Monthly Archives: March 2015

Music affects on the brain

A recent paper identified genes that changed their expression as a result of music performance in trained musicians. (see citation below). There were a surprising number of affected genes, 51 genes had increased and 22 had decreased expression, compared to controls who were also trained musicians but were not involved in making or listening to music for the same time period. It is also impressive that this set of 73 genes has a very broad range of presumed functions and effects in the brain.

Another interesting aspect is the overlap of a number of these genes with some that have been identified in song birds. This implies that the music/sophisticated sound perception and production has been conserved from a common ancestor of birds and mammals.

It has been known for some time that musical training has a positive effect on intelligence and outlook – that it assists learning. Musical training changes the structure of the brain. Now scientists are starting to trace the biology of music’s effects. Isn’t it about time that education stopped treating music (and other arts for that matter) as unimportant frills? It should not be the first thing to go when money or teaching time is short.

Here is the Abstract:

Music performance by professional musicians involves a wide-spectrum of cognitive and multi-sensory motor skills, whose biological basis is unknown. Several neuroscientific studies have demonstrated that the brains of professional musicians and non-musicians differ structurally and functionally and that musical training enhances cognition. However, the molecules and molecular mechanisms involved in music performance remain largely unexplored. Here, we investigated the effect of music performance on the genome-wide peripheral blood transcriptome of professional musicians by analyzing the transcriptional responses after a 2-hr concert performance and after a ‘music-free’ control session. The up-regulated genes were found to affect dopaminergic neurotransmission, motor behavior, neuronal plasticity, and neurocognitive functions including learning and memory. Particularly, candidate genes such as SNCA, FOS and DUSP1 that are involved in song perception and production in songbirds, were identified, suggesting an evolutionary conservation in biological processes related to sound perception/production. Additionally, modulation of genes related to calcium ion homeostasis, iron ion homeostasis, glutathione metabolism, and several neuropsychiatric and neurodegenerative diseases implied that music performance may affect the biological pathways that are otherwise essential for the proper maintenance of neuronal function and survival. For the first time, this study provides evidence for the candidate genes and molecular mechanisms underlying music performance.”

Kanduri, C., Kuusi, T., Ahvenainen, M., Philips, A., Lähdesmäki, H., & Järvelä, I. (2015). The effect of music performance on the transcriptome of professional musicians Scientific Reports, 5 DOI: 10.1038/srep09506

Recommended video

This link has a series of interviews with prominent neuroscientists (Haggard, Smith, Koch, Greenfield, Martin, Hameroff, Theise). “Does brain make mind” is a good watch.

Free Will has lost all meaning

A headline got me going and the summary got me laughing, “Even worms have free will.” ScienceDaily has the item (here) on a paper about reactions of a worm to odors (A. Gordus, N. Pokala, S. Levy, S. Flavell, C. Bargmann; Feedback from Network States Generates Variability in a Probabilistic Olfactory Circuit; Cell, 2015)

This is not just any worm that has free will, it is C. elegans, a microscopic worm whose brain is completely known, all 302 neurons and their few thousand connecting synapses. Each neuron has a name and has been individually studied. Most of the little networks in the tiny brain have been studied to some extent. What can they mean when they say that C.elegans has free will? “If offered a delicious smell, for example, a roundworm will usually stop its wandering to investigate the source, but sometimes it won’t. Just as with humans, the same stimulus does not always provoke the same response, even from the same individual.

So it appears that free will can be ascribed to anything that is not completely predictable. Until, that is, it is understood enough to be predictable. But no, it does not even have to be unpredictable. They appear to have an understanding of the little 3 neuron web that controls whether the worm stops at an odor. “We found that the collective state of the three neurons at the exact moment an odor arrives determines the likelihood that the worm will move toward the smell.” So it appears that anything that can do more than a single thing when triggered with a particular stimulation, has free will. I think that would include all living things and a good many inanimate things too. Weather seems to fit the bill.

I hate to be pedantic but why use the phrase ‘free will’ with a meaning that is not remotely related to its philosophical meaning or its legal meaning. It either means that a choice is made outside the brain in some spiritual mind or it means that a choice was made consciously and carries attached responsibility. It should not be reduced to a meaning like: a worm will stop for a smell or go on depending on the state of 3 of its neurons. If sensory information is going to have only one effect on motor action, we do not need a brain at all; the sensory neurons can connect directly with the motor neurons with no need for other neurons in between. C. elegans may have a very small brain but it is a brain and it’s function is to nuance behavior – not a surprise when it does.

Here is the abstract, unlike the press release, it is very reasonable and does not mention free will:

Variability is a prominent feature of behavior and is an active element of certain behavioral strategies. To understand how neuronal circuits control variability, we examined the propagation of sensory information in a chemotaxis circuit of C. elegans where discrete sensory inputs can drive a probabilistic behavioral response. Olfactory neurons respond to odor stimuli with rapid and reliable changes in activity, but downstream AIB interneurons respond with a probabilistic delay. The interneuron response to odor depends on the collective activity of multiple neurons—AIB, RIM, and AVA—when the odor stimulus arrives. Certain activity states of the network correlate with reliable responses to odor stimuli. Artificially generating these activity states by modifying neuronal activity increases the reliability of odor responses in interneurons and the reliability of the behavioral response to odor. The integration of sensory information with network states may represent a general mechanism for generating variability in behavior.


New method - BWAS

There is a report of a new method of analyzing fMRI scans – using enormous sets of data and giving very clear results. Brain-wide association analysis (BWAS for short) was used in a comparison of autistic and normal brains in a recent paper (citation below).

The scan data is divided into 47,636 small areas of the brain, voxels, and then these are analyzed in pairs, each voxel with all other voxels. This gives 1,134,570,430 data points for each brain. This sort of analysis has been done in the past but only for restricted areas of the brain and not the whole brain. The method was devised by J. Feng, University of Warwick, Computer Department.

This first paper featuring the method shows its strengths. Cheng and others used data from over 900 existing scans from various sources that had matched autistic and normal pairs. The results are in the abstract below. (This blog does not usually deal with information on autism and similar conditions but tries to keep to normal function; I am not a physician. So the results are not being discussed, just the new method.)

A flow chart of the brain-wide association study [termed BWAS, in line with genome-wide association studies (GWAS)] is shown in Fig. 1. This ‘discovery’ approach tests for differences between patients and controls in the connectivity of every pair of brain voxels at a whole-brain level. Unlike previous seed-based or independent components-based approaches, this method has the advantage of being fully unbiased, in that the connectivity of all brain voxels can be compared, not just selected brain regions. Additionally, we investigated clinical associations between the identified abnormal circuitry and symptom severity; and we also investigated the extent to which the analysis can reliably discriminate between patients and controls using a pattern classification approach. Further, we confirmed that our findings were robust by split data cross-validations.” FC = functional connectivity; ROI = region of interest.

The results are very clear and have a very good statistical probability.

Abstract: “Whole-brain voxel-based unbiased resting state functional connectivity was analysed in 418 subjects with autism and 509 matched typically developing individuals. We identified a key system in the middle temporal gyrus/superior temporal sulcus region that has reduced cortical functional connectivity (and increased with the medial thalamus), which is implicated in face expression processing involved in social behaviour. This system has reduced functional connectivity with the ventromedial prefrontal cortex, which is implicated in emotion and social communication. The middle temporal gyrus system is also implicated in theory of mind processing. We also identified in autism a second key system in the precuneus/superior parietal lobule region with reduced functional connectivity, which is implicated in spatial functions including of oneself, and of the spatial environment. It is proposed that these two types of functionality, face expression-related, and of one’s self and the environment, are important components of the computations involved in theory of mind, whether of oneself or of others, and that reduced connectivity within and between these regions may make a major contribution to the symptoms of autism.

Cheng, W., Rolls, E., Gu, H., Zhang, J., & Feng, J. (2015). Autism: reduced connectivity between cortical areas involved in face expression, theory of mind, and the sense of self Brain DOI: 10.1093/brain/awv051

Adaptive forgetting

We know that memories are changed by up-dating details, consolidating similar memories, and forgetting some altogether. In a recent paper, researchers have shown that forgetting a memory can be due to recall of other memories (citation and abstract below). Remembering a memory enhances that memory but can suppress similar memories that interfere with its recall. This ‘adaptive forgetting’ strengthens often recalled memories and causes forgetting of interfering memories.

The New York Times has a report on this paper (here) giving details of the method.

Wimber and others, using scans and pattern analysis were able to observe the activity of memories in the visual cortex. First the subjects were trained to associate words with unrelated pictures – each word was associated with two different pictures. Then they were given a word and asked to remember the first picture they were trained to associate with that word. The pattern analysis showed the extent of the pattern for the first picture and for the second picture. This trial was repeated several times amongst other trials. The pattern for the first picture grew stronger over the repeated trials and the pattern of the second picture grew weaker. To see what had happened to the second picture, the subjects were shown each picture along with a similar one and asked which picture they had been trained and tested on in each pair. They knew the correct first picture but not had more trouble identifying the correct second picture – in other words, the memory of the word and second picture association was being destroyed.

This has implications for witness testimony after repeated questioning – the questioning may have destroyed some memories by adaptive forgetting. It also weakens the theory that memories are not forgotten but overlaid and hidden by newer memories.

Here is the abstract of the paper (Wimber, Alink, Charest, Kriegeskorte, Anderson; Retrieval induces adaptive forgetting of competing memories via cortical pattern suppression. Nature Neuroscience, 2015) “Remembering a past experience can, surprisingly, cause forgetting. Forgetting arises when other competing traces interfere with retrieval and inhibitory control mechanisms are engaged to suppress the distraction they cause. This form of forgetting is considered to be adaptive because it reduces future interference. The effect of this proposed inhibition process on competing memories has, however, never been observed, as behavioral methods are ‘blind’ to retrieval dynamics and neuroimaging methods have not isolated retrieval of individual memories. We developed a canonical template tracking method to quantify the activation state of individual target memories and competitors during retrieval. This method revealed that repeatedly retrieving target memories suppressed cortical patterns unique to competitors. Pattern suppression was related to engagement of prefrontal regions that have been implicated in resolving retrieval competition and, critically, predicted later forgetting. Thus, our findings demonstrate a cortical pattern suppression mechanism through which remembering adaptively shapes which aspects of our past remain accessible.

Could this have anything to do with the urban myth about the professor who complained that every time he remembered a student’s name, he forgot the name of another fish?

The BBC report: “Dr Wimber told the BBC the implications of the new findings were not as simple as a “one in, one out” policy for memory storage. “It’s not that we’re pushing something out of our head every time we’re putting something new in. The brain seems to think that the things we use frequently are the things that are really valuable to us. So it’s trying to keep things clear - to make sure that we can access those important things really easily, and push out of the way those things that are competing or interfering.” The idea that frequently recalling something can cause us to forget closely related memories is not new; Dr Wimber explained that it had “been around since the 1990s“.

This probably is only be one of the ways we forget our memories.


Meta-memory surprises

There was a parlor game that was played when I was young. Something in the room would become the focus of attention. Maybe a calendar picture would be remarked on and a short discussion of the picture would follow. The trick was to get people to look carefully at the picture. Then the person who was fooling the rest would suddenly tell everyone to close their eyes and ask them if they thought they could remember the picture. A number of questions are asked of whoever is very confident: how many clouds in the sky?; how many windows in the house?; is the spout of the teapot to the left or right?; what colour is the vase with the flowers in it? The amusement was that the confident person often could not answer the questions.

What about something really simple? Researchers (see citation below) used the Apple logo. They found that people were confident but could not remember the logo well enough to draw it accurately. It is seen so often and is not a thing that has to be distinguished for similar images, so we remember the general gist of it but not the details. Myself, I thought I had drawn it correctly, but no, my leaf touched the apple, and my bite was on the wrong side. There are three things here. Do we remember well enough to: recognize something, reproduce the details of something, have confidence in the memory of it? Most people are very confident, moderately good at recognizing and hopeless with the details. However, we can remember detail if we need to (that seems to me an efficient strategy).

The researchers also make an interesting observation. “However, in naturalistic settings there is probably no intent to encode the details of the Apple logo, leading to an interesting dissociation: Increased exposure increases familiarity and confidence, but does not reliably affect memory. Despite frequent exposure to a simple and visually pleasing logo, attention and memory are not always tuned to remembering what we may think is memorable. ” The colours of the Google logo are also ubiquitous and not actually often remembered.

Here is the abstract: “People are regularly bombarded with logos in an attempt to improve brand recognition, and logos are often designed with the central purpose of memorability. The ubiquitous Apple logo is a simple design and is often referred to as one of the most recognizable logos in the world. The present study examined recall and recognition for this simple and pervasive logo and to what degree metamemory (confidence judgements) match memory performance. Participants showed surprisingly poor memory for the details of the logo as measured through recall (drawings) and forced-choice recognition. Only 1 participant out of 85 correctly recalled the Apple logo, and fewer than half of all participants correctly identified the logo. Importantly, participants indicated higher levels of confidence for both recall and recognition, and this overconfidence was reduced if participants made the judgements after, rather than before, drawing the logo. The general findings did not differ between Apple and PC users. The results provide novel support for theories of attentional saturation, inattentional amnesia, and reconstructive memory; additionally they show how an availability heuristic can lead to overconfidence in memory for logos. ”

Blake, A., Nazarian, M., & Castel, A. (2015). The Apple of the mind’s eye: Everyday attention, metamemory, and reconstructive memory for the Apple logo The Quarterly Journal of Experimental Psychology, 1-8 DOI: 10.1080/17470218.2014.1002798

Looking at qualia

For years there have been questions about whether we see the same colours, hear the same sounds, smell the same odours. How can we tell what someone else experiences in their conscious awareness? Well plainly, today at least, we can’t tell what someone else experiences.

But multivariate pattern analyses gives a type of decoding of patterns of activity in the brain. It has been used to do a type of ‘mind reading’ – but with the disadvantage that the code to ‘read’ a particular perception or thought is highly personal. The activity pattern resulting from a particular picture will be decoded only after many examples of pictures have been studied in that individual to create a decoding program. This tell us nothing (or very, very little) about how our perceptions may be similar.

Sight, hearing and smell are complex domains, and so it is not surprising that the activity patterns are individual. But taste has only a handful of qualities (sweet, salty, sour, bitter, savory) compared to extremely large numbers of qualities in colour, pitch and basic odours. Of course a perception has added qualities of intensity, has various mixtures of the basic qualities, and has emotional overtones. Still a low number of basic qualities and a restricted range of intensities gives a much more tractable decoding program. Taste can also be analysed early in its perception and some of the pattern’s elements are ‘hardwired’. The Crouzet paper (abstract below) has highlights: “large-scale electrophysiological response patterns code for taste quality in humans; taste quality is represented early in the central gustatory system; neural response patterns correlate with subjective perceptual experience.”

If it is further found in future research that these patterns are similar for different individuals tasting the same taste, then it would raise the probability that our experiences of other senses are also similar. If the patterns for different individuals show no similarity, then the probability that we share qualia is low.

Here is the abstract of the paper (S. Crouzet, N. Busch, K. Ohla; Taste Quality Decoding Parallels Taste Sensations; 2015 Current Biology):

In most species, the sense of taste is key in the distinction of potentially nutritious and harmful food constituents and thereby in the acceptance (or rejection) of food. Taste quality is encoded by specialized receptors on the tongue, which detect chemicals corresponding to each of the basic tastes (sweet, salty, sour, bitter, and savory), before taste quality information is transmitted via segregated neuronal fibers, distributed coding across neuronal fibers, or dynamic firing patterns to the gustatory cortex in the insula. In rodents, both hardwired coding by labeled lines and flexible, learning-dependent representations and broadly tuned neurons seem to coexist. It is currently unknown how, when, and where taste quality representations are established in the cortex and whether these representations are used for perceptual decisions. Here, we show that neuronal response patterns allow to decode which of four tastants (salty, sweet, sour, and bitter) participants tasted in a given trial by using time-resolved multivariate pattern analyses of large-scale electrophysiological brain responses. The onset of this prediction coincided with the earliest taste-evoked responses originating from the insula and opercular cortices, indicating that quality is among the first attributes of a taste represented in the central gustatory system. These response patterns correlated with perceptual decisions of taste quality: tastes that participants discriminated less accurately also evoked less discriminated brain response patterns. The results therefore provide the first evidence for a link between taste-related decision-making and the predictive value of these brain response patterns.”

Note: Kathrine Ohla sent this

I just came across your blog entry "looking for qualia" and like to
thank you for discussing our work. I am glad it raises so much interest
also outside the "taste community".
If it's not too much to ask, I would appreciate if you included the
hyperlink to the paper. This would allow your readers to find the full
article quicker.

An unnecessary exaggeration

Science 2.0 has a posting (here) on what is called brain to brain interfaces which they and other cannot resist calling telepathy; neither could the original press release writers.

I really think this ‘telepathy’ label is unnecessary. Telepathy implies communication directly on a mental (in the dualistic sense) rather than physical level. In other words telepathy is not natural but supernatural. What is being discussed now is a very physical communication involving a number of machines. No dualistic mental stage enters into it.

No doubt this technology, when it is perfected, will be useful in a number of ways. But as communication between most humans for most purposes, it will not beat language. In essence it is much like language: one brain has a thought and translates it into a form that can be transmitted, it is transmitted, and the receiver translates it back into a thought. That way of communicating sounds a lot like language to me. Just because it uses the internet to carry the message and non-intrusive machines to get information out of one brain and into another, does not mean it is different from language in principle. Language translates thoughts into words that are broadcast by the motor system, carried by sound through the air, received by the sensory system and made into words which can be translated into thoughts. It works well. If this new BBI stuff is telepathy then so is language (and semaphore for that matter).

Language also has some mind-control aspects. If I yell “STOP” it is very likely that another person will freeze before they can figure out why I yelled or why it may be a good idea to stop. It is as if I reached into their brain and pulled the halt cord. If you say “dog” I am going to look at the dog or search for one if there is no obvious dog. You have reached into my brain and pushed my attention from wherever it was focused onto a dog. If someone says “2 and 2 equals”, people will think “4” just like that. Someone has reached in and set the memory recall to find what completes that equation. People can also point metaphorically to shared concepts and so on. This amounts to people influencing one another’s brains.

With writing we have even managed to have time and distance gaps between speakers and listeners.

Language has other advantages but the greatest is that almost everyone has the mechanism already in a very advanced form. We are built to learn language as children and once learned it is handy, cheap and resilient.

Connectivity is not one idea

Sebastian Seung sold the idea that “we are our connectome”. What does that mean? Connectivity is a problem to me. Of course, the brain works only because there are connections between cells and between larger parts of the brain. But how can we measure and map it. Apparently there are measurement problems.

When some research says that A is connected to B it can mean a number of things. A could be a sizable area of the brain that has a largish nerve tract to B. This means that some neurons in A have axons that extend all the way to B, and some neurons in B have synapses with each of those axons. We could be talking about smaller and smaller groups of neurons until we have a pair of connected neurons. This is anatomy – it does not tell us when and how the connections are active or what they accomplish, just that a possible path is visible.

On the other hand A and B may share information. A and B are active at the same time in some circumstance. They are receiving the same information, either one from the other, or both from some other source. Quite often this means they are synchronized in their activity; it is locked together in a rhythm. Or they may react differently but always to the same type of information. Or one may feed the other information (directly or indirectly). A and B need only be connected when they are involved in the function that gives them shared information. Here we see the informational connection but necessarily the path.

A and B may be connected by a known causal link. A makes B active. Whenever A is active it causes B to be active too. This causal link gives no automatic information about path or even, at times, what information may be shared.

On a very small scale cells that are close together can be connected by contacts with glial cells, local voltage potentials and chemical gradients. Here the connections are even more difficult to map.

And finally overall there are control mechanisms that switch on and off various connection routes.

The whole brain is somewhat plastic and so can change its connectivity structure over time to better serve the needs of the individual. When it comes down to it, the connectivity that makes us each unique, the results of learning and memory, is the most plastic. It is changing all the time and can be very hard to map.

Saying “connectome” without any detailed specification is next to meaningless and “we are our connectome” is certainly true but somewhat vacuous.

A recent paper (citation below) took 4 common ways of measuring connectivity and compared them pair-wise. None of the pairs had a high level of agreement and some pairs had hardly any. There may be a lot of reasons for this but a big one has to be that the various methods were not measuring the same thing. In general, authors say that they are measuring, by what method and why. These nuances occasional do not make it to the abstract or conclusion, often never make it to the press release, and nearly never to news articles.

Here is the abstract and a diagram from the Jones paper.

Measures of brain connectivity are currently subject to intense scientific and clinical interest. Multiple measures are available, each with advantages and disadvantages. Here, we study epilepsy patients with intracranial electrodes, and compare four different measures of connectivity. Perhaps the most direct measure derives from intracranial electrodes; however, this is invasive and spatial coverage is incomplete. These electrodes can be actively stimulated to trigger electrophysical responses to provide the first measure of connectivity. A second measure is the recent development of simultaneous BOLD fMRI and intracranial electrode stimulation. The resulting BOLD maps form a measure of effective connectivity. A third measure uses low frequency BOLD fluctuations measured by MRI, with functional connectivity defined as the temporal correlation coefficient between their BOLD waveforms. A fourth measure is structural, derived from diffusion MRI, with connectivity defined as an integrated diffusivity measure along a connecting pathway. This method addresses the difficult requirement to measure connectivity between any two points in the brain, reflecting the relatively arbitrary location of the surgical placement of intracranial electrodes. Using a group of eight epilepsy patients with intracranial electrodes, the connectivity from one method is compared to another method using all paired data points that are in common, yielding an overall correlation coefficient. This method is performed for all six paired-comparisons between the four methods. While these show statistically significant correlations, the magnitudes of the correlation are relatively modest (r2 between 0.20 and 0.001). In summary, there are many pairs of points in the brain that correlate well using one measure yet correlate poorly using another measure. These experimental findings present a complicated picture regarding the measure or meaning of brain connectivity.”

Jones, S., Beall, E., Najm, I., Sakaie, K., Phillips, M., Zhang, M., & Gonzalez-Martinez, J. (2014). Low Consistency of Four Brain Connectivity Measures Derived from Intracranial Electrode Measurements Frontiers in Neurology, 5 DOI: 10.3389/fneur.2014.00272

A radical suggestion

How much and what type of our thinking is consciously done? The naïve feeling is that all our thinking is conscious. But we know better and tend to believe that a good deal of our thoughts are created unconsciously. I want to put forward the notion that none of our thoughts are the product of consciousness. Please set aside your disbelief for a short while in order to understand this idea and then you can resume your critical faculties and judge it.

Consciousness is about memory not thought. We cannot remember experiences unless we consciously experienced them. We can only know that we have been unconscious be noticing a discontinuity in our memory. We are probably only forced to have conscious experience of items that have been held in working memory – this has been called type 2 cognition, which always forms a conscious experience and uses working memory. That does not necessarily mean that the type 2 cognition is a product of the mechanism of consciousness.

Memory of experiences has functions. Why would we remember an event? We might find such information useful in future is about the only answer. For example, if we know there is a nasty dog in a particular yard, we may want to notice whether the gate is closed before we pass by. The various places we have experienced and mapped in memory have a lot of information associated with them. That is useful to have ‘on tap’ when we find ourselves in a particular place. ‘Where’ is an important element of the memory of an event. Also ‘when’, ‘who’ and ‘what’ are elements of most events. This information is available from the mechanisms of perception, recognition, navigation etc. We know that the processes that create these elements are not conscious, but the end product is. We also want other pieces of information to form an event to remember and use in recall. We want to know the event’s place in chains of cause and effect, whether it was an important event, what our emotional involvement was, whether it was a surprise or predicted. A very important element has to do with agency. We want to know whether we had any part in causing the event, and if we did was it deliberate or accidental, and whether the outcome was favourable or not. We assume that much of this volition information is created by conscious rather than unconscious mechanisms but experiments put that in doubt. And quite honestly there is no way that we could tell the difference.

Consciousness only needs to contain what is worth remembering but not all may be remembered. We can think of consciousness as the leading edge of memory containing all the information needed for the stable memory. However, we really do need to tell the difference between the ‘now’ and the stored memory of the past. And, although a fairly full description of ‘now’ may be delivered to short-term memory, much of it may be discarded before it reaches a more stable form. Memories are sketchy compared to conscious experience. The conscious stage of memory also has access to the current state of much of the brain. Low-level vision, hearing, feeling etc. can be used by the conscious model of ‘now’ to give it vivid realism – this would not be as easy for older memories.

Of course, these episodic memories are not our only memories and there are memories that are not produced from consciousness. Consciousness may have other functions than memory. All that I am trying to show here is that it is possible that consciousness is not involved in cognition. It may record some aspects if they will be important to remember for the future, but consciousness is not a cognition or thought engine in the brain. It is the engine to assemble experiences to be remembered as experiences.

Resume critical faculties…