Björn Brembs

*[During my [flyfishing vacation last
year](http://blogarchive.brembs.net/comment-n862.html), pretty much
nothing was happening on this blog. Now that I've migrated the blog to
WordPress, I can actually schedule posts to appear when in fact I'm not
even at the computer. I'm using this functionality to re-blog a few
posts from the [archives](http://blogarchive.brembs.net) during the
month of august while I'm away. This post is from [September 13,
2011](http://blogarchive.brembs.net/comment-n778.html):]{style="font-size: 12px;"}  
*

<div>

I wasn't planning to comment on [Kerri Smith's piece on Free
Will](https://www.nature.com/news/2011/110831/full/477023a.html){target="_blank"
rel="external"} (probably paywalled) in the last issue of *Nature*
magazine. However, this morning I read a paper on Free Will in robots
(or rather 'agents'), which urged me to suggest some updates to the
sadly (otherwise Ms. Smith is producing outstanding work, especially her
podcasts!) outdated discussion in the *Nature* article.

Her article starts out with a modern variation of Libet's famous
experiments. These experiments can be caricatured like this: "press a
button whenever you feel like it and watch a clock while you're making
the decision to tell us when you think you've made the decision". It is
then little surprise that some form of brain activity (either
electrical, in the case of Libet or blood flow, in the case of the
modern fMRI studies) can be recorded before the time point when the
study participants self-reportedly made the decision.

Detailed treatment of these experiments isn't really needed here, as any
biologist realizes that all our thoughts are indeed based on brain
activity and thus any conscious act or thought must be either
simultaneous to or preceded by nervous activity. The amount of this time
difference may vary with the task and the method of activity
measurement. The fMRI brain scans allowed researchers to predict a dual
choice to 60%, i.e., just above chance level. Clearly, even with modern
brain scans a brain isn't even close to a system one might call
'deterministic' by any stretch of the word.

From the way I read the article, the most important point drawn by the
researchers is that the thought process itself is based on brain
activity. John Dylan-Haynes:

> <div>
>
> "I'll be very honest, I find it very difficult to deal with this," he
> says. "How can I call a will 'mine' if I don't even know when it
> occurred and what it has decided to do?"
>
> </div>

I'd counter that question with another question: what else then brain
activity would you have expected when you peered into a brain? Dualism
has been dead since Popper's and Eccles' "The Self and its Brain" in
1977. Why is this article still beating a dead horse?

About half way through the article, this exact issue is raised:

> <div>
>
> The trouble is, most current philosophers don't think about free will
> like that, says Mele. Many are materialists --- believing that
> everything has a physical basis, and decisions and actions come from
> brain activity. So scientists are weighing in on a notion that
> philosophers consider irrelevant.
>
> </div>

Precisely! And yet, towards the end of the article, the dualism creeps
back in, by the same philosopher who so rightly dismissed it:

> <div>
>
> Philosophers are willing to admit that neuroscience could one day
> trouble the concept of free will. Imagine a situation (philosophers
> like to do this) in which researchers could always predict what
> someone would decide from their brain activity, before the subject
> became aware of their decision. "If that turned out to be true, that
> would be a threat to free will," says Mele.
>
> </div>

Even if this prediction were possible, any decision would still be ours,
as it would still not be possible to predict the decision from the time
when the decision-task was initiated. In other words: one would need to
observe the decision-making process for some time in order to eventually
project where it is going to end up. I think it is very likely that we
will be able to go rather far with this approach, but because our brain
is still calling the shots, this has absolutely no relevance for the
question on how free the decision was. We are not slaves of our brains,
we *are* our brains. And this means an upgrade for our understanding of
human nature, or you are vastly underestimating the abilities of brains.

But enough of the disappointing aspects of this article. I was reminded
of it because of a very exciting article by a physicist in Austria,
[Hans J.
Briegel](https://www.uibk.ac.at/sp-physik/people/h_briegel.html){target="_blank"}:
"[On machine creativity and the notion of free
will](https://arxiv.org/abs/1105.1759){target="_blank"}". It displayed a
modern understanding of the scientific issues surrounding a
materialistic (i.e., scientific) notion of free will and provided a
proof of principle of how Free Will may be implemented in physical
objects. And these objects don't even have to be biological in origin!
As Briegel writes:

> <div>
>
> To put it provocatively, even if human freedom were to be an illusion,
> humans would still be able, in principle, to build free robots.
> Amusing.
>
> </div>

Amusing indeed! The paper by Briegel elaborates on a method to provide
software agents with a degree of freedom without breaking any laws of
nature, a method he calls '[projective
simulation](https://arxiv.org/abs/1104.3787){target="_blank"}'.

Briegel claims that Free Will by projective simulation, could, "in
principle, be realized with present-day technology in form of \[...\]
robots." Projective simulation means that the robots have a flexible
sort of memory that allows the agent to simulate situations that are
similar, but not identical to, events that it has encountered before.
There are rules according to which these 'projections' can be generated
by the robot, so they're not arbitrary, but they contain a degree of
randomness (or 'spontaneity') that allows them to "increasingly detach
themselves from a strict causal embedding into the surrounding world".
Briegel realizes that, in biological systems, much of the required
random variability is readily available, but because we don't know how
it is being used, we cannot say much about the relevance of it. In fact,
with reference to Quantum Indeterminacy, he arrives at almost the same
wording as I did in my [Proc. Roy. Soc
Article](http://blogarchive.brembs.net/request98.html){target="_blank"}:

> <div>
>
> We may not need quantum mechanics to understand the principles of
> projective simulation, but we have it. And this is our safeguard that
> ensures true indeterminism on a molecular level, which is amplified to
> random noise on a higher level. Quantum randomness is truly
> irreducible and provides the seed for genuine spontaneity.
>
> </div>

It is gratifying to see how close we came of each other, without knowing
of each other. Here is my way of putting it:

> <div>
>
> Because of this nonlinearity, it does not matter (and it is currently
> unknown) if the 'tiny disturbances' are objectively random as in
> quantum randomness or if they can be attributed to system, or thermal
> noise. What can be said is that principled, quantum randomness is
> always some part of the phenomenon, whether it is necessary or not,
> simply because quantum fluctuations do occur. Other than that it must
> be a non-zero contribution, there is currently insufficient data to
> quantify the contribution of such quantum randomness. In effect, such
> nonlinearity may be imagined as an amplification system in the brain
> that can either increase or decrease the variability in behaviour by
> exploiting small, random fluctuations as a source for generating
> large-scale variability.
>
> </div>

If this topic is of any interest to you, you really ought to read
Briegel's paper!

Basically, the discussion about freedom today has progressed beyond the
question of whether it exists (the dualistic notion, everyone agrees,
does not), but how it has been implemented in a material world that is
powerful and creative enough to not need any supernatural forces. It is
sad that this was only briefly touched upon in the *Nature* piece, when
it should have been the very core of the article.

------------------------------------------------------------------------

</div>

<div>

Smith, K. (2011). Neuroscience vs philosophy: Taking aim at free will
Nature, 477 (7362), 23-25 DOI:
[10.1038/477023a](https://dx.doi.org/10.1038/477023a){rev="review"}

</div>


*During my flyfishing vacation last year, pretty much nothing was happening on this blog. Now that I’ve migrated the blog to WordPress, I can actually schedule posts to appear when in fact I’m not even at the computer. I’m using this functionality to re-blog a few posts from the archives during the month of august while I’m away.

Flashback: Programming Free Will – creative robots

*[During my [flyfishing vacation last
year](http://blogarchive.brembs.net/comment-n862.html), pretty much
nothing was happening on this blog. Now that I've migrated the blog to
WordPress, I can actually schedule posts to appear when in fact I'm not
even at the computer. I'm using this functionality to re-blog a few
posts from the [archives](http://blogarchive.brembs.net) during the
month of august while I'm away. This post is from [October 25,
2010](http://blogarchive.brembs.net/comment-n676.html):]{style="font-size: 12px;"}  
*

Brains are what mathematicians call "[information
sources](https://en.wikipedia.org/wiki/Information_source_%28mathematics%29){target="_blank"
rel="external"}". At least this is one of the results of a set of
elaborate experiments together with sophisticated analyses and
computations reported in the current issue of [*Nature
Neuroscience*](https://www.nature.com/neuro/journal/v13/n10/abs/nn.2630.html){target="_blank"}
(subscription required). The article, entitled "Intrinsic biophysical
diversity decorrelates neuronal firing while increasing information
content", studies a set of neurons in the brain's main olfactory center,
the olfactory bulb. These neurons, mitral cells, receive input from
olfactory sensory neurons with their receptors in the olfactory
epithelium in the nose. The authors looked at particular subsets of
these neurons in the mouse brain, namely the ones that receive their
input within a single identical so-called 'glomerulus', a neuropil
structure characterized by the fact that it contains only the terminals
from olfactory receptor neurons that express the same olfactory
receptor. This means that the input these mitral cells receive is highly
correlated. In other words, these mitral cells receive virtually
identical stimulation and the authors looked at the output these neurons
generate in response to the input.

In order to do this, the used
[patch](https://en.wikipedia.org/wiki/Patch_clamp){target="_blank"}
electrodes to stimulate and record from these neurons. In order to
provide realistic input scenarios, they passed more or less random
amounts of current into one neuron at a time and then evaluated their
output. What they found was that each neuron seemed to look at a
different aspect of the input, leading to this population of cells to
lose the correlation in their activity that is present in their input.
Put differently, every neuron reacts differently to the same input and
even if you give all mitral cells in the same glomerulus the same input
(like the same smell), each mitral cell will respond with a different
train of activity degrading any correlation that might have been present
in the input.

This all make a lot of sense, because in this way, each neuron looks at
the same stimulus from a slightly different perspective, enhancing the
amount of information the animal can get from a single stimulus. From
the point of view of information coding, this is an advantage, that
comes with a disadvantage: some neurons will create 'phantom'
information, information that isn't there. The authors do not mention
this with a single word, but they show it in their first figure:

![urban_2010.png](http://blogarchive.brembs.net/e107_images/newspost_images/urban_2010.png){loading="lazy"
decoding="async" width="662" height="394"}

In a) you can see the olfactory receptor neurons projecting into a
single glomerulus and the mitral cells which receive their input. In b)
and c) you see examples of mitral cells and their recordings to a
single, depolarizing constant current. While one neuron, b), does what
one would expect with constant input -- constant output, i.e., firing --
the other neuron, c), shows irregular, bursting activity that doesn't
reveal the constancy in the input signal at all. To put it drastically,
one could say that this neuron is 'hallucinating'. This example shows
very clearly the drawback, in terms of information coding, of neurons
decorrelating correlated input: some of the information the transmit may
not be present in the sensory input at all. Already at this very early
stage, the very first synapse after the sensory neurons, the brain is
already altering, expanding and interpreting the sensory signal. In
fact, it's already making up its own information that is independent
from the outer world. This is profound!

I've been thinking about the conundrum of '[noise in the
brain](http://blogarchive.brembs.net/comment-n516.html){target="_blank"}'
before and already before this publication now, it has been very
suggestive to argue that the variability in neural activity is not just
random, pernicious noise but has some functional significance -- a
significance which we don't quite understand, yet. The authors here
argue that one part of that significance is to capture all the
information in a sensory stimulus. I'd agree with that but from their
experiments I'll take another function which they don't mention: the
capability to react slightly differently to always the same stimulus.
This capability of doing things differently every time the same
situation comes along is vital for survival. Here's a great example of
what can happen to you, if you don't do that and react always with the
same response to the same stimulus:

::: {.youtube style="width: 350; height: 300;"}
:::

Tentacled snakes hunt by exploiting the predictability of fish: they
elicit a so-called C-start response in their prey in order to predict
where the fish will be going, only to then intercept the fish's escape
path. The result: the fish swims right into the mouth of the snake. This
video was published by [Ken
Catania](https://medschool.mc.vanderbilt.edu/biosci/bio_fac.php?id3=9129),
who studies these animals.

The results by Padmanabhan and Urban provide further evidence that the
highly variable activity of neurons is not 'noise' in a complex system,
but actively generated by the brain not only to increase information
capacity, but also to behave unpredictably, creatively and spontaneously
in an unpredictable, dangerous and competitive world.

It also means that adding information to a sensory stimulus may be a
disadvantage in terms of information coding, but it wasn't eliminated by
[evolution](http://brembs.net/evolution){target="_blank" rel="external"}
because it prevented animals from becoming too predictable -- a classic
cost/benefit trade-off. All this happens already at the very first
synapse after sensory transduction -- how much information is added in
the more central stages of computing in the brain? Methinks, the
question is not "why do some people hallucinate?", the question should
be, "why don't we all?"...

------------------------------------------------------------------------

Padmanabhan, K., & Urban, N. (2010). Intrinsic biophysical diversity
decorrelates neuronal firing while increasing information content Nature
Neuroscience, 13 (10), 1276-1282 DOI:
[10.1038/nn.2630](https://dx.doi.org/10.1038/nn.2630){rev="review"}


Flashback: The brain creates something out of nothing

*[During my [flyfishing vacation last
year](http://blogarchive.brembs.net/comment-n862.html), pretty much
nothing was happening on this blog. Now that I've migrated the blog to
WordPress, I can actually schedule posts to appear when in fact I'm not
even at the computer. I'm using this functionality to re-blog a few
posts from the [archives](http://blogarchive.brembs.net) during the
month of august while I'm away. This post is from [June 9,
2010](http://blogarchive.brembs.net/comment-n616.html):]{style="font-size: 12px;"}  
*

I have no idea when it started, but probably long before Darwin, the
notion of 'design' kept creeping into descriptions of biological
organisms or traits: Birds are designed to fly or the eye is designed to
see. I've also been guilty of using the word 'design' for biological
objects every now and then. However, after reading a fair bit and after
thinking for some time now, I've come to the conclusion that the word
'design' is so misleading and not even wrong, that it should never be
used in biology at all, ever.

I'm only partially saying this because of a prominent creationist
movement in the US awfully dubbed 'intelligent design' (which couldn't
be further from biological reality). My main reason is that the use of
'design' is pernicious for biological research. 'Design' or engineering
approaches have been used over and over in biology and many if not most
of them have gone the way of Newtonian mechanics: extremely useful and
successful initially (and to some extent still today), but
scientifically falsified eventually. Take a rather recent, prominent
example: [Lee
Hood](https://en.wikipedia.org/wiki/Lee_Hood){target="_blank"
rel="external"}'s automobile paradigm, according to which systems
biology is akin to finding car parts without a manual in the fog and
then trying to assemble the car. Current research shows that genetic
networks are, in contrast to car components, highly plastic and
forgiving of errors (a phenomenon termed robustness, often due to
[degeneracy](https://www.pnas.org/content/98/24/13763.full){target="_blank"}
in evolved systems). Even though the car analogy might seem daunting, it
is still grossly oversimplified and biologically misleading. Indeed,
expecting genetic networks to behave as stably as car components will
lead to the wrong experiments and the wrong conclusions. Nevertheless,
systems biology was and still is a very successful branch of biology.
I'm not a systems biologist, but I would be surprised if many systems
biologists still bought into the car analogy these days any more, after
what they have found out until today.

For the same reasons, there is no [blind
watchmaker](https://en.wikipedia.org/wiki/The_Blind_Watchmaker){target="_blank"},
because there is no watch. The analogy may still be useful in a
rule-of-thumb kind of way, but biologically it is completely false.

Another, much older engineering approach is that of brains as
input-output systems in neuroscience (the 'sensorimotor hypothesis'),
which purports that brains passively wait for stimuli to occur in order
to respond to them, much like radios, computers or other equipment that
we have designed. In some fields of neuroscience (and psychology) this
approach has been so pervasive that *any* behavior is referred to as a
response, assuming that there *always* must be an underlying stimulus
triggering the behavior. It is not only recent ecological and
ethological research on predators specializing in exploiting stereotypic
behaviors in prey species which shows that being responsive is not an
evolutionary stable strategy: responding reliably to the same stimuli in
the same predictable way will neither get you to the unexpected food
patch nor prevent a predator or competitor from predicting your next
move. "Nature red in tooth and claw" will make sure that any predictable
species will not last for long. There is a very good ultimate cause for
the Harvard Law of Animal Behavior: "Under carefully controlled
experimental circumstances, an animal will behave as it damned well
pleases": species which didn't obey the law have not survived. It thus
appears that for the last 100 odd years, neuroscience has been studying
the exceptions to the rule that brains are always active and are
constantly producing output, on which sensory stimuli merely exert a
modest, modulatory role. I think it is fair to assume that one reason
for this research direction (apart from the relative experimental ease)
is that there is no mechanism or object we have designed that works in
such a way. Everything we have made responds to commands and so people
thought this is how brains operate.

Given the success of this approach in biology and of Newtonian mechanics
in physics, it is no surprise that some thinkers have come to see brains
as deterministic Newtonian clockworks. Complicated, maybe, but
deterministic and predictable none the less. Any observed behavioral
variability was shrugged off as random noise, when indeed it was the one
brain function that kept animals in the run for the next generation. It
is high time that neuroscientists realize that Newtonian mechanics are
as falsified in biology as they are in physics: the world is not
deterministic and neither are brains. The fact that brains are not
engineered, but evolved allows for freedom of choice without
quasi-magical quantum computing in the brain. All the brain requires to
be unpredictable is some source of variability from which it can
generate spontaneity, and there is plenty of such variability in neurons
and their components, with or without quantum effects. The selection
pressure of predictable animals being outcompeted, eaten or left without
a mate established early on that every brain is equipped with a function
which allows for adaptive behavioral choice. In some animals, there was
need for more of such capabilities. Those animals seem to have more
freedom of choice. Other animals could get away with being more
predictable, giving the impression of being less 'free' and more
[robot-like](https://www.esf.org/index.php?id=6460){target="_blank"}.
I'm starting to get the impression that the model systems used in
neuroscience are predominantly of the latter sort.
![smoking.png](http://blogarchive.brembs.net/e107_images/emotes/yellow/smoking.png){decoding="async"}

Be that as it may, all animals possess this trait to a larger or lesser
degree and have been using it for survival and procreation since the
very first brain evolved. I think it is time biology sheds the last
remnants of classical thinking and starts to study 'free will' as the
biological trait it is: the ability to behave differently in the same
situations, the ability to chose from identical options, the mental coin
toss. The centuries of philosophical thinking on this topic have
provided us with a wonderful framework within which these empiricial
findings can be embedded. Because [brains are output-input
systems](http://blogarchive.brembs.net/content39.html){target="_self"}
(rather than the other way around), our lab has started to study the
[spontaneous choices of the fruit
fly](http://brembs.net/spontaneous){target="_self"}
*[Drosophila](http://brembs.net/spontaneous){target="_self"}* and how
the brain generates them. Currently, a graduate student in our lab is
studying where in the brain these processes take place in order to later
be able to understand how the circuits mediating these choice function.
It is a testament to the idiocy of creationists that [our research was
featured on a creationist
blog](https://www.uncommondescent.com/intelligent-design/flies-show-free-will/){target="_blank"}
as supporting creationism. The opposite is the case: all brains possess
free will precisely because there is no design in biology.
[Evolution](http://brembs.net/evolution){target="_blank" rel="external"}
is the only reason why we have free will and it is neither dualistic,
nor spiritual, nor mystic: it is biological.


Flashback: All brains possess free will because there is no design in biology

*[During my [flyfishing vacation last
year](http://blogarchive.brembs.net/comment-n862.html), pretty much
nothing was happening on this blog. Now that I've migrated the blog to
WordPress, I can actually schedule posts to appear when in fact I'm not
even at the computer. I'm using this functionality to re-blog a few
posts from the [archives](http://blogarchive.brembs.net) during the
month of august while I'm away. This post is from [May 8,
2009](http://blogarchive.brembs.net/comment-n516.html):]{style="font-size: 12px;"}  
*

I was recently alerted to a group of theoretical publications which deal
with the issue of apparent 'noise' in neuronal populations. The [Nature
Reviews Neuroscience](https://www.nature.com/nrn){target="_blank"
rel="external"} article "[Neural correlations, population coding and
computation](https://www.nature.com/nrn/journal/v7/n5/full/nrn1888.html){target="_blank"}"
by Bruno B. Averbeck, Peter E. Latham &  Alexandre Pouget covers this
area quite well.  
Basically, the authors claim that the variability one can see when
recording from the brain when the same stimulus is presented repeatedly
is noise and must be detrimental for the tranmission of information and
hence a problem the brain must solve:

> <div>
>
> Part of the difficulty in understanding population coding is that
> neurons are noisy: the same pattern of activity never occurs twice,
> even when the same stimulus is presented. Because of this noise,
> population coding is necessarily probabilistic. If one is given a
> single noisy population response, it is impossible to know exactly
> what stimulus occurred. Instead, the brain must compute some estimate
> of the stimulus (its best guess, for example), or perhaps a
> probability distribution over stimuli.
>
> </div>

It needs to be noted that the authors do not refer to sensory neurons,
which code sensory information with great precision. Instead, they look
at neurons deep in the mammalian brain, many synapses away from the
primary sensory afferents. What I don't understand from their article is
why this should be considered 'noise'. Obviously, if high fidelity
between the site of sensory input and the site of recording were
required, there would be a single axon going there, and not via many
syapses. Synapses are time consuming and energetically expensive. During
development, unused synapses are being pruned throughout the brain.
Thus, the variability must reflect some computation which takes place in
the synapses from the site of sensory input to the site of recording.
Let me illustrate this with a picture:

![neuralnoise.png](http://blogarchive.brembs.net/e107_images/newspost_images/neuralnoise.png){.aligncenter
decoding="async"}

Of course, if one records from neuron N~R~ and stimulates sensory neuron
N~S~, as in A, there is a lot of processing going on in the synapses
along N~1-4~. This is happening even without any external input into the
single conveyor belt of information. Of course, there never is such a
conveyor belt, that idea is already misleading. After the very first
synapse (from wherever you start), there are always inputs from other
sites, feed-forward and feedback connections, etc. But even in this
simplest model of information transmission, every synapse is a
computational component and not just a link between neurons adding
variability to the sensory signal for no reason. These synapses would
not be there if this processing was not some important brain function.
This is illustrated in B: if simple and reliable information
transmission from N~S~ to N~R~ were important, there would only be one
single axon from N~S~ to N~R~, without any additional processing.

I would really like to hear good arguments as to why the recorded
variability should be 'noise' and a problem for information coding,
rather than a reflection of the brain doing what it's supposed to do:
finding out what the best action is under the current circumstances.

------------------------------------------------------------------------

Averbeck, B., Latham, P., & Pouget, A. (2006). Neural correlations,
population coding and computation Nature Reviews Neuroscience, 7 (5),
358-366 DOI:
[10.1038/nrn1888](https://dx.doi.org/10.1038/nrn1888){rev="review"}


Flashback: Noise in the brain?

[*During my [flyfishing vacation last
year](http://blogarchive.brembs.net/comment-n862.html), pretty much
nothing was happening on this blog. Now that I've migrated the blog to
WordPress, I can actually schedule posts to appear when in fact I'm not
even at the computer. I'm using this functionality to re-blog a few
posts from the [archives](http://blogarchive.brembs.net) during the
month of august while I'm away. This post is from [June
13](http://blogarchive.brembs.net/news749.html),
2011:*]{style="font-size: 12px;"}

<div>

</div>

<div>

</div>

<div>

Most neuroscientists would subscribe to the sensorimotor hypothesis,
according to which brains mainly evaluate sensory input to compute motor
output. For instance, Mike Mauk wrote now over ten years ago: "brain
function is ultimately best understood in terms of input/output
transformations and how they are produced" \[1\]. Tony Dickinson
recognized already in 1985 that "Indeed, so pervasive is the basic
assumption of this model that it is common to refer to any behaviour as
a 'response' and thus by implication \[...\] assume that there must be
an eliciting stimulus." \[2\]. Textbooks to this day mostly begin with a
graph showing sensory input entering the brain (usually via the eyes)
and then motor-output leaving it.However, more and more information is
now accumulating that to the extent that these stimulus-response
relationships actually exist, they may be the exception, rather then the
rule of what brains are doing when they're not in a laboratory
experiment. Perhaps most recently, in the area of human brain research
this change in perception has also begun. Marcus Raichle's "Two views of
brain function" \[3\] provides plenty of evidence against the
sensorimotor hypothesis. There are many more examples of this kind of
evidence. For me personally, the most eye-opening one was this famous
video by Ken Catania:

</div>

<div>

</div>

<div>

If all behavior were always organized according to stimulus-response
schemes such as the C-start response in fish, animals would be extremely
vulnerable not only to predators (or prey), but of course also to
competitors. [Evolution](http://brembs.net/evolution){target="_blank"
rel="external"} is a competitive business: if you're too predictable,
you lose.

In our labs, reproducibility is key to success. This is precisely the
reason why escape responses are so well-studied: these are the
exceptions where animals have specialized in speed and sacrificed
unpredictability in an evolutionary trade-off. I would hypothesize that
no species would survive for long if all other behaviors sacrificed
unpredictability in this way,

More likely, brains need to balance input-output processing with
[output-input processing](http://blogarchive.brembs.net/brains.php),
with the latter probably being both the more prevalent and the
[ancestral form of behavioral
control](http://blogarchive.brembs.net/comment-n532.html). It is this
delicate balance that brains must constantly strike to survive,
procreate and be successful. If we want to understand what the brains we
study are really doing when they are not in the lab, we need to take a
step back and design more experiments that don't require a response, but
an action. This process has already started, but the realization that we
have been heading down the stimulus-response direction for too long has
not widely set in yet, IMHO.

The stimulus-response approach has been hugely successful for the most
derived and simplified forms of behavior -- and we're still far from
done with the task. Now comes the vastly more complex task of
understanding how brains decide which action to take next, when there is
no simple stimulus providing unambiguous information. Many labs have
already started to embark on this task. In our lab, we study [animals in
the complete absence of discrete sensory
stimulation](http://brembs.net/spontaneous), in order to find out how
brains create "something out of nothing". Which actions are you
studying?

This post was originally written for the launch of the new social
network for neuroscientists,
[NeurOnline](https://neuronline.sfn.org){target="_blank" rel="external"}
(@[SfN](https://sfn.org){target="_blank"}).

</div>

------------------------------------------------------------------------

\[1\] Mauk, M. (2000). The potential effectiveness of simulations versus
phenomenological models Nature Neuroscience, 3 (7), 649-651 DOI:
[10.1038/76606](https://dx.doi.org/10.1038/76606){rev="review"}  
\[2\] Dickinson, A. (1985). Actions and Habits: The Development of
Behavioural Autonomy Philosophical Transactions of the Royal Society B:
Biological Sciences, 308 (1135), 67-78 DOI:
[10.1098/rstb.1985.0010](https://dx.doi.org/10.1098/rstb.1985.0010){rev="review"}  
\[3\] Raichle, M. (2010). Two views of brain function Trends in
Cognitive Sciences, 14 (4), 180-190 DOI:
[10.1016/j.tics.2010.01.008](https://dx.doi.org/10.1016/j.tics.2010.01.008){rev="review"}


<em>
 During my flyfishing vacation last year, pretty much nothing was happening on this blog. Now that I’ve migrated the blog to WordPress, I can actually schedule posts to appear when in fact I’m not even at the computer. I’m using this functionality to re-blog a few posts from the archives during the month of august while I’m away.
</em>

Rogue Scholar Posts

Flashback: Programming Free Will – creative robots

Flashback: The brain creates something out of nothing

Flashback: All brains possess free will because there is no design in biology

Flashback: Noise in the brain?

Flashback: ‘stimulus-response’ concept based on artifacts?