# How do human brains represent things?

**URL:** <https://discourse.numenta.org/t/how-do-human-brains-represent-things/3403>\
**Category:** General Neuroscience\
**Created:** [January 31, 2018, 9:21pm UTC](https://discourse.numenta.org/t/how-do-human-brains-represent-things/3403 "2018-01-31T21:21:10Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![Ed\_Pell](https://avatars.discourse-cdn.com/v4/letter/e/6bbea6/32.png) [@Ed\_Pell](https://discourse.numenta.org/u/Ed_Pell)\
**Post date:** [January 31, 2018, 9:21pm UTC](https://discourse.numenta.org/t/how-do-human-brains-represent-things/3403/1 "2018-01-31T21:21:10Z")

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The question I have is how do brains build internal representations:

1. go from general to specific  
or
2. specific to general

Using dog as an example  
dog to legs/tail/head/trunk to tail has tip, legs come in front and back and have orientation and paws on end, head has many features, this can go on tongue is long and wet and warm,…

or

tail tip/paws/nose leads us to tail/leg/head leads us to dog

I am not asking about the sensor system rather the internal mental representation. I note that little kids start drawing people as stick figures with simple legs and arms and head. Sort of the opposite approach used by sensor processing. As the child grows/learns and their representation grows it adds finer and finer features.

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**Author:** ![rhyolight](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.numenta.org/rhyolight/32/3922_2.png) [@rhyolight](https://discourse.numenta.org/u/rhyolight)\
**Post date:** [February 1, 2018, 4:37pm UTC](https://discourse.numenta.org/t/how-do-human-brains-represent-things/3403/2 "2018-02-01T16:37:20Z")

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That is an open question at the core of Numenta’s theory research. We will release a paper when we think we have a clear theory. You’ll certainly want to read this if you have not already:

> [@A Theory of How Columns in the Neocortex Enable Learning the Structure of the World](https://discourse.numenta.org/t/why-does-the-neocortex-have-layers-and-columns-a-theory-of-learning-the-3d-structure-of-the-world/2524):
>
> Fresh off the press from bioarxiv…

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**Author:** ![Bitking](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.numenta.org/bitking/32/3099_2.png) [@Bitking](https://discourse.numenta.org/u/Bitking)\
**Post date:** [February 4, 2018, 3:29am UTC](https://discourse.numenta.org/t/how-do-human-brains-represent-things/3403/3 "2018-02-04T03:29:59Z")

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Funny you should ask that.  
To answer your immediate question: tail and other furry bits build up to the big shaggy dog, with all the doggy bits coexisting and stacking up as splotches of activations across a grid pattern. The doggy does not stand alone, you sort him out of the overall scene so there are other patterns stacking up in the same grid representation all at the same time. [1][2][3]

This doggy grid pattern in the association area is the key to recall the associated doggy related info from other parts of the brain. I don’t expect to find any direct connections to this information at the lower-sensory areas.

Note that a doggy in the other parts of the brain primes recognition in the sensory areas, presumably through forming the same general grid patterns. [4]

> [@How HTM is supposed to deal with spatial invariance?](https://discourse.numenta.org/t/how-htm-is-supposed-to-deal-with-spatial-invariance/3051/16):
>
> As far as HTM and spatial invariance - how does the brain do this? It’s not all done in one go. We know something about the processing that is done in the subcortical structures. We know of place cells, grid cells[7], head position cells[6], border cells (more than likely whisker cell signaling in rodents), and goodness knows what else.[13][14] It is clear that the brain is forming an abstract representation of space. We even know the native data structure format - distributed grids. In part …

> [@How HTM is supposed to deal with spatial invariance?](https://discourse.numenta.org/t/how-htm-is-supposed-to-deal-with-spatial-invariance/3051/34):
>
> Spin, The entorhinal cortex is cortex. One of the takeaway lessons I have gotten from books like “On Intelligence” is that cortex is cortex. The distributed grid representation is clearly spread over a very large chunk of the entorhinal cortex. Why should this computing pattern not be found elsewhere in the cortex? The older allocortex in the hippocampus communicates with the neocortex and distills this representation into chunks like “places.” That strongly suggests that the place information…

> [@How HTM is supposed to deal with spatial invariance?](https://discourse.numenta.org/t/how-htm-is-supposed-to-deal-with-spatial-invariance/3051/38):
>
> Consider the entorhinal cortex and what is being represented: a mixture of the vestibular system, visual representation, self-motion, postural feedback. Perhaps more. When you look at the repeating patterns where do you see any of that in the distributed dispersal that we choose to call a grid system? I see that as the output of a common digestion system that ends up in a “common format.” The grid cells under discussion are a byproduct of explaining the coding that surrounds the hippocampus. Ev…

> [@How HTM is supposed to deal with spatial invariance?](https://discourse.numenta.org/t/how-htm-is-supposed-to-deal-with-spatial-invariance/3051/47):
>
> Let’s do a bit of a deep dive on this - the representation of sounds as a time sequence. This leads to more general questions that seems relevant to this conversation. In programming of computers, we can assign a space for variables, pull them apart and bring them back together as needed for various operations. In neural tissues, we don’t have this luxury. The various sensory streams come in on the same stream with successive waves laying one atop the next. In vision, we have the overall scene…

See also, the Feb 2 hackers hang out.

> [@HTM Hackers' Hangout - Feb 2, 2018](https://discourse.numenta.org/t/htm-hackers-hangout-feb-2-2018/3376):
>
> Whoops! I skipped last month’s hangout. Sorry! So this will be the first hangout of 2018. If anyone wants to suggest topics, please do so in a post. This month, we’ll talk about: Grid cells community fork python 3 siraj raval research update (?) As always, you can watch live or after the event here: Stay tuned to this thread for a link to join the hangout and discuss live immediately before the broadcast.

[1] Understanding mid-level representations in visual processing.

> **[Understanding mid-level representations in visual processing - PubMed](https://pubmed.ncbi.nlm.nih.gov/26053241/)**
>
> It is clear that early visual processing provides an image-based representation of the visual scene: Neurons in Striate cortex (V1) encode nothing about the meaning of a scene, but they do provide a great deal of information about the image features...

[2] Probing intermediate stages of shape processing  
[http://jov.arvojournals.org/article.aspx?articleid=2389021](http://jov.arvojournals.org/article.aspx?articleid=2389021)

[3] Processing context: Asymmetric interference of visual form and texture  
in object and scene interactions

> **[Processing context: Asymmetric interference of visual form and texture in...](https://pubmed.ncbi.nlm.nih.gov/26499389/)**
>
> Substantive evidence has demonstrated that scene-centered global image features influence the processing of objects embedded in complex visual scenes. Conversely, a growing body of work suggests that relevant object information may inherently...

[4] Feedforward and Feedback Processes in Vision

> **[Feedforward and Feedback Processes in Vision](https://www.frontiersin.org/research-topics/2406/feedforward-and-feedback-processes-in-vision)**
>
> The visual system consists of hierarchically organized distinct anatomical areas functionally specialized for processing different aspects of a visual object (Felleman & Van Essen, 1991). These visual areas are interconnected through ascending...