Tag Archives: science

Videos on computational neuroscience – by me!

I haven’t been blogging much, and that is partly because I have been organizing weekly meetings devoted to computational neuroscience. Between January and July, my friends and I did a series on dynamical systems theory in neuroscience. I created a YouTube channel for the videos.

Here’s the playlist for the dynamical systems series:

This month we started talking about Stephen Grossberg’s new book, ‘Conscious Mind, Resonant Brain’. Grossberg set up the department where I did my PhD, and his ideas suffuse how I think about mind and brain. I’m uploading the videos as they happen. Here’ the playlist:

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Which is the most evolutionarily advanced part of the human brain?

This is a potentially controversial issue, since there is no consensus yet on the evolution of the brain, beyond a very coarse-grained chronology. Broadly speaking, neocortical areas are new, hence the term “neo-cortex”. But among cortical areas, there is still some disagreement about which areas emerged most recently in primates.

Based on what we know about development in the womb, along with structural findings, my labmates, who are neuroanatomists, suggest that the “eulaminate” areas — the ones that have sharply defined layers — may be the most recent, evolutionarily, compared to the “agranular” and “dysgranular” cortices, which have less sharply defined layers. These less sharply defined areas are also labeled as “limbic”.

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A Clockwork Orange? (A brief musing on the concept of a neural “code”)

I was asked this question on Quora:

Are there many layers of neural codes from the human retina to the optic nerve and the optic nerve to the brain, or are they essentially same signals relayed?

Here’s how I responded:

Here’s a question: in a system composed of clockwork, is there a “code”?

I ask this because I find that the “code” metaphor is often misleading when thinking about biology. Codes are composed of symbols. But it is not clear that neurons communicate using symbols.

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What are emotions?

What indeed?

My research is on cognitive-emotional interaction, so I suppose I am qualified to answer this question. 🙂

But my answer cannot be the answer, since there is actually no consensus among scientists concerning the definition of emotions.

[Illustration of grief from Charles Darwin’s book The Expression of the Emotions in Man and Animals.]

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Dopamine is not the “feel good” molecule (and the very concept of a feel good molecule is meaningless)

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Dopamine is not the feel good molecule or the basis of pleasure. The idea that any molecule considered in isolation could be the basis of a subjective experience is basically nonsense.

For people who can’t really reason through this idea, there is plenty of experimental evidence showing the complexity of each and every “celebrity” neurochemical — dopamine, serotonin, oxytocin, and so on.

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What is neuroplasticity?

I was asked this question on Quora:

Can you explain to a layman what neuroplasticity entails?

Neuroplasticity is the umbrella term for all of the brain’s mechanisms for learning and memory.

Since the average layperson already knows about learning and memory, I’m not sure whether there are any interesting implications.

Unless of course you are surprised that the brain is involved in learning and memory. Then the implications are vast. 🙂

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No New Neurons? No Problem!

This answer was written in response to the following Quora question:

New research has found no neurogenesis in human adults, could this mean there is none or could it mean that neural stem cells are undetectable with the used techniques? What are your thoughts on this?

It’s good that you’re thinking of such things, since that is exactly what researchers themselves have to do, and what reviewers do. In order to show that the method works, there have to be adequate controls as part of the experiment.

And this is in fact the case. The paper would not have been published without controls.

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“The first rule of intelligence: Don’t talk about your intelligence”

That line is from an article in The Atlantic about how poor people are at self-assessment:

People Don’t Actually Know Themselves Very Well

“The first rule of intelligence: Don’t talk about your intelligence. It’s something you prove, not something you claim. As comedian Patton Oswalt quipped about humor, the only person who goes around saying “I’m funny” is a not-funny person. If you were really funny, you’d just make people laugh.”

To me this kind of thing is pretty obvious, but I guess some people really need to be reminded of it.

Here’s another paragraph with several important reminders, particularly for people who blather about intelligence and cognitive biases:

“This is why people consistently overestimate their intelligence, a pattern that seems to be more pronounced among men than women. It’s also why people overestimate their generosity: It’s a desirable trait. And it’s why people fall victim to my new favorite bias: the I’m-not-biased bias, where people tend to believethey have fewer biases than the average American. But you can’t judge whether you’re biased, because when it comes to yourself, you’re the most biased judge of all. And the more objective people think they are, the more they discriminate, because they don’t realize how vulnerable they are to bias.”

Are mental disorders the same as brain disorders? Maybe not!

I am currently reading an excellent paper that will be published in Behavioral and Brain Sciences soon. It raises some very important issues with popular conceptions of mental illness.

Brain disorders? Not really… Why network structures block reductionism in psychopathology research

These two figures capture some of the key points:

Here is the abstract:

“In the past decades, reductionism has dominated both research directions and funding policies in clinical psychology and psychiatry. However, the intense search for the biological basis of mental disorders has not resulted in conclusive reductionist explanations of psychopathology. Recently, network models have been proposed as an alternative framework for the analysis of mental disorders, in which mental disorders arise from the causal interplay between symptoms. In this paper, we show that this conceptualization can help understand why reductionist approaches in psychiatry and clinical psychology are on the wrong track. First, symptom networks preclude the identification of a common cause of symptomatology with a neurobiological condition, because in symptom networks there is no such common cause. Second, symptom network relations depend on the content of mental states and as such feature intentionality. Third, the strength of network relations is highly likely to partially depend on cultural and historical contexts as well as external mechanisms in the environment. Taken together, these properties suggest that, if mental disorders are indeed networks of causally related symptoms, reductionist accounts cannot achieve the level of success associated with reductionist disease models in modern medicine. As an alternative strategy, we propose to interpret network structures in terms of D. C. Dennett’s (1987) notion of real patterns, and suggest that, instead of being reducible to a biological basis, mental disorders feature biological and psychological factors that are deeply intertwined in feedback loops. This suggests that neither psychological nor biological levels can claim causal or explanatory priority, and that a holistic research strategy is necessary for progress in the study of mental disorders.”

Behavioral and Brain Sciences is one of the premier journals for “big thinking” in cognitive science and neuroscience, so it’s great to see these ideas there.