Rare Constructions Are More Often Sentence‐Initial

Main clause phenomena (MCPs) are syntactic constructions that occur predominantly or exclusively in main clauses. I propose a processing explanation for MCPs. Sentence processing is easiest at the beginning of the sentence (requiring less search); this follows naturally from widely held assumptions about sentence processing. Because of this, a wider variety of constructions can be allowed at the beginning of the sentence without overwhelming the sentence‐processing mechanism. Unlike pragmatic and grammatical accounts of MCPs, the processing account predicts avoidance of MCPs in non‐initial main clauses (non‐initial coordinate clauses and premodified clauses). A corpus study supports these predictions, but it is somewhat inconclusive. A further corpus study examines another type of syntactic construction, premodifying adjunct phrases (“openers”); the prediction here is that less common types of opener will be especially avoided in non‐initial contexts. The prediction is confirmed, supporting the processing view of rare constructions.     

The Faulty Magnitude Detector: Why SNARC‐Like Tasks Cannot Support a Generalized Magnitude System

Do people represent space, time, number, and other conceptual domains using a generalized magnitude system (GMS)? To answer this question, numerous studies have used the spatial‐numerical association of response codes (SNARC) task and its variants. Yet, for a combination of reasons, SNARC‐like effects cannot provide evidence for a GMS, even in principle. Rather, these effects support a broader theory of how people use space metaphorically to scaffold their understanding of myriad non‐spatial domains, whether or not these domains exhibit variation in magnitude.     

“Seeing Rain”: Integrating phenomenological and Bayesian predictive coding approaches to visual hallucinations and self-disturbances (Ichstörungen) in schizophrenia

We present a schizophrenia patient who reports “seeing rain” with attendant somatosensory features which separate him from his surroundings. Because visual/multimodal hallucinations are understudied in schizophrenia, we examine a case history to determine the role of these hallucinations in self-disturbances (Ichstörungen). Developed by the early Heidelberg School, self-disturbances comprise two components: 1. The self experiences its own automatic processing as alien to self in a split-off, “doubled-I.” 2. In “I-paralysis,” the disruption to automatic processing is now outside the self in omnipotent agents. Self-disturbances (as indicated by visual/multimodal hallucinations) involve impairment in the ability to predict moment-to-moment experiences in the ongoing perception-action cycle. The phenomenological approach to subjective experience of self-disturbances complements efforts to model psychosis using the computational framework of hierarchical predictive coding. We conclude that self-disturbances play an adaptive, compensatory role following the uncoupling of perception and action, and possibly, other low-level perceptual anomalies.     

音乐训练促进诗句韵律整合加工的神经过程

本研究采用ERP技术,考察音乐训练组和对照组完成诗句押韵判断任务时,在绝句末对韵律信息(含声调和韵母两个维度)的整合加工过程。结果发现,在100～300 ms,仅音乐训练组在声调/韵母合适条件下,对韵母/声调的一致性进行深入分析,并诱发了更大的正波;在韵母违反条件下,声调违反相比声调合适诱发了更小的正波。在300～750ms,两组被试均在绝句末对诗句内出现的韵母和声调违反进行整合分析并诱发了广泛分布的负波。不过,对照组仅在声调/韵母合适条件下进行,而音乐训练组则在声调/韵母违反条件下完成此过程。综上,音乐训练组和对照组均会在诗句末完成押韵信息的整合加工,但是音乐训练组对韵律信息(尤其是声调)的加工更敏感和快速,并且对不同类型的违反有更精细的差异性反应     

数据权属与规制探讨

数据可分为原生数据与衍生数据。原生数据视来源不同分属国家、集体或个人。数据处理而形成的衍生数据往往涉及多方利益,形成“利益光谱”,对应多方权利主体。基于价值优先次序、权利位阶规则等,数据利益的“两头强化,多方平衡”,是我国法律数据确权和规制的指导思想。“两头强化”是指法律强化对位于“利益光谱”两端的国家利益与个人权益的保护,“多方平衡”指的是多方主体数据权益的平衡。数据规制的“硬法”进路为：明确法律概念,分析“利益光谱”,确定利益归属,权衡优先次序,平衡多方利益,搭建规制框架,制定具体规则。

     

Measuring information demand of a dynamic in-vehicle display while driving – A study evaluating the MARS (Masking Action Relevant Stimuli) method

The MARS (Masking Action Relevant Stimuli) method assesses information demand for dynamic stimuli while driving. An action relevant stimulus is masked and the driver presses a button to unmask the stimulus for a limited period. We interpreted button presses as information demand. Following our previous research (Rittger, Kiesel, Schmidt, & Maag, 2014), the current study further evaluates the method. We applied the MARS method to a dynamic in-vehicle display containing recommendations from a traffic light assistant. In a driving simulator, drivers approached intersections with different traffic light phasing. The display either presented simple or complex information. In half of the drives, the participants used the MARS method. The study had a full within subjects design and fixations were recorded in all conditions. The results showed that the information demand varied according to the information in the display and the traffic light phase. A comparison of button presses with fixations showed that one unmasking interval came along with one fixation on the display. As a conclusion, the MARS method can distinguish between conditions with high and low information demand for the display. Button presses relate to fixations on the display. Hence, the MARS method is a promising tool to assess the information demand in dynamic environments and can be applied as an extension or alternative for eye tracking.