[jegp]

Is this novel? Spatial codes have been known for long and neuron (populations) are known to code for time [1]. That reference also states that "Neurons that respond selectively to the temporal and spatio-temporal structure of sensory stimuli have also been identified in the auditory system of birds and mammals". Doesn't that pre-empt the conclusion that "Thus, the brain can represent time and space as overlapping but dissociable dimensions".

[1]: https://royalsocietypublishing.org/doi/10.1098/rstb.2012.046...

[neuronerdgirl]

It does not, just that both dimensions are coded for in some way. Per the current article, temporal and spatial codes have been previously studied in isolation, so it was not known if or how they might be intertwined. This has elucidated new nuances of that relationship.

[godelski]

> Is this novel?

Novelty is not a good question to ask. It is meaningless.

Instead ask:

- Is it plagiarized? Or is it redundant information organized in a way that does not benefit others?

- Does it provide utility to __someone__ in the research community?

- Is it void of any major mistakes?

Novelty is just an absurd idea that is *destructive* to scientific progress. If you abstract ideas, nearly every idea is just <x idea, abstracted> + <y idea, abstracted>. Generally, science moves forward in small steps. You DO NOT want to criticize work on novelty because you actively encourage obscurification. This happens, a lot, and not just by small teams[0]. Unless you are intimately familiar with the specific sub-niche, you probably can't accurately judge novelty because the small steps and the nature of expertise is literally predicated on having an extremely nuanced understanding of a topic. So you're going to abstract and cause the aforementioned error if not careful.

In fact, a well written paper will often trick you into thinking that you already knew all this beforehand. This is even codified in the Socratic method. So many new things that change the world often leave us thinking "well that was obvious." Maybe it was, maybe it is only obvious in hindsight. Either way, it was useful. Either way, you didn't do it, and someone has to.

As far as your reference vs the one here, at least to me they seem quite distinguishable from the abstract alone. From further reading, I'm not sure how you conflate these other than they are studying the same topic. For one, your work (which was 10 years ago btw) isn't working on mammals while the current one studies rats. The new one looks much more detailed, has more complex task and convincing experiment, and honestly, is far more reproducible. I am curious why you think these ideas are identical or so similar that no new knowledge is gained. This is an honest ask. I do want to understand[1]

I think we need to ask ourselves what we want from science. For me, that is: reproducibility, communication (the clearer the better), and exploration of the unknown (exciting or mundane). Personally I don't care about utility, but that's because the abstract comment above and I've seen history to show this purist it naive at best and egotistical at worst (thinking I know so well). (I can list entire fields if need be. I'll give you a start: knot theory) I actually want explicitly non-novel works to be, frankly, common! Trust, but verify. We did not trust the LK-99 authors and move on, we verified. Even with failure to replicate, we still learned a lot. Don't forget that part! I'm perfectly fine if we have "too many" papers, as there's already more than any one can read today (look at ML if you want. It hasn't died, it accelerated when everyone started pushing preprints (and boy do most of those not get published, many for this exact reason. I've had to defend great papers written by rock stars because self proclaimed novices thought the work was not novel enough, including in workshops...). I don't want a focus on utility because we shouldn't railroad research paths. This is often even incompatible with the concept of "novelty"! I'm happy to let researchers explore "dumb" ideas because if it works it works and if it doesn't I'd rather them write it down and let others know.

We need to SERIOUSLY consider the incentives of research, because I for one think they are not aligned with the goals.

I'm upvoting your comment not because I agree, but because it is an all too common sentiment I see, and I believe it is ruining science. The worst of Goodhart's Law: Goodhart's Hell. But you are welcome to disagree and I am happy to learn and understand the positions of others. I'm just in my little bubble trying to learn about other little bubbles.

[0] https://www.youtube.com/watch?v=Pl8BET_K1mc&t=2526s

[1] https://news.ycombinator.com/item?id=39648459

[jegp]

Thank you for your seriously thoughtful insights. You're saying we should have reproducibility, communication, and exploration. I fully agree with that, but I would like to push back on your point that novelty is destructive. Can't redundancy be similarly destructive? Given finite resources, shouldn't the authors have some responsibility to check their findings against previous insights? Otherwise, in the worst case, Goodhart can forget about his law because we'll never agree on any metrics in the first place.

To clarify, this is orthogonal to the point about the paper. I'm still not convinced it's entirely different, but I agree that the value of the paper doesn't purely depend on that. It's a nice exposition irregardless.

[godelski]

I'm not sure if you'll be surprised to find out that I agree with you.

Thing is, we're naturally inclined to pursue new things. There's already incredible amounts of natural pressure to pursue progress and innovate. It is much more lucrative regardless of the criteria for publication. Even the most modest of researchers are overjoyed when they find a clever solution or stumble on something no one else has before. We're naturally driven in this direction.

That said, I'm not going to claim this too isn't hackable. All metrics are hackable. My belief is just that metrics are guides, not answers. I believe Goodhart would agree, and that's his point. His point is yours, that no one will agree on metrics in the first place. Because the truth is, that no metric is perfectly aligned with a goal. His law isn't saying how to generate a good metric, his law is a warning about over reliance on metrics. To use them mindlessly.

The thing is you have to embrace the chaos. Maybe consider Pournelle's Iron Law of Bureaucracy as well. Bureaucrats can't create nuanced metrics, they must be mindless or else they would need an expert to interpret them in the first place.