Biologically Plausible Learning on Neuromorphic Hardware Architectures

With an ever-growing number of parameters defining increasingly complex networks, Deep Learning has led to several breakthroughs surpassing human performance. As a result, data movement for these millions of model parameters causes a growing imbalance known as the memory wall. Neuromorphic computing is an emerging paradigm that confronts this imbalance by performing computations directly in analog memories. On the software side, the sequential Backpropagation algorithm prevents efficient parallelization and thus fast convergence. A novel method, Direct Feedback Alignment, resolves inherent layer dependencies by directly passing the error from the output to each layer. At the intersection of hardware/software co-design, there is a demand for developing algorithms that are tolerable to hardware nonidealities. Therefore, this work explores the interrelationship of implementing bio-plausible learning in-situ on neuromorphic hardware, emphasizing energy, area, and latency constraints. Using the benchmarking framework DNN+NeuroSim, we investigate the impact of hardware nonidealities and quantization on algorithm performance, as well as how network topologies and algorithm-level design choices can scale latency, energy and area consumption of a chip. To the best of our knowledge, this work is the first to compare the impact of different learning algorithms on Compute-In-Memory-based hardware and vice versa. The best results achieved for accuracy remain Backpropagation-based, notably when facing hardware imperfections. Direct Feedback Alignment, on the other hand, allows for significant speedup due to parallelization, reducing training time by a factor approaching N for N-layered networks

Science at the Heart of Psychotherapy: A Review of Three Evidence-Based Treatments

Changes in the U.S. healthcare system over the past fewdecades have led to a transformation of the mental healthfield. The demand for accountability and the need for effective,cost-efficient treatments have spurred the movementtoward evidence-based practices. Today, a number of empiricallybased psychotherapies exist that have proven efficaciousin the treatment of a wide range of physical and psychologicaldisorders. Despite the strong evidence base for these treatments,their dissemination and implementation have beenslow. The intention of the present article is to summarize themajor characteristics of three types of psychotherapy (cognitivebehavioral therapy, acceptance and commitment therapy,and dialectical behavior therapy) that have received muchempirical support and have demonstrated applicability to awide range of both mental and medical problems. For eachtreatment, some background information is provided, alongwith the theoretical underpinnings of the treatment, a summaryof the current state of the evidence, and limitations andcriticisms in the literature

The feasibility and effects of eye movement training for visual field loss after stroke: a mixed methods study

Acknowledgements The author(s) would like to thank the designers of all included scanning training tools for providing free access during this study. They wish to note that MyHappyNeuron is designed for a general population, and a version specifically for healthcare use (HappyNeuron Pro) is also available. We would also like to thank the low vision centres and rehabilitation officers involved in this study Funding This study was funded by the Stroke Association (UK) by way of a Junior Research and Training Fellowship held by the lead author (TSA JRTF 2011/02). MCB, AP and the NMAHP Research Unit are funded by the Scottish Government Health and Social Care Directorates. The views expressed here are those of the authors and not necessarily those of the funders.Peer reviewedPublisher PD

Relationship of stream flow regime in the western Lake Superior basin to watershed type characteristics

To test a conceptual model of non-linear response of hydrologic regimes to watershed characteristics, we selected 48 secondand third-order study sites on the North and South Shores of western Lake Superior, MN(USA) using a random-stratified design based on hydrogeomorphic region, fraction mature forest, and fraction watershed storage (lakeCwetland area/watershed area). We calculated several commonly used hydrologic indices from discharge and velocity estimates, including daily flow indices, overall flood indices, low flow variables, and ratios or ranges of flow percentiles reflecting the nature of cumulative frequency distributions. Four principal components (PCs) explained 85.9 and 88.6% of the variation of flow metrics among second- and third-order stream sites, respectively. Axes of variation corresponded to a runoff vs. baseflow axis, flow variability, mean flow, and contrasts between flood duration and frequency. Analysis of velocity metrics for third-order streams yielded four PCs corresponding to mean or maximum velocity, Froude number, and inferred shear velocity, as well as spate frequencies vs. intervals associated with different velocity ranges. Using discriminant function analysis, we could discriminate among watershed classes based on region, mature forest, or watershed storage as a function of flow metrics. For second-order streams, median flow (Qs50) increased as watershed storage increased. North Shore streams showed a more skewed distribution and greater spread of discharge values than did South Shore streams for both stream orders, while third-order North Shore streams exhibited a higher frequency of spates. Independent of regional differences, loss of mature forest increased the range of variation between baseflow and peak flows, and depressed baseflow. Consistent with our initial model for watershed classification, Classification and Regression Tree (CART) analysis confirmed significant thresholds of change in flow metrics averaging between 0.506 and 0.636 for fraction mature forest and between 0.180 and 0.258 for fraction watershed storage

Book Review: \u3ci\u3eWhy Are All the Black Kids Sitting Together in the Cafeteria? and Other Conversations About Race\u3c/i\u3e

Why Are All the Black Kids Sitting Together in the Cafeteria? and Other Conversations About Race is a 2017 revised and updated edition to Dr. Beverly Daniel Tatum’s original book written in 1997. The book explores decades of research on the psychology of racism, with an emphasis on the psychology of racial identity in Black, White, and other ethnic and cultural identities. The author helps readers gain a better understanding of historic and modern racism and the implications it has on individuals today. The book also contains important messages for people who work with diverse groups of adults and particularly of youth