Oscillations in the central brain ofDrosophilaare phase locked to attended visual features

Object-based attention describes the brain’s capacity to prioritize one set of stimuli while ignoring others. Human research suggests that the binding of diverse stimuli into one attended percept requires phase-locked oscillatory activity in the brain. Even insects display oscillatory brain activity during visual attention tasks, but it is unclear if neural oscillations in insects are selectively correlated to different features of attended objects. We addressed this question by recording local field potentials in theDrosophilacentral complex, a brain structure involved in visual navigation and decision making. We found that attention selectively increased the neural gain of visual features associated with attended objects and that attention could be redirected to unattended objects by activation of a reward circuit. Attention was associated with increased beta (20- to 30-Hz) oscillations that selectively locked onto temporal features of the attended visual objects. Our results suggest a conserved function for the beta frequency range in regulating selective attention to salient visual features.

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Physical exercise increases overall brain oscillatory activity but does not influence inhibitory control in young adults

10.1101/268995 ◽

2018 ◽

Author(s):

Luis F. Ciria ◽

Pandelis Perakakis ◽

Antonio Luque-Casado ◽

Daniel Sanabria

Keyword(s):

Physical Exercise ◽

Inhibitory Control ◽

Frequency Band ◽

Brain Function ◽

Acute Exercise ◽

Brain Activity ◽

Oscillatory Activity ◽

Power Increase ◽

Oscillatory Brain Activity ◽

Exercise Induced

AbstractExtant evidence suggests that acute exercise triggers a tonic power increase in the alpha frequency band at frontal locations, which has been linked to benefits in cognitive function. However, recent literature has questioned such a selective effect on a particular frequency band, indicating a rather overall power increase across the entire frequency spectrum. Moreover, the nature of task-evoked oscillatory brain activity associated to inhibitory control after exercising, and the duration of the exercise effect, are not yet clear. Here, we investigate for the first time steady state oscillatory brain activity during and following an acute bout of aerobic exercise at two different exercise intensities (moderate-to-high and light), by means of a data-driven cluster-based approach to describe the spatio-temporal distribution of exercise-induced effects on brain function without prior assumptions on any frequency range or site of interest. We also assess the transient oscillatory brain activity elicited by stimulus presentation, as well as behavioural performance, in two inhibitory control (flanker) tasks, one performed after a short delay following the physical exercise and another completed after a rest period of 15’ post-exercise to explore the time course of exercise-induced changes on brain function and cognitive performance. The results show that oscillatory brain activity increases during exercise compared to the resting state, and that this increase is higher during the moderate-to-high intensity exercise with respect to the light intensity exercise. In addition, our results show that the global pattern of increased oscillatory brain activity is not specific to any concrete surface localization in slow frequencies, while in faster frequencies this effect is located in parieto-occipital sites. Notably, the exercise-induced increase in oscillatory brain activity disappears immediately after the end of the exercise bout. Neither transient (event-related) oscillatory activity, nor behavioral performance during the flanker tasks following exercise showed significant between-intensity differences. The present findings help elucidate the effect of physical exercise on oscillatory brain activity and challenge previous research suggesting improved inhibitory control following moderate-to-high acute exercise.

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The separation of auditory experience and the temporal structure of MEG recorded brain activity

10.1101/189480 ◽

2017 ◽

Author(s):

Chris Allen

Keyword(s):

High Frequency ◽

Temporal Dynamics ◽

Brain Activity ◽

Temporal Structure ◽

Oscillatory Activity ◽

Auditory Stimuli ◽

Brain Oscillations ◽

Successful Separation ◽

Auditory Experience ◽

Oscillatory Brain Activity

AbstractDo brain oscillations limit the temporal dynamics of experience? This pre-registered study used the separation of auditory stimuli to track perceptual experience and related this to oscillatory activity using magnetoencephalography. The rates at which auditory stimuli could be individuated matched the rates of oscillatory brain activity. Stimuli also entrained brain activity at the frequencies at which they were presented and a progression of high frequency gamma band events appeared to predict successful separation. These findings support a generalised function for brain oscillations, across frequency bands, in the alignment of activity to delineate representations.

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The rate of transient beta frequency events predicts behavior across tasks and species

eLife ◽

10.7554/elife.29086 ◽

2017 ◽

Vol 6 ◽

Cited By ~ 78

Author(s):

Hyeyoung Shin ◽

Robert Law ◽

Shawn Tsutsui ◽

Christopher I Moore ◽

Stephanie R Jones

Keyword(s):

High Power ◽

Event Rate ◽

Brain Activity ◽

Detection Task ◽

Field Potentials ◽

Motor Action ◽

Attention Tasks ◽

Beta Power ◽

Beta Frequency ◽

Abnormal Behaviors

Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and/or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations.

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EEG correlates of working memory performance in females

10.1101/098301 ◽

2017 ◽

Author(s):

Yuri G. Pavlov ◽

Boris Kotchoubey

Keyword(s):

Working Memory ◽

Individual Differences ◽

High Performance ◽

Brain Activity ◽

Memory Performance ◽

Two Dimensions ◽

Oscillatory Activity ◽

Theta Power ◽

Low Performance ◽

Oscillatory Brain Activity

AbstractBackgroundThe study investigates oscillatory brain activity during working memory (WM) tasks. The tasks employed varied in two dimensions. First, they differed in complexity from average to highly demanding. Second, we used two types of tasks, which required either only retention of stimulus set or retention and manipulation of the content. We expected to reveal EEG correlates of temporary storage and central executive components of WM and to assess their contribution to individual differences.ResultsGenerally, as compared with the retention condition, manipulation of stimuli in WM was associated with distributed suppression of alpha1 activity and with the increase of the midline theta activity. Load and task dependent decrement of beta1 power was found during task performance. Beta2 power increased with the increasing WM load and did not significantly depend on the type of the task.At the level of individual differences, we found that the high performance (HP) group was characterized by higher alpha rhythm power. The HP group demonstrated task-related increment of theta power in the left anterior area and a gradual increase of theta power at midline area. In contrast, the low performance (LP) group exhibited a drop of theta power in the most challenging condition. HP group was also characterized by stronger desynchronization of beta1 rhythm over the left posterior area in the manipulation condition. In this condition, beta2 power increased in the HP group over anterior areas, but in the LP group over posterior areas.ConclusionsWM performance is accompanied by changes in EEG in a broad frequency range from theta to higher beta bands. The most pronounced differences in oscillatory activity between individuals with high and low WM performance can be observed in the most challenging WM task.

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Neural oscillations while remembering traumatic memories in PTSD

10.1101/639310 ◽

2019 ◽

Author(s):

Inbal Reuveni ◽

Noa Herz ◽

Omer Bonne ◽

Tuvia Peri ◽

Shaul Schreiber ◽

...

Keyword(s):

Traumatic Event ◽

Brain Activity ◽

Traumatic Experience ◽

Oscillatory Activity ◽

Traumatic Memory ◽

Trauma Narratives ◽

Frequency Bands ◽

Traumatic Memories ◽

Localization Analysis ◽

Oscillatory Brain Activity

AbstractBackgroundIn posttraumatic stress disorder (PTSD), the traumatic event is often re-experienced through vivid sensory fragments of the traumatic experience. Though the sensory phenomenology of traumatic memories is well established, neural indications for this qualitative experience are lacking. The current study aimed at monitoring the oscillatory brain activity of PTSD patients during directed and imaginal exposure to the traumatic memory using magnetoencephalography (MEG), in a paradigm resembling exposure therapy.MethodsBrain activity of healthy trauma-exposed controls and PTSD participants was measured with MEG as they listened to individualized trauma narratives as well as to a neutral narrative and as they imagined the narrative in detail. Source localization analysis on varied frequency bands was conducted in order to map neural generators of altered oscillatory activity.ResultsPTSD patients exhibited increased power of high-frequency bands over visual areas and increased delta and theta power over auditory areas in response to trauma recollection compared to neutral recollection, while controls did not show such differential activation. PTSD participants also showed abnormal modulation of lower frequencies in the medial prefrontal cortex.ConclusionsElicitation of traumatic memories results in a distinct neural pattern in PTSD patients compared to healthy trauma-exposed individuals. Investigating the oscillatory neural dynamics of PTSD patients can help us better understand the processes underlying trauma re-experiencing.

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The rate of transient beta frequency events predicts impaired function across tasks and species

10.1101/128769 ◽

2017 ◽

Cited By ~ 3

Author(s):

Hyeyoung Shin ◽

Robert Law ◽

Shawn Tsutsui ◽

Christopher I. Moore ◽

Stephanie R. Jones

Keyword(s):

High Power ◽

Brain Activity ◽

Field Potential ◽

Motor Action ◽

Attention Tasks ◽

Beta Power ◽

Beta Frequency ◽

First Time ◽

Abnormal Behaviors ◽

Local Field Potential Lfp

AbstractBeta frequency oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of many healthy and abnormal behaviors, including perception, attention and motor action. Recent evidence shows that in non-averaged signals, beta can emerge as transient high-power “events”. As such, functionally relevant differences in averaged power across time and trials can reflect accumulated changes in the number, power, duration, and/or frequency span of the events. We show for the first time that functionally relevant differences in averaged prestimulus beta power in human sensory neocortex reflects a difference in the number of high-power beta events per trial, i.e., the rate of events. Further, high power beta events close to the time of the stimulus were more likely to impair perception. This result is consistent across detection and attention tasks in human magnetoencephalography (MEG) and is conserved in local field potential (LFP) recordings of mice performing a detection task. Our findings suggest transient brain rhythms are best viewed as a “rate metric” in their impact on function, and provides a new framework for understanding and manipulating functionally relevant rhythmic events.

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Unmixing Oscillatory Brain Activity by EEG Source Localization and Empirical Mode Decomposition

Computational Intelligence and Neuroscience ◽

10.1155/2019/5618303 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 3

Author(s):

Sofie Therese Hansen ◽

Apit Hemakom ◽

Mads Gylling Safeldt ◽

Lærke Karen Krohne ◽

Kristoffer Hougaard Madsen ◽

...

Keyword(s):

Empirical Mode Decomposition ◽

Source Localization ◽

Primary Motor Cortex ◽

Brain Activity ◽

Motor Evoked Potential ◽

Region Of Interest ◽

Oscillatory Activity ◽

Electrical Brain Activity ◽

Mode Decomposition ◽

Oscillatory Brain Activity

Neuronal activity is composed of synchronous and asynchronous oscillatory activity at different frequencies. The neuronal oscillations occur at time scales well matched to the temporal resolution of electroencephalography (EEG); however, to derive meaning from the electrical brain activity as measured from the scalp, it is useful to decompose the EEG signal in space and time. In this study, we elaborate on the investigations into source-based signal decomposition of EEG. Using source localization, the electrical brain signal is spatially unmixed and the neuronal dynamics from a region of interest are analyzed using empirical mode decomposition (EMD), a technique aimed at detecting periodic signals. We demonstrate, first in simulations, that the EMD is more accurate when applied to the spatially unmixed signal compared to the scalp-level signal. Furthermore, on EEG data recorded simultaneously with transcranial magnetic stimulation (TMS) over the hand area of the primary motor cortex, we observe a link between the peak to peak amplitude of the motor-evoked potential (MEP) and the phase of the decomposed localized electrical activity before TMS onset. The results thus encourage combination of source localization and EMD in the pursuit of further insight into the mechanisms of the brain with respect to the phase and frequency of the electrical oscillations and their cortical origin.

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Intraoperative localization of spatially and spectrally distinct resting-state networks in Parkinson’s disease

Journal of Neurosurgery ◽

10.3171/2018.11.jns181684 ◽

2020 ◽

Vol 132 (4) ◽

pp. 1234-1242 ◽

Cited By ~ 1

Author(s):

Paolo Belardinelli ◽

Ramin Azodi-Avval ◽

Erick Ortiz ◽

Georgios Naros ◽

Florian Grimm ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Network Effects ◽

Brain Activity ◽

Dynamic Imaging ◽

Oscillatory Activity ◽

Network Information ◽

Novel Approach ◽

Electrophysiological Recordings ◽

Intraoperative Localization

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for symptomatic Parkinson’s disease (PD); the clinical benefit may not only mirror modulation of local STN activity but also reflect consecutive network effects on cortical oscillatory activity. Moreover, STN-DBS selectively suppresses spatially and spectrally distinct patterns of synchronous oscillatory activity within cortical-subcortical loops. These STN-cortical circuits have been described in PD patients using magnetoencephalography after surgery. This network information, however, is currently not available during surgery to inform the implantation strategy.The authors recorded spontaneous brain activity in 3 awake patients with PD (mean age 67 ± 14 years; mean disease duration 13 ± 7 years) during implantation of DBS electrodes into the STN after overnight withdrawal of dopaminergic medication. Intraoperative propofol was discontinued at least 30 minutes prior to the electrophysiological recordings. The authors used a novel approach for performing simultaneous recordings of STN local field potentials (LFPs) and multichannel electroencephalography (EEG) at rest. Coherent oscillations between LFP and EEG sensors were computed, and subsequent dynamic imaging of coherent sources was performed.The authors identified coherent activity in the upper beta range (21–35 Hz) between the STN and the ipsilateral mesial (pre)motor area. Coherence in the theta range (4–6 Hz) was detected in the ipsilateral prefrontal area.These findings demonstrate the feasibility of detecting frequency-specific and spatially distinct synchronization between the STN and cortex during DBS surgery. Mapping the STN with this technique may disentangle different functional loops relevant for refined targeting during DBS implantation.

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An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States

Brain Sciences ◽

10.3390/brainsci11030330 ◽

2021 ◽

Vol 11 (3) ◽

pp. 330

Author(s):

Dalton J. Edwards ◽

Logan T. Trujillo

Keyword(s):

External Validity ◽

Spectral Power ◽

Brain Activity ◽

Outdoor Environment ◽

Oscillatory Activity ◽

Brain State ◽

Beta Band ◽

Eeg Spectral Power ◽

Eeg Power ◽

Human Participants

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4–7 Hz, alpha: 8–13 Hz, low beta: 14–20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.

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Visual predictions, neural oscillations and naïve physics

Scientific Reports ◽

10.1038/s41598-021-95295-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Blake W. Saurels ◽

Wiremu Hohaia ◽

Kielan Yarrow ◽

Alan Johnston ◽

Derek H. Arnold

Keyword(s):

Brain Activity ◽

Dynamic Environment ◽

Predictive Performance ◽

Brain Regions ◽

Internal Models ◽

Oscillatory Activity ◽

Alpha Band ◽

Core Property ◽

Ball Tracking ◽

Band Activity

AbstractPrediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.

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