Real-time decoding of question-and-answer speech dialogue using human cortical activity.

Natural communication often occurs in dialogue, differentially engaging auditory and sensorimotor brain regions during listening and speaking. However, previous attempts to decode speech directly from the human brain typically consider listening or speaking tasks in isolation. Here, human participants listened to questions and responded aloud with answers while we used high-density electrocorticography (ECoG) recordings to detect when they heard or said an utterance and to then decode the utterance's identity. Because certain answers were only plausible responses to certain questions, we could dynamically update the prior probabilities of each answer using the decoded question likelihoods as context. We decode produced and perceived utterances with accuracy rates as high as 61% and 76%, respectively (chance is 7% and 20%). Contextual integration of decoded question likelihoods significantly improves answer decoding. These results demonstrate real-time decoding of speech in an interactive, conversational setting, which has important implications for patients who are unable to communicate

A compact to revitalise large-scale irrigation systems using a leadership-partnership-ownership ‘theory of change’

In countries with transitional economies such as those found in South Asia, large-scale irrigation systems (LSIS) with a history of public ownership account for about 115 million ha (Mha) or approximately 45% of their total area under irrigation. In terms of the global area of irrigation (320 Mha) for all countries, LSIS are estimated at 130 Mha or 40% of irrigated land. These systems can potentially deliver significant local, regional and global benefits in terms of food, water and energy security, employment, economic growth and ecosystem services. For example, primary crop production is conservatively valued at about US$355 billion. However, efforts to enhance these benefits and reform the sector have been costly and outcomes have been underwhelming and short-lived. We propose the application of a 'theory of change' (ToC) as a foundation for promoting transformational change in large-scale irrigation centred upon a 'global irrigation compact' that promotes new forms of leadership, partnership and ownership (LPO). The compact argues that LSIS can change by switching away from the current channelling of aid finances controlled by government irrigation agencies. Instead it is for irrigators, closely partnered by private, public and NGO advisory and regulatory services, to develop strong leadership models and to find new compensatory partnerships with cities and other river basin neighbours. The paper summarises key assumptions for change in the LSIS sector including the need to initially test this change via a handful of volunteer systems. Our other key purpose is to demonstrate a ToC template by which large-scale irrigation policy can be better elaborated and discussed

Inferring Population Dynamics in Macaque Cortex

The proliferation of multi-unit cortical recordings over the last two decades, especially in macaques and during motor-control tasks, has generated interest in neural "population dynamics": the time evolution of neural activity across a group of neurons working together. A good model of these dynamics should be able to infer the activity of unobserved neurons within the same population and of the observed neurons at future times. Accordingly, Pandarinath and colleagues have introduced a benchmark to evaluate models on these two (and related) criteria: four data sets, each consisting of firing rates from a population of neurons, recorded from macaque cortex during movement-related tasks. Here we show that simple, general-purpose architectures based on recurrent neural networks (RNNs) outperform more "bespoke" models, and indeed outperform all published models on all four data sets in the benchmark. Performance can be improved further still with a novel, hybrid architecture that augments the RNN with self-attention, as in transformer networks. But pure transformer models fail to achieve this level of performance, either in our work or that of other groups. We argue that the autoregressive bias imposed by RNNs is critical for achieving the highest levels of performance. We conclude, however, by proposing that the benchmark be augmented with an alternative evaluation of latent dynamics that favors generative over discriminative models like the ones we propose in this report.Comment: 23 pages, 10 figures, 4 table

Developing effective institutions for water resources management: A case study in the Deduru Oya Basin, Sri Lanka

River basins / Water resource management / Water lifting / Wells / Domestic water / Population / Economic aspects / Income / Irrigation programs / Institutions / Policy / Groundwater / Agricultural development / Fish farming / Pumps / Ecology / Water supply / Drought / Poverty / Land use / Water scarcity / Natural resources / Agricultural production / Cropping systems

Analytic solutions of the 1D finite coupling delta function Bose gas

An intensive study for both the weak coupling and strong coupling limits of the ground state properties of this classic system is presented. Detailed results for specific values of finite $N$ are given and from them results for general $N$ are determined. We focus on the density matrix and concomitantly its Fourier transform, the occupation numbers, along with the pair correlation function and concomitantly its Fourier transform, the structure factor. These are the signature quantities of the Bose gas. One specific result is that for weak coupling a rational polynomial structure holds despite the transcendental nature of the Bethe equations. All these new results are predicated on the Bethe ansatz and are built upon the seminal works of the past.Comment: 23 pages, 0 figures, uses rotate.sty. A few lines added. Accepted by Phys. Rev.