
Brain Activity ◽  
Brain Regions ◽  
Blocking Effect ◽  
Anterior Cingulate ◽  
Caudate Putamen ◽  
Fdg Uptake ◽  
The Brain ◽  
Previous Learning

Pavlovian conditioning effects on the brain were investigated by mapping rat brain activity with fluorodeoxyglucose (FDG) autoradiography. The goal was to map the effects of the same tone after blocking or eliciting a conditioned emotional response (CER). In the tone-blocked group, previous learning about a light blocked a CER to the tone. In the tone-excitor group, the same pairings of tone with shock US resulted in a CER to the tone in the absence of previous learning about the light. A third group showed no CER after pseudorandom presentations of these stimuli. Brain systems involved in the various associative effects of Pavlovian conditioning were identified, and their functional significance was interpreted in light of previous FDG studies. Three conditioning effects were mapped: 1) blocking effects: FDG uptake was lower in medial prefrontal cortex and higher in spinal trigeminal and cuneate nuclei in the tone-blocked group relative to the tone-excitor group. 2) Contiguity effects: relative to pseudorandom controls, similar FDG uptake increases in the tone-blocked and -excitor groups were found in auditory regions (inferior colliculus and cortex), hippocampus (CA1), cerebellum, caudate putamen, and solitary nucleus. Contiguity effects may be due to tone-shock pairings common to the tone-blocked and -excitor groups rather than their different CER. And 3) excitatory effects: FDG uptake increases limited to the tone-excitor group occurred in a circuit linked to the CER, including insular and anterior cingulate cortex, vertical diagonal band nucleus, anterior hypothalamus, and caudoventral caudate putamen. This study provided the first large-scale map of brain regions underlying the Kamin blocking effect on conditioning. In particular, the results suggest that suppression of prefrontal activity and activation of unconditioned stimulus pathways are important neural substrates of the Kamin blocking effect.

Responses to Rare Visual Target and Distractor Stimuli Using Event-Related fMRI

2000 ◽  
Vol 83 (5) ◽  
pp. 3133-3139 ◽  
Author(s):  
Vincent P. Clark ◽  
Sean Fannon ◽  
Song Lai ◽  
Randall Benson ◽  
Lance Bauer
Keyword(s):  
Brain Activity ◽  
Temporal Cortex ◽  
Stimulus Presentation ◽  
Brain Regions ◽  
Event Related Potential ◽  
Anterior Cingulate ◽  
Fmri Signal ◽  
Fmri Study ◽  
Evoked Activity ◽  
Anatomic Locations

Previous studies have found that the P300 or P3 event-related potential (ERP) component is useful in the diagnosis and treatment of many disorders that influence CNS function. However, the anatomic locations of brain regions involved in this response are not precisely known. In the present event-related functional magnetic resonance imaging (fMRI) study, methods of stimulus presentation, data acquisition, and data analysis were optimized for the detection of brain activity in response to stimuli presented in the three-stimulus oddball task. This paradigm involves the interleaved, pseudorandom presentation of single block-letter target and distractor stimuli that previously were found to generate the P3b and P3a ERP subcomponents, respectively, and frequent standard stimuli. Target stimuli evoked fMRI signal increases in multiple brain regions including the thalamus, the bilateral cerebellum, and the occipital-temporal cortex as well as bilateral superior, medial, inferior frontal, inferior parietal, superior temporal, precentral, postcentral, cingulate, insular, left middle temporal, and right middle frontal gyri. Distractor stimuli evoked an fMRI signal change bilaterally in inferior anterior cingulate, medial frontal, inferior frontal, and right superior frontal gyri, with additional activity in bilateral inferior parietal lobules, lateral cerebellar hemispheres and vermis, and left fusiform, middle occipital, and superior temporal gyri. Significant variation in the amplitude and polarity of distractor-evoked activity was observed across stimulus repetitions. No overlap was observed between target- and distractor-evoked activity. These event-related fMRI results shed light on the anatomy of responses to target and distractor stimuli that have proven useful in many ERP studies of healthy and clinically impaired populations.

scholarly journals Reduced gray matter volume in the anterior cingulate, orbitofrontal cortex and thalamus as a function of mild depressive symptoms: a voxel-based morphometric analysis

2014 ◽  
Vol 44 (13) ◽  
pp. 2833-2843 ◽  
Author(s):  
C. A. Webb ◽  
M. Weber ◽  
E. A. Mundy ◽  
W. D. S. Killgore
Keyword(s):  
Depressive Symptoms ◽  
Gray Matter ◽  
Orbitofrontal Cortex ◽  
Gray Matter Volume ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Dimensional Approach ◽  
Matter Volume ◽  
Conjunction Analysis

BackgroundStudies investigating structural brain abnormalities in depression have typically employed a categorical rather than dimensional approach to depression [i.e. comparing subjects with Diagnostic and Statistical Manual of Mental Disorders (DSM)-defined major depressive disorder (MDD)v. healthy controls]. The National Institute of Mental Health, through their Research Domain Criteria initiative, has encouraged a dimensional approach to the study of psychopathology as opposed to an over-reliance on categorical (e.g. DSM-based) diagnostic approaches. Moreover, subthreshold levels of depressive symptoms (i.e. severity levels below DSM criteria) have been found to be associated with a range of negative outcomes, yet have been relatively neglected in neuroimaging research.MethodTo examine the extent to which depressive symptoms – even at subclinical levels – are linearly related to gray matter volume reductions in theoretically important brain regions, we employed whole-brain voxel-based morphometry in a sample of 54 participants.ResultsThe severity of mild depressive symptoms, even in a subclinical population, was associated with reduced gray matter volume in the orbitofrontal cortex, anterior cingulate, thalamus, superior temporal gyrus/temporal pole and superior frontal gyrus. A conjunction analysis revealed concordance across two separate measures of depression.ConclusionsReduced gray matter volume in theoretically important brain regions can be observed even in a sample that does not meet DSM criteria for MDD, but who nevertheless report relatively elevated levels of depressive symptoms. Overall, these findings highlight the need for additional research using dimensional conceptual and analytic approaches, as well as further investigation of subclinical populations.

Default-Mode Activity during a Passive Sensory Task: Uncoupled from Deactivation but Impacting Activation

2004 ◽  
Vol 16 (9) ◽  
pp. 1484-1492 ◽  
Author(s):  
Michael D. Greicius ◽  
Vinod Menon
Keyword(s):  
Episodic Memory ◽  
Cognitive Processing ◽  
Neural Activity ◽  
Default Mode Network ◽  
Brain Activity ◽  
Block Design ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
High Demand ◽  
Default Mode

Deactivation refers to increased neural activity during low-demand tasks or rest compared with high-demand tasks. Several groups have reported that a particular set of brain regions, including the posterior cingulate cortex and the medial prefrontal cortex, among others, is consistently deactivated. Taken together, these typically deactivated brain regions appear to constitute a default-mode network of brain activity that predominates in the absence of a demanding external task. Examining a passive, block-design sensory task with a standard deactivation analysis (rest epochs vs. stimulus epochs), we demonstrate that the default-mode network is undetectable in one run and only partially detectable in a second run. Using independent component analysis, however, we were able to detect the full default-mode network in both runs and to demonstrate that, in the majority of subjects, it persisted across both rest and stimulus epochs, uncoupled from the task waveform, and so mostly undetectable as deactivation. We also replicate an earlier finding that the default-mode network includes the hippocampus suggesting that episodic memory is incorporated in default-mode cognitive processing. Furthermore, we show that the more a subject's default-mode activity was correlated with the rest epochs (and “deactivated” during stimulus epochs), the greater that subject's activation to the visual and auditory stimuli. We conclude that activity in the default-mode network may persist through both experimental and rest epochs if the experiment is not sufficiently challenging. Time-series analysis of default-mode activity provides a measure of the degree to which a task engages a subject and whether it is sufficient to interrupt the processes—presumably cognitive, internally generated, and involving episodic memory—mediated by the default-mode network.

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