Dataset Information

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

ABSTRACT: The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens through which to reconsider some previously published neurophysiological data. To allow for direct comparison with our own data, we trained the neural network to perform binary risky choices. We find that value correlates are ubiquitous and are always accompanied by non-value information, including spatial information (i.e., no pure value signals). Evaluation, comparison, and selection were not distinct processes; indeed, value signals even in the earliest stages contributed directly, albeit weakly, to action selection. There was no place, other than at the level of action selection, at which dimensions were fully integrated. No units were specialized for specific offers; rather, all units encoded the values of both offers in an anti-correlated format, thus contributing to comparison. Individual network layers corresponded to stages in a continuous rotation from input to output space rather than to functionally distinct modules. While our network is likely to not be a direct reflection of brain processes, we propose that these principles should serve as hypotheses to be tested and evaluated for future studies.

SUBMITTER: Balasubramani PP

PROVIDER: S-EPMC5882864 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

Balasubramani Pragathi P PP Moreno-Bote Rubén R Hayden Benjamin Y BY

Frontiers in computational neuroscience 20180328

The brain uses a mixture of distributed and modular organization to perform computations and generate appropriate actions. While the principles under which the brain might perform computations using modular systems have been more amenable to modeling, the principles by which the brain might make choices using distributed principles have not been explored. Our goal in this perspective is to delineate some of those distributed principles using a neural network method and use its results as a lens ...[more]

PMID: 29643773

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Project description:BackgroundMedical schools with distributed or regional programs encourage people to live, work, and learn in communities that may be economically challenged. Local spending by the program, staff, teachers, and students has a local economic impact. Although the economic impact of DME has been estimated for nations and sub-national regions, the community-specific impact is often unknown. Communities that contribute to the success of DME have an interest in knowing the local economic impact of this participation. To provide this information, we estimated the economic impact of the Northern Ontario School of Medicine (NOSM) on selected communities in the historically medically underserviced and economically disadvantaged Northern Ontario region.MethodsEconomic impact was estimated by a cash-flow local economic model. Detailed data on program and learner spending were obtained for Northern Ontario communities. We included spending on NOSM's distributed education and research programs, medical residents' salary program, the clinical teachers' reimbursement program, and spending by learners. Economic impact was estimated from total spending in the community adjusted by an economic multiplier based on community population size, industry diversity, and propensity to spend locally. Community employment impact was also estimated.ResultsIn 2019, direct program and learner spending in Northern Ontario totalled $64.6 M (million) Canadian Dollars. Approximately 76% ($49.1 M) was spent in the two largest population centres of 122,000 and 165,000 people, with 1-5% ($0.7 M - $3.1 M) spent in communities of 5000-78,000 people. In 2019, total economic impact in Northern Ontario was estimated to be $107 M, with an impact of $38 M and $36 M in the two largest population centres. The remaining $34 M (32%) of the economic impact occurred in smaller communities or within the region. Expressed alternatively as employment impact, the 404 full time equivalent (FTE) positions supported an additional 298 FTE positions in Northern Ontario. NOSM-trained physicians practising in the region added an economic impact of $88 M.ConclusionsBy establishing programs and bringing people to Northern Ontario communities, NOSM added local spending and knowledge-based economic activity to a predominantly resource-based economy. In an economically deprived region, distributed medical education enabled distributed economic impact.

Dataset Information

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

Publications

Using a Simple Neural Network to Delineate Some Principles of Distributed Economic Choice.

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