Circuit neuroscience: the road ahead
Rafael Yuste · Frontiers in Neuroscience · 2008
It is difficult to write about grand challenges in our field without pontificating or pretending to show a degree of certainty in assessing the field that I do not possess.I would rather comment on a few of the issues that particularly worry me.Therefore, this article is just a snapshot of our field now, as I see it, and encourage readers to read it as the opinion of just one of their colleagues.My comments are aimed at Circuit Neuroscience.What exactly is Circuit Neuroscience?As stated in the mission statement of Frontiers in Neural Circuits, I follow the definition of Circuit Neuroscience as the understanding of the computational function of neural circuits, linking this function with the circuit micro-structure.Within this field, I will address three different types of challenges: scientific, methodological and sociological ones.scientific problems: I think that it is fair to say that we are profoundly ignorant about the structure and function of neural circuits.One could say that the goal of our field is to reverse-engineer biological circuits and that in order to do so we need to know their structure and logic, so that we can understand their computational algorithms.Like engineering students in their final college exam, we are attempting to decipher the "transfer function" of unknown circuits, this time biological ones.To do so effectively, for most neural circuits in most species, we need to solve the following problems:Cell Types Problem: In terms of the structure of neural circuits, one of the fundamental problems we are facing generally is that we still do not know which is the exact complement of neuronal cell types present.In spite of more than a hundred years of neuroanatomy, this issue is still not resolved and it is difficult to imagine how we could reverse engineer a circuit without knowing the list of its parts.Why are we still ignorant of this list?Besides the fact that the neuronal cell types don't come pre-labeled and that they are normally mixed together, anatomical efforts in the past have been essentially qualitative, often without clear criteria to differentiate between cell types.The introduction of quantitative anatomical approaches is greatly helping in discerning among cell types.Also, classifications of neurons are increasingly relying on a multifaceted description of their phenotypes, encompassing not just anatomical, but also electrophysiological and molecular