#radioactive commentary, w/ apologies to all admirable people of #BrainSTOA working hard on #DataSharing. This highlights a need to broaden #sharing to #computations & #insights. Premises were clear in Ngai’s “data resource development”, Bjaalie’s “modeling workflow” #Teamscience
Data sharing is good. Too much data creation, objectionable. Overreliance of data might be used to obfuscate gaps in theory, analysis and interpretation. Data is also a currency for misused scientific power. #InclusiveScience
At this point, we should also focus on sharing #ComputationalTools (and explaining them, and building expertise in using them). #ComputationalNeuroscience.

We should enhance collective vetting of our interpretations of their meaning.
We developed a cult for data because reliance on soft thoughts processes failed us in the past. But we went to far and lost the enormous respect due to computing and (collective) thinking. #BalanceTheoryExperiment
If only I could have had 1M$ each time I heard a B.R.A.I.N. initiative PI say: “I have sh!tloads of data, don’t know what to do with them, will give you crumbs for help analyze!” #gatekeepers
To pollinate Data Sharing, I think #BRAINSTOA and other agencies need to invest in sharing, training for their computational analysis tools. This was too discretely mentioned yesterday morning.
#ComputationalNeuroscience
#BRAINSTOA and other federations/agencies could also invest in collective forms of debate to vet data, analysis and interpretation and create a more integrated theory of the brain. #SharingTheories Publishing incentivize against meaning integration. "a scientist would rather share their colleague's tooth
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More from @ETognoli

5 Oct
1/6 Dear Colleagues from Computer Science, HCI & Artificial Intelligence, let me present a preprint with my colleague @shihonghuang . "Emotionally-Informed Decisions: Bringing Gut's Feelings into Self-adaptive and Co-adaptive Software Systems" at arxiv.org/abs/2110.01503 #emotions
2/6 My software engineer colleague @shihonghuang and I reflected on the enormous parallelisms between the cognitive aids that are software systems and human cognition, in particular decision-making and emotion. It led us to conceptualize a software system with gut's feeling. Even as software systems are rapidly gaining skills that bea
3/6 In a section aimed at Computer Scientists, we reviewed the neurobiological and behavioral basis of #DecisionMaking. We examined factors that affect it, in particular uncertainty, risk, time and emotion. intention, planning, valuation, choice, response selection,
Read 6 tweets

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