By: Adam Santoro
The following text is my personal view on the pattern separation problem. In my opinion, the problem stems from the use of logical fallacies. I don’t accuse anyone of using any of the following fallacies, and, to be honest, most of it comes out in verbal discussions and not in text. I’m also ignoring any differences in definitions of pattern separation, as I think those are not part of the “main problem.” There are a lot of subtleties in the text below, but I think they are crucial. So…here’s my take.
I’ll start by pointing out an important logical fallacy called “affirming the consequent.” It has this form (taken from Wikipedia):
As modus ponens, the following argument contains no formal fallacies: 1.If P then Q 2.P 3.Therefore Q A logical fallacy associated with this format of argument is referred to as affirming the consequent, which would look like this: 1. If P then Q 2. Q 3. therefore P This is a fallacy because it does not take into account other possibilities. To illustrate this more clearly, substitute the letters with premises. 1. If it rains, the street will be wet 2. The street is wet. 3. Therefore it rained. Although it is possible that this conclusion is true, it does not necessarily mean it MUST be true. The street could be wet for a variety of other reasons that this argument does not take into account.
Let’s use a more science-y example:
1. If neurons are exposed to high levels of mystery growth factor MYST-A, then dendritic arborization increases 2. There is increased dendritic arborization 3. Therefore the neurons were exposed to MYST-A
This logic, of course, would never pass reviews. However, the following is logically valid:
1. If neurons are exposed to high levels of mystery growth factor MYST-A, then dendritic arborization increases 2. Neurons are exposed to high levels of MYST-A 3. Therefore there is increased dendritic arborization.
Whether this is true is a different question from whether it is valid. The above conclusion is only true if premise 1 (and 2) is true. We’ll get back to this point soon. Let’s go back to the fallacy.
Pattern separation is a phenomenon at the level of the cell population. It is a cellular mechanism. This is the logical form that affirms the consequent (i.e., it is invalid):
1. If pattern separation occurs, then the animal discriminates. 2. The animal discriminates. 3. Therefore, pattern separation occurs.
This is much different from this valid logical form:
1. If an animal discriminates, then pattern separation occurs. 2. The animal discriminates. 3. Pattern separation occurs.
The first form affirms the consequent. It does not take into consideration any other possibilities to explain successful discrimination. For example, the animal could have discriminated because of some other mechanism, let’s call it the “discrimination mechanism” (DM). By illustrating premise 2, we do not know whether PS or DM is at play. This is similar to seeing an increase in dendritic arborization from the first MYST-A logical form – do we know that dendritic arborization was caused by MYST-A? How about some other growth factor?
Now for the second form. The second form is logically valid, but the truth of the conclusion depends on the truth of the premises. For our purposes, premise 1 is crucial:
1. If an animal discriminates, then pattern separation occurs.
Here is the excellent example Tim Bussey uses in his blog post:
“The classic example of the kind of interference pattern separation reduces involves car parking. If I ask you about something you did 3 days ago, you can probably give me a good answer. But if you park your car in the same multi-story car park every day, and I ask you where you parked your car 3 days ago, it is exceedingly difficult. The memories of parking your car every day are so similar that they are difficult to discriminate, and become confused in memory. Pattern separation is process that helps to reduce this confusion – we’d be a lot more confused about all sorts of memories if we didn’t have it!”
Bussey explains that PS can reduce interference, essentially increasing discrimination. For us to confidently (and truthfully) state that “if an animal discriminates, then pattern separation occurs” we need to know that discrimination necessarily entails pattern separation. By “necessarily entails” I mean that every time discrimination occurs, a pattern separation mechanism is at play, 100% of the time (or, >95% for us biologists 🙂 ). We need to know that when our car-park confusion is reduced, it is because of pattern separation. In order to rely on the conclusions of this logical form, it is not enough to assume that pattern separation could be a cause of our reduced car-park confusion.
My position is that discrimination does not entail pattern separation. In fact, it has not even been demonstrated that pattern separation (specifically in the dentate gyrus) even occurs at all!! This was the basis of my paper. Briefly put, my points were as follows:
1) It has not been experimentally demonstrated that pattern separation at the level of the cell population occurs.
2) Discrimination does not entail pattern separation since discrimination can be caused by other mechanisms (I discussed rate mapping, often used under the umbrella as “pattern separation,” as one potential mechanism. Cellular pattern separation in regions upstream of the dentate gyrus is another mechanism. Computational processes going on in the sensory systems is another).
A note on behavioral neuroscience. It has been critiqued that this is a matter of understanding how behavioral neuroscience “works,” but it is really not. Bussey correctly states that in behavioral neuroscience, we postulate “a putative process/construct/computation” and we “devise tasks to try to capture that function.” Importantly though, the examples given (and truthfully, the only valid examples I can think of) for the validity of this approach are for tasks that try to capture cognitive/behavioral functions. For example, we can have a task that tries to capture working memory, or attention. Similarly, our-touch screen, or radial arm maze, or context fear discrimination task tries to capture the behavioral phenomenon called “discrimination.” This type of workflow is completely valid, and is the foundation of behavioral neuroscience. I’d like to emphasize again that this workflow considers tasks that capture cognitive functions. Not tasks that capture underlying mechanisms. To do that we turn to molecular/cellular neuroscience. For example, you aren’t going to devise a behavioral task that tries to capture LTP, or synaptogenesis. You simply measure those things directly instead. The task can capture some cognitive function that depends on LTP – but you’d have to actually measure LTP in your experiment in order to make any conclusions about it. You wouldn’t perform the cognitive task and state that LTP occurs without measuring it (unless, of course, previous work established that the task necessarily entails LTP).
Thus, this workflow has its bounds. It falls apart is if we use the tasks to capture 1) unproven mechanisms of behavioral functions, and 2) mechanisms that are not necessarily entailed by the behavioral functions. As I stated above, we need to be quite certain that a cognitive phenomenon necessarily entails a particular mechanism (and that the mechanism even exists to begin with) if we are to make proper conclusions. So if, for example, a certain task necessarily entails LTP somewhere in an underlying circuit, then sure, we can say that the task “captures” this LTP mechanism. But this is trivial, and of no use. We aren’t doing behavioral neuroscience tasks to capture cellular mechanisms. The purpose of the workflow is to evaluate cognitive functions. This is how we measure cognitive functions. For the mechanisms, we have our other (direct) measurements.
“The behavioural pattern separation experiments — e.g., lesion the dentate gyrus, test on a putative test of pattern separation — are more of the same. As pattern separation putatively results in reducing the confusability, increasing the discriminability, of events, the parameter we manipulate is discriminability of events.”
Indeed, pattern separation putatively results in increasing discriminability. The task, however, tries to capture event discrimination. The task does not try to capture pattern separation. If transcription of protein-A putatively causes memory interference,why don’t we use a task that captures memory interference and then make conclusions on the transcription of protein-A without actually measuring protein-A transcription? According to the original computational work, pattern separation is a ubiquitous information processing phenomenon, so it is just as “widespread” as LTP, and surely isn’t unique to spatial discrimination. Pattern separation, and pattern convergence, happen everywhere, all the time. It is simply a cellular process that is begging for measurement.
So what is the “problem with pattern separation.” In my opinion, there are many:
1) Some pattern separation literature affirms the consequent (1. If pattern separation occurs, then the animal discriminates. 2. The animal discriminates. 3. Therefore, pattern separation occurs.)
2) Some literature that does not affirm the consequent assumes the truth of the premise that discrimination (and the tasks used to capture discrimination) necessarily entails a pattern separation mechanism (specifically in the dentate gyrus). We don’t know if other mechanisms are at play.
3) There is disagreement as to whether pattern separation at the level of the cell population even occurs. It’s wonderful as a computational idea, but it needs to be experimentally demonstrated.
4) No study has looked at cell population activity in the DG’s input and output and has causally established the role of the DG in pattern separation.
This is all just my humble opinion, and I appreciate all the effort put forth to the discussion. A lot of the I left out any discussion of defining pattern separation behaviorally. I think the problems of having multiple definitions of a single term are easy to spot.