Brain, Mind, and Cognition

This is your brain on music by Daniel J. Levitin

Essay Joel Edenberg

First of all I think this book could be a lot better if it was presented in a more interactive

format. Majority of the time when I was reading I did not have access to any media player.

So I could not actually listen to the songs mentioned in the text. As a lot of the mentioned

songs where unknown to me, or at least based on the titles, the general understanding of

contexts was probably suffering. An interactive computer version with links to music

samples could offer a lot better overall experience.

But in general I enjoyed the book and found it interesting. It contained a lot of interesting

facts and some pretty unique ideas. Even though I actually have studied music before I found

the explanations in first chapters really helpful. Sometimes the heavy usage of people names

got a bit annoying but other than that it was good.

The most interesting though or idea

I found the explanation why we enjoy the music the most interesting. It made me think

about something I had not thought about before. Why do we like music and what kind of

music we like? Before reading this book I considered this question too abstract to actually

answer. Similarly we could ask that why do you like this specific color or why do you like that

car? The answer seems to lie deep in person’s personality and coming up with a reasonable

explanation seems hard.

The author states that we like music because it plays with our expectations. When we hear

music our brain tries to predict what sound we will hear next. Usually these predictions are

met as the “thing” we call music has to have some kind of structure or sound pattern. But

sometimes those predictions are violated and we hear something unexpected. These

surprises keep our mind interested in the given music.

Now why would we find listening to predictable patterns pleasurable? If we consider the

general concept of how brains work, presented by Jeff Hawkins, we know that predicting is

the core working principle of brain. So our brain is constantly predicting everything that is

happening to us. While performing activities we are constantly improving our predictions as

we get additional information. The initial guesses are often very rough approximations and

end up being changed a lot – refined over time. In general predicting correctly is pleasurable

because our brain has successfully figured out the underlying patterns. We feel good as our

brain has succeeded. But after some time it gets boring and fictional - does not resemble real

life. It seems like an abstract world with ideal concepts. There are no unexpected events to

make the situation more challenging.

Now if we are listening to some very simplistic music all of our predictions are met. In real

life that is never the case. So in order to keep the music interesting there have to be some

violation of expectations. The music has to take unexpected turns to keep us interested. Our

brain is forced to focus more on the music, because it keeps getting the next sounds

“wrong”. It tries to come up with new schemas and patters for describing the sounds it is

hearing but every now and then the model is violated by the music composer.

But why would we enjoy predicting wrongly? Why should we feel any kind of positive

feelings when our brain fails at its core functionality – predicting. I think it has something to

do with the cost of actions. In real world every action we take has a cost. Imagine a person

walking - for every step our brain predicts where to put the feet in order to complete the

next step. Based on the visual information from eyes brain predicts where to place the feet.

Now if this prediction is off by even a small margin (ground is actually lower than we thought

it will be) we are forced to waist a lot more resources - energy. We try to avoid falling down

by using a lot of additional muscles. We use arms to regain the balance, strengthen the

entire body and try to re-adjust the foot position rapidly. So every time our brain

expectations are not met we get penalized with energy loss.

Now listening to music is in some way different. There is no penalty in predicting the next

sounds wrongly. It is like a harmless game where we do not pay any fee for performing

badly. I think this is one of the reasons why we find small anomalies in music pleasurable.

While listening to music our brain does not receive any negative feedback for being wrong.

Based on these ideas we can start to explain as well why people like specific types of music.

The patterns presented to the listener need to be simple enough for recognition but

unpredictable enough to keep the listener interested.

Ideas obtained from the book for building intelligent systems:

Music is closely related with emotions. It can change our mood interact with us. But giving

emotions to machines is probably useless and could even lead to some unwanted results. So

I do not think giving artificial intelligence the ability to understand music is necessary.

Without emotions there is no beneficial value between noise and what we call music. Sure

machine could find patterns in sounds as well but without emotions there is no rewarding

value or purpose for it.

What we could do instead is to learn from our auditory system how to handle sound. The

input of sound is usually very noisy containing a lot of sound sources mixed together. The

problem of identifying sound sources and separating them can be solved by using similar

techniques to how humans do it. For example the distance could be determined by the

volume of sound and the relative position could be determined by comparing 2 sound inputs

from different locations. While even humans have trouble with some specific sound

identification tasks (for example determining whether the sound is coming from front or

from behind) we can use similar solutions to what evolution has come up with. Thanks to

outer ear some higher frequency sounds are cut off if they are received from behind. But if

we cannot predict if those higher frequencies should be present then just slightly turning our

head can identify the position. Closely learning how sound is processed by humans can lead

to new solutions for artificial intelligence.

Also the way how music and songs are stored in our memory could be beneficial to study

and understand. We remember the abstract representation or schema of different attributes

describing each song, but at the same time we can remember specific facts about it (like

lyrics, in what key it starts, tempo, etc.). By recalling one aspect of the song we can recall all

the other variables. This highly intertwined data structure would allow very flexible queries

and data retrieval.

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This is Your Brain on Music: The Science of a Human Obsession

Review by Artem Kaliuk

If you develop an ear for sounds that are musical it is like developing an ego. You begin to refuse sounds that are not musical and that way cut yourself off from a good deal of experience.

John Cage (1912 – 1992)

I do not know many people going for higher education in their thirties. Among those I know (or those I have only heard of) I cannot recall anybody making not just a successful career, but a universally-recognized name in science. This is why Daniel Levitin already seemed to be an interesting person even before I started reading his book. Having provided a detailed overview of a music theory in the first chapters of the book, Professor Levitin steps into discussion of the brain predicting, reacting and delighting us with music.

The theory behind the text lines resembles with the layered prediction-memory framework which Jeff Hawkins introduced in his book (here the top-down and bottom-up cases are explained by top-level and low-level processing, respectively). Accepting the importance of physiological structure of the brain to the cognitive processes, Levitin, however, emphasizes several times on his particular interest in mind as an abstraction of the brain activity. Giving an analogy with software burnt into the hardwired structure, the author tries to see the reasons for feeling and enjoying the music. As before, I disagree with such analogy as software instructs and controls the hardwire, while mind is something that comes out as result of electrochemical (say, physical) activity in the brain. Our minds can be adapted by simply affecting this activity (with drugs or other stimuli), while the software stays either running properly or erroneously due to internal failures or memory damages. Mind is based on the current physical activity and previous experience. I can only accept the notion of software applied to genes: the genetic information which we receive from our parents to some extent defines our temper, preferences and future development. But it is still a rough comparison to a computer program – what we receive encoded in genes does not necessarily define our fate (children having aptitude for music being exceeded by their less-talented but more hardworking fellows is an encouraging example provided by Daniel Levitin).

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Fascinating in this book is:

- that studying music or how the brain works on music allows us to look incredibly farther into the brain than it seems at the first glance. Music proves to be a good test tool involving prediction, emotions and grouping.

- the newly-discovered complementary role of cerebellum. For a long time the oldest part of the brain was thought of as a “control room” for human motions. Now there is evidence that cerebellum also stores the temporal information about the music we are listening to and then it recalls this information when while reproducing the music. Moreover, an amazing fact is that cerebellum was discovered to be a center for emotions;

- categorization. In previous readings we were already exposed to an amazing paradigm of invariant representations in our memory. In This is Your Brain on Music the author explores the idea of invariant memory as a categorization problem. Here we witness a debate between two classical groups of memory theorists – constructivists, who stand for idea of some general low-detail pattern being stored for each experience we encounter, while the details are defined and added later; and record-keepers who insist on storing exact details of each object or event just the way it is done by a tape-recorder. At the first glance constructivism seems to be a way more reasonable approach, but Levitin breaks our expectation by giving examples which prove the two points of view to be both right and wrong. As a result, we are introduced to a new memory theory. Professor Levitin assumes that with multiple-trace memory every experience is stored and, what is more important, can be retrieved and replayed in our minds by “firing the right cue” – a complementary experience (a melody, an odor or a friend’s joke) which we had at this moment. That is why we sometimes laugh when somebody makes a statement which is not funny by its nature (but causes us to fire a neural network storing an inside-joke related to this particular phrase); that is why we want our professors to give us interesting and easy-to-understand examples when explaining a highly-complex theory. The more we access the memory (or, simply speaking, the more we repeat a particular primary experience in a tandem with the complimentary one), the “stronger” the synapses become and the faster the information retrieval will be done. This is already a good motivational example both for chip memory designers (and I believe similar optimization strategies are already implemented) and teachers (to make the students remember things in an easy way. However, education still possesses a huge potential for improvement).

- chapter about emotions. During our previous meetings several times we touched upon the issue of having an artificial mind without emotions. There is a hard-to-observe mechanism behind emotions when we listen to music. However, it was shown that at least three components of the brain are involved into emotional reactions to music

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(amygdala, cerebellum and nucleus accumbens). Even more interesting is to see when we experience pleasure: either when predicting the next piece of music correctly or, when a musician surprises us by violating the structure which we were expecting. Indeed, being a good musician requires not only having the technical skills, but also breaking the patterns to call emotions (why do you think Nickelback is the worst band ever?). Surprisingly, this phenomenon can be discovered in the fields not directly related to music: breaking the clichés (for instance, in product design) is one of the key success factors in business.

Inspiration for building intelligent systems

I am quite sceptical about the idea of creating a silicon chip with a voice of Christina Aguilera (however, mounted on top of a dancing robot, it could be a perfect participant for the Eurovision song contest), so I did not consider any androids for this part. Instead, reading about the categorization for MP3 search engine made me recall some thoughts I had several years ago. The author mentioned problems of finding the versions of the same song by different artists. It could be useful to apply the speech recognition techniques to extract the lyrics of the song. As each artist has a distinct timbre, it would be interesting to analyze the timbre of the voice (in the way humans do) on each uploaded song based on a small fragment and create a category for this particular artist. Based on the recognized text we could now look up for the song “Mr. Sandman”; based on the difference in voice timbres, it will give out versions by different artists.

Creating an artificial auditory system as a functional replica of the human one can be widely used for sensor fusion. Most of the current applications in robotics involve processing visual and vestibular data from cameras and accelerometers. Analyzing the audio data coming from the environment can help significantly when detecting obstacles or moving threats for both human and robot navigation applications (inside the factory building, on the road or even in the air). It was mentioned that visual and auditory systems are the best developed. It would be also interesting to apply similar processing techniques (recall that cortex regions for each sensory system are all of the same structure and functional principle) for haptic interactions and odor analysis.

After all, I cannot restrict myself from the negative emotions I had about the book: Professor Levitin LOVES referring to numerous people he met, talked to, had a drink with or was just ignored by. I consider this constant name-dropping together with a deep excursion into the music theory (which I find much less useless and annoying) to be one of the reasons for my slow progress through some of the chapters (I got simply lost in names and “DAH-dah-ta DUM-dum’s”). Despite that (and the author’s criticism of Frank Sinatra), this book made me think of a music in a different way and it is quite likely that I may read it once again (and I have already recommended “…Your Brain on Music” to some of my friends).

This is Your Brain on Music, by Daniel Letvin

Scott Kenealy

January 7, 2012

1 Introduction

Daniel Letvin’s book,This is Your Brain on Music, is best thought of as a series of essays related to therole of music in the evolution, development, and operation of the human brain. Although it sometimesruns off on self-indulgent tangents (such as the chapter about meeting Francis Crick), the core of the bookrevolves around music’s significance to humans, why we are “programmed” to have a disposition towardsmusic (and certain musical styles over others), as well as what use music serves in other brain functions.

2 Main Point of Your Brain on Music

Pinning the main point of the book down to just one thing is rather difficult, as the book seems to me to becloser to a series of essays involving the brain and music rather than a monolithic whole. I don’t considerthis a bad thing, as the book doesn’t seem to try to present anyunified theory, but rather considers severalfacets individually. That being said, the book seems to focus around three main points: music utilizesa large variety of basic brain functions, it is closely tied to emotion, and seems to be advantageous tosurvival in line with Darwinian natural selection.

2.1 Music and Brain Functions

It is sometimes claimed that swimming is the best exercise one can do, since it requires one to work nearlyevery group of muscles. Music can be thought of as the brain’sanalogue to swimming. In it’s most basicand passive form, it exercises timing functions, matches patterns and makes predictions. Pay a little closerattention, and spatial details, such as the size of the room,become clear. Perhaps you’re listening to JimmyPage of Led Zeppelin play guitar with a violin bow, Thurston Moore of Sonic Youth shoving a screwdriverinto his guitar, or Kevin Shields of My Bloody Valentine shoegazing a wall of sound out of a single guitar,and simply pondering over how such strange sounds could be produced. At the more active end, you maybe engaged in creative pursuits, performing, composing, orengineering music.

It should be fairly obvious that even simply listening to music hones a variety of brain functions.Looking back to Jeff Hawkin’s book,On Intelligence, one is immediately reminded of the themes ofprediction, pattern matching, and invariant representations. Despite the fact that a song can vary greatlyamong live versions, covers, etc., it is not difficult to recognize any of these variations of a song we alreadyknow. Likewise, we expect certain patterns to hold, such as time signature or overall “style”, and can bepleasantly surprised when artists slightly violate these expectations.

Overall, one of the defining factors of music enjoyment is this twist in expectations. Too little variationis seen as boring, while too erratic of a composition sounds incomprehensible. Thus, little children who

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have no real music experience tend to enjoy very simple music, as just noticing the pattern is difficultenough. Casual listening adults expect some variation, and tend to enjoy the semi-stable music of Sinatra,U2, and Metallica, but are turned off by the chaos of The Velvet Underground or Captain Beefheart andhis Magic Band.

The complexity of music is described by the degree to which expectations are broken and also the dif-ficulty of noticing a pattern out of seeming chaos. Variationcan be manifested in a variety of independentparameters, such as tempo, timbre, and pitch. Although I don’t remember it being mentioned in the book,I would assume that the brain regions associated with operations in these domains begin developing ratherindependently, and different experiences result in unequal development of these regions, so a large dealof music’s enjoyment could come from chaos in one domain firmly grounded in the predictable in otherdomains.

2.2 Ties to Emotion

It’s no secret that music, as a form of art, attempts to express that which is difficult to express adequatelyin words. Music in movies sets the tone (fast-paced music during a chase scene), prepares us for what iscoming next (the approaching shark song inJaws), or misleads us (any horror film where suspense is builtout of nothing). Ballads try to go beyond simple statements oflove, while religious hymns express manyof mankind’s deepest hopes and desires.

All of these are closely tied to emotion, and it is generally accepted that any emotions and our perceivedsignificance of an event correspond to one another. Neuroscientists point to the relation of the amygdalaand memory, as well as the evolutionary need for quick responses to dangerous events. When music caneasily be coupled with emotions, it is easy to understand thewidespread significance of music acrosshuman cultures.

This also leads to the interesting effect that as to why we tend to enjoy the music we heard as teenagers.The teenage years are an emotional roller coaster, so it is nosurprise that music is one of the details whichbecome well-preserved in memory from that period.

It does amaze me how well the two are linked, though. For example, I remember driving several yearsago to see my then-girlfriend on a particularly nice day, with a Neutral Milk Hotel album in my car, andjust thinking how happy I was at that time, and now every time Ihear the opening line of the third trackon that album, I not only immediately think of this, but I can remember very specific details, such as thespot on the road where my car was, accurate within a few meters.

2.3 Natural Selection

Since music appears in every human culture, one must gather that it was either advantageous for survival,a byproduct of something advantageous, or universally accepted as a desirable quality in a mate. Letvinseems to lean on the first, but also implies that it may be a combination of all of these factors.

A smarter creature is more likely to survive than a dumber, but otherwise equal, counterpart, and Letvinestablishes earlier that music tends to involve large partsof the brain. Thus, applying music as a form ofmental exercise, it would make sense that those creatures practicing music would more effectively developtheir brains, increasing the odds of survival. Music can also serve for communication purposes, and simpletone patterns may be good substitutes for basic communication, such as yes/no or group hunting orders,so music would be just as necessary to survival as language.

Other scientists claim that music is a spandrel, a byproductof something useful. This probably hassome degree of truth in it. After all, it is not difficult to think of situations in which good recognition

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of timing, pitch, and timbre would be useful to most any animal. Thus, music may simply play on ournecessary natural capacities in such an enjoyable fashion that it managed to easily arise and stick around.

Sexual selection may also be related. Supposing music to be acompletely useless skill, the meremeans to develop such a skill would be indicative of a creature with its more pressing affairs, such as foodand shelter, already so well taken care of that it can squander its efforts elsewhere. In short, it may beequivalent to the peacock tail or the sports car.

I’m no evolutionary biologist, but I’d say that all three have something to contribute. I can think ofsituations in which music would be directly advantageous and of important survival skills indirectly relatedto music. Meanwhile, it’s no secret that successful musicians can sleep with pretty much whomever theywant, so it certainly must play a role in innate preferences in mate search.

3 Application to the Construction of Intelligent Machines

This book struck me as a good extension toOn Intelligence. Like the Hawkins book,Brain on Music wasteeming with ideas related to pattern recognition and prediction. It mainly served to reinforce my faith inHawkins’ ideas.

One thing the music book focused a bit more on is the role of emotion. I’m not exactly sure howone would make some sort of emotion processing unit artificially, but in the human brain, it is critical forsorting the useful from the irrelevant. Perhaps we could build a system very different concept of emotionsthan could serve as an analogue to human emotions; that mightprevent an intelligent system to get caughtup in superstition and flimflam. On the other hand, many of the most important modern conflicts, suchas Israel/Palestine, are incredibly emotionally charged,and I can’t see an intelligent computer coming upwith good solutions to these problems without being able to properly understand the emotional stances ofthe involved parties.

Towards the end of the book, there is a brief comment in passing about mirror neurons, which fire bothwhen observing an action and when performing the action, andare important for learning. Supposing wecan get a brain-like architecture successfully prototypedin hardware, the next biggest challenge will bethe training of such a system. These mirror neurons seem likea good place to look for inspiration.

4 Concluding Thoughts

I found the book to be well thought out and a pleasant enough read, but I’m not entirely sold on the amountof content it held which was relevant to the course. Overall,it seemed much of the important content wasa restatement of the Hawkins book. I listen to a wide variety of music, play a few instruments, can readsheet music, and know basic music theory, so much of the material was familiar, but I imagine to someonewho is not, some of the content was difficult and not particularly important.

Having started on the final book for this class, I’ve noticed that there isn’t a book which focuseson superstition, trickery, or fallacious thinking, but that seems like a highly relevant complement to theHawkins book. On the topic, I’ve only read Michael Shermer’sWhy People Believe Weird Things, but thereare enough books on the topic that I imagine one would be well-suited for this class. Perhaps somethingfrom that field would be a better choice than the music book.

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This is your Brain on Music Thomas Knauer

Throughout the book Levitin is contrasting a prototype theory with an exemplar theory for storing memories. The first concept holds that only an abstract invariant version of the perceived data input is stored. Whereas the second one implies that everything is explicitly saved in a conceptual memory system. Although I personally felt as Levitin opposes the detailed record tape version, at some point he starts doubting. Further he supports his doubts with some examples which show that one is able to recall tiny little details from their past. How is it possible to remember certain details with a simple invariant pattern? He finally holds that:

“… we are storing both the abstract and the specific information contained in melodies. This may be the case for all kinds of sensory stimuli.”

As I was convinced by Hawkins’ idea of using invariant representations retained through patterns in our brain, I stopped thinking about other possible storing mechanisms. But there was one thing Hawkins did not mention in his book, namely how we can recall stored things. Levitin, on the other hand, is promoting the multiple-trace memory model as a possible solution. It assumes that:

“… context is encoded along with memory traces, the music that you have listened to at various times in your life is cross-coded with the events of those times. That is, the music is linked to events of the time, and those events are linked to the music.”

In theory everything we observe is potentially stored and we only need the right cue to recall it. In the authors opinion memory is encoded in groups of neurons and by recreating the required configuration it can be retrieved. Here is where music comes into play, respectively musical pieces. They can give crucial hints in order to remember certain things. Songs, among other sensory stimuli, can retrieve almost forgotten memories.

Let us continue with the mind game that theoretically everything can be remembered by getting the right cue. The ability to remember things then could be maximised by having a unique hint for everything saved on your personal mind hard disk. The obvious problem here is that we have only a limited amount of cues. What I want to point out is that if there are several clues available for one and the same memory cell it becomes easier to evoke it. In addition, along one memory trace other traces can arise and reveal whole memory networks. For this reason thinking about your 10th birthday might remind you of details from your childhood that you had not thought of for a long time. Associating one and the same hint with too many memories, however, can lead to the opposite effect. That is why you cannot use a popular song, which you have heard again and again in different situations, as a cue; since there are too many memory traces having the same source.

To sum up I experienced the discussed topic as being the most interesting one. It was complementing ideas of Jeff Hawkins and brought up some new ideas. However, I still do not feel well informed of how one explicitly recalls memories and how the theatre of minds can be imagined.

Using the knowledge of the book This is Your Brain on Music to build intelligent machines might sound unconnected at the beginning. Interestingly, these research areas have more in common than one might expect.

What is an intelligent device? How do you define intelligent behaviour? And is an intelligent machine supposed to be inerrable? General speaking artificially created intelligence must work properly under all circumstances. People tend to lose their trust in machines if they feel overburdened by their uncontrolled behaviour. Now think in terms of intelligence as an imitation of the human brain, mind and cognition. Incorrect decisions made by humans are simply handled as human failure. Yet hardly anyone mistrusts human confidence. Is that not contradictory? Copying our brainpower but not allowing wrongdoing? In my opinion it is essential to find a trade-off between acceptable errors and degrees of intelligence.

Furthermore, I personally attach importance to the mentioned trust issue.

While I was working as a student trainee at the Institute for Data Processing my supervisor was doing research in the field of Trust between Cognitive Vehicles. This provided me with some insight information in this area and taught me how difficult it is to define trust in an abstract way. Once a sophisticated framework is established the next challenge is to teach how trust, reputation and other factors can be combined and adjusted by participants of a trust network. One main approach was to find out how fast wrong information spreads out within a mesh for different trust implementations.1 This leads to the origin of trust, namely security. Sometimes it feels like while rushing from one achieved success to another we forget about the new created potential for hackers and other bad guys to manipulate and misuse intelligent devices. Thus I think that more attention should be paid to this topic as its importance will even increase in the future.

A representative for trust in combination with intelligent devices is how to

decide which source of information is most reliable if there are multiple sources available. Another concrete example is to consider trustfulness in terms of the possibility to influence or obscure either the device itself, the way of data collection by sensors, or, as mentioned before, the data origin.

Much of what we perceive contains missing and obscured information. Thus it

is necessary to implicate the environment when creating intelligent procedures. One and the same intelligent device probably performs different outside than inside which can lead to unexpected behaviour. In fact, miscellaneous surroundings affect the

1 http://mediatum.ub.tum.de/doc/997457/997457.pdf

data we are receiving with our set of sensory organs. Since our brain is steadily adapting to the given environment it seems that our sensation is working somewhat independent to it. On that account, for example, we usually do not need to understand every single word in order to understand a sentence. For working out the message two steps are required. The first one is to readjust the organs to the ambience and the second one is to fill in the occurring gaps. How we can use this for our purposes is discussed in the following.

I would like to introduce one approach which is performing with a perceptual system that can restore information. The basic idea is to create a multi sensory perception system with a parallel working feature extraction. The features are calculated independently and the outputs are continuously updated. The main task of a multidimensional framework is to support the detection of the desired information. The following paragraph will illustrate the discussed concept.

Think about creating a device for detecting fire and setting of a fire alarm. The

most common concepts are using smoke detectors to become aware of an emergency. Now this system can be expanded to a more sophisticated multi sensory arrangement by adding an infrared camera and a microphone. The IR camera can be used to identify fire pockets before enough smoke is produced in order to activate a smoke detector. The sound pick-up can be used to extract fire specific sounds. All of them are working independently. An intelligent device can be trained to react properly in different situations as it comprises and controls all of the extracted information. With this concept it would be possible to distinguish between a case of emergency and a simple candle light. Further it would work faster and more reliable than present systems and could help to reduce false alarms and would thus provide more safety. The predicting aspect for this system is that, for instance, the sound of an explosion or a new unusual source of heat could be compared to previous happenings or predefined patterns and with its result corresponding actions can be operated.

Levitin holds that it is a tricky issue to categorise things with a specific scheme. He tries to define characteristics of a typical bird; having wings, being able to fly and being monogamous. Further he is asking whether or not a penguin fits into this definition. It does in some ways, but it is very far from the stereotype. Indeed, there are approximately 8,800 species of birds. With this and some other examples he points out that it is not always possible to draw a strict line between categories in order to satisfy all cases. Most of the time, however, it is not necessary to take all individual cases into consideration. A limited number of possible input data can reduce the possible outputs. With this knowledge, instead of using a simple Fast and Frugal Tree approach, it could be more accurate to use an overlapping and modified prototype theory where one object can be part of several categories, as it was proposed by Lakoff2.

2 http://www.tu-chemnitz.de/phil/leo/rahmen.php?seite=r_wiss/steffen_hecke.php

This  Is  your  brain  on  Music  The  science  of  a  human  obsession                                              Eric  Lambers    At  one  point  of  reading  this  book  –  I  asked  myself  why  is  Mr  Levitin  even  searching  for  answers?  Is  he  trying  to  create  music  that  will  affect  people  psychologically,  or  he  is  he  just  innately  curious?  I  think  the  latter.  Whilst  he   does   not   aim   to  map   the   brain   and  what   happens  where,   he   is  more  concerned  with  the  how  and  why  things  happened  in  the  brain  as  a  direct  result   from   listening   to   music.   Many   of   the   ideas   that   he   refers   to,   or  studies   that   he   has   personally   conducted,   are   quite   interested.   With  respect   to   the   brain,   he   talks   about   how   the   brain   is   different   in   people  who   are   accomplished   musicians   compared   to   the   average   layperson.   I  forget  which   part   of   the   brain   is   enlarged,   but   he   refers   to   a   part   of   the  brain   that   can   grow   to   be   larger   through   practice,   and   that   musically  inclined   people   do   actually   have   different   brains   to   tone   deaf   karaoke  singers  like  myself!      To  be  critical  at  the  same  time  the  book  drags  in  with  a  seemingly  infinite  number   of   explanations   and   analogies   that   had   me   losing   interest   very  rapidly   in  what  he  had   to  say.  However  his   ideas  were  quite  stimulating,  once   again   the   topic   of   invariant   representations   is   fundamental   to  listening  to  music,  and  how  we  can  so  easily  remember  a  song.    I  find  this  aspect  of  music  and  our  brains   to  be   the  most   interesting  concept  of   the  book.   I   myself   have   problems   remembering   names   of   songs   (or   even  people   for   that   matter),   but   I   can   remember   tunes   and   recognise   tunes  (and   people   similarly)   with   ease.   I   can   remember   basic   chord  progressions,  when  the  pitch  should  increase  or  decrease,  and  many  other  factors.   The   way   in   which   music   is   stored   in   my   brain,   as   invariant  representations  is  quite  accurate.  I  can  recognise  a  familiar  song  whether  it   is   played   on   a   different   instrument,   with   a   different   pitch,   loudness,  tempo,   even   rhythm.   The   brain   is   so   well   adapted   to   making   these  connections  that  our  intelligence  goes  far  beyond  that  of  computers.      The   case   of   labelling   mislabelled   songs   on   people’s   MP3   databases   was  simple   for   a   computer   to   rectify   –   as   easy   as   scanning   a   barcode   at   a  supermarket.  However  this  is  far  from  intelligence.    Computers  struggle  to  identify   music   if   it   is   slightly   different,   in   any   way.   Be   it   a   cover   band  (which  is  highly  recognisable)  or  simply  a  faulty  set  of  speakers  that  do  not  reproduce   hi-­‐fi   sounds,   computers   are   in   no   way   at   the   same   level   as  humans  for  listening  to  and  distinguishing  sounds.      From  reading  this  book,  music  has  become  something  so  much  more  than  pleasing   sounds.   The   psychological   processes   involved   are   not   simple  processes,  such  as  sound  waves  reaching  the  ear  >  converted  to  electrical  signals  >  simple  emotional  response.  Different  pitches  fire  in  your  brain  at  

specific   frequencies,   different   processes   occur   for   every   song.   Music   is  something  amazing  that  has  been  evolutionarily  developed  from  (I  would  now   like   to   agree   with   Darwin)   mating   ceremonies   in   primitive   human  populations.   Music   is   used   in   Australian   Aboriginal   tribes   to   tell   their  history,  the  Old  Testament  used  to  be  orated  to  hymn  music  –  music  also  helps  to  remember.  It  is  not  a  mere  ‘parasite’  of  communication,  for  I  think  it   is   too   intertwined  with   communication   to   call   it   a   parasite   –   they   are  almost  one  and  the  same.  Music  communicates  emotions,  and  in  that  way  it   is  a  medium  for  story  telling.  Listen  to  song  lyrics  that  you  hear  on  the  radio  –  it  is  a  story.  Shitty  teen  music  is  an  exception,  with  terrible  music  such  as  Rebecca  Black’s  “Friday”  (lyrics  go  along  the  lines  of,  “should  I  sit  in  the  front  seat  or  the  back  seat”,  as  if  it  is  some  sort  of  moral  dilemma  –  it  is   a   truly   painful   song   to   listen   to).   Whilst   Levitin   mainly   focuses   on  listening   to   music   in   regards   to   emotional   reactions,   I   think   playing   of  music  is  also  an  outlet  for  many  people.  A  lot  of  very  popular  music  stars  have  consequently  committed  suicide  –  and  my  personal  explanation  may  be  a  bit  off  line  –  but  it  is  my  opinion.  I  think  that  some  musicians  play  and  compose  music  to  free  themselves  from  negative  emotions,  and  sometimes  that   can  be   too  much   for   them,   leading   to  drug  and  alcohol   abuse,   along  with   other   problems.   As   such   I   think   that   music   is   a   highly   psycho-­‐emotional   concept   that   can   be   pleasing   to   most   people,   either   playing  music  or  listening  to  it.      The   emotional   attachment   to  music   is   also  quite   interesting   to  me.   I   can  personally  think  of  several  songs  that  will  always  bring  memories  flooding  back  into  my  mind.  One  of  Bruno  Mars’  songs,  about  catching  a  grenade  for  lover,   will   forever   remind   me   of   driving   around   British   Columbia   in  Canada.  It  was  forever  overplayed  on  the  radio,  and  will  always  remind  me  of  the  positive  memories  of  cruising  around  on  road  trips  with  mates  to  go  skiing.  I  am  sure  that  I  will  also  have  songs  from  my  time  here  in  Germany,  such   as   Fliegerlied,   and   Living   Next   door   to   Alice   –   from  Oktoberfest   of  course!  Without  music  in  those  instances,  my  memories  would  be  so  much  less  than  what  they  are  for  me  mentally.      So  what  can  be  taken  from  Daniel’s  research  and  to  be  used   in  reality,   to  somehow  better  our  society,  and  how  people  act  and   feel?   I   find  his   idea  about  personal  radio  stations  to  be  quite  interesting.  He  mentions  towards  the  end  of  the  book  that  in  the  near  future  personal  radio  stations  may  be  a  reality.  A  station  that  is  fine  tuned  and  manicured  over  time  to  ensure  that  it   plays  music   according   to   an   algorithm   of   one’s   personal  music   tastes,  their  openness  to  new  styles  of  music  –  all  leading  to  what  could  be  termed  a  ‘perfect’  radio  station.  What  goes  beyond  this  notion  of  a  personal  radio  station  is  that  there  is  an  element  of  control  that  can  be  extracted  from  the  algorithm  that  selects  music.    Since  Levitin  has  proved  through  evidence  in  his  novel,  different  kinds  of  music  and  sounds  make  different  parts  of  the  

brain   fire,  and  encourage  different  hormones   to  be  released   in   the  brain.  Dopamine,   for  example,   to  relax  people,  has  been  found  to  be  released  in  the  brain  when  certain  music  is  listened  to.  On  a  side  note,  even  as  I  write  this   essay,   I   listen   to   classical   music,   as   I   believe   it   calms   and   helps   to  generate  clarity,  especially  in  times  of  mental  writing  blanks!      Levitin  explains  that   the  emotions  we  experience   from  listening  to  music  arise   from   the   prediction   models   inside   our   brain,   that   happen  subconsciously.  He  says   that   if  a  song   is   too  predictable,   it   in  effect   ‘over  satisfies’,   and  provides   little   stimulation.  But  when  a   song  requires  more  complex  prediction  models  within   the  brain,  when  expectations  are  met,  the  brain  rewards  itself  with  emission  of  certain  hormones.  He  even  says  that   when   composers   go   against   these   predictions,   our   brain   can  sometimes   also   enjoy   these   variances   as   a   way   for   the   brain   to   ‘work  harder’  to  accurately  predict  the  next  chord  progression.      This   automated   intelligence   could   be   quite   an   important   program   to   be  developed   in   the   near   future.   Personally,   I   do   not   take   the   time   to  download/buy  music  that  I  like  and  to  install  it  upon  my  iPod,  categorise  it  into  playlists  and  favourites  –  all  on  top  of  having  to  carry  an  iPod  around  with   headphones.   I   find   it   too  much   of   a   nuance,   and   I   do   prefer   just   to  listen  to  a  radio  station  that  has  an   infinite  number  of  different  songs,  as  well  as  the  radio  stations  that  are  known  to  always  play  those  classic  hits!  I  think  that  is  it  not  beyond  the  realm  of  computer  intelligence  to  eventually  arrive   at   a   point   in   time  when   it   is   able   to   simulate  music   according   to  preferences   in  rhythm,   tempo,  groove,  beat  –  many  different   factors.  As   I  have   commented   in  my  previous   rambling   essays,   I   think   that   there   is   a  fine  line  that  should  not  be  crossed  by  computer  intelligence  that.   I  think  that  human  input  is  still  required  and  should  not  be  eliminated  from  music  especially!    The  human  component  of  music  is  quite  integral  –  the  emotions  conveyed  by  a  human  through  singing,  or  playing  music  can  send  clear  messages  to  the   listener.   Levitin   alludes   to   this  when  he  mentions  Frank  Sinatra,   and  how  all   his  music  post  1980  was   sung  with   the   “satisfaction  of   someone  who   just  had  someone  killed”  or  along  those   lines.  However  pre  1980  he  sang  with   passion   and   strained   every   note   in   a   specific  way   in   order   to  create  different  emotions.    

My  Thoughts  on  “This  Is  Your  Brain  On  Music“  

By  Marius  Loch  

Intro  

Daniel  J.  Levitin  started  his  career  as  record  producer  and  sound  engineer  while  being  a  musician  himself.  He   later  turned   into  a  neuroscientist  specializing   in  music  perception  and  cognition.   In  his  book  “This   Is  Your  Brain  on  Music:  The  Science  of  a  Human  Obsession“(2006)  he  combines  the  fields  music  and  neuroscience  to  give  an  overview  to  the  layperson,  exploring  the  connection  between   the   subjects.   After   an   introduction   to   some  musical   basics   (which   reanimated  many  forgotten  memories   from  my  high  school  music  classes)  he   talks  about  why  we   like  music  and  what  we  like  in  music  (much  is  about  fulfilling  and  violating  expectations)  and  why  we  like  what  we  like  (we  mostly  acquire  our  musical  taste  in  our  childhood).  In  the  later  chapters  he  discusses  musical   expertise,   always   stressing   the  point   that   everyone   is   somehow  an  expert   in  music   as  there  are  different  kinds  of  expertise.  The  last  chapter  is  about  where  music  comes  from  from  an  evolutionary  point  of  view.  

Fluid  and  crystallized  intelligence    

Another   memory   from   my   time   in   high   school   was   evoked   when   Levitin   writes   about  categorization  and  how  our  music  memory  works.  In  my  philosophy  class  (in  the  book  cognitive  psychology  is  referred  to  as  “empirical  philosophy”)  in  11th  grade  we  had  a  guest  speaker:  Prof.  G.  Curio,  a  neuroscience  professor  from  Charite  Berlin.  He  gave  a  class  about  freedom  of  will  and  within  talked  about  the  difference  in   intelligence  between  young  and  older  people:  he  claimed  younger  people  have  a  “fluid  intelligence”,  enabling  them  to  quickly  pick  up  new  skills  and  solve  problems.   Adults   on   the   contrary   have   a   “crystallized   intelligence”,   they   have   a   structured  framework  of  knowledge  based  on  experience  and  prior   learning;   it  becomes  more  difficult   to  pick  up  things  in  a  new  field,  but  easier  to  apply  existing  knowledge  or  to  classify  objects  within  our  developed  framework.  I  remember  how  I  liked  the  idea  how  we  developed  a  structure  of  our  world  and  sort  new  information  into  that  structure.  

This   correlates   to  much   from   Levitin’s   book.   In   the   chapter   “Anticipation”   he   tells   us   how  we  build  our  frameworks:    “An  important  way  that  our  brain  deals  with  standard  situations  is  that  it  extracts  those  elements  that  are  common  to  multiple  situations  and  creates  a  framework  within  which   to   place   them;   this   framework   is   called   a   schema”   (p.115).   He   claims  we   have  musical  schemas  as  well  for  all  kind  of  things:  styles  and  eras,  certain  bands,  artist  and  genres,  covering  rhythms,  chords,  typical  motifs  and  sequence,  etc.  -­‐  we  learn  what  the  “legal  moves  in  the  music  of  our  culture”  are.    The   author   also   describes   how   these   schemas   are   developed   mostly   in   our   youth:   we   start  already   prenatal,   in   the   womb   of   our   mothers.   By   the   age   of   two   children   start   to   show  preference   towards   the  music  of   their   culture   (p.  230),   then   the  age   ten   to  eleven  becomes  a  turning  point  when  all  children  start  to  care  about  music,  even  those  who  didn’t  care  so  far  (p.  231).   The   most   influential   period   is   the   age   around   fourteen   when   teenagers   start   their  “emotional  self-­‐discovery”  and  use  music  as  social   identification  (p.  231).  By  the  age  of  twenty  

the  brain  is  mostly  “finished”  and  it  becomes  seemingly  more  difficult  to  learn  new  skills  (p.  233)  –  also  our  framework  for  music  is  mostly  set.    This  framework  (and  the  containing  schemas)  describe  how  we  think  music  has  to  be  and  what  its   “legal  moves”   are   –   these   are   our   expectations   towards  music.   As   the   author   goes   on   and  points   out   several   times   in   the   book,  we   like  music   that   fulfills   our   expectations,   but   violates  them  every  now  and  then:      “The  thrills,  chills,  and  tears  we  experience  from  music  are  the  result  of  having  our  expectations  artfully  manipulated  by  a  skilled  composer  and  the  musicians  who  interpret  that  music.  […]  The  setting  up  and  then  manipulating  of  expectations  is  the  heart  of  music.”    If   it   is   too   simple  we   perceive   it   as   boring;   if   it   is   too   complex  we   can’t   find   any   structure   or  familiarity   and   don’t   like   it   (p.   235).   The   terms   simple   and   complex   of   course   depend   on   our  framework  and  how  advanced  it  is  in  a  particular  style  or  genre.  

This   correlates   well   to   Prof.   Curio’s   description   of   fluid   and   crystallized   intelligence.   In   our  childhood  we  use  our  fluid  intelligence  and  pick  up  the  rules  of  our  cultures  music.  The  music  we  listen  to  in  that  time  shape  our  understanding  of  what  music  is  and  what  to  expect  of  it.  By  the  time  we  become  adults   these  expectations  represent  our   taste   in  music.  We  don’t  “learn”  any  more  new  music   (unless  we  actively  strive  to  do  so),  but  we  apply  our  crystallized   intelligence.  We  listen  to  music  and  try  to  fit  it  into  our  framework  and  based  on  that  decide  whether  we  like  it  or  not.  

Memory-­‐prediction  framework  with  multiple-­‐trace  memory  

In   chapter   five   where   memory   and   categorization   are   discussed   the   author   describes   one  problem:   it   is   easy   for   a   computer   to   “recognize”   a   song   by   look   up.   But   it   is   very   difficult   to  recognize   two   different   versions   of   the   same   song   by   comparison.   “The   brain   does   this   with  ease,   but   no   one   has   invented   a   computer   that   can   even   begin   to   do   this.”   (p.   135)   he  immediately   gives   a   reason   in   the   next   sentence:   ”This   different   ability   of   computers   and  humans  is  related  to  a  debate  about  the  nature  and  function  of  memory  in  humans.”  

As  scholars  of  Jeff  Hawkins  “On  Intelligence”  this  rings  a  bell  of  course,  memory  as  a  crucial  part  of  an  intelligent  system.  There  are  more  parallels:  Hawkin’s  intelligent  system  as  memory-­‐based  prediction  system  corresponds  perfectly  to  the  human’s  perception  of  music.  Build  a  frame  work  in  memory  by  pattern  recognition,  predict  what  comes  next  and  be  alert  (or  in  the  case  of  music  pleasurably  surprised)  if  the  prediction  wasn’t  quite  correct.  When   we   then   read   Levitin’s   description   of   tune   recognition   the   parallel   is   complete:   “Tune  recognition   involves   a   number   of   complex   neural   computations   interacting   with   memory.   It  requires   that   our   brains   ignore   certain   features   while   we   focus   only   on   features   that   are  invariant  from  one  listening  to  the  next—and  in  this  way,  extract  invariant  properties  of  a  song.”  (p  133).  The  abstraction  of  invariant  features  is  also  a  central  theme  in  Hawkin’s  book.    In  other  words  Levitin’s  description  of  how  we  perceive  music   reads   like  a  manual   to  Hawkins  intelligent   machines.   So   exploring   the   “debate   about   the   nature   and   function   of   memory   in  humans”  (see  above)  seems  like  a  good  point  to  help  with  building  intelligent  systems.    

In  this  discussion  two  views  are  introduced.    One  is  the  constructivist  theory  (relational  memory),  claiming  the  brain  only  stores  “relations  between  objects  and   ideas,  but  not  necessarily  details  about   the  objects   themselves”   (p.  135).  This   implies  we  actually  construct  our  memories  every  time  we  access  them  and  details  are  more  of  a  sophisticated  guess.  The  second  view  is  the  record-­‐keeping  theory  (absolute  memory),  claiming  memory  stores  most  our  experience  accurately  and  in  detail.  Unfortunately  there  is  a  lot  of  evidence  for  both  theories.  An  easy  and  intuitive  example:  every  one  of  us  will  recognize  a  song  we  know,  even  if  it  was  transposed  by  some  tones.  We  will  also  recognize   it,   when   it   is   played   faster   or   slower   than   the   original.   This   would   support   the  constructivist   theory,  as   the  different  versions  are   identified  by  the  relationship  of   the  sounds.  On   the   other   hand   everyone   will   notice,   when   a   song   is   played   different   to   a   famous  performance  like  a  radio  version  listened  to  all  summer  long.  In  fact  most  people  will  not  only  be  able  to  tell  the  difference,  but  be  able  to  reproduce  the  famous  version  (as  far  as  their  musical  means  will  allow).  This  supports   the  record-­‐keeping  theory,  as   it   requires  absolute   information  about  a  certain  performance.    One   interesting   aspect   that   comes   up   in   the   discussion   about   the   two   memory   systems:  apparently  we  rely  on  sequences  to  memorize  music.  Most  humans  and  even  expert  musicians  can’t  evoke  the  memory  of  an  arbitrary  moment   in  a  song.   If  we  want   to  remember  a  specific  part,  we  have   to   scan   the   song   from   the  beginning  or  another   significant   landmark  within   the  song.   Levitin   concludes:   “This   suggests   that   our   memory   for   music   involves   hierarchical  encoding—not   all   words   are   equally   salient,   and   not   all   parts   of   a  musical   phrase   hold   equal  status.  We  have  certain  entry  points  and  exit  points   that  correspond  to  specific  phrases   in   the  music  […]”.  Another  two  important  keywords  from  Hawkins  book:  sequences  for  memorization  and  applying  a  hierarchy.    As  a  solution  to  the  two  conflicting  memory  systems  the  author  introduces  a  hybrid  theory:  the  multiple-­‐trace   memory.   According   to   this   theory   we   store   specific   (absolute)   information   as  record-­‐keeping  would  suggest.  Furthermore  it  is  suggested:  “As  we  attend  to  a  melody,  we  must  be  performing  calculations  on  it;  in  addition  to  registering  the  absolute  values,  […]  we  must  also  be  calculating  melodic   intervals  and   tempo-­‐free   rhythmic   information   […]  creating  a  pitch-­‐free  template   […]   in   order   to   recognize   songs   in   transposition.   […]   [This]   suggest[s]   that   we   are  storing  both  the  abstract  and  the  specific  information  contained  in  melodies.”  As  this  theory  claims  to  preserve  the  context  of  a  memory,  it  would  explain  how  we  link  music  to  certain  situations  in  our  live  and  how  listening  to  a  song  can  conjure  the  memory  of  a  forgotten  event  far  in  the  past.    So   we   saw   how   closely   linked   the   perception   of   music   in   the   sense   of   Daniel   Levitin   is   to  intelligent  machines  in  the  sense  of  Jeff  Hawkins.  A  key  feature  of  both  seems  to  be  the  human  memory   system.   Therefore   Levitin   introduced   the   multiple-­‐trace   memory   theory   somewhat  combining  the  record-­‐keeping  and  the  constructivist  approach  by  storing  absolute,  but  also  on-­‐the-­‐spot  calculated  (abstracted)  information.  Maybe  a  further  development  and  analysis  of  this  memory   system   could   –   applied   in   computer   systems   –   deliver   a   breakthrough   for   intelligent  machines.  

This Is Your Brain on Music The Science of a Human Obsession

Alexandra Marinescu Brain, Mind and Cognition

“We are [...] under the illusion that we simply open our eyes and we see. A bird chirps outside the window and we instantly hear. Sensory perception creates mental images in our minds – representations of the world outside our heads – so quickly and seamlessly that it seems there is nothing to it. This is an illusion. [...] Our perceptual system is supposed to distort the world we see and hear. We naturally assume that the world is just as we perceive it. But experiments have forced us to confront the reality that this is not the case.” Normally, while reading a book, I have to underline specific passages of text, which I find of great importance, passages that somehow say and mean more to me than the rest of the book, passages that manage to change my beliefs or the way I understand my surroundings, the environment I live in. The quote above did more than that. I had to write it down, I had to think about it. Underlining it wasn’t enough anymore. So the world isn’t what we perceive it to be. Everything we see or hear or touch or even taste is just a mental projection of the real world. I found myself thinking about a normal day in my life starting with the moment I wake up in the morning and start “seeing”, perceiving my surroundings. And I surprisingly got stuck at this point, since my first thought was about the daylight. If what we perceive as “light” is only a mental image, the response of our brain to the sensory perception of an oscillation, can it be that there is no “light” at all? It seems that the human brain assigns a “label” to everything he processes, based on the different categories he “learns” over time. And if we also recall the beliefs of E. Rosch, we can also understand why something can be “more or less a category member; rather than being all or none as Aristotle has believed, there are shades of membership, degrees of fit to a category, and subtle shadings”. Our sensors perceive “light” and we think of it as a “day”, or “dark” and we know that the “night” has come. We perceive something in between the two categories, neither a “day” nor a “night”, so we it must be either a dawn or a sunset. But then again, these are only mental images. “Light”, as we perceive it, may indeed not exist. The “day” is just the label we gave to a category of sensory data our brain processes. One might jump to the conclusion that we live in the dark, but that cannot be true, since “dark” is also just a label.

I kept reading the text passage again and again and couldn’t get to a conclusion. I tried to find answers in the book, but instead I found only further questions and text passages to write down. For example this one: “Perhaps the ultimate illusion [...] is the illusion of structure and form”. So not only does our world look, sound and feel differently as we all perceive it, now it also doesn’t have a structure at all! It seems that we make sense of the world depending only on the environment we grow up in, on the things we learn over the years, on our experience. To sum up, we do see “light” or “dark” instead of a certain wavelength, or a “bed” or a “table” instead of the individual atoms they are made of. They might not exist in the real world as we perceive them, but that doesn’t make them, in my opinion, unreal, just different. We see a bunch of organized, oscillating particles and assign them a label based of the categories we learned over the time; we are the ones giving a structure and a sense to our world by interpreting our sensory perceptions. How can the knowledge obtained from the book be used for building intelligent machines? I strongly believe there is still a very long way we have to go before building truly intelligent machines. I also believe that we will not be able to do that unless we have an understanding of how the brain really works. Unless scientists come up with a theory that manages to provide a unitary answer to the raised questions, no breakthrough will be made. The book of reference may not make a breakthrough, but it most certainly introduces an entirely new point of view in studying the brain, by considering music and its effects. So what if we learn how to endow robots with emotion from the brain’s perception on music? “Tempo is a major fact in conveying emotion. Songs with fast tempos tends to be regarded as happy, and songs with slow tempos as sad. [...] In order to be moved by music (physically and emotionally) it helps a great deal to have a readily predictable beat. [...] Music communicates to us emotionally through systematic violations of expectations. As music unfolds, the brain constantly updates its estimates of when new beats will occur, and takes satisfaction in matching a mental beat with a real-in-the-world one, and takes delight when a skillful musician violates that expectation in an interesting way”. For a robot isn’t, of course, a trivial task to react emotional to the different violations of their expectations, with these “expectations” being nothing else but a probabilistic model based on the training data they were given.

But when interacting with people, this could take a totally new turn. People do react differently when interacting with machines, compared to the times when they are dealing with fellow humans, mostly because they know that such machines don’t share the same internal structure – reactions, emotions, thoughts – as they do. But if we were to apply on machines what we learned from music, robots would be able to give rise to emotions only by violating the expectations of the humans. By adapting the tempo and the timbre of their “voice”, robots should be therefore able to communicate different emotions to the people they are interacting with. Of course, this is yet another way of tricking people into thinking that robots are truly endowed with emotions. It still doesn’t represent a step forward in building truly emotional robots. Another big constraint is, of course, the “mind”. “For cognitive scientists, the word mind refers to that part of each of us that embodies our thoughts, hopes, desires, memories, beliefs and experiences. The brain, on the other hand, is an organ of the body, a collection of cells and water, chemicals and blood vessels, that resides in the skull. Activity in the brain gives rise to the contents of mind. [...] Different programs can run on what is essentially the same hardware – different minds can arise from very similar brains”. I do want to believe that there is more to us than an evolved brain. I refuse to believe that “this feeling – the self – could be an illusion, just as it certainly feels as though the earth is standing still, not spinning around on its axis at a thousand miles per hour”. And for this reason I also strongly believe that robots will remain just “hardware”; they might get to have the intelligence of a human brain, but they will never have a “mind” – “the self”.

Audrey Pedro

This Is Your Brain On Music from Daniel Levitin

12/01/2012

Daniel Levitin is interested in music (he works as a music producer) and in particular

in how music is processed by the human brain in order to understand why is music such a

big deal for most of the people. His book This Is Your Brain On Music presents his theory

and researches’ results on the topic.

Two points were to me particularly interesting in this book, the first one because of

personal experience and the second because of its power. What I found very impressive in

this book due to personal experience is the theory about how music tastes are created.

Indeed I always found it very funny that people stay so attached to the music they were

listening in their youth and when they are listening to it they become the young person they

were almost instantaneously. This phenomenon can very easily be observed in wedding for

example.

Here Daniel Levitin gives an explanation: as a language or any other learned skill,

music structures are acquired without too much effort in the youth. The parallel made with

language was the one that spoke to me. Young children are able to learn a language without

any grammar lessons and so on: they just ear it and memorize what other say. Then they

build language structures and become “native” speaker which means they master the

language with no much effort. In comparison to older people learning a new language the

way young children become “expert” in their mother tongue is astonishing. For music it is

exactly the same: until a certain age learning new structures is very easy and then it

demands some effort. Yet this learning ability decreasing with age has nothing so illogical but

what I found interesting is the combination with the fact that people do like music if they are

familiar to its structure. When I read that I was surprised, it means then that new songs we

like are just similar to other songs we already like, boring no?

Actually not so much because as Levitin explains the same structure allows many

variations (music has many components that can be changed: pitch, rhythm, timbre…) and

the known frame is just a “safety” for the listener. This idea impacted me because of personal

experience (it is even an example used by Levitin about Latin music). I grow up with a

Colombian mother who was listening to salsa, merengue, beguine and other Latin music. I

now appreciate this kind of music very much and I love dance on it but it is very difficult for

me to find dance partners and to put my music on parties. Worst I have the impression that

people don’t get the difference between salsa and merengue when I can hear it since the first

notes . Well reading the page concerning that (241 in my edition) was a relief. I finally know

why I feel so alone when listening to Latin music.

I must admit that this book was the first I was not so enthusiastic to read. First of all

the beginning was very technical in music and I think that knowing what pitch, timbre, meter

and loudness are do not help for enjoying music listening. As Levitin says the “expert”

language is too complicated and creates a separation between musicians and other people

which first was not always there and then is not necessarily justified. I’d like to come back to

the parallel with languages: native speakers are able to detect very easily if a sentence is

correct or not but in general they do not know the grammatical rule violated. Concerning

music, people can appreciate music without naming everything. I was hoping that after this

chapter the book would become more interesting but I was disappointed. I did not manage to

get really in the book before chapter 6 and it is now difficult to synthetize ideas about what I

read before this chapter. Chapter 6 gets my attention by presenting what I felt like the core

idea of the book: how music experience is anchored in the reptilian brain and how it calls the

emotion region of the brain (amygdala).

“Music is an art from whose medium is sound and silence”, definition of music from

Wikipedia mentions the music as an “art” and it is the most common definition. Art belongs to

the evolved human skills about just creating aesthetic for itself without any vital need

underneath. But in his book Levitin explains that music is something managed by the older

part of the brain, a region we have in common with reptilians such as snakes and that this

region makes the link between music experience and strong emotion reactions. The reptilian

brain allows us to protect ourselves: it normally manages inputs that lead to strong emotion

reactions in order to make us act without thinking too much in dangerous situations. When

we feel burning for example, the reptilian brain will immediately transmit that we have to run

away from fire to save our live and the amygdala is the medium used to make it quick. So

here the theory seems contradictory: how an art can be managed by a region dealing with

vital needs? Levitin explains how music isn’t just an art but an evolved skill still being an

instinct (see chapter 9).

The music-as-an-instinct theory is very satisfiable concerning the main question of the

book “understanding a human obsession” or why is music such a big deal in all societies and

cultures known. It is not just an art but an instinct that we still have and this explains why

mothers sing to their babies to calm them down and why dance is considered as something

so erotic / intimate.

This leads us to the second part of the essay concerning what would be useful in this

book if I was working on an intelligent machine. This book is not so easy to use for building

intelligent machines since the author does not mention any theory about intelligence in

general but focuses on music. Nevertheless understanding music can be considered as a

part of human intelligence.

The first point mentioned above about structures learning and recalling them is an

interesting track. An intelligent machine could learn to build structures in order to apprehend

other unknown things when the structure is similar. This ability could be useful for other

domains of learning (mathematics, linguistic…). This characteristic corresponds to a

synthesis ability. It joins the theories of the two previous books that a frame of memorized

known structures that can be adapted to new situations is the basis of intelligence.

This common point emerging from the three first books confirm that intelligence

probably rely on it. Intelligence is the adaptation of known frames to the unkown.

Brain, Mind and Cognition Nadja Peters

Daniel Levitin – This Is Your Brain On Music 09-01-2012

What’s your opinion of the most interesting thought? Where did the book give you inspiration for building intelligent systems and what is your inspiration? Why is it sometimes so hard to remember all the interesting things one is supposed to learn in class? Even though the professors try to teach us in the most passionate way (at least let’s assume that for now), most people have a hard time understanding (e.g. math) and remembering facts (e.g. differences between programming languages or computer architectures). On the contrary it is quite easy to remember non-relevant things like the number of marriages of your favorite actor or the number of goals your soccer team achieved in the last season. Such facts are usually very interesting, but they do not at all help us passing the upcoming exams. So why are facts, which we need to learn to move on in our careers, much harder to remember than unnecessary details about our favorite athletes? As Daniel Levitin tells in his book “This Is Your Brain On Music”, we need special cues to retrieve memory from our brain (Chapter 5, You Know My Name, Look Up The Number). He also tells us that the more passion is related to a memory, the more likely we will remember it. So how can we possibly add as much passion to remembering “boring” things as to things we are really interested in? Usually the problem is not about the content of a class being boring (at least this SHOULD not be the problem, although one never finds every subject equally interesting), but the problem is about sitting down and start learning, memorizing. Although one has acquired more knowledge and has a great chance to pass exams after doing some successful learning process, it still involves a lot of stress and pressure. As shown in the statistics, many people are not able to keep up with that kind of pressure and simply quit their studies (to keep things correct: being under pressure is of course not the only reason to quit studies but in these days it is becoming more and more relevant2).

.

0 5

10 15 20 25 30 35 40 45 50

Students giving up university1

Brain, Mind and Cognition Nadja Peters

Daniel Levitin – This Is Your Brain On Music 09-01-2012

As this is a topic which is important for every one of us, it is interesting to find ways to improve this situation and bring more joy into the lives of stressed students. But how are we supposed to improve this situation? There are different possibilities:

1. Take away the pressure from student 2. Find methods of learning that are so effective that the student feel comfortable 3. Find methods of relaxing that restore the students psychological condition

Possibility one is definitely the easiest one. Taking away the pressure can be done by simply making the classes less challenging. As that is usually not increasing the esteem of a university the pressure could also be taken away by increasing the number of semesters that a student need to achieve a degree. As we are studying brain, mind and cognition we will not go the easy way but try to figure how we can use our knowledge to develop solutions for possibilities two and three. So how can we manipulate the neurons in our brain to make learning more effective and how can we manipulate them to make ourselves feel comfortable and relaxed (without using drugs or similar)? As Daniel Levitin points out, for remembering things we need certain cues. A cue can be compared to a key to a door. When one possesses a certain key, that person can open a special door in one’s brain and get access to the information lying beyond. Levitin also says that memories which involve certain emotions can be remembered easier by our brain. How can we use this knowledge to stimulate our brain? How can we create some sets of mnemonics for certain topics and fill those with emotions, so we can remember them most effectively? In this case effectively means that one uses the smallest amount of time possible for learning but can remember the things for a long period of time. Moreover learning should not be tight to sitting at the desk and staring at formulas all over again but involve some kind of actions that make it more comfortable. But how can we achieve that something a person does not like is actually fun? To go with Levitin we could pick some music that makes us feel good and listen to it before learning. Every time we feel bad we can turn it on and get some positive emotions out of it. At this point, I would like to cite my favorite quote: “Repetition, when done skillfully by a master composer, is emotionally satisfying to our brains, and makes the listening experience as pleasurable as it is,” (Chapter 5, p. 167). But is it really enough to stimulate our neurons with some really good pieces of music? As we have learned, the brain is of versatile structure. So what happens if we listen to some pieces of music that we like and then do something else we do not like? In my opinion the stimulation will lose its effect because the structure of the neurons will adapt after some time and the association we have with a certain piece of music will change. We cannot even compare music to drugs although many people like to do this: If someone takes drugs, that person will simply increase the dose to get satisfied, but if we increase the dose of music we do not like anymore, it will probably make us feel worse and8

Brain, Mind and Cognition Nadja Peters

Daniel Levitin – This Is Your Brain On Music 09-01-2012

frustrated. So in my opinion to keep the positive effect of music we should not use it to make us happy before doing things we do not like. After some time it will not work anymore. We found out what probably will not help us learning more effectively, but what is it that WILL? What we need for a good strategy is not only a good set of cues and some emotions make the cues more effective but we also need to repeat the things we want to remember all over again. Repetition is, besides understanding the context, the most important clue to remember things. But what is able to get stuck in our minds by being repeated all over again and being pleasant as well? In our everyday lives, most of us are listening to music most of the time. We can remember a lot of songs and even sing along to a lot of songs? What if we do not sing along to lyrics sung by Michael Jackson or Elvis Presley but create our own songs, songs we use to memorize things we have to learn for an exam for example? What if professors would create songs and record their lessons? So we would not only buy scripts by the beginning of the semester but also some recordings to listen to on our MP3 players while going to university in the mornings. After some time we could sing along and remember all the lessons simply by humming the melody of the song. Sure, this method cannot save us from solving difficult math equations but in most cases doing practical exercises is not half as boring as memorizing things. Doing learning sessions could get another meaning if students simply met in a club and started dancing and singing to the lectures. As Levitin says in his book, the ability to make music and being affected by music is natural to us because it is determined by our genes (Chapter 9, The Music Instinct). So when we want to build intelligent machines, what kind of genes do we need? What are we supposed to tell it so that it can function properly? Stephen Jay Gould is of the opinion that music is nothing that we developed to survive, but that it is a by-product by other functions as language. What happens if our intelligent system developed some by-products that we did not want it to develop? Whenever we design a system we want to be in control of that system. How can we be sure that intelligent systems do not develop their own mind? By their own mind I do not mean, that they decide to take over planet earth because they are of the opinion that human kind is not able to control the system properly. What if they simply make mistakes? Actually, it would be normal, because making mistakes is human, but how can we trust in a machine that drives our car in the wrong direction, for example? Maybe we could create a machine that records lessons at university and automatically converts them to songs we can listen to. Those machines would not harm our lives by making mistakes. I really do think that listening to songs instead of simply sitting at your desk and staring at a book would improve our learning performance and make the learning process more enjoyable but who would actually transform the content of a lesson into a song and record it? There is not only need in people who actually do know the subject but other people who can do the performance. Although the effort seems quite large on the first glance, I would love to test that method of learning. ______________________________________________________________________________ 1 Das Studentenportal, Studienabbrecherstudie, 2005, http://www.studserv.de/studium/statistik.php (access: 05-01-2012) 2 Nina Zimmermann, Studenten unter Druck, 2008, http://www.spiegel.de/unispiegel/studium/0,1518,569612,00.html (access: 05-01-2012)

Written Discussion on Daniel J.Levitins ”This Is Your Brain On

Music”

Martin Reverchon

January 9, 2012

1 What is in your opinion the most interestingthought/idea?

Being only an ‘expert listener’ and unfortunately having no visible talent in be-ing an ‘expert performer’ this book made me joyfully think about how music andsounds affect us in our daily life. My roommate is a clarinet student at the Uni-versity of Music and Performing Arts Munich and therefore we tend to talk a lotabout music in general (and I certainly did bombard her with a lot of questionsabout the little of music theory we were taught in the book). However, I by myselfnever made a connection between music theory and our brain. Therefore, I wasespecially surprised by the – in hindsight relatively obvious – fact that music andsound like any other perceptional sense we have constantly affect the state ourbrain and each individual neuron in it.

Stimulating electrodes deep inside the brain begin to unfold their potential.Depth-electrodes can cure Cluster-Headaches, muscular spasms or obsessive com-pulsive disorders. Patients who washed their hands hundreds of times daily cannow again lead a normal life. With the help of depth-electrodes it was even possi-ble to awaken a patient who was in coma for six years.

I have recently heard about a neuro-technology called ‘controlled reset’ (CR R©).In brain regions that are affected by a certain type of diseases with symptoms oftremors and tinniti often lack sensory input that influences the state the affectedset of neurons is in. Without this input it is possible that these cell assembliesfall into a self-induced state of mutual pathological synchronisation – of whichthe above mentioned symptoms stem from. Without the input it is impossible todesynchronize the afflicted neuronal areas. This is the point where neuro-implants

1

come into play. An electrode is surgically inserted into the patients brain. Firingat specific frequencies the electrode is able to weaken and ultimately desynchro-nize the synchronous firing of the neurons resulting into the relief of the malady.

Surprisingly it was found that in certain cases where a proportion of the visual– or in this case auditory – nerve was still intact, no surgical operation is neces-sary. Presenting the patient a sound pattern similar to the electrodes impulsesresulted into the cure of the symptoms, too! This is another very good exampleof how sound affects us. Since all of the above mentioned therapies with depth-electrodes work, is it possible to affect our brain by mere presentation of audio orvisual patterns to cure these sicknesses? Could it be an even more powerful tool?

Music is able to lift our mood, bring us down, soothe our temper or enrage us.As shown above it might even cure cerebral illnesses. I think it would be greatif we found the principles in how exactly music and sounds affect our brains. Ifwe could wield that power like a scalpel ’surgical’ non-invasive sound therapiescould be used to cure or relieve a wide variety of mental or structural cerebral ill-nesses. It could be used to put us in several desired cerebral states. May that bea soothed state for patients with bipolar disease or excitement and agitation forlethargic people. It is even thinkable to reach some kind of transhumanism viasounds and music. We could put ourselves into states where we are able to per-ceive the world better, where we are able to learn quicker and, on the other hand,where we can erase unwanted memory (if this is desirable is of course a broad eth-ical discourse).

2 Where did the book give you inspiration forbuilding intelligent systems and what is yourinspiration?

I recently had the chance to visit ACE in its lab. ACE stands for “AutonomousCity Explorer”. The ACE–project envisions to create a robot that will autono-mously navigate in an unstructured urban environment and find its way throughinteraction with humans. To achieve this, research results from the fields of au-tonomous navigation, path planning, environment modelling, and human-robotinteraction are combined. However, on first sight I have to admit that I felt a bitfrightened by its appearance. Besides its bulky built and its massive jaws thatlook like they could easily crack a coconut it had a red antenna wiggling in a snake-like way on its head (which is used to point in different direction – a pretty use-less feature as it turned out, I was told by the researchers). Being asked for direc-tions by this clunker I’d rather change the side of the sidewalk than help this odd

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penguin-shaped massive monstrosity. Designing a more appealing shape for thisrobot will certainly wield a higher acceptance during human-robot interaction.But the right set of sounds could also be employed to make a valuable positivefirst impression, when this robot approaches humans in order to fulfil its objec-tive. Moreover, during all situations where human-robot interaction is necessarythe right choice of a comforting voice can set a positive mood for human-robot in-teraction. However, this does admittedly not lead to intelligent machines. It mayjust change the way we look at robots and intelligent systems.

Gerd Gigerenzer stated in his book ”Gut Feelings” that a specific intelligentsystem – I suppose a neural network of some kind – was able to learn speech if itwas presented with only simple sentences. I wonder if this was possible for music,too. Could an intelligent understand music if we presented it with simple chimeslike commercial jingles, simple enough for a toddler to hum. Advancing over a bitmore complex music like minimal music to big symphonies a structure similar tothose that are processing our speech could emerge. Would a similar neural net-work be able to learn the basics of pitch, rhythm, tempo, contour, timbre, meter,key, melody and harmony like the different cues of speech; grammar, vocabulary,syntax, semantics and prosody?

Taking Daniel J. Levitins approach of looking at the brain under the influenceof music could be adapted to analyse the behaviour of neural networks. This wouldnot only help in the field of research of neural networks. With the achieved in-sight in neural networks we could also get more knowledgeable about the impactof sounds and music on the brain on a functional level.

There are two remaining big questions in this world. The first one is ”Howdid the universe into existence”. The second one is ”How does our brain work”.Achieving an understanding of the brain on both, the functional and the behaviourallevel, would bring us closer to a solution for the latter problem. Thus, applyingmusic to several different aspect of brain research on a biological and a techni-cal level can be of great interest. This gets even more clear if look at one of Lev-itins statements in the book: “Cosmides and Tooby argue that music’s function inthe developing child is to help prepare its mind for a number of complex cognitiveand social activities, exercising the brain so that it will be ready for the demandsplaced on it by language and social interaction.”. Taking this as an analogy forthe development of technical system, I think that a similar approach could bearfeasible results.

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Tudor Timisescu

Report on the book “This Is Your Brain on Music”

1. What is the main point of the book according to your opinion?

With the book “This Is Your Brain on Music”, the author, Daniel J. Levitin, intends to familiarize the reader with basic aspects of musical theory, related to the various aspects of musical perception and interpretation, with the way all of these aspects are processed by the human hearing apparatus and the brain and with how they all fit it together to create emotions and impressions inside the mind.

Music is composed of a large palette of elements, such as pitch, rhythm, tempo, contour, timbre, loudness, reverberation, meter, key, melody and harmony. All of these elements come together to create a specific impression on the listener. That we can distinguish between a note played on a piano and the very same note played on a clarinet or if a piece of music is played in a small cramped room or a big concert hall is nothing short of miracle, the author believes. Human perception is far more advanced than any of today’s fancy computer algorithms and will be for much longer.

All of these individual elements are processed in different regions of the brain, from areas of the neocortex, to the cerebellum (the oldest part of the brain), to the amygdala (the part of the brain that deals with emotions). This last connection reinforces the profoundly emotional role that listening or playing music has. The music processing “machine” follows the layered approach proposed by Hawkins in his book “On Intelligence”.

Seeing as how music has a very big emotional charge linked to it, memories that are associated with musical passages also share this charge. This helps them to be better remembered, even in extreme situations like those of Alzheimer’s disease patients.

Music has a natural flow to it. Sounds coming at us without any structure to them will only be perceived as noise. It is the structure of musical passages that give music its “sound” and “feel”. Anticipation of what will come next in a musical piece is key to what the listener feels. We have all experienced the feeling that while listening to a particular passage of music we have never heard before we still kind of know what will come up next. Sometimes though, these anticipations are violated and a sort of inner turmoil is created. It is through a mix of these two states that good music is made: if a piece is too predictable, then it becomes boring; a piece that is too unpredictable sounds foreign. The way composers create these mixes is what separates the skilled ones from the novices.

Although too simple pieces of music (children’s songs for example) are indeed boring, complicated music is not necessarily good music. Very often, you will find a great deal of proficient players, who can play notes at lightning speeds without making any mistakes, but their playing sounds bland and boring. It is the ones who can transmit the most emotion that are the most successful (as if pouring their soul into their music) and the human mind is very good at telling these ones out.

Many studies have been done to determine the impact of nature vs. nurture in musical ability. There is no clear evidence either way. Some people tend to think that musical talent is something that only some people possess. They give as examples musically inclined families. This argument, though, can be countered with the positive reinforcement argument: children that grow up in such families are more likely receive positive reinforcement for pursuing musical activities and will be much more inclined to continue to do so. There is also a theory stating that there is a certain minimum of practice anybody needs in order to become an expert in a certain field (ten thousand hours). According to this theory, anyone can become an expert as long as he or she spends this much time honing his or her skills. Such an argument can also be countered by the fact that different people progress at different rates. As it is with most everything, the truth is probably somewhere in the middle.

The final chapter of the book is devoted to the evolutionary aspect of music. The questions on researchers’ minds are why and how did musical ability develop in humans. The author challenges one of the major theories of human evolution saying that music is simply a by-product of other evolutionary traits such as speech and did not evolve separately. He proposes a theory in which music serves a central role in early human mating, much as it does for some species of birds. An individual who can spend effort on such a “useless” skill such as playing music is surely pretty well off, demonstrating a high degree of intellectual and/or physical prowess.

2. How can the knowledge obtained from this book be used to create intelligent machines?

This book’s main focus is on musical perception, interpretation and, to a lesser extent, playing. My view is that the quest to build intelligent machines is nowhere near the state of building machines that should be concerned with any of these aspects, as there are far more other aspects that have to be addressed first (just making a machine actually be able to hear for example).

Maybe in the far future, machines that can play music and musical instruments might get built. In order to play music, they will have to be able to understand music, which is where some of the ideas in this book could come in. To what degree these machines will be successful compared to human players remains to be seen (see the argument above about conferring emotion).

Another suggestion of where machines might take over is in any application that requires song recognition. An example is the licensing agency where operators must monitor airplay of songs. Algorithms for song recognition exist (the author himself worked in the field), but are nowhere mature enough to fully replace humans, most probably because they don’t consider too many aspects of the song being analyzed.

Yet another application for musically trained machines is in personalized radio stations. I have used a similar service like this in the past and it was pretty good (most of the times), although I’m guessing it worked based on previous categorizations of songs by human operators. Machines that can perform this categorization automatically or even emulate a user’s preferences would be a step forward.

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Essay “This Is Your Brain On Music”

by Daniel Levitin

From Georg Victor

Introduction

The book “This Is Your Brain On Music” from Daniel Levitin is all about how music and your brain,

respectively your mind, are connected. The author is quite an interesting character, who started as a

musician, became a producer and started his academic career late in his life, compared to the majority

of scientists.

Since he never was an engineer and he never touched the topic of artificial intelligence, not during his

academic work and neither in the book this essay is about, there are much less connections to AI than,

for example, in the first book of the course, “On Intelligence”, by Jeff Hawkins.

Still, there are many ideas the two books share: Equality and consistency, for example. Also Daniel

Levitin states in different parts of the book that all sensory input is processed in a similar way. Also

talents or expertise in completely different fields is formed the same way: roughly 10,000 hours of

practice is necessary to become an expert – no matter if we talk about scientists, athletes, artists, etc.

Main Point

On the other hand there is one fundamental discrepancy between the theories of Hawkins and Levitin:

the way our brain stores memories. Hawkins’ book is good for telling us how the neocortex is organized

and how we can build a system simulating the way we think – and with that, intelligent machines. This

book, “This Is Your Brain On Music”, gives us a suggestion on how to organize the memory in an

intelligent way.

The author describes the two leading theories and how none of the two is completely right. In a very

convincing way he points out the strengths and weaknesses of each theory. The first one is called

“constructivist”. Like Hawkins describes it in his book, we humans only store the essential relations of

objects, experiences, etc. Since that, it is possible to e.g. recognize a song, even if it is distorted in one

or many ways. The second theory, called “record keeping/tape recorder”, lacks an explanation for this.

It says that all the details of our input are preserved and only lost due to normal biological processes.

But isn’t this what we also experience each and every day, that we remember exact details of

something? Levitin calls many examples, e.g. the one experiment where people remembered the exact

pitch of their favorite songs. This experiment is particular good because Hawkins, who simplified many

things (deliberately to get a streamlined, easily understandable book that gives a consistent theory

about how our brain works – the “Memory Prediction Framework”), stated that we just store the

relative change of pitch of a song, not the pitch itself.

Daniel Levitin develops an approach that combines the both theories in a new way. I would summarize

this approach as based on

Georg Victor Essay on “This Is Your Brain On Music“

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Hierarchical, prototype-based, context sensitive, dynamical categories

The author did not come up with this theory. Eleanor Rosch is a professor of psychology at the

University of California, Berkeley. She did her undergraduate thesis of her philosophy study about

Wittgenstein. Later on she quit with plain philosophy and finished her Ph.D. at Harvard with the

fundamental thesis about categories.

(A) Categories are formed around prototypes.

A category, e.g. “fruit”, contains several attributes, e.g. peaches, bananas, etc. But each

category contains one prototype. For “fruit”, this could be apple for most of us Europeans.

We divide the world into basic level categories that include as much as possible attributes.

The size is limited by the second principle of sharing as few as possible members with other

categories.

(B) These prototypes can have a biological or physiological foundation;

If we take the “fruit” example: Of course in other cultures, where there are no apples

available, there will be another prototype for this category. If the category even exists,

since categorization itself is of course culture, time, etc. dependent. Prototypes can also be

promoted by physiological facts, e.g. the anatomy of our ears.

(C) Category membership can be thought of as a question of degree, with some tokens

being “better” exemplars than others;

“Better” means here more “privileged”. How privileged a certain item is, can be estimated

by these three experiments:

Response Times Prototypes are elected faster in queries than non-prototype members

Priming Participants got triggered with a certain category. For prototypes, they

identified faster, if two words are the same (“apple – apple”), than for other items

Exemplars When participants are asked to name items of a certain category,

“better” (more privileged / typical) items are named more often

(D) New items are judged in relation to the prototypes, forming gradients of category

membership; […]

An interesting fact is that in some experiments of Rosch, she found out that we even make

up prototypes. In one experiment she showed distorted pixilated images to the

participants. These images were varying only a little bit from the “prototype” image. A

week later, they were shown again the images, now including these prototypes. A huge

percentage thought that they saw the prototypes before. So whenever we sense a new

item we ask ourselves (unconscious): how good does it relate to the (real or made-up)

prototype? for each category.

(E) There don’t need to be any attributes which all category members have in common,

and boundaries don’t have to be definite.

The borders of any category are not strict. Also, objects (attributes) can be the member of

more than one category.

Georg Victor Essay on “This Is Your Brain On Music“

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How can this idea help us building intelligent machines?

If we start asking the question from above, we only have to look at ourselves and our everyday live to

find the many advantages and surprising things we can achieve with the memory we have.

Of course there is the size of the memory. Nobody knows the exact number but Paul Reber, professor

of psychology at Northwestern University, states that we can keep information with an approximate

equivalent of 2.5 Petabyte. Sure, there are already supercomputers with this amount of storage

capacity and what’s now huge will be found in personal computers in the near or middle future. Still, I

find this number stunning. It can only be achieved by the very organization of how we store

information. The brain uses the relation of objects, respectively sensory input - it does not store every

tiny aspect.

But much more than the sheer size of it is the organization and how it allows us to react in new

situations, how we interpret new sensory input. In the end it is this organization that really makes us

able to think the way we do. We can classify objects within seconds. We can distinguish easily if

different sensory input belongs to one entity or to different objects. Certain triggers bring back dozens

of memories, associations, and similarities with past events within fractions of a second. We can group

new experiences into the right cluster of familiar experiences and understand a lot through our

memory. We can even predict the future through our past – at least partly. All of these points are until

now extremely hard to implement into machines and computers.

Personal Opinion

I personally quite liked reading the book. Unfortunately I started reading it too late (after New Year’s

Eve…) so I had some time pressure and could not fully appreciate all the aspects of it. Still, it gave me a

good understanding of how complex the affects of music on our brain are and how deep it is involved in

our evolution.

It is funny to read that Darwin was “equating music with the peacocks’ tail.” But isn’t that what we are

all thinking? That the guys playing the guitar or singing in a cool band (thus having the biggest tail)

always get all the girls? Now I finally have the scientific evidence. It has to be like that. No reason to get

intimidated or insecure. Fortunately the author points out many other peacock tail categories we can

choose from, if we are bad musicians: luxurious items, extensive dancing, general display of fitness, etc.

So there is hope for everyone!

It made me a little bit sad, or should I say frustrated, that Levitin states several times how our brain-

development is finished more or less with the beginning of our twenties. How difficult it is to learn

completely new things when we did not develop the brain structures before this time of your life. How

determined your preferences are. I mean, of course I know all of these, I heard it before. I don’t believe

we can invent ourselves completely new just if we want it. But to read it over and over again black on

white is quite depressing, isn’t it? Thank you, Daniel Levitin

Anyway, the thing that made me stop crying is what the book is all about: music. Levitin names so many

different bands and tells anecdotes about different artists that I started to listen to a lot of new music

while reading this book. I started to appreciate music and my Nubert loudspeakers, my Yamaha AX-497

even more than before. Thank you, Daniel Levitin