scholarly journals Human Brain Activity Predicts Individual Differences in Prior Knowledge Use during Decisions

2012 ◽  
Vol 24 (6) ◽  
pp. 1462-1475 ◽  
Author(s):  
Kathleen A. Hansen ◽  
Sarah F. Hillenbrand ◽  
Leslie G. Ungerleider
Keyword(s):  
Prior Knowledge ◽  
Brain Activity ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Anterior Insula ◽  
Activity Levels ◽  
Knowledge Use ◽  
Ample Evidence ◽  
Tuning Curves ◽  
Abstract Shapes

Studies by cognitive psychologists, psychophysicists, neuroscientists, and economists provide ample evidence that humans use prior knowledge to bias decisions adaptively. In this study, we sought to locate and investigate the brain areas mediating this behavior. Participants viewed ambiguous abstract shapes and decided whether a shape was of Category A (smoother) or B (bumpier). The decision was made in the context of one of two prior knowledge cues, 80/20 and 50/50. The 80/20 cue indicated that upcoming shapes had an 80% probability of being of one category, for example, B, and a 20% probability of being of the other. The 50/50 cue indicated that upcoming shapes had an equal probability of being of either category. The shift in bias produced by the 80/20 cue relative to the 50/50 cue was of the predicted sign for every subject but varied in magnitude. We searched for brain regions in which activity changes correlated with the extent of the bias shift; these were dorsolateral pFC (middle frontal gyrus), inferior frontal junction, anterior insula, inferior parietal lobule, intraparietal sulcus, head of the caudate, posterior cingulate cortex, and fusiform gyrus. The findings indicate that an individual's brain activity in these regions reflects the extent to which that individual makes use of prior knowledge to bias decisions. We also created within-ROI tuning curves by binning the shape curvature levels and plotting brain activity levels at each of the nine bins. In the fronto-parietal and anterior insula ROIs, the tuning curves peaked at targets contraindicated by the prior knowledge cue (e.g., Category B targets if the 80/20 cue meant 20% probability B). The increased activity in these regions likely indicates a no-go response when sufficient perceptual evidence favored the alternative contraindicated by the 80/20 cue.

scholarly journals Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

2021 ◽  
Author(s):  
Takashi Nakano ◽  
Masahiro Takamura ◽  
Haruki Nishimura ◽  
Maro Machizawa ◽  
Naho Ichikawa ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Fmri Data ◽  
Independent Test ◽  
The Individual ◽  
The Brain

AbstractNeurofeedback (NF) aptitude, which refers to an individual’s ability to change its brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical NF applications. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude independent of NF-targeting brain regions. We combined the data in fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect the resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Next we validated the prediction model using independent test data from another site. The result showed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting NF aptitude may be involved in the attentional mode-orientation modulation system’s characteristics in task-free resting-state brain activity.

scholarly journals A functional MRI study of presurgical cognitive deficits in glioma patients

2020 ◽  
Author(s):  
Irena T Schouwenaars ◽  
Miek J de Dreu ◽  
Geert-Jan M Rutten ◽  
Nick F Ramsey ◽  
Johan M Jansma
Keyword(s):  
Functional Mri ◽  
Cognitive Deficits ◽  
Brain Activity ◽  
Neuropsychological Testing ◽  
Region Of Interest ◽  
High Grade Glioma ◽  
Brain Regions ◽  
Brain State ◽  
Low Grade ◽  
Activity Levels

Abstract Background The main goal of this functional MRI (fMRI) study was to examine whether cognitive deficits in glioma patients prior to treatment are associated with abnormal brain activity in either the central executive network (CEN) or default mode network (DMN). Methods Forty-six glioma patients, and 23 group-matched healthy controls (HCs) participated in this fMRI experiment, performing an N-back task. Additionally, cognitive profiles of patients were evaluated outside the scanner. A region of interest–based analysis was used to compare brain activity in CEN and DMN between groups. Post hoc analyses were performed to evaluate differences between low-grade glioma (LGG) and high-grade glioma (HGG) patients. Results In-scanner performance was lower in glioma patients compared to HCs. Neuropsychological testing indicated cognitive impairment in LGG as well as HGG patients. fMRI results revealed normal CEN activation in glioma patients, whereas patients showed reduced DMN deactivation compared to HCs. Brain activity levels did not differ between LGG and HGG patients. Conclusions Our study suggests that cognitive deficits in glioma patients prior to treatment are associated with reduced responsiveness of the DMN, but not with abnormal CEN activation. These results suggest that cognitive deficits in glioma patients reflect a reduced capacity to achieve a brain state necessary for normal cognitive performance, rather than abnormal functioning of executive brain regions. Solely focusing on increases in brain activity may well be insufficient if we want to understand the underlying brain mechanism of cognitive impairments in patients, as our results indicate the importance of assessing deactivation.

scholarly journals Differences in Brain Activity during a Verbal Associative Memory Encoding Task in High- and Low-fit Adolescents

2013 ◽  
Vol 25 (4) ◽  
pp. 595-612 ◽  
Author(s):  
Megan M. Herting ◽  
Bonnie J. Nagel
Keyword(s):  
Aerobic Fitness ◽  
Brain Function ◽  
Brain Activity ◽  
Memory Performance ◽  
Neural Circuitry ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Memory Encoding ◽  
Medial Pfc

Aerobic fitness is associated with better memory performance as well as larger volumes in memory-related brain regions in children, adolescents, and elderly. It is unclear if aerobic exercise also influences learning and memory functional neural circuitry. Here, we examine brain activity in 17 high-fit (HF) and 17 low-fit (LF) adolescents during a subsequent memory encoding paradigm using fMRI. Despite similar memory performance, HF and LF youth displayed a number of differences in memory-related and default mode (DMN) brain regions during encoding later remembered versus forgotten word pairs. Specifically, HF youth displayed robust deactivation in DMN areas, including the ventral medial PFC and posterior cingulate cortex, whereas LF youth did not show this pattern. Furthermore, LF youth showed greater bilateral hippocampal and right superior frontal gyrus activation during encoding of later remembered versus forgotten word pairs. Follow-up task-dependent functional correlational analyses showed differences in hippocampus and DMN activity coupling during successful encoding between the groups, suggesting aerobic fitness during adolescents may impact functional connectivity of the hippocampus and DMN during memory encoding. To our knowledge, this study is the first to examine the influence of aerobic fitness on hippocampal function and memory-related neural circuitry using fMRI. Taken together with previous research, these findings suggest aerobic fitness can influence not only memory-related brain structure, but also brain function.

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.

scholarly journals Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

2020 ◽  
Author(s):  
Amelie Haugg ◽  
Ronald Sladky ◽  
Stavros Skouras ◽  
Amalia McDonald ◽  
Cameron Craddock ◽  
...  
Keyword(s):  
Real Time ◽  
Clinical Symptoms ◽  
Brain Activity ◽  
Treatment Success ◽  
Self Regulation ◽  
Brain Regions ◽  
Activity Levels ◽  
Success Predictors ◽  
Learning Success ◽  
Study Database

AbstractNeurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

scholarly journals Comparison of Four fMRI Paradigms Probing Emotion Processing

2021 ◽  
Vol 11 (5) ◽  
pp. 525
Author(s):  
Corinna Hartling ◽  
Sophie Metz ◽  
Corinna Pehrs ◽  
Milan Scheidegger ◽  
Rebecca Gruzman ◽  
...  
Keyword(s):  
Brain Activity ◽  
Emotion Processing ◽  
Brain Regions ◽  
Anterior Insula ◽  
Anterior Cingulate ◽  
Future Research ◽  
Activation Patterns ◽  
Study Planning ◽  
Dorsolateral Prefrontal ◽  
The Right

Previous fMRI research has applied a variety of tasks to examine brain activity underlying emotion processing. While task characteristics are known to have a substantial influence on the elicited activations, direct comparisons of tasks that could guide study planning are scarce. We aimed to provide a comparison of four common emotion processing tasks based on the same analysis pipeline to suggest tasks best suited for the study of certain target brain regions. We studied an n-back task using emotional words (EMOBACK) as well as passive viewing tasks of emotional faces (FACES) and emotional scenes (OASIS and IAPS). We compared the activation patterns elicited by these tasks in four regions of interest (the amygdala, anterior insula, dorsolateral prefrontal cortex (dlPFC) and pregenual anterior cingulate cortex (pgACC)) in three samples of healthy adults (N = 45). The EMOBACK task elicited activation in the right dlPFC and bilateral anterior insula and deactivation in the pgACC while the FACES task recruited the bilateral amygdala. The IAPS and OASIS tasks showed similar activation patterns recruiting the bilateral amygdala and anterior insula. We conclude that these tasks can be used to study different regions involved in emotion processing and that the information provided is valuable for future research and the development of fMRI biomarkers.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

Comparative analysis of changes of bioelectrical activity of the brain during the neutral touch and during the performance of the myofascial release technique

2018 ◽  
pp. 46-55
Author(s):  
A. F. Belyaev ◽  
G. E. Piskunova
Keyword(s):  
Soft Tissue ◽  
Brain Activity ◽  
Direct Action ◽  
Brain Regions ◽  
Therapeutic Touch ◽  
Bioelectrical Activity ◽  
Therapeutic Action ◽  
Osteopathic Treatment ◽  
The Difference ◽  
Multiparameter Analysis

Introduction. One of the main tools of an osteopath are soft tissue techniques, which have a number of particular qualities such as minimization of force and duration of indirect techniques with an emphasis on muscle and ligamentous structures; combination of gestures, tendency to maximal relaxation and exclusion of direct action on pathological symptoms such as tension, overtone and pain. Minimization of the force applied during the performance of soft tissue techniques often invites a question whether there are differences between the usual touch and the therapeutic touch of an osteopath.Goal of research - to reveal the changes in the bioelectrical activity of the cerebral cortex arising in the process of osteopathic treatment in order to prove its specifi city in comparison with nonspecifi c tactile stimulation (neutral touch).Materials and methods. 75 people were examined with the use of multiparameter analysis of multichannel EEG in different times. 25 patients were clinically healthy adults, whereas 50 patients had signs of somatic dysfunctions.Results. Computer encephalography permits to perceive the difference between the neutral touch and the therapeutic action. An identifi cation reaction is a response to the neutral touch (changes in brain bioelectrical activity with an increase in statistically signifi cant connections in the temporal lobes), whereas the therapeutic action provokes the state of purposeful brain activity during still point (intensifi cation of frontooccipital interactions).Conclusions. Osteopathic action causes additional tension in the processing of incoming information, which requires participation of different brain regions, including interhemispheric mechanisms associated with analysis, maintenance of attention and regulation of targeted activities.

scholarly journals Visual predictions, neural oscillations and naïve physics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blake W. Saurels ◽  
Wiremu Hohaia ◽  
Kielan Yarrow ◽  
Alan Johnston ◽  
Derek H. Arnold
Keyword(s):  
Brain Activity ◽  
Dynamic Environment ◽  
Predictive Performance ◽  
Brain Regions ◽  
Internal Models ◽  
Oscillatory Activity ◽  
Alpha Band ◽  
Core Property ◽  
Ball Tracking ◽  
Band Activity

AbstractPrediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.

scholarly journals Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

2021 ◽  
Author(s):  
Adeline Jabès ◽  
Giuliana Klencklen ◽  
Paolo Ruggeri ◽  
Christoph M. Michel ◽  
Pamela Banta Lavenex ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Resting State ◽  
Cognitive Aging ◽  
Temporal Dynamics ◽  
Spatial Working Memory ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

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