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ARTICLE
Year : 2008  |  Volume : 30  |  Issue : 1  |  Page : 32-38 Table of Contents   

Trends- A tool for recognition of emotions in neuropsychiatric disorders


1 Dept. of Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore - 560029, India
2 Dept. of Biostatistics, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore - 560029, India
3 Dept. of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore - 560029, India

Correspondence Address:
Rishikesh V Behere
Dept. of Psychiatry, National Institute of Mental Health & Neurosciences, Hosur Road, Bangalore-560029
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0253-7176.43132

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   Abstract 

Defects in social cognition which includes Facial Emotion Recognition Deficits [FERD] have been consistently demonstrated in most neuropsychiatric disorders. Influences of culture, age & sex on emotional expression and perception necessitates that a tool standardized in the Indian population be developed to study these deficits in Indian patients.
Four experienced and trained actors (one young male, one young female, one older male and one older female) emoted six basic emotions, namely happy, sad, fear, anger, surprise and disgust at two different intensities [i.e. high and low] along with neutral facial expressions. 52 still images and 28 video clips were obtained. These images were then validated by 51 students from various mental health disciplines and five qualified psychiatrists. On statistical analysis the tool was found to have good inter­rater agreement and internal consistency.
TRENDS is a tool validated for use in the Indian population, which captures the full range and nature of emotional expressions akin to real life situations and can be utilized for future behavioral and functional imaging studies in Indian patients. Such research can give useful insights into the neurobiological basis of neuropsychiatric disorders and has important implications for improving socio-occupational functioning.


How to cite this article:
Behere RV, Raghunandan V, Venkatasubramanian G, Subbakrishna D K, Jayakumar P N, Gangadhar B N. Trends- A tool for recognition of emotions in neuropsychiatric disorders. Indian J Psychol Med 2008;30:32-8

How to cite this URL:
Behere RV, Raghunandan V, Venkatasubramanian G, Subbakrishna D K, Jayakumar P N, Gangadhar B N. Trends- A tool for recognition of emotions in neuropsychiatric disorders. Indian J Psychol Med [serial online] 2008 [cited 2019 Sep 22];30:32-8. Available from: http://www.ijpm.info/text.asp?2008/30/1/32/43132


   Introduction Top


Emotion Recognition - Basic Concepts

Homo sapiens are considered as social animals with a highly evolved 'social brain' as an adaptive response to an increasingly complex social environment [1] . Charles Darwin in his historical book has suggested that emotions in man have evolved through a process of natural selection and facial expression is an important means to communicate emotions and intentions [2] . The ability to understand the mental state of others, and recognize facial emotional expressions form an important part of social cognition which also involves - face perception, emotional processing, theory of mind & self-reference and working memory [3].

Recent advances in cognitive neurosciences and functional neuroimaging studies show that emotional processing is not an isolated event but closely mediates cognition and behavior. Preattentive processing of emotional events has been shown to enhance perception. This privileged processing of emotional events enhances explicit memory for these events by activation of the amygdala. Emotional inputs from the ventromedial prefrontal cortex have been shown to influence high-level decision making [4] . Philips et al, [5] have suggested that emotional processing may be dependent upon the functioning of two neural systems: a ventral system including the amygdala, insula, ventral striatum, and ventral regions of the anterior cingulate gyrus, and prefrontal cortex, which is important for identification of the emotional significance of environmental stimuli and the production of affective states. The dorsal system includes the hippocampus, dorsal regions of the anterior cingulate gyrus and the prefrontal cortex which is important for performance of executive functions and effortful rather than automatic regulation of affective states.

Importance of Emotion Recognition Research

Emotional dys-regulation is a common feature of most psychiatric disorders ranging from psychosis, mood disorders, and anxiety spectrum disorders. Facial expressions of emotions have been used as probes in many behavioral and neuroimaging studies in various neuropsychiatric disorders [6] . In schizophrenia, Facial Emotion Recognition Deficits [FERD] are correlated with severe symptomatology [7] . These deficits are specific for identifying negative emotions [8] and also patients do not seem to benefit from greater emotional intensity [9]. However these deficits are not correlated with duration of symptoms, demographic characteristics [10] or therapeutic effect of antipsychotics [11] indicating that they may be a trait marker for schizophrenia.

FERD have also been found in other psychiatric disorders like bipolar affective disorder [12] and body dysmorphic disorder [13] . FERD has been well demonstrated in various neurological disorders. In stroke patients emotion recognition deficits are known [14] to occur more in right hemispheric lesions [15],[16] and in isolated thalamic lesions [17] Deficits in recognition of negative emotions are seen in early Alzheimer's disease [18] and Fronto Temporal Dementia [19] . It is hypothesized that some of the behavioral problems in dementia could be related to these FERD [20] . Similar deficits in negative emotions of anger and disgust are also seen in Huntington's disease [21] . FERD are well demonstrated in Parkinson's disease [22] more so for disgust in un-medicated patients [23] and in those with associated cognitive impairment [24] . Neurophysiological studies show amygdala under activation in response to fearful stimuli In  Parkinsonism More Details, [25] similar findings are also seen in patients with post encephalitic damage to amygdala [26] .

Tools for Assessment of Emotion Recognition

Pioneering work in the field of emotion recognition was done by Izard [27] and Ekman and Friesen. [28] They gave a description of the 6 basic human emotions of happy, sad, fear, anger, surprise and disgust and also first devised a tool with a set of black and white photographs of posed emotions restricted in ethnicity and age. Other such tools developed are the FEEL test [29] taken from the JACFEE series (Japanese and Caucasian Facial Expressions of Emotion), [30]. The Facial Discrimination Task [FDT] [31] which are a set of images of emotions expressed by trained actors developed at the university of Pennsylvania which were later validated. [32] The Penn Emotion Recognition Test is set of 96 validated images consisting of 16 neutral images and 8 high and low intensity images for each basic emotion except surprise. [33] A method of developing 3 dimensional images from 2 dimensional images has also been developed for use in functional MRI studies of FERD. [6] An inter rater agreement of 60% [34] to 80% [35],[36] between healthy volunteers has been generally accepted for the images used as stimuli in various studies in FERD. Only 2 studies have used dynamic (video) images as stimuli. [37],[38]

Need for a culturally sensitive emotion recognition assessment tool

Perception of emotion is known to be influenced by ethnicity. [39] The main cultural difference found has been that among Western cultures, which are more open versus conservative Asian cultures, Americans tend to appraise emotional situations as more pleasant when compared to East Asians. [40] In a meta-analysis of cultural specificity of emotion recognition an in group advantage was found where emotions were recognized more accurately when they were both expressed and perceived by members of the same national or ethnic group. [41] In a cross cultural study, Indian schizophrenia patients and controls were found to perform poorly as compared to their American and German counterparts on tasks of emotion discrimination using facial expression of Caucasian actors. [42] The authors proposed that this was due to the unfamiliarity of the Indian sample to Caucasian faces. A more recent study; where groups of normal Indian, American and Japanese subjects viewed facial emotions expressed by actors of all 3 nationalities, supported this in group advantage. [43] Culture is also known to play a role in influencing course and outcome and planning of multidisciplinary treatments of mental disorders. [44] Hence data on FERD studies on western population cannot be generalized to Indian patients. Studies have shown that female patients perform better on emotion recognition tasks and overall female faces are better recognized suggesting a sex difference in FERD. [9] Age also seems to play a role in influencing emotion recognition. In a study young bipolar patients were found to misidentify faces of same peer age group as angry while no such error was found with adult faces. [45] Hence any tool used to study FERD should take into account variations of age and sex on emotional expressions.

Limitations of the available 'Indian' tool

To the best of our knowledge, only one emotion recognition tool specific for Indian subjects has been published till date (as per PubMed & Google Scholar search on 29 July 2007). In India Mandal [46] has validated a set of 30 photographs of Indian actors expressing 6 basic emotions. These photographs had a 70% agreement and at least 3 point discrimination on a 7 point intensity rating between raters. However these were black and white photographs. Stimuli capturing more closely the dynamic, full color, full-channel nature of emotional expressions would bolster ecological validity of future studies. [43] Also, use of dynamic stimuli is more akin to real life situations, and hence has greater implications in studies for understanding FERD.

TRENDS - A Novel "Indian" Tool

Given the influence of ethnicity, age and sex on emotional expression and perception and the need for stimuli capturing the dynamic, full color, full­channel nature of emotional expressions for research in the field of FERD; it is imperative that a tool be developed for research in Indian patients. Unfortunately, no such tool with specificity for Indian subjects incorporating these entire methodological rigors is available. The current study aimed at first time development of an advanced tool for emotion recognition appropriate for research in Indian subjects namely - the Tool for Recognition of Emotions in Neuropsychiatric DisorderS with the acronym - TRENDS.

Methods: Preparation of the tool:

The tool consists of two arms - the static (still photographs) and the dynamic (videos) arm. Four trained actors (one young male, one young female, one older male and one older female) who had an experience of around ten years acting in theatre were chosen. They were asked to emote the six basic emotions of happy, sad, fear, anger, surprise and disgust at two different intensities high and low along with neutral facial expressions. Still photographs using a five mega pixel digital camera and videos using an analog video camera were taken. A three point lighting system was used to avoid any background shadows and enhance picture quality. All pictures were taken from a fixed distance of three feet. Dynamic images were converted from the avi to mpeg format and edited using a professional video editing software, in order to obtain four second video clips of each emotional expression. Hence a total of 52 static and 28 dynamic images were obtained. All dynamic images had emotions expressed in a single intensity but for the static images emotions were expressed at two different intensities. The images were then arranged in a random order using random number generator software and separate power point presentations were prepared for the static and dynamic images with the images appearing in the random order sequence.

Validation of the tool:

The tool was validated by 51 students from the departments of Psychiatry, Clinical Psychology and Psychiatric Social Work, NIMHANS. The images were viewed on a 15 inch computer monitor from a distance of one meter in a closed room without any external distractions. Images (not used in the final tool) of the various emotions were shown as examples to ensure that the subjects understood the meaning of the emotions expressed. The subjects first viewed the static and then the dynamic images and had to select one correct response from the seven alternatives (neutral, happy, sad, fear, anger, surprise, disgust) given to them for each image viewed. There was no time limit given for viewing and marking the responses. The tool was also validated by five qualified psychiatrists in the manner as described above.

Statistical Analyses

The statistical analyses were performed using the Statistical Package for Social Sciences [SPSS] version 11. The following statistical tests were done: Cronbach's alpha analysis & independent samples t-test (two-tailed).


   Results Top


Each image being unique in the age, sex, intensity and type of emotion; were assessed individually. The percentage of correct responses for each image (static and dynamic) is given in the table below [Table 1] & [Table 2]. The overall Cronbach's a score which is a measure of internal consistency was 0.669 for static images and 0.447 for dynamic images.

High intensity images had significantly greater mean scores than low intensity images (df = 2, 46; t = 2.897; p = 0.007). Only 7 low intensity static images (sad-olderfemale, fear-youngmale, fear­-youngfemale, anger-oldermale, surprise­olderfemale, disgust-olderfemale, and disgust­youngfemale) were identified correctly by less than 60% of the raters. All the neutral and happy images scored above 80% [Figure 1] & [Figure 2]. All dynamic images had an agreement of greater than 80% excepting one (surprise-oldermale). Mean scores of dynamic images were significantly greater than those of static images. (df = 2,78; t = 3.449; p = 0.001)

Similar findings were seen in the validation by the five Qualified Psychiatrists (QP). The QP also scored below 60% in the low intensity images mentioned above excepting fear-youngmale and disgust-olderfemale. In addition anger-youngmale also received a low score of 40%


   Discussion Top


The higher mean scores of happy and neutral emotions are in accordance with previous studies which have consistently found these two emotions to be correctly identified by patients and controls with accuracy of greater than 80%. [6],[34] As would have been expected higher intensity emotions were better recognized, however studies have shown that difference between schizophrenia patients and control groups was more significant with higher intensity than low intensity emotions. [9],[47] The 7 images with less than 60% agreement could probably be termed as ambiguous images. Previous studies have shown that schizophrenia patients with positive symptoms tend to over attribute emotions and also the spatial detection of positive faces are more efficient with increasing anhedonia. [8] In these studies there was positive correlation between delusional sub score of SAPS and emotion matching, indicating that delusional patients are hyper attentive to others expression. [48] Hence it would be interesting to see the response of schizophrenia patients to these ambiguous images in future studies. Dynamic images seem to be better recognized than static images as all dynamic stimuli except one scored above 80%. Although the cronbach's alpha score of dynamic (0.447) is lesser than that of the static images (0.669), this could possibly be explained by the lesser number of stimuli with dynamic images (28) as compared to static images (52).


   Implications Top


The presence of FERD in disorders like Parkinsonism, Huntington's disease, thalamic stroke and also psychiatric disorder like schizophrenia suggests the involvement of basal ganglia, limbic system and dopaminergic system in emotion perception. [49] Functional MRI studies have demonstrated under activation of amygdala & hippocampus [35] and prefrontal cortex [50] in response to fear in schizophrenia patients.

FERD also has important treatment implications as use of non pharmacological interventions like cognitive enhancement therapy has been shown to significantly enhance social cognition in a 2 year randomized trial. [51] A recent review by Pinkham et al, suggests a possible role of serotonergic and GABAergic agents in modulation of amygdala mediated emotional processing based on preliminary findings of pharmacological fMRI studies. [52] Impaired emotion recognition also has considerable impact on a person's abilities to communicate and comprehend non verbal cues. Hence it may adversely affect the social and functional outcome of schizophrenia [53] and other neuropsychiatric disorders. One year follow up study of FERD, cognitive and social functioning in schizophrenia patients versus controls showed that FERD partially mediated between cognitive and social functioning. [54]

Hence studies on FERD are warranted in future as it could (1) provide a window to understanding the neurobiological substrates of various neuropsychiatric disorders. (2) Have important treatment implications. (3) Improve socio-­occupational functioning in neuropsychiatric disorders. This tool is currently being used by the authors in behavioral and fMRI studies on patients of schizophrenia and their first degree relatives.


   Conclusion Top


TRENDS, is a unique tool which has been validated in the Indian population and found to have good internal consistency. Its uniqueness lies in the fact that (1) It has both a static and dynamic component and comprehensively captures the full range and nature of emotional expressions, akin to real life situations. (2) It takes into account variations of age and sex on emotional expressions. (3) It is a culture sensitive tool. Given the influences of culture on emotional expression, perception and course and outcome of severe mental disorders; this tool and can be used for future behavioral and fMRI studies in Indian neuropyschiatric patients.


   Acknowledgement Top


The authors would like to acknowledge the financial support provided by the ICMR, under the MD/MS/DM/MCH thesis financial assistance programme of ICMR, Manpower development.

 
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    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2]


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    Abstract
    Introduction
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