Goal-Directed Processing of Naturalistic Stimuli Modulates Large-Scale Functional Connectivity

Humans selectively process external information according to their internal goals. Previous studies have found that cortical activity and interactions between specific cortical areas such as frontal-parietal regions are modulated by behavioral goals. However, these results are largely based on simple stimuli and task rules in laboratory settings. Here, we investigated how top-down goals modulate whole-brain functional connectivity (FC) under naturalistic conditions. Analyses were conducted on a publicly available functional magnetic resonance imaging (fMRI) dataset (OpenfMRI database, accession number: ds000233) collected on twelve participants who made either behavioral or taxonomic judgments of behaving animals containing in naturalistic video clips. The task-evoked FC patterns of the participants were extracted using a novel inter-subject functional correlation (ISFC) method that increases the signal-to-noise ratio for detecting task-induced inter-regional correlation compared with standard FC analysis. Using multivariate pattern analysis (MVPA) methods, we successfully predicted the task goals of the participants with ISFC patterns but not with standard FC patterns, suggests that the ISFC method may be an efficient tool for exploring subtle network differences between brain states. We further examined the predictive power of several canonical brain networks and found that many within-network and across-network ISFC measures supported task goals classification. Our findings suggest that goal-directed processing of naturalistic stimuli systematically modulates large-scale brain networks but is not limited to the local neural activity or connectivity of specific regions

A Cognitive Neuroscience of Social Groups

We used functional magnetic resonance imaging to investigate how the human brain processes information about social groups in three domains. Study 1: Semantic knowledge. Participants were scanned while they answered questions about their knowledge of both social categories and non-social categories like object groups and species of nonhuman animals. Brain regions previously identified in processing semantic information are more robustly engaged by nonsocial semantics than stereotypes. In contrast, stereotypes elicit greater activity in brain regions implicated in social cognition. These results suggest that stereotypes should be considered distinct from other forms of semantic knowledge. Study 2: Theory of mind. Participants were scanned while they answered questions about the mental states and physical attributes of individual people and groups. Regions previously associated with mentalizing about individuals were also robustly responsive to judgments of groups. However, multivariate searchlight analysis revealed that several of these regions showed distinct multivoxel patterns of response to groups and individual people. These findings suggest that perceivers mentalize about groups in a manner qualitatively similar to mentalizing about individual people, but that the brain nevertheless maintains important distinctions between the representations of such entities. Study 3: Social categorization. Participants were scanned while they categorized the sex and race of unfamiliar Black men, Black women, White men, and White women. Multivariate pattern analysis revealed that multivoxel patterns in FFA--but not other face-selective brain regions, other category-selective brain regions, or early visual cortex--differentiated faces by sex and race. Specifically, patterns of voxel-based responses were more similar between individuals of the same sex than between men and women, and between individuals of the same race than between Black and White individuals. These results suggest that FFA represents the sex and race of faces. Together, these three studies contribute to a growing cognitive neuroscience of social groups.Psycholog

Interpreting EEG and MEG signal modulation in response to facial features: the influence of top-down task demands on visual processing strategies

The visual processing of faces is a fast and efficient feat that our visual system usually accomplishes many times a day. The N170 (an Event-Related Potential) and the M170 (an Event-Related Magnetic Field) are thought to be prominent markers of the face perception process in the ventral stream of visual processing that occur ~ 170 ms after stimulus onset. The question of whether face processing at the time window of the N170 and M170 is automatically driven by bottom-up visual processing only, or whether it is also modulated by top-down control, is still debated in the literature. However, it is known from research on general visual processing, that top-down control can be exerted much earlier along the visual processing stream than the N170 and M170 take place. I conducted two studies, each consisting of two face categorization tasks. In order to examine the influence of top-down control on the processing of faces, I changed the task demands from one task to the next, while presenting the same set of face stimuli. In the first study, I recorded participants’ EEG signal in response to faces while they performed both a Gender task and an Expression task on a set of expressive face stimuli. Analyses using Bubbles (Gosselin & Schyns, 2001) and Classification Image techniques revealed significant task modulations of the N170 ERPs (peaks and amplitudes) and the peak latency of maximum information sensitivity to key facial features. However, task demands did not change the information processing during the N170 with respect to behaviourally diagnostic information. Rather, the N170 seemed to integrate gender and expression diagnostic information equally in both tasks. In the second study, participants completed the same behavioural tasks as in the first study (Gender and Expression), but this time their MEG signal was recorded in order to allow for precise source localisation. After determining the active sources during the M170 time window, a Mutual Information analysis in connection with Bubbles was used to examine voxel sensitivity to both the task-relevant and the task-irrelevant face category. When a face category was relevant for the task, sensitivity to it was usually higher and peaked in different voxels than sensitivity to the task-irrelevant face category. In addition, voxels predictive of categorization accuracy were shown to be sensitive to task-relevant, behaviourally diagnostic facial features only. I conclude that facial feature integration during both N170 and M170 is subject to top-down control. The results are discussed against the background of known face processing models and current research findings on visual processing

COGNITIVE CONTROL OF ABSTRACT TASK RULES

Humans can perform complex behavior according to the goal of the task and its rules, and swiftly adapt their behavior to the new rule when there is a change in circumstances. How do our brains select and implement the appropriate rules? Cognitive control is the ability to select task-relevant information over other irrelevant distracting information. The neural mechanism of cognitive control is typically described in terms of resolution of conflict among sensory representations of stimuli or among competing motor responses. However, an understanding of the mechanisms by which the brain executes control over abstract, learned, representations of rule information has remained elusive. Moreover, it is unclear whether a single control mechanism governs different sources of conflict among task rules or whether dissociable mechanisms of cognitive control exist. In this dissertation, we used functional neuroimaging and behavioral experiments to examine the conflict-driven cognitive control mechanisms in humans for resolving conflict among abstract representations of task rules. By using a newly devised paradigm that can directly manipulate the degree of conflict at the task-rule level, we found conflict among abstract representations of task rules was resolved by feedback from the right inferior frontal gyrus enhancing the activity of the brain region processing the relevant abstract information, rather than suppressing the activity of the brain region processing the irrelevant abstract information. To examine the generality of the conflict-driven cognitive control mechanism, we independently manipulated the levels of conflict for task switching (switch/repeat) and cue congruency (incongruent/congruent) using a factorial design. We found these two sources of task-rule conflict recruit different brain circuits for conflict resolution. Furthermore, by employing a behavioral proportion manipulation (changing the frequency of conflict trials within a single block), we found these two sources of rule-related conflict respond differently to the same manipulation. These results support a conflict-specific cognitive control account in which qualitatively distinct mechanisms recruit separate neural resources to resolve each type of conflict independently. Together, these findings provide a mechanistic view of how cognitive control of abstract rule representations is accomplished

Feature-Specific Patterns of Attention and Functional Connectivity in Human Visual Cortex

The ability to successfully allocate attention to a particular space or feature in the visual world is vital for successful day-to-day functioning. Attention refers to a narrowing of focus, with increased processing of an attended attribute at the expense of other non-attended dimensions. This attentional mechanism can modulate activity in the visual cortex and beyond. However, the full range of spatial scales at which attentional effects are evident in the visual cortex as a function of task is still relatively little understood. This thesis aimed to investigate the effects of attentional modulation across the visual cortex at several spatial scales, examining activation at the level of mean activity in individual regions-of-interest (ROIs), comparing patterns of voxel-level activity, and employing connectivity-style approaches to examine communication between multiple visual areas simultaneously

Mécanismes cognitifs dans la catégorisation d'objets visuels

La catégorisation est un processus fondamental de la reconnaissance d'objets. Pour comprendre ses mécanismes sous-jacents, cette thèse interroge le rôle du niveau de catégorisation, de l'attention, de la mémoire, et de la relation entre les catégories d'objets, dans la catégorisation de scènes naturelles. Les résultats de la première étude indiquent que les performances de catégorisation sont influencées par les caractéristiques diagnostiques de la tâche. Une seconde étude montre que des objets naturels peuvent être catégorisés en quasi-absence d'attention. Les résultats de la troisième étude indiquent que les scènes sont encodées en mémoire à long-terme sans instruction explicite et catégorisées automatiquement. La dernière étude explore les interactions entre deux représentations d'objets actives simultanément. Plus le degré de relation entre deux objets est élevé, plus le traitement du second objet est affecté. Pour expliquer ces résultats un modèle, inspiré de la physiologie, est proposé qui postule que le niveau d'interaction entre des catégories d'objet actives simultanément dépend du niveau de chevauchement entre les patterns d'activité du cortex inféro-temporal produits par chacun des objets. Les résultats de cette thèse sont compatibles avec l'idée que les caractéristiques visuelles des objets sont traitées automatiquement (étude 3) en quasi-absence d'attention (étude 2) et représentées dans la voie visuelle ventrale de façon distribuée et continue. Les performances de catégorisation dépendraient de la similarité des catégories cibles et distracteurs (étude 1) ou de la similarité entre les représentations actives de deux objets (étude 4).Categorization is a fundamental process of object recognition. To determine its underlying mechanisms, a series of experiments examined the roles of stimulus properties, categorization level, attention, memory, and category-relatedness in natural scene categorization tasks. The results of the first study suggest that categorization performance is driven by characteristics that are diagnostic for the task. A second study shows that visual objects embedded in complex natural scenes can be categorized in the near-absence of attention. The results of a third study suggest that long-term encoding of complex scenes happens without any explicit instruction, and information about object categories is processed automatically. The final study explores the interaction between two concurrently active category representations by presenting two objects in a rapid sequence. The greater the degree of relatedness between two objects, the more affected the processing of the second object is. To explain these results a physiologically inspired model is proposed, which posits that the extent of interaction between concurrently active objects depends on the extent of overlap between the activity patterns in the infero-temporal cortex elicited by the two objects. The results of this thesis support the idea that visual object characteristics are processed automatically (study 3) in the near-absence of attention (study 2) and represented in the ventral stream in a distributed and continuous manner. Categorization performance would depend on the similarity between and within the target and the distractor categories (study 1) or on the similarity between two active object representations (study 4)