scholarly journals Cortical activity is more stable when sensory stimuli are consciously perceived

2015 ◽  
Vol 112 (16) ◽  
pp. E2083-E2092 ◽  
Author(s):  
Aaron Schurger ◽  
Ioannis Sarigiannidis ◽  
Lionel Naccache ◽  
Jacobo D. Sitt ◽  
Stanislas Dehaene
Keyword(s):  
Spatial Scales ◽  
Threshold Level ◽  
Stimulus Onset ◽  
Conscious Perception ◽  
Subjective Report ◽  
Sensory Stimuli ◽  
Eeg Data ◽  
Pattern Similarity ◽  
The Stability ◽  
Global Brain

According to recent evidence, stimulus-tuned neurons in the cerebral cortex exhibit reduced variability in firing rate across trials, after the onset of a stimulus. However, in order for a reduction in variability to be directly relevant to perception and behavior, it must be realized within trial—the pattern of activity must be relatively stable. Stability is characteristic of decision states in recurrent attractor networks, and its possible relevance to conscious perception has been suggested by theorists. However, it is difficult to measure on the within-trial time scales and broadly distributed spatial scales relevant to perception. We recorded simultaneous magneto- and electroencephalography (MEG and EEG) data while subjects observed threshold-level visual stimuli. Pattern-similarity analyses applied to the data from MEG gradiometers uncovered a pronounced decrease in variability across trials after stimulus onset, consistent with previous single-unit data. This was followed by a significant divergence in variability depending upon subjective report (seen/unseen), with seen trials exhibiting less variability. Applying the same analysis across time, within trial, we found that the latter effect coincided in time with a difference in the stability of the pattern of activity. Stability alone could be used to classify data from individual trials as “seen” or “unseen.” The same metric applied to EEG data from patients with disorders of consciousness exposed to auditory stimuli diverged parametrically according to clinically diagnosed level of consciousness. Differences in signal strength could not account for these results. Conscious perception may involve the transient stabilization of distributed cortical networks, corresponding to a global brain-scale decision.

scholarly journals Initial-state-dependent, robust, transient neural dynamics encode conscious visual perception

2017 ◽  
Author(s):  
Alexis T. Baria ◽  
Brian Maniscalco ◽  
Biyu J. He
Keyword(s):  
Visual Perception ◽  
Activity Pattern ◽  
Human Subjects ◽  
Brain Activity ◽  
Threshold Level ◽  
Stimulus Onset ◽  
Conscious Perception ◽  
Initial State ◽  
State Dependent ◽  
Dynamical Nature

ABSTRACTRecent research has identified late-latency, long-lasting neural activity as a robust correlate of conscious perception. Yet, the dynamical nature of this activity is poorly understood, and the mechanisms governing its presence or absence and the associated conscious perception remain elusive. We applied dynamic-pattern analysis to whole-brain slow cortical dynamics recorded by magnetoencephalography (MEG) in human subjects performing a threshold-level visual perception task. Up to 1 second before stimulus onset, brain activity pattern across widespread cortices significantly predicted whether a threshold-level visual stimulus was later consciously perceived. This initial state of brain activity interacts nonlinearly with stimulus input to shape the evolving cortical activity trajectory, with seen and unseen trials following well separated trajectories. Furthermore, cortical activity trajectories during conscious perception are fast evolving and robust to small variations in the initial state. These results suggest that brain dynamics underlying conscious visual perception belongs to the class of initial-state-dependent, robust, transient neural dynamics.AUTHOR SUMMARYWhat brain mechanisms underlie conscious perception? A commonly adopted paradigm for studying this question is to present human subjects with threshold-level stimuli. When shown repeatedly, the same stimulus is sometimes consciously perceived, sometimes not. Using magnetoencephalography, we shed light on the neural mechanisms governing whether the stimulus is consciously perceived in a given trial. We observed that depending on the initial brain state defined by widespread activity pattern in the slow cortical potential (<5 Hz) range, a physically identical, brief (30 - 60 ms) stimulus input triggers distinct sequences of activity pattern evolution over time that correspond to either consciously perceiving the stimulus or not. Such activity pattern evolution forms a “trajectory” in the state space and affords significant single-trial decoding of perceptual outcome from 1 sec before to 3 sec after stimulus onset. While previous theories on conscious perception have emphasized sustained, high-level activity, we found that brain dynamics underlying conscious perception exhibit fast-changing activity patterns. These results significantly further our understanding on the neural mechanisms governing conscious access of a stimulus and the dynamical nature of neural activity underlying conscious perception.

An Efficient Deep Learning Paradigm for Deceit Identification Test on EEG Signals

2021 ◽  
Vol 12 (3) ◽  
pp. 1-20
Author(s):  
Damodar Reddy Edla ◽  
Shubham Dodia ◽  
Annushree Bablani ◽  
Venkatanareshbabu Kuppili
Keyword(s):  
Brain Computer Interface ◽  
Wavelet Packet ◽  
Stimulus Onset ◽  
Computer Interface ◽  
Band Pass Filter ◽  
Eeg Signals ◽  
Pass Filter ◽  
Eeg Data ◽  
Identification Test ◽  
Band Pass

Brain-Computer Interface is the collaboration of the human brain and a device that controls the actions of a human using brain signals. Applications of brain-computer interface vary from the field of entertainment to medical. In this article, a novel Deceit Identification Test is proposed based on the Electroencephalogram signals to identify and analyze the human behavior. Deceit identification test is based on P300 signals, which have a positive peak from 300 ms to 1,000 ms of the stimulus onset. The aim of the experiment is to identify and classify P300 signals with good classification accuracy. For preprocessing, a band-pass filter is used to eliminate the artifacts. The feature extraction is carried out using “symlet” Wavelet Packet Transform (WPT). Deep Neural Network (DNN) with two autoencoders having 10 hidden layers each is applied as the classifier. A novel experiment is conducted for the collection of EEG data from the subjects. EEG signals of 30 subjects (15 guilty and 15 innocent) are recorded and analyzed during the experiment. BrainVision recorder and analyzer are used for recording and analyzing EEG signals. The model is trained for 90% of the dataset and tested for 10% of the dataset and accuracy of 95% is obtained.

scholarly journals Impact of generalized brain arousal on sexual behavior

2010 ◽  
Vol 107 (5) ◽  
pp. 2265-2270 ◽  
Author(s):  
Zachary M. Weil ◽  
Qiuyu Zhang ◽  
Allison Hornung ◽  
David Blizard ◽  
Donald W. Pfaff
Keyword(s):  
Emotional Reactivity ◽  
Behavioral Arousal ◽  
Sensory Stimuli ◽  
Vertebrate Brain ◽  
Plus Maze ◽  
Initial Activation ◽  
High Level ◽  
Global Brain ◽  
Motivated Behaviors ◽  
The Impact

Although there is an extensive amount known about specific sensory and motor functions of the vertebrate brain, less is understood about the regulation of global brain states. We have recently proposed that a function termed generalized arousal (Ag) serves as the most elemental driving force in the nervous system, responsible for the initial activation of all behavioral responses. An animal with increased generalized CNS arousal is characterized by greater motor activity, increased responsivity to sensory stimuli, and greater emotional lability. Implicit in this theory was the prediction that increases in generalized arousal would augment specific motivated behaviors that depend on arousal. Here, we address the idea directly by testing two lines of mice bred for high or low levels of generalized arousal and assessing their responses in tests of specific forms of behavioral arousal, sex and anxiety/exploration. We report that animals selected for differential generalized arousal exhibit marked increases in sensory, motor, and emotional reactivity in our arousal assay. Furthermore, male mice selected for high levels of generalized arousal were excitable and showed more incomplete mounts before the first intromission (IN), but having achieved that IN, they exhibited far fewer IN before ejaculating, as well as ejaculating much sooner after the first IN, thus indicating a high level of sexual arousal. Additionally, high-arousal animals of both sexes exhibited greater levels of anxiety-like behaviors and reduced exploratory behavior in the elevated plus maze and light-dark box tasks. Taken together, these data illustrate the impact of Ag on motivated behaviors.

scholarly journals Dependence of the stimulus-driven microsaccade rate signature on visual stimulus polarity

2020 ◽  
Author(s):  
Tatiana Malevich ◽  
Antimo Buonocore ◽  
Ziad M. Hafed
Keyword(s):  
Stimulus Onset ◽  
Neural Mechanisms ◽  
Oculomotor Control ◽  
Background Luminance ◽  
Subsequent Increase ◽  
Rapid Reduction ◽  
Sensory Stimuli ◽  
Gaze Fixation ◽  
Early Access ◽  
Steady Rate

AbstractMicrosaccades have a steady rate of occurrence during maintained gaze fixation, which gets transiently modulated by abrupt sensory stimuli. Such modulation, characterized by a rapid reduction in microsaccade frequency followed by a stronger rebound phase of high microsaccade rate, is often described as the microsaccadic rate signature, owing to its stereotyped nature. Here we investigated the impacts of stimulus polarity (luminance increments or luminance decrements relative to background luminance) and size on the microsaccadic rate signature. We presented brief visual flashes consisting of large or small white or black stimuli over an otherwise gray image background. Both large and small stimuli caused robust early microsaccadic inhibition, but only small ones caused a subsequent increase in microsaccade frequency above baseline microsaccade rate. Critically, small black stimuli were always associated with stronger modulations in microsaccade rate after stimulus onset than small white stimuli, particularly in the post-inhibition rebound phase of the microsaccadic rate signature. Because small stimuli were also associated with expected direction oscillations to and away from their locations of appearance, these stronger rate modulations in the rebound phase meant higher likelihoods of microsaccades opposite the black flash locations relative to the white flash locations. Our results demonstrate that the microsaccadic rate signature is sensitive to stimulus polarity, and they point to dissociable neural mechanisms underlying early microsaccadic inhibition after stimulus onset and later microsaccadic rate rebound at longer times thereafter. These results also demonstrate early access of oculomotor control circuitry to sensory representations, particularly for momentarily inhibiting saccade generation.New and noteworthyMicrosaccades are small saccades that occur during gaze fixation. Microsaccade rate is transiently reduced after sudden stimulus onsets, and then strongly rebounds before returning to baseline. We explored the influence of stimulus polarity (black versus white) on this “rate signature”. We found that small black stimuli cause stronger microsaccadic modulations than white ones, but primarily in the rebound phase. This suggests dissociated neural mechanisms for microsaccadic inhibition and subsequent rebound in the microsaccadic rate signature.

scholarly journals Precise and pervasive phasic bursting in locus coeruleus during maternal behavior

2021 ◽  
Author(s):  
Roman Dvorkin ◽  
Stephen D. Shea
Keyword(s):  
Social Behavior ◽  
Locus Coeruleus ◽  
Maternal Behavior ◽  
Sensory Stimuli ◽  
Pup Retrieval ◽  
Subsequent Behavior ◽  
Maternal Interaction ◽  
Key Aspects ◽  
Global Brain ◽  
Relationship Of

ABSTRACTThe noradrenergic locus coeruleus (LC) mediates key aspects of arousal, memory, and cognition in structured tasks, but its contribution to natural behavior remains unclear. Neuronal activity in LC is organized into sustained (‘tonic’) firing patterns reflecting global brain states and rapidly fluctuating (‘phasic’) bursts signaling discrete behaviorally significant events. LC’s broad participation in social behavior including maternal behavior is well-established, yet the temporal relationship of its activity to sensory events and behavioral decisions in this context is unknown. Here, we made electrical and optical recordings from LC in female mice during maternal interaction with pups. We find that pup retrieval stably elicits precisely timed and pervasive phasic activation of LC that can’t be attributed to sensory stimuli, motor activity, or reward. Correlation of LC activity with retrieval events shows that phasic events are most closely related to subsequent behavior. We conclude that LC likely drives goal-directed action selection during social behavior with globally-broadcast noradrenaline release.

scholarly journals To stay or not to stay: The stability of choice perseveration in value-based decision making

2020 ◽  
Vol 74 (1) ◽  
pp. 199-217
Author(s):  
Ulrike Senftleben ◽  
Martin Schoemann ◽  
Matthias Rudolf ◽  
Stefan Scherbaum
Keyword(s):  
Decision Making ◽  
Stimulus Onset Asynchrony ◽  
Real Life ◽  
Stimulus Onset ◽  
Time Interval ◽  
Decision Task ◽  
Cognitive Stability ◽  
Inter Trial Interval ◽  
The Stability ◽  
Onset Asynchrony

In real life, decisions are often naturally embedded in decision sequences. In contrast, in the laboratory, decisions are oftentimes analysed in isolation. Here, we investigated the influence of decision sequences in value-based decision making and whether the stability of such effects can be modulated. In our decision task, participants needed to collect rewards in a virtual two-dimensional world. We presented a series of two reward options that were either quick to collect but were smaller in value or took longer to collect but were larger in value. The subjective value of each option was driven by the options’ value and how quickly they could be reached. We manipulated the subjective values of the options so that one option became gradually less valuable over the course of a sequence, which allowed us to measure choice perseveration (i.e., how long participants stick to this option). In two experiments, we further manipulated the time interval between two trials (inter-trial interval), and the time delay between the onsets of both reward options (stimulus onset asynchrony). We predicted how these manipulations would affect choice perseveration using a computational attractor model. Our results indicate that both the inter-trial interval and the stimulus onset asynchrony modulate choice perseveration as predicted by the model. We discuss how our findings extend to research on cognitive stability and flexibility.

scholarly journals The Effects of Human Visual Sensory Stimuli on N1b Amplitude: An EEG Study

2020 ◽  
Vol 9 (9) ◽  
pp. 2837
Author(s):  
Damien Moore ◽  
Toshikazu Ikuta ◽  
Paul D. Loprinzi
Keyword(s):  
Visual Cortex ◽  
Visual Stimulation ◽  
Human Model ◽  
Sensory Stimuli ◽  
Neural Connections ◽  
Black And White ◽  
Adaptive Mechanisms ◽  
Eeg Data ◽  
Significant Difference ◽  
Stimulation Paradigm

Sensory systems are widely known to exhibit adaptive mechanisms. Vision is no exception to input dependent changes in its sensitivity. Recent animal work demonstrates enhanced connectivity between neurons in the visual cortex. The purpose of the present experiment was to evaluate a human model that noninvasively alters the amplitude of the N1b component in the visual cortex of humans by means of rapid visual stimulation. Nineteen participants (Mage = 24 years; 52.6% male) completed a rapid visual stimulation paradigm involving black and white reversal checkerboards presented bilaterally in the visual field. EEG data was collected during the visual stimulation paradigm, which consisted of four main phases, a pre-tetanus block, photic stimulus, early post-tetanus, and late post-tetanus. The amplitude of the N1b component of the pre-tetanus, early post-tetanus and late post-tetanus visual evoked potentials were calculated. Change in N1b amplitude was calculated by subtracting pre-tetanus N1b amplitude from early and late post-tetanus. Results demonstrated a significant difference between pre-tetanus N1b (M = −0.498 µV, SD = 0.858) and early N1b (M = −1.011 µV, SD = 1.088), t (18) = 2.761, p = 0.039, d = 0.633. No difference was observed between pre-tetanus N1b and late N1b (p = 0.36). In conclusion, our findings suggest that it is possible to induce changes in the amplitude of the visually evoked potential N1b waveform in the visual cortex of humans non-invasively. Additional work is needed to corroborate that the potentiation of the N1b component observed in this study is due to similar mechanisms essential to prolonged strengthened neural connections exhibited in cognitive structures of the brain observed in prior animal research. If so, this will allow for the examination of strengthened neural connectivity and its interaction with multiple human sensory stimuli and behaviors.

Persistence in the fine-scale distribution and spatial aggregation of fishing

2018 ◽  
Vol 76 (4) ◽  
pp. 1072-1082 ◽  
Author(s):  
Niels T Hintzen ◽  
Geert Aarts ◽  
Adriaan D Rijnsdorp
Keyword(s):  
High Stability ◽  
Large Scale ◽  
Spatial Scales ◽  
Negative Relationship ◽  
Fishing Effort ◽  
Local Scale ◽  
Fine Scale ◽  
Effort Allocation ◽  
The Stability ◽  
First Time

Abstract High-resolution vessel monitoring (VMS) data have led to detailed estimates of the distribution of fishing in both time and space. While several studies have documented large-scale changes in fishing distribution, fine-scale patterns are still poorly documented, despite VMS data allowing for such analyses. We apply a methodology that can explain and predict effort allocation at fine spatial scales; a scale relevant to assess impact on the benthic ecosystem. This study uses VMS data to quantify the stability of fishing grounds (i.e. aggregated fishing effort) at a microscale (tens of meters). The model links effort registered at a large scale (ICES rectangle; 1° longitude × 0.5° latitude, ˜3600 km2) to fine spatial trawling intensities at a local scale (i.e. scale matching gear width, here 24 m). For the first time in the literature, the method estimates the part of an ICES rectangle that is unfavourable or inaccessible for fisheries, which is shown to be highly stable over time and suggests higher proportions of inaccessible grounds for either extremely muddy or courser substrates. The study furthermore shows high stability in aggregation of fishing, where aggregation shows a positive relationship with depth heterogeneity and a negative relationship with year-on-year variability in fishing intensity.

scholarly journals Attention Optimization Method for EEG via the TGAM

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yu Wu ◽  
Ning Xie
Keyword(s):  
Optimization Method ◽  
Faculty Members ◽  
Computer Interface ◽  
Research Teams ◽  
Practical Applications ◽  
Eeg Data ◽  
Data Feedback ◽  
Data Output ◽  
The Stability ◽  
Stability And Accuracy

Since the 21st century, noninvasive brain-computer interface (BCI) has developed rapidly, and brain-computer devices have gradually moved from the laboratory to the mass market. Among them, the TGAM (ThinkGear Asic Module) and its encapsulate algorithm have been adopted by many research teams and faculty members around the world. However, due to the limited development cost, the effectiveness of the algorithm to calculate data is not satisfactory. This paper proposes an attention optimization algorithm based on the TGAM for EEG data feedback. Considering that the data output of the TGAM encapsulate algorithm fluctuates greatly, the delay is high and the accuracy is low. The experimental results demonstrated that our algorithm can optimize EEG data, so that with the same or even lower delay and without changing the encapsulate algorithm of the module itself, it can significantly improve the performance of attention data, greatly improve the stability and accuracy of data, and achieve better results in practical applications.

Bidirectional connectivity in rivers and implications for watershed stability and management

2015 ◽  
Vol 72 (5) ◽  
pp. 785-795 ◽  
Author(s):  
Jonathan W. Moore
Keyword(s):  
Human Impacts ◽  
Spatial Scales ◽  
Ecological Resilience ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Challenges And Opportunities ◽  
Watershed Governance ◽  
The Stability ◽  
Natural Scale ◽  
Future Management

River networks are connected in both upstream and downstream directions on large spatial scales by movement of water, materials, and animals. Here I examine the implications of these linkages for the stability, productivity, and management of watersheds and their migratory fishes. I use simple simulations of watershed alteration to illustrate that degradation can erode the productivity and stability of both upstream and downstream fisheries. Through analysis of an existing global dataset on rivers, I found that larger rivers tend to be more fragmented than smaller rivers. I offer three challenges and opportunities for the future management of watersheds. First, given that human impacts can spread up and down rivers, there is a need to align the scales of impact assessments with the natural scale of river systems. Second, free-flowing rivers naturally dampen variability; thus, the conservation of connectivity, habitat, and biodiversity represents a key opportunity to sustain the processes that confer stability. Third, watersheds represent natural units of social–ecological systems; watershed governance would facilitate reciprocal feedbacks between people and ecosystems and enable more social–ecological resilience.

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