Nickolaos F. Fragopanagos

Influence of attentional demands on the processing of emotional facial expressions in the amygdala

Recent studies have cast doubts on the appealing idea that the processing of threat-related stimuli in the amygdala is unconstrained by the availability of attentional resources. However, these studies exclusively used face stimuli presented at fixation and it is unclear whether their conclusion can apply to peripheral face stimuli. Thus, we designed an experiment in which we manipulated the perceptual attentional load of the task used to divert attention from peripheral face stimuli: participants were presented simultaneously with four peripheral pictures (two faces, either both neutral or both fearful, and two houses) that were slightly tilted, and had to match two of these pictures (defined by their position on the screen) either for orientation of the tilt or for identity. The identity task was confirmed to involve greater attentional load than the orientation task by differences in accuracy, reaction times, subsequent face recognition performance, and patterns of activation in several cortical regions. In the orientation task, ignored fearful faces led to stronger activation in the right amygdala than ignored neutral faces. However, this differential response was abolished when participants performed the difficult identity-matching task. Thus, emotional processing of peripheral faces in the amygdala also appears to depend on the available perceptual attentional resources.

Efficient Attentional Selection Predicts Distractor Devaluation: Event-related Potential Evidence for a Direct Link between Attention and Emotion

Links between attention and emotion were investigated by obtaining electrophysiological measures of attentional selectivity together with behavioral measures of affective evaluation. Participants were asked to rate faces that had just been presented as targets or distractors in a visual search task. Distractors were rated as less trustworthy than targets. To study the association between the efficiency of selective attention during visual search and subsequent emotional responses, the N2pc component was quantified as a function of evaluative judgments. Evaluation of distractor faces (but not target faces) covaried with selective attention. On trials where distractors were later judged negatively, the N2pc emerged earlier, demonstrating that attention was strongly biased toward target events, and distractors were effectively inhibited. When previous distractors were judged positively, the N2pc was delayed, indicating unfocused attention to the target and less distractor suppression. Variations in attentional selectivity across trials can predict subsequent emotional responses, strongly suggesting that attention is closely associated with subsequent affective evaluation.

Feature-based inhibition underlies the affective consequences of attention

Rapid selection of a target in the presence of similar distractors can cause subsequent affective evaluation of a distractor to be more negative than that for the selected object. This distractor devaluation effect has previously been attributed to an association of attentional inhibition with the distractors representation. Here, we investigated whether the associated inhibition leading to distractor devaluation is object based or feature based. Using colour-tinted face and building stimuli in a two-item simple visual search, followed by evaluation of face stimuli on a trustworthiness scale, we report that emotional evaluation was modified by prior attention whenever the search stimuli and the to-be-evaluated face shared the distractor feature, regardless of whether face identity seen in the two successive tasks matched or not. These data support the notion that inhibition can be feature-based and show that such inhibition can have emotional consequences.

2006 Special Issue: Attention as a controller

We investigate, by constructing suitable models, the manner in which attention and executive function are observed to interact, including some aspects of the influence of value/emotion on this interaction. Attention is modelled using the recent engineering control model (Corollary Discharge of Attention Movement, CODAM), which includes suitable working memory components. We extend this model to take account of various executive functions performed in working memory under attention control, such as rehearsal, substitution and transformation of buffered activity. How these are achieved is specified in suitable extension of CODAM. Further extensions are then made to include emotional values of stimuli. All of these extensions are supported by recent experimental brain imaging data on various working memory tasks, which are simulated with reasonable accuracy. We conclude our analysis by a discussion on the nature of cognition as seen in terms of the resulting extended attention model framework.

Modelling the interaction of attention and emotion

We review a recently developed engineering control approach to attention, presenting detailed attention control function assignments to the wealth of brain modules experimentally observed. The control system is extended to include biasing by emotional valence, with qualitative analysis given of a range of emotion paradigms and more detailed simulation described for two further paradigms. The implications of these results for better understanding of the interaction of emotion and attention concludes the paper, and in, particular gives a possible resolution of the question as to unaware versus aware processing of emotional material.

Emotion in speech: towards an integration of linguistic, paralinguistic, and psychological analysis

If speech analysis is to detect a speakers emotional state, it needs to derive information from both linguistic information, i.e., the qualitative targets that the speaker has attained (or approximated), conforming to the rules of language; and paralinguistic information, i.e., allowed variations in the way that qualitative linguistic targets are realised. It also needs an appropriate representation of emotional states. The ERMIS project addresses the integration problem that those requirements pose. It mainly comprises a paralinguistic analysis and a robust speech recognition module. Descriptions of emotionality are derived from these modules following psychological and linguistic research that indicates the information likely to be available. We argue that progress in registering emotional states depends on establishing an overall framework of at least this level of complexity.

Modelling working memory through attentional mechanisms

Recent studies of working memory have shown that the network of brain areas that supports working memory function overlaps heavily with the well studied network of selective attention. It has thus been suggested that working memory may operate by means of a repeated focusing of attention on the internal representations of the items that need to be maintained. We have employed our CODAM model of attention to simulate a specific working memory paradigm based on precisely this concept of ‘refreshing’ internal representations using attention. We propose here that the well known capacity limit of working memory can be attributed to the ‘scarceness’ of attentional resources. The specific mechanism of CODAM for modelling such scarceness is used in the paradigm to explain the behavioural and brain imaging data. This and related paradigms allow us to extend the specification of CODAM sites and functions to more detailed executive functions under executive control.

ANNA: An Artificial Neural Network for Attention to Emotional Recognition

Emotional experience has two distinct components in human beings: ‘automatic’ and ‘attended’. The former of these is based more heavily on the ventral and limbic areas of the brain; the attention part is concerned with cognitive aspects of experience, and involves more dorsal components. A rapidly increasing body of knowledge on these two separate components of human experience is being developed through brain imaging, single cell recording and deficit analyses under emotional as compared to neutral inputs. We start by summarizing this data. We then incorporate the data into a recently developed engineering control model of attention and motor responses. The crucial extension of this model involves a ventral/limbic brain network building representations of salience and valence. A simulation of a simple paradigm is used to demonstrate the considerable dissociation possible between the cognitive and emotional components. The system is developed to give an extension of standard artificial neural network architectures to a new class, in which attention effects are explicitly included through adaptive feedback modulation. Learning laws are developed which extend BEP to the attention case. An artificial emotion recognition system is developed as part of this architectural analysis.