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The hippocampus as a 'predictive map'

deepmind.com

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Re: The hippocampus as a 'predictive map'

#11
post #10

Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence. What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?

Downvoters please explain what's so stupid about my question.

Re: The hippocampus as a 'predictive map'

#13
post #11
post #10

Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence. What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?

Downvoters please explain what's so stupid about my question.

I upvoted you, and I'm actually glad you asked the question despite downvotes. I imagine those who did are of the opinion that essentially you're ascribing too much function to the neurotransmitters themselves, as opposed to the contexts in which the presence of the neurotransmitters are used as signals.

Take a look at this brain schematic here [0]. I vehemently disagree with some of the presented-as-fact ideological aspects of the article, but the depiction of neurotransmitters working differently in different brain regions is illustrative.

i.e., a dopamine molecule does not already constitute a meaningful coordinate system -- it doesn't have a meaning in and of itself, such as "the reward molecule", or euphoria/"feel-good"/"addiction trap"/excitement molecule) in the brain. Rather, the dopamine molecule has locally-interpreted semantics.

To make this more concrete with examples of different aspects of dopamine alone:

- "dopamine is known to encode the confidence level of motor predictions" - Scott Alexander, psychiatrist [1]

- saturating the synaptic cleft between neurons with released (or non-recycled) dopamine is a part some euphoric processes (e.g. drugs, orgasm, gambling) in the striatum negra

- 'excess' (not a simple thing to determine for individuals imo) dopamine is related with psychosis (not per se causally), and antipsychotics are often designed to blunt dopamine transmission

However,

- dopamine transmission is also fundamentally necessary for muscle movement, in the motor cortex

- additionally, the conscious sensation of dopamine is highly dependent upon the frequency of dopaminergic neuron spikes

- Parkinson's disease is (iirc, said to be,) the result of the degeneration of motor neurons; shakiness, problems sleeping;

What does that mean for AI? Well, if we want to go beyond network topology, and start to use new varieties of component substrates, the individual types of signals they represent must either a) be fairly meaningless outside of a specific context or b) not be suited for learning from evidence and generalization of data. Check out [2], [3], and [4] for more.

[0] http://www.nationalgeographic.com/magazine/2017/09/the-addic...

[1] http://slatestarcodex.com/2017/09/12/toward-a-predictive-the...

[2] https://www.edge.org/conversation/stephen_wolfram-ai-the-fut... (not that i am a huge fan of wolfram :P)

[3] https://www.edge.org/responses/what-scientific-concept-would..., ctrl-f "biological"

[4] https://en.wikipedia.org/wiki/Multi-state_modeling_of_biomol...

Re: The hippocampus as a 'predictive map'

#14
post #11
post #10

Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence. What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?

Downvoters please explain what's so stupid about my question.

I didn't downvote, but I have an inkling. I'll share what some of these people may be thinking about your comment. I'll be hyper-critical there because you specifically asked about why someone might have downvoted, so don't take it personally.

"Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence."

Well, it doesn't. Not at all. It looks as if you conflate one very specific AI techique (deep neural networks) with all of AI. Because that one technique is currently insanely popular and has been widely mainstream reported and hyped that makes it look as if your education in that field did not go beyond reading a couple of mainstream media articles. Also, there's a whole huge subfield in AI which is actually defined by it's focus on learning from rewards, which you seem not to be aware of.

"What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?"

Not applicable as written, too broad and unspecific. "Not even wrong." Looks like someone with superficial knowledge is just throwing a few sticks into the blue in the hope that someone might be aroused to a reply which competently tries to make actual sense out of it.

Re: The hippocampus as a 'predictive map'

#15
Hmmm. I'll need to read more closely later and make a real comment, but since when did Gershman or anyone at DeepMind get on the predictive-coding train?

Nonetheless, this kind of algorithm sounds like exactly what I expect from a predictive brain that cares fundamentally about trajectories.

Re: The hippocampus as a 'predictive map'

#16
post #11
post #10

Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence. What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?

Downvoters please explain what's so stupid about my question.

Edit instead of replying to your post.

Re: The hippocampus as a 'predictive map'

#18
post #10

Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence. What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?

Current AI approaches don't have that much to do with the biological brain. Despite the name 'neuronal networks' that we have history to thank for, it's better think of them as just long compositions of functions with a lot of parameters one can tweak.

Historically researchers looked at activation functions that are at least somewhat justified by nature, like the sigmoid. More recently people have focused on the mathematical aspects and figured out that the rectified liner unit `ReLU(x) = max(x, 0)` works just as well if not better for most applications.

Maxout networks (https://arxiv.org/pdf/1302.4389.pdf) are another interesting development in that direction.

There's still lots we can learn from biology, of course; but the last decades rapid advances we saw from deep learning at most barely relate to real brains.

Re: The hippocampus as a 'predictive map'

#19
post #11
post #10

Reading about rewards in AI context makes me wonder, why current AI only focuses on the network topology aspect of natural intelligence. What about the neurotransmitters like dopamine or serotonine? Could they (or more specific: their effects) be key to an AI that feels more “natural“?

Downvoters please explain what's so stupid about my question.

People assume you believe your idea is novel when it's not.
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