Connectionists: How the brain works

[Brian J Mingus]

Is there anything that can't be represented as a single equation or a
really long run on sentence aka model?

With regards to whether new models such as *poesis are accepted by the
field, I think this really boils down to identity politics. Most
researchers are doing a mix of wanting to understand how their brain works
and wanting to help humanity by grokking the brain to solve problems like
epilepsy etc. The part of them that just wants to understand how their
brain works will obviously tend to prefer their own personal rotation of
the space. The part that wants to help humanity sees the need to integrate
new theories, but this conflicts with the ego and these new theories are
more likely to be changed beyond recognition to fit into a given
researchers existing framework than to be supported and encouraged.

Every once in a while a researcher will stumble upon a description so short
and so elegant that it easily transcends the usefulness of all existing
theories. However, the brain isn't like previous objects of study. It's
essentially the most sophisticated thing that science has ever turned its
gaze on. Whether it lends itself to simple "single equation" descriptions
is an open question, but I personally doubt it. All models are wrong, and
this applies to every model of the brain. Some models are useful, and this
also applies to every model of the brain. For the purposes of understanding
how your own brain works, an arbitrary rotation of a sophisticated theory
seems quite sufficient. For solving actual problems, like epilepsy, some
models will be more useful than others. That said, a model isn't always
even needed to solve a problem: the latest epilepsy drugs are the most
effective and they are found by shotgun approaches which result in drugs
that work and for reasons that nobody understands.

Zooming out, I like to ask myself whether there's a reason things are the
way they are. This is obviously an unanswerable question, but it does shine
a light on the fact that we have egos, and that this process of
ego-scaffolding leads to many researchers focusing on different
perspectives at different levels of analysis. The academic publishing
system then broadcasts these perspectives, and whether or not we give truly
fair credit assignment versus implicitly mashing their theory into our own
preferred framework, everything does in the end get all mixed up together,
resulting in a better set of theories overall. One wonders if this
apparently fortuitous coincidence isn't a coincidence after all. I
personally suspect the usefulness of what we're doing is that we are all
contributing to the building of something great. While this somewhat
justifies the existing system, given that it actually appears to be working
(in a way that none of us understands), I would also advocate a more
egalitarian approach where we open our minds to as many theories as
possible and cheer on perspectives different from our own. And from this
angle, I really like the promise of more informal mailing list
conversations for the spread of ideas and hope that you guys keep it up,
because I love reading your ideas. And I wish more folks would jump in too
and help us all out, rather than just hiding out in the darkness of the
literature!

Brian

https://www.linkedin.com/profile/view?id=74878589


On Fri, May 23, 2014 at 8:43 AM, Hans du Buf <dubuf at ualg.pt> wrote:

> I was out for some time (mailbox overflooded) and now saw again discussions
> about vision and motor control and single equations and and and...
> Why don't you start with the archaic part of our brain? (NOT the frontal
> lobe
> and rich club - the massive communication hubs; white matter - only these
> distinguish us and great apes from rodents)
> I've been reading a few recent reviews, and the idea comes up that the
> enormous complexity is the astonishing result of merely replicating very
> few structures over and over (single equation :-)
> We know the laminar structure of the neocortex and the connections and
> processing (FF input from a lower level, horizontal processing, FB input
> from
> a higher level), the hierarchies V1 V2 etc and M1 M2 etc and A1 A2 etc.
> Oops, FF = feedforward.
> These hierarchies are reciprocally connected: V2 groups features from V1,
> V4 groups features from V2, until IT cortex with population coding
> of (parts of) meaningful objects, but in each step up with less
> localisation
> (IT knows what the handle and shank of screwdriver are, and about where,
> and that they belong together; but don't ask IT to put the tip into the
> slot
> in the head of a screw - for that you need V1, but V1 has absolutely no
> clue
> what a screwdriver is). FF+FB is likely predictive coding with a generative
> grouping model. If you have V1 and V2, you also have V4 and IT. You can
> also assume that the processing in the V and M and A hierarchies is the
> same: one equation.
> All neocortical areas are reciprocally connected to pulvinar (LGN in case
> of
> vision) and higher-order thalamic areas in a laminar way, and then to basal
> ganglia via layers for arms, face and legs. The BG take decisions, most
> important
> keyword: DISinhibition. One equation.
> All visual areas are still connected to motor areas (archaic brain,
> rodents,
> screwdriver).
> All motor areas are connected to sensory areas: corollary discharge signals
> were first introduced because of saccadic eye movements, but they are
> ubiquitous for distinguishing external from self-induced percepts, and at
> all levels: from reflex inhibition, sensory filtration, stability analysis
> up to
> sensorimotor learning and planning. I boldly assume: one equation.
>
> Once you understand this, you could assume the same principles for other
> cortices, like the anterior and posterior cingulate: ACC for arousal and
> attention, error, conflict, reward, learning; PCC for more internal
> attention
> and salience. The PCC is connected to thalamus and striatum (basal ganglia,
> decisions!). ACC+PCC balance internal and external attention, both between
> narrow and broad attention. Internal: daydreaming, freewheeling, autism.
> Fronto-parietal network: short-term flexible allocation of selective
> attention.
> Cingulo-opercular network: longer-term, maintain task-related goals.
> They interact via cerebellar and thalamic nodes, work in parallel.
> They are part of the default mode network: external goal-oriented action
> vs. self-regulation. Homeostasis. Small imbalance between endogenous and
> exogenous processes: ADHD.
> Anterior insula and dorso-lateral PCC: balance between excessive control
> and
> lack of control. Imbalance: obsessive-compulsive disorder or schizophrenia.
>
> Keep in mind that our brain is always testing hypotheses and predicting
> errors,
> always at the brink of failure. Metastability: shift through multiple,
> short-lived
> yet stable states. You tweak a parameter and the brain freaks out. It is
> amazing
> that (in my view) a very few principles could be applied to understand how
> our
> brain works - and that most brains seem to work quite  well.
>
> Finally (I need to get some work done), the brain is not a bunch of
> artificial neural
> networks which are trained once. It constantly re-trains itself like a
> babbling baby,
> although this is rarely noticed.
> Am I too bold?
> Hans
>
>
>
>
>
> On 05/23/2014 03:27 AM, Janet Wiles wrote:
>
>> Will a single equation be a good model of the brain as a whole? Unlikely!
>> Will a set of equation-sized-chunks of knowledge suffice? It works for
>> physics, but remains an empirical question for neuroscience.
>>
>> The point is not about what's the best way to model the brain, but
>> rather, what models are adopted widely, while others remain the province of
>> a single lab.  A model that can be expressed as a single equation seems to
>> be a particularly effective meme for computational researchers.
>>
>> Janet
>>
>>
>>
> =======================================================================
> Prof.dr.ir. J.M.H. du Buf                          mailto:dubuf at ualg.pt
> Dept. of Electronics and Computer Science - FCT,
> University of Algarve,                            fax (+351) 289 818560
> Campus de Gambelas, 8000 Faro, Portugal. tel (+351) 289 800900 ext 7761
> =======================================================================
> UALG Vision Laboratory:            http://w3.ualg.pt/~dubuf/vision.html
> =======================================================================
>
>
>
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