LMAYQ: seriously deep questions

And now, let me answer your Seriously Deep Questions. All questions answered can be found in the LMAYQ index. And as always these are real true search terms that the all-knowing Internet directed to The Cellular Scale. Let's begin.

Thoughts on grass (source)

 1. "Do thoughts look like trees?" 

Great question. Lots of things look like trees, certainly neurons do. But thoughts themselves? 

It is my personal opinion that thoughts do not actually look like anything. I've dissected many a brain and haven't ever seen one. However, let's suppose thoughts look like something, what would they look like?

One possibility is that the thought looks like what you are thinking about. A pretty ancient idea is that there are actually two of every object, one that is external (the actual object), and one that is internal which is our representation of that object. This can be taken quite literally in which case if you are looking at or thinking about a tree, your thought will look like a tree, but if you are thinking about a dog, your thought will look like a dog. This strikes me as unlikely.

So another way to look at it is what does the brain look like when it is having a thought? In this case there is some support for the 'thought looks like what you are thinking' hypothesis, but it is very limited.

Do thoughts look like nets? (source)

Above is a famous example of how a visual stimulus can be reflected in the brain in a very literal way. In this case a monkey looks at a grid and the activation pattern in the brain looks like a grid. But these days 'thoughts' usually look like this:

thinking (source)

And there is no obvious or literal relationship between the shape of the fMRI image and the thought that is thunk.


 2. "Why Neuroscience?"


Because neuroscience is our best chance at answering important questions like 'what do thoughts look like?' and 'How do we know what we know?'


 3. "Do neurons tell you how to move or do they fire in response?"

Another excellent and deep question. The answer is (of course) that they do both. 

People used to think of the brain as a black box, where sensory input comes in (like through your eyes) and gets 'processed' by the brain and a motor output comes out (like through your hands).

All of these steps, the sensory input, the motor output, and the processing in between take neurons.
But of course there is the Venus flytrap which doesn't have 'neurons' per se, but does receive sensory input and generate motor output.

But the processing part of this process, the black box, is really complicated. There really is an unanswered question there about whether neurons are responding to something or telling something. When studies find that mirror neurons fire 'in response to' seeing actions performed, or that some amygdala neurons fire in response to pictures of animals, the question is always why are these neurons firing? Are the neurons telling another part of the brain 'this is an animal'? or are the neurons responding to that information? 

© TheCellularScale

Cortical spine growth and learning how to eat pasta

There are two aspects to neuron shape. One is the pattern of dendritic or axonal branching, and the other is the pattern of spines. Spines are the little protrusions that come off of the dendrite often receiving synaptic inputs.

spines on a pyramidal neuron (source)

Because these spines are associated with excitatory synapses, and because synapse development is thought to be the cellular basis of learning, it makes sense that spines would grow when we learn.

But how would they grow exactly?

Using transcranial two-photon microscopy (a window into the brain of a living mouse), Fu et al. (2012) have caught images of neural learning in action.

A window into the mouse brain (source)

 The authors used two learning tasks to investigate how spines grow during learning. In the "reaching" task, mice had to reach their paw into a slit and grab a seed. In the "capellini handling task" the mouse is given a 2.5 cm length of (I am not making this up) angel hair pasta and learns how to handle it for eating. learning is measured by how fast the mouse eats the pasta. 

learning how to eat pasta makes mouse cortical spines grow (source)

They found that spines grow during learning (not too surprising). But spines also grow when the mouse is exposed to a motor-enriched environment (like a mouse-sized playground).

Fu et al. 2012 (Figure 2C+D)

The interesting difference between learning a specific task rather than just playing is that the spines grow in distinct clusters when the mice are taught a learning task. C shows the total spine growth, while D shows the proportion of clustered spines to total spines. Reach only means the mice were only taught the reaching task, and cross-training means they were taught both the reaching task and the pasta handling task. 

The authors explain two possible functions for these spine clusters:

"Positioning multiple synapses between a pair of neurons in close proximity allows nonlinear summation of synaptic strength, and potentially increases the dynamic range of synaptic transmission well beyond what can be achieved by random positioning of the same number of synapses."

Meaning spines that are clustered and receive inputs from the same neuron have more power to influence the cell than spines further apart.

"Alternatively, clustered new spines may synapse with distinct (but presumably functionally related) presynaptic partners. In this case, they could potentially integrate inputs from different neurons nonlinearly and increase the circuit’s computational power. "

Meaning that maybe the spines don't receive input from the same neuron, but are clustered so they can integrate signals across neurons more powerfully.

And of course...

"Distinguishing between these two possibilities would probably require circuit reconstruction by electron microscopy following in vivo imaging to reveal the identities of presynaptic partners of newly formed spines."

 More work is needed to figure out what is really going on.

 © TheCellularScale


Fu M, Yu X, Lu J, & Zuo Y (2012). Repetitive motor learning induces coordinated formation of clustered dendritic spines in vivo. Nature, 483 (7387), 92-5 PMID: 22343892