Mirror Neurons: Imitation and Emotional Differences Among Males and Females

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MIRROR NEURONS:

IMITATION AND EMOTIONAL DIFFERENCES AMONG MALES AND FEMALES

AmberRose Reale

A Thesis Submitted to the Faculty of

The Charles E. Schmidt College of Science

In Partial Fulfillment of the Requirements for the Degree of

Master of Arts

Florida Atlantic University

Boca Raton, Florida

May 2014

ACKNOWLEDGEMENTS

I would like to thank my thesis advisor and committee for all of their help and support throughout this process. I would also like to thank the undergraduates who helped me with testing and my fellow graduate students for their endless hours of assistance and understanding. You’ve all made this process much easier and more enjoyable.

To my soon-to-be husband, Hunter, “thank you” can’t express how grateful I am to you for your unwavering understanding and support through all the late nights and crazy questions. I could not have done it without you.

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ABSTRACT

Author: AmberRose Reale

Title: Mirror Neurons: Imitation and Emotional Differences Among Males and Females

Institution: Florida Atlantic University

Thesis Advisor: Dr. Monica Rosselli

Degree: Master of Arts

Year: 2014

The mirror neuron system consists of a specific class of visuomotor neurons, which fire for both observation and execution of an action (di Pellegrino et al., 1992), as well as showing differences for empathy and gender. Fifty males (M = 25.94) and fifty females (M = 25.48) watched short clips of a hand tapping fingers in a sequence in neutral and emotional settings. Participants were asked to imitate emotions while watching and repeating the finger sequences. A univariate ANOVA discovered significant differences in response times for males and females in the emotion trials, which were eliminated when empathy was included in the analysis. Findings show those higher in empathy are faster at imitation of a motor task in emotional settings.

DEDICATION

To my mother for her everlasting support and unshakable belief in my ability, and to my

father for instilling in me the importance of education.

MIRROR NEURONS:

IMITATION AND EMOTIONAL DIFFERENCES AMONG MALES AND FEMALES

LIST OF TABLES ...... viii LIST OF FIGURES ...... iv INTRODUCTION ...... 1 Mirror Neuron Discovery ...... 3 Mirror Neuron System in Humans ...... 6 Imitation in the Mirror Neuron System ...... 8 Empathetic Gender Differences ...... 10 Gender Differences in Brain Structures Supporting Empathy ...... 11 Empathy and the Mirror Neuron System ...... 12 Working Memory ...... 15 Present Research ...... 16 Predictions ...... 17 METHOD ...... 19 Participants ...... 19 Materials and Procedures ...... 20 Statistical analysis ...... 23 RESULTS ...... 25 DISCUSSION ...... 31 Limitations ...... 36 Implications ...... 37 APPENDIX ...... 40 vi

TABLES ...... 43 FIGURES ...... 46 REFERENCES ...... 48

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LIST OF TABLES

Table 1 Demographic Characteristics of Sample By Gender ...... 43 Table 2 Means and Standard Deviations for All Trials ...... 44 Table 3 Difference Scores for RT for Males and Females ...... 45

viii

LIST OF FIGURES

Figure 1 Means Graph for Empathy by Gender...... 46 Figure 2 Mean Response Times by Gender ...... 47

I. INTRODUCTION

The mirror neuron system (MNS) consists of a specific class of visuomotor neurons, which fire for both observation of an action, and for execution of that action (di

Pellegrino, Fadiga, Fogassi, Gallese & Rizzolatti, 1992). The MNS was first discovered in area F5 in the macaque monkey brain (Gallese, Fadiga, Fogassi, & Rizzolatti, 1996;

Rizzolatti & Craighero, 2004), but was later also found in the human brain (hMNS), specifically in the left frontal operculum and the right anterior parietal region (Iacoboni,

Woods, Brass, Bekkering, Mazziotta, & Rizzolatti, 1999). Since that time, much research has been conducted to test the abilities and limitations of the human mirror neuron system, from communicative gesture implications, to language and cognitive development, and even to a possible explanation for autism spectrum disorder (ASD)

(Dapretto et al., 2006; Enticott et al., 2012; Mainieri, Heim, Straube, Binkofski, &

Kircher, 2013; Perlovsky, & Ilin, 2013).

The specific abilities of the hMNS which this study utilized were that of empathy and motor learning/imitation. We decided to test these abilities as they have been strongly linked with the hMNS (Baird, Scheffer, & Wilson, 2011; Catmur., Walsh, & Heyes,

2009; Goldenberg, & Karnath, 2006; Iacoboni, 2009; Iacoboni, & Dapretto, 2006;

Kaplan, & Iacoboni, 2006; Pfeifer, Iacoboni., Mazziotta, & Dapretto, 2008) and we

believed further research into these abilities may have a strong influence on learning

techniques implemented for individuals who have been hypothesized to have impaired

mirror neuron systems, such as children with ASD.

Empathy has been described as the ability to understand, perceive, and actually

feel the emotional states of others (Derntl et al. 2010) and tends to be a trait strongly

linked with women. Females are thought to be more caring and empathetic than males,

with a generally stronger ability to express emotion (Hall and Matsumoto, 2004;

Montagne et al., 2005). As will be discussed in further detail shortly, the hMNS has been linked to empathy (Baird, Scheffer, & Wilson, 2011; Schulte-Ruther et al., 2008), showing significant gender differences (Cheng, Lee, Yang, Lin, Hung, & Decety, 2008;

Cheng, Tzeng, Decety, Imada, & Hsieh, 2006), but little to no research has been conducted to see the impact of emotion on learning/imitation differences among males and females. Therefore, this study aimed to address gender differences associated with empathy, and with motor learning and imitation within the mirror neuron system.

This research tested the accuracy of learning and motor imitation for males and females in various emotional settings. This study hoped to aid understanding of gender differences as they pertain to motor learning in emotionally varied settings. Specifically, we used the paradigm developed by Kessels, Montagne, Hendriks, Perrett, and de Haan in 2013 to test sensitivity to emotion in males and females, along with the Empathic

Concern subscale of the Interpersonal Reactivity Index to measure empathy, and corroborated these findings to determine that women are more empathetic than are men.

We then analyzed the differences of this same sample in motor imitation during various emotional states; our goal was to correlate the levels of empathy with the accuracy of 2

motor imitation. The findings from magnetoencephalography (MEG) and

electroencephalography (EEG) studies provided support for the differences seen for

males and females in the mirror neuron system, and for the role empathy plays within the

MNS. Both studies provide neuroimaging support for the significant gender and empathetic differences this current work hypothesized to find (Cheng et al., 2006; Cheng et al. 2008; Schulte-Ruther et al., 2008; Woodruff, Martin, & Bilyk, 2011; Yang, Decety,

Lee, Chen, & Cheng, 2008).

Review of Literature

Mirror Neuron Discovery

In 1988, Rizzolatti, Camarda, Fogassi, Lupino, and Matelli discovered that neurons in area F5 of the macaque monkey’s premotor cortex were activated by particular types of grasping. di Pellegrino, Fadiga, Fogassi, Gallese, and Rizzolatti (1992) went on to study the activity of F5 neurons in macaque monkeys, specific to behavioral situations in which they could separate stimulus-associated responses from neuronal activity related to movements. They planned to explain the features of these specific neurons and the behavioral causes and social implications of these novel functions of the premotor neurons. In both studies, monkeys were connected to recording devices, with single neurons being recorded during various tasks. The neurons were first tested by presentation of informal objects to the monkey. Objects of different sizes and shapes were presented in various spatial positions, and neurons which were seen to fire to the hand movement of the monkey in relation to an object were then studied further, in

behaviorally controlled situations. Trials were conducted by having the monkey press a

switch with its index finger and thumb. If the monkey held this switch for 1.2-1.5

seconds, a door would open, allowing the monkey to obtain the food located inside the

box. If they did not hold the switch down for the allotted amount of time, the trial was

aborted. The arm and hand movements were recorded during these trials. The neurons

were also tested for the monkeys’ observation of meaningful movements performed by

the researchers such as grasping objects, placing food on a surface, retrieving the food,

and giving the food to another researcher. For control, the experimenters tested whether

these same neurons fired in the presence of hand-object relationships performing

meaningless tasks, such as presenting the food with forceps instead of a hand, and

presenting movements of the hand without food.

The results show the neuronal discharges were as sharply defined for grasping observation as for grasping execution. Most of these neurons fired for both observation

and imitation of a grasping action, which led them to be named “mirror neurons” (MN).

Another important finding for this experiment was that when the food was presented to

the monkey via forceps instead of a hand, the action was not sufficient to trigger neuron

firing. The same was found for movements of the hand unrelated to food presentation.

This experiment showed that neurons within area F5 of the macaque monkey fire

specifically for performance of grasping actions and observation of grasping actions in

meaningful situations.

The authors discuss the impact of their findings in regards to the fundamental

function of the premotor cortex. They state that while the retrieval of appropriate motor 4

acts is in response to visual stimuli such as shape, color, and size, the meaning behind an observed action can also trigger the retrieval of a motor action response. These findings

were also interpreted as evidence of shared cortical circuitry for gesture perception and

limb praxis, as the activation of neurons only for observed movements that closely

corresponded with the action performed by the monkey caused the initial neuronal

activation.

In 1996, Gallese, Fadiga, Fogassi, & Rizzolatti set out to test the action

recognition properties of mirror neurons in area F5 of macaque monkeys, specifically

which actions were recognized and activated in area F5. They recorded electrical activity

of 532 neurons in the rostral part of inferior area 6 in two macaque monkeys. They tested

area F5 in both the right and left hemisphere in one monkey, and only in the left

hemisphere for the second monkey. The monkeys were trained to reach for items once

they were placed within grasping reach, but not before. After isolation of neurons in the

specified brain region, the neuron discharge was measured for both grasping of objects

(mainly food) by the monkeys and for the monkeys’ observation of the experimenter

grasping these objects. As in di Pellegrino et al.’s 1992 research, in order to verify that

these neurons only fired during observation and imitation, the experimenters also

performed additional tasks, such as waving their hands, displaying unpleasant objects, or

lifting their arms. Electrical recordings were obtained during all trials to determine which

of the 532 isolated neurons were, in fact, mirror neurons. They discovered 92 neurons

which fired for both active movements made by the monkey, and for meaningful actions

executed by the experimenter. These 92 mirror neurons are the basis for rest of their

study. They researched further which specific actions elicited firing of these 92 mirror neurons. They discovered that the neurons were triggered most effectively by actions involving the mouth or hands, specifically grasping, placing, or manipulating hand actions.

In summary, mirror neurons were initially discovered in the premotor cortex, specifically area F5 of macaque monkeys in 1988, and have been found to activate both during observation and imitation of meaningful actions. Mirror neurons have continued to be studied in greater detail since that time, and this additional research has discovered that mirror neurons trigger strongest for observed and executed actions involving hands or the mouth, especially for manipulating hand actions.

Mirror Neuron System in Humans

The study of mirror neurons increased in the years following these studies, and in

2004, 16 years after the first discovery of mirror neurons, enough research had been conducted for Rizzolatti and Craighero to publish a review of the mirror neuron system

(MNS), including the location of these neurons and their circuitry, and evidence for a mirror neuron system in humans. Rizzolatti & Craighero first explain that mirror neurons, which respond to action observation, are not exclusively located in area F5, but that the circuitry of these neurons includes the ventral premotor cortex (which includes F5) and the rostral part of the inferior parietal lobule. They discuss that the cortical mirror neuron circuit in the monkey brain is comprised of these two main regions. The latter area receives input from the superior temporal sulcus (STS), and sends an output to the ventral

premotor cortex, including area F5. Rizzolatti and Craighero do point out that while the

STS is related to mirror neuron circuitry, it has no innate motor properties and can

therefore not be included as a part of the cortical mirror neuron circuit.

The authors go on to discuss the discovery of the human mirror neuron system

(hMNS). Various neuropsychological testing and brain imaging experiments, such as

transcranial magnetic stimulation (TMS), were important tools in the discovery of a

mirror neuron system in humans. Rizzolatti and Craighero cite research conducted by

Gangitano, Mottaghy, & Pascual-Leone (2001) in which TMS, which elicits electrical stimulation of the central nervous system, was utilized and the motor-evoked potentials

(MEPs) were recorded from the hand muscles of volunteers while they observed others making grasping movements. The results showed motor cortical excitability during the observed action. Rizzolatti and Craighero conclude from this, and other studies with similar results, that the human homologue for the mirror neuron system involves the rostral part of the inferior parietal lobule (the same location found to be activated in the mirror neuron circuitry of the monkey), the lower part of the precentral gyrus, and the posterior part of the inferior frontal gyrus (IFG). They also explain that the human MNS possesses even more important properties than that of the monkey MNS, with meaningless movements activating the mirror neuron system and also the movements forming an action, and not just the action itself, activating these neurons in humans. The reviewers state the importance of the hMNS role in determining the ability of humans to imitate the actions of others and its involvement in action understanding.

The MNS can contribute to our understanding of human learning. Observation

and imitation are key components to how a child learns. The mirror neuron system is

activated for both observation and imitation, and is therefore important in learning

capabilities of humans, as humans first observe an action and then duplicate it in order to

learn. The importance of our current research lie in the hypothesized result that women will perform more accurately for motor tasks during emotional settings. This result, if significant, may aide in additional understanding of advanced learning mechanisms for typically developing humans, and those who may have impairment of their mirror neuron system, as it will provide insight into the effect of emotion on the ability to learn a new task. Currently, the approaches for learning do not differ based on gender. This research could expose an idea that males and females, specifically those with MNS impairment, need to be taught differently, and that a generalized approach isn’t the best approach.

Imitation in the Mirror Neuron System

The mirror neuron system has been found to be a major underlying structure for imitation learning. One of the first experiments to discover how strongly linked the hMNS is with imitation learning was the research conducted by Buccino et al. in 2004.

The experiment involved scanning participants during one of four stages: observation of guitar chords played by a guitarist, a pause following the observation, execution of the observed chords, and rest. Through functional magnetic resonance imaging (fMRI), they looked at the various regions of the brain activated during each stage and found that the basic circuit underlying imitation learning was the mirror neuron circuit (specifically, the inferior parietal lobule, the posterior part of the inferior frontal gyrus, and the adjacent 8

premotor cortex). They state that the mirror neuron system is the core system underlying imitation based learning. The results of Buccino et al.’s research lead Rizzolatti and

Craighero to propose in their 2004 review of the MNS that, during the learning of a new motor task with intent to imitate, the observed actions are decomposed into elementary acts, and then recombined within the mirror neuron circuitry.

It’s important to note that Buccino et al. concludes that, while the mirror neuron system plays a core role in imitation learning of novel hand actions, there are other neural systems that play crucial roles in sequence imitation learning. The research currently proposed based its finger sequencing task on the understanding that the mirror neuron system is the core system underlying imitation based learning (Buccino et al. 2004).

Further research should be conducted to test this task simultaneously with brain imaging to exactly pinpoint any other systems that may be activated during the imitation learning of a motor task. However, it is clear from the literature that the hMNS is activated during these tasks, and was therefore able to be tested in the proposed manner.

Imitation tasks can be influenced by the participants’ working memory (WM) capacity as the viewer must hold information in their brain in order to duplicate what they see. van Leeuwen, van Baaren, Martin, Dijksterhuis, and Bekkering (2009) tested working memory’s impact on behavioral imitation. They used images of finger cues, in conjunction with an N-Back secondary task which included either high or low working memory load manipulation. The results of this experiment showed that working memory, in fact, facilitates behavioral imitation. They found that response speed to the finger cues were faster for the spatial cues in the high WM load group, supporting their hypothesis 9

that working memory aides in imitation. Due to the importance of WM in motor

learning, our study controlled for the contribution of WM to gender differences in motor

imitation accuracy by testing working memory in all participants, and then using any

significant WM differences for males and females as a covariate in our analysis.

Empathetic Gender Differences

In 2005, Montagne et al. researched gender differences in emotional sensitivity.

They used a computer generated program to show subjects faces which morphed from

neutral to one of six emotions. The subjects were asked to label the emotion they

perceived from a list provided to them. Then they were asked to go back through the

animated sequence and state at what point they were able to perceive each emotion. The

latter tested sensitivity and the former tested accuracy. The results showed women were

better for both accuracy and sensitivity than were men for all emotions. The results were

significant specific to women’s accuracy in recognizing sadness and surprise, and for

men significantly less sensitive than women for the emotions of anger and disgust. The

task that the current research will use is the Emotion Recognition Task (ERT), which is a

paradigm developed by Montagne et al. based on their 2005 research. The ERT uses

morphed faces to display emotions, and the subjects are asked to choose which emotion

is being displayed. The ERT is different from Montagne et al.’s 2005 work in that it does

not require subjects to go back and label when they were able to identify the emotion.

In 2008, a study by Schulte-Ruther et al. found support for the theory that males and females use varying strategies of both cognitive and emotional processing that

contribute to specific empathetic gender differences. Their experiment involved the use

of functional magnetic resonance imaging to look at which regions in the brain were

activated during empathetic testing. They found that the neural networks that support

empathy are modulated by gender. Their results suggest that “better empathic abilities of

females are related to their enhanced reliance on the hMNS when assessing the emotional

states of other people and their own emotional response to the feelings of others,”

(Schulte-Ruther et al., 2008). Based on these findings it seems reasonable to predict that

females will perform better than males on motor sequencing tasks when emotions are

involved.

Gender Differences in Brain Structures Supporting Empathy

In a study conducted by Schulte-Rüther, Markowitsch, Shah, Fink, and Piefke

(2008) twenty six participants were tested to discover gender differences in brain

networks supporting empathy. There were three baseline tasks used, one for feelings

evoked from self (responding to their own emotional response to the stimuli), one for

feelings evoked from other (participants evaluated the emotion expressed on the screen),

and head direction, (towards or averted by 45 degrees). Head direction, gender, and age

tasks on neutral faces were used as a high-level baseline condition. In the experiment,

subjects were placed in an fMRI machine and shown blocks consisting of four different

trials using self-, other-, and high-level baseline tasks. Participants were instructed to either focus on their own feelings (self) or to evaluate the emotion on the face shown

(other), after which animated face stimuli of emotional faces expressing either anger or fear were shown. Participants were then prompted to choose from four, one or two word 11

lists describing the images on the screen. In two separate runs, each participant was asked to rate each face based on intensity of feeling evoked from self and expressed by the face stimulus.

The results of this study found activation in both conditions in the inferior frontal

gyri bilaterally, which is an area that has been implicated in the human mirror neuron

system (Iacoboni, Woods, Brass, Bekkering, Mazziotta, & Rizzolatti, 1999). Schulte-

Rüther et al.’s 2008 results substantiate the involvement of the hMNS in the emotional

aspects of empathy. They conclude that neural networks supporting empathy are

regulated by gender, based on the areas activated during testing (specifically, that females

have enhanced reliance on the hMNS when assessing the emotional states of other people

and their own emotional response to the feelings of others, due to better empathic

capabilities). Males may have a more cognitive strategy, especially when determining

their own emotional response to the feelings of others, thus having less empathic ability

when compared to females.

Empathy and the Mirror Neuron System

Mu rhythms reflect an “idling” state in the sensorimotor cortex that is seen in the

absence of any movement and have recently become associated with mirror neurons

(Pineda, 2005). It has been found that both motor execution and motor observation

suppress the mu rhythm in similar ways (Muthukumaraswamy & Johnson, 2004), just as

mirror neurons are activated for both motor observation and execution. It is therefore

clear why there is an interest in this sensorimotor rhythm as it pertains to motor neurons.

Woodruff, Martin, and Bilyk (2011) have hypothesized that mirror neurons are a mechanism through which visual information about an action is transferred to the motor cortex. They used this theory as a basis to study the association between empathy and mu suppression in the sensorimotor cortex, stating that this finding would be in addition to the mirroring processing found in self-other (empathic) distinctions.

Woodruff et al. utilized EEG to record mu suppression in the human motor cortex, specifically the area of the brain that controls voluntary movement, including mirror neurons. They aimed to correlate suppression of this wave with empathic abilities.

Their procedure included three conditions: a video of a hand tapping the thumb and index finger (observation), the participant executing the tapping himself (execution), and a video of a hand at rest (rest). These three conditions were tested while simultaneous EEG recordings were taken. The results of the suppressions during the three conditions were then correlated with the subscales of the Interpersonal Reactivity Scale (IRI) (a self- report scale measuring empathic abilities), specifically the perspective taking (PT) subscale. To find significance at each electrode, they calculated a difference score by subtracting observed action mu suppression from executed action mu suppression. The authors found a negative correlation between the calculated mu suppression difference and the PT scale. The mu suppression was indicated by negative numbers, meaning the stronger the suppression, the more negative a number. The results show that a greater difference score implies higher perspective taking ability. This finding confirmed their hypothesis that the differences for self- and other-induced mu suppression is significantly

correlated with perspective taking skills. They state, based on their findings, that the

neural activity reflected in mu suppression is related to empathic abilities.

Other work that provides support for mu suppression implications associated with

mirror neurons and their involvement with empathy is that of Yang, Decety, Lee, Chen,

and Cheng. Their 2009 research showed suppressed mu rhythms for pain empathy, and

showed a correlation of that finding with the personal distress subscale of the IRI. An

interesting aspect of their work was that this correlation was only found in the female

participants. This finding suggests the presence of gender differences in pain empathy within the sensorimotor cortex. The authors further state that the mu rhythm can be a potential biomarker of empathic mimicry. This result lends support to the current study’s hypothesis that a female’s accuracy of performance on a motor task in emotional situations would differ from males and would also be more strongly correlated with the empathy subscale of the IRI.

Further support for this hypothesis can be found in Cheng, Tzeng, Decety, Imada, and Hsieh’s 2006 study, which investigated gender differences in the MNS. They utilized the highly reproducible poststimulus rebounds of mu rhythms detected by MEG measures from the primary motor cortex (M1) to evaluate the MNS of males and females, and to observe any differences. They state that suppression occurs just before rebound of the mu rhythm, and the suppression indicates cortical activation, just as the studies above claimed.

They tested this rebound in 10 males and 10 females during three conditions, including a resting state, a hand state, and a dot state. During the dot state, subjects attended to a dot on the screen, and during the hand state, the subjects watched a clip of a right hand manipulating an object. The rest state was used as control. The results of this study were very significant, showing stronger mu suppression (M1 activation) for females than for males in the hand condition, whereas the reverse was true for the dot condition. These findings lead to the conclusion that gender differences are exhibited by the MNS, with females having a stronger activation of the motor cortex when watching a hand perform an action than males.

A limitation to this study was that they employed a male hand for the hand task.

During the experiment, researchers did ask subjects to estimate the gender of the hand and found about only half the participants could correctly guess the sex of the hand, however, the authors do state that this variable could have an effect on the females’ response to the hand and that could be the reason for the increased activation. To avoid this possible confounding, the current research will utilize an androgynous hand. Based on an anonymous survey given to the community in which various hands will be rated on levels of femininity and masculinity, the most androgynously rated hand will be used for all motor imitation tasks used in the study.

Working Memory

Working memory (WM) refers to refers to the storage and manipulation of information (Baddeley, 2012) and can be implicated in imitation tasks as the viewer must

hold information in their brain in order to duplicate what they see. van Leeuwen, van

Baaren, Martin, Dijksterhuis, and Bekkering (2009) tested working memory’s impact on behavioral imitation by testing executive functioning and working memory during imitation tasks. They used images of finger cues, in conjunction with an N-Back secondary task which included either high or low working memory load manipulation.

Participants were asked to attend to a finger cue (either attending to the finger movement itself, or to a black X on one of the fingers while ignoring the movement of the other fingers) and to move the indicated finger. At the same time, one of two N-Back tasks were used to manipulate the participants’ working memory. Half of the participants were put into a low WM group, and the other a high WM group. The goal of this task was to remember a letter for a certain period of time so that it can later be compared to other letters. The number of letters the participants were asked to remember indicated whether they were in the low or high WM group.

The results of this experiment showed that working memory, in fact, facilitates behavioral imitation. They found that response speed to the finger cues were faster for the spatial cues in the high WM load group, supporting their hypothesis that working memory aides in imitation.

Present Research

Empathy is defined as an individuals’ ability to feel the emotional states of others

(Derntl et al., 2010). Therefore, our research refers to empathy as the ease with which a person can emotionally relate to another, and their ability to process these emotions. Our

current paradigm used emotions to test that ability (empathy) and its effect on a motor

task. The current research intended to analyze gender differences in the association

between empathic tendencies and the participant’s ability to imitate a finger motor task, with the assumption that this imitative task reflects mirror neuron performance (Buccino et al., 2004; Catmur et al., 2009; Gangitano et al., 2001; Iacoboni et al., 2009; Mainieri et al., 2013). The first aim of this study was to determine if women were more empathetic than men. Additionally, this study aimed to see if more empathetic people would perform better on motor imitation tasks after controlling for nonverbal working memory capacity.

Another aim of this study was to analyze any difference in performance for the emotion

trials between males and females. As well, this research planned to shed light on the

implication of emotion in learning and its impact on the mirror neuron system, which may provide insight into possible adjustment for learning techniques for individuals

thought to have impaired mirror neuron systems.

Predictions

The first aim of this study, in accordance with previous studies, hypothesized

there would be a significant difference in levels of empathy between gender, with females showing higher levels of empathy than men. We also predicted, in accordance with this study’s second aim, that women would show stronger performances in the imitation tasks across all trials. We predicted a main gender effect, specifically for the emotions happy and angry, with gender, with a significantly higher score for females across both emotion trials. This prediction was based on the supposition that the ease with which females can process emotions was greater than that for males, due to their increased levels of 17

empathy. Thus, we hypothesized that their accuracy and response times would be

significantly better, as it would take males longer to process the emotions, therefore

delaying their response time, and affecting their accuracy.

Empathy has been found to be involved in mirror neuron activation (Yang,

Decety, Lee, Chen, and Cheng, 2009), with brain regions, including the rostral part of the

inferior parietal lobule, the lower part of the precentral gyrus, and the posterior part of the

IFG showing mirror neuron activation for meaningless movements, as well as movements forming an action (Buccino et al., 2004). As our task required action of a hand movement, it is posited to activate mirror neurons. Therefore, we propose that significant differences in reaction time or accuracy of finger tapping in the emotional settings (which will be attributed to empathetic differences as stated above), can also be stated to affect mirror neuron activation. These results, if found, will lend support to our hypothesis that empathy affects mirror neuron functioning. We can then conclude that a stronger performance for females within this task, which should by all accounts activate mirror neurons, will be related to females’ higher level of empathy. Previous research supports differences in the MNS for males and females, and shows empathy plays a role in MN activation. Therefore, we predict the motor finger sequencing task, in concordance with emotion duplication, will show differing results among males and females, which can then be proposed to be the end result of mirror neuron firing differences.

II. METHOD

Participants

100 individuals, evenly distributed males and females, aged 18 to 45 were utilized

for this study. One way analyses of variance (ANOVAs) were run to detect any significant differences in our sample for age and years of education between males and females. There was not a significant difference in age for males (M = 25.94, SD = 6.87)

2 and females (M = 25.48, SD = 7.22); F(1,98) = 1.07, p = .745, ηp = .001. There also was

no significant difference in years of education for males (M = 16.88, SD = 3.15) and

2 females (M = 16.37, SD = 1.51); F(1,98) = 1.07, p = .304, ηp = .011. All participants fell

within normative data provided by Kessels,, van Zandvoort, Postma, Kappelle, & de

Haan (2000) for Block Span (M = 6.22, SD = 1.32) and Total Score (M = 57.79, SD =

22.63) of working memory (see table 1). These results support homogeneity within our

sample and aid in applicability of our sample to the population. However, the total score

from the working memory task showed significant differences between males (M =

2 62.94, SD = 25.08) and females (M = 52.64, SD = 18.74); F(1, 98)= 5.41, p = .022, ηp =

.001. Consequently, we used this factor as a covariate for all further analysis in order to

account for any differences that may have been attributed to working memory. Inclusion

criteria involved a score between 20-61 on the Toronto Alexithymia Scale, however, we did find a significant difference for alexithymia scores between males (M = 40.76, SD =

2 8.98) and females (M = 37.34, SD = 7.60); F(1,98) = 4.23, p = .042, ηp = .041 (see table

1). Therefore, we ran secondary analyses with alexithymia scores as an additional

covariate to detect any differences in our results with this measure included.

Ethnicity distribution was as follows: 45% European American, 10% African

American, 23% Hispanic/Latino, 7% Afro-Caribbean, and 15% other. As our test showed

an image of a right hand, we used only right handed participants, reducing the possibility of handedness as a confounding variable. Additionally, participants were currently free from any psychiatric disorders, and had no history of traumatic head injury. We recruited students from FAU classes, with extra credit as an incentive in participating classes. We also tested members of the community, on a volunteer basis, with no additional incentive.

We recruited subjects from the community through word of mouth and referrals from those who have participated and from peers. We also sent out recruitment emails to potential subjects.

Materials and Procedures

After signing the consent form, participants were given a demographic questionnaire before the test was administered to determine education, ethnicity, previous psychological disorders, etc. Also, before the administration of the experimental paradigm, participants completed the 20-item Toronto Alexithymia Scale to test for any issues with identifying their emotions. The Toronto Alexithymia Scale is a self-report measure which allows for identification of individuals who have trouble identifying and describing emotions. These individuals also tend to minimalize emotional experiences.

This scale has three subsections: the difficulty describing feelings subscale (DDF) is used 20

to measure difficulty describing emotions, the difficulty identifying feelings (DIF)

subscale is used to measure difficulty identifying emotions, and the externally-oriented thinking subscale (EOT) is used to measure the tendency of individuals to focus their

attention externally. The scores are as follows: 0-51, non-alexithymia, 52-60, possible alexithymia, 61 or higher, alexithymia. This scale demonstrates good internal consistency

(Cronbach’s alpha = .81) and test-retest reliability (.77, p<.01) (Bagby,, Parker, & Taylor,

1994). Once this was completed, the Emotion Recognition Task was administered.

The Emotion Recognition Task (ERT) was provided to us by

Metrasquare/DiagnoseIS (Montagne, Kessels, De Haan, & Perrett, 2007) and was used to duplicate the emotion recognition portion of Montagne et al. 2008’s work. The emotion recognition task is a paradigm used to measure the perception of facial emotional expressions at different intensities. We computed a total score for each emotion by adding the number of emotions correctly labeled (max = 16 per emotion). As well, a total score for the ERT was computed by adding the individual totals per emotion

(total = 96) to obtain an average score for each participant, for each emotion. We compared the results of our participants’ ability to recognize and label emotions to those provided by Kessels et al. to verify that our participants fell within the normal distribution of emotion recognition for males and females.

Next, we implemented our own novel experimental paradigm to test emotion imitation and gender effects on motor sequence imitation and response time (in milliseconds). In all trials, a short video of hand tapping four fingers in various sequences was shown to the participants. We employed the use of a female right hand for the 21

videos. The hand was chosen via a hand androgyny survey distributed online in which

different hands were rated from very feminine to very masculine. 86 people participated

in the survey, and we chose the hand rated most androgynous in an attempt to avoid

gender of the hand effecting results.

This section of the experiment had three sections. A baseline task was designed to

obtain each subjects’ basic response time (RT) and accuracy for finger sequence

imitation. They were asked to duplicate various finger sequences without any emotional

imitation (no emotion). Following the first set of trials, each participant was shown a still frame of one of the faces previously identified by the subject during the ERT. They were asked to imitate the emotion shown while watching and repeating, a finger tapping sequence shown on screen, just as before (emotion imitation). There were two emotion sections tested, happy and angry, for a total of three trial sections. For all sections, the finger sequence was recorded via key presses and graded on accuracy, based on correct/incorrect responses. The scale for accuracy was measured on how many key presses were accurately duplicated in the correct order. Response time was recorded for all participants, for each trial.

A computerized variation of the Spatial Span of the Weschler Memory Scale, the

Corsi Block-Tapping Task, was then administered to the participants. This task tested the nonverbal working memory of the subjects, to account for significant differences between males and females in in the ability to hold and recall the information given in the imitation task. Results of the Corsi task for males and females are shown in table 1.

The final task administered was the Empathic Concern subscale of the

Interpersonal Reactivity Index. The Empathic Concern subscale of the Interpersonal

Reactivity Index was used to assess the participants’ tendency to experience feelings of sympathy and compassion for others. It is a self-report scale and measured the participants’ degree of empathetic concern. (The standardized alpha coefficients for this subscale for males = .68 and for females = .73, and test-retest reliability for males =.72, and for females =.70) (Davis, 1980). The results of this scale provided the scores of empathy for each subject.

Statistical analysis

One-way ANOVAs were run to look at descriptive information for participants and to look for any significant differences for males and females within our sample. We also looked at any significant differences for males and females for age, years of education, alexithymia scores, and working memory scores in order to verify homogeneity for our sample and to control for any significant differences when running additional analyses. In accordance with the first aim of this study, we initially ran an

ANOVA to look for significant differences for empathy scores among gender. We expected to find significantly higher scores on the IRI scale for women.

To test the additional aims of the study, that women will perform better on emotional imitation tasks, we conducted two 3 x 2 repeated measures ANCOVAs with

gender as the between factor and the motor imitation tasks (with and without emotion) as

the within factors, first with working memory as a covariate, then with alexithymia added

as an additional covariate. An interaction between factors was expected with females presenting more accurate motor scores than males under the emotion conditions only. We also ran two 3 x 2 repeated measures ANCOVAs with gender as the between factor and the response times for each trial as the within factors, with the same covariate procedure as before. We predicted similar finding for response time and accuracy, with females performing faster than males. Again, we predict that males will show decreased processing ability for emotions, and thus take additional time for duplication in the emotion tasks.

If interactions were significant, additional analyses were run to look at differences for males and females in each trial, along with follow up analyses to look at main and interaction effects for significant differences. Additionally, we looked at the correlations between accuracy and response time for each trial set. Statistical analyses were run using

IBM SPSS Statistics for Windows, Version 21.0.

Finally, we ran post hoc power analyses to analyze the power of our sample. The program we employed for this analysis takes the effect size, degrees of freedom, and number of covariates from each analysis and computes sample power based on this information. We utilized the partial eta squared effect sizes in our analyses of our sample power. Post hoc power analyses were run on G*Power 3, version 3.1.9 (Faul, Erdfelder,

Lang, & Buchner, 2007).

III. RESULTS

Results from an ANOVA show a significant difference in empathy scores for

males (M = 20.16, SD = 3.85) and females (M = 23.44, SD = 3.55); F(1,98) = 19.63, p <

2 .001, ηp = .167 (see table 3, figure 1). This finding supports our first hypothesis which stated that females would be more empathic than males. Also, this finding is consistent

with normative data, lending further support for the representativeness of our sample to

the population. Based upon normative data, we were able to split participants into two

categories of empathy for testing purposes: average empathy (0-24) and high empathy

(25-28). These cutoffs were determined by averaging the means, plus one standard

deviation, of the normative data of the IRI for males (M = 19.04, SD = 4.21) and females

(M = 21.67, SD = 3.83). The average of these scores was 24.37, therefore 24 was used as our cutoff. There were a total of 70 average empathy participants (27 females) and 30

high empathy level participants (23 females). These levels of empathy were to be used if

necessary to split participants by levels instead of gender later in our analyses. However,

this was not found to be necessary in our final analysis.

Our working memory task, the Corsi Block task, was analyzed by comparing

participants’ mean performance scores for the Block Span and Total Score variables with

the normative data supplied by Kessels et al. (2000). Participants results fell within the

2 norm for both block span (M = 6.22, SD = 1.32), F(1,98) = 3.37, p = .069, ηp = .033 and

2 total score (M = 57.79, SD = 22.62), F(1,98) = 5.41, p = .022, ηp = .052. As the Corsi 25

total score was significant for gender, we used this variable as a covariate in our additional analyses.

While any participants who scored 61 or higher on our alexithymia scale

(indicating alexithymia) were excluded from analysis, we ran an ANOVA to look for any differences among gender in this score for our participants. We found a significant difference in alexithymia scores for males (M = 40.76, SD = 8.98) and females (M =

2 37.34, SD = 7.60); F(1,98) = 4.23, p = .042, ηp = .041. This variable was used as a covariate during future analysis to test for any differences associated with this factor.

To test our second hypothesis, a 2x3 (gender x emotion) analysis of covariance with repeated measures for accuracy was run, first with working memory only as a covariate. It was predicted that there would be a significant interaction between gender and accuracy on the emotion trials, indicating a gender difference in the emotion trials for accuracy. While significance was found for emotion accuracy within trials, F(2,96) =

2 3.64, p = .030, ηp = .070, no significant interaction was observed between accuracy and

2 gender, F(2,96) = .011, p = .989, ηp = .000 (see table 2). The results show a difference in direction for males and females, with slower response times for males in the neutral and angry trials, but faster response times for males in the happy trial. This indicates quicker responses for females in no emotion and angry trials, but faster response times for males in the happy trials (see figure 2).

Next, we ran the same analysis, but with alexithymia score as an added covariate to test for additional differences. This analysis showed no significance for accuracy

2 within trials, F(2,95) = .603, p = .549, ηp = .013, or for the interaction between accuracy

2 and gender, F(2,95) = .002, p = .998, ηp = .000. The inclusion of alexithymia as a

covariate eliminated the significance for accuracy among trials, but had no effect on the

accuracy and gender interaction. These findings don’t support our hypothesis that

accuracy on an emotional paradigm would be modulated by gender.

To see if any differences would be found for response time among tasks by

gender, we ran two additional 2 x 3 (gender x emotion) analyses of covariance with

repeated measures for response time. The first analysis included working memory as a

covariate. Interestingly, in partial support of our proposed hypothesis that response time

would additionally be effected by emotion and gender, our results showed significance at

the .05 level for an interaction between gender and emotion response time for the

2 emotion trials, F(2,96) = 3.28, p = .042, ηp = .064. This finding lends support to the

differences between males and females in the speed of duplication of finger taps in

emotionally varied situations, with males performing slower in neutral and angry tasks,

but faster in happy trials. Our second 2 x 3 ANCOVA, with both working memory and

alexithymia score as covariates, eliminated the significant differences between gender

2 and response time, F(2,95) = .352, p = .704, ηp = .007. While the gender and response

time interaction did begin to near significance with these covariates, no significance was

2 found for the interaction, F(2,95) = 2.68, p = .073, ηp = .053.

To understand the direction of the response time and gender interaction, we ran a

one-way ANCOVA to look at differences in RT for each trial. However, no significance

2 was found for the no emotion trial, F(2,97) = 1.31, p = .256, ηp = .013, the angry trial,

2 2 F(2,97) = 1.88, p = .173, ηp = .019, or the happy trial, F(2,97) = .125, p = .724, ηp =

.001 . This lack of significance is in accordance with our second analysis for response

time, including alexithymia as a covariate. As males scored significantly higher on the alexithymia scale, indicating more difficulty in labelling their own emotions, it would follow that including alexithymia as a covariate would affect our results in regard to gender.

Yet, as our results did show nearer to significant findings for the interaction of

gender with response time, and as there were differences in response times for angry and

happy trials for males (M = 5101.59ms, SD = 787.48ms, and M = 4865.22ms, SD =

623.50ms, respectively) and not females (M = 4949.86ms, SD = 682.06ms, and M =

4960.86ms, SD = 713.03ms, respectively), we decided to create a differences variable,

using the mean scores from both emotion trials in order to further test our hypothesis (see

figure 2).

We subtracted the happy response time trials from the angry response time trials

to obtain our difference score. A one-sample t-test for the difference scores showed that

response times for males and females in the emotion trials differed in that females stayed

relatively stable across both emotion trials (M = -11.01, SD = 527.88), t(49) = -.147, p =

.883, while there was a significant difference for males in response times for angry and

happy trials (M = 236.37, SD = 536.12); t(49) = 3.12, p = .003 (see table 3).

Utilizing this information, we ran a univariate ANCOVA to test the effects of

gender on this differences score, first with the working memory score as a covariate, and

then with working memory and alexithymia as covariates, as before. From our first

analysis, we found a significant gender difference in response times for angry and happy

2 stimuli, F(1,97) = 5.37, p = .023, ηp = .052. To look at the effect of empathy on this

finding, we included the empathy scores of the participants as an additional covariate.

2 When we did this, we found a significant empathy effect, F(1,96) = 5.82, p = .018, ηp =

2 .057 but the gender effect was eliminated, F(1,96) = 1.60, p = .209, ηp = .016.

For our second ANCOVA, we again found a significant gender difference in

2 response times for angry and happy stimuli, F(1,96) = 4.52, p = .036, ηp = .045. Once

more, when including empathy score as an additional covariate, we found a significant

2 empathy effect, F(1,95) = 5.28, p = .024, ηp = .053, but our gender effect was again

2 eliminated, F(1,95) = 1.60, p = .209, ηp = .017. This indicates that the more empathic a

person is, the faster their response times are for the emotion trials, signifying a faster RT

for processing between the angry and happy stimuli relating to empathy.

When we analyzed the correlations between accuracy and response time, no

emotion accuracy was negatively correlated with no emotion response time, r = -.223, p <

.05, and anger response time, r = -.269, p < .01. There was a nonsignificant negative

correlation of -.196 (p = n.s.) between no emotion accuracy and happy response time.

Anger accuracy and anger response time were significantly negatively correlated, r = -

.239, p < .05. There was a nonsignificant negative correlation of -.157 (p = n.s.) for

anger accuracy and anger response time, as well as a nonsignificant negative correlation

of r = -.180 (p = n.s.) anger accuracy and happy response time. As for happy accuracy, we found a significant negative for correlation for all trials, with a no emotion response time correlation of r = -.242, p < .05, a angry response time correlation of r = -.247, p <

.05, and a happy response time correlation of r = -.337, p < .01.

Post hoc power analyses were run for all null hypotheses which weren’t rejected, with no power reaching more than .10, indicating poor probability of detecting differences in the population from our sample. Thus, acceptance of null hypotheses that were not rejected was not possible.

IV. DISCUSSION

Results showed that levels of empathy are significantly different for males and

females, with levels of empathy in females being significantly higher than males. This

finding supports our study’s first hypothesis and is also in accordance with previous

research which state that empathetic differences within neural networks are modulated by

gender (Montagne, Kessels, Frigerio, de Haan, Edward, & Perrett, 2005, & Schulte-

Rüther, Markowitsch, Shah, Fink, & Piefke, 2008). Additionally, our results show that

accuracy and response time for emotional trials are not affected by gender or empathy level, and that reaction time differences between emotion trials are modulated by empathy scores, but not by gender. These findings were in contradiction of our hypothesis that females would perform better across all emotional trial tasks, which we proposed would be related to their higher levels of empathy and therefore lower attention to the processing of emotions. Additionally, it is important to note that working memory, while clearly activated during our task, was controlled for during analysis and can therefore not be said to have had an effect on our results.

When looking at raw response times across trials, no significant effect was found for gender. However, when we used only emotion trials, and converted the raw scores into differences scores, which were created by subtracting happy mean scores from angry

mean scores, we did find significance. This, we propose, was related to the fact that only emotion trials were utilized, and that it provided differences for emotional response time, versus a total response time, allowing for analysis of more specific differences for males and females for emotion overall. Additionally, the task employed the use of happy and angry emotions. The valence of these emotions has been found to be positive and negative, respectively (Neta, Davis, & Whalen, 2011). We therefore used these two emotions to obtain information on both positively and negatively charged emotions, without the need for numerous emotion trials. We believe it was a way to focus the test on emotional differences, without worry of blurred lines for the valence of the emotions.

However, that is not to say that adding in more emotions wouldn’t improve the results.

We will discuss this further shortly.

As stated above, our results showed that there was a significant effect of trial on accuracy. Our finding of significance for accuracy among trials supports the use of our current paradigm in testing emotion duplication by showing that there was an effect of emotion on accuracy within each trial, indicating a difference for the participants in each trial. Therefore, the paradigm was not simply testing accuracy or working memory, but that it in fact was testing a difference between neutral and emotional tasks. However, gender did not show to modulate this difference. Thus, our prediction that women would show stronger accuracy performance in the imitation tasks across all trials was not supported by the current data.

An important difference between our study and previous research is that we didn’t measure the activation of the mirror neuron system during the motor task; therefore we 32

are not sure if this brain activation occurred. However, previous research by Woodruff et

al. (2011) and Cheng, Tzeng, Decety, Imada, and Hsieh (2006) provided significant

evidence for mirror neuron activation for tasks involving action of a hand movement,

either with or without intentionality. As our task involved observation and duplication of

hand movements, very similar to the neuroimaging studies above, it is reasonable to state that our task activated mirror neurons in similarly located brain regions.

Furthermore, our null results contradict previous findings which discovered

gender differences in favor of females for tasks which activated mirror neurons (Cheng,

Tzeng, Decety, Imada, & Hsieh, 2006; Schulte-Rüther, Markowitsch, Shah, Fink, &

Piefke, 2008; & Yang, Decety, Lee, Chen, & Cheng, 2009). The previous research used similar tasks of hand manipulation to activate mirror neurons, but did not include emotional aspects in their design, and instead correlated their findings only with self- report empathy scales. It is possible that our current task, with the utilization of emotion duplication during motor imitation, caused an unrelated region of the brain to become activated which may have overtaken the strength of the mirror neuron system involvement in our task. However, this proposed reasoning cannot be substantiated without neuroimaging techniques being employed during testing. For now, it can only be surmised that, while the MNS was probably active for these tasks, there are additional factors influencing our results.

We saw a decrease in response time for males from the neutral and angry trials

(similar RT) to the happy trials (faster RT), yet females showed very steady response times across all trials. This finding could be proposed to support our statement that the 33

ease with which females process emotions is higher than males, though the analysis did

not support this. To further evaluate the possibility of gender effects within our sample,

we look to our results from our differences scores analysis. The process of computing a

difference score was also employed by Woodruff et al. in their 2011 research. While

studying correlations between observation and execution, they calculated a difference

score by subtracting observed action mu suppression from executed action mu

suppression and found significance at each electrode. They found significant correlations

between mu suppression within the motor cortex with empathic abilities, leading them to

conclude that differences for self- and other-induced mu suppression were significantly modulated by empathic abilities. We did find significant interaction for gender in the

differences scores among emotion trials. This led us to propose that the emotion trials

caused a significant decrease in reaction time for males, which initially lent support to

our hypothesis. However, once empathy was included, that finding was nullified. We

conclude that empathy, not gender, modulates the differences in response time, nullifying

our initially proposed hypothesis.

From this conclusion, it is reasonable to state that those with higher levels of

empathy have a quicker response time in emotionally driven imitation tasks. These

results relate to similar mu suppression-based EEG findings which correlated mu

suppression with empathic abilities and empathy factors. Mu rhythms, as discussed

above, reflect an “idling” state in the sensorimotor cortex and are suppressed during

motor execution and motor observation. Therefore, suppression of mu rhythms has been

found to be highly related to mirror neuron activity (Muthukumaraswamy & Johnson,

2004). Hence, our results, coupled with previous research correlating mu suppression

with empathic ability and subscales of the IRI, can substantiate the differences found in

our sample, and further support the activation of mirror neurons in this task (Cheng et al.,

2006; Muthukumaraswamy & Johnson, 2004; Yang et al., 2009; & Woodruff et al.,

2011).

Any significant correlations found for accuracy and response time were negative, indicating that the faster the response time, the more accurate the response. Specifically for the angry trials, we saw that the more accurate the motor duplication, the quicker the response time, but no significant correlation was seen for angry accuracy and happy or no emotion response time. As well, the faster the response for the angry trials, the more accurate participants were for all trials, no emotion, angry, and happy. This was an interesting finding, as it could show that negative emotions may cause slower response times, and therefore decreased accuracy of trials. Future research could look further into this hypothesis, to determine if negatively valenced emotions did in fact cause a processing impairment, and if that is related to levels of empathy.

The difference between our findings and the previous research is that the research conducted previously also found a difference between males and females in activation of mirror neurons and mu suppression. We can only conclude from this that the differences between paradigms, specifically the addition of emotion into the task, created additional brain region activation, which influenced the proposed gender differences. Additionally, the significant difference among males and females in alexithymia scores could also play a role in the lack of significant results discovered from this research. It is possible that 35

males, who scored higher on the scale of alexithymia than females, did in fact affect our results. While participants are not considered highly alexithymic until scores reach 61 or above, the difference in scores for males and females may have resulted in inadequately matched participants, preventing this study from finding the proposed results.

Limitations

The sample size of this study was a limitation, as our post hoc power analyses did not find anything higher than .10, indicating we had insufficient power to detect the effect that is in the population. This may be due to (1) the effect being small within the population itself, or (2) our sample size being insufficient, or a possible combination of the two. Regardless, more participants may increase the power, and allow for accurate reporting of differences among males and females. Additionally, our power could be increased by further treatment validity. As our motor/emotion task was novel, and no techniques were employed to physiologically test emotion duplication for participants, it stands to reason that we may not have truly caused emotional duplication within our subjects. Future research should employ additional measures, such as skin conductance equipment, during testing to verify a difference in sympathetic nervous system activation during neutral and emotional tasks.

Another limitation to this study was that no imaging techniques were employed.

While there is strong evidence to support mirror neuron activation without the use of neuroimaging, it would provide stronger evidence of mirror neuron activation if this study was run in conjunction with a neuroimaging technique, such as fMRI. Additionally,

neuroimaging during testing would allow for specific regions of the brain to be viewed, which would lead to additional knowledge about what regions of the brain may be overpowering the gender differences previously found in motor imitation tasks similar to the ones used in the current study. Future research could also employ more than two emotion trials to discover the range of differences in response times among gender.

Implications

Previous research has shown gender differences within the mirror neuron system, as well as empathy differences (di Pellegrino, Fadiga, Fogassi, Gallese,& Rizzolatti,

1992; Gallese, Fadiga, Fogassi, & Rizzolatti, 1996; Rizzolatti, Camarda, Fogassi,

Lupino, & Matelli, 1988; & Rizzolatti & Craighero, 2004). It has been found to activate both for observation of an action, and duplication of that action (Buccino et al., 2004;

Gangitano, Mottaghy, & Pascual-Leone, 2001; & Schulte-Ruther et al., 2008). At the same time, there has been no previous research to look at interactions of empathy within the MNS specific to gender. While our results did not support our predictions, it still provides useful information for future researchers, as this research is one of the first to study imitation learning and the effects of empathy and gender within the MNS. The results of this experiment can be used as guidelines, starting points, and baseline information for future research on gender and emotion effects on mirror neuron paradigms.

Additionally, as there are no emotion and motor imitation tasks currently in use, we had to create a novel paradigm for this experiment. Even though our results did not

support our purported hypotheses, our paradigm was found to be significantly accurate

for testing emotional impact in the accuracy trials, as significant differences were found

among trials. This finding can support the use of this task in future experiments and can

provide an otherwise non-existent paradigm for this field of study. As well, future work

employing the use of neuroimaging or skin conductance devices could enable researchers

to more accurately assess differences in emotion and non-emotion trials, and use that information, along with our findings, to analyze specific emotional differences between trials.

While more research should still be conducted to look further into gender differences in emotionally varied situations, this research does provide some insight into the differences within this system for males and females, and the implication that emotions may play a role in learning. Moreover, our results, while providing further support for previous findings of empathetic differences among gender, also provide a starting point for research to be conducted to test the impact of emotion on response time and performance ability in emotionally varied situations.

The impact of this research could aide in advanced teaching techniques for males and females, as well as those with ASD, as they are proposed to have impaired mirror neuron systems (Dapretto et al., 2006; Enticott et al., 2012; Mainieri, Heim, Straube,

Binkofski, & Kircher, 2013; & Perlovsky, & Ilin, 2013). Taking into account a difference in time needed to duplicate a motor task in emotionally charged situations for less empathic subjects, the current applied behavioral analysis tasks employed for ASD children may need to adjust certain tasks required of them, based upon emotional factors. 38

This work, along with future studies on this subject, will provide insight on adjustments that need to be made for each child based on their emotional processing, and will therefore help them to learn better, in a more structured lesson suited to their needs.

Additionally, future work should explore the gender differences discussed herein with the aide of neuroimaging techniques to account for any supplementary regions activated during these tasks.

V. APPENDIX

INTERPERSONAL REACTIVITY INDEX

The following statements inquire about your thoughts and feelings in a variety of situations. For each item, indicate how well it describes you by choosing the appropriate letter on the scale at the top of the page: A, B, C, D, or E. When you have decided on your answer, please circle the corresponding letter beneath the question. READ EACH ITEM CAREFULLY BEFORE RESPONDING. Answer as honestly as you can. Thank you.

ANSWER SCALE:

A B C D E DOES NOT DESCRIBES ME DESCRIBE ME VERY WELL WELL

1. I often have tender, concerned feelings for people less fortunate than me.

A B C D E

2. Sometimes I don't feel very sorry for other people when they are having problems.

A B C D E

3. When I see someone being taken advantage of, I feel kind of protective towards them.

A B C D E

4. Other people’s misfortunes do not usually disturb me a great deal.

A B C D E

5. When I see someone being treated unfairly, I sometimes don't feel very much pity for them.

A B C D E

6. I am often quite touched by things that I see happen.

A B C D E

7. I would describe myself as a pretty soft-hearted person.

A B C D E

Table 1 Demographic Characteristics of Sample by Gender

MALES (n=50) FEMALES (n=50) Partial eta MIN MAX M SD MIN MAX M SD F Sig. Squared AGE 18 44 25.94 6.87 18 45 25.48 7.22 1.07 .745 .001 EDUCATION 10 24.5 16.88 3.15 13.5 20 16.37 1.51 1.07 .304 .011 CORSI BLOCK SPAN 4 9 6.46 1.4 4 8 5.98 1.2 3.37 .069 .033 CORSI TOTAL 24 117 62.94 25.08 16 96 52.64 18.74 5.41 .022 .052 EMPATHY SCORE 10 28 20.16 3.85 17 28 23.44 3.55 19.63 .000 .167 ALEXITHYMIA SCORE 24 56 40.76 8.98 23 58 37.05 8.45 4.23 0.042 0.53

Table 2 Means and Standard Deviations for Accuracy and Response Times, All Trials

ACCURACY MEANS RESPONSE TIME MEANS NEUTRAL ANGER HAPPY NEUTRAL ANGER HAPPY Male Mean 3.6250 3.4475 3.3925 5109.2150 5101.5925 4865.2200 (n=50) Std. Deviation .29667 .45305 .44644 853.54074 787.47887 623.49606 Female Mean 3.5463 3.3450 3.3263 4952.3100 4949.8550 4960.8600 (n=50) Std. Deviation .36439 .54240 .41521 732.68113 682.06034 713.02829 Total Mean 3.5856 3.3963 3.3594 5030.7625 5025.7238 4913.0400 (N=100) Std. Deviation .33294 .49986 .43021 795.30057 736.88357 668.09962

Table 3 Difference Scores for RT for Males and Females

MALES FEMALES Sig. Sig. t df (2-tailed) t df (2-tailed) Difference_Scores_RT 3.118 49 .003 -.147 49 .883

Figure 1 Means Graph for Empathy by Gender

VI.

Figure 2 Mean Response Times by Gender

5150

5100

5050

5000

4950 MALES 4900 FEMALES

4850

4800

4750

4700 NO EMOTION ANGRY HAPPY

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