Skip to main content

Emotional processing in patients with single brain damage in the right hemisphere

Abstract

Background

The interest in the relationship between brain damage and social cognition has increased in recent years. The objectives of the present study were the following: (1) to evaluate and compare emotional facial recognition and subjective emotional experience in patients who have suffered a single ischemic stroke in the right hemisphere (RH) and in healthy people, (2) to analyze the relationship between both variables in both groups of subjects, and (3) to analyze the association between the cerebral location of the stroke and these two variables.

Methods

Emotional facial recognition and the subjective emotional experience of 41 patients who had suffered a single ischemic stroke in the RH and 45 volunteers without previous cerebrovascular pathology were evaluated.

Results

Brain damaged patients performed lower in facial emotional recognition and had a less intense subjective emotional response to social content stimuli compared to healthy subjects. Likewise, among patients with RH ischemic stroke, we observed negative associations between facial recognition of surprise and reactivity to unpleasant images, and positive associations between recognition of disgust and reactivity to pleasant images. Finally, patients with damage in the caudate nucleus of the RH presented a deficit in the recognition of happiness and sadness, and those with damage in the frontal lobe exhibited a deficit in the recognition of surprise, compared to those injured in other brain areas.

Conclusions

Emotional facial recognition and subjective emotional experience are affected in patients who have suffered a single ischemic stroke in the RH. Professionals caring for stroke patients should improve their understanding of the general condition of affected persons and their environment, assess for risk of depression, and facilitate their adaptation to work, family, and social environments.

Peer Review reports

Background

Ischemic stroke (IS) has been classically defined as a neurological deficit resulting from an acute episode characterized by an interruption of blood flow in the central nervous system [1]. The patient with right hemisphere (RH) IS may present with an impulsive and disinhibited behavioral style, personality and/or mood changes, irritability, alterations in sexual behavior, emotional lability, flat affect, alexithymia and low emotional facial expressivity, and anosognosia or decreased insight and difficulty in recognizing one's own limitations and impact on daily life [2,3,4,5]. Also, the RH has been shown to play a special role in the development of symptoms of mania and other bipolar syndromes in the presence of lesions located in the temporal lobe, caudate nucleus, thalamus, ventral pontine area, anterior region, and subcortical region [3, 6, 7]. It also seems to be related to the appearance of psychotic symptoms in lesions of the fronto-parietal cortex, temporo-parieto-occipital cortex and thalamus [8, 9] and with the presence of generalized anxiety disorder, apathy, alexithymia, dysphoria and sleep problems [2, 5, 10]. Depressive symptomatology, one of the most frequent outcomes after a stroke, has traditionally been related to the location of the lesion in the left hemisphere [7, 11, 12] and evidence has also been found of its relationship with the RH [2, 13]. This occurs particularly in those cases in which the predominant symptomatology is not purely emotional but cognitive and vegetative [14, 15] and in the chronic phase of stroke [16, 17].

Social cognition is also altered in stroke. Social cognition refers to the neurocognitive processes responsible for the perception, interpretation, processing, and flexible use of social information, in order to guide interpersonal behavior [18, 19]. Social cognition is responsible for the processing of social stimuli that are typically characterized by their changing nature and personal relevance, ranging from the perception of other individuals to the processing of complex social situations. The main domains of social cognition are emotion processing (EP), mentalizing, attributional bias/style, and social perception. EP is a person's ability to correctly identify the emotions of others and to manage one's own emotions. Traditionally, the RH has been considered to play a fundamental role in EP, being involved in tasks related to emotional perception, expression, and experience [20,21,22] especially in the presence of social interaction stimuli [23, 24]. The RH dominance hypothesis posits that this hemisphere is dominant for the perception and expression of all types of emotions, regardless of their affective valence [20, 25,26,27,28,29,30,31,32]. Some of the explanations proposed to justify this hypothesis suggest that emotion management requires functions that have been attributed to the RH, such as nonverbal, integrative, holistic, perceptual and visuospatial processing of perceived stimuli, while the left hemisphere is responsible for verbal and cognitive processing of stimuli, more distant from emotions [33].

In recent years there has been great interest in how acquired brain damage affects social cognition. The importance of emotions, empathy and social cognition in post-stroke recovery has been previously described [33,34,35,36,37]. However, few studies have investigated the impact of an IS on a relevant variable of social cognition (EP) and to examine the relationship between the lesion of certain brain structures and EP. Accordingly, the aims of this cross-sectional study are as follows: (1) to assess and compare emotional facial recognition and subjective emotional experience in patients who have suffered a single ischemic stroke in RH and in persons without ischemic stroke, (2) to examine the relationship between these two EP variables in both groups of subjects, and (3) to analyze the association between cerebral location of the stroke and these two variables. We hypothesized that (1) patients with a lesion after a single ischemic stroke in RH will show a lower number of hits on the facial emotion recognition task and a subjective response of lower emotional intensity than healthy subjects, (2) scores on emotional face recognition and subjective emotional response will correlate positively with each other in the two groups of participants, and (3) patients with brain damage in limbic and/or prefrontal structures will show a greater deficit in emotional face recognition and a subjective emotional response of lower intensity compared to patients with lesions in other brain areas.

Material and methods

Participants

We recruited 41 patients who had suffered a single ischemic stroke in the RH. The inclusion criteria for these patients were: age ≥ 18 years, ischemic lesion(s) after a single stroke, language preservation, and no history of previous cognitive impairment (as reported by the patient and/or family members). In addition, 45 volunteers with no previous cerebrovascular pathology participated in this cross-sectional study. Twenty-two of these 45 individuals lived with their own family, 14 lived in a nursing home, 6 lived alone, and 3 lived with their family of origin. In both groups, exclusion criteria included a history of head trauma, presence of moderate or severe depression, central nervous system disease, visual defect or any medical condition that could affect their cognitive performance. In the group of patients, any subject with a previous cerebrovascular pathology, diagnosed clinically or according to radiological signs, was excluded. In addition, we excluded those who had suffered lacunar strokes and those who presented signs of previous territorial cerebral infarctions. In the group of healthy subjects, we excluded persons with a history of cerebrovascular disease.

Measures

Oxfordshire Community Stroke Project (OCSP; [38]). The OCSP is a system based on clinical criteria that distinguishes between the following categories of cerebral infarction: Total Anterior Cerebral Infarction (TACI) of frequently embolic etiology, Partial Anterior Cerebral Infarction (PACI) in which the most common etiologies are cardioembolic and atherosclerosis, and Posterior Circulation Infarction (POCI) whose most common etiology is atherosclerosis.

Mini-Mental State Examination (MMSE; [39]); Spanish version of Lobo et al. [40]. The MMSE measures the general cognitive status of the individual through 30 items that assess the following cognitive functions: spatial–temporal orientation, attention, concentration and memory, abstraction (calculation), language and visuospatial perception, and following basic instructions. The MMSE has shown adequate values of reliability, validity, sensitivity, and specificity in the Spanish population [40].

Hamilton Depression Rating Scale (HAM-D; Hamilton [41, 42]); Spanish version of Ramos-Brieva and Cordero-Villafáfila [43, 44]. The HAM-D measures the severity of depressive symptoms through 17 questions in which the clinician evaluates the following symptoms: depressed mood, feelings of guilt, suicidal ideation, insomnia (early, intermediate, and late types), activity level, psychomotor inhibition or agitation, psychic and somatic anxiety levels, gastrointestinal, genital or general somatic symptoms, hypochondriasis, weight loss, and level of insight. The HAM-D has shown adequate reliability, validity, and sensitivity to change in the Spanish population [43,44,45].

Ekman 60 Faces Test (EK-60F; Ekman and Friesen [46]). Spanish version of Molinero et al. [47]. The EK-60F measures the ability to recognize emotions through 60 black and white photographs of 8 × 10 cm each. These photographs show the faces of 10 actors (6 women and 4 men) expressing 6 basic emotions: happiness, sadness, disgust, fear, surprise, and anger. After randomly presenting the photographs, the participant must choose which emotion is expressed in each of them; the response options are the 6 emotions mentioned. The total score for this test is 60 points, based on the number of correct answers. The EK-60F has demonstrated adequate reliability and validity values in clinical and community samples in different countries; in Spain, normative data have been published in adolescent population [47].

International Affective Picture System (IAPS; Lang et al. [48, 49]); Spanish version of Moltó et al. [50, 51]. The IAPS has 1196 color photographs with content ranging from everyday scenes and objects to rare and potentially disturbing images. In the present study, we selected 54 photographs from the IAPS (following the procedure of Bradley and Lang [52]; Hempel et al. [53]; Sánchez-Navarro et al. [54]) which were divided, according to Spanish normative data, into 3 categories: 18 pleasant, 18 neutral and 18 unpleasant photographs. To evaluate the subjective emotional experience, the participant must rate each picture on a scale ranging from 1 (very unpleasant) to 9 (very pleasant). In addition, we divided these same photographs into two other categories: social (two or more people in a social interaction situation) and non-social. The IAPS has been used and validated in different countries; in Spain, normative scores have been obtained [50, 51, 55].

Modified Rankin Scale (mRS; [56]). In the mRS, clinicians globally assess the degree of physical disability in patients after stroke through seven levels of severity, from the "mild" category (0 points) to the "death" category (6 points). In this study, we grouped the levels of disability into 3 categories: mild (0–2 points), moderate (3 points), and severe (4–5 points).

National Institute of Health Stroke Scale (NIHSS; [57]); Spanish version of Montaner and Alvarez-Sabín [58]. NIHSS is a systematic assessment tool that provides a quantitative measure of stroke-related neurologic deficit through 11 items that explore: cortical functions, motor function, upper cranial nerves, language, sensitivity, and coordination. In the present study, we grouped severity levels into 4 categories: mild (0–3 points), moderate (4–15 points), severe (16–20 points), and very severe (> 20 points) deficits. The NIHSS has shown good psychometric properties in Spanish population [58].

Procedure

Patients were recruited from the Cerebrovascular Pathology Unit of the Hospital Clínico San Carlos in Madrid, Spain using non-probability accidental sampling (convenience sample). Eligible patients signed an informed consent form and the study was approved by the Ethical Committee for Clinical Research of the aforementioned hospital. Healthy subjects were matched for age, sex, and education level with the patient sample. In both groups, we conducted an interview assessing sociodemographic variables and the following clinical variables: alcohol and tobacco consumption, beta-blocker and beta-agonist medication intake, and presence of past and current mental disorder. In addition, we assessed the cognitive status with the MMSE (only as a screening test), and the presence of depression with the HAM-D.

In the group of patients, the location of the brain lesion was determined from their clinical history and at least one computed tomography (CT) and/or magnetic resonance imaging (MRI) according to the following classification: frontal, parietal, temporal, occipital, lenticular, caudate, thalamus, insular cortex or limbic system. Following the acute ischemic stroke care protocols implemented in our hospital, we performed a baseline brain CT scan and CT-angiography to assess the supra-aortic trunks and the circle of Willis from the aortic arch to the cranial vertex. The contrast medium used was Optiray Ultraject® 300 mg/mL. MRI was acquired using a 1.5 T scanner (Signa HDxt, GE Healthcare, Milwaukee, USA). The location of the lesion of 14 patients was determined by CT and MRI; the lesion of 26 patients was determined only by CT, and the lesion of 1 patient was determined only by MRI. We used these same imaging tests to determine the territory of the cerebral artery affected in the stroke (anterior, middle, or posterior cerebral artery). The type of cerebral infarction was classified by OCSP criteria. We measured the degree of physical disability after stroke with the mRS and the severity of the cognitive deficit with the NIHSS.

Emotional facial recognition and subjective emotional experience were then assessed. The mean number of days between the time of the stroke of 35 patients and the time of this evaluation was 318.9 days (SD = 147.4). For assessment of emotional facial recognition and subjective emotional experience, all participants sat approximately 50 cm from a computer monitor (1080 × 720 ppi resolution) projecting the EK-60F and IAPS photographs, at an angle of about 9° × 7° from the participants view. The photographs were presented with similar characteristics in terms of luminance and contrast. The EK-60F photographs were presented randomly. In the case of the IAPS, we created three PowerPoint presentations, each containing the same photographs (54 in total) but arranged differently to eliminate the potential effect of presentation order. Each of these three series of photographs began with a different image. The series were randomly assigned to subjects. Each subject was presented with only one of these series of photographs. We asked subjects to rate the photographs according to their affective valence (pleasant, neutral, or unpleasant).

Statistical analysis

We performed data analysis with the IBM SPSS Statistics version 24 program. In the IAPS, we calculated the arithmetic mean of the values assigned to the photographs, rated by each subject in both groups as unpleasant, pleasant and neutral, and the mean of all ratings in this dimension (global subjective emotional reactivity). Next, each participant's ratings (affective valence) of the same IAPS photos were taken into account, ordered this time according to their social (e.g., social scenes depicting people) and non-social (e.g., objects depicted) content. For each participant in the two groups, we calculated the arithmetic mean of the values assigned to the social and non-social photographs. Comparison between the group of stroke patients and the group of healthy subjects on sociodemographic and clinical variables was performed with χ2 or Student's t-tests. To compare emotional facial recognition and subjective emotional experience between the two groups and within each group, a two-factor analysis of variance (ANOVA) was performed. Post hoc analyses were performed using Bonferroni and Tukey corrections. Given the brain-level differences related to sex, as well as the influence of this variable on neural plastic capacity and aging [59,60,61,62,63], it was decided to include this variable as a factor in the ANOVAs. To examine the relationship between emotional facial recognition and subjective emotional experience in the two groups of subjects separately, we used Pearson correlation coefficients. Finally, to examine the brain localization of emotional facial recognition and subjective emotional experience in the patient group, we used the nonparametric Mann–Whitney U test comparing the presence versus absence of lesion for each brain region. The significance level in all hypothesis contrast tests was 0.05.

Results

Table 1 shows the sociodemographic characteristics of the participants in both samples. Table 2 includes results about location of the lesions in the group of patients. As shown, multiple regions which overlap with each other were affected although they were caused by only one stroke episode. At the end of this Results section, we examine the association between patients' lesion location and the emotional facial recognition and the subjective emotional experience. In the group of healthy subjects there were more people living in a residence, and in the group of patients there were more people living with their own family. As for the clinical variables, there were only significant differences between the two groups in tobacco use since healthy subjects smoked significantly more than the patients (χ2 = 5.87; p = 0.02).

Table 1 Sociodemographic characteristics of the participants
Table 2 Brain location of the lesion caused by a single ischemic stroke in the right hemisphere

Emotional facial recognition and subjective emotional experience in patients and healthy subjects

Table 3 shows the mean scores of patients and healthy subjects on the EK-60F and on the IAPS. In terms of facial recognition, healthy subjects exhibited a higher number of hits on the total EK-60F (F = 6.90; p = 0.01) and, specifically, on pictures expressing happiness (F = 6.42; p = 0.01), sadness (F = 5.91; p = 0.01), and anger (F = 4.31; p = 0.04) than patients who had suffered a stroke. An intra-group comparison revealed that patients (F = 31.34; p = 0.00) and healthy subjects (F = 37.37; p = 0.00) had a higher number of hits in the recognition of the facial expression of happiness than in the recognition of all other emotions.

Table 3 Mean scores of patients and healthy subjects on the EK-60F and the IAPS

Regarding the subjective emotional experience, although we found no significant differences between patients and healthy subjects regarding the total mean of evaluations of all IAPS images, men in both groups rated the set of images and, in addition, the pleasant images more positively than women (F = 9.93; p = 0.00 and F = 9.79; p = 0.00 respectively). Likewise, healthy persons rated social images more positively than patients (F = 5.55; p = 0.02) while males in both groups rated them more positively than females (F = 16.03; p = 0.00). An intra-group comparison revealed that patients (F = 196.01; p = 0.00) and healthy subjects (F = 369.94; p = 0.00) rated pleasant images more positively than neutral and unpleasant ones and, furthermore, healthy males (F = 9.21; p = 0.00) gave more positive ratings to social images than to nonsocial ones.

Within the group of patients, individuals with a severe level of disability (χ2 = 6.08; p = 0.04) and individuals with a very severe cognitive deficit after stroke (χ2 = 6.05; p = 0.04) rated unpleasant IAPS images closer to neutral than other patients, suggesting a subjective emotional reaction of lower intensity. Similar results were found for the severity of the neurological deficit in the case of non-social imagery (χ2 = 8.86; p = 0.01). In addition, negative correlations were found between the levels of disability and severity of the neurological deficit (at discharge) and the total facial recognition score (r = − 0.37; p = 0.01 and r = − 0.04; p = 0.00, respectively). Finally, individuals with a mild level of physical disability according to the mRS (χ2 = 6.70; p = 0.03) and with cognitive deficit of moderate severity at discharge according to the NIHSS (χ2 = 5.79; p = 0.01) obtained a higher number of hits in the recognition of happiness than the rest of the patients.

Relationship between emotional facial recognition and subjective emotional experience in patients and healthy subjects

In the patient group, we found no significant relationship between total scores on emotional facial recognition and subjective emotional experience. However, total scores on emotional recognition tended to be associated with pleasant picture appraisals (r = 0.30, p = 0.056) while we found significant relationships between surprise recognition scores and unpleasant picture appraisals (r =  − 0.37; p = 0.01), and between disgust recognition scores and pleasant picture appraisals (r = 0.36; p = 0.02). In the group of healthy subjects, we did not find a significant relationship between total scores on emotional facial recognition and subjective emotional experience. However, we found significant relationships between total scores on emotional recognition and evaluations of unpleasant and neutral images (r = 0.30; p = 0.04 and r =  − 0.39; p = 0.01 respectively). Similarly, among healthy subjects, we found significant relationships between disgust and anger recognition scores with unpleasant image appraisals (r = 0.39; p = 0.00 and r = 0.29; p = 0.05 respectively) and between fear and surprise recognition scores with neutral image appraisals (r =  − 0.35; p = 0.02 and r =  − 0.42; p = 0.00, respectively).

Brain localization of stroke and emotional facial recognition and subjective emotional experience

Regarding emotional facial recognition (see Fig. 1), patients with damage in the caudate nucleus presented a lower number of hits in facial recognition of happiness and sadness than those lesioned in other brain areas (U = 42.5; p = 0.01 and U = 34.5; p = 0.01 respectively). In addition, those with parietal lobe damage exhibited more hits in fear recognition than those without damage in this area (U = 110.5; p = 0.03). Finally, individuals with frontal lobe damage were less successful in recognizing surprise than those with lesions in other areas (U = 123.5; p = 0.03). As for the subjective emotional experience of the patients, we found no significant differences in the evaluation of the images when comparing the different locations of the brain lesion.

Fig. 1
figure 1

Median of hits in facial recognition of happiness, sadness, fear, and surprise according to the location of the lesion following stroke in the right hemisphere; * = p < 0.05

Discussion

In this study, we examined and compared two EP variables, emotional facial recognition and subjective emotional experience, in patients who had suffered a single ischemic stroke in the RH and in subjects without neurological lesions. Both groups were matched in terms of age, sex, presence of psychopathology, cognitive level, and educational level. In addition, we analyzed the relationship between these two EP variables in both groups of subjects and the association between the cerebral location of the stroke and these two variables.

Emotional facial recognition and subjective emotional experience in patients and healthy subjects

First, we found that healthy subjects performed better in the test of emotional facial recognition than the RH stroke patients, suggesting an alteration of this ability in people with this neurological deficit. These results are consistent with the RH dominance hypothesis, which posits a specialization of this hemisphere for the different abilities related to emotion processing, including the perception of positive and negative emotions, especially in the presence of facial and prosodic stimuli and, therefore, with a nonverbal component [28,29,30, 33, 64]. On the other hand, subjects in both groups recognized facial expression of happiness to a greater extent than all other emotions, a response pattern similar to that found in other studies [47, 65, 66].

Second, the absence of significant differences between patients and healthy subjects regarding their subjective emotional response to the presentation of imagery may have been due to the relatively good preservation of the stroke-affected group, as patients had preserved language and no history of prior cognitive impairment. However, the fact that males in both groups rated the set of images more pleasantly than females is consistent with some studies that have found a higher intensity of subjective response in females to stimuli with negative affective valence and a higher emotional intensity in males to stimuli with positive affective valence [67,68,69,70,71,72]. On the other hand, healthy subjects rated images of social content significantly more positively than patients. This finding is consistent with prior studies showing a relationship between RH and the processing of social information at the attentional and emotional levels [23, 24]. Likewise, the fact that males in both groups presented a more positive subjective emotional response to social content images than females may be explained by the presence of a greater number of photographs with positive valence and erotic content among the selected social content images.

Relationship between emotional facial recognition and subjective emotional experience in patients and healthy subjects

A detailed analysis of the relationship between the different dimensions of these variables showed results of interest. Specifically, we observed significant relationships (1) in the patient group, between scores on recognition of surprise and disgust, and ratings of unpleasant and pleasant images respectively, (2) in the group of healthy subjects, between total scores on emotional facial recognition and ratings of unpleasant and neutral images, and (3) in the group of healthy subjects, between recognition of disgust and anger and ratings of unpleasant images, and between recognition of fear and surprise and ratings of neutral images. Although these findings are consistent with studies suggesting a relationship between emotional facial recognition and emotional experience (e.g., Buchanan, et al. [73]; Calder et al. [74]) these results should be interpreted with caution, given that no significant relationship was found between total scores on emotional facial recognition and subjective emotional experience in the two groups of participants, and the relatively small sample size of both groups.

Brain localization of stroke and emotional facial recognition and subjective emotional experience

We found that patients' brain lesions located in different areas were related to facial recognition of different emotions. These results are consistent with other studies that relate emotional perception and identification to subcortical areas (such as the caudate nucleus and surrounding areas) and to temporal and frontal cortical areas [75,76,77,78,79,80,81,82,83,84,85,86,87]. On the one hand, this emphasizes the role of both cortical and subcortical regions of the RH in facial emotion recognition. On the other hand, our findings provide preliminary evidence about the differential role of brain regions in specific emotions in stroke patients, as has been suggested in healthy subjects using functional MRI experiments [88]. Future studies that incorporate a more detailed characterization of stroke brain injury in the RH in a larger sample of patients with more extensive lesions are needed to clarify the relationship between stroke location and subjective emotional experience. As well, other behavioral measures related to emotional processing, such as time reaction to stimuli, should be included in future research.

A deficit in facial emotion recognition in individuals with a single RH stroke has important clinical implications. This deficit implies difficulties in social interactions, isolation, problems in conflict resolution, frustration in interpersonal relationships, feelings of discomfort, and social disconnection [33, 89, 90]. Moreover, the fact that patients showed a lower subjective emotional response to social stimuli than healthy subjects suggests an attenuated emotional response to social situations that may impact on quality of life. Since depression is the most common neuropsychiatric sequelae after stroke [6, 7], it is possible that these social cognitive impairments may heighten the risk of experiencing depression especially after a severe ischemic stroke event. Considering the findings of this cross-sectional study, professionals caring for stroke patients should improve their understanding of the general condition of the persons and their environment, assess for risk of depression, and facilitate their adaptation to work, family and social environments.

The present investigation has the following limitations. First, a significant percentage of healthy individuals lived in a nursing home, which could imply a lower degree of functionality with respect to the group of stroke patients. Second, the sample size was small when intra-group comparisons were performed. Third, in the group of patients, we assessed their cognitive status with the MMSE (only as a screening test), a tool that is less sensitive than the Montreal Cognitive Assessment (MoCA) in screening for cognitive impairment after acute stroke [91]. Fourth, the lesion of 26 patients was determined only by CT, a less informative tool than MRI. Fifth, the number of photographs in the social category was lower than the number of non-social photographs and they had different proportions of images with positive and negative emotional valence. Sixth, neuroimaging assessment was based on visual reads and qualitative evaluation of several prespecified brain regions. Finally, it is possible that between the imaging test performed on individuals with stroke and the assessment phase of this cross-sectional study, clinically silent ischemic strokes may have occurred, producing subtle neuropsychological alterations.

Conclusions

Patients with brain damage secondary to RH ischemic stroke display lower performance in emotional facial recognition compared to healthy subjects without brain damage. In addition, these patients present a subjective emotional response of lower intensity to stimuli with social content compared to healthy subjects. Likewise, males present a more positive subjective emotional response than females, regardless of the existence of brain damage in the RH. We observed that patients with brain damage due to RH ischemic stroke negatively associate facial recognition of surprise with unpleasant images and positively associate facial recognition of disgust with pleasant images. Finally, patients with damage to the caudate nucleus of the RH present a deficit in the recognition of happiness and sadness and those with damage to the frontal lobe of the same hemisphere present a deficit in the recognition of surprise. Future research comparing EP in RH and left hemisphere stroke, and/or combining multiple neuroimaging techniques (e.g., structural, diffusion-tensor imaging, functional MRI) in patients who have suffered a single ischemic stroke in the RH is necessary to further understand the neural underpinnings of EP in stroke patients.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

IS:

Ischemic stroke

RH:

Right hemisphere

EP:

Emotion processing

OCSP:

Oxfordshire Community Stroke Project

TACI:

Total Anterior Cerebral Infarction

PACI:

Partial Anterior Cerebral Infarction

POCI:

Posterior Circulation Infarction

MMSE:

Mini-Mental State Examination

HAM-D:

Hamilton Depression Rating Scale

EK-60F:

Ekman 60 Faces test

IAPS:

International Affective Picture System

mRS:

Modified Rankin Scale

NIHSS:

National Institute of Health Stroke Scale

CT:

Computed tomography

MRI:

Magnetic resonance imaging

ANOVA:

Analysis of variance

MoCA:

Montreal Cognitive Assessment

References

  1. Sacco RL, Kasner SE, Broderick JP, Caplan LR, Culebras A, Elkind MS, et al. An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2013;44(7):2064–89.

    Article  Google Scholar 

  2. Castellanos-Pinedo F, Hernández-Pérez JM, Zurdo M, Rodríguez-Fúnez B, Hernández-Bayo JM, García-Fernández C, et al. Influence of premorbid psychopathology and lesion location on affective and behavioral disorders after ischemic stroke. J Neuropsychiatry Clin Neurosci. 2011;23(3):340–7.

    Article  Google Scholar 

  3. Cummings JL. Neuropsychiatric manifestations of right hemisphere lesions. Brain Lang. 1997;57(1):22–37.

    Article  Google Scholar 

  4. Erhan H, Ochoa E, Borod J, Feinberg T. Consequences of right cerebrovascular accident on emotional functioning: diagnostic and treatment implications. CNS Spectr. 2000;5(3):25–38.

    Article  Google Scholar 

  5. Spalletta G, Ripa A, Bria P, Caltagirone C, Robinson RG. Response of emotional unawareness after stroke to antidepressant treatment. Am J Geriatr Psychiatry. 2006;14(3):220–7.

    Article  Google Scholar 

  6. Luna-Matos M, Mcgrath H, Gaviria M. Manifestaciones neuropsiquiátricas en accidentes cerebrovasculares. Rev Chil Neuropsiquiatr. 2007;45(2):129–40.

    Google Scholar 

  7. Robinson RG. Neuropsychiatric consequences of stroke. Annu Rev Med. 1997;48(1):217–29.

    Article  Google Scholar 

  8. Devine MJ, Bentley P, Jones B, Hotton G, Greenwood RJ, Jenkins IH, et al. The role of the right inferior frontal gyrus in the pathogenesis of post-stroke psychosis. J Neurol. 2014;261(3):600–3.

    Article  Google Scholar 

  9. Rabins PV, Starkstein SE, Robinson RG. Risk factors for developing atypical (schizophreniform) psychosis following stroke. J Neuropsychiatry Clin Neurosci. 1991;3(1):6–9.

    Article  Google Scholar 

  10. Paradiso S, Anderson BM, Boles Ponto LL, Tranel D, Robinson RG. Altered neural activity and emotions following right middle cerebral artery stroke. J Stroke Cerebrovasc Dis. 2011;20(2):94–104.

    Article  Google Scholar 

  11. Alajbegovic A, Djelilovic-Vranic J, Alajbegovic S, Nakicevic A, Todorovic L, Tiric-Campara M. Post stroke depression. Med Arch. 2014;68(1):47–50.

    Article  Google Scholar 

  12. Jiang XG, Lin Y, Li YS. Correlative study on risk factors of depression among acute stroke patients. Eur Rev Med Pharmacol Sci. 2014;18(9):81–90.

    Google Scholar 

  13. Wei N, Yong W, Li X, Zhou Y, Deng M, Zhu H, et al. Post-stroke depression and lesion location: a systematic review. J Neurol. 2015;262(1):81–90.

    Article  Google Scholar 

  14. Gallo JJ, Rabins PV, Lyketsos CG, Tien AY, Anthony JC. Depression without sadness: functional outcomes of nondysphoric depression in later life. J Am Geriatr Soc. 1997;45(5):570–8.

    Article  Google Scholar 

  15. Paradiso S, Vaidya J, Tranel D, Kosier T, Robinson RG. Nondysphoric depression following stroke. J Neuropsychiatry Clin Neurosci. 2008;20(1):52–61.

    Article  Google Scholar 

  16. Bhogal SK, Teasell R, Foley N, Speechley M. Lesion location and poststroke depression: systematic review of the methodological limitations in the literature. Stroke. 2004;35(3):794–802.

    Article  Google Scholar 

  17. Shimoda K, Robinson RG. The relationship between poststroke depression and lesion location in long-term follow-up. Biol Psychiatry. 1999;45(2):187–92.

    Article  Google Scholar 

  18. Adolphs R. The neurobiology of social cognition. Curr Opin Neurobiol. 2001;11(2):231–9.

    Article  Google Scholar 

  19. Penn DL, Corrigan PW, Bentall RP, Racenstein JM, Newman L. Social cognition in schizophrenia. Psychol Bull. 1997;121(1):114–32.

    Article  Google Scholar 

  20. Blonder LX, Burns AF, Bowers D, Moore RW, Heilman KM. Right hemisphere facial expressivity during natural conversation. Brain Cogn. 1993;21(1):44–56.

    Article  Google Scholar 

  21. Harciarek M, Heilman KM, Jodzio K. Defective comprehension of emotional faces and prosody as a result of right hemisphere stroke: modality versus emotion-type specificity. J Int Neuropsychol Soc. 2006;12(6):774–81.

    Article  Google Scholar 

  22. Spence S, Shapiro D, Zaidel E. The role of the right hemisphere in the physiological and cognitive components of emotional processing. Psychophysiology. 1996;33(2):112–22.

    Article  Google Scholar 

  23. Greene DJ, Zaidel E. Hemispheric differences in attentional orienting by social cues. Neuropsychologia. 2011;49(1):61–8.

    Article  Google Scholar 

  24. Semrud-Clikeman M, Goldenring Fine J, Zhu DC. The role of the right hemisphere for processing of social interactions in normal adults using functional magnetic resonance imaging. Neuropsychobiology. 2011;64(1):47–51.

    Article  Google Scholar 

  25. Borod JC, Bloom RL, Brickman AM, Nakhutina L, Curko EA. Emotional processing deficits in individuals with unilateral brain damage. Appl Neuropsychol. 2002;9(1):23–36.

    Article  Google Scholar 

  26. Cicero BA, Borod JC, Santschi C, Erhan HM, Obler LK, Agosti RM, et al. Emotional versus nonemotional lexical perception in patients with right and left brain damage. Cogn Behav Neurol. 1999;12(4):255–64.

    Google Scholar 

  27. Crucian GP, Hughes JD, Barrett AM, Williamson DJ, Bauer RM, Bowers D, et al. Emotional and physiological responses to false feedback. Cortex. 2000;36(5):623–47.

    Article  Google Scholar 

  28. Dara C, Bang J, Gottesman RF, Hillis AE. Right hemisphere dysfunction is better predicted by emotional prosody impairments as compared to neglect. J Neurol Transl Neurosci. 2014;2(1):1037.

    Google Scholar 

  29. Godfrey HK, Grimshaw GM. Emotional language is all right: emotional prosody reduces hemispheric asymmetry for linguistic processing. Laterality. 2016;21(4–6):568–84.

    Article  Google Scholar 

  30. Harciarek M, Heilman KM. The contribution of anterior and posterior regions of the right hemisphere to the recognition of emotional faces. J Clin Exp Neuropsychol. 2009;31(3):322–30.

    Article  Google Scholar 

  31. Innes BR, Burt DM, Birch YK, Hausmann M. A leftward bias however you look at it: revisiting the emotional chimeric face task as a tool for measuring emotion lateralization. Laterality. 2016;21(4–6):643–61.

    Article  Google Scholar 

  32. Starkstein SE, Federoff JP, Price TR, Leiguarda RC, Robinson RG. Neuropsychological and neuroradiologic correlates of emotional prosody comprehension. Neurology. 1994;44(3 Pt 1):515–22.

    Article  Google Scholar 

  33. Yuvaraj R, Murugappan M, Norlinah MI, Sundaraj K, Khairiyah M. Review of emotion recognition in stroke patients. Dement Geriatr Cogn Disord. 2013;36(3–4):179–96.

    Article  Google Scholar 

  34. Baldo JV, Kacinik NA, Moncrief A, Beghin F, Dronkers NF. You may now kiss the bride: interpretation of social situations by individuals with right or left hemisphere injury. Neuropsychologia. 2016;80:133–41.

    Article  Google Scholar 

  35. Eslinger PJ, Parkinson K, Shamay SG. Empathy and social-emotional factors in recovery from stroke. Curr Opin Neurol. 2002;15(1):91–7.

    Article  Google Scholar 

  36. Fossati P. Neural correlates of emotion processing: from emotional to social brain. Eur Neuropsychopharmacol. 2012;22(Suppl 3):S487–91.

    Article  Google Scholar 

  37. Leigh R, Oishi K, Hsu J, Lindquist M, Gottesman RF, Jarso S, et al. Acute lesions that impair affective empathy. Brain. 2013;136(8):2539–49.

    Article  Google Scholar 

  38. Bamford J, Sandercock P, Dennis M, Warlow C, Burn J. Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet. 1991;337(8756):1521–6.

    Article  Google Scholar 

  39. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.

    Article  Google Scholar 

  40. Lobo A, Saz P, Marcos G, Día JL, de la Cámara C, Ventura T, et al. Revalidación y normalización del Mini-Examen Cognoscitivo (primera versión en castellano del Mini-Mental Status Examination) en la población general geriátrica. Med Clin (Barc). 1999;112(20):767–74.

    Google Scholar 

  41. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56–62.

    Article  Google Scholar 

  42. Hamilton M. The Hamilton Rating Scale for Depression. In: Sartorius N, Ban TA, editors. Assessment of depression. Berlin: Springer; 1986. p. 143–52.

    Chapter  Google Scholar 

  43. Ramos-Brieva JA, Cordero-Villafáfila A. Validación de la versión castellana de la Escala de Hamilton para la Depresión. Actas Luso Esp Neurol Psiquiatr Cienc Afines. 1986;14:324–34.

    Google Scholar 

  44. Ramos-Brieva JA, Cordero-Villafáfila A. A new validation of the Hamilton Rating Scale for Depression. J Psychiatr Res. 1988;22(1):21–8.

    Article  Google Scholar 

  45. Bobes J, Bulbena A, Luque A, Dal-Ré R, Ballesteros J, Ibarra N, et al. Evaluación psicométrica comparativa de las versiones en español de 6, 17 y 21 ítems de la Escala de Valoración de Hamilton para la Evaluación de la Depresión. Med Clin (Barc). 2003;120(18):693–700.

    Article  Google Scholar 

  46. Ekman P, Friesen WV. Pictures of facial affect. Palo Alto: Consulting Psychologists; 1976.

    Google Scholar 

  47. Molinero C, Bonete S, Gómez-Pérez MM, Calero MD. Estudio normativo del “test de 60 caras de Ekman” para adolescentes españoles. Psicol Conductual. 2015;23(2):361–71.

    Google Scholar 

  48. Lang PJ, Bradley MM, Cuthbert BN. International Affective Picture System (IAPS): affective ratings of pictures and instruction manual (Tech. Rep. No. A-8). Gainesville: University of Florida; 2008.

  49. Lang PJ, Bradley MM, Cuthbert BN. International Affective Picture System (IAPS): instruction manual and affective ratings (Tech. Rep. No. A-4). Gainesville: University of Florida; 1999.

  50. Moltó J, Montañés S, Poy R, Segarra P, Pastor MC, Tormo MP, et al. Un nuevo método para el estudio experimental de las emociones: el International Affective Picture System (IAPS). Adaptación española. Rev Psicol Gen Apl. 1999;52(1):55–87.

    Google Scholar 

  51. Moltó J, Segarra P, López R, Esteller À, Fonfría A, Pastor MC, et al. Adaptación española del International Affective Picture System (IAPS). Tercera parte. An Psicol. 2013;29(3):965–84.

    Article  Google Scholar 

  52. Bradley MM, Lang PJ. Affective reactions to acoustic stimuli. Psychophysiology. 2000;37(2):204–15.

    Article  Google Scholar 

  53. Hempel RJ, Tulen JHM, van Beveren NJM, Mulder PGH, Hengeveld MW. Subjective and physiological responses to emotion-eliciting pictures in male schizophrenic patients. Int J Psychophysiol. 2007;64(2):174–83.

    Article  Google Scholar 

  54. Sánchez-Navarro JP, Martínez-Selva JM, Torrente G, Román F. Psychophysiological, behavioral, and cognitive indices of the emotional response: a factor-analytic study. Span J Psychol. 2008;11(1):16–25.

    Article  Google Scholar 

  55. Vila J, Sánchez M, Ramírez I, Fernández MC, Cobos P, Rodríguez S, et al. El Sistema Internacional de Imágenes Afectivas (IAPS): adaptación española. Segunda parte. Rev Psicol Gen Apl. 2001;54(4):635–57.

    Google Scholar 

  56. Van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, Van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke. 1988;19(5):604–7.

    Article  Google Scholar 

  57. Brott T, Adams HP, Olinger CP, Marler JR, Barsan WG, Biller J, et al. Measurements of acute cerebral infarction: a clinical examination scale. Stroke. 1989;20(7):864–70.

    Article  Google Scholar 

  58. Montaner J, Alvarez-Sabín J. La escala de ictus del National Institute of Health (NIHSS) y su adaptación al español. Neurología. 2006;21(4):192–202.

    Google Scholar 

  59. Cooke B, Hegstrom CD, Villeneuve LS, Breedlove SM. Sexual differentiation of the vertebrate brain: principles and mechanisms. Front Neuroendocrinol. 1998;19(4):323–62.

    Article  Google Scholar 

  60. Good CD, Johnsrude I, Ashburner J, Henson RNA, Friston KJ, Frackowiak RSJ. Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains. Neuroimage. 2001;14(3):685–700.

    Article  Google Scholar 

  61. Ingalhalikar M, Smith A, Parker D, Satterthwaite TD, Elliott MA, Ruparel K, et al. Sex differences in the structural connectome of the human brain. Proc Natl Acad Sci U S A. 2014;111(2):823–8.

    Article  Google Scholar 

  62. Murphy DGM, DeCarli C, Mclntosh AR, Daly E, Mentis MJ, Pietrini P, et al. Sex differences in human brain morphometry and metabolism: an in vivo quantitative magnetic resonance imaging and positron emission tomography study on the effect of aging. Arch Gen Psychiatry. 1996;53(7):585–94.

    Article  Google Scholar 

  63. Witelson DF. Sex and the single hemisphere: specialization of the right hemisphere for spatial processing. Science. 1976;193(4251):425–7.

    Article  Google Scholar 

  64. Guranski K, Podemski R. Emotional prosody expression in acoustic analysis in patients with right hemisphere ischemic stroke. Neurol Neurochir Pol. 2015;49(2):113–20.

    Article  Google Scholar 

  65. Dodich A, Cerami C, Canessa N, Crespi C, Marcone A, Arpone M, et al. Emotion recognition from facial expressions: a normative study of the Ekman 60-Faces Test in the Italian population. Neurol Sci. 2014;35(7):1015–21.

    Article  Google Scholar 

  66. Edwards J, Jackson HJ, Pattison PE. Emotion recognition via facial expression and affective prosody in schizophrenia: a methodological review. Clin Psychol Rev. 2002;22(6):789–832.

    Article  Google Scholar 

  67. Bradley MM, Codispoti M, Sabatinelli D, Lang PJ. Emotion and motivation II: sex differences in picture processing. Emotion. 2001;1(3):300–19.

    Article  Google Scholar 

  68. Deng Y, Chang L, Yang M, Huo M, Zhou R. Gender differences in emotional response: inconsistency between experience and expressivity. PLoS ONE. 2016;11(6):e0158666.

    Article  Google Scholar 

  69. Maffei A, Vencato V, Angrilli A. Sex differences in emotional evaluation of film clips: interaction with five high arousal emotional categories. PLoS ONE. 2015;10(12):e0145562.

    Article  Google Scholar 

  70. Seidlitz L, Diener E. Sex differences in the recall of affective experiences. J Pers Soc Psychol. 1998;74(1):262–71.

    Article  Google Scholar 

  71. Sharp C, Van Goozen S, Goodyer I. Children’s subjective emotional reactivity to affective pictures: gender differences and their antisocial correlates in an unselected sample of 7–11-year-olds. J Child Psychol Psychiatry. 2006;47(2):143–50.

    Article  Google Scholar 

  72. Stevens JS, Hamann S. Sex differences in brain activation to emotional stimuli: a meta-analysis of neuroimaging studies. Neuropsychologia. 2012;50(7):1578–93.

    Article  Google Scholar 

  73. Buchanan TW, Bibas D, Adolphs R. Associations between feeling and judging the emotions of happiness and fear: findings from a large-scale field experiment. PLoS ONE. 2010;5(5):e10640.

    Article  Google Scholar 

  74. Calder AJ, Keane J, Manes F, Antoun N, Young AW. Impaired recognition and experience of disgust following brain injury. Nat Neurosci. 2000;3(11):1077–8.

    Article  Google Scholar 

  75. Adolphs R, Baron-Cohen S, Tranel D. Impaired recognition of social emotions following amygdala damage. J Cogn Neurosci. 2002;14(8):1264–74.

    Article  Google Scholar 

  76. Aziz-Zadeh L, Sheng T, Gheytanchi A. Common premotor regions for the perception and production of prosody and correlations with empathy and prosodic ability. PLoS ONE. 2010;5(1):e8759.

    Article  Google Scholar 

  77. Sprengelmeyer R, Young AW, Calder AJ, Karnat A, Lange H, Homberg V, et al. Loss of disgust. Perception of faces and emotions in Huntington’s disease. Brain. 1996;119(5):1647–65.

    Article  Google Scholar 

  78. Zaitchik D, Walker C, Miller S, LaViolette P, Feczko E, Dickerson BC. Mental state attribution and the temporoparietal junction: an fMRI study comparing belief, emotion, and perception. Neuropsychologia. 2010;48(9):2528–36.

    Article  Google Scholar 

  79. Tippett DC, Godin BR, Oishi K, Oishi K, Davis C, Gomez Y, et al. Impaired recognition of emotional faces after stroke involving right amygdala or insula. Semin Speech Lang. 2018;39(1):87–100.

    Article  Google Scholar 

  80. Calder AJ, Lawrence AD, Young AW. Neuropsychology of fear and loathing. Nat Rev Neurosci. 2001;2(5):352–63.

    Article  Google Scholar 

  81. Lee TM, Sun D, Leung MK, Chu LW, Keysers C. Neural activities during affective processing in people with Alzheimer’s disease. Neurobiol Aging. 2013;34(3):706–15.

    Article  Google Scholar 

  82. Neumann D, Keiski MA, McDonald BC, Wang Y. Neuroimaging and facial affect processing: implications for traumatic brain injury. Brain Imaging Behav. 2014;8(3):460–73.

    Article  Google Scholar 

  83. Phan KL, Wager T, Taylor SF, Liberzon I. Functional neuroanatomy of emotion: a meta-analysis of emotion activation studies in PET and fMRI. Neuroimage. 2002;16(2):331–48.

    Article  Google Scholar 

  84. Puce A, Allison T, Bentin S, Gore JC, McCarthy G. Temporal cortex activation in humans viewing eye and mouth movements. J Neurosci. 1998;18(6):2188–99.

    Article  Google Scholar 

  85. Roberts DL, Penn DL. Social cognition in schizophrenia: from evidence to treatment. Oxford: Oxford University Press; 2013.

    Book  Google Scholar 

  86. Sabatinelli D, Fortune EE, Li Q, Siddiqui A, Krafft C, Oliver WT, et al. Emotional perception: meta-analyses of face and natural scene processing. Neuroimage. 2011;54(3):2524–33.

    Article  Google Scholar 

  87. Said CP, Haxby JV, Todorov A. Brain systems for assessing the affective value of faces. Philos Trans R Soc Lond B Biol Sci. 2011;366(1571):1660–70.

    Article  Google Scholar 

  88. Vytal K, Hamann S. Neuroimaging support for discrete neural correlates of basic emotions: a voxel-based meta-analysis. J Cogn Neurosci. 2010;22(12):2864–85.

    Article  Google Scholar 

  89. Addington J, Saeedi H, Addington D. Influence of social perception and social knowledge on cognitive and social functioning in early psychosis. Br J Psychiatry. 2006;189(4):373–8.

    Article  Google Scholar 

  90. Couture SM, Penn DL, Roberts DL. The functional significance of social cognition in schizophrenia: a review. Schizophr Bull. 2006;32(S1):S44-63.

    Article  Google Scholar 

  91. Dong Y, Sharma VK, Chan BPL, Venketasubramanian N, Teoh HL, Seet RCS, et al. The Montreal Cognitive Assessment (MoCA) is superior to the Mini-Mental State Examination (MMSE) for the detection of vascular cognitive impairment after acute stroke. J Neurol Sci. 2010;299(1–2):15–8.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

Dr. Jordi A. Matias-Guiu is supported by Instituto de Salud Carlos III through the project INT20/00079 (co-funded by European Regional Development Fund “A way to make Europe”). Dr. Roberto Rodriguez-Jimenez is supported by Instituto de Salud Carlos III through the project PI19/00766 (Fondo de Investigaciones Sanitarias/FEDER).

Author information

Authors and Affiliations

Authors

Contributions

SA-F, PS, and GL contributed to the conception and design of the study. J-AM-G and CG-E recruited and evaluated the patients. SA-F, PS, and GL also participated in patient assessment, performed data analysis, and participated in the discussion. NA-G and SA-F wrote the first draft. RR-J and B-JS reviewed the entire manuscript. All authors read and approved the submitted version.

Corresponding author

Correspondence to Nelson Andrade-González.

Ethics declarations

Ethics approval and consent to participate

The study was performed in compliance with the Helsinki Declaration for research on humans and was approved by the Ethical Committee for Clinical Research of the University Hospital San Carlos of Madrid (Spain). All patients signed an informed consent form.

Consent for publication

Not applicable.

Competing interests

Dr. Álvarez-Fernández, Dr. Andrade-González, Dr. Simal, Dr. Matias-Guiu, Dr. Gómez-Escalonilla, and Mr. Stiles declares no competing interests. Dr. Rodriguez-Jimenez has been a consultant for, spoken in activities of, or received grants from Instituto de Salud Carlos III, Fondo de Investigación Sanitaria (FIS), CIBERSAM, Madrid Regional Government, Janssen-Cilag, Otsuka-Lundbeck, Pfizer, Ferrer, Juste, Takeda, Exeltis, Casen-Recordati, and Angelini Pharma. Dr. Lahera has been a consultant to or has received honoraria or grants from Janssen-Cilag, Otsuka-Lundbeck, Angelini Pharma, Lilly, Astra-Zeneca, CIBERSAM, and Instituto de Salud Carlos III.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Álvarez-Fernández, S., Andrade-González, N., Simal, P. et al. Emotional processing in patients with single brain damage in the right hemisphere. BMC Psychol 11, 8 (2023). https://doi.org/10.1186/s40359-022-01033-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40359-022-01033-x

Keywords