Category Archives: research

Correcting your naughty insula: modelling respiration, pulse, and motion artifacts in fMRI

Posted in Cognitive Neuroscience, figures, Methodology, Mindfulness, Neuroscience, Plasticity, research by

important update: Thanks to commenter “DS”, I discovered that my respiration-related data was strongly contaminated due to mechanical error. The belt we used is very susceptible to becoming uncalibrated, if the subject moves or breathes very deeply for example. When looking at the raw timecourse of respiration I could see that many subjects, included the one displayed here, show a great deal of “clipping” in the timeseries. For the final analysis I will not use the respiration regressors, but rather just the pulse and motion. Thanks DS!

As I’m working my way through my latest fMRI analysis, I thought it might be fun to share a little bit of that here. Right now i’m coding up a batch pipeline for data from my Varela-award project, in which we compared “adept” meditation practitioners with motivation, IQ, age, and gender-matched controls on a response-inhibition and error monitoring task. One thing that came up in the project proposal meeting was a worry that, since meditation practitioners spend so much time working with the breath, they might respirate differently either at rest or during the task. As I’ve written about before, respiration and other related physiological variables such as cardiac-pulsation induced motion can seriously impact your fMRI results (when your heart beats, the veins in your brain pulsate, creating slight but consistent and troublesome MR artifacts). As you might expect, these artifacts tend to be worse around the main draining veins of the brain, several of which cluster around the frontoinsular and medial-prefrontal/anterior cingulate cortices. As these regions are important for response-inhibition and are frequently reported in the meditation literature (without physiological controls), we wanted to try to control for these variables in our study.

disclaimer: i’m still learning about noise modelling, so apologies if I mess up the theory/explanation of the techniques used! I’ve left things a bit vague for that reason. See bottom of article for references for further reading. To encourage myself to post more of these “open-lab notes” posts, I’ve kept the style here very informal, so apologies for typos or snafus. :D

To measure these signals, we used the respiration belt and pulse monitor that come standard with most modern MRI machines. The belt is just a little elastic hose that you strap around the chest wall of the subject, where it can record expansions and contractions of the chest to give a time series corresponding to respiration, and the pulse monitor a standard finger clip. Although I am not an expert on physiological noise modelling, I will do my best to explain the basic effects you want to model out of your data. These “non-white” noise signals include pulsation and respiration-induced motion (when you breath, you tend to nod your head just slightly along the z-axis), typical motion artifacts, and variability of pulsation and respiration. To do this I fed my physiological parameters into an in-house function written by Torben Lund, which incorporates a RETROICOR transformation of the pulsation and respiration timeseries. We don’t just use the raw timeseries due to signal aliasing- the phsyio data needs to be shifted to make each physiological event correspond to a TR. The function also calculates the respiratory volume time delay (RVT), a measure developed by Rasmus Birn, to model the variability in physiological parameters1. Variability in respiration and pulse volume (if one group of subjects tend to inhale sharply for some conditions but not others, for example) is more likely to drive BOLD artifacts than absolute respiratory volume or frequency (if one group of subjects tend to inhale sharply for some conditions but not others, for example). Finally, as is standard, I included the realignment parameters to model subject motion-related artifacts. Here is a shot of my monster design matrix for one subject:

DM_NVR

You can see that the first 7 columns model my conditions (correct stops, unaware errors, aware errors, false alarms, and some self-report ratings), the next 20 model the RETROICOR transformed pulse and respiration timeseries, 41 columns for RVT, 6 for realignment pars, and finally my session offsets and constant. It’s a big DM, but since we have over 1000 degrees of freedom, i’m not too worried about all the extra regressors in terms of loss of power. What would be worrisome is if for example stop activity correlated strongly with any of the nuisance variables –  we can see from the orthogonality plot that in this subject at least, that is not the case. Now lets see if we actually have anything interesting left over after we remove all that noise:

stop SPM

We can see that the Stop-related activity seems pretty reasonable, clustering around the motor and premotor cortex, bilateral insula, and DLPFC, all canonical motor inhibition regions (FWE-cluster corrected p = 0.05). This is a good sign! Now what about all those physiological regressors? Are they doing anything of value, or just sucking up our power? Here is the f-contrast over the pulse regressors:

pulse

Here we can see that the peak signal is wrapped right around the pons/upper brainstem. This makes a lot of sense- the area is full of the primary vasculature that ferries blood into and out of the brain. If I was particularly interested in getting signal from the brainstem in this project, I could use a respiration x pulse interaction regressor to better model this6. Penny et al find similar results to our cardiac F-test when comparing AR(1) with higher order AR models [7]. But since we’re really only interested in higher cortical areas, the pulse regressor should be sufficient. We can also see quite a bit of variance explained around the bilateral insula and rostral anterior cingulate. Interestingly, our stop-related activity still contained plenty of significant insula response, so we can feel better that some but not all of the signal from that region is actually functionally relevant. What about respiration?

resp

Here we see a ton of variance explained around the occipital lobe. This makes good sense- we tend to just slightly nod our head back and forth along the z-axis as we breath. What we are seeing is the motion-induced artifact of that rotation, which is most severe along the back of the head and periphery of the brain. We see a similar result for the overall motion regressors, but flipped to the front:

Ignore the above, respiration regressor is not viable due to “clipping”, see note at top of post. Glad I warned everyone that this post was “in progress” :) Respiration should be a bit more global, restricted to ventricles and blood vessels.

motion

Wow, look at all the significant activity! Someone call up Nature and let them know, motion lights up the whole brain! As we would expect, the motion regressor explains a ton of uninteresting variance, particularly around the prefrontal cortex and periphery.

I still have a ways to go on this project- obviously this is just a single subject, and the results could vary wildly. But I do think even at this point we can start to see that it is quite easy and desirable to model these effects in your data (Note: we had some technical failure due to the respiration belt being a POS…) I should note that in SPM, these sources of “non-white” noise are typically modeled using an autoregressive (AR(1)) model, which is enabled in the default settings (we’ve turned it off here). However as there is evidence that this model performs poorly at faster TRs (which are the norm now), and that a noise-modelling approach can greatly improve SnR while removing artifacts, we are likely to get better performance out of a nuisance regression technique as demonstrated here [4]. The next step will be to take these regressors to a second level analysis, to examine if the meditation group has significantly more BOLD variance-explained by physiological noise than do controls. Afterwards, I will re-run the analysis without any physio parameters, to compare the results of both.

References:

1. Birn RM, Diamond JB, Smith MA, Bandettini PA.
Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI.
Neuroimage. 2006 Jul 15;31(4):1536-48. Epub 2006 Apr 24.↩

2. Brooks J.C.W., Beckmann C.F., Miller K.L. , Wise R.G., Porro C.A., Tracey I., Jenkinson M.
Physiological noise modelling for spinal functional magnetic resonance imaging studies
NeuroImage in press: DOI: doi: 10.1016/j.neuroimage.2007.09.018

3. Glover GH, Li TQ, Ress D.
Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR.
Magn Reson Med. 2000 Jul;44(1):162-7.

4. Lund TE, Madsen KH, Sidaros K, Luo WL, Nichols TE.
Non-white noise in fMRI: does modelling have an impact?
Neuroimage. 2006 Jan 1;29(1):54-66.

5. Wise RG, Ide K, Poulin MJ, Tracey I.
Resting fluctuations in arterial carbon dioxide induce significant low frequency variations in BOLD signal.
Neuroimage. 2004 Apr;21(4):1652-64.

2. Brooks J.C.W., Beckmann C.F., Miller K.L. , Wise R.G., Porro C.A., Tracey I., Jenkinson M.
Physiological noise modelling for spinal functional magnetic resonance imaging studies
NeuroImage in press: DOI: doi: 10.1016/j.neuroimage.2007.09.018↩

7. Penny, W., Kiebel, S., & Friston, K. (2003). Variational Bayesian inference for fMRI time series. NeuroImage, 19(3), 727–741. doi:10.1016/S1053-8119(03)00071-5

Google Wave for Scholarly Co-authorship: excerpt from Neuroplasticity and Consciousness Abstract

Posted in images, internet, Neuroscience, phenomenology, Philosophy, research by

Gary Williams and I are working together on a paper investigating the consciousness and neuroplasticity. We’re using Google wave for this collaboration, and I must say it is an excellent co-authorship tool. There is nothing quite so neat as watching your ideas flow and meld together in real time. There are now new built in document templates that make these kinds of projects a blast. As an added bonus, all edits are identified and tracked in real time, letting you keep easy track of who wrote what. One of the most suprising things to come out of this collaboration is the newness of the thoughts. Whatever it is we end up arguing, it is definetely not reducible to the sum of it’s parts. As a teaser, I thought I’d post a thread from the wave I made this morning. This is basically just me rambling on about consciousness and plasticity after reading the results of our wave. I wish I could post the movie of our edits, but that will have to wait for the paper’s submission.

I have an idea I want to work in that was provoked by this paper:
http://www.jneurosci.org/cgi/content/abstract/30/18/6205

Somewhere in here I still feel a nagging paradox, but I can’t seem to put my finger on it. Maybe I’m simply trying to explain something I don’t have an explanation for. I’m not sure. Consider this a list of thoughts that may or may not have any relationship to the kind of account we want to make here.

They basically show that different synthesthetic experiences have different neural correlates in the structural brain matter. I think it would be nice to tie our paper to the (likely) focus of the other papers; the idea of changing qualia / changing NCCs. Maybe we can argue that, due to neural plasticity, we should not expect ‘neural representations’ for sensory experience between any two adults to be identical; rather we should expect that every individual develops their own unique representational qualia that are partially ineffable. Then we can argue that it this is precisely why we must rely on narrative scaffolding to make sense of the world; it is only through practice with narrative, engendered by frontal plasticity, that we can understand the statistical similarities between our qualia and others. Something is not quite right in this account though… and our abstract is basically fine as is.

So, I have my own unique qualia that are constantly changing- my qualia and NCCs are in dynamical flux with one another. However, my embodiment pre-configures my sensory experience to have certain common qualities across the species. Narrative explanations of the world are grounded in capturing this intersubjectivity; they are linguistic representations of individual sense impressions woven together by cultural practices and schema. What we want to say is that, I am able to learn about the world through narrative practice precisely because I am able to map my own unique sensory representations onto others.

I guess that last part of what I said is still weak, but it seems like this could be a good element to explore in the abstract. It keeps us from being too far away from the angle of the call though, maybe. I can’t figure out exactly what I want to say. There are a few elements:

  • Narratives are co-created, coherent, shareable, complex representations of the world that encode temporality, meaning, and intersubjectivity.
  • I’m able to learn about these representations of the world through narrative practice; by mapping my own unique dynamic sensory experience to the sensory and folk psychological narratives of others.
  • Narrative encodes sensory experience in ways that transcend the limits of personal qualia; they are offloaded and are no longer dynamic in the same way.
  • Sensory experience is in constant flux and can be thrown out of alignment with narrative, as in the case of most psychopathy.
  • I need some way to structure this flux; narrative is intersubjective and it provides second order qualia??
  • Narrative must be plastic as it is always growing; the relations between events, experiences, and sensory representations must always be shifting. Today I may really enjoy the smell of flowers and all the things that come with them (memory of a past girlfriend, my enjoyment of things that smell sweet, the association I have with hunger). But tommorow I might get buried alive in some flowers; now my sensory representation for flowers is going to have all new associations. I may attend to a completely different set of salient factors; I might find that the smell now reminds me of a grave, that I remember my old girlfriend was a nasty bitch, and that I’m allergic to sweet things. This must be reflected in the connective weights of the sensory representations; the overall connectivity map has been altered because a node (the flower node) has been drastically altered by a contra-narrative sensory trauma.
  • I think this is a crucial account and it helps explain the role of the default mode in consciousness. On this account, the DMN is the mechanism driving reflective, spontaneous narrativization of the world. These oscillations are akin to the constant labeling and scanning of my sensory experience. That they in sleep probably indicates that this process is highly automatic and involved in memory formation. As introspective thoughts begin to gain coherency and collude together, they gain greater roles in my over all conscious self-narrative.
  • So I think this is what I want to say: our pre-frontal default mode is system is in constant flux. The nodes are all plastic, and so is the pattern of activations between them. This area is fundamentally concerned with reflective-self relatedness and probably develops through childhood interaction. Further, there is an important role of control here. I think that a primary function of social-constructive brain areas is in the control of action. Early societies developed complex narrative rule systems precisely to control and organize group action. This allowed us to transcend simple brute force and begin to coordinate action and to specialize in various agencies. The medial prefrontal cortex, the central node, fundementally invoked in acts of social cognition and narrative comprehension, has massive reciprocal connectivity to limbic areas, and also pre-frontal areas concerned with reward and economic decision making.
  • We need a plastic default mode precisely to allow for the kinds of radical enculturation we go through during development. It is quite difficult to teach an infant, born with the same basic equipment as a caveman, the intricacies of mathematics and philosophy. Clearly narrative comprehension requires a massive amount of learning; we must learn all of the complex cultural nuances that define us as modern humans.
  • Maybe sensory motor coupling and resonance allow for the simulation of precise spatiotemporal activity patterns. This intrinsic activity is like a constant ‘reading out’ of the dynamic sensory representations that are being constantly updated, through neuroplasticity; whatever the totality of the connection weights, that is my conscious narrative of my experience.
  • Back to the issue of control. It’s clear to me that the prefrontal default system is highly sensitive to intersubjective or social information/cues. I think there is really something here about offloading intentions, which are relatively weak constructions, into the group, where they can be collectively acted upon (like in the drug addict/rehab example). So maybe one role of my narration system is simply to vocalize my sensory experience (I’m craving drugs. I can’t stop craving drugs) so that others can collectively act on them.

Well there you have it. I have a feeling this is going to be a great paper. We’re going to try and flip the whole debate on it’s head and argue for a central role of plasticity in embodied and narrative consciousness. It’s great fun to be working with Gary again; his mastery of philosophy of mind and phenomenology are quite fearsome, and we’ve been developing these ideas forever. I’ll be sure to post updates from GWave as the project progresses.

Snorkeling ’the shallows’: what’s the cognitive trade-off in internet behavior?

Posted in internet, Neuroscience, phenomenology, Philosophy, research, social media, Uncategorized by

I am quite eager to comment on the recent explosion of e-commentary regarding Nicolas Carr’s new book. Bloggers have already done an excellent job summarizing the response to Carr’s argument. Further, Clay Shirky and Jonah Lehrer have both argued convincingly that there’s not much new about this sort of reasoning. I’ve also argued along these lines, using the example of language itself as a radical departure from pre-linguistic living. Did our predecessors worry about their brains as they learned to represent the world with odd noises and symbols?

Surely they did not. And yet we can also be sure that the brain underwent a massive revolution following the acquisition of language. Chomsky’s linguistics would of course obscure this fact, preferring us to believe that our linguistic abilities are the amalgation of things we already possessed: vision, problem solving, auditory and acoustic control. I’m not going to spend too much time arguing against the modularist view of cognition however; chances are if you are here reading this, you are already pretty convinced that the brain changes in response to cultural adaptations.

It is worth sketching out a stock Chomskyian response however. Strict nativists, like Chomsky, hold that our language abilities are the product of an innate grammar module. Although typically agnostic about the exact source of this module (it could have been a genetic mutation for example), nativists argue that plasticity of the brain has no potential other than slightly enhancing or decreasing our existing abilities. You get a language module, a cognition module, and so on, and you don’t have much choice as to how you use that schema or what it does. The development of anguage on this view wasn’t something radically new that changed the brain of its users but rather a novel adaptation of things we already and still have.

To drive home the point, it’s not suprising that notable nativist Stephen Pinker is quoted as simply not buying the ‘changing our brains’ hypothesis:

“As someone who believes both in human nature and in timeless standards of logic and evidence, I’m skeptical of the common claim that the Internet is changing the way we think. Electronic media aren’t going to revamp the brain’s mechanisms of information processing, nor will they supersede modus ponens or Bayes’ theorem. Claims that the Internet is changing human thought are propelled by a number of forces: the pressure on pundits to announce that this or that “changes everything”; a superficial conception of what “thinking” is that conflates content with process; the neophobic mindset that “if young people do something that I don’t do, the culture is declining.” But I don’t think the claims stand up to scrutiny.”

Pinker makes some good points- I agree that a lot of hype is driven by the kinds of thinking he mentions. Yet, I do not at all agree that electronic media cannot and will not revamp our mechanisms for information processing. In contrast to the nativist account, I think we’ve better reason than ever to suspect that the relation between brain and cognition is not 1:1 but rather dynamic, evolving with us as we develop new tools that stimulate our brains in unique and interesting ways.

The development of language massively altered the functioning of our brain. Given the ability to represent the world externally, we no longer needed to rely on perceptual mechanisms in the same way. Our ability to discriminate amongst various types of plant, or sounds, is clearly sub-par to that of our non-linguistic brethren. And so we come full circle. The things we do change our brains. And it is the case that our brains are incredibly economical. We know for example that only hours after limb amputation, our somatosensory neurons invade the dormant cells, reassigning them rather than letting them die off. The brain is quite massively plastic- Nicolas Carr certainly gets that much right.

Perhaps the best way to approach this question is with an excerpt from social media. I recently asked of my fellow tweeps,

To which an astute follower replied:

Now, I do realize that this is really the central question in the ‘shallows’ debate. Moving from the basic fact that our brains are quite plastic, we all readily accept that we’re becoming the subject of some very intense stimulation. Most social media, or general internet users, shift rapidly from task to task, tweet to tweet. In my own work flow, I may open dozens and dozens of tabs, searching for that one paper or quote that can propel me to a new insight. Sometimes I get confused and forget what I was doing. Yet none of this interferes at all with my ‘deep thinking’. Eventually I go home and read a fantastic sci-fi book like Snowcrash. My imagination of the book is just as good as ever; and I can’t wait to get online and start discussing it. So where is the trade-off?

So there must be a trade-off, right? Tape a kitten’s eyes shut and its visual cortex is re-assigned to other sensory modalities. The brain is a nasty economist, and if we’re stimulating one new thing we must be losing something old. Yet what did we lose with language? Perhaps we lost some vestigial abilities to sense and smell. Yet we gained the power of the sonnet, the persuasion of rhetoric, the imagination of narrative, the ability to travel to the moon and murder the earth.

In the end, I’m just not sure it’s the right kind of stimulation. We’re not going to lose our ability to read in fact, I think I can make an extremely tight argument against the specific hypothesis that the internet robs us of our ability to deep-think. Deep thinking is itself a controversial topic. What exactly do we mean by it? Am I deep thinking if I spend all day shifting between 9 million tasks? Nicolas Carr says no, but how can he be sure those 9 million tasks are not converging around a central creative point?

I believe, contrary to Carr, that internet and social media surfing is a unique form of self stimulation and expression. By interacting together in the millions through networks like twitter and facebook, we’re building a cognitive apparatus that, like language, does not function entirely within the brain. By increasing access to information and the customizability of that access, we’re ensuring that millions of users have access to all kinds of thought-provoking information. In his book, Carr says things like ‘on the internet, there’s no time for deep thought. it’s go go go’. But that is only one particular usage pattern, and it ignores ample research suggesting that posts online may in fact be more reflective and honest than in-person utterances (I promise, I am going to do a lit review post soon!)

Today’s internet user doesn’t have to conform to whatever Carr thinks is the right kind of deep-thought. Rather, we can ‘skim the shallows’ of twitter and facebook for impressions, interactions, and opinions. When I read a researcher, I no longer have to spend years attending conferences to get a personal feel for them. I can instead look at their wikipedia, read the discussion page, see what’s being said on twitter. In short, skimming the shallows makes me better able to choose the topics I want to investigate deeply, and lets me learn about them in whatever temporal pattern I like. Youtube with a side of wikipedia and blog posts? Yes please. It’s a multi-modal whole brain experience that isn’t likely to conform to ‘on/off’ dichotomies. Sure, something may be sacrificed, but it may not be. It might be that digital technology has enough of the old (language, vision, motivation) plus enough of the new that it just might constitute or bring about radically new forms of cognition. These will undoubtably change or cognitive style, perhaps obsoleting Pinker’s Bayesian mechanisms in favor of new digitally referential ones.

So I don’t have an answer for you yet ToddStark. I do know however, that we’re going to have to take a long hard look at the research review by Carr. Further, it seems quite clear that there can be no one-sided view of digital media. It’s not anymore intrinsically good or bad than language. Language can be used to destroy nations just as it can tell a little girl a thoughtful bed time story. If we’re to quick to make up our minds about what internet-cognition is doing to our plastic little brains, we might miss the forest for the trees. The digital media revolution gives us the chance to learn just what happens in the brain when its’ got a shiny new tool. We don’t know the exact nature of the stimulation, and finding out is going to require a look at all the evidence, for and against. Further, it’s a gross oversimplification to talk about internet behavior as ‘shallow’ or ‘deep’. Research on usage and usability tells us this; there are many ways to use the internet, and some of them probably get us thinking much deeper than others.

A defense of vegetarian fMRI (1/2)

Posted in images, Neuroscience, research by

Recently there’s been much ado about a newly published fMRI study of empathetic responding in vegetarians, vegans, and omnivores. The study isn’t perfect, which the authors admit, but I find it interesting and relatively informative for an fMRI paper. The Neurocritic doesn’t, rather he raises some seemingly serious issues with the study. I promised on twitter I’d defend my claim that the study is good (and that neurocritic could do better). But first, a motivated ramble to distract and confuse you.

As many of you might realize, neuroscience could be said to be going through something like puberty. While the public remains infatuated with every poorly worded research report, researchers within the neurosciences have to view brain mapping through an increasingly skeptical lens. This is a good thing: science progresses through the introduction and use of new technologies and the eventual skeptical refinement of their products.

And certainly there is plenty of examples shoddy neuroscience out there, whether it’s reports of voodoo correlations or inconsistencies between standard fMRI analyses packages. Properly executed, attention to these issues and a healthy skepticism of the methods will ultimately result in a refined science. Yet we must also be careful to apply the balm of skepticism in a refined manner: neuroscientists are people to, and we work in an increasingly competitive field where there are few well-defined standards and even less clarity.

Take an example from my lab that happened just today.  We’re currently analyzing some results from a social cognition experiment my colleague Kristian Tylen and I conducted last year. Like many fMRI results, our hypotheses (which were admitable a bit vague when we made them) were not exactly supported by our findings. Rather we ended up with a scattered series of blobs that appeared to mostly center on early visual areas. This is obviously boring and unpublishable, and after some time we decided to do a small volume correction on some areas we’d discussed in a published paper. This finally revealed some interesting findings somewhere around the TPJ, which brings me to the point of this story.

My research has thus far mostly focused on motor and prefrontal regions. We in neuroimaging can often fall victim to what I call ‘blob blind sight’ where we focus so greatly on a single area or handful of areas that we forget there’s’ a wide world of cortex out there. Imagine my surprise when I tried to get clear about whether our finding was situated in exactly the pSTS, TPJ, or nearby inferior parietal lobule (IPL) only to discover that these three areas are nearly indistinguishable from one another anatomically.

All of these regions are involved in different aspects of social cognition, and across the literature there are no clear anatomical differentiation between them. In many cases, researchers will just lump them together as pSTS/TPJ, regardless of the fact that a great deal of research has gone on explicitly differentiating them. Now what does one do with a blob that lands somewhere in the middle, overlapping all three? More specifically, imagine the case where your activation foci lands smack dab in the middle, or a few voxels to the left. Is it TPJ? Or IPL? Or is it really the conjunction of all three, and if so, how does one make sense of that given the wide array of functions and connectivity patterns for these areas. IPL is a part of the default mode, whereas TPJ and pSTS are not. It’s really quite a mess, and the answer you choose will likely depend upon the interpretation you give, given the vast variety of functions allocated to these three regions.

The point of all this, which begins to lead to my critique of TNC critique, is that it is not a simple matter of putting ones foot down and claiming that the lack of an expected activation or the presence of an unexpected one is damning or indicative of bad science. It’s an inherent problem in a field where hundreds of papers are published monthly with massive tables of activation foci. To say that a study has gone awry because they don’t report your favorite area misses the point. What’s more important is to evaluate the methods and explain the totality of the findings reported.

So that’s one huge issue confronting most researchers. Although there are some open source ‘foci databases’ out there, they are underused and hard to rely on. One can of course try to pinpoint the exact area, but in reality the chance that you’ll have such a focused blob is pretty unlikely. Rather, researchers have to rely on extra-scanner measures and common sense to make any kind of interesting theoretical inferences from fMRI. This post was meant to be a response to The Neurocritic, who took issue with my taking issue of his taking issue with a certain vegetarian fmri study… but I’m already an hour late coming home from work and I’m afraid I’ve failed to deliver. I did take the time this afternoon to go thoroughly through both the paper and TNC’s response however, and I think I’ve got a pretty compelling argument. Next time: why the neurocritic is plain wrong ;)

Site update

Posted in research, updates by

As of today, neuroconscience.com is now redirecting to my wordpress.com blog. I did this to increase security- it appears my old blog may have been hacked- as well as usability. As I am still ironing out the kinks of the move, you may see little bits of construction dust here and there. This is also probably only a temporary solution- ideally I plan to move back to neuroconscience.com once I can get everything working correctly.

As for future posts, I’ve been on a serious hiatus due to work related issues. I’m currently trying to translate the ideas you see here to some summer experiments, a process that has proven extremely difficult. Hopefully things will really start to pick up in the next few weeks. In the meantime, updates will be sporadic at best.