Philippe G. Schyns

A mechanism for impaired fear recognition after amygdala damage

Ten years ago, we reported that SM, a patient with rare bilateral amygdala damage, showed an intriguing impairment in her ability to recognize fear from facial expressions. Since then, the importance of the amygdala in processing information about facial emotions has been borne out by a number of lesion and functional imaging studies. Yet the mechanism by which amygdala damage compromises fear recognition has not been identified. Returning to patient SM, we now show that her impairment stems from an inability to make normal use of information from the eye region of faces when judging emotions, a defect we trace to a lack of spontaneous fixations on the eyes during free viewing of faces. Although SM fails to look normally at the eye region in all facial expressions, her selective impairment in recognizing fear is explained by the fact that the eyes are the most important feature for identifying this emotion. Notably, SMs recognition of fearful faces became entirely normal when she was instructed explicitly to look at the eyes. This finding provides a mechanism to explain the amygdalas role in fear recognition, and points to new approaches for the possible rehabilitation of patients with defective emotion perception.

From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition

In very fast recognition tasks, scenes are identified as fast as isolated objects How can this efficiency be achieved, considering the large number of component objects and interfering factors, such as cast shadows and occlusions? Scene categories tend to have distinct and typical spatial organizations of their major components If human perceptual structures were tuned to extract this information early in processing, a coarse-to-fine process could account for efficient scene recognition A coarse description of the input scene (oriented “blobs” in a particular spatial organization) would initiate recognition before the identity of the objects is processed We report two experiments that contrast the respective roles of coarse and fine information in fast identification of natural scenes The first experiment investigated whether coarse and fine information were used at different stages of processing The second experiment tested whether coarse-to-fine processing accounts for fast scene categorization The data suggest that recognition occurs at both coarse and fine spatial scales By attending first to the coarse scale, the visual system can get a quick and rough estimate of the input to activate scene schemas in memory, attending to fine information allows refinement, or refutation, of the raw estimate

Bubbles: a technique to reveal the use of information in recognition tasks

Everyday, people flexibly perform different categorizations of common faces, objects and scenes. Intuition and scattered evidence suggest that these categorizations require the use of different visual information from the input. However, there is no unifying method, based on the categorization performance of subjects, that can isolate the information used. To this end, we developed Bubbles, a general technique that can assign the credit of human categorization performance to specific visual information. To illustrate the technique, we applied Bubbles on three categorization tasks (gender, expressive or not and identity) on the same set of faces, with human and ideal observers to compare the features they used.

The development of features in object concepts

According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individuals existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction.

Transmitting and Decoding Facial Expressions

This article examines the human face as a transmitter of expression signals and the brain as a decoder of these expression signals. If the face has evolved to optimize transmission of such signals, the basic facial expressions should have minimal overlap in their information. If the brain has evolved to optimize categorization of expressions, it should be efficient with the information available from the transmitter for the task. In this article, we characterize the information underlying the recognition of the six basic facial expression signals and evaluate how efficiently each expression is decoded by the underlying brain structures.

Coarse blobs or fine edges? Evidence that information diagnosticity changes the perception of complex visual stimuli

Efficient categorizations of complex visual stimuli require effective encodings of their distinctive properties. However, the question remains of how processes of object and scene categorization use the information associated with different perceptual spatial scales. The psychophysics of scale perception suggests that recognition uses coarse blobs before fine scale edges, because the former is perceptually available before the latter. Although possible, this perceptually determined scenario neglects the nature of the task the recognition system must solve. If different spatial scales transmit different information about the input, an identical scene might be flexibly encoded and perceived at the scale that optimizes information for the considered task-i.e., the diagnostic scale. This paper tests the hypothesis that scale diagnosticity can determine scale selection for recognition. Experiment 1 tested whether coarse and fine spatial scales were both available at the onset of scene categorization. The second experiment tested that the selection of one scale could change depending on the diagnostic information present at this scale. The third and fourth experiments investigated whether scale-specific cues were independently processed, or whether they perceptually cooperated in the recognition of the input scene. Results suggest that a mandatory low-level registration of multiple spatial scales promotes flexible scene encodings, perceptions, and categorizations.

Dr. Angry and Mr. Smile : when categorization flexibly modifies the perception of faces in rapid visual presentations

Are categorization and visual processing independent, with categorization operating late, on an already perceived input, or are they intertwined, with the act of categorization flexibly changing (i.e. cognitively penetrating) the early perception of the stimulus? We examined this issue in three experiments by applying different categorization tasks (gender, expressive or not, which expression and identity) to identical face stimuli. Stimuli were hybrids: they combined a man or a woman with a particular expression at a coarse spatial scale with a face of the opposite gender with a different expression at the fine spatial scale. Results suggested that the categorization task changes the spatial scales preferentially used and perceived for rapid recognition. A perceptual set effect is shown whereby the scale preference of an important categorization (e.g. identity) transfers to resolve other face categorizations (e.g. expressive or not, which expression). Together, the results suggest that categorization can be closely bound to perception.

Show Me the Features! Understanding Recognition From the Use of Visual Information

We propose an approach that allows a rigorous understanding of the visual categorization and recognition process without asking direct questions about unobservable memory representations. Our approach builds on the selective use of visual information in recognition and a new method (Bubbles) to depict and measure what this information is. We examine three face-recognition tasks (identity, gender, expressive or not) and establish the componential and holistic information responsible for recognition performance. On the basis of this information, we derive task-specific gradients of probability for the allocation of attention to the different regions of the face.

Diagnostic Colors Mediate Scene Recognition

In this research, we aim to ground scene recognition on information other than the identity of component objects. Specifically we seek to understand the structure of color cues that allows the express recognition of scene gists. Using the L*a*b* color space we examined the conditions under which chromatic cues concur with brightness to allow a viewer to recognize scenes at a glance. Using different methods, Experiments 1 and 2 tested the hypothesis that colors do contribute when they are diagnostic (i.e., predictive) of a scene category. Experiment 3 examined the structure of colored cues at different spatial scales that are responsible for the effects of color diagnosticity reported in Experiments 1 and 2. Together, the results suggest that colored blobs at a coarse spatial scale concur with luminance cues to form the relevant spatial layout that mediates express scene recognition.

Rhythmic TMS Causes Local Entrainment of Natural Oscillatory Signatures

Summary Background Neuronal elements underlying perception, cognition, and action exhibit distinct oscillatory phenomena, measured in humans by electro- or magnetoencephalography (EEG/MEG). So far, the correlative or causal nature of the link between brain oscillations and functions has remained elusive. A compelling demonstration of causality would primarily generate oscillatory signatures that are known to correlate with particular cognitive functions and then assess the behavioral consequences. Here, we provide the first direct evidence for causal entrainment of brain oscillations by transcranial magnetic stimulation (TMS) using concurrent EEG. Results We used rhythmic TMS bursts to directly interact with an MEG-identified parietal α-oscillator, activated by attention and linked to perception. With TMS bursts tuned to its preferred α-frequency (α-TMS), we confirmed the three main predictions of entrainment of a natural oscillator: (1) that α-oscillations are induced during α-TMS (reproducing an oscillatory signature of the stimulated parietal cortex), (2) that there is progressive enhancement of this α-activity (synchronizing the targeted, α-generator to the α-TMS train), and (3) that this depends on the pre-TMS phase of the background α-rhythm (entrainment of natural, ongoing α-oscillations). Control conditions testing different TMS burst profiles and TMS-EEG in a phantom head confirmed specificity of α-boosting to the case of synchronization between TMS train and neural oscillator. Conclusions The periodic electromagnetic force that is generated during rhythmic TMS can cause local entrainment of natural brain oscillations, emulating oscillatory signatures activated by cognitive tasks. This reveals a new mechanism of online TMS action on brain activity and can account for frequency-specific behavioral TMS effects at the level of biologically relevant rhythms.