Local spatial analysis: an easy-to-use adaptive spatial EEG filter

Spatial EEG filters are widely used to isolate event-related potential (ERP) components. The most commonly used spatial filters (e.g., the average reference and the surface Laplacian) are "stationary." Stationary filters are conceptually simple, easy to use, and fast to compute, but all assume that the EEG signal does not change across sensors and time. Given that ERPs are intrinsically nonstationary, applying stationary filters can lead to misinterpretations of the measured neural activity. In contrast, "adaptive" spatial filters (e.g., independent component analysis, ICA; and principal component analysis, PCA) infer their weights directly from the spatial properties of the data. They are, thus, not affected by the shortcomings of stationary filters. The issue with adaptive filters is that understanding how they work and how to interpret their output require advanced statistical and physiological knowledge. Here, we describe a novel, easy-to-use, and conceptually simple adaptive filter (local spatial analysis, LSA) for highlighting local components masked by large widespread activity. This approach exploits the statistical information stored in the trial-by-trial variability of stimulus-evoked neural activity to estimate the spatial filter parameters adaptively at each time point. Using both simulated data and real ERPs elicited by stimuli of four different sensory modalities (audition, vision, touch, and pain), we show that this method outperforms widely used stationary filters and allows to identify novel ERP components masked by large widespread activity. Implementation of the LSA filter in MATLAB is freely available to download.NEW & NOTEWORTHY EEG spatial filtering is important for exploring brain function. Two classes of filters are commonly used: stationary and adaptive. Stationary filters are simple to use but wrongly assume that stimulus-evoked EEG responses (ERPs) are stationary. Adaptive filters do not make this assumption but require solid statistical and physiological knowledge. Bridging this gap, we present local spatial analysis (LSA), an adaptive, yet computationally simple, spatial filter based on linear regression that separates local and widespread brain activity (https://www.iannettilab.net/lsa.html or https://github.com/rorybufacchi/LSA-filter)

Peletização de sementes de milheto

The pearl millet seed is small and its size varies, making sowing more difficult. The pelleting technique increases and homogenizes seed size, but it is essential to determine the physical and physiological characteristics of pelleted seeds. The physiological analysis consisted of: first germination count, final germination, speed emergence index, and seedling emergence. Physical analysis consisted of determining the 1000-seed weight, 1000-seed volume and fragmentation. The control treatment did not receive any coating, and the other 36 treatments combined four binders: bentonite, polyvinyl acetate (PVA), polyvinylpyrrolidone (PVP) and methyl cellulose (Methocel®), and nine powder coating products: microcellulose, plaster, vermiculite, magnesium thermophosphate (Yoorin®), phytic acid, dicalcium phosphate, super simple phosphate (SS), monoamonic phosphate (MAP) and reactive phosphate. Among the materials used to form the pearl millet pellet, the most efficient binders were the polyvinyl acetate and the methyl cellulose, and as coaters, the vermiculite and the microcellulose.As sementes de milheto são pequenas e têm tamanho variado, vindo a dificultar a semeadura. A técnica de peletização aumenta e uniformiza a forma das sementes. No entanto, é necessário determinar as características físicas e fisiológicas das sementes peletizadas. Logo, as análises fisiológicas consistiram do teste de germinação, primeira contagem de germinação, índice de velocidade de emergência e emergência final. As análises físicas consistiram do teste de peso de mil sementes, volume de mil sementes e fragmentação. A testemunha foi o tratamento de sementes sem peletização, os demais 36 tratamentos combinaram quatro adesivos: bentonita, acetato de polvinilina (PVA), polivinilpirrolidona (PVP) e metil celulose (Methocel®), e nove produtos de enchimento em pó: microcelulose, gesso, vermiculita, termofosfato magnesiano (Yoorin®), fitina, fosfato bicálcico, fosfato super simples (SS), fosfato monoamônico (MAP) e fosfato natural reativo. Dentre os materiais testados para formar a pelota de semente de milheto nesta pesquisa, os adesivos mais eficientes foram o acetato de polvinilina e a metil celulose. Já os materiais de enchimento em pó mais eficientes foram a vermiculita e a microcelulose.CNP

Consequências fisiológicas da dessecação em sementes de açaí (Euterpe oleracea Mart.).

O presente trabalho foi realizado com o objetivo de verificar os efeitos imediatos da desidratação sobre a qualidade fisiológica de sementes de açaí. Anteriormente à secagem das sementes da cultivar BRS Pará foi determinado o teor de água das mesmas e selecionado o lote daquelas que apresentavam o maior teor de água, que foi de 43,4%. As sementes foram submetidas à secagem, em equipamento com circulação forçada de ar (30±2ºC), até atingirem o teor de água de 37,4%, 30,3% 26,1%, 21,0%, 15,% e 11,9%, constituindo os demais tratamentos. O efeito da secagem sobre a qualidade das sementes foi avaliado por meio das determinações de germinação, tempo médio de germinação, velocidade de emergência, comprimento e massa da matéria seca de plântulas. A secagem até 37,4% de água não produz efeitos fisiológicos prejudiciais imediatos sobre as sementes de açaí, contudo, abaixo de 30,3% há redução progressiva da germinação e do vigor das sementes e ao atingirem 15,1% de teor de água, o desempenho fisiológico é anulado.Título em inglês: Physiological consequences of desiccation in Euterpe oleracea Mart. seeds. Disponível também on-line

Conservação de sementes de açaí (Euterpe oleracea Mart.).

Sementes de Euterpe oleracea são consideradas recalcitrantes e demandam ampliação do conhecimento sobre os fatores que interferem na sua conservação. Diante disso, o presente trabalho foi realizado com o objetivo de verificar os efeitos do teor de água da semente e da temperatura do ambiente na manutenção da qualidade das mesmas. Sementes da cultivar BRS Pará, com diferentes teores de água (43,4; 37,4; 30,3; 26,1; 21,0; 15,1 e 11,9%) e acondicionadas em sacos de polietileno foram armazenadas sob temperaturas de 20, 15 e 10 ºC durante 360 dias e submetidas a avaliações periódicas do teor de água, da germinação e do vigor. A secagem parcial até 37,4% de água não produz efeitos imediatos sobre a germinação e o vigor das sementes, a partir daí a secagem favorece, progressivamente, a deterioração das sementes e, ao atingirem 15,1% as sementes não germinam. Após o armazenamento, sementes com 21,0% de água ou menos não germinam independentemente da temperatura. A associação de 43,4% de água na semente e o armazenamento em ambiente a 20 ºC favorece a conservação das sementes por até 270 dias

Brain Responses to Surprising Stimulus Offsets: Phenomenology and Functional Significance

Abrupt increases of sensory input (onsets) likely reflect the occurrence of novel events or objects in the environment, potentially requiring immediate behavioral responses. Accordingly, onsets elicit a transient and widespread modulation of ongoing electrocortical activity: the Vertex Potential (VP), which is likely related to the optimisation of rapid behavioral responses. In contrast, the functional significance of the brain response elicited by abrupt decreases of sensory input (offsets) is more elusive, and a detailed comparison of onset and offset VPs is lacking. In four experiments conducted on 44 humans, we observed that onset and offset VPs share several phenomenological and functional properties: they (1) have highly similar scalp topographies across time, (2) are both largely comprised of supramodal neural activity, (3) are both highly sensitive to surprise and (4) co-occur with similar modulations of ongoing motor output. These results demonstrate that the onset and offset VPs largely reflect the activity of a common supramodal brain network, likely consequent to the activation of the extralemniscal sensory system which runs in parallel with core sensory pathways. The transient activation of this system has clear implications in optimizing the behavioral responses to surprising environmental changes

Population history from the Neolithic to present on the Mediterranean island of Sardinia: an ancient DNA perspective

Recent ancient DNA studies of western Eurasia have revealed a dynamic history of admixture, with evidence for major migrations during the Neolithic and Bronze Age. The population of the Mediterranean island of Sardinia has been notable in these studies –} Neolithic individuals from mainland Europe cluster more closely with Sardinian individuals than with all other present-day Europeans. The current model to explain this result is that Sardinia received an initial influx of Neolithic ancestry and then remained relatively isolated from expansions in the later Neolithic and Bronze Age that took place in continental Europe. To test this model, we generated genome-wide capture data (approximately 1.2 million variants) for 43 ancient Sardinian individuals spanning the Neolithic through the Bronze Age, including individuals from Sardinia{’}s Nuragic culture, which is known for the construction of numerous large stone towers throughout the island. We analyze these new samples in the context of previously generated genome-wide ancient DNA data from 972 ancient individuals across western Eurasia and whole-genome sequence data from approximately 1,500 modern individuals from Sardinia. The ancient Sardinian individuals show a strong affinity to western Mediterranean Neolithic populations and we infer a high degree of genetic continuity on the island from the Neolithic (around fifth millennium BCE) through the Nuragic period (second millennium BCE). In particular, during the Bronze Age in Sardinia, we do not find significant levels of the {“}Steppe{” ancestry that was spreading in many other parts of Europe at that time. We also characterize subsequent genetic influx between the Nuragic period and the present. We detect novel, modest signals of admixture between 1,000 BCE and present-day, from ancestry sources in the eastern and northern Mediterranean. Within Sardinia, we confirm that populations from the more geographically isolated mountainous provinces have experienced elevated levels of genetic drift and that northern and southwestern regions of the island received more gene flow from outside Sardinia. Overall, our genetic analysis sheds new light on the origin of Neolithic settlement on Sardinia, reinforces models of genetic continuity on the island, and provides enhanced power to detect post-Bronze-Age gene flow. Together, these findings offer a refined demographic model for future medical genetic studies in Sardinia

The geography of recent genetic ancestry across Europe

The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of recent genealogical ancestry over the past three thousand years at a continental scale. We detected 1.9 million shared genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 10-50 genetic common ancestors from the last 1500 years, and upwards of 500 genetic ancestors from the previous 1000 years. These numbers drop off exponentially with geographic distance, but since genetic ancestry is rare, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1000 years. There is substantial regional variation in the number of shared genetic ancestors: especially high numbers of common ancestors between many eastern populations likely date to the Slavic and/or Hunnic expansions, while much lower levels of common ancestry in the Italian and Iberian peninsulas may indicate weaker demographic effects of Germanic expansions into these areas and/or more stably structured populations. Recent shared ancestry in modern Europeans is ubiquitous, and clearly shows the impact of both small-scale migration and large historical events. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.Comment: Full size figures available from http://www.eve.ucdavis.edu/~plralph/research.html; or html version at http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm