The retina receives signals from all over the brain, and that is kind of weird

As a neuroscientist, when I think of the retina I am trained to think of a precise set of neurons that functions like a machine, grinding out the visual basis of the world and sending it on to the brain. It operates independently of the rest of the system with the only feedback coming from muscles that move the eye around and dilate the pupils. So when someone [Philipp Berens] casually mentioned to me that yes, the retina does in fact receive signals from the brain? Well, I was floored.

I suppose I should not have been surprised. In fruit flies, there has been a steady accumulation of evidence that the brain sends signals to the eye to get it ready to compensate for any movement the animal will make. Intuitively, that makes a lot of sense. If you are trying to make sense of the visual world, of course you would want to be able to compensate for any sudden changes that you already know about.

It turns out that there is a huge mass of feedback connections from the brain to the retina in birds and mammals, something termed the centrifugal visual system. And inputs are sent via this system from both visual areas and non-visual areas (olfactory, frontal, limbic, and so on). So imagine – your eye knows about what you are smelling. Why? In order to do what?

The answer, it turns out, is that we don’t know. It sends all sorts of neurotransmitters and neuromodulators. The list of peptides it sends are long (GnRH, NPY, FMRF, VIP, etc) as is the list of regions that send feedback to the retina. It seems as if which regions send feedback to the retina is very species-specific, suggesting something about the environment each animal is in. But why?

This is a post long on questions and short on answers. It is more a reminder that the nice, feedforward systems that we have simple explanations for are really complex, multimodal systems designed to create appropriate behaviors in appropriate circumstances. Also it is a reminder to myself about how little I know about the brain, and how mistaken I am about even the simplest things…

I would love someone more knowledgable than me to pipe up and tell me something functional about what these connections do?

References

Repérant J, Médina M, Ward R, Miceli D, Kenigfest NB, Rio JP, & Vesselkin NP (2007). The evolution of the centrifugal visual system of vertebrates. A cladistic analysis and new hypotheses. Brain research reviews, 53 (1), 161-97 PMID: 17059846

Vereczki, V. The centrifugal visual system of rat. Doctoral Thesis. PDF.

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Every spike matters, down to the (sub)millisecond

There was a time when the neuroscience world was consumed by the question of how individual neurons were coding information about the world. Was it in the average firing rate? Or did every precise spike matter, down to the millisecond? Was it, potentially, more complicated?

Like everything else in neuroscience, the answer was resolved in a kind of “it depends, it’s complicated” kind of way. The most important argument against the role of precise spike timing is noise. There is the potential for noise in sensory input, noise between every synapse, noise at every neuron. Why not make the system robust to this noise by taking some time average? On the other hand, if you want to respond quickly you can’t take too much time to average – you need to respond!

Much of the neural coding literature comes from sensory processing where it is easy to control the input. Once you get deeper into the brain, it becomes less clear how much of what the neuron is receiving is sensory and not some shifting mass.

The field has shifted a bit with the rise of calcium indicators which allow imaging the activity of large population of neurons at the expense of timing information. Not only does it sacrifice precise timing information but it can be hard to get connectivity information. Plus, once you start thinking about networks the nonlinear mess makes it hard to think about timing in general.

The straightforward way to decide whether a neuron is using the specific timing of each spike to mean something is to ask whether that timing contains any information. If you jitter the precise position of any given spike my 5 milliseconds, 1 millisecond, half a millisecond – does the neural code become more redundant? Does this make the response of the neuron any more random at that moment in time than it was before?

Just show an animal some movie and record from a neuron that responds to vision. Now show that movie again and again and get a sense of how that neuron responds to each frame or each new visual scene. Then the information is just how stereotyped the response is at any given moment compared to normal, how much more certain you are at that moment than any other moment. Now pick up a spike and move it over a millisecond or so. Is this within the stereotyped range? Then it probably isn’t conveying information over a millisecond. Does the response become more random? Then you’ve lost information.

But these cold statistical arguments can be unpersuasive to a lot of people. It is nice if you can see a picture and just understand. So here is the experiment: songbirds have neurons which directly control the muscles for breathing (respiration). This provides us with a very simple input/output system, where the input is the time of a spike and the output is the air pressure exerted by the muscle. What happens when we provide just a few spikes and move the precise timing of one of these spikes?

The beautiful figure above is one of those that is going directly into my bag’o’examples. What it shows is a sequence of three induced spikes (upper right) where the time of the middle spike changes. The main curves are the how the pressure changes with the different timing in spikes. You can’t get much clearer than that.

Not only does it show, quite clearly, that the precise time of a single spike matters but that it matters in a continuous fashion – almost certainly on a sub-millisecond level.

Update:

The twitter thread on this post ended up being useful, so let me clarify a few things. First, the interesting thing about this paper is not that the motor neurons can precisely control the muscle; it is that when they record the natural incoming activity, it appears to provide information on the order of ~1ms; and the over-represented patterns of spikes include the patterns in the figure above. So the point is that these motor neurons are receiving information on the scale of one millisecond and that the information in these patterns has behaviorally-relevant effects.

Some other interesting bits of discussion came up. What doesn’t use spike-timing information? Plenty of sensory systems do; I thought at first that maybe olfaction doesn’t but of course I was wrong. Here’s a hypothesis: all sensory and motor systems do (eg, everything facing the outside world). (Although, read these papers). When would you expect spike-timing to not matter? When the number of active input neurons are large and uncorrelated. Does spike timing make sense for Deep Networks where the neurons are implicitly representing firing rates? Here is a paper that breaks it down into rate and phase.

References

Srivastava KH, Holmes CM, Vellema M, Pack AR, Elemans CP, Nemenman I, & Sober SJ (2017). Motor control by precisely timed spike patterns. Proceedings of the National Academy of Sciences of the United States of America, 114 (5), 1171-1176 PMID: 28100491

Nemenman I, Lewen GD, Bialek W, & de Ruyter van Steveninck RR (2008). Neural coding of natural stimuli: information at sub-millisecond resolution. PLoS computational biology, 4 (3) PMID: 18369423

All Watched Over By Machines Of Loving Grace

I like to think (and
the sooner the better!)
of a cybernetic meadow
where mammals and computers
live together in mutually
programming harmony
like pure water
touching clear sky.

I like to think
(right now, please!)
of a cybernetic forest
filled with pines and electronics
where deer stroll peacefully
past computers
as if they were flowers
with spinning blossoms.

I like to think
(it has to be!)
of a cybernetic ecology
where we are free of our labors
and joined back to nature,
returned to our mammal
brothers and sisters,
and all watched over
by machines of loving grace.

 

Richard Brautigan (1967)

Posted in Art

How do you keep track of all your projects?

One of the central tasks that we must perform as scientists – especially as we progress in our careers – is project management. To that end, I’ll admit that I find myself a bit overwhelmed with my projects lately. I have many different things I’m working on with many different people, and every week I seem to lose track of one or another. So I’m looking for a better method! It seems to me that the optimal method to keep track of projects would have the following characteristics:

  1. Ping me every week about any project that I have not touched
  2. Re-assess each project every week, both in terms of what I need to do and the priority for the project as a whole
  3. Split the projects into subtypes: data gathering, analysis, tool building, writing (etc).
  4. Be clear in my weekly/monthly/longer-term goals. Review these every week
  5. Some kind of social pressure to keep you on-task

Right now I use a combination of Wunderlist, Evernote, Google Calendar and Brain Focus (keep track of how much time I spend on each task with a timer)… but when I get busy with one particular project I will become monofocused and tune out the rest. Optimally, there would be some way to ping myself that I really do need to work on other things, at least a little. And it is too easy to adapt to whatever pinging mechanism the App Of The Moment is using and start ignoring it. Is it possible to get an annoying assistant/social mechanism that keeps you on task with a random strategy to prevent adaptation? IFTTT?

I asked about this on Twitter and everyone has a strong opinion on the right way to do this, and every opinion is different. They tend to split into:

  1. Have people bother you constantly
  2. Slack (only works with buy in from others)
  3. Trello and Workflowy
  4. Something called GTD
  5. Put sticky notes everywhere
  6. Github
  7. Spreadsheets with extensive notes

I’m super curious if there is a better strategy for project management. Perhaps I am not using slack correctly? Suggestions?