You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Interpersonal Synchrony: A Survey of Evaluation Methods across Disciplines 
Chapter Title:  Significance Test: Bootstrap 
1. Abstract of Cited Paper (BIB001):  This study examined the influence of sex, social dominance, and context on motion-tracked head movements during dyadic conversations. Windowed cross-correlation analyses found high peak correlation between conversants' head movements over short (≈2-s) intervals and a high degree of nonstationarity. Nonstationarity in head movements was found to be positively related to the number of men in a conversation. Surrogate data analysis offsetting the conversants' time series by a large lag was unable to reject the null hypothesis that the observed high peak correlations were unrelated to short-term coordination between conversants. One way that high peak correlations could be observed when 2 time series are offset by a large time lag is for each time series to exhibit self-similarity over a range of scales. Multifractal analysis found small-scale fluctuations to be persistent, τ(q) 0.5. These results are consistent with a view that symmetry is formed between conversants over short intervals and that this symmetry is broken at longer, irregular intervals. 
2. Abstract of Cited Paper (BIB002):  Nonverbal synchrony in face-to-face interaction has been studied in numerous empirical investigations focusing on various communication channels. Furthermore, the pervasiveness of synchrony in physics, chemistry and biology adds to its face-validity. This paper is focused on establishing criteria for a statistical evaluation of synchrony in human interaction. When assessing synchrony in any communication context, it is necessary to distinguish genuine synchrony from pseudosynchrony, which may arise due to random coincidence. By using a bootstrap approach, we demonstrate a way to quantify the amount of synchrony that goes beyond random coincidence, thus establishing an objective measure for the phenomenon. Applying this technique to psychotherapy data, we develop a hypothesis-driven empirical evaluation of nonverbal synchrony. The method of surrogate testing in order to control for chance is suitable to any corpus of empirical data and lends itself to better empirically informed inference. 
3. Abstract of Cited Paper (BIB003):  The decisive role of interpersonal coordination in social interactions is well established. As human beings, we are "experts" in decoding and producing social signals, learning since our birth. Though, equipping a machine with the same abilities represents a great challenge to design socially-accepted interfaces. Assessing automatically this coordination requires selecting the most relevant features. In this paper, various audio and visual features are investigated to characterize interactional synchrony in a cooperative task. A hierarchical representation of the similarity between extracted features is proposed. The properties of time-domain (correlation coefficients) and frequency-domain (coherence) synchrony measures are confronted. The presented results support the evidence that synchrony is a multimodal phenomenon. Moreover, it can be assessed both on local (short-length windows of interaction) or global scales (entire interaction). 
4. Abstract of Cited Paper (BIB004):  Mimicry occurs in conversations both when people agree with each other and when they do not. However, it has been reported that there is more mimicry when people agree than when they disagree: when people want to express shared opinions and attitudes, they do so by displaying behavior that is similar to their interlocutors' behavior. In a conversation, mimicry occurs in order to gain acceptance from an interaction partner by conforming to that person's attitudes, opinions, and behavior. In this paper we describe how visual behavioral information expressed between two interlocutors can be used to detect and identify visual mimicry. We extract and encode visual features that are expected to represent mimicry in a useful way. In order to show that mimicry has indeed occurred, we calculate correlations between visual features extracted from the interactants and compare these against each other and against a baseline. We show that it is possible to visualize the occurrence of visual mimicry during the progress of a conversation which allows us to research in which situations and to what extent mimicry occurs.

Literature Review:
A critical question when attempting to detect dependence relationships between features is where the boundary between scores indicating significant and insignificant synchrony should be. Ashenfelter et al. summarize the issue BIB002 : "...it is reasonable to ask whether these coefficients are due to the coordination between people as they act in a mutual perception-action cycle or if these values might be due to the overall context of the conversation." Consequently, a baseline is needed to compare the scores and determine the significance of the measure. Bernieri and Rosenthal originally proposed a rating method ("the pseudosynchrony experimental paradigm") to evaluate the interactional synchrony that occurred in a dyadic interaction  . The method consists of synthesizing surrogate data (pseudointeractions): Video images of dyadic partners are isolated and recombined in a random order. Judges then rate the original and pseudointeractions videos. Pseudointeraction scores constitute a baseline to judge the scores obtained in the original interaction. The idea of generating surrogate data and comparing the synchrony scores on the genuine and surrogate data sets has been extended to automatic computation of interactional synchrony. First, features are extracted for each dyadic partner. The temporal structure of the first partner's time series is destroyed and reassociated with the second partner's original time series. Synchrony scores are assessed using the original and surrogate data sets. The synchrony scores on the surrogate data set constitute a baseline for judging for the dyad's coordination BIB001 , BIB002 , BIB005 . Ramseyer and Tschacher go beyond the comparison with a single surrogate data set BIB003 . They build N (N = 100) surrogate data sets and estimate the distribution of the surrogate synchrony scores. A statistical test is performed to test the hypothesis that the genuine synchrony score stems from the same distribution as the surrogate synchrony scores. Interactional synchrony scores are considered significant if genuine synchrony scores are above two standard deviations of the pseudosynchrony scores (one-sided z-test, p < 0:05). Various methods have been used to generate the surrogate data sets (offsetting one time series of a large time lag BIB002 , time-shuffling n-second-length windows of one time series BIB003 , BIB004 , BIB001 associating mismatched partners who did not interact with one another BIB001 . Ramseyer and Tschacher BIB003 provide for a methodological description of resampling methods for synchrony assessment. These methods are subject to three main criticisms in the context of studying naturalistic interaction data. First, the evaluation and interpretation of these methods are particularly delicate. On the basis of the discriminative or predictive power of the measure, the authors cannot really know if it is real synchrony that is measured or just a co-occurrence of events without meaning, particularly for features as global as Motion Energy. Moreover, the measures provided by these methods are mostly global and do not shed light on what happened locally during the interaction; they do not provide a local model of the communication dynamics. Second, the importance of speech and multimodality is often concealed in these methods. Third, these methods are suitable for analyzing a database but do not provide direct insights on how to equip a machine with such coordination skills.