I found many aspects of this paper to be most helpful and interesting.
In the abstract, she says "I argue that the most pressing philosophical questions at the intersection of neuroscience and artificial intelligence are ultimately concerned with defining the phenomena to be explained and with what constitute valid explanations of such phenomena". (not an easy thing to do!)
And as taken from the Introduction: "...Perhaps especially because of the diverse background assumptions of my collaborators, I was encouraged to question the most basic aspects of my research. Why was I doing this research? To what scientific goal would my research contribute? How were the proposed methods suited to that goal? I found it very challenging to situate my research into a broader scientific enterprise. .....This eventually led me to read more philosophy of science, especially about explanation and understanding. Learning about these topics, which are not typically covered in science training programs, made it easier to step back to see the bigger picture. Scientists, compared with philosophers, may generally be more concerned with the finer details of science: the outcomes of specific experiments, an individual’s research program,or the verification of a particular hypothesized causal relationship. .....This learning journey made me realize that my field is at risk of reinventing the wheel when it comes to these discussions about the merits of different scientific approaches and models..."
And have cited it in the beginning of my 2024 insight article:
"The amount of data that can be gathered about the human brain has been growing exponentially in recent years, but it could be argued that relatively little progress has been made in actually understanding how the brain works. While there may be sociological and philosophical reasons for this lack of progress (see, for example, Thompson, 2021), a main reason is the low level of interactions between the experimental and theoretical/modeling communities in neuroscience (Marder, 2015). Bridging this divide will be difficult because it requires researchers on both sides to leave their comfort zones and learn more about each other’s work, including the constraints that both sides work under. If not, there is a risk that the results of beautiful experiments, or the outputs of thoughtful models, will not be fully appreciated by everyone working in that particular field of neuroscience."