Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader-follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis

Prevailing climatic trends and runoff response from Hindukush–Karakoram–Himalaya, upper Indus Basin

Largely depending on the meltwater from the Hindukush–Karakoram–Himalaya, withdrawals from the upper Indus Basin (UIB) contribute half of the surface water availability in Pakistan, indispensable for agricultural production systems, industrial and domestic use, and hydropower generation. Despite such importance, a comprehensive assessment of prevailing state of relevant climatic variables determining the water availability is largely missing. Against this background, this study assesses the trends in maximum, minimum and mean temperatures, diurnal temperature range and precipitation from 18 stations (1250–4500 m a.s.l.) for their overlapping period of record (1995–2012) and, separately, from six stations of their long-term record (1961–2012). For this, a Mann–Kendall test on serially independent time series is applied to detect the existence of a trend, while its true slope is estimated using the Sen's slope method. Further, locally identified climatic trends are statistically assessed for their spatial-scale significance within 10 identified subregions of the UIB, and the spatially (field-) significant climatic trends are then qualitatively compared with the trends in discharge out of corresponding subregions. Over the recent period (1995–2012), we find warming and drying of spring (field-significant in March) and increasing early melt season discharge from most of the subregions, likely due to a rapid snowmelt. In stark contrast, most of the subregions feature a field-significant cooling within the monsoon period (particularly in July and September), which coincides well with the main glacier melt season. Hence, a decreasing or weakly increasing discharge is observed from the corresponding subregions during mid- to late melt season (particularly in July). Such tendencies, being largely consistent with the long-term trends (1961–2012), most likely indicate dominance of the nival but suppression of the glacial melt regime, altering overall hydrology of the UIB in future. These findings, though constrained by sparse and short observations, largely contribute in understanding the UIB melt runoff dynamics and address the hydroclimatic explanation of the Karakoram Anomaly

Mode stabilized terrace InGaAsP lasers on semi-insulating InP

Mode stabilized terrace InGaAsP lasers have been fabricated on semi-insulating InP substrates. The fabrication involves a selective, single-step liquid phase epitaxial growth process, and a lateral Zn diffusion. Two versions of the terrace lasers are fabricated, and threshold currents as low as 35 mA and 50 mA respectively are obtained. The lasers operate with a stable single lateral mode. High power performance is observed. These lasers are suitable for monolithic integration with other optoelectronic devices

Direct measurement of the carrier leakage in an InGaAsP/InP laser

Carrier leakage over the heterobarrier in an InGaAsP/InP laser is measured directly in a laser-bipolar-transistor structure. Experimental results indicate a significant amount of carrier leakage under normal laser operating conditions

Classification of inter-subject fMRI data based on graph kernels

The analysis of human brain connectivity networks has become an increasingly prevalent task in neuroimaging. A few recent studies have shown the possibility of decoding brain states based on brain graph classification. Graph kernels have emerged as a powerful tool for graph comparison that allows the direct use of machine learning classifiers on brain graph collections. They allow classifying graphs with different number of nodes and therefore the inter-subject analysis without any kind of previous alignment of individual subject's data. Using whole-brain fMRI data, in this paper we present a method based on graph kernels that provides above-chance accuracy results for the inter-subject discrimination of two different types of auditory stimuli. We focus our research on determining whether this method is sensitive to the relational information in the data. Indeed, we show that the discriminative information is not only coming from topological features of the graphs like node degree distribution, but also from more complex relational patterns in the neighborhood of each node. Moreover, we investigate the suitability of two different graph representation methods, both based on data-driven parcellation techniques. Finally, we study the influence of noisy connections in our graphs and provide a way to alleviate this problem