Neuroconscience

The latest thoughts, musings, and data in cognitive science and neuroscience.

Tag: Brains

Are we watching a paradigm shift? 7 hot trends in cognitive neuroscience according to me

brainonfire

In the spirit of procrastination, here is a random list I made up of things that seem to be trending in cognitive neuroscience right now, with a quick description of each. These are purely pulled from the depths of speculation, so please do feel free to disagree. Most of these are not actually new concepts, it’s more about they way they are being used that makes them trendy areas.


7 hot trends in cognitive neuroscience according to me

Oscillations

Obviously oscillations have been around for a long time, but the rapid increase of technological sophistication for direct recordings (see for example high density cortical arrays and deep brain stimulation + recording) coupled with greater availability of MEG (plus rapid advance in MEG source reconstruction and analysis techniques) have placed large-scale neural oscillations at the forefront of cognitive neuroscience. Understanding how different frequency bands interact (e.g. phase coupling) has become a core topic of research in areas ranging from conscious awareness to memory and navigation.

Complex systems, dynamics, and emergence

Again, a concept as old as neuroscience itself, but this one seems to be piggy-backing on several trends towards a new resurgence. As neuroscience grows bored of blobology, and our analysis methods move increasingly towards modelling dynamical interactions (see above) and complex networks, our explanatory metaphors more frequently emphasize brain dynamics and emergent causation. This is a clear departure from the boxological approach that was so prevalent in the 80’s and 90’s.

Direct intervention and causal inference

Pseudo-invasive techniques like transcranial direct-current stimulation are on the rise, partially because they allow us to perform virtual lesion studies in ways not previously possible. Likewise, exponential growth of neurobiological and genetic techniques has ushered in the era of optogenetics, which allows direct manipulation of information processing at a single neuron level. Might this trend also reflect increased dissatisfaction with the correlational approaches that defined the last decade? You could also include steadily increasing interest in pharmacological neuroimaging under this category.

Computational modelling and reinforcement learning

With the hype surrounding Google’s £200 million acquisition of Deep Mind, and the recent Nobel Prize award for the discovery of grid cells, computational approaches to neuroscience are hotter than ever. Hardly a day goes by without a reinforcement learning or similar paper being published in a glossy high-impact journal. This one takes many forms but it is undeniable that model-based approaches to cognitive neuroscience are all the rage. There is also a clear surge of interest in the Bayesian Brain approach, which could almost have it’s own bullet point. But that would be too self serving  ;)

Gain control

Gain control is a very basic mechanism found throughout the central nervous system. It can be understood as the neuromodulatory weighting of post-synaptic excitability, and is thought to play a critical role in contextualizing neural processing. Gain control might for example allow a neuron that usually encodes a positive prediction error to ‘flip’ its sign to encode negative prediction error under a certain context. Gain is thought to be regulated via the global interaction of neural modulators (e.g. dopamine, acetylcholine) and links basic information theoretic processes with neurobiology. This makes it a particularly desirable tool for understanding everything from perceptual decision making to basic learning and the stabilization of oscillatory dynamics. Gain control thus links computational, biological, and systems level work and is likely to continue to attract a lot of attention in the near future.

Hierarchies that are not really hierarchies

Neuroscience loves its hierarchies. For example, the Van Essen model of how visual feature detection proceeds through a hierarchy of increasingly abstract functional processes is one of the core explanatory tools used to understand vision in the brain. Currently however there is a great deal of connectomic and functional work pointing out interesting ways in which global or feedback connections can re-route and modulate processes from the ‘top’ directly to the ‘bottom’ or vice versa. It’s worth noting this trend doesn’t do away with the old notions of hierarchies, but instead just renders them a bit more complex and circular. Put another way, it is currently quite trendy to show ‘the top is the bottom’ and ‘the bottom is the top’. This partially relates to the increased emphasis on emergence and complexity discussed above. A related trend is extension of what counts as the ‘bottom’, with low-level subcortical or even first order peripheral neurons suddenly being ascribed complex abilities typically reserved for cortical processes.

Primary sensations that are not so primary

Closely related to the previous point, there is a clear trend in the perceptual sciences of being increasingly liberal about how ‘primary’ sensory areas really are. I saw this first hand at last year’s Vision Sciences Society which featured at least a dozen posters showing how one could decode tactile shape from V1, or visual frequency from A1, and so on. Again this is probably related to the overall movement towards complexity and connectionism; as we lose our reliance on modularity, we’re suddenly open to a much more general role for core sensory areas.


Interestingly I didn’t include things like multi-modal or high resolution imaging as I think they are still actually emerging and have not quite fully arrived yet. But some of these – computational and connectomic modelling for example – are clearly part and parcel of contemporary zeitgeist. It’s also very interesting to look over this list, as there seems to be a clear trend towards complexity, connectionism, and dynamics. Are we witnessing a paradigm shift in the making? Or have we just forgotten all our first principles and started mangling any old thing we can get published? If it is a shift, what should we call it? Something like ‘computational connectionism’ comes to mind. Please feel free to add points or discuss in the comments!

My response to Carr and Pinker on Media Plasticity

Our ongoing discussion regarding the moral panic surrounding Nicolas Carr’s book The Shallows continues over at Carr’s blog today, with his recent response to Pinker’s slamming the book. I maintain that there are good and bad (frightening!!) things in both accounts. Namely, Pinker’s stolid refusal to acknowledge the research I’ve based my entire PhD on, and Carr’s endless fanning of the one-sided moral panic.

Excerpt from Carr’s Blog:

Steven Pinker and the Internet

And then there’s this: “It’s not as if habits of deep reflection, thorough research and rigorous reasoning ever came naturally to people.” Exactly. And that’s another cause for concern. Our most valuable mental habits – the habits of deep and focused thought – must be learned, and the way we learn them is by practicing them, regularly and attentively. And that’s what our continuously connected, constantly distracted lives are stealing from us: the encouragement and the opportunity to practice reflection, introspection, and other contemplative modes of thought. Even formal research is increasingly taking the form of “power browsing,” according to a 2008 University College London study, rather than attentive and thorough study. Patricia Greenfield, a professor of developmental psychology at UCLA, warned in a Science article last year that our growing use of screen-based media appears to be weakening our “higher-order cognitive processes,” including “abstract vocabulary, mindfulness, reflection, inductive problem solving, critical thinking, and imagination.”

As someone who has enjoyed and learned a lot from Steven Pinker’s books about language and cognition, I was disappointed to see the Harvard psychologist write, in Friday’s New York Times, a cursory op-ed column about people’s very real concerns over the Internet’s influence on their minds and their intellectual lives. Pinker seems to dismiss out of hand the evidence indicating that our intensifying use of the Net and related digital media may be reducing the depth and rigor of our thoughts. He goes so far as to assert that such media “are the only things that will keep us smart.” And yet the evidence he offers to support his sweeping claim consists largely of opinions and anecdotes, along with one very good Woody Allen joke.

Right here I would like to point out the kind of leap Carr is making. I’d really like a closer look at the supposed evidence demonstrating  “our intensifying use of the Net and related digital media may be reducing the depth and rigor of our thoughts.” This is a huge claim! How does one define the ‘depth’ and ‘rigor’ of our thoughts? I know of exactly one peer-reviewed high impact paper demonstrating a loss of specifically executive function in heavy-media multi-taskers. While there is evidence that generally speaking, multi-tasking can interfere with some forms of goal-directed activity, I am aware of no papers directly linking specific forms of internet behavior to a drop in executive function. Furthermore, the HMM paper included in it’s measure of multi-tasking ‘watching tv’, ‘viewing funny videos’, and ‘playing videogames’. I don’t know about you, but for me there is definitely a difference between ‘work’ multitasking, in which I focus and work through multiple streams, and ‘play’ multitasking, in which I might casually surf the net while watching TV. The second claim is worse- what exactly is ‘depth’? And how do we link it to executive functioning?

Is Carr claiming people with executive function deficits are incapable or impaired in thinking creatively? If it takes me 10 years to publish a magnum opus, have I thought less deeply than the author that cranks out a feature length popular novel every 2 years? Depth involves a normative judgment of what separates ‘good’ thinking from ‘bad’ thinking, and to imply there is some kind of peer-reviewed consensus here is patently false. In fact, here is a recent review paper on fmri creativity research (is this depth?) indicating that the existing research is so incredibly disparate and poorly defined as to be untenable. That’s the problem with Carr’s claims- he oversimplifies both the diversity of internet usage and the existing research on executive and creative function. To be fair to Carr, he does go on to do a fair job of dismantling Pinker’s frighteningly dogmatic rejection of generalizable brain plasticity research:

One thing that didn’t surprise me was Pinker’s attempt to downplay the importance of neuroplasticity. While he acknowledges that our brains adapt to shifts in the environment, including (one infers) our use of media and other tools, he implies that we need not concern ourselves with the effects of those adaptations. Because all sorts of things influence the brain, he oddly argues, we don’t have to care about how any one thing influences the brain. Pinker, it’s important to point out, has an axe to grind here. The growing body of research on the adult brain’s remarkable ability to adapt, even at the cellular level, to changing circumstances and new experiences poses a challenge to Pinker’s faith in evolutionary psychology and behavioral genetics. The more adaptable the brain is, the less we’re merely playing out ancient patterns of behavior imposed on us by our genetic heritage.

Here is my response, posted on Nick’s blog:

Hi Nick,

As you know from our discussion at my blog, I’m not really a fan of the extreme views given by either you or Pinker. However, I applaud the thorough rebuttal you’ve given here to Stephen’s poorly researched response. As someone doing my PhD in neuroplasticity and cognitive technology, it absolutely infuriated me to see Stephen completely handwave away a decade of solid research showing generalizable cognitive gains from various forms of media-practice. To simply ignore findings from, for example the Bavalier lab, that demonstrate reliable and highly generalizable cognitive and visual gains and plasticity is to border on the unethically dogmatic.

Pinker isn’t well known for being flexible within cognitive science however; he’s probably the only person even more dogmatic about nativist modularism than Fodor. Unfortunately, Stephen enjoys a large public following and his work has really been embraced by the anti-religion ‘brights’ movement. While on some levels I appreciate this movement’s desire to promote rationality, I cringe at how great scholars like Dennett and Pinker seem totally unwilling to engage with the expanding body of research that casts a great deal of doubt on the 1980’s era cogsci they built their careers on.

So I give you kudos there. I close as usual, by saying that you’re presenting a ‘sexy’ and somewhat sensationalistic account that while sure to sell books and generate controversy, is probably based more in moral panic than sound theory. I have no doubt that the evidence you’ve marshaled demonstrates the cognitive potency of new media. Further, I’m sure you are aware of the heavy-media multitasking paper demonstrating a drop in executive functioning in HMMs.

However, you neglect in the posts I’ve seen to emphasize what those authors clearly did: that these findings are not likely to represent a true loss of function but rather are indicators of a shift in cognitive style. Your unwillingness to declare the normative element in your thesis regarding ‘deep thought’ is almost as chilling as Pinker’s total refusal to acknowledge the growing body of plasticity research. Simply put, I think you are aware that you’ve conflated executive processing with ‘deep thinking’, and are not really making the case that we know to be true.

Media is a tool like any other. It’s outcome measures are completely dependent on how we use it and our individual differences. You could make this case quite well with your evidence, but you seem to embrace the moral panic surrounding your work. It’s obvious that certain patterns, including the ones probably driving your collected research, will play on our plasticity to create cognitive differences. Plasticity is limited however, and you really don’t play on the most common theme in mental training literature: balance and trade-off. Your failure to acknowledge the economical and often conservative nature of the brain forces me to lump your work in with the decade that preceded your book, in which it was proclaimed that violent video games and heavy metal music would rot our collective minds. These things didn’t happen, except in those who where already at high risk, and furthermore they produced unanticipated cognitive gains. I think if you want to be on the ‘not wrong’ side of history, you may want to introduce a little flexibility to your argument. I guess if it makes you feel better, for many in the next generation of cognition researchers, it’s already too late for a dogmatic thinker like Pinker.

Final thoughts?

A defense of vegetarian fMRI (1/2)

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 ;)

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