scholarly journals Multivariate pattern analysis of fMRI data for imaginary and real colours in grapheme-colour synaesthesia

2017 ◽  
Author(s):  
Mathieu J. Ruiz ◽  
Michel Dojat ◽  
Jean-Michel Hupé
Keyword(s):  
Pattern Analysis ◽  
Region Of Interest ◽  
Neural Correlates ◽  
Neural Processing ◽  
Colour Perception ◽  
Multivoxel Pattern Analysis ◽  
Processing Difference ◽  
Subjective Phenomenon ◽  
Multivariate Pattern ◽  
Univariate Analyses

AbstractGrapheme-colour synaesthesia is a subjective phenomenon related to perception and imagination, in which some people involuntarily but systematically associate specific, idiosyncratic colours to achromatic letters or digits. Its investigation is relevant to unravel the neural correlates of colour perception in isolation from low-level neural processing of spectral components, as well as the neural correlates of imagination by being able to reliably trigger imaginary colour experiences. However, functional MRI studies using univariate analyses failed to provide univocal evidence of the activation of the ‘colour network’ by synaesthesia. Applying Multivariate (multivoxel) Pattern Analysis (MVPA) on 20 synaesthetes and 20 control participants, we tested whether the neural processing of real colours (concentric rings) and synaesthetic colours (black graphemes) shared patterns of activations. Region of interest analyses in retinotopically and anatomically defined visual regions revealed neither evidence of shared circuits for real and synaesthetic colour processing, nor processing difference between synaesthetes and controls. We also found no correlation with individual experiences, characterised by measuring the strength of synaesthetic associations. The whole brain, searchlight, analysis led to similar results. We conclude that identifying the neural correlates of the synaesthetic experience of colours may still be beyond the reach of present technology and data analysis techniques.

Decoding Brain States for Planning Functional Grasps of Tools: A Functional Magnetic Resonance Imaging Multivoxel Pattern Analysis Study

2018 ◽  
Vol 24 (10) ◽  
pp. 1013-1025 ◽  
Author(s):  
Mikolaj Buchwald ◽  
Łukasz Przybylski ◽  
Gregory Króliczak
Keyword(s):  
Pattern Analysis ◽  
Premotor Cortex ◽  
Region Of Interest ◽  
Occipital Cortex ◽  
Multivoxel Pattern Analysis ◽  
Grasp Planning ◽  
Lateral Occipital Complex ◽  
Fine Grained ◽  
Traditional Approaches ◽  
Neural Selectivity

AbstractObjectives: We used multivoxel pattern analysis (MVPA) to investigate neural selectivity for grasp planning within the left-lateralized temporo-parieto-frontal network of areas (praxis representation network, PRN) typically associated with tool-related actions, as studied with traditional neuroimaging contrasts. Methods: We used data from 20 participants whose task was to plan functional grasps of tools, with either right or left hands. Region of interest and whole-brain searchlight analyses were performed to show task-related neural patterns. Results: MVPA revealed significant contributions to functional grasp planning from the anterior intraparietal sulcus (aIPS) and its immediate vicinities, supplemented by inputs from posterior subdivisions of IPS, and the ventral lateral occipital complex (vLOC). Moreover, greater local selectivity was demonstrated in areas near the superior parieto-occipital cortex and dorsal premotor cortex, putatively forming the dorso-dorsal stream. Conclusions: A contribution from aIPS, consistent with its role in prospective grasp formation and/or encoding of relevant tool properties (e.g., potential graspable parts), is likely to accompany the retrieval of manipulation and/or mechanical knowledge subserved by the supramarginal gyrus for achieving action goals. An involvement of vLOC indicates that MVPA is particularly sensitive to coding of object properties, their identities and even functions, for a support of grip formation. Finally, the engagement of the superior parieto-frontal regions as revealed by MVPA is consistent with their selectivity for transient features of tools (i.e., variable affordances) for anticipatory hand postures. These outcomes support the notion that, compared to traditional approaches, MVPA can reveal more fine-grained patterns of neural activity. (JINS, 2018, 24, 1013–1025)

scholarly journals Distinct and overlapping neural correlates of metacognitive monitoring and metacognitive control

2020 ◽  
Author(s):  
Annika Boldt ◽  
Sam Gilbert
Keyword(s):  
Pattern Analysis ◽  
Mental States ◽  
Neural Correlates ◽  
Multivariate Pattern Analysis ◽  
Monitoring And Control ◽  
Metacognitive Monitoring ◽  
Metacognitive Control ◽  
Multivariate Pattern ◽  
And Control ◽  
Influence Behavior

Metacognition describes the process of monitoring one’s own mental states, often for the purpose of cognitive control. Previous research has investigated how metacognitive signals are generated (metacognitive monitoring), for example when people judge their confidence in their decisions and memories. Research has also investigated how these metacognitive signals are used to influence behavior (metacognitive control), for example setting a reminder (i.e. cognitive offloading) for something you are not confident you will remember. However, the mapping between metacognitive monitoring and metacognitive control has not been directly studied on a neural level. We used fMRI to investigate a delayed-intentions task with a reminder element, allowing participants to use their metacognitive insight to engage metacognitive control. Using multivariate pattern analysis, we found that we could separately decode both monitoring and control, and, to a lesser extent, cross-classify between them. Therefore, brain patterns associated with monitoring and control are partially, but not fully, overlapping.

scholarly journals Neural correlates of conscious visual perception lie outside the visual system: evidence from the double-drift illusion

2019 ◽  
Author(s):  
Sirui Liu ◽  
Qing Yu ◽  
Peter U. Tse ◽  
Patrick Cavanagh
Keyword(s):  
Visual System ◽  
Visual Processing ◽  
Pattern Analysis ◽  
Activity Patterns ◽  
Neural Correlates ◽  
Multivariate Pattern Analysis ◽  
Visual Areas ◽  
Visual Cortices ◽  
Multivariate Pattern ◽  
The Brain

SummaryWhen perception differs from the physical stimulus, as it does for visual illusions and binocular rivalry, the opportunity arises to localize where perception emerges in the visual processing hierarchy. Representations prior to that stage differ from the eventual conscious percept even though they provide input to it. Here we investigate where and how a remarkable misperception of position emerges in the brain. This “double-drift” illusion causes a dramatic mismatch between retinal and perceived location, producing a perceived path that can differ from its physical path by 45° or more [1]. The deviations in the perceived trajectory can accumulate over at least a second [1] whereas other motion-induced position shifts accumulate over only 80 to 100 ms before saturating [2]. Using fMRI and multivariate pattern analysis, we find that the illusory path does not share activity patterns with a matched physical path in any early visual areas. In contrast, a whole-brain searchlight analysis reveals a shared representation in more anterior regions of the brain. These higher-order areas would have the longer time constants required to accumulate the small moment-to-moment position offsets that presumably originate in early visual cortices, and then transform these sensory inputs into a final conscious percept. The dissociation between perception and the activity in early sensory cortex suggests that perceived position does not emerge in what is traditionally regarded as the visual system but emerges instead at a much higher level.

scholarly journals Is there an amodal “semantic” area in the left posterior temporal lobe?

2018 ◽  
Author(s):  
Feng Rong ◽  
Jiang Xu ◽  
Karen Emmorey ◽  
Allen R. Braun ◽  
Gregory Hickok
Keyword(s):  
Temporal Lobe ◽  
Sensory Modality ◽  
Region Of Interest ◽  
Temporal Region ◽  
Left Posterior ◽  
High Level ◽  
Mri Study ◽  
Multivariate Pattern ◽  
Open Question ◽  
Univariate Analyses

Portions of the left posterior temporal lobe are widely believed to comprise a “convergence zone” for integrating information from various sensory modalities and therefore for accessing high-level semantic information. It is an open question whether the network in this posterior temporal lobe region is coding/processing abstract, amodal information or whether neural codes retain sensory modality-tied representations. A recent functional MRI study (Xu et al. 2009, PNAS, 106, 20664-20669) seems to support the amodal account: using standard univariate general linear model (GLM) analyses, the left posterior temporal lobe region was equally activated during the processing of visually presented meaningful symbolic hand gestures and auditorily presented spoken glosses of those same gestures, relative to meaningless control gestures/speech, thus showing no preferential response according to modality of presentation of the same information. However, standard univariate analyses may not be sensitive to the micro-organization of the region of interest. In the present study we reanalyzed the same dataset using a region of interest (ROI)-based multivariate pattern classification method to assess modality sensitivity in the posterior temporal lobe ROI. We found that the pattern of activity in the ROI significantly discriminated between the visual and auditory conditions, including the meaningless control conditions. Moreover, mapping of the prediction coefficients onto the voxels within the ROI demonstrated a gradient of preference among modalities, where the gesture preferring voxels were distributed more medial and posterior, and the speech preferring voxels were distributed more lateral and anterior. These findings suggest that the left posterior temporal region is not coding information in an amodal format, at least broadly, but contains sub-regions that are sensitive to each individual modality.

scholarly journals Neural correlates of ground plane perception revealed using multivariate pattern analysis

2012 ◽  
Vol 12 (9) ◽  
pp. 1202-1202
Author(s):  
K. B. Porter ◽  
P. J. Kohler ◽  
C. E. P. Cavanagh ◽  
P. U. Tse
Keyword(s):  
Pattern Analysis ◽  
Ground Plane ◽  
Neural Correlates ◽  
Multivariate Pattern Analysis ◽  
Multivariate Pattern

scholarly journals Tools of the Trade Multivoxel pattern analysis in fMRI: a practical introduction for social and affective neuroscientists

2020 ◽  
Vol 15 (4) ◽  
pp. 487-509 ◽  
Author(s):  
Miriam E Weaverdyck ◽  
Matthew D Lieberman ◽  
Carolyn Parkinson
Keyword(s):  
Pattern Analysis ◽  
Analytical Techniques ◽  
Affective Neuroscience ◽  
Neural Responses ◽  
Multivoxel Pattern Analysis ◽  
The Past ◽  
Neuroscience Research ◽  
Single Voxel ◽  
The Family ◽  
Univariate Analyses

Abstract The family of neuroimaging analytical techniques known as multivoxel pattern analysis (MVPA) has dramatically increased in popularity over the past decade, particularly in social and affective neuroscience research using functional magnetic resonance imaging (fMRI). MVPA examines patterns of neural responses, rather than analyzing single voxel- or region-based values, as is customary in conventional univariate analyses. Here, we provide a practical introduction to MVPA and its most popular variants (namely, representational similarity analysis (RSA) and decoding analyses, such as classification using machine learning) for social and affective neuroscientists of all levels, particularly those new to such methods. We discuss how MVPA differs from traditional mass-univariate analyses, the benefits MVPA offers to social neuroscientists, experimental design and analysis considerations, step-by-step instructions for how to implement specific analyses in one’s own dataset and issues that are currently facing research using MVPA methods.

scholarly journals Multivoxel Pattern Analysis Reveals a Neural Phenotype for Trust Bias in Adolescents

2019 ◽  
Vol 31 (11) ◽  
pp. 1726-1741 ◽  
Author(s):  
Sarah M. Tashjian ◽  
João F. Guassi Moreira ◽  
Adriana Galván
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Pattern Analysis ◽  
Neural Mechanisms ◽  
Female Adolescents ◽  
Multivariate Pattern Analysis ◽  
Brain Response ◽  
Multivoxel Pattern Analysis ◽  
Pattern Similarity ◽  
Multivariate Pattern

The extent to which individuals are inclined to judge unfamiliar others as trustworthy can have important implications for social functioning. Using multivariate pattern analysis, a neural phenotype of trust bias was identified in 48 human adolescents (ages 14–18 years, 26 female). Adolescents who exhibited more similar brain response to faces at the extremes of a trustworthy gradient were more likely to rate neutral faces as trustworthy. This relation between neural pattern representation and trust bias was evinced in the amygdala. Amygdala–insula connectivity dissimilarity to faces at the extremes of the trustworthy gradient was associated with greater trust bias to neutral faces, serving as a distinct circuit-level contributor to decision-making over and above of amygdala pattern similarity. These findings aid understanding of neural mechanisms contributing to individual differences in social evaluations of ambiguity.

Sign in / Sign up

Export Citation Format

Share Document