scholarly journals Multivoxel Pattern Analysis for fMRI Data: A Review

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Abdelhak Mahmoudi ◽  
Sylvain Takerkart ◽  
Fakhita Regragui ◽  
Driss Boussaoud ◽  
Andrea Brovelli
Keyword(s):  
Neural Activity ◽  
Time Course ◽  
Pattern Analysis ◽  
Reference Model ◽  
Performance Estimation ◽  
Support Vector ◽  
Brain Areas ◽  
Experimental Conditions ◽  
Multivoxel Pattern Analysis ◽  
Brain Functions

Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs). In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves.

scholarly journals Neural Representations of the Committed Romantic Partner in the Nucleus Accumbens

2021 ◽  
pp. 095679762110218
Author(s):  
Ryuhei Ueda ◽  
Nobuhito Abe
Keyword(s):  
Nucleus Accumbens ◽  
Neural Activity ◽  
Romantic Relationship ◽  
Pattern Analysis ◽  
Activity Patterns ◽  
Neural Mechanism ◽  
Romantic Partners ◽  
Multivoxel Pattern Analysis ◽  
Neural Representations ◽  
The Social

Having an intimate romantic relationship is an important aspect of life. Dopamine-rich reward regions, including the nucleus accumbens (NAcc), have been identified as neural correlates for both emotional bonding with the partner and interest in unfamiliar attractive nonpartners. Here, we aimed to disentangle the overlapping functions of the NAcc using multivoxel pattern analysis, which can decode the cognitive processes encoded in particular neural activity. During functional MRI scanning, 46 romantically involved men performed the social-incentive-delay task, in which a successful response resulted in the presentation of a dynamic and positive facial expression from their partner and unfamiliar women. Multivoxel pattern analysis revealed that the spatial patterns of NAcc activity could successfully discriminate between romantic partners and unfamiliar women during the period in which participants anticipated the target presentation. We speculate that neural activity patterns within the NAcc represent the relationship partner, which might be a key neural mechanism for committed romantic relationships.

scholarly journals Temporo-parietal cortex involved in modeling one’s own and others’ attention

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Arvid Guterstam ◽  
Branden J Bio ◽  
Andrew I Wilterson ◽  
Michael Graziano
Keyword(s):  
Theory Of Mind ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Activity Patterns ◽  
Exogenous Attention ◽  
Attentional State ◽  
Brain Areas ◽  
Multivoxel Pattern Analysis ◽  
Directing Attention ◽  
The Brain

In a traditional view, in social cognition, attention is equated with gaze and people track other people’s attention by tracking their gaze. Here, we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.

scholarly journals Temporo-Parietal Cortex Involved in Modeling One’s Own and Others’ Attention

2020 ◽  
Author(s):  
Arvid Guterstam ◽  
Branden J Bio ◽  
Andrew I Wilterson ◽  
Michael SA Graziano
Keyword(s):  
Theory Of Mind ◽  
Pattern Analysis ◽  
Brain Activity ◽  
Activity Patterns ◽  
Exogenous Attention ◽  
Attentional State ◽  
Brain Areas ◽  
Multivoxel Pattern Analysis ◽  
Directing Attention ◽  
The Brain

AbstractIn a traditional view, in social cognition, attention is equated with gaze and people track attention by tracking other people’s gaze. Here we used fMRI to test whether the brain represents attention in a richer manner. People read stories describing an agent (either oneself or someone else) directing attention to an object in one of two ways: either internally directed (endogenous) or externally induced (exogenous). We used multivoxel pattern analysis to examine how brain areas within the theory-of-mind network encoded attention type and agent type. Brain activity patterns in the left temporo-parietal junction (TPJ) showed significant decoding of information about endogenous versus exogenous attention. The left TPJ, left superior temporal sulcus (STS), precuneus, and medial prefrontal cortex (MPFC) significantly decoded agent type (self versus other). These findings show that the brain constructs a rich model of one’s own and others’ attentional state, possibly aiding theory of mind.Impact statementThis study used fMRI to show that the human brain encodes other people’s attention in enough richness to distinguish whether that attention was directed exogenously (stimulus-driven) or endogenously (internally driven).

scholarly journals Metacognition facilitates the exploitation of unconscious brain states

2019 ◽  
Author(s):  
Aurelio Cortese ◽  
Hakwan Lau ◽  
Mitsuo Kawato
Keyword(s):  
Reinforcement Learning ◽  
Neural Activity ◽  
Pattern Analysis ◽  
Brain Activity ◽  
High Dimensional ◽  
Multivoxel Pattern Analysis ◽  
Brain States ◽  
Optimal Action ◽  
The Brain ◽  
Do So

AbstractCan humans be trained to make strategic use of unconscious representations in their own brains? We investigated how one can derive reward-maximizing choices from latent high-dimensional information represented stochastically in neural activity. In a novel decision-making task, reinforcement learning contingencies were defined in real-time by fMRI multivoxel pattern analysis; optimal action policies thereby depended on multidimensional brain activity that took place below the threshold of consciousness. We found that subjects could solve the task, when their reinforcement learning processes were boosted by implicit metacognition to estimate the relevant brain states. With these results we identified a frontal-striatal mechanism by which the brain can untangle tasks of great dimensionality, and can do so much more flexibly than current artificial intelligence.

A Simple Method for Estimation of Lipoxygenase and Cyclo-Oxygenase Pathways in Human Platelets - the Use of Thiobarbituric Acid Reaction

1980 ◽  
Vol 44 (02) ◽  
pp. 111-114 ◽  
Author(s):  
Hiroshi Takayama ◽  
Minoru Okuma ◽  
Haruto Uchino
Keyword(s):  
Time Course ◽  
Normal Values ◽  
Human Platelet ◽  
Thiobarbituric Acid ◽  
Human Platelets ◽  
Optimal Conditions ◽  
Experimental Conditions ◽  
Simple Method ◽  
Acid Reaction ◽  
Optimal Ph

SummaryTo develop a simple method for estimation of platelet lipoxygenase (PLO) and cyclo-oxygenase (PCO) pathways, the arachidonic acid (AA) metabolism of human platelet was investigated under various experimental conditions by the use of the thiobarbituric acid (TBA) reaction and a radioisotope technique. A TBA-reactive substance different from malondialdehyde (MDA) via PCO pathway was detected and shown to be derived from the PLO pathway. Since the optimal pH and time course of its formation were different from those of MDA formation via PCO pathway, PLO and PCO pathways were estimated by quantitating the TBA-reactive substances produced by the incubation of AA either with aspirin-treated platelets or with untreated ones, respectively, each under optimal conditions. Normal values expressed in terms of nmol MDA/108 platelets were 1.17±0.34 (M±SD, n = 31) and 0.79±0.15 (n = 31) for PLO and PCO pathways, respectively.

Engaging regularly with fiction influences connectivity in cortical areas for language and mentalizing

2017 ◽  
Author(s):  
Roel M. Willems ◽  
Franziska Hartung
Keyword(s):  
Functional Connectivity ◽  
Time Course ◽  
Language Skills ◽  
Brain Regions ◽  
Brain Areas ◽  
Daily Lives ◽  
Cortical Areas ◽  
Social Abilities ◽  
Behavioral Evidence ◽  
Amount Of Reading

Behavioral evidence suggests that engaging with fiction is positively correlated with social abilities. The rationale behind this link is that engaging with fictional narratives offers a ‘training modus’ for mentalizing and empathizing. We investigated the influence of the amount of reading that participants report doing in their daily lives, on connections between brain areas while they listened to literary narratives. Participants (N=57) listened to two literary narratives while brain activation was measured with fMRI. We computed time-course correlations between brain regions, and compared the correlation values from listening to narratives to listening to reversed speech. The between-region correlations were then related to the amount of fiction that participants read in their daily lives. Our results show that amount of fiction reading is related to functional connectivity in areas known to be involved in language and mentalizing. This suggests that reading fiction influences social cognition as well as language skills.

A Machine Learning Based Approach of Performance Estimation for High-Pressure Compressor Airfoils

2018 ◽  
Author(s):  
Jonas Marx ◽  
Stefan Gantner ◽  
Jörn Städing ◽  
Jens Friedrichs
Keyword(s):  
Machine Learning ◽  
High Pressure ◽  
Machine Learning Algorithms ◽  
Performance Estimation ◽  
Predictive Maintenance ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Operating Characteristics ◽  
High Pressure Compressor ◽  
Pressure Compressor

In recent years, the demands of Maintenance, Repair and Overhaul (MRO) customers to provide resource-efficient after market services have grown increasingly. One way to meet these requirements is by making use of predictive maintenance methods. These are ideas that involve the derivation of workscoping guidance by assessing and processing previously unused or undocumented service data. In this context a novel approach on predictive maintenance is presented in form of a performance-based classification method for high pressure compressor (HPC) airfoils. The procedure features machine learning algorithms that establish a relation between the airfoil geometry and the associated aerodynamic behavior and is hereby able to divide individual operating characteristics into a finite number of distinct aero-classes. By this means the introduced method not only provides a fast and simple way to assess piece part performance through geometrical data, but also facilitates the consideration of stage matching (axial as well as circumferential) in a simplified manner. It thus serves as prerequisite for an improved customary HPC performance workscope as well as for an automated optimization process for compressor buildup with used or repaired material that would be applicable in an MRO environment. The methods of machine learning that are used in the present work enable the formation of distinct groups of similar aero-performance by unsupervised (step 1) and supervised learning (step 2). The application of the overall classification procedure is shown exemplary on an artificially generated dataset based on real characteristics of a front and a rear rotor of a 10-stage axial compressor that contains both geometry as well as aerodynamic information. In step 1 of the investigation only the aerodynamic quantities in terms of multivariate functional data are used in order to benchmark different clustering algorithms and generate a foundation for a geometry-based aero-classification. Corresponding classifiers are created in step 2 by means of both, the k Nearest Neighbor and the linear Support Vector Machine algorithms. The methods’ fidelities are brought to the test with the attempt to recover the aero-based similarity classes solely by using normalized and reduced geometry data. This results in high classification probabilities of up to 96 % which is proven by using stratified k-fold cross-validation.

scholarly journals Role of Mammalian Auditory Cortex in the Perception of Elementary Sound Properties

2001 ◽  
Vol 85 (6) ◽  
pp. 2350-2358 ◽  
Author(s):  
Sanjiv K. Talwar ◽  
Pawel G. Musial ◽  
George L. Gerstein
Keyword(s):  
Auditory Cortex ◽  
Time Course ◽  
Auditory Evoked Potentials ◽  
Mammalian Species ◽  
Sound Intensity ◽  
Primary Auditory Cortex ◽  
Normal Hearing ◽  
Auditory Task ◽  
Experimental Conditions

Studies in several mammalian species have demonstrated that bilateral ablations of the auditory cortex have little effect on simple sound intensity and frequency-based behaviors. In the rat, for example, early experiments have shown that auditory ablations result in virtually no effect on the rat's ability to either detect tones or discriminate frequencies. Such lesion experiments, however, typically examine an animal's performance some time after recovery from ablation surgery. As such, they demonstrate that the cortex is not essential for simple auditory behaviors in the long run. Our study further explores the role of cortex in basic auditory perception by examining whether the cortex is normally involved in these behaviors. In these experiments we reversibly inactivated the rat primary auditory cortex (AI) using the GABA agonist muscimol, while the animals performed a simple auditory task. At the same time we monitored the rat's auditory activity by recording auditory evoked potentials (AEP) from the cortical surface. In contrast to lesion studies, the rapid time course of these experimental conditions preclude reorganization of the auditory system that might otherwise compensate for the loss of cortical processing. Soon after bilateral muscimol application to their AI region, our rats exhibited an acute and profound inability to detect tones. After a few hours this state was followed by a gradual recovery of normal hearing, first of tone detection and, much later, of the ability to discriminate frequencies. Surface muscimol application, at the same time, drastically altered the normal rat AEP. Some of the normal AEP components vanished nearly instantaneously to unveil an underlying waveform, whose size was related to the severity of accompanying behavioral deficits. These results strongly suggest that the cortex is directly involved in basic acoustic processing. Along with observations from accompanying multiunit experiments that related the AEP to AI neuronal activity, our results suggest that a critical amount of activity in the auditory cortex is necessary for normal hearing. It is likely that the involvement of the cortex in simple auditory perceptions has hitherto not been clearly understood because of underlying recovery processes that, in the long-term, safeguard fundamental auditory abilities after cortical injury.

Sign in / Sign up

Export Citation Format

Share Document