scholarly journals In Search of Consciousness: Examining the Temporal Dynamics of Conscious Visual Perception using MEG time-series data

2019 ◽  
Author(s):  
Anh-Thu Mai ◽  
Tijl Grootswagers ◽  
Thomas A. Carlson
Keyword(s):  
Visual Information ◽  
Visual Masking ◽  
Time Series Data ◽  
Temporal Dynamics ◽  
Self Report ◽  
Series Data ◽  
Backward Masking ◽  
Stimulus Information ◽  
Visual Consciousness ◽  
The Brain

AbstractThe mere presence of information in the brain does not always mean that this information is available to consciousness (de-Wit, Alexander, Ekroll, & Wagemans, 2016). Experiments using paradigms such as binocular rivalry, visual masking, and the attentional blink have shown that visual information can be processed and represented by the visual system without reaching consciousness. Using multivariate pattern analysis (MVPA) and magneto-encephalography (MEG), we investigated the temporal dynamics of information processing for unconscious and conscious stimuli. We decoded stimulus information from the brain recordings while manipulating visual consciousness by presenting stimuli at threshold contrast in a backward masking paradigm. Participants’ consciousness was measured using both a forced-choice categorisation task and self-report. We show that brain activity during both conscious and non-conscious trials contained stimulus information, and that this information was enhanced in conscious trials. Overall, our results indicate that visual consciousness is characterised by enhanced neural activity representing the visual stimulus, and that this effect arises as early as 180 ms post-stimulus onset.

scholarly journals The Neurophysiology of Backward Visual Masking: Information Analysis

1999 ◽  
Vol 11 (3) ◽  
pp. 300-311 ◽  
Author(s):  
Edmund T. Rolls ◽  
Martin J. Tovée ◽  
Stefano Panzeri
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Computational Models ◽  
Direct Evidence ◽  
Visual Masking ◽  
Neuronal Response ◽  
Short Soas ◽  
Stimulus Onset ◽  
Backward Masking ◽  
Neuronal Responses

Backward masking can potentially provide evidence of the time needed for visual processing, a fundamental constraint that must be incorporated into computational models of vision. Although backward masking has been extensively used psychophysically, there is little direct evidence for the effects of visual masking on neuronal responses. To investigate the effects of a backward masking paradigm on the responses of neurons in the temporal visual cortex, we have shown that the response of the neurons is interrupted by the mask. Under conditions when humans can just identify the stimulus, with stimulus onset asynchronies (SOA) of 20 msec, neurons in macaques respond to their best stimulus for approximately 30 msec. We now quantify the information that is available from the responses of single neurons under backward masking conditions when two to six faces were shown. We show that the information available is greatly decreased as the mask is brought closer to the stimulus. The decrease is more marked than the decrease in firing rate because it is the selective part of the firing that is especially attenuated by the mask, not the spontaneous firing, and also because the neuronal response is more variable at short SOAs. However, even at the shortest SOA of 20 msec, the information available is on average 0.1 bits. This compares to 0.3 bits with only the 16-msec target stimulus shown and a typical value for such neurons of 0.4 to 0.5 bits with a 500-msec stimulus. The results thus show that considerable information is available from neuronal responses even under backward masking conditions that allow the neurons to have their main response in 30 msec. This provides evidence for how rapid the processing of visual information is in a cortical area and provides a fundamental constraint for understanding how cortical information processing operates.

scholarly journals Temporal dynamics of stomatal conductance of plants under water deficit: can homeostasis be improved by more complex dynamics?

2004 ◽  
Vol 47 (3) ◽  
pp. 423-431 ◽  
Author(s):  
Gustavo Maia Souza ◽  
Ricardo Ferraz de Oliveira ◽  
Victor José Mendes Cardoso
Keyword(s):  
Stomatal Conductance ◽  
Sugar Beet ◽  
Water Deficit ◽  
Time Series Data ◽  
Temporal Dynamics ◽  
Complex Dynamics ◽  
Fractal Dimensions ◽  
Series Data ◽  
Complex Behaviour ◽  
Lz Complexity

In this study we hypothesized that chaotic or complex behavior of stomatal conductance could improve plant homeostasis after water deficit. Stomatal conductance of sunflower and sugar beet leaves was measured in plants grown either daily irrigation or under water deficit using an infrared gas analyzer. All measurements were performed under controlled environmental conditions. In order to measure a consistent time series, data were scored with time intervals of 20s during 6h. Lyapunov exponents, fractal dimensions, KS entropy and relative LZ complexity were calculated. Stomatal conductance in both irrigated and non-irrigated plants was chaotic-like. Plants under water deficit showed a trend to a more complex behaviour, mainly in sunflower that showed better homeostasis than in sugar beet. Some biological implications are discussed.

scholarly journals Uncovering the environmental drivers of short-term temporal dynamics in an epibenthic community from the Western English Channel

2019 ◽  
Vol 99 (7) ◽  
pp. 1467-1479
Author(s):  
Elizabeth Talbot ◽  
Jorn Bruggeman ◽  
Chris Hauton ◽  
Stephen Widdicombe
Keyword(s):  
Time Series Data ◽  
Temporal Dynamics ◽  
Anthropogenic Impacts ◽  
Benthic Communities ◽  
Food Limitation ◽  
Environmental Drivers ◽  
Sediment Surface ◽  
Series Data ◽  
English Channel ◽  
Larval Recruitment

AbstractBenthic communities, critical to the health and function of marine ecosystems, are under increasing pressure from anthropogenic impacts such as pollution, eutrophication and climate change. In order to refine predictions of likely future changes in benthic communities resulting from these impacts, we must first better constrain their responses to natural seasonality in environmental conditions. Epibenthic time series data (July 2008–May 2014) have been collected from Station L4, situated 7.25 nautical miles south of Plymouth in the Western English Channel. These data were analysed to establish patterns in community abundance, wet biomass and composition, and to link any observed patterns to environmental variables. A clear response to the input of organic material from phytoplankton blooms was detected, with sediment surface living deposit feeders showing an immediate increase in abundance, while predators and scavengers responded later, with an increase in biomass. We suggest that this response is a result of two factors. The low organic content of the L4 sediment results in food limitation of the community, and the mild winter/early spring bottom water temperatures allow the benthos to take immediate advantage of bloom sedimentation. An inter-annual change in community composition was also detected, as the community shifted from one dominated by the anomuran Anapagurus laevis to one dominated by the gastropod Turitella communis. This appeared to be related to a period of high larval recruitment for T. communis in 2013/2014, suggesting that changes in the recruitment success of one species can affect the structure of an entire community.

scholarly journals Assessing the Use of Sentinel-2 Time Series Data for Monitoring Cork Oak Decline in Portugal

2019 ◽  
Vol 11 (21) ◽  
pp. 2515 ◽  
Author(s):  
Ana Navarro ◽  
Joao Catalao ◽  
Joao Calvao
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Series Data ◽  
Temporal Dynamics ◽  
Cork Oak ◽  
Series Data ◽  
Tree Level ◽  
Oak Decline ◽  
Sentinel 2

In Portugal, cork oak (Quercus suber L.) stands cover 737 Mha, being the most predominant species of the montado agroforestry system, contributing to the economic, social and environmental development of the country. Cork oak decline is a known problem since the late years of the 19th century that has recently worsened. The causes of oak decline seem to be a result of slow and cumulative processes, although the role of each environmental factor is not yet established. The availability of Sentinel-2 high spatial and temporal resolution dense time series enables monitoring of gradual processes. These processes can be monitored using spectral vegetation indices (VI) as their temporal dynamics are expected to be related with green biomass and photosynthetic efficiency. The Normalized Difference Vegetation Index (NDVI) is sensitive to structural canopy changes, however it tends to saturate at moderate-to-dense canopies. Modified VI have been proposed to incorporate the reflectance in the red-edge spectral region, which is highly sensitive to chlorophyll content while largely unaffected by structural properties. In this research, in situ data on the location and vitality status of cork oak trees are used to assess the correlation between chlorophyll indices (CI) and NDVI time series trends and cork oak vitality at the tree level. Preliminary results seem to be promising since differences between healthy and unhealthy (diseased/dead) trees were observed.

scholarly journals GABAA Agonist Reduces Visual Awareness: A Masking–EEG Experiment

2012 ◽  
Vol 24 (4) ◽  
pp. 965-974 ◽  
Author(s):  
Anouk M. van Loon ◽  
H. Steven Scholte ◽  
Simon van Gaal ◽  
Björn J. J. van der Hoort ◽  
Victor A. F. Lamme
Keyword(s):  
Receptor Antagonist ◽  
Detection Rate ◽  
Visual Masking ◽  
Visual Awareness ◽  
Pharmacological Intervention ◽  
Common Mechanism ◽  
Backward Masking ◽  
Neural Event ◽  
Visual Consciousness ◽  
Human Participants

Consciousness can be manipulated in many ways. Here, we seek to understand whether two such ways, visual masking and pharmacological intervention, share a common pathway in manipulating visual consciousness. We recorded EEG from human participants who performed a backward-masking task in which they had to detect a masked figure form its background (masking strength was varied across trials). In a within-subject design, participants received dextromethorphan (a N-methyl-d-aspartate receptor antagonist), lorazepam (LZP; a GABAA receptor agonist), scopolamine (a muscarine receptor antagonist), or placebo. The behavioral results show that detection rate decreased with increasing masking strength and that of all the drugs, only LZP induced a further decrease in detection rate. Figure-related ERP signals showed three neural events of interest: (1) an early posterior occipital and temporal generator (94–121 msec) that was not influenced by any pharmacological manipulation nor by masking, (2) a later bilateral perioccipital generator (156–211 msec) that was reduced by masking as well as LZP (but not by any other drugs), and (3) a late bilateral occipital temporal generator (293–387 msec) that was mainly affected by masking. Crucially, only the intermediate neural event correlated with detection performance. In combination with previous findings, these results suggest that LZP and masking both reduce visual awareness by means of modulating late activity in the visual cortex but leave early activation intact. These findings provide the first evidence for a common mechanism for these two distinct ways of manipulating consciousness.

scholarly journals A better way to define and describe Morlet wavelets for time-frequency analysis

2018 ◽  
Author(s):  
Michael X Cohen
Keyword(s):  
Frequency Analysis ◽  
Time Series Data ◽  
Sine Wave ◽  
Stationary Time Series ◽  
Series Data ◽  
Time Frequency Analysis ◽  
Temporal Precision ◽  
Time Frequency ◽  
Number Of Cycles ◽  
The Brain

AbstractMorlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal precision and frequency precision. It is typically defined as the “number of cycles,” but this parameter is opaque, and often leads to uncertainty and suboptimal analysis choices, as well as being difficult to interpret and evaluate. The purpose of this paper is to present alternative formulations of Morlet wavelets in time and in frequency that allow parameterizing the wavelets directly in terms of the desired temporal and spectral smoothing (as full-width at half-maximum). This formulation provides clarity on an important data analysis parameter, and should facilitate proper analyses, reporting, and interpretation of results. MATLAB code is provided.

scholarly journals Stochastic Claims Reserving Methods with State Space Representations: A Review

Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 198
Author(s):  
Nataliya Chukhrova ◽  
Arne Johannssen
Keyword(s):  
Time Series ◽  
State Space ◽  
Life Insurance ◽  
Time Series Data ◽  
Temporal Dynamics ◽  
Insurance Companies ◽  
Series Data ◽  
Time Series Models ◽  
Life Insurer ◽  
High Flexibility

Often, the claims reserves exceed the available equity of non-life insurance companies and a change in the claims reserves by a small percentage has a large impact on the annual accounts. Therefore, it is of vital importance for any non-life insurer to handle claims reserving appropriately. Although claims data are time series data, the majority of the proposed (stochastic) claims reserving methods is not based on time series models. Among the time series models, state space models combined with Kalman filter learning algorithms have proven to be very advantageous as they provide high flexibility in modeling and an accurate detection of the temporal dynamics of a system. Against this backdrop, this paper aims to provide a comprehensive review of stochastic claims reserving methods that have been developed and analyzed in the context of state space representations. For this purpose, relevant articles are collected and categorized, and the contents are explained in detail and subjected to a conceptual comparison.

scholarly journals Application of OU processes to modelling temporal dynamics of the human microbiome, and calculating optimal sampling schemes

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Toby Kenney ◽  
Junqiu Gao ◽  
Hong Gu
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Temporal Dynamics ◽  
Stable State ◽  
Mean Reversion ◽  
Series Data ◽  
Optimal Sampling ◽  
Healthy Individuals ◽  
Temporal Continuity ◽  
Better Than

Abstract Background The vast majority of microbiome research so far has focused on the structure of the microbiome at a single time-point. There have been several studies that measure the microbiome from a particular environment over time. A few models have been developed by extending time series models to accomodate specific features in microbiome data to address questions of stability and interactions of the microbime time series. Most research has observed the stability and mean reversion for some microbiomes. However, little has been done to study the mean reversion rates of these stable microbes and how sampling frequencies are related to such conclusions. In this paper, we begin to rectify this situation. We analyse two widely studied microbial time series data sets on four healthy individuals. We choose to study healthy individuals because we are interested in the baseline temporal dynamics of the microbiome. Results For this analysis, we focus on the temporal dynamics of individual genera, absorbing all interactions in a stochastic term. We use a simple stochastic differential equation model to assess the following three questions. (1) Does the microbiome exhibit temporal continuity? (2) Does the microbiome have a stable state? (3) To better understand the temporal dynamics, how frequently should data be sampled in future studies? We find that a simple Ornstein–Uhlenbeck model which incorporates both temporal continuity and reversion to a stable state fits the data for almost every genus better than a Brownian motion model that contains only temporal continuity. The Ornstein–Uhlenbeck model also fits the data better than modelling separate time points as independent. Under the Ornstein–Uhlenbeck model, we calculate the variance of the estimated mean reversion rate (the speed with which each genus returns to its stable state). Based on this calculation, we are able to determine the optimal sample schemes for studying temporal dynamics. Conclusions There is evidence of temporal continuity for most genera; there is clear evidence of a stable state; and the optimal sampling frequency for studying temporal dynamics is in the range of one sample every 0.8–3.2 days.

scholarly journals Temporal uncertainty affects the visual processing of predicted stimulus properties

2020 ◽  
Author(s):  
Sanjeev Nara ◽  
Mikel Lizarazu ◽  
Craig G Richter ◽  
Diana C Dima ◽  
Mathieu Bourguignon ◽  
...  
Keyword(s):  
Visual Processing ◽  
Visual Information ◽  
Temporal Dynamics ◽  
External Environment ◽  
Predictive Processing ◽  
External Information ◽  
Specific Information ◽  
Temporal Uncertainty ◽  
Suppression Effect ◽  
The Brain

AbstractPredictive processing has been proposed as a fundamental cognitive mechanism to account for how the brain interacts with the external environment via its sensory modalities. The brain processes external information about the content (i.e. “what”) and timing (i.e., “when”) of environmental stimuli to update an internal generative model of the world around it. However, the interaction between “what” and “when” has received very little attention when focusing on vision. In this magnetoencephalography (MEG) study we investigate how processing of feature specific information (i.e. “what”) is affected by temporal predictability (i.e. “when”). In line with previous findings, we observed a suppression of evoked neural responses in the visual cortex for predictable stimuli. Interestingly, we observed that temporal uncertainty enhances this expectation suppression effect. This suggests that in temporally uncertain scenarios the neurocognitive system relies more on internal representations and invests less resources integrating bottom-up information. Indeed, temporal decoding analysis indicated that visual features are encoded for a shorter time period by the neural system when temporal uncertainty is higher. This supports the fact that visual information is maintained active for less time for a stimulus whose time onset is unpredictable compared to when it is predictable. These findings highlight the higher reliance of the visual system on the internal expectations when the temporal dynamics of the external environment are less predictable.

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