Author Archives: Anika Wu

Electric Feel

A section of the museum! Daft Punk, an electric music duo, is French.

While travelling in Paris, I’ve passed quite a few musicians performing on the streets, whether they are singing, playing an instrument, or both. As someone who listens to music almost nonstop, I always find myself feeling a little brighter after I pass by these performers during my daily outings. What can I say? Music makes me happy, and good music happier. It’s not often that one finds time and space just for listening to music, but the “Electro: From Kraftwerk to Daft Punk” exhibit at the Philharmonie de Paris offered me this very opportunity, revisualizing the sonic experience of electronic dance music (EDM) into an immersive physical space. Tracing the origins of EDM to the present and featuring the works by renowned duo Daft Punk, “Electro” left me thinking about EDM for quite some time after I’d left. How do our brains process and respond to music, and how might the case be different for EDM?

I went to Shaky Beats music festival a year ago. The festival had several EDM artists playing.

Research suggests that listening to music is more complex than we might think, as it activates an entire network of cortical and subcortical areas (Zatorre and Krumhansl, 2002). Even the perception of rhythm involves multiple brain regions (Zatorre et al., 2007). When we hear music we like, our reward systems may activate, and when we tap our feet or bob our heads, we do so almost unbeknownst ourselves through activation of the basal ganglia (Trost et al., 2014; Zatorre et al., 2007).

A recent functional magnetic resonance imaging (fMRI) study by Brodal and colleagues examined the relationship between rhythmic music and basal ganglia, an area of the brain typically associated with fine motor skills (Hikosaka et al., 2002; Brodal et al., 2017). To test participants, researchers created a continuous-stimulation design (10.16 minutes long, 120 beats per minute) using an EDM-style composition. Ambient noise generated by the MR scanner was synchronized with the music to mimic an accompanying instrument and to prevent disturbance of participants’ listening experiences. The continuous-stimulation design was a departure from previous studies’ use of short chunks of music, which Brodal and colleagues believed may have caused limitations (Brodal et al., 2017).

Regions researchers observed. (Brodal et al., 2017)

Researchers used stochastic dynamic causal modeling (sDCM), a technology used to examine interactions between auditory perception, rhythm processing, and reward processing, to observe connectivity in the auditory cortex, putamen/pallidum (PP), and ventral striatum/nucleus accumbens (VSNAc) of both hemispheres. The latter two grouped terms were chosen for this study because the low resolution of raw fMRI data prevented distinction between grouped locations.

The sDCM revealed significant connections between all three areas in both hemispheres, as well as reduced functional connectivity in the reward system. Results supported the hypothesis that stimulation from rhythmic EDM-like music decreases connectivity in the right VSNAc from and to the basal ganglia and auditory network. Stimulation also resulted in decreased self-inhibition via the VSNAc, as well as changed hemodynamic parameter of the VSNAc, suggesting an increased level of activation. Furthermore, reduced connectivity was observed in basal ganglia, reward system, basal ganglia and auditory network. Ultimately, results demonstrated reduced reward system connectivity in participants listening to rhythmic music, thus supporting the hypothesis that the ventral striatum/nucleus accumbens region plays a significant role in processing the emotions associated with listening to music (Koelsch, 2014).

As Brodal and colleagues note themselves, one weakness of the study is its methodological constraints. Though evidence already exists on rhythm and the observed effects, researchers’ use of only one music piece prevents confident establishment of a connection, at least in relation to the present study (Brodal et al., 2017). Furthermore, participants’ states while listening to the given music is only compared to one other state, the resting state. Brodal and colleagues note that it is thus impossible to definitively determine whether the observed effects emerged during the resting state (Brodal et al., 2017). Lastly, though not a weakness, laboratory conditions in the Brodal team’s study are far different from normal conditions in which one might listen to music. EDM in particular is often celebrated at large outdoor festivals, and it would be interesting to understand how music interacts with festival environments and other relevant factors to affect our emotions, reward circuits, and capacity for inhibition.

Or who knows? Maybe I’ll see for myself at my next EDM festival. In an era of increasing technologization, electronic music represents not only technology, but also the capability of technology to bring humans together. And it’s comforting knowing that something so powerful can serve us by bringing us joy.



Brodal HP, Osnes B, Specht K (2017) Listening to rhythmic music reduces connectivity within the basal ganglia and the reward system. Frontiers in Neuroscience. 11:153.

Hikosaka O, Nakamura K, Sakai K, Nakahara H (2002) Central mechanisms of motor skill learning. Current Opinion in Neurobiology 12(2):217-222.

Koelsch S (2014) Brain correlates of music-evoked emotions. Nature Reviews: Neuroscience. 15:170-180.

Cité de la Musique: Philharmonie de Paris (n.d.) The Electro exhibition.

Trost W, Frühholz S, Schӧn D, Labbé C, Pichon S, Grandjean D, Vuilleumier P (2014) Getting the beat: Entrainment of brain activity by musical rhythm and pleasantness. NeuroImage 103:55-64.

Zatorre RJ, Chen JL, Penhune VB (2007) When the brain plays music: Auditory-motor interactions in music perception and production. Nature Reviews: Neuroscience 8:547-558.

Zatorre RJ, Krumhansl CL (2002) Mental models and musical minds. Science 298:2138-2139.

Image 1-2 taken by myself

Image 3 taken from (Brodal et al., 2017).

OMG, More Stairs?!?

When I came to Paris, I thought I was prepared for everything: the bakeries, the museums, the landmarks, the culture — but nothing could have prepared me for the walking I was about to do. Unlike the suburban areas around Emory or my hometown of Topeka, Kansas, where a car is considered necessary for most outings, the streets of Paris are easily traversable by foot, and public transportation is much more accessible. And in a city so beautiful, I had a hard time refusing the ease of foot travel. Still, with the recent muggy weather, walking hasn’t felt quite as pleasant. People always say “no pain, no gain,” and I began to wonder what all my walking was doing for me brain-wise.

My steps before and after I came to Paris. As one can see, my steps significantly increased after I came to Paris, May 22th.

Turns out, there’s a lot to be gained from regular aerobic exercise. Consistent research has pointed to the role of physical activity in cognitive function and has grown in volume over the past decade (Soga et al., 2015). General movement has been suggested to contribute to brain plasticity, which in turn facilitates interaction between cognitive and motor functioning (Doyon and Benali, 2005). Furthermore, research has also linked physical activity to academic performance (Castelli et al., 2007). While these results doesn’t necessarily mean that taking up routine walking or running will guarantee better grades or memory, the two do seem to be invariably related.

Amidst this burgeoning research, Colcombe and colleagues decided to research the cortical mechanisms beneath cardiovascular fitness-related changes in cognitive function (Colcombe et al., 2004). Functional magnetic resonance imaging (fMRI) was used to study how changes in fitness might affect the brain. Researchers particularly focused on the anterior circular cingulate (ACC), an area of the limbic system linked to brain structures responsible for sensory, motor, emotional, and cognitive information (Bush et al., 2000).

The study took place in 2 segments, with Study 1 involving high-fit (HF) older adults, and Study 2 involving adults randomly assigned to either a cardiovascular fitness training (CFT) group or a stretching and toning group (control) (Colcombe et al., 2004). All participants in both groups underwent a flanker task in which they filtered and identified incongruent cues (Colcombe et al., 2004). The flanker test allowed researchers to study participants’ ability to filter and respond to relevant information (Colcombe et al., 2004). Researchers then compared cortical mechanisms triggered by incongruent clues to those triggered by congruent ones, to see whether HF adults would demonstrate higher activation in attention- and control-related regions (Colcombe et al., 2004).

fMRI scans of the ACC illustrate activation of different cortical areas in the task-related activity (Colcombe et al., 2004).

Sure enough, fMRI scans supported the study’s hypothesis that older adults with high levels of measured cardiovascular fitness would demonstrate significantly more activation in cortical regions linked with attention selection and control (Colcombe et al., 2004). These cortical regions include the medial frontal gyrus (MFG), superior frontal gyrus (SFG), and superior parietal lobe (SPL) (Colcombe et al., 2004). Significantly less activation was observed in the ACC, which is linked with behavioral conflict and adaptation of attentional control (Colcombe et al., 2004).

One weakness of the study by Colcombe and colleagues is the cross-sectional approach taken in Study 1. Being observational, cross-sectional studies are vulnerable to non-response bias, which can lead to a participant pool unrepresentative of the population (Sedgwick, 2014). Furthermore, data can only be collected during one set period of time, leaving researchers unable to create long-term representations of cause and effect (Sedgwick, 2014). However, it is important to note that longitudinal studies might also be difficult to complete with older participants, due to possible interference from disease or other age-related complications (Sedgwick, 2014). Ultimately, the research by Colcombe and colleagues was important at the time of its publication because it expanded upon existing research regarding the underlying cortical mechanisms of cardiovascular fitness.

More recent research by Brockett and colleagues suggests that physical exercise may contribute to extensive plasticity and increased cognitive functioning (Brockett et al., 2015). Rats who ran for moderate durations of 12 days were able to better discriminate than control rats in a task testing medial prefrontal cortex (mPFC) function, though little difference was seen between both groups in a task testing perirhinal cortex (PRC) function (Brockett et al., 2015). In a second experiment, runner rats took less trials and errors than control sedentary rats to reach criteria for simple discrimination, reversal, extradimensional shift (Brockett et al., 2015). Researchers also tested whether running influences astrocytes, non-neural brain cells that communicate with neurons and suggest links to synaptic plasticity, learning, and memory (Brockett et al., 2015). Co-labelling of astrocytes with visual markers revealed increase in astrocytes cell body area in the hippocampus, mPFC, and OFC (Brockett et al., 2015). These results aligned with data from the behavioral tests, suggesting that physical exercise can enhance cognitive performance in tasks that activate the hippocampus, mPFC, and OFC (Brockett et al., 2015). The lack of significant change to the PRC suggests that routine running lacks observable relation to the PRC. Ultimately, results suggest greater cognitive performance in tasks reliant on the prefrontal cortex, as well as enhanced synaptic, dendritic, and astrocytic measures in several regions. This evidence supports the hypothesis that physical exercise contributes positively to plasticity and cognitive functioning. Together, both papers by Colcombe, Brockett, and their colleagues have contributed to the growing understanding that exercise generally promotes greater cognitive functioning.

Brockett and colleagues’ research has made me wonder how much I would have to run to achieve the human equivalent of a rat’s 12-day regimen. As a student, it’s incredibly easy to get sucked into the grind and become deskbound. But the grind is exactly why brain power is important for the students, and optimizing my brain power in exchange for a few minutes and some physical effort has started to sound like a much better idea than the old me would have thought.


Brockett AT, LaMarca EA, Gould E (2015) Physical exercise enhances cognitive flexibility as well as astrocytic and synaptic markers in the medial prefrontal cortex. Public Library of Science ONE 10(5): e0124859.

Bush G, Luu P, Posner MI (2000) Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Sciences. 4(6):215-222. 6613(00)01483-2.

Castelli DM, Hillman CH, Buck SM, Erwin HE (2007) Physical fitness and academic achievement in third- and fifth-grade students. Journal of Sport and Exercise Psychology 29(2):239-252.

Colcombe SJ, Kramer AF, Erickson KI, Scalf  P, McAuley E, Cohen NJ, Webb A, Jerome GJ, Marquez DX, Elavsky S (2004) Cardiovascular fitness, cortical plasticity, and aging. Proceedings of the National Academy of Sciences of the United States of America            101(9):3316-3321.

Doyon J, Benali H (2005) Reorganization and plasticity in the adult brain during learning of motor skills. Current Opinion in Neurobiology 15(2):161-167.

Sedgwick P (2014) Cross sectional studies: Advantages and disadvantages. BMJ 348.

Soga K, Shishido T, Nagatomi R (2015) Executive function during and after acute moderate aerobic exercise in adolescents. Psychology of Sport and Exercise 16:7-17.

Image 1 taken by myself.

Image 2 from Colcombe et al., 2004.

Beauty is in the Eye of the Beholder

Mount Sainte-Victoire by Paul Cézanne.

The short time that I’ve been in Paris has felt so much longer than a few weeks. Last week, I spent several hours at the Musée d’Orsay, where I finally fulfilled my dream of viewing impressionist masterpieces face-to-face. A few nights later, I was looking through the photos that I’d taken during my recent travels, when one particular photo of a building caught my eye. Something about the image irked me. The asymmetry, I realized, was throwing my mind into a sort of desire to fix the photo. I began to wonder: What makes something beautiful, and what does symmetry have to do with it?


A building I saw when walking to the Soup Bar and thinking I didn’t like the way it looked.


A study by Makin and colleagues used a “gaze-driven evolutionary algorithm” to examine three factors: 1) Do people evaluate symmetry instinctively? 2) Do people prefer perfect symmetry or slightly imperfect imagery? 3) When people grow familiar with symmetry, do they lose fascination with it? Researchers employed eye-tracking technology to observe for factors that attracted 54 test subjects’ gazes (Makin et al.,2016). Observation of event-related potentials (ERPs) following exposure to abstract patterns suggested that ERPs responsible for aesthetic evaluation (beautiful vs. ugly) did not fire during evaluation of symmetry. In regards to the three questions initially posed, overall results suggested that, though symmetry was a significant factor in participants’ selection, 1) people do not automatically evaluate symmetry, and rather prefer slight imperfection; 2) people do not express marked preference for either symmetry or slight imperfection; 3) people’s interest in symmetry does not change following familiarization.

Based on this study, it seems like symmetry plays a part in all of our visual imagery preferences, though likely not to a critical extent. Perfect isn’t perfect. The question of aesthetic preference brought my thoughts back to what I’d seen at the d’Orsay. I began thinking about Cézanne and Monet, and what I’d read.

When Cézanne split from the impressionist project of “worshipping light” (Lehrer 103), he began a ceaseless quest to mimic the fleeting nature of the physical world. The images we see slowly take shape as they filter from V1 to V5. As Jonah Lehrer writes, “If the mind didn’t impose itself on the eye, then our vision would be full of voids” (Lehrer 117). Cézanne’s nonfinito technique taps into this process. Unlike the classic impressionists, Cézanne’s use of blank space mimicked the brain’s process of filling in emptiness to create meaning in otherwise meaningless sensory information.

Take, for example, a thin gray stripe, a “fragile scratch against the sprawling void” (Lehrer 115). Alongside the ambiguous forms of trees, a river, and the sky, it adopts a sensible identity as a mountain range, as our mind has already identified a coherent nature scene. Cézanne’s art alludes to the senselessness of reality and our capability — and need —  to make sense of it.

Vered Aviv concludes that abstract art promotes new meaningful neural connections that lead to higher-level brain states. The brain process after viewing abstract art “is apparently rewarding as it enables the exploration of yet undiscovered inner territories of the viewer’s brain” (Aviv, 2014). “‘The eye is not enough… One needs to think as well.’ Cézanne’s epiphany was that our impressions require interpretation; to look is to create what you see” (Lehrer, 2008).

Research by Hochstein and Ahissar proposes that “Vision at a glance reflects high-level mechanisms, while vision with scrutiny reflects a return to low-level representations” (Hochstein and Ahissar, 2002). Impressionism attempted to recreate an ‘impression’ of nature, a fleeting moment. Though Cézanne’s works outgrew impressionism with its abstract techniques, Monet’s works remained comparably decipherable and photographic. One might compare Cézanne’s works with what Hochstein and Ahissar call vision at a glance, and Monet’s to vision with scrutiny, a prolonged observation and interpretation of a perceived landscape. If “Cézanne’s art was a mirror held up to the mind” (Lehrer, 2008), then “‘Monet [was] only an eye’” (Lehrer, 2008), a lens.

Lehrer writes that “[Cézanne] forces us to see, in the same static canvas, the beginning and end of our sight… The painting emerges, not from the paint or the light, but from somewhere inside our mind” (Lehrer, 2008). Though recent research has since revealed much more about art, visual interpretation, and various other related processes, Cézanne was an anomaly of his time, a painter with a vision that was simultaneously humanistic and scientific.

When photography first developed during the era of impressionism, French painters rebelled because “the camera was a liar… Because reality did not consist of static images. Because the camera stops time, which cannot be stopped” (Lehrer, 2008). I wonder what Cézanne would have thought in my position. Maybe he would have already identified by then the inherent futility in taking the “perfect” picture, or recognized that my disappointment in the photo lay in the inherent dishonesty of photography.

Or maybe Makin and colleagues were onto something when they suggested that symmetry isn’t a necessary condition of beauty. After all, it was the imperfections and the fleeting nature of Cézanne’s fruit and Monet’s flowers that left them floating through my consciousness long after I returned to my apartment. In the end, I guess, beauty is in the eye — and the brain — of the  beholder.


Makin ADJ, Bertamini M, Jones A (2016) A gaze-driven evolutionary algorithm to study aesthetic evaluation of visual symmetry. i-Perception March-April:1-18.

Aviv V (2014) What does the brain tell us about abstract art? Frontiers in Human Neuroscience 8:85.

Hochstein S and Ahissar M (2002) View from the top: Hierarchies and reverse hierarchies in the visual system. Neuron 36(5):791-804.

Lehrer J (2008) Paul Cézanne: The process of sight. In Proust was a neuroscientist (Reprint ed.). pp. 96-119. Mariner.

Image 1 (Lehrer, 2008)

Image 2 was taken by myself.

Love In Paris!

If you know me, you’ll know that one of my favorite films is the French movie, “Amélie” (2001). Set in none other than the charming French village of Montmartre, “Amélie” tells a whimsical story of attraction and love. Once a hub for working-class citizens, Montmartre drew many artists with its liberal reputation. Renowned painters van Gogh, Renoir, and Toulouse-Lautrec were among the many to call the village home (Myers, 2007).

In the film, Amélie works for the Monsieur Collignon at the Café des 2 Moulins, a real location in Montmartre.

I was thrilled to visit the village with a group of my friends. After a few hours exploring, one particular sight remained with me. A gate heavy with love locks — a common sight in the so-called city of love and a symbol of couples’ eternal love. Between the love locks, the cobbled streets, and Le Mur des Je T’aime, my Montmartre, like Amélie’s, spoke of whimsy and love.

Spanning 40 square meters, Le Mur des Je T’aime was created in 2000 and features the phrase “I love you” in 250 different languages. The red fragments represent pieces of a broken heart, and the wall itself represents the capacity for healing through love.

Theories of love have evolved and developed constantly for centuries. Some of us believe in love at first sight. Others, like those who hang their locks upon gates, believe in eternal love. All of us have experienced love in some form or another, whether it be companionate, romantic, or maternal.

One study aiming to answer the question of whether romantic love lasts, observed through functional magnetic resonance imaging (fMRI) that the test subjects, 10 women and 7 men in reported long-term romantic relationships,  exhibited significant brain activity in dopamine-rich areas and areas associated with maternal love when shown images specific to their romantic partners (Acevedo et al., 2012). Responses to long-term partners’ images were measured alongside control images of close friends, familiar acquaintances, and low-familiar acquaintances. Researchers gave participants questionnaires measuring romantic love, obsession, IOS (closeness with one’s partner), friendship-based love, sexual frequency, and relationship length. In short, activation patterns in patients’ brain regions suggested that subjects experienced pleasure when presented with stimuli related to their long-term romantic partners. The ventral tegmental area (VTA), an area of the brain often generally associated with romantic love, showed activation in long-term relationships as well. Interestingly, among activated regions was the posterior hippocampus, an area that seems to activate in response to hunger or cravings (LaBar et al., 2001; Pelchat et al., 2004) — which makes me feel a tiny bit better about my love for ice cream.

While signifiers of romantic love activated dopamine-rich brain areas related to desire, those related to friendship largely activated opiate-rich ones related to pleasure. The study cites a key distinction previously established by researchers Berridge and Robinson, between  “wanting” and “liking,” that positions the two as mutually exclusive. While wanting someone is related to the reward that long-term romantic bonds connote, liking someone is more so an aspect of attachment and pair-bonds. Acevedo and her team wrote that, as a drive, romantic desire is unlike basic emotions in that it is comparatively goal-driven and “hard to control” (Acevedo et al., 2012). They observed that the brains of those in long-term romantic relationships also exhibited significant activity in the opiate- and serotonin-rich areas associated with friendly attachment — activity that is absent from early-stage romance.

Romantic partners attach their locks to this gate in Montmartre to eternalize their love. Love locks are a common sight across Paris.

An article published by Song et al. in 2015 focuses on a similar study that supports the role of romantic love in altering brain architecture, results which align with those of previous fMRI studies (Song et al., 2015). Song et al. acknowledges the work of Acevedo et al. in using fMRI to propose brain regions related and unrelated to romantic love, as well as the work of later researchers (Cacioppo et al., 2012) in dividing these identified regions into those responsible for emotion, reward, and memory, and those responsible for social cues and memory. One weakness of the present study is its longitudinal approach, a model which often resists laboratory control. Song et al. suggest that future research conducted on the topic implement cognitive and behavioral tasks to directly test the hypothesis that love-related alterations of resting brain function reflect an evolutionary drive to select the most fit partner (de Boer et al., 2012). Still, despite its limitations, the study by Song et al. is ultimately valuable because it highlights the function of romantic love.

Ultimately, the study by Acevedo et al. posits that long-term relationships can sustain reward- and value-based brain signals similar to those typically observed during the beginning stages of love, while also fostering the type of “liking” associated with friendly attachment and bonding. In other words, long-term romantic love is possible, and one can love their partner and be their best friend, too.

Of the hundreds and thousands of Parisians and tourists who’ve eternalized their romances on locks upon the fences of Paris, maybe some will succeed. All of us will find love in Paris, whether it be with the city, other people, or life itself. And I can’t wait to find out what comes my way!



Acevedo BP, Aron A, Fisher HE, Brown LL (2012) Neural correlates of long-term intense romantic love. Social Cognitive and Affective Neuroscience 7:145-159.

Cacioppo S, Bianchi-Demicheli F, Frum C, Pfaus JG, Lewis JW (2012) The common neural bases between sexual desire and love: a multilevel kernel density fMRI analysis. The Journal of Sexual Medicine 9:1048-1054.

de Boer A, Van Buel EM, Ter Horst GJ (2012) Love is more than just a kiss: a neurobiological perspective on love and affection. Neuroscience 201:114-124.

LaBar KS, Gitelman DR, Mesulam MM, Parrish TB (2001). Impact of signal-to-noise on functional MRI of the human amygdala. Neuroreport 12:3461–4.

Myers N (2007) The Lure of Montmartre, 1880–1900. Heilbrunn Timeline of Art History.

Paris Convention and Visitors Bureau (n.d.) Le mur des je t’aime. Paris.

Pelchat ML, Johnson A, Chan R, Valdez J, Ragland JD (2004) Images of desire: food-craving activation during fMRI. Neuroimage 23:1486–93.

Song H, Zou Z, Kou J, Liu Y, Yang L, Zilverstand A, Uquillas Fd,  Zhang X (2015) Love-related changes in the brain: a resting state functional magnetic resonance imaging study. Frontiers in Human Neuroscience.

Image 1, Café des 2 Moulins from “Amélie” (2001): Wikimedia Commons.

Images 2-3 were taken by myself.