Fine-grained Temporal Resolution Research Articles

Complexity organization of resting-state functional-MRI networks.

Entropy measures are increasingly being used to analyze the structure of neural activity observed by functional magnetic resonance imaging (fMRI), with resting-state networks (RSNs) being of interest for their reproducible descriptions of the brain's functional architecture. Temporal correlations have shown a dichotomy among these networks: those that engage with the environment, known as extrinsic, which include the visual and sensorimotor networks; and those associated with executive control and self-referencing, known as intrinsic, which include the default mode network and the frontoparietal control network. While these inter-voxel temporal correlations enable the assessment of synchrony among the components of individual networks, entropic measures introduce an intra-voxel assessment that quantifies signal features encoded within each blood oxygen level-dependent (BOLD) time series. As a result, this framework offers insights into comprehending the representation and processing of information within fMRI signals. Multiscale entropy (MSE) has been proposed as a useful measure for characterizing the entropy of neural activity across different temporal scales. This measure of temporal entropy in BOLD data is dependent on the length of the time series; thus, high-quality data with fine-grained temporal resolution and a sufficient number of time frames is needed to improve entropy precision. We apply MSE to the Midnight Scan Club, a highly sampled and well-characterized publicly available dataset, to analyze the entropy distribution of RSNs and evaluate its ability to distinguish between different functional networks. Entropy profiles are compared across temporal scales and RSNs. Our results have shown that the spatial distribution of entropy at infra-slow frequencies (0.005-0.1 Hz) reproduces known parcellations of RSNs. We found a complexity hierarchy between intrinsic and extrinsic RSNs, with intrinsic networks robustly exhibiting higher entropy than extrinsic networks. Finally, we found new evidence that the topography of entropy in the posterior cerebellum exhibits high levels of entropy comparable to that of intrinsic RSNs.

Moving visual world experiments online? A web-based replication of Dijkgraaf, Hartsuiker, and Duyck (2017) using PCIbex and WebGazer.js.

The visual world paradigm is one of the most influential paradigms to study real-time language processing. The present study tested whether visual world studies can be moved online, using PCIbex software (Zehr & Schwarz, 2018) and the WebGazer.js algorithm (Papoutsaki et al., 2016) to collect eye-movement data. Experiment 1 was a fixation task in which the participants looked at a fixation cross in multiple positions on the computer screen. Experiment 2 was a web-based replication of a visual world experiment by Dijkgraaf et al. (2017). Firstly, both experiments revealed that the spatial accuracy of the data allowed us to distinguish looks across the four quadrants of the computer screen. This suggest that the spatial resolution of WebGazer.js is fine-grained enough for most visual world experiments (which typically involve a two-by-two quadrant-based set-up of the visual display). Secondly, both experiments revealed a delay of roughly 300 ms in the time course of the eye movements, possibly caused by the internal processing speed of the browser or WebGazer.js. This delay can be problematic in studying questions that require a fine-grained temporal resolution and requires further investigation.

Foreign-accented sentence comprehension is challenging for older adults: ERP evidence from semantic and grammar processing

Research has shown that older adults have increased difficulty comprehending foreign-accented speech. As these studies have only used behavioral measures, we exploited the fine-grained temporal resolution of EEG/ERPs to examine neural signatures of foreign- and native-accented sentence comprehension in older adults. Older adults, all normal-hearing monolingual English speakers, listened to foreign Chinese-accented and native English-accented sentences while ERPs were recorded. Foreign- and native-accented sentences contained semantic or pronoun errors, or were semantically and grammatically correct. We also gathered behavioral measures of sentence comprehension, and examined how neural activity during sentence processing relates to individual differences in listeners’ attitudes towards accented speakers, linguistic and cognitive skills, and hearing acuity. Older adults showed high comprehension accuracy of both foreign-accented and native-accented sentences. In contrast, ERP data showed different neural responses to foreign- and native-accented sentences: Semantic errors elicited an N400 effect in native-accented sentences, but not in foreign-accented sentences. Grammatical errors elicited a P600, not further qualified by accent type. Hearing acuity and individual differences in language attitudes, cognitive and linguistic variables did not systematically correlate with ERP patterns. These findings suggest that older adults are ultimately engaging in foreign-accented sentence comprehension, but non-native pre-lexical speech signals do not attain activation needed for strong lexical activation during online processing, resulting in strained and more effortful higher-level processing of semantics downstream the sentence.

Alpha and broadband high-frequency activity track task dynamics and predict performance in controlled decision-making.

Intracranial recordings in human subjects provide a unique, fine-grained temporal and spatial resolution inaccessible to conventional non-invasive methods. A prominent signal in these recordings is broadband high-frequency activity (approx. 70-150Hz), generally considered to reflect neuronal excitation. Here we explored the use of this broadband signal to track, on a single-trial basis, the temporal and spatial distribution of task-engaged areas involved in decision-making. We additionally focused on the alpha rhythm (8-14Hz), thought to regulate the (dis)engagement of neuronal populations based on task demands. Using these signals, we characterized activity across cortex using intracranial recordings in patients with intractable epilepsy performing the Multi-Source Interference Task, a Stroop-like decision-making paradigm. We analyzed recordings both from grid electrodes placed over cortical areas including frontotemporal and parietal cortex, and depth electrodes in prefrontal regions, including cingulate cortex. We found a widespread negative relationship between alpha power and broadband activity, substantiating the gating role of alpha in regions beyond sensory/motor cortex. Combined, these signals reflect the spatio-temporal pattern of task-engagement, with alpha decrease signifying task-involved regions and broadband increase temporally locking to specific task aspects, distributed over cortical sites. We report sites that only respond to stimulus presentation or to the decision report and, interestingly, sites that reflect the time-on-task. The latter predict the subject's reaction times on a trial-by-trial basis. A smaller subset of sites showed modulation with task condition. Taken together, alpha and broadband signals allow tracking of neuronal population dynamics across cortex on a fine temporal and spatial scale.

Dynamic inter-brain synchrony in real-life inter-personal cooperation: A functional near-infrared spectroscopy hyperscanning study

How two brains communicate with each other during social interaction is highly dynamic and complex. Multi-person (i.e., hyperscanning) studies to date have focused on analyzing the entire time series of brain signals to reveal an overall pattern of inter-brain synchrony (IBS). However, this approach does not account for the dynamic nature of social interaction. In the present study, we propose a data-driven approach based on sliding windows and k-mean clustering to capture the dynamic modulation of IBS patterns during interactive cooperation tasks. We used a portable functional near-infrared spectroscopy (fNIRS) system to measure brain hemodynamic response between interacting partners (20 dyads) engaged in a creative design task and a 3D model building task. Results indicated that inter-personal communication during naturalistic cooperation generally presented with a series of dynamic IBS states along the tasks. Compared to the model building task, the creative design task appeared to involve more complex and active IBS between multiple regions in specific dynamic IBS states. In summary, the proposed approach stands as a promising tool to distill complex inter-brain dynamics associated with social interaction into a set of representative brain states with more fine-grained temporal resolution. This approach holds promise for advancing our current understanding of the dynamic nature of neurocognitive processes underlying social interaction.

Distinguishing between rumination and intrusive memories in PTSD using a wearable self-tracking instrument: a proof-of-concept case study

Abstract Rumination has been shown to play a part in post-traumatic stress disorder (PTSD), but its relation to the intrusions characteristic of PTSD has mainly been investigated experimentally. This proof-of-concept case study explored the occurrence, personal experiences, and possible relation between rumination and intrusions in two PTSD patients in their daily living using a mixed method approach. A novel wearable self-tracking instrument was employed which provided fine-grained temporal resolution of observation data and could eliminate recall bias. Furthermore, quantitative and qualitative data were collected on participants’ symptoms, rumination and experiences of using the self-tracking instrument. First, without distinguishing between the two phenomena, the participants tracked both for a week. After receiving psychoeducational training for distinguishing between rumination and intrusions, the differentiated phenomena were tracked for a week. Both participants reported being subjectively able to distinguish between rumination and intrusions and made observations with high adherence during the project. Data hinted at a possible temporal relation between the phenomena in line with theories posing rumination as a maladaptive coping strategy as well as an exacerbator of PTSD symptoms. However, relations to mood were inconclusive. Furthermore, by using the self-tracking instrument, participants gained a heightened awareness of the characteristics of rumination and intrusions and contextual cues for occurrence, as well as a greater sense of momentary agency. Results reveal promising prospects in using the wearable self-tracking instrument for further investigation of the relation between rumination and intrusions in the lived lives of PTSD patients, as well as potential for incorporating this method in clinical treatment. Key learning aims (1) Self-tracking with the One Button Tracker is a novel symptom registration method, particularly suited for use in psychotherapeutic treatment and research. (2) Rumination and intrusions appear to the participants as distinct cognitive phenomena and treatment targets in PTSD. (3) Registering rumination and intrusions in real-time could reveal important temporal relations between them and the contexts in which they occur. (4) The data obtained with this self-tracking method can potentially be used as a tool in, and for the further development of psychotherapy for PTSD.

ViCrypt to the Rescue: Real-Time, Machine-Learning-Driven Video-QoE Monitoring for Encrypted Streaming Traffic

Video streaming is the killer application of the Internet today. In this article, we address the problem of real-time, passive Quality-of-Experience (QoE) monitoring of HTTP Adaptive Video Streaming (HAS), from the Internet-Service-Provider (ISP) perspective - i.e., relying exclusively on in-network traffic measurements. Given the wide adoption of end-to-end encryption, we resort to machine-learning (ML) models to estimate multiple key video-QoE indicators (KQIs) from the analysis of the encrypted traffic. We present ViCrypt, an ML-driven monitoring solution able to infer the most important KQIs for HTTP Adaptive Streaming (HAS), namely stalling, initial delay, video resolution, and average video bitrate. ViCrypt performs estimations in real-time, during the playback of an ongoing video-streaming session, with a fine-grained temporal resolution of just one second. For this, it relies on lightweight, stream-like features continuously extracted from the encrypted stream of packets. Empirical evaluations on a large and heterogeneous corpus of YouTube measurements show that ViCrypt can infer the targeted KQIs with high accuracy, enabling large-scale passive video-QoE monitoring and proactive QoE-aware traffic management. Different from the state of the art, and besides real-time operation, ViCrypt is not bound to coarse-grained KQI-classes, providing better and sharper insights than other solutions. Finally, ViCrypt does not require chunk-detection approaches for feature extraction, significantly reducing the complexity of the monitoring approach, and potentially improving on generalization to different HAS protocols used by other video-streaming services such as Netflix and Amazon.

Factors contributing to stability and instability in alpha-amylase activity in diluted saliva samples over time

For the measurement of salivary alpha-amylase (sAA) activity, saliva samples first have to be diluted. There is some evidence for instability, that is, a decline of sAA activity in diluted samples. It is not clear which factors during dilution may contribute to this phenomenon and how quickly this decline of sAA activity occurs.Several experiments were conducted to investigate whether and how the material of the container (polystyrene (PS), polypropylene (PP), glass; experiment 1) and the diluent (saline (NaCl) solution, phosphate buffer saline (PBS), ultra-pure water; experiment 2) may affect sAA stability in diluted samples over a broad time window of up to 5 h. To study the velocity of the phenomenon in a fine-grained temporal resolution, sAA activity during the dilution process was studied (experiment 3).The results suggest that the (in)stability of sAA activity in diluted samples is determined by the interaction of material, diluent, and time. The sAA activity was relatively stable if saliva samples were diluted with a NaCl solution or PBS in glass tubes. However, sAA activity in diluted samples decreased in plastic containers (PS, PP), or if ultra-pure water was used as the diluent. There was a clear time effect on this decline. However, the decline appears to require some time to evolve and may not occur immediately during the dilution process. To conclude, the dilution of saliva samples should preferably be conducted with NaCl solution or PBS in glass containers. If glass containers are not available, PS and PP containers can be used if the dilution is processed quickly (within 25 min) and the measurement is initiated immediately upon dilution.

Childhood mobility revealed by strontium isotope analysis: a review of the multiple tooth sampling approach

Strontium isotope analysis of archeological skeletal materials is a highly effective and commonly employed analytical tool to investigate past human mobility and migration. Most such studies to date have focused on the analysis of a single tooth sample per individual to identify migration. Increasingly, however, studies have analyzed multiple teeth from the same individual permitting the detection of migrations occurring during childhood, more fine-grained temporal resolution of the age at which migration(s) occurred, and even the identification of multiple migration episodes. In this study, we review the application of such approaches to a wide range of archeological contexts worldwide. We compiled and analyzed published 87Sr/86Sr data for 1043 individuals from 122 sites to explore the potential variability of childhood mobility patterns cross-culturally. The results demonstrate a high degree of variability in childhood mobility that differs significantly between different regions and time periods. Potential interpretations involved in multiple tooth 87Sr/86Sr analysis are reviewed, including heterogeneity in variance of regional 87Sr/86Sr, as well as variability in human mobility patterns such as residential change of whole family, fosterage, herding activities, post-marital residence rules, or forced migrations. Various limitations and caveats concerning the multiple teeth sampling approach are also critically discussed.

Large-Scale, Fine-Grained, Spatial, and Temporal Analysis, and Prediction of Mobile Phone Users' Distributions Based upon a Convolution Long Short-Term Model.

Accurate and timely estimations of large-scale population distributions are a valuable input for social geography and economic research and for policy-making. The most popular large-scale method to calculate such estimations uses mobile phone data. We propose a novel method, firstly based upon using a kernel density estimation (KDE) to estimate dynamic mobile phone users’ distributions at a two-hourly scale temporal resolution. Secondly, a convolutional long short-term memory (ConvLSTM) model was used in our study to predict mobile phone users’ spatial and temporal distributions for the first time at such a fine-grained temporal resolution. The evaluation results show that the predicted people’s mobility derived from the mobile phone users’ density correlates much better with the actual density, both temporally and spatially, as compared to traditional methods such as time-series prediction, autoregressive moving average model (ARMA), and LSTM.

The fog regime in a tropical montane cloud forest in Brazil and its effects on water, light and microclimate

Fog is a frequent phenomenon in tropical montane cloud forests (TMCFs). These ecosystems are important to the water supply of adjacent lowland regions which is largely determined by the effect of fog on TCMF evapotranspiration rates and hydrological balance. Understanding fog regimes at fine-grained temporal resolution is key to predict plant functioning and effects of climatic changes in TMCFs, especially on key hydrological services that these forests provide. Here, we combine a suite of micrometeorological and hydrological sensors with a visibilimeter, a reliable sensor of fog occurrence, to gather fine-grained information on fog frequency, duration and timing and its contribution to water inputs, light availability and microclimatic variability in a Brazilian TMCF. Despite occurring on 64% of days, fog was highly variable at daily and seasonal scales, occurring mostly at night and during the rainy season. Approximately 1200 liters of fog were intercepted per tree per year (259 mm or 10.7% of total net precipitation). Fog also increased net precipitation provided by concomitant fog-rain events. Monthly net precipitation to precipitation ratio, a measure of how much water arrives at the soil and how much evaporates or is intercepted by the canopy, was 0.96 - much higher than the 0.72 typical of lowland rainforest, due to the additional fog water input on TMCF. Cloudiness, and not fog, dominated light availability and inter-day microclimatic variability (air temperature and vapor pressure deficit). High fog regime variability indicates that understanding TMCFs functioning requires integration of plant function with fine-grained data of fog and cloud occurrence. We discuss possible consequences of our results to TMCFs plant functioning.

Effects on P3 of spreading targets and response prompts apart

When key-press responses to targets have to be withheld until the presentation of response prompts, target-evoked P3 amplitudes are reduced and so is the P3 difference between rare and frequent targets (the oddball effect on P3). Recently we showed that this even applied when go-signals followed targets by 100ms. Here we aimed at replicating this result with more fine-grained temporal resolution in 100ms steps from 0ms to 500ms, and dissecting the P3 complex to stimulus- and response-related portions by applying residue iteration decomposition (RIDE). Frequent and rare target stimuli (in random series) were followed by go signals (and occasional no-go signals), with block-wise fixed stimulus-onset asynchronies (SOAs) from 0ms to 500ms. Target-evoked P3 amplitudes decreased monotonically across SOAs. Part of this decrease might have been due to an overlapping Contingent Negative Variation (CNV) prior to go signals, increasing across SOAs. When CNV was subtracted out by forming rare-frequent difference waveforms, oddball-P3 was largest at SOA 0, smallest at SOA 500, and equally large at SOAs 100–400. According to RIDE, it was P3's response-related part that was increased at SOA0. These results may be interpreted in terms of the stimulus-response-link reactivation hypothesis of P3.

Ventromedial prefrontal cortex drives hippocampal theta oscillations induced by mismatch computations

Detecting environmental change is fundamental for adaptive behavior in an uncertain world. Previous work indicates the hippocampus supports the generation of novelty signals via implementation of a match–mismatch detector that signals when an incoming sensory input violates expectations based on past experience. While existing work has emphasized the particular contribution of the hippocampus, here we ask which other brain structures also contribute to match–mismatch detection. Furthermore, we leverage the fine-grained temporal resolution of magnetoencephalography (MEG) to investigate whether mismatch computations are spectrally confined to the theta range, based on the prominence of this range of oscillations in models of hippocampal function. By recording MEG activity while human subjects perform a task that incorporates conditions of match–mismatch novelty we show that mismatch signals are confined to the theta band and are expressed in both the hippocampus and ventromedial prefrontal cortex (vmPFC). Effective connectivity analyses (dynamic causal modeling) show that the hippocampus and vmPFC work as a functional circuit during mismatch detection. Surprisingly, our results suggest that the vmPFC drives the hippocampus during the generation and processing of mismatch signals. Our findings provide new evidence that the hippocampal–vmPFC circuit is engaged during novelty processing, which has implications for emerging theories regarding the role of vmPFC in memory.

Attentional guidance by the contents of working memory and the N2PC component

Abstract The Biased Competition Model suggests that stimuli matching the contents of working memory increase the likelihood that memory-matching items will be attended. According to this account, the representations in working memory create an involuntary capture of attention toward memory-matching items in the visual field. This influential assumption proposed by the biased competition model has been explored in a number of studies, showing that the contents of working memory exert an automatic bias in favor of memory matching items. These studies showed that active maintenance of objects in working memory automatically shift attention toward the memory matching-object and produce a negative early lateralized event related potential (ERP), the N2pc, toward the side of visual field where the memorized item appeared. This component, the N2pc is an important tool to investigate the allocation of attention by working memory representations, especially for the activity the activity that is specific to the hemisphere which is contralateral with respect to the hemifield containing e.g. the to-be-remembered items could be measured. This characteristic of the N2pc facilitates measuring the general direction of attention with fine-grained temporal resolution. Therefore, the N2pc could be used as an index to describe the lateralization effect of memorized items on attention related studies.

COMT Val158Met genotype is associated with fluctuations in working memory performance: converging evidence from behavioural and single-trial P3b measures

Intra-subject variability in reaction times (ISV) is a promising endophenotype for several psychiatric conditions, but its neural underpinnings are not yet established. Converging evidence from neuroimaging, molecular genetics, and psychopharmacology suggests that ISV could index catecholaminergically-mediated neural noise. The fine-grained temporal resolution of electroencephalography is ideal for investigating ISV, but only if potential neural correlates of ISV can be assessed in single trials. Based on evidence that ISV is associated with dopaminergic functioning, we apply a recently developed method of single-trial P3b analysis to investigate the association of COMT Val158Met genotype with measures of ISV on the behavioural and neural levels at different working memory loads. Greater number of Met alleles was associated with poorer and more intra-individually variable performance on the tasks, and greater latency jitter in single-trial P3bs. These converging results at the behavioural and neurophysiological levels confirm previous observations that prefrontal dopamine availability is associated with stability and accuracy of cognitive performance. Together with previous studies, these data imply pleiotropic cognitive effects of COMT genotype.

Influences of structure and agency on the perception of musical change.

In previous work, we and others have shown that continuous perceptions of change in an ongoing piece of music can be significant predictors of nonmusicians' continuous perception of the affect expressed by the piece (Bailes & Dean, 2012; Dean & Bailes, 2010), as can other continuous features such as acoustic intensity (Dean, Bailes, & Schubert, 2011; Schubert, 1999, 2004). Yet some evidence has suggested that such nonmusicians are fairly indifferent to large structural features. For example, the global liking of classical music and its perceived expression are little perturbed when sections are shuffled (Eitan & Granot, 2008), when tonal music is presented without tonal closure (Cook, 1987) or after conversion into atonal music of otherwise similar structure (Lalitte, Bigand, Kantor-Martynuska, & Delbe, 2009). This might indicate that musical sections are not explicitly perceived. On the other hand, evidence concerning Roger Reynolds' Angel of Death (for instruments and computer sound) suggests that sectionalisation was indeed perceived in this work (McAdams, Vines, Vieillard, Smith, & Reynolds, 2004). This large-scale concert experiment involved a minority of nonmusicians, but participants could often recognize recurrences of musical material. In this experiment, the task demand to focus continuously on familiarity or resemblance within the piece related explicitly to large-scale structure.The ambiguities in the results just summarized led us to seek to establish whether large-scale musical structures and features of agency (such as solo vs. orchestral sections in a concerto) are reflected in nonmusicians' continuous perceptions of change in music, and to minimize the demand characteristics of the experimental task. Given the disparities about perceptions of large-scale structure under explicit (demand-driven) test conditions, we hypothesized that an impact of large-scale musical structure on continuous perception of local musical change could be detected, and this would provide an implicit measure, without an explicit demand-driven focus on perceiving large-scale structure. Specifically, we hypothesized that large-scale musical segments would predict perceptual response regime-shifts, points which separate segments of different characteristics within the overall response time series. We second hypothesized that such relationships between large-scale musical structure and continuous perception of change would hold within non-Western music, unfamiliar to our nonmusician listeners, as well as in potentially more familiar music. So we investigated this issue with respect to a diverse range of acoustic and electroacoustic pieces from several cultures and periods.Our analysis of continuous perceptual ratings detects statistical in the response time series. This common terminology is slightly misleading: such analyses do not simply detect special features at a particular point, but rather, differences between the overall characteristics of successive segments of the temporal data series. Two of the pieces studied comprise only a single musical segment: if musical segments were the only influence, then no perceptual changepoints would be found in these. However, previous work also shows that surface features, such as short-term changes in acoustic intensity, strongly influence perceived change (Dean & Bailes, 2010); hence, we expect that segments will be perceived in these structurally uniform pieces, and that there will be perceptual segments in the structurally varied works besides those reflecting the musicological structure. The key test of our primary hypothesis is therefore whether the musicological segments coincide with perception changepoints, accepting that additional changepoints may be expected.One might theorise that inexperienced listeners would lack the ability to group and hierarchically organize the low-level features of the music as it flows: they might not be able to transform perceptions at a fine-grained temporal resolution (continuous change) into those in a larger time frame (musical structure). …