Shaping dynamical neural computations using spatiotemporal constraints

Dynamics play a critical role in computation. The principled evolution of states over time enables both biological and artificial networks to represent and integrate information to make decisions. In the past few decades, significant multidisciplinary progress has been made in bridging the gap between how we understand biological versus artificial computation, including how insights gained from one can translate to the other. Research has revealed that neurobiology is a key determinant of brain network architecture, which gives rise to spatiotemporally constrained patterns of activity that underlie computation. Here, we discuss how neural systems use dynamics for computation, and claim that the biological constraints that shape brain networks may be leveraged to improve the implementation of artificial neural networks. To formalize this discussion, we consider a natural artificial analog of the brain that has been used extensively to model neural computation: the recurrent neural network (RNN). In both the brain and the RNN, we emphasize the common computational substrate atop which dynamics occur -- the connectivity between neurons -- and we explore the unique computational advantages offered by biophysical constraints such as resource efficiency, spatial embedding, and neurodevelopment.Comment: 7 figures, 18 page

2021 Adult Foster Home Resident and Community Characteristics Report on Adult Foster Homes

This report describes results from an annual study of Oregon adult foster homes (AFH). Data contained in this report include home and owner characteristics; monthly charges and payment sources; and resident characteristics, personal and health-related needs. The study’s purpose was to collect and report data that can inform and advise policymakers, state and county agency staff, aging advocates and AFH owners about the status of AFHs in Oregon. These data were collected between December 2020 and February 2021. This report constitutes the first year during the COVID-19 pandemic that these annual data were collected

2021 Community-Based Care: Resident and Community Characteristics Report on Assisted Living, Residential Care, and Memory Care Communities

This report summarizes findings from the 7th annual study of Oregon assisted living (AL) and residential care (RC) facilities, including memory care (MC) communities. The purpose of this report is to inform Oregon Department of Human Services (ODHS), providers, consumers, and other interested parties about this sector of long-term services and supports (LTSS) and ensure data-informed policy decisions. The report contains information about various resident and community characteristics, including capacity and supply, resident demographics and health services use, and community services, policies, fees, and staffing. These data were collected between winter 2020 and spring 2021. This report constitutes the first year during the COVID-19 pandemic that these annual data were collected