30/03/2012 by admin.

I really do try to keep an open mind about this sort of thing. My usually view is very conventional, scientific, no nonsense on most matters; what counts is evidence and logical thinking. But this is something I try to keep from blinding me to possibilities from outside the scientific mainstream. So here is something interesting from IHM (which takes donations and sells products and so may not be a trustworthy scientific source).

Research in the new discipline of neurocardiology shows that the heart is a sensory organ and a sophisticated center for receiving and processing information. The nervous system within the heart (or “heart brain”) enables it to learn, remember, and make functional decisions independent of the brain’s cerebral cortex. Moreover, numerous experiments have demonstrated that the signals the heart continuously sends to the brain influence the function of higher brain centers involved in perception, cognition, and emotional processing.
In addition to the extensive neural communication network linking the heart with the brain and body, the heart also communicates information to the brain and throughout the body via electromagnetic field interactions. The heart generates the body’s most powerful and most extensive rhythmic electromagnetic field. Compared to the electromagnetic field produced by the brain, the electrical component of the heart’s field is about 60 times greater in amplitude, and permeates every cell in the body. The magnetic component is approximately 5000 times stronger than the brain’s magnetic field and can be detected several feet away from the body with sensitive magnetometers.
The heart generates a continuous series of electromagnetic pulses in which the time interval between each beat varies in a dynamic and complex manner. The heart’s ever-present rhythmic field has a powerful influence on processes throughout the body. We have demonstrated, for example, that brain rhythms naturally synchronize to the heart’s rhythmic activity, and also that during sustained feelings of love or appreciation, the blood pressure and respiratory rhythms, among other oscillatory systems, entrain to the heart’s rhythm.

In the context of the neurons in other parts of the body, especially the gut, it would not be surprising if the heart had a similar effect on the brain. The report goes on into various ideas what have less firm foundations, but maybe some grains of truth as well. I am not competent to sort the wheat from the chaff. This part that I have included here does seem fairly reasonable. I have long identified the idea of life with the rhythms of living things and identified the central essence of my ’self’ with the rhythms of my whole body. This may be my illusion (rather than the more common illusion of the conscious mind being the essence of self).

Posted in Uncategorized | 2 Comments »

21/03/2012 by admin.

Those that follow this blog know that one of the repeated messages is that the results of single experiments are not to be trusted. We should be convinced by those ideas that have been shown by a number of different people, methods and subjects. (Also nothing is falsified by single experiments.) Its is the fabric, not the thread, of results that is convincing. This is particularly important with new technical tools such as neural scans. We really don’t know how trustworthy they are; the equipment, the mathematical manipulations, the interpretations are in flux. But it is what we have for physical evidence and so we do the best we can with it.

Neuroskeptic (here) has posted on a paper by Hupe and others that shows that there is a BOLD signature from blinks of the eyes in the scans of the visual cortex. It appears that once the problem is known, it should be possible to avoid it affecting results.

it’s long been believed that blink suppression mechanisms in the eye and brain somehow block out the responses that would otherwise happen during a blink….Then they (Hupe etal) simply treated the blinks as events, and used standard analysis methods to find neural activation associated with them. Blinks caused a significant BOLD response over a number of “visual” areas….I don’t think we should be too worried yet….However, as the authors point out, there is a risk that alterations in blink rate, caused, perhaps, by emotional or cognitive stress, might be wrongly “found” to be causing visual cortex activation, which might call into question claims of “top-down” influences on early visual cortex… oh dear.

Posted in Uncategorized | 1 Comment »

09/03/2012 by admin.

D Bishop has a post on BishopBlog (here), “Time for neuroimaging (and PNAS) to clean up its act”. This is a great posting: well argued and organized.

She has found a paper (for other reasons) that appears to have a good reputation but breaks a number of rules. All its conclusions are invalid. Because some authors had a financial interest in the results, it should have been reviewed carefully but it was not found wanting by the original peer reviewers or later authors who cited it or used its graphics. Wow – what an example.

What was wrong? The first conclusion was not valid because an important control group was missing – a group who had the condition but was not treated. The second conclusion was not valid because it was based on a faulty statistical procedure. The third is invalid it does not take account of within-group variance. Conclusion 4 relied on unusual outliers and some dodgy stats.

She makes some recommendation to correct this sort of thing which she had found in a number of papers.

Is there a solution? One suggestion is that reviewers and readers would benefit from a simple cribsheet listing the main things to look for in a methods section of a paper in this area. Is there an imaging expert out there who could write such a document, targeted at those like me, who work in this broad area, but aren’t imaging experts? Maybe it already exists, but I couldn’t find anything like that on the web.

Imaging studies are expensive and time-consuming to do, especially when they involve clinical child groups. I’m not one of those who thinks they aren’t ever worth doing. If an intervention is effective, imaging may help throw light on its mechanism of action. However, I do not think it is worthwhile to do poorly-designed studies of small numbers of participants to test the mode of action of an intervention that has not been shown to be effective in properly-controlled trials. It would make more sense to spend the research funds on properly controlled trials that would allow us to evaluate which interventions actually work.

Good idea!

Posted in Uncategorized | 1 Comment »

06/03/2012 by admin.

I find the traces of old theories in our language intriguing. We still talk about heat in ways that hark back to the phlogiston theory – we talk of the flow of heat like it was a fluid. We talk of the sun rising, as if Galileo had never been, although we all know it is the earth that is turning. The language always carries fossils of long-gone beliefs. So it will be with our theories of thought and behavior; the old phrases will remain along side newer understandings.

In our minds we have a simplified version of how the world works. For example infants have a folk physics. They can roughly estimate the path of a falling object. We have the ‘theory of mind’ that gives us a rough understanding of what goes on in the heads of others (and ourselves). We all have a folk psychology that we have built up over the years from what we have read and what we have experienced as a refinement of our theory of mind. Even than it is still a rough estimate of how brains work. It seems we are now creating a folk neuropsychology. Paul Rodriguez has studied this emerging folk ‘knowledge’ using its effect on language (see citation below). This is brought to my attention by an item in the Mind Hacks blog (here).

Rodriguez studied ordinary language in ordinary situations, not the language of experts, and looked for the metaphors and metonymies in use – the method of cognitive semantics. He found that in many statements, ‘mind’ and ‘brain’ were interchangable.

I will argue that for the most part “brain” and “mind” are used in similar ways with similar meanings, but whereas “mind” may have an aspect of subjectivity, “brain” has a concrete and physical dimension.

Examples are given.

THE MIND IS A CONTAINER: in my mind, clear your mind – THE BRAIN IS A CONTAINER: in my brain but not yet on paper, stuff that sticks in our brain

THE MIND IS A MACHINE: crank out ideas – THE BRAIN IS A MACHINE: her brain was churning, my brain wasn’t switched on

THE MIND IS A RECORDING MEDIUM FOR MEMORY (LIKE A COMPUTER): my mind was blank, etched in my mind – THE BRAIN IS A RECORDING MEDIUM: etched onto the brain, imprinted on the brain

THE MIND IS A MUSCLE: mental leaps, mental exercise – THE BRAIN IS A MUSCLE: flex your brain

IDEAS ARE FOOD: hard to swallow, chewing over – THE BRAIN NEEDS IDEAS FOR NOURISHMENT: feed your brain

UNDERSTANDING IN GRASPING: get a handle on, grasp the concept – THE BRAIN CAN UNDERSTAND CONCEPTS BY GRASPING: trying to wrap my brain around it

But there are differences between the metaphoric use of the two words.

Despite the possible overlap in meaning between mind and brain, they are not completely interchangeable. One trivial example is that “mind” can be a verb related to thinking, as in “never mind.” More interestingly, there are common phrases about the mind as a noun that do not seem to apply so easily to the brain. Consider the following examples: “I want to give you a piece of my brain” versus “I want to give you a piece of my mind,” “Will you change your brain?” versus “Will you change your mind?” “Open your brain” versus “Open your mind.”

The nature of some metaphors can be quite reductionist. Here are some examples:

THE BRAIN AS AGENT AND/OR LOCUS OF IDEAS: songs sped from brain to paper

THE BRAIN AS AGENT AND/OR LOCUS OF TRUE KNOWLEDGE: my brain knows what to do but me body won’t do it, they know in their brain but can’t vertalize

THE BRAIN AS AGENT AND/OR LOCUS OF DELIBERATION: how hard it is to ignore the famous even when your brain tells you to.

THE BRAIN AS EXPERIENCER OF PERCEPTIONS: this menu is confusing my brain

If you are as interested in language as you are in neuroscience, I recommend that you read the original paper and enjoy its many insights. It is very readable. You will be able to see the scope of this research from the papers conclusion:

In summary, I have shown that brain and mind have overlapping referents, brain and mind are conceptualized similarly, reporting brain states can be substituted for reporting mental states, and brain images engender new shared cultural symbols that characterize mental phenomena. The use of these brain references to talk about mental states and mental experiences is a reductionist mode of explaining behavior. In that sense, it is a rudimentary folk neuropsychology.

I have also applied a cognitive semantic analysis to the use of metaphors, speech acts, jokes, advertisements, and other images to the ordinary language of “brain.” Other work in the public understanding of genetics, or science and technology more generally, has also examined metaphors, such as frequency and types in popular media or development and change of analogies over time in popular science. For an analysis of lay understandings, some work has used interview techniques to evaluate how science is assimilated. Some analyses of culture and science have also focused on the nature of science narratives and their impact on policy discussions, legal decisions, and personal attitudes. The cognitive semantic analysis of metaphor, speech acts, and imagery in ordinary language is complementary to all these approaches because it focuses on the network of conceptual schemas underlying common sense understanding. As well as identifying and categorizing metaphors as a whole unit, deconstructing the meanings of cultural symbols, or situating social perspectives, a cognitive semantic analysis decomposes the underlying concepts that organize and structure the way we conceive and talk about things. The cognitive semantic analysis helps reveal the source of entailments, generalizations, inferences, discourse effects and social meanings involved in everyday language. This kind of analysis seems especially crucial for the public understanding of neuroscience because the mind is something abstract that we know subjectively, theories of brain function are still immature, and the dualist sense that the mind is not physical makes this a difficult matter to talk about in purely objective terms.

Rodriguez, P. (2006). Talking brains: a cognitive semantic analysis of an emerging folk neuropsychology Public Understanding of Science, 15 (3), 301-330 DOI: 10.1177/0963662506063923

Posted in Uncategorized | 2 Comments »

03/03/2012 by admin.

A recent paper (K Fenna etal. 2011, When less is heard than meets the ear: Change deafness in a telephone conversation, The Quarterly Journal of Experimental Psychology) showed that there is change deafness as well as change blindness. If people are not expecting the stranger on the other end of a phone call to change, they will not notice the change. We really do not take in as much of what is happening as we think we do. Here is the abstract:

During a conversation, we hear the sound of the talker as well as the intended message. Traditional models of speech perception posit that acoustic details of a talker’s voice are not encoded with the message whereas more recent models propose that talker identity is automatically encoded. When shadowing speech, listeners often fail to detect a change in talker identity. The present study was designed to investigate whether talker changes would be detected when listeners are actively engaged in a normal conversation, and visual information about the speaker is absent. Participants were called on the phone, and during the conversation the experimenter was surreptitiously replaced by another talker. Participants rarely noticed the change. However, when explicitly monitoring for a change, detection increased. Voice memory tests suggested that participants remembered only coarse information about both voices, rather than fine details. This suggests that although listeners are capable of change detection, voice information is not continuously monitored at a fine-grain level of acoustic representation during natural conversation and is not automatically encoded. Conversational expectations may shape the way we direct attention to voice characteristics and perceive differences in voice.

Posted in Uncategorized | 1 Comment »

26/02/2012 by admin.

When we refer to spatial arrangements in language, there are three different ways to do it. We can see ourselves as central and refer to the positions of other objects by their headings from us. So, that post is behind me or that house is to my left – relative or egocentric frame. We can also see some other object as the reference. So, that post is behind the house or the garden is on the left of the car – intrinsic or object oriented frame. Finally we can use the world as the reference. So, the post is to the west of the house – absolute or world oriented frame. How people handle the choice of referent is largely a matter of culture and language. European languages mainly use a relative frame of reference as default – we are usually the reference. But there is often room for ambiguity. Does the “the ball is in front of the man” mean it that the ball is between me and the man or does it mean that the man is facing the ball? This interests me in particular because I often seem to misinterpret what is meant or am left wondering. In the past, I have put it down to being left-handed.

Janzen, Haum and Levinson (see citation) investigated relative and intrinsic using the possibilities of ambiguity. They created sentences like “the ball is in front of the man” and three drawings to go with the sentence. One drawing would be true in both relative and intrinsic interpretations; one would be false for both; one would be true for one interpretation and false for the other. They showed a picture and sentence and asked the subject to say whether the drawing was a correct description of the sentence. The subjects were given feedback on whether their answers were correct. This feedback was either based on the relative or the intrinsic interpretation and the subjects came to judge the sentence-drawing pairs according to the feedback type they were receiving. During a block of trials, consistent feedback (correct, incorrect) was given so inducing either a relative or intrinsic frame. Midway through the trials, the second block began and the feedback was switched to the alternative reference frame without any explanation . Only correct answers were used in the analysis. This gave results for identical sentence-drawing pairs viewed in each of the two frames of reference. The subjects spoke Dutch which tends to use relative reference. Event-related fMRI was used to follow the differences in cortical activity in the two reference frames following identical linguistic and visual input.

They found two networks, an intrinsic one and a relative one. The differentiation starts early at the level of sentence processing (that is before the drawing is shown and the answer required). Increased brain activity in bilateral parahippocampal gyrus was associated with the intrinsic frame of reference whereas increased activity in the right superior frontal gyrus and in the parietal lobe was observed for the relative frame of reference.

Comparing trials with intrinsic as well as relative pictures to baseline trials we found a shared widespread network with increased activity in occipital, parietal, temporal and frontal brain regions. This is in line with evidence from an fMRI study that distinguished viewer-, object-, and landmark-centered distance judgments, and found common activity for all three types in bilateral parietal, occipital, and right frontal premotor regions as well.

In the present study we directly compared intrinsic with relative trials and observed increased activity for intrinsic trials in bilateral parahippocampal gyrus, an area closely connected to the hippocampus through the entorhinal and perirhinal gyrus. Recent neuroimaging studies emphasize the importance of the parahippo-campal gyrus for the recognition of familiar as well as novel spatial environments and scenes and for object-location memory . To correctly solve intrinsic trials participants needed to consider the spatial relation of two objects and decide whether the scene matched a previously presented sentence. Therefore scene representation within the parahippocampal gyrus should be able to support intrinsic frames of reference.

fMRI data has shown that the parietal lobe is associated with representations of object locations in an egocentric reference frame. The present data when comparing relative trials to baseline trials supports the involvement of the parietal lobe. We observed increased activity in the left parietal lobe for the relative frame of reference only, confirming neurophysiological studies which report the involvement of the parietal lobe in egocentric coding.

Relative trials as compared to intrinsic trials also showed strongly increased activity in superior frontal gyrus. This is in line with findings from researchers who have observed a parietal/frontal network for viewer-centered coding.

This gives a glimpse at the way a language is interpreted in the brain by creating a model of what is understood by words.

Janzen, G., Haun, D., & Levinson, S. (2012). Tracking Down Abstract Linguistic Meaning: Neural Correlates of Spatial Frame of Reference Ambiguities in Language PLoS ONE, 7 (2) DOI: 10.1371/journal.pone.0030657

Posted in Uncategorized | 1 Comment »

23/02/2012 by admin.

The pitfalls of experimental methods in neuroscience have not all been worked out. I’ll say it again, no one result is reliable in science; what is convincing is a fabric of results – not a string but a fabric. This is especially true in a new field.

Micah at neuroconscience blog has a posting on possible BOLD signal problems. (here)

Particularly in fMRI research, we’re all too familiar with certain regions that seem to pop up in study after study, regardless of experimental paradigm. When it comes to areas like the anterior cingulate cortex (ACC) and insula (AIC), the trend is glaringly obvious. Generally when I see the same brain region involved in a wide a variety of tasks, I think there must be some very general level function which encompasses these paradigms. Off the top of my head, the ACC and AIC are major players in cognitive control, pain, emotion, consciousness, salience, working memory, decision making, and interoception to name a few. Maybe on a bad day I’ll look at a list like that and think, well localization is just all wrong, and really what we have is a big fat prefrontal cortex doing everything in conjunction. A paper published yesterday in Cerebral Cortex (Di, Kannurpatti, Rypma, Biswal: Calibrating BOLD fRMI Activations with Neurovascular and Anatomical Constraints) took my breath away and lead to a third, more sinister option: a serious methodological confound in a large majority of published fMRI papers.

An important line of research in neuroimaging focuses on noise in fMRI signals. The essential problem of fMRI is that, while it provides decent spatial resolution, the data is acquired slowly and indirectly via the blood-oxygenation level dependent (BOLD) signal. The BOLD signal is messy, slow, and extremely complex in its origins. Although we typically assume increasing BOLD signal equals greater neural activity, the details of just what kind of activity (e.g. excitatory vs inhibitory, post-synaptic vs local field) are murky at best. Advancements in multi-modal and optogenetic imaging hold a great deal of promise regarding the signal’s true nature, but sadly we are currently at a “best guess” level of understanding. This weakness means that without careful experimental design, it can be difficult to rule out non-neural contributors to our fMRI signal. Setting aside the worry about what neural activity IS measured by BOLD signal, there is still the very real threat of non-neural sources like respiration and cardiovascular function confounding the final result. This is a whole field of research in itself, and is far too complex to summarize here in its entirety. The basic issue is quite simple though.

Well, maybe not that simple – go to the original posting for the physiology. The upshot is that it is really important to control for the subject holding their breath or breathing differently at different times in the protocol.

The authors conclude that “(results) indicated that the adjustment tended to suppress activation in regions that were near vessels such as midline cingulate gyrus, bilateral anterior insula, and posterior cerebellum.” It seems that indeed, our old friends the anterior insula and cingulate cortex are extremely susceptible to neurovascular confound.

What does this mean for cognitive neuroscience? For one, it should be clear that even well-controlled fMRI designs can exhibit such confounds. This doesn’t mean we should throw the baby out with the bathwater though; some designs are better than others. Thankfully it’s pretty easy to measure respiration with most scanners, and so it is probably a good idea at minimum to check if one’s experimental conditions do indeed create differential respiration patterns. Further, we need to be especially cautious in cases like meditation or clinical fMRI, where special participant groups may have different baseline respiration rates or stronger parasympathetic responses to stimuli.

Experimental methods in neuroscience are new enough and complicated enough to be misleading. It is reassuring to me that there are researchers looking at possible short-comings of these methods.

Posted in Uncategorized | 1 Comment »

14/02/2012 by admin.

Here is another of the Edge question essays, by Timothy D Wilson, “We are what we do”. The Edge answers are (here).

My favorite is the idea that people become what they do. …

Self-perception theory turns common wisdom on its head. People act the way they do because of their personality traits and attitudes, right? They return a lost wallet because they are honest, recycle their trash because they care about the environment, and pay $5 for a caramel brulée latte because they like expensive coffee drinks. While it is true that behavior emanates from people’s inner dispositions, Bem’s insight was to suggest that the reverse also holds. If we return a lost wallet, there is an upward tick on our honesty meter. After we drag the recycling bin to the curb, we infer that we really care about the environment. And after purchasing the latte, we assume that we are coffee connoisseurs.

Hundreds of experiments have confirmed the theory and shown when this self-inference process is most likely to operate (e.g., when people believe they freely chose to behave the way they did, and when they weren’t sure at the outset how they felt).

Self-perception theory is an elegant in its simplicity. But it is also quite deep, with important implications for the nature of the human mind. Two other powerful ideas follow from it. The first is that we are strangers to ourselves. After all, if we knew our own minds, why would we need to guess what our preferences are from our behavior? If our minds were an open book, we would know exactly how honest we are and how much we like lattes. Instead, we often need to look to our behavior to figure out who we are. Self-perception theory thus anticipated the revolution in psychology in the study of human consciousness, a revolution that revealed the limits of introspection.

But it turns out that we don’t just use our behavior to reveal our dispositions - we infer dispositions that weren’t there before. Often, our behavior is shaped by subtle pressures around us, but we fail to recognize those pressures. As a result, we mistakenly believe that our behavior emanated from some inner disposition. Perhaps we aren’t particularly trustworthy and instead returned the wallet in order to impress the people around us. But, failing to realize that, we infer that we are squeaky clean honest. Maybe we recycle because the city has made it easy to do so (by giving us a bin and picking it up every Tuesday) and our spouse and neighbors would disapprove if we didn’t. Instead of recognizing those reasons, though, we assume that we should be nominated for the Green Neighbor of the Month Award. Countless studies have shown that people are quite susceptible to social influence, but rarely recognize the full extent of it, thereby misattributing their compliance to their true wishes and desires–the well-known fundamental attribution error. … In short, we should all heed Kurt Vonnegut’s advice: “We are what we pretend to be, so we must be careful about what we pretend to be.”

This is the same idea as the notion that our justifications are guesses that we produce when required and may not be the primary reasons for our actions. The most clear demonstrations of these guesses are in split brain subjects and people under hypnosis but there are many others. We cannot examine our motives through introspection but are in great danger of fooling ourselves.

Posted in Uncategorized | 1 Comment »

11/02/2012 by admin.

Back to the Edge question (here). Stanislas Dehaene gave his answer to ‘What is your favorite deep, elegant, or beautiful explanation?’ as The Universal Algorithm for Human Decisions. Most is below:

All of our mental decisions appear to be captured by a simple rule that weaves together some of the most elegant mathematics of the past centuries: Brownian motion, Bayes’ rule, and the Turing machine.

Let us start with the simplest of all decisions: how do we decide that 4 is smaller than 5? Psychological investigation reveals many surprises behind this simple feat. First, our performance is very slow: the decision takes us nearly half a second… Second, our response time is highly variable from trial to trial, anywhere from 300 milliseconds to 800 milliseconds… Third, we make errors - it sounds ridiculous, but even when comparing 4 with 5, we sometimes make the wrong decision. Fourth, our performance varies with the meaning of the objects: we are much faster, and make fewer errors, when the numbers are far from each other (such as 1 and 5) than when they are close (such as 4 and 5).

Well, all of the above facts, and many more, can be explained by a single law: our brain takes decisions by accumulating the available statistical evidence and committing to a decision whenever the total exceeds a threshold.

Let me unpack this statement. The problem that the brain faces when taking a decision is one of sifting the signal from the noise. The input to any of our decision is always noisy: photons hit our retina at random times, neurons transmit the information with partial reliability, and spontaneous neural discharges (spikes) are emitted throughout the brain, adding noise to any decision. Even when the input is a digit, neuronal recordings show that the corresponding quantity is coding by a noisy population of neurons that fires at semi-random times, with some neurons signaling “I think it’s 4″, others “it’s close to 5″, or “it’s close to 3″, etc. Because the brain’s decision system only sees unlabeled spikes, not full-fledged symbols, it is a genuine problem for it to separate the wheat from the chaff.

In the presence of noise, how should one take a reliable decision? The mathematical solution to that the problem was first addressed by Alan Turing, when he was cracking the Enigma code at Bletchley Park. Turing found a small glitch in the Enigma machine, which meant that some of the German messages contained small amounts of information - but unfortunately, too little to be certain of the underlying code. Turing realized that Bayes’ law could be exploited to combine all of the independent pieces of evidence. Skipping the math, Bayes’ law provides a simple way to sum all of the successive hints, plus whatever prior knowledge we have, in order to obtain a combined statistic that tells us what the total evidence is.

With noisy inputs, this sum fluctuates up and down, as some incoming messages support the conclusion while others merely add noise. The outcome is what mathematicians call a “random walk” or “Brownian motion”, a fluctuating march of numbers as a function of time. In our case, however, the numbers have a currency: they represent the likelihood that one hypothesis is true (e.g. the probability that the input digit is smaller than 5). Thus, the rational thing to do is to act as a statistician, and wait until the accumulated statistic exceeds a threshold probability value. Setting it to p=0.999 would mean that we have one chance in a thousand to be wrong.

… There is a speed-accuracy trade-off: we can wait a long time and take a very accurate but conservative decision, or we can hazard a response earlier, but at the cost of making more errors. Whatever our choice, we will always make a few errors.

Suffice it to say that the decision algorithm I sketched, and which simply describes what any rational creature should do in the face of noise, is now considered as a fully general mechanism for human decision making. It explains our response times, their variability, and the entire shape of their distribution. It describes why we make errors, how errors relate to response time, and how we set the speed-accuracy trade-off. It applies to all sorts of the decisions, from sensory choices (did I see movement or not?) to linguistics (did I hear “dog” or “bog”?) and to higher-level conundrums (should I do this task first or second?). And in more complex cases, such as performing a multi-digit calculation or a series of tasks, the model characterizes our behavior as a sequence of accumulate-and-threshold steps, which turns out to be an excellent description of our serial, effortful Turing-like computations.

Furthermore, this behavioral description of decision-making is now leading to major progress in neuroscience. In the monkey brain, neurons can be recorded whose firing rates index an accumulation of relevant sensory signals. The theoretical distinction between evidence, accumulation and threshold helps parse out the brain into specialized subsystems that “make sense” from a decision-theoretic viewpoint.

As with any elegant scientific law, many complexities are waiting to be discovered… Nevertheless, as a first approximation, this law stands as one of the most elegant and productive discoveries of twentieth-century psychology: humans act as near-optimal statisticians, and any of our decisions corresponds to an accumulation of the available evidence up to some threshold.

To nit-pick a bit. Algorithm seems an inappropriate term in the title. Turin is mentioned in two contexts but only the phrase ‘our serial, effortful Turing-like computations’ seems to refer to what we call a Turing machine; the decoding trick does not have to do with Turing machines. The neural noise level in the brain seems a regulated parameter to due with sensitivity and not just an unavoidable by-product of neural activity. None of these picky things take away from the brilliant explanation.

Posted in Uncategorized | 1 Comment »

08/02/2012 by admin.

A recent paper examined a patient with deaf-hearing, analogous to blind-sight, where there can be detection of a signal without conscious awareness of it. (citation below) For example, a person with blind-sight may avoid an obstacle without awareness of it; and, a deaf-hearing person may be startled and orient towards a noise without consciously hearing it.

Deaf-hearing seems to be the more rare condition and so this stroke victim was examined extensively. The path from within the ear through the brain stem to the thalamus was normal. But bilateral damage to the auditory areas of the cortex seemed to completely disrupt the processing of the signal. There appeared to be a problem with the communication between the thalamus and the cortex as well as damage to the cortex.

However, despite this break in the usual path, a signal designated P3 did occur within the cortex. The discussion has this passage:

Bernat et al. (2001) offer evidence that subliminal stimuli can evoke consistent P3 waves. They speculated that P3 could represent a link between unconscious and conscious awareness in the context updating processes. In our patient the generation of P3-like potentials implied that deviant stimuli were selectively processed bypassing networks involved in conscious perception. Schonwiesner et al. (2007) and Pandya (1995) hypothesized that association areas in and adjacent to the auditory parabelt might form an independent circuit from thalamo-cortical projections in the auditory system. These alternate pathways could be preserved in our patient and responsible for the generation of P3-like potentials.

What does a P3 wave indicate?

P3 offers a covert and indirect measure of attentional resource allocation that represents an index of change detection. P3 is related to the activity of associative cortical areas and is sensitive to complex processes around recalled information, stimulus significance, recognized auditory information and memory context updating. The sources of P3 are believed to be located in heteromodal areas of the fronto-parietal cortex and their activation might reflect an attention switch to an environmental change …. some authors have demonstrated an asymmetrical cortical activation of P3 by using unilateral auditory stimulation. Among others, Gilmore and colleagues (2009) argued that in normal condition the right hemisphere is more prominently engaged during working memory and updating processes underlying P3 …the patient showed robust P3-like components over the left posterior areas and a significantly lower distribution of the potentials over the right fronto-temporal and central areas in response to right ear stimulation. The left ear stimulation could not evoke any detectable responses.

In other words, P3 is about an event rather then a sound, switching attention to unusual events. In this patient there was a left hemisphere P3 but not the right hemisphere one – and it appears to be the right hemisphere P3 that engages consciousness.

The authors use these results to give input to the choice between two hypotheses. A simple hierarchical model where each level of processing is necessary for the next is not consistent with the findings. But the reverse hierarchy theory, which asserts that neural circuits mediating a certain percept can be modified starting at the highest representational level and progressing to lower-levels in search of more refined high resolution information to optimize perception, would not be ruled out by the paradoxical findings in this patient.

Personally, although not explicit in the paper, I find the results are more evidence for: one, the necessity of thalamus-cortex communication to consciousness; two, attention being a much more complex entity when just the focus of consciousness; three, that there is a difference in how the left and right hemispheres handle sound; and four, the importance of top-down inputs (expectations) in forming perceptions.

Cavinato, M., Rigon, J., Volpato, C., Semenza, C., & Piccione, F. (2012). Preservation of Auditory P300-Like Potentials in Cortical Deafness PLoS ONE, 7 (1) DOI: 10.1371/journal.pone.0029909

Posted in Uncategorized | 1 Comment »