I enjoyed Venniro et al’s article, but I feel that their narrative suffered from the over-inclusion of too much data. To me, I wish the paper had been split into two separate articles, a methods piece, and a manipulation/exploration piece. I think that they spent a great deal of time in the discussion talking about the translational impact this new behavioral paradigm provides and discussing why it’s more accurate of human addiction. Because of this, they ignored the latter part of their research on implicating PCK∂ cells and the neuronal correlate of this behavior. I think that in terms of a nature article, I expect more of that in targeting specific neuronal populations and determining their role in a particular behavior. Additionally, I think that their methods suffered greatly from a lack of detailed explanation of every step of the timeline. I found their first figure on the whole quite confusing and still don’t quite understand what all of the graphs indicate. This behavior is incredibly long as far as a lot of behavioral paradigms go. I feel that the graphic they produced does not completely explain what’s going on and when and what the graphs are showing in retrospect. There are numerous amount of sessions and trails that all happen on different days for different amounts and different times. Additionally, this behavior requires a custom-built apparatus that I think would have benefited from a graphic replication. Even with the insufficient graphic, their textual explanation in the paper itself was not sufficient without seeking the supplementary data. I think that this new behavioral context could have warranted an entirely separate methods paper, detailing the specifics of the paradigm and the pros and cons of its usage. Ultimately, the authors argue that this behavior is far more translationally relevant and would, in theory, benefit from wide application in many labs then. I think that the lack of specific focus on methods separate from parsing out the modifications of the operant condition with social option weakens the ultimate impact of their findings. I found myself struggling to understand the entire timeline of their methods and felt that their neural exploration was insufficient and could have been deeper. I would have liked to have seen some sort of optogenetic or chemogenetic manipulation. If they found that this population of cells is implicated in this behavior of addition, I would have liked to see a more thorough dive into the underlying mechanism or a more concrete circuit exploration. The addition of the Immuno and RNAscope data feels secondary to the paper, but it’s actually quite important that they were able to target a specific group of cells that could mediate the protective nature of social-choice in addiction recovery. Because of the need to focus on the justification of the paradigm itself, the importance of the circuit is lost. I know that NatureNeuro limits the number of figures to 5 and I think that because of this, the behavioral explanation feels incomplete and I feel that from the first experiment I’m at a deficit on understanding what’s going on in the paper. I felt I wanted a separate and thorough explanation of the behavior and it’s specific benefits and limitations as it can be applied to drug research.
I think that Guglielmo et al did a better job of centering their narrative and focusing on the CRF pathway as a major role in addiction behaviors in alcohol-dependent rats. I do wish that they would have done a round of controls in the opposite direction and see if CRF cells are responsible for bidirectional control of alcohol-addiction behaviors. If they were to additionally optogenetically over-activate these CRF cells, would we see a quantifiable increase in alcohol-related behaviors? I think that they controlled for their experiment really well, but I would like to see what the effect of overactivation had on behavior. Going forward, I think that identifying the other 20% of the activated cells in the Central amygdala will be key to understanding the entire ensemble and the microcircuit responsible for the data they saw. I think that the application of single-cell RNAseq would benefit them greatly. Because they are looking at a cell population that is already labeled with fluorescence, they can FACS easily and apply additional clustering to determine within the transcriptionally active populations what their genetic identification is. I think exploring the potential microcircuit in the inactivation of CRF cells that limits alcohol-seeking behaviors would be fascinating. I’d like to see a more in-depth tracing experiment to determine what cells the CRF population monosynaptically synapses onto. Additionally, of these cells what are their identifications. I think it’s possible that these cells might be SST+ interneurons. In a fear context within the Amygdala, PV cells synapse onto SSTs and through disinhibition, we see the expression of fear learning in freezing behaviors. It could be possible in a plain state, that these CRF cells are also synapsing onto SST axons and causing local disinhibition that allows for the activation of the BNST pathway. By introducing GABAergic antagonists and then manipulating further interneurons populations, one can begin to elucidate the neuronal circuit responsible. I think what would be particularly telling would be an ephys experiment in vitro of recording from nearby interneurons after inactivation/activation of the CRF population in the CeA. Prior to my work in the Dimidschstein lab, I never fully understood how important interneurons are. The path of cellular communication is not straight and often these cells are largely responsible for the minute differences we see in the behavioral output.
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