scholarly journals EEG signals index a global signature of arousal embedded in neuronal population recordings

2020 ◽  
Author(s):  
Richard Johnston ◽  
Adam C. Snyder ◽  
Rachel S. Schibler ◽  
Matthew A. Smith
Keyword(s):  
Single Neuron ◽  
Visual Stimulation ◽  
Explanatory Power ◽  
Neuronal Population ◽  
Brain State ◽  
Global Changes ◽  
Eeg Signals ◽  
Neural Recordings ◽  
Slow Drift ◽  
Saccade Velocity

AbstractElectroencephalography (EEG) has long been used to index brain states, from early studies describing activity during visual stimulation to modern work employing complex perceptual tasks. These studies shed light on brain-wide signals but lacked explanatory power at the single neuron level. Similarly, single neuron studies can suffer from inability to measure brain-wide signals. Here, we combined these techniques while monkeys performed a change detection task and discovered a link between EEG and a signal embedded in spiking responses. This ‘slow drift’ was associated with arousal: decreases in pre-stimulus α power/increases in P1 amplitude were accompanied by :1) increases in pupil size, false alarm rate and saccade velocity; and 2) decreases in microsaccade rate and reaction time. These results show that brain-wide EEG signals can be used to index modes of activity acquired from direct neural recordings, that in turn reflect global changes in brain state that influence perception and behavior.

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

Effects of Saccades on the Activity of Neurons in the Cat Lateral Geniculate Nucleus

1998 ◽  
Vol 79 (2) ◽  
pp. 922-936 ◽  
Author(s):  
Daeyeol Lee ◽  
Joseph G. Malpeli
Keyword(s):  
Lateral Geniculate Nucleus ◽  
Visual Stimulation ◽  
Dark Condition ◽  
Lateral Geniculate ◽  
Visual Inputs ◽  
Saccade Velocity ◽  
Time Courses ◽  
Evoked Activity ◽  
X Cells ◽  
Y Cells

Lee, Daeyeol and Joseph G. Malpeli. Effects of saccades on the activity of neurons in the cat lateral geniculate nucleus. J. Neurophysiol. 79: 922–936, 1998. Effects of saccades on individual neurons in the cat lateral geniculate nucleus (LGN) were examined under two conditions: during spontaneous saccades in the dark and during stimulation by large, uniform flashes delivered at various times during and after rewarded saccades made to small visual targets. In the dark condition, a suppression of activity began 200–300 ms before saccade start, peaked ∼100 ms before saccade start, and smoothly reversed to a facilitation of activity by saccade end. The facilitation peaked 70–130 ms after saccade end and decayed during the next several hundred milliseconds. The latency of the facilitation was related inversely to saccade velocity, reaching a minimum for saccades with peak velocity >70–80°/s. Effects of saccades on visually evoked activity were remarkably similar: a facilitation began at saccade end and peaked 50–100 ms later. When matched for saccade velocity, the time courses and magnitudes of postsaccadic facilitation for activity in the dark and during visual stimulation were identical. The presaccadic suppression observed in the dark condition was similar for X and Y cells, whereas the postsaccadic facilitation was substantially stronger for X cells, both in the dark and for visually evoked responses. This saccade-related regulation of geniculate transmission appears to be independent of the conditions under which the saccade is evoked or the state of retinal input to the LGN. The change in activity from presaccadic suppression to postsaccadic facilitation amounted to an increase in gain of geniculate transmission of ∼30%. This may promote rapid central registration of visual inputs by increasing the temporal contrast between activity evoked by an image near the end of a fixation and that evoked by the image immediately after a saccade.

The evolution of the English street gang

2019 ◽  
Vol 18 (2) ◽  
pp. 64-78 ◽  
Author(s):  
John Pitts
Keyword(s):  
Young People ◽  
Global Change ◽  
Design Methodology ◽  
Relevant Literature ◽  
Explanatory Power ◽  
Global Changes ◽  
Street Gang ◽  
Public Authorities ◽  
Content Type ◽  
Evolutionary Trajectories

Purpose The purpose of this paper is to consider what the author might call the evolution of the evolutionary argument about gangs and, while acknowledging its explanatory power, suggests that gangs may develop in very different ways depending on the available opportunities, pre-existing forms of criminality in the areas in which gangs emerge and global change. Design/methodology/approach It is based on a review of the relevant literature and interviews with purposive samples of research, criminal justice and social welfare professionals and young people involved in or affected by gang crime. Findings were triangulated with data held by the police and other public authorities. Findings The term “street gang” includes a wide variety of groupings all of which are involved in some form of crime but with differential levels of organisation and commitment to purely instrumental goals. Gangs may form but not necessarily evolve. Gangs appear to develop in very different ways depending on the available opportunities, pre-existing forms of criminality in the areas in which they emerge and global changes in drugs markets. Originality/value The originality of the paper consists in its interrogation of the concept of “gang evolution” and its discussion of the variety of forms and evolutionary trajectories of gangs.

scholarly journals Cross-frequency phase-amplitude coupling in repetitive movements in patients with Parkinson's disease

2021 ◽  
Author(s):  
Ruxue Gong ◽  
Christoph Mühlberg ◽  
Mirko Wegscheider ◽  
Christopher Fricke ◽  
Jost-Julian Rumpf ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Primary Motor Cortex ◽  
Premotor Cortex ◽  
Neuronal Population ◽  
Motor Symptom ◽  
Healthy Controls ◽  
Eeg Signals ◽  
Oscillatory Eeg ◽  
Phase Amplitude

Bradykinesia is a cardinal motor symptom in Parkinson's disease whose pathophysiology is incompletely understood. When signals are recorded from the cortex or scalp at rest, affected patients display enhanced phase-amplitude coupling between β (13-30Hz) and broadband γ (50-150Hz) oscillatory activities. However, it remains unclear whether and how abnormal phase-amplitude coupling is involved in slowing Parkinsonian movements during their execution. To address these questions, we analyzed high-density EEG signals recorded simultaneously with various motor activities and at rest in 19 patients with Parkinson's disease and 20 healthy controls. The motor tasks consisted of repetitive index finger pressing, and slow and fast tapping movements. Individual EEG source signals were computed for the premotor cortex, primary motor cortex, primary somatosensory cortex, and primary somatosensory complex. For the resting condition and the pressing task, phase-amplitude coupling averaged over the 4 motor regions and the entire movement period was larger in patients than in controls. In contrast, in all tapping tasks, state-related phase-amplitude coupling was similar between patients and controls. These findings were not aligned with motor performance and EMG data, which showed abnormalities in patients for tapping but not for pressing, suggesting that the strength of β-broadband γ phase-amplitude coupling during the movement period does not directly relate to Parkinsonian bradykinesia. Subsequently, we examined the dynamics of oscillatory EEG signals during motor transitions. When healthy controls performed the pressing task, dynamic phase-amplitude coupling increased shortly before pressing onset and decreased subsequently. A strikingly similar motif of coupling rise and decay was observed around the offset of pressing and around the onset of slow tapping, suggesting that such transient phase-amplitude coupling changes may be linked to transitions between different movement states - akin to preparatory states in dynamical systems theory of motor control. In patients, the modulation of phase-amplitude coupling was similar in (normally executed) pressing, but flattened in slow (abnormally executed) tapping compared to the controls. These deviations in phase-amplitude coupling around motor action transients may indicate dysfunctional evolution of neuronal population dynamics from the preparatory state to movement generation in Parkinson's disease. These findings may indicate that cross-frequency coupling is involved in the pathophysiology of bradykinesia in Parkinson's disease through its abnormal dynamic modulation.

scholarly journals Person authentication based on eye-closed and visual stimulation using EEG signals

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hui Yen Yap ◽  
Yun-Huoy Choo ◽  
Zeratul Izzah Mohd Yusoh ◽  
Wee How Khoh
Keyword(s):  
User Satisfaction ◽  
Visual Stimulation ◽  
Support Vector ◽  
Biometric System ◽  
Eeg Signals ◽  
Pairwise Correlation ◽  
Eyes Closed ◽  
Recording Process ◽  
Electroencephalogram Eeg ◽  
Accuracy Performance

AbstractThe study of Electroencephalogram (EEG)-based biometric has gained the attention of researchers due to the neurons’ unique electrical activity representation of an individual. However, the practical application of EEG-based biometrics is not currently widespread and there are some challenges to its implementation. Nowadays, the evaluation of a biometric system is user driven. Usability is one of the concerning issues that determine the success of the system. The basic elements of the usability of a biometric system are effectiveness, efficiency and user satisfaction. Apart from the mandatory consideration of the biometric system’s performance, users also need an easy-to-use and easy-to-learn authentication system. Thus, to satisfy these user requirements, this paper proposes a reasonable acquisition period and employs a consumer-grade EEG device to authenticate an individual to identify the performances of two acquisition protocols: eyes-closed (EC) and visual stimulation. A self-collected database of eight subjects was utilized in the analysis. The recording process was divided into two sessions, which were the morning and afternoon sessions. In each session, the subject was requested to perform two different tasks: EC and visual stimulation. The pairwise correlation of the preprocessed EEG signals of each electrode channel was determined and a feature vector was formed. Support vector machine (SVM) was then used for classification purposes. In the performance analysis, promising results were obtained, where EC protocol achieved an accuracy performance of 83.70–96.42% while visual stimulation protocol attained an accuracy performance of 87.64–99.06%. These results have demonstrated the feasibility and reliability of our acquisition protocols with consumer-grade EEG devices.

scholarly journals Spatio-temporal patterns of population responses in the visual cortex under Isoflurane: from wakefulness to loss of consciousness

2020 ◽  
Author(s):  
Shany Nivinsky Margalit ◽  
Neta Gery Golomb ◽  
Omer Tsur ◽  
Aeyal Raz ◽  
Hamutal Slovin
Keyword(s):  
Visual Stimulation ◽  
Neuronal Population ◽  
Loss Of Consciousness ◽  
Population Activity ◽  
Population Responses ◽  
Anesthetic Drugs ◽  
Visual Areas ◽  
Visual Cortices ◽  
Evoked Activity ◽  
Higher Visual Areas

AbstractAnesthetic drugs are widely used in medicine and research to mediate loss of consciousness (LOC). Despite the vast use of anesthesia, how LOC affects cortical sensory processing and the underlying neural circuitry, is not well understood. We measured neuronal population activity in the visual cortices of awake and isoflurane anesthetized mice and compared the visually evoked responses under different levels of consciousness. We used voltage-sensitive dye imaging (VSDI) to characterize the temporal and spatial properties of cortical responses to visual stimuli over a range of states from wakefulness to deep anesthesia. VSDI enabled measuring the neuronal population responses at high spatial (meso-scale) and temporal resolution from several visual regions (V1, extrastiate-lateral (ESL) and extrastiate-medial (ESM)) simultaneously. We found that isoflurane has multiple effects on the population evoked response that augmented with anesthetic depth, where the largest changes occurred at LOC. Isoflurane reduced the response amplitude and prolonged the latency of response in all areas. In addition, the intra-areal spatial spread of the visually evoked activity decreased. During visual stimulation, intra-areal and inter-areal correlation between neuronal populations decreased with increasing doses of isoflurane. Finally, while in V1 the majority of changes occurred at higher doses of isoflurane, higher visual areas showed marked changes at lower doses of isoflurane. In conclusion, our results demonstrate a reverse hierarchy shutdown of the visual cortices regions: low-dose isoflurane diminishes the visually evoked activity in higher visual areas before lower order areas and cause a reduction in inter-areal connectivity leading to a disconnected network.

scholarly journals Neuronal population activity dynamics reveal a low-dimensional signature of operant learning

2021 ◽  
Author(s):  
Renan M. Costa ◽  
Douglas A. Baxter ◽  
John H. Byrne
Keyword(s):  
Single Neuron ◽  
Brain Regions ◽  
Neuronal Population ◽  
High Dimensional ◽  
Operant Learning ◽  
Population Activity ◽  
Temporal Shift ◽  
Voltage Imaging ◽  
Low Dimensional ◽  
Activity Dynamics

AbstractLearning engages a high-dimensional neuronal population space spanning multiple brain regions. We identified a low-dimensional signature associated with operant conditioning, a ubiquitous form of learning in which animals learn from the consequences of behavior. Using single-neuron resolution voltage imaging, we identified two low-dimensional motor modules in the neuronal population underlying Aplysia feeding. Our findings point to a temporal shift in module recruitment as the primary signature of operant learning.

scholarly journals Monitoring Brain State and Behavioral Performance during Repetitive Visual Stimulation

2021 ◽  
Vol 11 (23) ◽  
pp. 11544
Author(s):  
Alexander K. Kuc ◽  
Semen A. Kurkin ◽  
Vladimir A. Maksimenko ◽  
Alexander N. Pisarchik ◽  
Alexander E. Hramov
Keyword(s):  
Visual Stimulation ◽  
Brain Activity ◽  
Decision Time ◽  
Task Demands ◽  
Brain State ◽  
Time On Task ◽  
Behavioral Performance ◽  
Task Effects ◽  
Perceptual Performance ◽  
Eeg Power

We tested whether changes in prestimulus neural activity predict behavioral performance (decision time and errors) during a prolonged visual task. The task was to classify ambiguous stimuli—Necker cubes; manipulating the degree of ambiguity from low ambiguity (LA) to high ambiguity (HA) changed the task difficulty. First, we assumed that the observer’s state changes over time, which leads to a change in the prestimulus brain activity. Second, we supposed that the prestimulus state produces a different effect on behavioral performance depending on the task demands. Monitoring behavioral responses, we revealed that the observer’s decision time decreased for both LA and HA stimuli during the task performance. The number of perceptual errors lowered for HA, but not for LA stimuli. EEG analysis revealed an increase in the prestimulus 9–11 Hz EEG power with task time. Finally, we found associations between the behavioral and neural estimates. The prestimulus EEG power negatively correlated with the decision time for LA stimuli and the erroneous responses rate for HA stimuli. The obtained results confirm that monitoring prestimulus EEG power enables predicting perceptual performance on the behavioral level. The observed different time-on-task effects on the LA and HA stimuli processing may shed light on the features of ambiguous perception.

scholarly journals Drainage network position and historical connectivity explain global patterns in freshwater fishes’ range size

2019 ◽  
Vol 116 (27) ◽  
pp. 13434-13439 ◽  
Author(s):  
Juan Carvajal-Quintero ◽  
Fabricio Villalobos ◽  
Thierry Oberdorff ◽  
Gaël Grenouillet ◽  
Sébastien Brosse ◽  
...  
Keyword(s):  
Fish Species ◽  
Explanatory Power ◽  
Size Variation ◽  
River Basins ◽  
Freshwater Fishes ◽  
Geographic Range ◽  
Range Size ◽  
Global Changes ◽  
Freshwater Biodiversity ◽  
Geographic Range Size

Identifying the drivers and processes that determine globally the geographic range size of species is crucial to understanding the geographic distribution of biodiversity and further predicting the response of species to current global changes. However, these drivers and processes are still poorly understood, and no ecological explanation has emerged yet as preponderant in explaining the extent of species’ geographical range. Here, we identify the main drivers of the geographic range size variation in freshwater fishes at global and biogeographic scales and determine how these drivers affect range size both directly and indirectly. We tested the main hypotheses already proposed to explain range size variation, using geographic ranges of 8,147 strictly freshwater fish species (i.e., 63% of all known species). We found that, contrary to terrestrial organisms, for which climate and topography seem preponderant in determining species’ range size, the geographic range sizes of freshwater fishes are mostly explained by the species’ position within the river network, and by the historical connection among river basins during Quaternary low-sea-level periods. Large-ranged fish species inhabit preferentially lowland areas of river basins, where hydrological connectivity is the highest, and also are found in river basins that were historically connected. The disproportionately high explanatory power of these two drivers suggests that connectivity is the key component of riverine fish geographic range sizes, independent of any other potential driver, and indicates that the accelerated rates in river fragmentation might strongly affect fish species distribution and freshwater biodiversity.

scholarly journals Quality Assessment of Single-Channel EEG for Wearable Devices

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 601 ◽  
Author(s):  
Fanny Grosselin ◽  
Xavier Navarro-Sune ◽  
Alessia Vozzi ◽  
Katerina Pandremmenou ◽  
Fabrizio De Vico Fallani ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Single Channel ◽  
Low Cost ◽  
Wearable Devices ◽  
Brain State ◽  
Eeg Signals ◽  
Many Sources ◽  
The Brain

The recent embedding of electroencephalographic (EEG) electrodes in wearable devices raises the problem of the quality of the data recorded in such uncontrolled environments. These recordings are often obtained with dry single-channel EEG devices, and may be contaminated by many sources of noise which can compromise the detection and characterization of the brain state studied. In this paper, we propose a classification-based approach to effectively quantify artefact contamination in EEG segments, and discriminate muscular artefacts. The performance of our method were assessed on different databases containing either artificially contaminated or real artefacts recorded with different type of sensors, including wet and dry EEG electrodes. Furthermore, the quality of unlabelled databases was evaluated. For all the studied databases, the proposed method is able to rapidly assess the quality of the EEG signals with an accuracy higher than 90%. The obtained performance suggests that our approach provide an efficient, fast and automated quality assessment of EEG signals from low-cost wearable devices typically composed of a dry single EEG channel.

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