Revisiting the Role of the Fusiform Face Area in Expertise

2016 ◽  
Vol 28 (9) ◽  
pp. 1345-1357 ◽  
Author(s):  
Merim Bilalić
Keyword(s):  
Pattern Analysis ◽  
Spatial Relations ◽  
Fusiform Face Area ◽  
Multivariate Pattern Analysis ◽  
Multiple Objects ◽  
Activation Patterns ◽  
Face Area ◽  
Single Category ◽  
Multivariate Pattern

The fusiform face area (FFA) is considered to be a highly specialized brain module because of its central importance for face perception. However, many researchers claim that the FFA is a general visual expertise module that distinguishes between individual examples within a single category. Here, I circumvent the shortcomings of some previous studies on the FFA controversy by using chess stimuli, which do not visually resemble faces, together with more sensitive methods of analysis such as multivariate pattern analysis. I also extend the previous research by presenting chess positions, complex scenes with multiple objects, and their interrelations to chess experts and novices as well as isolated chess objects. The first experiment demonstrates that chess expertise modulated the FFA activation when chess positions were presented. In contrast, single chess objects did not produce different activation patterns among experts and novices even when the multivariate pattern analysis was used. The second experiment focused on the single chess objects and featured an explicit task of identifying the chess objects but failed to demonstrate expertise effects in the FFA. The experiments provide support for the general expertise view of the FFA function but also extend the scope of our understanding about the function of the FFA. The FFA does not merely distinguish between different exemplars within the same category of stimuli. More likely, it parses complex multiobject stimuli that contain numerous functional and spatial relations.

scholarly journals Individual face and house-related eye movement patterns distinctively activate FFA and PPA in the absence of faces and houses

2019 ◽  
Author(s):  
Lihui Wang ◽  
Florian Baumgartner ◽  
Falko R. Kaule ◽  
Michael Hanke ◽  
Stefan Pollmann
Keyword(s):  
Pattern Analysis ◽  
Perception And Action ◽  
Fusiform Face Area ◽  
Multivariate Pattern Analysis ◽  
Face Area ◽  
Gaze Patterns ◽  
Visual Areas ◽  
Uniform Background ◽  
Multivariate Pattern ◽  
Parahippocampal Place Area

We investigated if the fusiform face area (FFA) and the parahippocampal place area (PPA) contain a representation of fixation sequences that are typically used when looking at faces or houses. For this purpose, we instructed observers to follow a dot presented on a uniform background. The dot's movements represented gaze paths acquired separately while observers were looking at face or house pictures. Even when gaze dispersion differences were controlled, face- and house-associated gaze patterns could be discriminated by multivariate pattern analysis in the FFA and PPA. The discrimination of face- and house-associated gaze patterns in FFA and PPA was more sensitive for the current observer’s own gazes than for another observer’s gaze. Moreover, the discrimination of the observer’s own gaze patterns was specific to FFA and PPA, but was not observed in early visual areas (V1 – V4) or superior parietal lobule and frontal eye fields. These findings indicate a link between perception and action - the complex gaze patterns that are used to explore faces and houses - in the FFA and PPA.

scholarly journals Individual face- and house-related eye movement patterns distinctively activate FFA and PPA

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Lihui Wang ◽  
Florian Baumgartner ◽  
Falko R. Kaule ◽  
Michael Hanke ◽  
Stefan Pollmann
Keyword(s):  
Pattern Analysis ◽  
Perception And Action ◽  
Fusiform Face Area ◽  
Multivariate Pattern Analysis ◽  
Face Area ◽  
Gaze Patterns ◽  
Visual Areas ◽  
Uniform Background ◽  
Multivariate Pattern ◽  
Parahippocampal Place Area

AbstractWe investigated if the fusiform face area (FFA) and the parahippocampal place area (PPA) contain a representation of fixation sequences that are typically used when looking at faces or houses. Here, we instructed observers to follow a dot presented on a uniform background. The dot’s movements represented gaze paths acquired separately from observers looking at face or house pictures. Even when gaze dispersion differences were controlled, face- and house-associated gaze patterns could be discriminated by fMRI multivariate pattern analysis in FFA and PPA, more so for the current observer’s own gazes than for another observer’s gaze. The discrimination of the observer’s own gaze patterns was not observed in early visual areas (V1 – V4) or superior parietal lobule and frontal eye fields. These findings indicate a link between perception and action—the complex gaze patterns that are used to explore faces and houses—in the FFA and PPA.

scholarly journals Outcome contingency selectively affects the neural coding of outcomes but not of tasks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
David Wisniewski ◽  
Birte Forstmann ◽  
Marcel Brass
Keyword(s):  
Decision Making ◽  
Parietal Cortex ◽  
Neural Coding ◽  
Free Choice ◽  
Pattern Analysis ◽  
Maintenance Phase ◽  
Large Network ◽  
Multivariate Pattern Analysis ◽  
Multivariate Pattern

AbstractValue-based decision-making is ubiquitous in every-day life, and critically depends on the contingency between choices and their outcomes. Only if outcomes are contingent on our choices can we make meaningful value-based decisions. Here, we investigate the effect of outcome contingency on the neural coding of rewards and tasks. Participants performed a reversal-learning paradigm in which reward outcomes were contingent on trial-by-trial choices, and performed a ‘free choice’ paradigm in which rewards were random and not contingent on choices. We hypothesized that contingent outcomes enhance the neural coding of rewards and tasks, which was tested using multivariate pattern analysis of fMRI data. Reward outcomes were encoded in a large network including the striatum, dmPFC and parietal cortex, and these representations were indeed amplified for contingent rewards. Tasks were encoded in the dmPFC at the time of decision-making, and in parietal cortex in a subsequent maintenance phase. We found no evidence for contingency-dependent modulations of task signals, demonstrating highly similar coding across contingency conditions. Our findings suggest selective effects of contingency on reward coding only, and further highlight the role of dmPFC and parietal cortex in value-based decision-making, as these were the only regions strongly involved in both reward and task coding.

Role of the occipito-temporal theta rhythm in hand visual identification

2020 ◽  
Vol 123 (1) ◽  
pp. 167-177 ◽  
Author(s):  
Quentin Moreau ◽  
Eleonora Parrotta ◽  
Vanessa Era ◽  
Maria Luisa Martelli ◽  
Matteo Candidi
Keyword(s):  
Visual Processing ◽  
Functional Role ◽  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Theta Band ◽  
Time Frequency ◽  
Visual Identification ◽  
Multivariate Pattern ◽  
Healthy Participants

Neuroimaging and EEG studies have shown that passive observation of the full body and of specific body parts is associated with 1) activity of an occipito-temporal region named the extrastriate body area (EBA), 2) amplitude modulations of a specific posterior event-related potential (ERP) component (N1/N190), and 3) a theta-band (4–7 Hz) synchronization recorded from occipito-temporal electrodes compatible with the location of EBA. To characterize the functional role of the occipito-temporal theta-band increase during the processing of body-part stimuli, we recorded EEG from healthy participants while they were engaged in an identification task (match-to-sample) of images of hands and nonbody control images (leaves). In addition to confirming that occipito-temporal electrodes show a larger N1 for hand images compared with control stimuli, cluster-based analysis revealed an occipito-temporal cluster showing an increased theta power when hands are presented (compared with leaves) and show that this theta increase is higher for identified hands compared with nonidentified ones while not being significantly different between not identified nonhand stimuli. Finally, single trial multivariate pattern analysis revealed that time-frequency modulation in the theta band is a better marker for classifying the identification of hand images than the ERP modulation. The present results support the notion that theta activity over the occipito-temporal cortex is an informative marker of hand visual processing and may reflect the activity of a network coding for stimulus identity. NEW & NOTEWORTHY Hands provide crucial information regarding the identity of others, which is a key information for social processes. We recorded EEG activity of healthy participants during the visual identification of hand images. The combination of univariate and multivariate pattern analysis in time- and time-frequency domain highlights the functional role of theta (4–7 Hz) activity over visual areas during hand identification and emphasizes the robustness of this neuromarker in occipito-temporal visual processing dynamics.

scholarly journals A Distinct Role of the Temporal-Parietal Junction in Predicting Socially Guided Decisions

Science ◽  
2012 ◽  
Vol 337 (6090) ◽  
pp. 109-111 ◽  
Author(s):  
R. McKell Carter ◽  
Daniel L. Bowling ◽  
Crystal Reeck ◽  
Scott A. Huettel
Keyword(s):  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Incentive Compatible ◽  
Future Behavior ◽  
Human Participants ◽  
Multivariate Pattern ◽  
Distinct Role

To make adaptive decisions in a social context, humans must identify relevant agents in the environment, infer their underlying strategies and motivations, and predict their upcoming actions. We used functional magnetic resonance imaging, in conjunction with combinatorial multivariate pattern analysis, to predict human participants’ subsequent decisions in an incentive-compatible poker game. We found that signals from the temporal-parietal junction provided unique information about the nature of the upcoming decision, and that information was specific to decisions against agents who were both social and relevant for future behavior.

scholarly journals Different Neural Mechanisms Underlie Non-habitual Honesty and Non-habitual Cheating

2021 ◽  
Vol 15 ◽  
Author(s):  
Sebastian P. H. Speer ◽  
Ale Smidts ◽  
Maarten A. S. Boksem
Keyword(s):  
Cognitive Control ◽  
Pattern Analysis ◽  
Inferior Frontal Gyrus ◽  
Neural Mechanisms ◽  
Control Mechanisms ◽  
Multivariate Pattern Analysis ◽  
Automatic Response ◽  
Context Specific ◽  
Multivariate Pattern

There is a long-standing debate regarding the cognitive nature of (dis)honesty: Is honesty an automatic response or does it require willpower in the form of cognitive control in order to override an automatic dishonest response. In a recent study (Speer et al., 2020), we proposed a reconciliation of these opposing views by showing that activity in areas associated with cognitive control, particularly the inferior frontal gyrus (IFG), helped dishonest participants to be honest, whereas it enabled cheating for honest participants. These findings suggest that cognitive control is not needed to be honest or dishonest per se but that it depends on an individual’s moral default. However, while our findings provided insights into the role of cognitive control in overriding a moral default, they did not reveal whether overriding honest default behavior (non-habitual dishonesty) is the same as overriding dishonest default behavior (non-habitual honesty) at the neural level. This speaks to the question as to whether cognitive control mechanisms are domain-general or may be context specific. To address this, we applied multivariate pattern analysis to compare neural patterns of non-habitual honesty to non-habitual dishonesty. We found that these choices are differently encoded in the IFG, suggesting that engaging cognitive control to follow the norm (that cheating is wrong) fundamentally differs from applying control to violate this norm.

scholarly journals Decoding Digits and Dice with Magnetoencephalography: Evidence for a Shared Representation of Magnitude

2018 ◽  
Vol 30 (7) ◽  
pp. 999-1010 ◽  
Author(s):  
Lina Teichmann ◽  
Tijl Grootswagers ◽  
Thomas Carlson ◽  
Anina N. Rich
Keyword(s):  
Time Course ◽  
Numerical Cognition ◽  
Pattern Analysis ◽  
Brain Activity ◽  
High Temporal Resolution ◽  
Multivariate Pattern Analysis ◽  
Ongoing Debate ◽  
Activation Patterns ◽  
Magnitude Processing ◽  
Multivariate Pattern

Numerical format describes the way magnitude is conveyed, for example, as a digit (“3”) or Roman numeral (“III”). In the field of numerical cognition, there is an ongoing debate of whether magnitude representation is independent of numerical format. Here, we examine the time course of magnitude processing when using different symbolic formats. We presented participants with a series of digits and dice patterns corresponding to the magnitudes of 1 to 6 while performing a 1-back task on magnitude. Magnetoencephalography offers an opportunity to record brain activity with high temporal resolution. Multivariate pattern analysis applied to magnetoencephalographic data allows us to draw conclusions about brain activation patterns underlying information processing over time. The results show that we can cross-decode magnitude when training the classifier on magnitude presented in one symbolic format and testing the classifier on the other symbolic format. This suggests a similar representation of these numerical symbols. In addition, results from a time generalization analysis show that digits were accessed slightly earlier than dice, demonstrating temporal asynchronies in their shared representation of magnitude. Together, our methods allow a distinction between format-specific signals and format-independent representations of magnitude showing evidence that there is a shared representation of magnitude accessed via different symbols.

scholarly journals The Role of the Medial Prefrontal Cortex in Spatial Margin of Safety Calculations

2020 ◽  
Author(s):  
Song Qi ◽  
Logan Cross ◽  
Toby Wise ◽  
Xin Sui ◽  
John O’Doherty ◽  
...  
Keyword(s):  
Pattern Analysis ◽  
Functional Coupling ◽  
Positive Outcomes ◽  
Multivariate Pattern Analysis ◽  
Danger Signals ◽  
Margin Of Safety ◽  
Multivariate Pattern ◽  
Attack Location ◽  
Anterior Posterior

Humans, like many other animals, pre-empt danger by moving to locations that maximize their success at escaping future threats. We test the idea that spatial margin of safety (MOS) decisions, a form of pre-emptive avoidance, results in participants placing themselves closer to safer locations when facing more unpredictable threats. Using multivariate pattern analysis on fMRI data collected while subjects engaged in MOS decisions with varying attack location predictability, we show that while the hippocampus encodes MOS decisions across all types of threat, a vmPFC anterior-posterior gradient tracked threat predictability. The posterior vmPFC encoded for more unpredictable threat and showed functional coupling with the amygdala and hippocampus. Conversely, the anterior vmPFC was more active for the more predictable attacks and showed coupling with the striatum. Our findings suggest that when pre-empting danger, the anterior vmPFC may provide a safety signal, possibly via predictable positive outcomes, while the posterior vmPFC drives prospective danger signals.

scholarly journals Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data

2017 ◽  
Vol 29 (4) ◽  
pp. 677-697 ◽  
Author(s):  
Tijl Grootswagers ◽  
Susan G. Wardle ◽  
Thomas A. Carlson
Keyword(s):  
Time Series ◽  
Cognitive Neuroscience ◽  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Activation Patterns ◽  
Cognitive States ◽  
Classifier Selection ◽  
Computer Interfaces ◽  
Neuroimaging Data ◽  
Multivariate Pattern

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain–computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to “decode” different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

scholarly journals Multisensory coding in the multiple-demand regions: vibrotactile task information is coded in frontoparietal cortex

2017 ◽  
Vol 118 (2) ◽  
pp. 703-716 ◽  
Author(s):  
Alexandra Woolgar ◽  
Regine Zopf
Keyword(s):  
Pattern Analysis ◽  
Multivariate Pattern Analysis ◽  
Stimulus Information ◽  
General Role ◽  
Frontoparietal Cortex ◽  
Visual Tasks ◽  
Multivariate Pattern ◽  
Goal Directed Behavior ◽  
The Brain

How does the brain encode the breadth of information from our senses and use this to produce goal-directed behavior? A network of frontoparietal multiple-demand (MD) regions is implicated but has been studied almost exclusively in the context of visual tasks. We used multivariate pattern analysis of fMRI data to show that these regions encode tactile stimulus information, rules, and responses. This provides evidence for a domain-general role of the MD network in cognitive control.

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