Stable Task Representations under Attentional Load Revealed with Multivariate Pattern Analysis of Human Brain Activity

2015 ◽  
Vol 27 (9) ◽  
pp. 1789-1800 ◽  
Author(s):  
Jason L. Chan ◽  
Aaron Kucyi ◽  
Joseph F. X. DeSouza
Keyword(s):  
Neural Activity ◽  
Pattern Analysis ◽  
Univariate Analysis ◽  
Visual Presentation ◽  
Error Rates ◽  
Oculomotor Control ◽  
Multivariate Pattern Analysis ◽  
Attentional Load ◽  
Multivariate Pattern ◽  
Task Representations

Performing multiple tasks concurrently places a load on limited attentional resources and results in disrupted task performance. Although human neuroimaging studies have investigated the neural correlates of attentional load, how attentional load affects task processing is poorly understood. Here, task-related neural activity was investigated using fMRI with conventional univariate analysis and multivariate pattern analysis (MVPA) while participants performed blocks of prosaccades and antisaccades, either with or without a rapid serial visual presentation (RSVP) task. Performing prosaccades and antisaccades with RSVP increased error rates and RTs, decreased mean activation in frontoparietal brain areas associated with oculomotor control, and eliminated differences in activation between prosaccades and antisaccades. However, task identity could be decoded from spatial patterns of activation both in the absence and presence of an attentional load. Furthermore, in the FEFs and intraparietal sulcus, these spatial representations were found to be similar using cross-trial-type MVPA, which suggests stability under attentional load. These results demonstrate that attentional load may disrupt the strength of task-related neural activity, rather than the identity of task representations.

scholarly journals Motion opponency examined throughout visual cortex with multivariate pattern analysis of fMRI data

2020 ◽  
Author(s):  
Andrew E. Silva ◽  
Benjamin Thompson ◽  
Zili Liu
Keyword(s):  
Visual Cortex ◽  
Visual Processing ◽  
Pattern Analysis ◽  
Flicker Noise ◽  
Univariate Analysis ◽  
Motion Processing ◽  
List Type ◽  
Multivariate Pattern Analysis ◽  
Motion Energy ◽  
Multivariate Pattern

AbstractThis study explores how the human brain solves the challenge of flicker noise in motion processing. Despite providing no useful directional motion information, flicker is common in the visual environment and exhibits omnidirectional motion energy which is processed by low-level motion detectors. Models of motion processing propose a mechanism called motion opponency that reduces the processing of flicker noise. Motion opponency involves the pooling of local motion signals to calculate an overall motion direction. A neural correlate of motion opponency has been observed in human area MT+/V5 using fMRI, whereby stimuli with perfectly balanced motion energy constructed from dots moving in counter-phase elicit a weaker BOLD response than non-balanced (in-phase) motion stimuli. Building on this previous work, we used multivariate pattern analysis to examine whether the patterns of brain activation elicited by motion opponent stimuli resemble the activation elicited by flicker noise across the human visual cortex. Robust multivariate signatures of opponency were observed in V5 and in V3A. Our results support the notion that V5 is centrally involved in motion opponency and in the reduction of flicker noise during visual processing. Furthermore, these results demonstrate the utility of powerful multivariate analysis methods in revealing the role of additional visual areas, such as V3A, in opponency and in motion processing more generally.HighlightsOpponency is demonstrated in multivariate and univariate analysis of V5 data.Multivariate fMRI also implicates V3A in motion opponency.Multivariate analyses are useful for examining opponency throughout visual cortex.

scholarly journals Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience

2017 ◽  
Author(s):  
J. Brendan Ritchie ◽  
David Michael Kaplan ◽  
Colin Klein
Keyword(s):  
Cognitive Neuroscience ◽  
Strong Evidence ◽  
Neural Activity ◽  
Pattern Analysis ◽  
Neural Representation ◽  
Neural Decoding ◽  
Multivariate Pattern Analysis ◽  
Neural Representations ◽  
Multivariate Pattern ◽  
The Brain

AbstractSince its introduction, multivariate pattern analysis (MVPA), or “neural decoding”, has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the Decoder’s Dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the Dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the Dictum, arguing that it is false: decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the Dictum can be improved on, in order to better justify inferences about neural representation using MVPA.

scholarly journals Decoding Attended Information in Short-term Memory: An EEG Study

2013 ◽  
Vol 25 (1) ◽  
pp. 127-142 ◽  
Author(s):  
Joshua J. LaRocque ◽  
Jarrod A. Lewis-Peacock ◽  
Andrew T. Drysdale ◽  
Klaus Oberauer ◽  
Bradley R. Postle
Keyword(s):  
Neural Activity ◽  
Memory Trace ◽  
Pattern Analysis ◽  
Short Term Memory ◽  
Focus Of Attention ◽  
Multivariate Pattern Analysis ◽  
Short Term ◽  
Term Retention ◽  
Fmri Study ◽  
Multivariate Pattern

For decades it has been assumed that sustained, elevated neural activity—the so-called active trace—is the neural correlate of the short-term retention of information. However, a recent fMRI study has suggested that this activity may be more related to attention than to retention. Specifically, a multivariate pattern analysis failed to find evidence that information that was outside the focus of attention, but nonetheless in STM, was retained in an active state. Here, we replicate and extend this finding by querying the neural signatures of attended versus unattended information within STM with electroencephalograpy (EEG), a method sensitive to oscillatory neural activity to which the previous fMRI study was insensitive. We demonstrate that in the delay-period EEG activity, there is information only about memory items that are also in the focus of attention. Information about items outside the focus of attention is not detectable. This result converges with the fMRI findings to suggest that, contrary to conventional wisdom, an active memory trace may be unnecessary for the short-term retention of information.

scholarly journals A Multivariate Pattern Analysis of Metabolic Profile in Neurologically Impaired Children and Adolescents

Children ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 186
Author(s):  
Valeria Calcaterra ◽  
Giacomo Biganzoli ◽  
Gloria Pelizzo ◽  
Hellas Cena ◽  
Alessandra Rizzuto ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Glucose Metabolism ◽  
Children And Adolescents ◽  
Metabolic Profile ◽  
Children With Disabilities ◽  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Neurologically Impaired ◽  
Multivariate Pattern ◽  
Impaired Children

Background: The prevalence of pediatric metabolic syndrome is usually closely linked to overweight and obesity; however, this condition has also been described in children with disabilities. We performed a multivariate pattern analysis of metabolic profiles in neurologically impaired children and adolescents in order to reveal patterns and crucial biomarkers among highly interrelated variables. Patients and methods: We retrospectively reviewed 44 cases of patients (25M/19F, mean age 12.9 ± 8.0) with severe disabilities. Clinical and anthropometric parameters, body composition, blood pressure, and metabolic and endocrinological assessment (fasting blood glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, triglycerides, glutamic oxaloacetic transaminase, glutamate pyruvate transaminase, gamma-glutamyl transpeptidase) were recorded in all patients. As a control group, we evaluated 120 healthy children and adolescents (61M/59F, mean age 12.9 ± 2.7). Results: In the univariate analysis, the children-with-disabilities group showed a more dispersed distribution, thus with higher variability of the features related to glucose metabolism and insulin resistance (IR) compared to the healthy controls. The principal component (PC1), which emerged from the PC analysis conducted on the merged dataset and characterized by these variables, was crucial in describing the differences between the children-with-disabilities group and controls. Conclusion: Children and adolescents with disabilities displayed a different metabolic profile compared to controls. Metabolic syndrome (MetS), particularly glucose metabolism and IR, is a crucial point to consider in the treatment and care of this fragile pediatric population. Early detection of the interrelated variables and intervention on these modifiable risk factors for metabolic disturbances play a central role in pediatric health and life expectancy in patients with a severe disability.

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