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Thinking back on what I would've benefited from the most while growing up in an underserved community, neuroscience outreach workshops and lab tours would've been the most helpful. I believe hands-on experiences are the best at demystifying neuroscience in the younger population and sparking curiosity in the older population as well. The workshops could be, for example, visiting a classroom or community center, guiding the participants through brain dissections and explaining the different structures along with their function. Lab tours are also beneficial as they help students envision what an academic career in neuroscience would be like, and allow for the older population to get a better understanding of how experiments are done. As Hugo rightly pointed out, accessibility is key. Explaining concepts without overwhelming jargon is essential for maintaining the attention of non-scientists and maximizing understanding of the concepts being explained. By making neuroscience easy to understand and relatable, we can further its dissemination.

This is a great question to consider and discuss, because AI has the potential to exacerbate the existing rigor and reproducibility crisis, or to ameliorate it. As a contractor doing Program Development at NIA, I work on the Alzheimer's Preclinical Efficacy Database, or AlzPED (https://alzped.nia.nih.gov/) and analysis of publications in the field of testing Alzheimer's therapeutics in animal models shows the trends of poor rigor and reporting practices that are not getting better over time (atleast not fast enough). A crucial aspect of AI/ML models is that junk-in means junk-out - that is, the integrity of the data that models are trained on will dictate the utility and validity of these models. In considering how AI may intersect with rigor and reproducibility - it does come down to how scientists may use any other tool. Researchers, journals, non-profits, and funding agencies need to work to improve the rigor and reproducibility crisis, and as suggested previously, develop best practices, standards, and accountability measures for AI in parallel.

I'd like to raise 2 points for consideration and discussion of this topic. 1) I've learned a lot about neuroscience communication since the publication of my book, Baby Senses. I've been trying to learn from the artist and children's fiction writers communities how to make science more engaging. I often find that non-fiction can come across as dry and boring while fiction - even while being factual - can come across as enchanting and interesting. I've myself been using principles of story telling, art, and narrative creative non-fiction to get a lay audience interested in science, and have, for BAW 2024, used puppets to engage very young audiences in sensory neuroscience (in a collaborative project). 2) While communicating to communities traditionally under-represented in STEM and neuroscience, it is important to go in with a nuanced and considered approach. Once, when I was TAing a summer high school biology/histology class for first nations students during my Masters, I came out of the class thinking I had been incomprehensible. I kept attempting to make the session interactive and waiting for their response without understanding that culturally it is unusual for first nation communities to participate in interactions without "electing" a representative to speak for the group. This was very eye opening for me - when I read the teacher evaluations, the students still rated my class as one of the best they'd been to, which was completely contrary to my impressions. All this to say, when I approach neuroscience communication, I try to meet people where they are at and use a nuanced approach since minorities in science can feel easily discouraged from neuroscientific careers and a one-size-fits-all approach doesn't work.

I think there are 2 main ways to do this. The first is to create opportunities, from elementary school to the final years of graduation, integrating neuroscience into their lives and conveying the concept that neuroscience is not restricted to the laboratory or operating room. Neuroscience is all around us, it explains what we are! I think it should be taught like mathematics, geography, etc. I believe that also creating jobs and opportunities for employment, for studying at universities, is also a great idea, bringing the community together to take up positions, be interested in science, whether through extension courses. Regarding underserved communities, I think that outreach programs are vital. It is important that leaders in neuroscience, in the health area, educators, etc., get closer to vulnerable populations, going to these places, talking to people, understanding what they need, their desires, carrying out educational programs. Involving the leaders of these communities is a great strategy, and the experiences that can be shared are always rewarding. Many people need is just a chance for someone to believe in them, and if we have the chance to be this someone is just amazing

Neuroglionanobots… a pretty cool name, right? In the past, I considered myself a huge fan of IA, however, I didn’t consider how much AI could impact our work as scientists. I didn’t consider how many human activities can be affected by this new way of getting, organizing, and managing information. However, there are dark paths in which we need to be careful. The other day I saw a Facebook post in which a young fella showed how to do a Facebook place to get money. This guy showed how the AI was capable of choosing the best topic (health and self-care in this example), and the AI was capable of creating evidence that supports the contents of the page and creating smart quotes or highlights to get attention. At the end, this guy looks at the camera, so proud of his “work” and says that all this work was done in minutes thanks to the AI. So many problems in that post, in the first instance, one guy without any kind of preparation in health, medicine, pharmacy, etc. can do a place to advise on self-care and nutrition; secondly, nobody can corroborate the information because there is no clear how the IA took the information from the web; in third place, where is the ethics of doing in that way?; I can continue, but I believe that my point is out there. The IA feeds itself from the entrances that we do regularly, in the form of papers, books, blogs, comments, etc. but if we continuously use it to produce the products used for their feedback, then what??? Did you see the problem??? In the long term, the IA could be fed in a loop without entrance from the exterior… I know that I may be Im overreacting, but the truth is that we need laws to regulate the use of AI; we need to incorporate ethics in this discussion and we need to show to the new generations the implications of the misuse of AI. Long Live and Prosper humans

Hi brains!!! The first thing I should like to said, is that all this is my point of view obviously. We should start saying that we need to recognize that the knowledge is a right, and that all persons should have access to knowledge. If we understand that, we should create better programs in which we can introduce the science since the first levels of education. I believe that the later introduction in science in our lives, allows the pseudoscience to grown, allows the superstite behavior to establish and explain the world. In Mexico we have communities extremely poor. Unfortunately in this populations there is no schools, no science programs and evidently there is so much pseudoscientific believes. We need to bring the science to the communities, we need to do better efforts to explain in different word (far away of the scientific language) and let the science mesmerize the children in this communities in the same way that the science mesmerize ourselves (well, at least is my case). We need to do better science divulgation and better science programs for the elders for example. The elders are an abandoned group with needs for explanations and better understanding of their brains. obviously more science programs for young people... more science for everybody.

Hello my dear neuroscientists... I was once in the Gallaudet University a few years ago. I decided to visit it thanks to one of my favorite book from Oliver Sacks (seeing voices). In this book we are introduced, not only in neurobiological mechanisms in the brain of deaf people but in the struggle of the deaf persons in searching of their own spaces and representation. In my mind one university like that it should be silent, without the noise and the sounds of students voices and lessons, etc. Let me share that I was SO WRONG. The university is full of live with sounds and movements. The knowledge flows with the hands and arms and I was there, trying of figure out how that was possible. In this point I would like to add that the American Sign Language (ASL) is a language!!, is not French is not Spanish or English. It has rules, gramar and intonation (the processing of the ASL is in the same regions that the oral language, left hemisphere). However in a world of hearing people sometimes it hard to be deaf. Only a few universities around the world offers higher education for the deaf people. That means that the path of the deaf persons is hard, full of challenges and mountains to climb. But when we read stories like Melody`s I feel good, because the science it should be a right for everybody how wanted to be in. The science is inclusive doesn't matter the condition or gender or whatever. However for someones is harder than others. I shared the article with my students here in Mexico and they were so amazed for the conditions and challenges for the deaf persons. Sadly in Mexico we don't have an institution (like Gallaudet) for higher education of the deaf persons. But I hope that this kind of stories change the mind of the new generations. Best

Dr. Matthew Dalva is the Presidential Chair, Director of the Tulane Brain Institute and Professor of Cell and Molecular Biology. His research is focused on synapses biology. His lecture Seeing into the Synapse was an introduction to the study of synapses – how they form, how they are maintained, and what are the factors that affect their attributes (such as size and strength). One fascinating aspect of synapses is that they are quite sparse. While a single dendritic spine (protrusions from dendrites at the end of which synapses may form) may touch about 12 different axons, only one forms the synapse. To investigate questions like how decisions about synapse formation and maintenance are executed at the molecular and nano scales, Dr. Dalva discussed a series of experiments. The role of ephBs and ephrinBs (found in dendritic filopodia) in synapse formation was highlighted using knock-out animal models resulting in 40% fewer spine synapses, and the restoration of these proteins rescued synapse formation. Subsequent modeling of the role of EphB signaling demonstrated that while rapid photoactivation of this protein results in the retraction of filopodia to seek new targets, slow and sustained activation of this protein triggers synapse formation indicating that the rate of activation is the key to determining synapse formation. Next, Dr. Dalva discussed elements of structural features of a synapse and using super-resolution synaptic imaging shed light on the nano-scale order within synapses. The beautiful images of the synapses and quantification of these revealed nanocolumns of clustered proteins which determine synaptic strength/integrity – there was a correlation between number of the nanoscale column structures and size of the spine. Further investigation from his lab revealed that physical processes like liquid-liquid phase separation can play an important role in how proteins cluster to form these nanocolumns and determine synapse strength, both at the pre-synaptic and post-synaptic sites. As a neuroscientist and a neuroartist, I was very excited to tune in to this SfN webinar in March 2024. The title drew me in on multiple levels, the primary being curiosity to understand the synapse, the point of connection between neurons that forms the building blocks of all the amazing feats of nervous systems. I was also hoping for beautiful images of neuroart, and this lecture did not disappoint on any level. The lecture spanned many aspects of synapse biology – protein-protein interaction, structure-function relationships, biophysics, temporality of synapse formation, etc., and the rich discussions during the Q&A further expanded it. The discussion covered topics related to how synapse elements might be changing and how they can be measured during development, aging, disease, etc., as well as how these nanoscale elements might generalize across type of neurons (excitatory vs inhibitory). I would recommend this lecture to all neuroscientists with an interest in synapse biology.

I think the general principle of scientific research must always be ethics, and the neuroscientist must keep this in mind. So, I cannot conceive of a world where neuroscience is not linked to ethics, even though I know that this is not always true. I believe that the full use of ChatGPT without it being only instrumental for ideas (or helping with creativity blocks - who hasn't never had them?) is wrong and it goes against the ethical principles of intellectual property or creativity, of expression of science as a whole. ChatGPT does not obey the rules of academia, and still does not obey the rules of science. That said, the reality is that ChatGTP , Leonardo and others are here to stay. And if so, we should see it naturally and as a sign of the cultural revolution and the passage of time. And better than anything else, Neuroscience aways had thrived in challenge times. We have all the tools to adapt, so neuroscience and neuroscientists will adapt to this new cultural and intellectual transformation.But we need to have rules and establish standards of conduct about the instrumental , not protagonist, use of artificial intelligence .We need to stablish good practices and make use of verification tools (like AI detector programs).There are already good artificial intelligence detectors and I believe that they may be useful for scientific websites and accontable neuroscience journals . ChatGTP is a cultural , intelectual and social transformation . And like everything in humankind history, we must learn to adapt in a good and ethical way. Neuroscientists can play an important role in this adaptation and ajust ChatGTP to this new world of us.

I think leaders in the brain science community should lead efforts to include everyone. We need embrace all kinds of people because brain science does best when it has lots of different minds working on challenges together! People with different physical or mental traits, whether that features make things hard for them or help them , are really important for making the science world more interesting. I see this not only in this scientist's story 9which is amazing and inspiring), but in my own family too. My sister is an amazing doctor, despite having one-sided deafness, which she got as an adult. It was tough for her to deal with this new way of hearing, and it changed how she sees the world. But she had to adapt, and it also brought out new talents in her, making her better at her job. As a doctor, she got better at feeling things, seeing things, analizing patient's anatomy, all very important skills for her work. So, even though she was great before she lost her hearing, now she's even better. I admire her for inspiring her students and other doctors. And as an impaired hearing surgeon, she got really interested in brain science and I tease her that she is an honorary neuroscientist. I believe that it's our job to help people to adapt, embrace and live tho the fullest.