Kay Redfield Jamison, professor of psychiatry and behavioral sciences and co-director of the Johns Hopkins Mood Disorders Center at the Johns Hopkins University School of Medicine, convened a discussion of the effects of depression on creativity. Joining Jamison were two distinguished colleagues from the fields of neurology and neuropsychiatry, Dr. Terence Ketter and Dr. Peter Whybrow. The Music and the Brain series is co-sponsored by the Library’s Music Division and Science, Technology and Business Division, in cooperation with the Dana Foundation.

The “Depression and Creativity” symposium marks the bicentennial of the birth of German composer Felix Mendelssohn (1809-1847), who died after a severe depression following the death of his sister, Fanny Mendelssohn Hensel, also a gifted composer.

One of the nation’s most influential writers on creativity and the mind, Kay Redfield Jamison is a noted authority on bipolar disorder. She is the co-author of the standard medical text on manic-depressive illness and author of “Touched with Fire,” “An Unquiet Mind,” “Night Falls Fast” and “Exuberance: The Vital Emotion.”

Dr. Terence Ketter is known for extensive clinical work with exceptionally creative individuals and a strong interest in the relationship of creativity and madness. He is professor of psychiatry and behavioral sciences and chief of the Bipolar Disorders Clinic at Stanford University School of Medicine.

Dr. Peter Whybrow, an authority on depression and manic-depressive disease, is director of the Semel Institute for Neuroscience and Human Behavior at the University of California, Los Angeles (UCLA). He is also the Judson Braun Distinguished Professor and executive chair of the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine at UCLA. (description take from here).

And here’s the video:

1) Most people like decorating their house for Christmas. Some of them go too far, as you can see in this video. One possible reason for this behaviour could be the desire to communicate friendliness and cohesiveness with neighbours. Werner et al. examined whether strangers can accurately identify the more friendly residents, and what aspects of the homes’ exteriors contribute to their impressions. They also examine the possibility that residents who decorate for Christmas but who have few friends on the block may be using the decorations and other cues as a way of communicating their accessibility to neighbours.

Participants rated residents based only on photographs of their home and front yard. Stimulus homes had been preselected to represent the four cells of a two by two factorial design crossing the presence/absence of Christmas decorations with the resident’s self-rated social contact with neighbors (low/high). As expected, a main effect for the decorated factor indicated that raters used Christmas decorations as a cue that the residents were friendly and cohesive. Decoration interacted with sociability in a complex but interpretable way. In the absence of Christmas decorations, raters accurately distinguished between the homes of sociable and nonsociable residents; in open ended comments, they attributed their impressions to the relatively more ‘open’ and ‘lived in’ look of the sociable residents’ homes. When Christmas decorations were present, raters actually attributed greater sociability to the nonsociable residents, citing a more open appearance as the basis for their judgments. The results support the idea that residents can use their home’s exterior to communicate attachment and possibly to integrate themselves into a neighborhood’s social activities.

I have a feeling that extreme Christmas decorations probably fail to achieve this purpose and result in (further) alienation.

2)  What makes for a Merry Christmas? Not consumerism according to a study by Kasser et al. More specifically:

More happiness was reported when family and religious experiences were especially salient, and lower well-being occurred when spending money and receiving gifts predominated. Engaging in environmentally conscious consumption practices also predicted a happier holiday, as did being older and male. In sum, the materialistic aspects of modern Christmas celebrations may undermine well-being, while family and spiritual activities may help people to feel more satisfied.

You can read the full study here.

3) Christmassy stuff make you feel better if you’re a Christian or if you celebrate Christmas. Schmitt et al. examined the differential psychological consequences of being in the presence of a Christmas display on participants who did or did not celebrate Christmas, or who identified as Christian, Buddhist, or Sikh. Participants completed measures of psychological well-being while they were in a cubicle that was either decorated or not with a Christmas display. The Christmas decorations harmed non-celebrators and non-Christians well-being scores. The opposite effect was found on Christians. I’m wondering what’s the effect on atheists that were raised in Christian families/societies..

4) If you still believe in Santa Claus you might have to skip this one. Still here? You’re probably over 8. According to a (locked) study by Blair et al. this is the mean age at which disbelief in Santa Claus occurs  for both boys and girls. Another study (Anderson et al., 1994) examined the children’s reactions on discovering the Santa Claus myth.

Children reported predominantly positive reactions on learning the truth. Parents, however, described themselves as predominantly sad in reaction to their child’s discovery.

5) And finally, Christmas phobias, or the 12 neuroses of Christmas. Not very scientific but funny (unless you’re suffering from Ho-Ho-Phobia).

PS: I’m a bit surprised by the lack of neuroimaging studies on Christmas! I was hoping for something catchy and pointless like “Your brain on Santa Claus” or “The neuroscience of Christmas Carols”.

WERNER, C., PETERSONLEWIS, S., & BROWN, B. (1989). Inferences about homeowners’ sociability: Impact of christmas decorations and other cues Journal of Environmental Psychology, 9 (4), 279-296 DOI: 10.1016/S0272-4944(89)80010-6

Kasser, T., & Sheldon, K. (2002). What Makes for a Merry Christmas? Journal of Happiness Studies, 3 (4), 313-329 DOI: 10.1023/A:1021516410457

BLAIR, J., MC KEE, J., & JERNIGAN, L. (1980). CHILDREN’S BELIEF IN SANTA CLAUS, EASTER BUNNY AND TOOTH FAIRY Psychological Reports, 46 (3), 691-694 DOI: 10.2466/pr0.1980.46.3.691

Schmitt, M., Davies, K., Hung, M., & Wright, S. (2010). Identity moderates the effects of Christmas displays on mood, self-esteem, and inclusion Journal of Experimental Social Psychology, 46 (6), 1017-1022 DOI: 10.1016/j.jesp.2010.05.026

Anderson, C., & Prentice, N. (1994). Encounter with reality: Children’s reactions on discovering the Santa Claus myth Child Psychiatry and Human Development, 25 (2), 67-84 DOI: 10.1007/BF02253287

Surprisingly, only a few studies to date have addressed this issue. The first one was by Andrews and Coppola (1999), who recorded eye movements of 15 viewers while they were performing five different tasks.: (1) natural occurring eye movements in darkness, (2) viewing simple textured patterns, (3) scene perception, (4) visual search, and (5) reading. The authors concluded that apart from the visual environment, idiosyncracies also have a significant effect on eye movements.

In addition to examining the stability of eye movements across different tasks, Rayner et al also examined the possibe cultural differences influence on eye movements across the different tasks. Previous studies have provided some preliminary evidence of cultural differences. More specifically, Chua, Boland, and Nisbett (2005) examined the eye movement patterns of Chinese and native English speaking participants when looking at scenes. Cua et al found that Chinese were more likely to look at the background information in a scene, while the Americans looked at the foreground objects longer and sooner than the Chinese.

Rayner et al recruited seventy-four participants, which were divided into three different groups based on their knowledge and fluency of English and Chinese. The first group, the American group, consisted of native English speakers, the second , the native Chinese group consisted of 3 native speaking Chinese participants (who learnt to speak english later in their life), and finally, the Bilingual group consisted of Chinese participants who were either born in the USA or moved there before the age of 5. The right eye movements of each participant were tracked. All participants performed the following six tasks: (1) English reading, (2) face processing, (3) scene perception, (4) visual search, (5) Chinese character count, and (6) Chinese character search. In the English reading task, 40 English sentences were read . In the face processing and scene perception tasks, participants were shown 16 pictures of female faces and 24 pictures of scenes and asked to remember them for a later memory test. In the visual search task, participants were asked to find a brown square that was part of an array of brown circles and pink squares. In the Chinese character count task, participants counted the occurrences of a Chinese character in a paragraph of Chinese text. Finally, the participants who could read Chinese read 36 Chinese sentences.

Fixation duration and saccade size were used as primary indices of temporal and spatial processing in the tasks.

It is generally assumed (see Rayner, 1998) that (1) fixation duration reflects the time needed to process the informa-tion around fixation and the time needed to plan the next saccade and (2) saccade size is related to how much information can be processed on a fixation and how the next saccade target is selected.

The results of the present study suggest that fixation durations for a given individual tend to be fairly stable across different tasks. For the American and Bilingual groups, fixation durations in English reading did not correlate especially well with fixation durations in the other tasks, while for the Chinese group fixation durations in English reading did tend to correlate highly with the other tasks. Fixation durations in scene perception and face processing were highly correlated across all three participant groups. Saccade length did not correlate as well across tasks as did fixation duration. The correlations, however, tended to be positive when the reading tasks were eliminated from the analysis.

No correlation was found between fixation duration and saccade length across all of the tasks. According to Rayner et al this could be evidence that the mechanism responsible for determining when to move the eyes is largely independent of the mechanism responsible for determining where to move the eyes next.

Reading visual tasks are in general more understood than other visual tasks. The correlations in fixation durations for these different tasks does, however, suggest that there might be common aspects of processing between them. The nature of these mechanisms is not very clear. Rayner et al. suggest that:

Perhaps in non-reading tasks, some kind of timing mechanism determines when the eyes move; such a common timing mechanism would be expected to lead to correlations across tasks, particularly in fixation durations (and to a lesser extend, saccade length). Another possibility is that something like visual saliency.

Another interesting finding of this study was that the more experience participants had with either English or Chinese, the shorter the fixations and the longer the saccades they made. This effect did not depend on cultural characteristics of the participants. As far as the effect of culture on eye movements is concerned, only a few differences were identified. Chinese participants had systematically shorter fixations in the scene perception, face processing, and Chinese count tasks than the Americans. Their performance was similar on the two search tasks. The difference in the duration of fixation observed between Chinese and American participants is due to the Chinese trading off number of fixations with fixation duration. In other words, while they made somewhat shorter fixations, they also made slightly more fixations.

Rayner K, Li X, Williams CC, Cave KR, & Well AD (2007). Eye movements during information processing tasks: individual differences and cultural effects. Vision research, 47 (21), 2714-26 PMID: 17614113

ADHD is the most common neurodevelopmental disorder (Faraone et al., 2003) and affects about 3–6% of children (Tannock 1998). ADHD is defined by either an attentional dysfunction, hyperactive/impulsive behaviour or both (DSM-IV; American Psychiatric Association, 1994). Therefore, the diagnosis of ADHD has three subtypes: the Inattentive subtype (ADHD/IA), which is characterised by significant levels of inattention but subthreshold levels of hyperactive/ impulsive symptoms, the Hyperactive/Impulsive subtype (ADHD/HI), which is defined by hyperactivity/ impulsivity but not of inattention symptoms, and the Combined Inattentive-Hyperactive/Impulsive subtype (ADHD/C), which is characterised by maladaptive levels of both symptom clusters.

Caci H, Bouchez J, & Baylé FJ (2009). Inattentive symptoms of ADHD are related to evening orientation. Journal of attention disorders, 13 (1), 36-41 PMID: 19387003

The Symphony of Science is a musical project of John D Boswell, designed to deliver scientific knowledge and philosophy in musical form. The project owes its existence in large measure to the classic PBS Series Cosmos, by Carl Sagan, Ann Druyan, and Steve Soter, as well as all the other featured figures and visuals. Continuation of the videos relies on generous support from fans and followers.

Read more about the project here.

Here’s one of my favourites, “Ode To The Brain”.

In 2010 alone, there were over 40,500 h of live sporting events on broadcast and cable TV (Neilsen Company, 2011)

However, little is know about the personality  traits and the identity of people who like watching sports*.

Appelbaum and colleagues gathered  broad demographic, physiological, clinical, psychological, and pastime-preference information from a sample of 293 individuals to see what factors most reliably predicted sport spectating habits. First, they examined possible relationships between watching sports and physiological measures. Saliva was collected and baseline testosterone and cortisol levels were measured. Moreover, 2D:4D digit ratio was calculated for each individual. This measurement is a proxy of prenatal androgen exposure and has been shown to correlate with particular disorders. Secondly, they administered self-report scales looking at ADHD (Jasper/Goldberg adult ADD/ADHD questionnaire) and autism traits (AQ; Autism Spectrum Quotient). Furthermore, they investigated the relationship between sports spectating and personality traits. The NEO personality inventory (NEO-PI-R), which measures the “BigFive” personality traits, and the Barratt Impulsivity Scale (BIS-11) were used. Finally, Appelbaum et al. asked their participants about the pastime activities. The pastime involvement questionnaire asked participants how many hours a week they spend on a number of activities such as reading, playing sports, watching television and movies, and listening to music.

As expected gender and age significantly accounted for the variability in the results. Young males reported spending more time watching sports.  High levels of sports spectating were correlated with higher levels of extraversion, excitement seeking and gregariousness on the personality questionnaires. The participants who reported spending more hours watching sports also engaged more in specific pastime activities, such as participating in sports and exercise, watching TV/movies, and playing video games. No differences were observed in the self-report scales. More specifically, no differences in ADHD or autism symptoms were found between people who watch sports and people who don’t. Likewise, the authors didn’t find any relationship between digit ratio and sports watching.

No relationship was found between baseline concentrations of cortisol or testosterone and sports spectating. This came as a surprise to the authors who list a number of previous studies that identified higher concentrations of testosterone and cortisol in people who like sports. Now, before jumping to conclusions, take into account that the sport spectators in this study is not your average sports fan! Previous literature has identified two related concepts; fans and spectators. Even though those groups have some overlapping qualities, there are some key differences.

…a fan is typically associated with an emotional link to a sport or team, while a spectator is a more neutral descriptor of an individual who consumes sports (Wann & Dolan, 2001).

In this study, they were interested only in sports spectators (defined by the hours they spend watching sports). This could possibly explain why no relationship was found between sports watching and cortisol concentration.

Also, I think that there must be differences between spectators of different types of sports (e.g. rugby, tennis, snooker). The authors didn’t examined this, but it’d be interesting to see a study looking at differences in sports preferences between people who enjoy watching sports.

Gregory Appelbaum, L., Cain, M., Darling, E., Stanton, S., Nguyen, M., & Mitroff, S. (2011). What is the identity of a sports spectator? Personality and Individual Differences DOI: 10.1016/j.paid.2011.10.048

* Academics are probably not very keen on sports?

A study by Chen et al. that was published on the  JoN used a novel approach that combined non-invasive cortical functional mapping with whole-brain voxel-based morphometric analyses to investigate the anatomical relationship between the functionally mapped visual cortices and other cortical structures in healthy humans. Chen et al. found an interesting correlation between the size of V1 and primary auditory cortex. This relationship could be explained in terms of our everyday multisensory experience of the world. However, the size of those areas was anticorrelated with the size of the anterior prefrontal cortex (aPFC), the frontopolar part of the frontal cortex. In a few words, individuals with larger primary visual cortex had larger primary auditory cortex but smaller aPFC. This anticorrelation was only found for the primary sensory cortices and not for other visual cortices (e.g. V2, V3).

According to Chen et al.

…while one might expect a positive correlation between the whole-brain gray matter volume and the volume of its components, instead we found a striking anticorrelation for primary visual cortex: individuals with larger brains tended to have smaller primary visual cortices. In contrast, anterior prefrontal cortex was the single most enlarged region in a larger brain.

The aPFC is a particularly fascinating area. Apart from having many names (anterior PFC, the frontal pole, frontopolar cortex, rostral prefrontal cortex, BA 10…), aPFC is larger relative to the rest of the brain (Semendeferi et al., 2001) and is significantly different in humans compared to other primates (Semendeferi et al., 2001), suggesting that this region may contribute to the unique human behaviour. Furthermore, it is one of the last brain areas to mature in humans (Dumontheil et al., 2008) and has been recently identified as the region with the greatest relative prediction power about brain maturity over development (Dosenbach et al., 2011). Evidence from previous studies suggest that this particular area has a role in higher-order cognitive functions (including prospective memory)

The pairing between the expansion of anterior prefrontal cortex and the contraction of primary sensory cortices reflects a common ground for the formation of anatomically and phylogenetically remote cortical regions, and suggests the existence of a reciprocal link between high-order cognition and low-level sensation.

Future studies will attempt to further investigate this relationship and examine what the effects of these structural differences are on function and performance on various tests thought to tap on those areas.

Song C, Schwarzkopf DS, Kanai R, & Rees G (2011). Reciprocal anatomical relationship between primary sensory and prefrontal cortices in the human brain. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31 (26), 9472-80 PMID: 21715612

Schwarzkopf DS, Song C, & Rees G (2011). The surface area of human V1 predicts the subjective experience of object size. Nature neuroscience, 14 (1), 28-30 PMID: 21131954

Coren S, & Porac C (1987). Individual differences in visual-geometric illusions: predictions from measures of spatial cognitive abilities. Perception & psychophysics, 41 (3), 211-9 PMID: 3575080

Dumontheil I, Burgess PW, & Blakemore SJ (2008). Development of rostral prefrontal cortex and cognitive and behavioural disorders. Developmental medicine and child neurology, 50 (3), 168-81 PMID: 18190537

Semendeferi, K., Armstrong, E., Schleicher, A., Zilles, K., & Van Hoesen, G. W. (2001). Prefrontal cortex in humans and apes: a comparative study of area 10 American journal of physical anthropology, 3 (114), 224-241

Dosenbach NU, Nardos B, Cohen AL, Fair DA, Power JD, Church JA, Nelson SM, Wig GS, Vogel AC, Lessov-Schlaggar CN, Barnes KA, Dubis JW, Feczko E, Coalson RS, Pruett JR Jr, Barch DM, Petersen SE, & Schlaggar BL (2010). Prediction of individual brain maturity using fMRI. Science (New York, N.Y.), 329 (5997), 1358-61 PMID: 20829489

More specifically, strong right-handers compared to mixed-handers reported significantly decreased liking of unpopular music genres and marginally increased liking of popular genres. These differences do not appear to reflect differences in musical training or experience.  According to the author of the study handedness is associated with differences in cognitive flexibility. Previous studies suggest that strong right-handedness is associated with decreased interaction between the left and right cerebral hemispheres, which in turn is associated with decreased cognitive flexibility across various domains. The author concludes:

A number of studies report differences between conservatives and liberals in musical preferences (e.g., Glasgow & Cartier, 1985; North & Hargreaves, 2007). For example, Glashow and Cartier (1985) reported that conservatives prefer music that is safe and familiar, presumably reflecting preference for popular, not unpopular, genres. Given evidence that strong right-handedness is associated with increased conservative attitudes (Christman, 2008), this suggests a possible three-way connection between strong right-handedness, conservative views, and a lack of open-earedness. Accordingly, future research on individual differences in musical preferences would be well advised to include strength of handedness as a variable.

Finally, in case you’re curious, here are some of the genres included in each category: (a) popular: modern rock, classic rock, heavy metal, alternative rock, modern pop, 80s pop, R&B, Rap, Hip-hop, country, (b) unpopular: soul, funk, jazz, blues, folk, avant-garde, world, electronica, reggae, ambient, house. The categorisation of popular and unpopular genres was based on record sales (conventional music was defined as popular genres with high numbers of sales, while unconventional music was defined as less popular genres with lower numbers of sales). Even though the proposed idea is interesting, handedness is probably only one of the factors that might explain individual differences in musical preference. For a different approach see a recently published study by Chamorro-Premuzic et al. (2011) who found that individual differences in music consumption are predicted by uses of music and age rather than emotional intelligence, neuroticism, extraversion or openness.

Christman, S. D. (2011). Handedness and ‘open-earedness’: Strong right-handers are less likely to prefer less popular musical genres Psychology of Music : 10.1177/0305735611415751

Chamorro-Premuzic, T., Swami, V., & Cermakova, B. (2011). Individual differences in music consumption are predicted by uses of music and age rather than emotional intelligence, neuroticism, extraversion or openness Psychology of Music : 10.1177/0305735610381591

Emotion plays an important role in music. Even infants have been found to be capable of identifying emotions in musical excerpts (Nawrot, 2003). However, recognition of emotion in music has received little attention so far. A new study by Lima and Castro published in Cognition and Emotion examined the effects of ageing on the recognition of emotions in music. Previous studies looking at emotion recognition in other modalities have revealed that increasing age is associated with a decline in the recognition of some emotions but not others (for more information see meta-analysis by Ruffman et al. (2008)). Laukka and Juslin (2007) examined the effects of ageing on emotion recognition in music comparing young adults (around 24) and older adults (older than 65). Their results identified that older adults had more difficulty recognizing fear and sadness in both music and speech prosody, whereas no differences were observed for anger, happiness and neutrality.

The sample used by Lima et al. was of 114 healthy adults (67 female). They were aged between 17 and 84 years, and were divided into three groups with 38 participants each: younger(mean age=21.8 years), middle-aged (mean age=44.5 years) and older adults (mean age=67.2 years). Each group listened to 56 short musical excerpts that expressed happiness, sadness, fear/threat and peacefulness. Each category was consisted of 14 stimuli.

The results revealed significant age-related changes associated with specific emotions. More specifically, the authors identified a progressive decline in responsiveness to sad and scary music. No difference was found in happy music. Differences between age groups were also observed in the pattern of misclassifications for sad and peaceful music. Younger participants perceived more sadness in peaceful music, older participants perceived more peacefulness. This could be due to the structural features of peaceful and sad songs, which are both characterised by slow tempo. Future studies could further investigate this. In addition to that, Lima et al. took into account the years of musical training that the participants had. This analysis revealed a positive association between music training and the categorisation of musical emotions.

One possible explanation for the main findings of this study suggests that the decline in the recognition of particular emotions might reflect the age-related neuropsychological decline in brain regions (such as the amygdala) involved in emotion processing. Previous studies have showed that distinct brain regions are involved in the perception of different emotions (Mitterschiffthaler et al., 2007). Another possible explanation is the age-related positivity bias (Mather & Carstensen, 2005; Carstensen & Mikels, 2005). Age-related positivity bias suggests that people get older, they experience fewer negative emotions.

Future studies could attempt to identify particular brain regions involved in emotion recognition at different ages. Furthermore, since the age-related positivity bias might not be universal (older Chinese participants looked away from happy facial expressions and not from negative ones, see Fung et al., 2008), it’d be very interesting to investigate the effects of ageing on emotion recognition in music in participants from different cultures.

Lima CF, & Castro SL (2011). Emotion recognition in music changes across the adult life span. Cognition & emotion, 25 (4), 585-98 PMID: 21547762

Carstensen, L., & Mikels, J. (2005). At the Intersection of Emotion and Cognition. Aging and the Positivity Effect Current Directions in Psychological Science, 14 (3), 117-121 DOI: 10.1111/j.0963-7214.2005.00348.x

Ruffman T, Henry JD, Livingstone V, & Phillips LH (2008). A meta-analytic review of emotion recognition and aging: implications for neuropsychological models of aging. Neuroscience and biobehavioral reviews, 32 (4), 863-81 PMID: 18276008

Laukka, P., & Juslin, P. (2007). Similar patterns of age-related differences in emotion recognition from speech and music Motivation and Emotion, 31 (3), 182-191 DOI: 10.1007/s11031-007-9063-z

Mather M, & Carstensen LL (2005). Aging and motivated cognition: the positivity effect in attention and memory. Trends in cognitive sciences, 9 (10), 496-502 PMID: 16154382

Mitterschiffthaler, M., Fu, C., Dalton, J., Andrew, C., & Williams, S. (2007). A functional MRI study of happy and sad affective states induced by classical music Human Brain Mapping, 28 (11), 1150-1162 DOI: 10.1002/hbm.20337

Nawrot, E. (2003). The Perception of Emotional Expression in Music: Evidence from Infants, Children and Adults Psychology of Music, 31 (1), 75-92 DOI: 10.1177/0305735603031001325

Fung HH, Lu AY, Goren D, Isaacowitz DM, Wadlinger HA, & Wilson HR (2008). Age-related positivity enhancement is not universal: older Chinese look away from positive stimuli. Psychology and aging, 23 (2), 440-6 PMID: 18573017

The ability to avoid distractibility varies across individuals as measured by the Cognitive Failures Questionnaire (CFQ) (Broadbent et al., 1982). Studies on twins and families have showed that the ability to maintain attention in the presence of distractors is highly heritable (Boomsma, 1998). High degree of heritability suggests that the variability might be mediated by genetic influences on the brain, which may be expressed via variability in brain structure.

This hypothesis was tested by Kanai et al. by scanning 145 healthy adult individuals and obtaining their CFQ scores. They used voxel-based morphometry (VBM) to examine whether distractibility scores predicted brain structure. Their results revealed that the level of an individual’s distractibility in everyday life was predicted by variability in regional grey matter density of the left superior parietal lobe (SPL). Highly distractable individuals had larger grey matter density at the left SPL. This particular region has been implicated in top-down attentional control in previous studies (Mevorach et al., 2009). To examine whether there is a causal relationship between this region and distractibility, Kanai et al. applied transcranial magnetic stimulation (TMS) over the left SPL of the participants while they were performing an attentional capture paradigm. The results of the experiment suggest that the left SPL plays a role in suppressing distraction from task-irrelevant salient distractors in both visual fields.

Kanai R, Dong MY, Bahrami B, & Rees G (2011). Distractibility in daily life is reflected in the structure and function of human parietal cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience, 31 (18), 6620-6 PMID: 21543590

Boomsma, D. I. (1998). Genetic analysis of cognitive failures (CFQ): a study of dutch adolescent twins and their parents. Eur. J. Pers., 12(5):321-330.

Broadbent, D. E., Cooper, P. F., FitzGerald, P., and Parkes, K. R. (1982). The cognitive failures questionnaire (CFQ) and its correlates. The British journal of clinical psychology / the British Psychological Society, 21 (Pt 1):1-16.

Mevorach, C., Shalev, L., Allen, H. A., and Humphreys, G. W. (2009). The left intraparietal sulcus modulates the selection of low salient stimuli. Journal of cognitive neuroscience, 21(2):303-315.