Decoding Cognitive Function with Magnetoencephalography

2020 ◽  
pp. 278-298
Author(s):  
Dimitrios Pantazis
Keyword(s):  
Cognitive Function ◽  
Cognitive Neuroscience ◽  
Brain Activity ◽  
Mind Reading ◽  
Neuroimaging Data ◽  
Analytical Approaches ◽  
Abnormal Brain ◽  
Higher Sensitivity

Decoding of brain activity can perform feats of mind-reading by revealing what a person is seeing, perceiving, or remembering. Decoding can assess the information contained in magnetoencephalography (MEG) neural patterns, offering a principled approach to characterize differences in cognitive function between the normal and abnormal brain. Since their introduction, multivariate decoding methods have transformed cognitive neuroscience. They are now increasingly complementing traditional univariate methods for the analysis of neuroimaging data, in part owing to the higher sensitivity afforded by these techniques. However, deriving information from distributed MEG neural patterns requires special analytical approaches. The aim of this chapter is to introduce decoding techniques and their application in MEG. It reviews the different ways to extract MEG multivariate patterns and perform decoding analyses. It also highlights challenges and limitations in the interpretation of decoding results.

scholarly journals Individualizing Representational Similarity Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Seth M. Levine ◽  
Jens V. Schwarzbach
Keyword(s):  
Individual Differences ◽  
Cognitive Neuroscience ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Similarity Analysis ◽  
Representational Similarity Analysis ◽  
Analysis Technique ◽  
Neuroimaging Data ◽  
Translational Studies ◽  
Transfer Of Information

Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.

Distinguishing hypochondriasis and schizophrenia using regional homogeneity: a resting-state fMRI study and support vector machine analysis

2021 ◽  
pp. 1-29
Author(s):  
Kangyu Jin ◽  
Zhe Shen ◽  
Guoxun Feng ◽  
Zhiyong Zhao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Resting State ◽  
Parietal Lobe ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Middle Temporal Gyrus ◽  
Support Vector ◽  
Fmri Study

Abstract Objective: A few former studies suggested there are partial overlaps in abnormal brain structure and cognitive function between Hypochondriasis (HS) and schizophrenia (SZ). But their differences in brain activity and cognitive function were unclear. Methods: 21 HS patients, 23 SZ patients, and 24 healthy controls (HC) underwent Resting-state functional magnetic resonance imaging (rs-fMRI) with the regional homogeneity analysis (ReHo), subsequently exploring the relationship between ReHo value and cognitive functions. The support vector machines (SVM) were used on effectiveness evaluation of ReHo for differentiating HS from SZ. Results: Compared with HC, HS showed significantly increased ReHo values in right middle temporal gyrus (MTG), left inferior parietal lobe (IPL) and right fusiform gyrus (FG), while SZ showed increased ReHo in left insula, decreased ReHo values in right paracentral lobule. Additionally, HS showed significantly higher ReHo values in FG, MTG and left paracentral lobule but lower in insula than SZ. The higher ReHo values in insula were associated with worse performance in MCCB in HS group. SVM analysis showed a combination of the ReHo values in insula and FG was able to satisfactorily distinguish the HS and SZ patients. Conclusion: our results suggested the altered default mode network (DMN), of which abnormal spontaneous neural activity occurs in multiple brain regions, might play a key role in the pathogenesis of HS, and the resting-state alterations of insula closely related to cognitive dysfunction in HS. Furthermore, the combination of the ReHo in FG and insula was a relatively ideal indicator to distinguish HS from SZ.

Abnormal Brain Activity Related to Performance Monitoring and Error Detection in Children with ADHD

Cortex ◽  
2005 ◽  
Vol 41 (3) ◽  
pp. 377-388 ◽  
Author(s):  
Mario Liotti ◽  
Steven R. Pliszka ◽  
Ricardo Perez ◽  
Delia Kothmann ◽  
Marty G. Woldorff
Keyword(s):  
Error Detection ◽  
Performance Monitoring ◽  
Brain Activity ◽  
Children With Adhd ◽  
Abnormal Brain

scholarly journals Functional Neuroimaging and Psychology: What Have You Done for Me Lately?

2013 ◽  
Vol 25 (6) ◽  
pp. 834-842 ◽  
Author(s):  
Joseph M. Moran ◽  
Jamil Zaki
Keyword(s):  
Functional Imaging ◽  
Brain Mapping ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Psychological Theory ◽  
Quarter Century ◽  
Psychological Phenomena ◽  
Neuroimaging Data ◽  
Subsequent Behavior ◽  
Reverse Inference

Functional imaging has become a primary tool in the study of human psychology but is not without its detractors. Although cognitive neuroscientists have made great strides in understanding the neural instantiation of countless cognitive processes, commentators have sometimes argued that functional imaging provides little or no utility for psychologists. And indeed, myriad studies over the last quarter century have employed the technique of brain mapping—identifying the neural correlates of various psychological phenomena—in ways that bear minimally on psychological theory. How can brain mapping be made more relevant to behavioral scientists broadly? Here, we describe three trends that increase precisely this relevance: (i) the use of neuroimaging data to adjudicate between competing psychological theories through forward inference, (ii) isolating neural markers of information processing steps to better understand complex tasks and psychological phenomena through probabilistic reverse inference, and (iii) using brain activity to predict subsequent behavior. Critically, these new approaches build on the extensive tradition of brain mapping, suggesting that efforts in this area—although not initially maximally relevant to psychology—can indeed be used in ways that constrain and advance psychological theory.

scholarly journals Cognitive Network Neuroscience

2015 ◽  
Vol 27 (8) ◽  
pp. 1471-1491 ◽  
Author(s):  
John D. Medaglia ◽  
Mary-Ellen Lynall ◽  
Danielle S. Bassett
Keyword(s):  
Cognitive Neuroscience ◽  
Network Science ◽  
Structural Connectivity ◽  
Cognitive Network ◽  
Network Characteristics ◽  
Time Dynamics ◽  
Neuroimaging Data ◽  
Control Learning ◽  
And Function ◽  
Network Neuroscience

Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.

scholarly journals Sensorimotor brain dynamics reflect architectural affordances

2019 ◽  
Vol 116 (29) ◽  
pp. 14769-14778 ◽  
Author(s):  
Zakaria Djebbara ◽  
Lars Brorson Fich ◽  
Laura Petrini ◽  
Klaus Gramann
Keyword(s):  
Cognitive Processes ◽  
Cognitive Neuroscience ◽  
Brain Activity ◽  
Physical Structure ◽  
Ongoing Debate ◽  
Head Mounted Displays ◽  
Actual Movement ◽  
Imaging Approach ◽  
Essential Function ◽  
The Brain

Anticipating meaningful actions in the environment is an essential function of the brain. Such predictive mechanisms originate from the motor system and allow for inferring actions from environmental affordances, and the potential to act within a specific environment. Using architecture, we provide a unique perspective on the ongoing debate in cognitive neuroscience and philosophy on whether cognition depends on movement or is decoupled from our physical structure. To investigate cognitive processes associated with architectural affordances, we used a mobile brain/body imaging approach recording brain activity synchronized to head-mounted displays. Participants perceived and acted on virtual transitions ranging from nonpassable to easily passable. We found that early sensory brain activity, on revealing the environment and before actual movement, differed as a function of affordances. In addition, movement through transitions was preceded by a motor-related negative component that also depended on affordances. Our results suggest that potential actions afforded by an environment influence perception.

scholarly journals Recent advances in functional neuroimaging analysis for cognitive neuroscience

2018 ◽  
Vol 2 ◽  
pp. 239821281775272 ◽  
Author(s):  
Nitin Williams ◽  
Richard N. Henson
Keyword(s):  
Functional Neuroimaging ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Recent Analysis ◽  
Temporal Data ◽  
New Methods ◽  
Neuroimaging Data ◽  
The Rich ◽  
Scientific Questions ◽  
The Brain

Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives.

Social Empathy

2014 ◽  
Author(s):  
Elizabeth A. Segal
Keyword(s):  
Social Work ◽  
Brain Imaging ◽  
Cognitive Neuroscience ◽  
Policy Making ◽  
Brain Activity ◽  
Work Practice ◽  
Social Work Practice ◽  
Neuroscience Research ◽  
Social Empathy ◽  
The Relationship

This article defines and explains the concept and trait of social empathy and the relationship to interpersonal empathy. Both concepts are explained using the latest cognitive neuroscience research on brain activity. Through brain imaging, the components that together make up the full array of empathy have been identified and are discussed in relation to social work practice. The application of social empathy in the policy-making arena is described, and the implications for social work practice to enhance empathy are discussed.

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