Didem Gokcay

Relative Shift in Activity from Medial to Lateral Frontal Cortex During Internally Versus Externally Guided Word Generation

Goldberg (1985) hypothesized that as language output changes from internally to externally guided production, activity shifts from supplementary motor area (SMA) to lateral premotor areas, including Brocas area. To test this hypothesis, 15 right-handed native English speakers performed three word generation tasks varying in the amount of internal guidance and a repetition task during functional magnetic resonance imaging (fMRI). Volumes of significant activity for each task versus a resting state were derived using voxel-by-voxel repeated-measures t tests (p < .001) across subjects. Changes in the size of activity volumes for left medial frontal regions (SMA and pre-SMA/BA 32) versus left lateral frontal regions (Brocas area, inferior frontal sulcus) were assessed as internal guidance of word generation decreased and external guidance increased. Comparing SMA to Brocas area, Goldbergs hypothesis was not verified. However, pre-SMA/BA 32 activity volumes decreased significantly and inferior frontal sulcus activity volumes increased significantly as word generation tasks moved from internally to externally guided.

Processing Words with Emotional Connotation: An fMRI Study of Time Course and Laterality in Rostral Frontal and Retrosplenial Cortices

Responses of rostral frontal and retrosplenial cortices to the emotional significance of words were measured using functional magnetic resonance imaging (fMRI). Twenty-six strongly righthanded participants engaged in a language task that alternated between silent word generation to categories with positive, negative, or neutral emotional connotation and a baseline task of silent repetition of emotionally neutral words. Activation uniquely associated with word generation to categories with positive or negative versus neutral emotional connotation occurred bilaterally in rostral frontal and retrosplenial cortices. Furthermore, the time courses of activity in these areas differed, indicating that they subserve different functions in processing the emotional connotation of words. Namely, the retrosplenial cortex appears to be involved in evaluating the emotional salience of information from external sources, whereas the rostral frontal cortex also plays a role in internal generation of words with emotional connotation. In both areas, activity associated with positive or negative emotional connotation was more extensive in the left hemisphere than the right, regardless of valence, presumably due to the language demands of word generation. The present findings localize specific areas in the brain that are involved in processing emotional meaning of words within the brains distributed semantic system. In addition, time course analysis reveals diverging mechanisms in anterior and posterior cortical areas during processing of words with emotional significance.

Left-hemisphere processing of emotional connotation during word generation.

Areas of the brains left hemisphere involved in retrieving words with emotional connotations were studied with fMRI. Participants silently generated words from different semantic categories which evoked either words with emotional connotations or emotionally neutral words. Participants repeated emotionally neutral words as a control task. Compared with generation of emotionally neutral words, generation of words with emotional connotations engaged cortices near the left frontal and temporal poles which are connected to the limbic system. Thus, emotional connotations of words are processed in or near cortices with access to emotional experience.

Semantic monitoring of words with emotional connotation during fMRI: Contribution of anterior left frontal cortex

Previous studies showed that cortex in the anterior portions of the left frontal and temporal lobes participates in generating words with emotional connotations and processing pictures with emotional content. If these cortices process the semantic attribute of emotional connotation, they should be active whenever processing emotional connotation, without respect to modality of input or mode of output. Thus, we hypothesized that they would activate during monitoring of words with emotional connotations. Sixteen normal subjects performed semantic monitoring of words with emotional connotations, animal names, and implement names during fMRI. Cortex in the anterior left frontal lobe demonstrated significant activity for monitoring words with emotional connotations compared to monitoring tone sequences, animal names, or implement names. Together, the current and previous results implicate cortex in the anterior left frontal lobe in semantic processing of emotional connotation, consistent with connections of this cortex to paralimbic association areas. Current findings also indicate that neural substrates for processing emotional connotation are independent of substrates for processing the categories of living and nonliving things.

Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific Perspectives

Living in a computer era, the synergy between man and machine is a must, as the computers are integrated into our everyday life. The computers are surrounding us but their interfaces are far from being friendly. One possible approach to create a friendlier human-computer interface is to build an emotion-sensitive machine that should be able to recognize a human facial expression with a satisfactory classification rate and, eventually, to synthesize an artificial facial expression onto embodied conversational agents (ECAs), defined as friendly and intelligent user interfaces built to mimic human gestures, speech or facial expressions. Computer scientists working in computer interfaces (HCI) put up impressive efforts to create a fully automatic system capable to identifying and generating photo realistic human facial expressions through animation. This chapter aims at presenting current state-of-the-art techniques and approaches developed over time to deal with facial expression synthesis and animation. The topic’s importance will be further highlighted through modern applications including multimedia applications. The chapter ends up with discussions and open problems.

Quantification of the Effects of Transcutaneous Electrical Nerve Stimulation With Functional Magnetic Resonance Imaging: A Double-Blind Randomized Placebo-Controlled Study

OBJECTIVE To evaluate the effects of transcutaneous electric nerve stimulation (TENS) by using functional magnetic resonance imaging (fMRI) in patients with carpal tunnel syndrome (CTS). DESIGN Randomized controlled trial. SETTINGS University medical center and an outpatient imaging center. PARTICIPANTS Female patients with CTS (n=20) were randomized into 2 groups receiving either TENS (n=10) or sham TENS (n=10). In both groups, an initial baseline fMRI session was performed via stimulating digits 2, 5, and 3 in turn, 1 scan run for each. TENS versus sham TENS treatment was given, and a repeat imaging was performed starting 20 minutes after the treatment as follows: second finger on the 20th minute, fifth finger on the 25th minute (ulnar nerve innervated control finger), and third finger on the 30th min. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURE Differences in fMRI activation between the 2 groups were evaluated. RESULTS Our results demonstrated that 20 to 25 minutes after TENS treatment-but not in the sham TENS group-a significant fMRI signal decrease for digit 2 (post-TENS vs baseline) was observed in the secondary somatosensory regions, ipsilateral primary motor cortex (M1), contralateral supplementary motor cortex (SMA), contralateral parahippocampal gyrus, contralateral lingual gyrus, and bilateral superior temporal gyrus. Measurements on the 25th to 30th minutes for digit 5 were similar between the groups, with presence of activities in areas other than generally activated regions because of painful stimuli. Thirty to 35 minutes after TENS treatment, a significant fMRI signal decrease for digit 3 was detected in the contralateral M1 and contralateral SMA only in the TENS group. CONCLUSIONS Our findings showed that TENS treatment significantly decreased the pain-related cortical activations caused by stimulation of the median nerve-innervated fingers up to 35 minutes after treatment.

Valence-based Word-Face Stroop task reveals differential emotional interference in patients with major depression.

Word-Face Stroop task creates emotional conflict between affective words and affective faces. In this task, healthy participants consistently slow down while responding to incongruent cases. Such interference related slowdown is associated with recruitment of inhibitory processes to eliminate task-irrelevant information. We created a valence-based Word-Face Stroop task, in which participants were asked to indicate whether the words in the foreground are positive, negative or neutral. Healthy participants were faster and more accurate than un-medicated patients with major depression disorder (MDD). In addition, a significant congruence by group interaction is observed: healthy participants slowed down for incongruent cases, but MDD patients did not. Furthermore, for the negative words, healthy individuals made more errors while responding to incongruent cases but MDD patients made the lowest number of errors for this category. The emotional percepts of the patients were intact, because correct response rates in word valence judgments for positive/negative words, and reaction times for happy/sad faces had similar patterns with those of controls. These findings are supported by the analytical rumination interpretation of depression: patients lose speed/accuracy in laboratory tasks due to processing load spent during continuous rumination. However, for tasks in line with their preoccupation, continual practice makes the patients more vigilant and adept.

Stress Detection in Human–Computer Interaction: Fusion of Pupil Dilation and Facial Temperature Features

ABSTRACT In order to differentiate the affective state of a computer user as it changes from relaxation to stress, features derived from pupil dilation and periorbital temperature can be utilized. Absolute signal values and measurements computed from these can be fused to increase the accuracy of affective classification. In this study, entropy in a sliding window was used to accommodate the time differences in the physiological rise and fall profiles of pupil and thermal data. Two methods, decision tree and Adaboost with Random Forest (ABRF), were used for classification tests. Detection accuracy of stressful states varied between 65% and 83.8%. Best results can be reported as 83.9% for sensitivity and 83.8% for specificity. ABRF classifier outperformed the decision tree model. This study emphasizes the importance of data fusion, particularly when physiological signals differ with respect to their rise and fall windows across time. Use of entropy within a predefined time window provides a useful set of features to combine with actual measurements. Furthermore, the collection of pupil and thermal data is feasible because surface sensors are eliminated.

LOFA: software for individualized localization of functional MRI activity.

Although PET, SPECT, and fMRI studies have led to significant advances in functional mapping of the human brain, precise localization and quantification of activity in individual brains require additional procedures. Difficulties to be addressed by a localization strategy are: resolution of individual anatomic differences, differentiation of functional activity in closely juxtaposed brain regions, and management of multiple intricately shaped 3D anatomic structures. In this paper, we describe a localization tool, LOFA, which addresses these problems by forming ROIs with a user-driven interface. Using LOFA, complex 3D anatomy can be defined through open or closed loops and anatomic landmarks. Resulting partitions can be overlaid on top of each other to form multiple regions of interest (ROIs), and functional activity in these ROIs can be extracted individually, one after the other. LOFA introduces important paradigmatic advances over the other ROI analysis methods. The toolbox is interactive, fully compatible with AFNI (MCW), and requires Pv-Wave (VNI Inc.) license to run.

Role of pupil dilation and facial temperature features in stress detection

In order to differentiate the affective state of a computer user as it changes from relaxation to stress, features derived from pupil dilation and periorbital temperature are processed with machine learning techniques. When absolute signal values are used together with entropy based features, the accuracy of affective classification is observed to increase. When decision tree (C4.5) is tested for classification, best accuracy of detection of neutral versus aroused states is above 90%.