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

2017 ◽  
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.

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

eLife ◽  
2017 ◽  
Vol 6 ◽  
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.

scholarly journals Gait-phase modulates alpha and beta oscillations in the pedunculopontine nucleus

2021 ◽  
Author(s):  
Shenghong He ◽  
Alceste Deli ◽  
Petra Fischer ◽  
Christoph Wiest ◽  
Yongzhi Huang ◽  
...  
Keyword(s):  
Gait Cycle ◽  
Field Potential ◽  
Pedunculopontine Nucleus ◽  
Gait Control ◽  
Beta Power ◽  
Gait Phase ◽  
Beta Frequency ◽  
Stepping In Place ◽  
Local Field Potential Lfp ◽  
Deep Brain

AbstractBackgroudThe pedunculopontine nucleus (PPN) is a reticular collection of neurons at the junction of the midbrain and pons, playing an important role in modulating posture and locomotion. Deep brain stimulation of the PPN has been proposed as an emerging treatment for patients with Parkinson’s disease (PD) or multiple system atrophy (MSA) suffering gait-related atypical parkinsonian syndromes.ObjectiveIn this study, we investigated PPN activities during gait to better understand its functional role in locomotion. Specifically, we investigated whether PPN activity is rhythmically modulated during locomotion.MethodsPPN local field potential (LFP) activities were recorded from PD or MSA patients suffering from gait difficulties during stepping in place or free walking. Simultaneous measurements from force plates or accelerometers were used to determine the phase within each gait cycle at each time point.ResultsOur results showed that activities in the alpha and beta frequency bands in the PPN LFPs were rhythmically modulated by the gait phase within gait cycles, with a higher modulation index when the stepping rhythm was more regular. Meanwhile, the PPN-cortical coherence was most prominent in the alpha band. Both gait-phase related modulation in the alpha/beta power and the PPN-cortical coherence in the alpha frequency band were spatially specific to the PPN and did not extend to surrounding regions.ConclusionsThese results raise the possibility that alternating PPN stimulation in tandem with the gait rhythm may be more beneficial for gait control than continuous stimulation, although this remains to be established in future studies.

scholarly journals Novel Porous Brain Electrodes for Augmented Local Field Potential Signal Detection

Materials ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 542 ◽  
Author(s):  
Sung Lee ◽  
Kyeong-Seok Lee ◽  
Saurav Sorcar ◽  
Abdul Razzaq ◽  
Maan-Gee Lee ◽  
...  
Keyword(s):  
Local Field ◽  
Local Field Potential ◽  
Brain Activity ◽  
Field Potential ◽  
Porous Electrodes ◽  
Surface Topology ◽  
Neural Electrode ◽  
Flow Of Information ◽  
Potential Signal ◽  
Local Field Potential Lfp

Intracerebral local field potential (LFP) measurements are commonly used to monitor brain activity, providing insight into the flow of information across neural networks. Herein we describe synthesis and application of a neural electrode possessing a nano/micro-scale porous surface topology for improved LFP measurement. Compared with conventional brain electrodes, the porous electrodes demonstrate higher measured amplitudes with lower noise levels.

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

2020 ◽  
Vol 117 (47) ◽  
pp. 29925-29936
Author(s):  
Martyna J. Grabowska ◽  
Rhiannon Jeans ◽  
James Steeves ◽  
Bruno van Swinderen
Keyword(s):  
Brain Activity ◽  
Visual Navigation ◽  
Central Complex ◽  
Oscillatory Activity ◽  
Visual Features ◽  
Attention Tasks ◽  
Temporal Features ◽  
Object Based ◽  
Oscillatory Brain Activity ◽  
Beta Frequency

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.

scholarly journals Interactions between motor thalamic field potentials and single unit spiking predict behavior in rats

2019 ◽  
Author(s):  
Matt Gaidica ◽  
Amy Hurst ◽  
Christopher Cyr ◽  
Daniel K. Leventhal
Keyword(s):  
Task Performance ◽  
Brain Activity ◽  
Field Potential ◽  
Spike Timing ◽  
Delta Phase ◽  
Beta Power ◽  
High Gamma ◽  
Gamma Power ◽  
Complex Relationships ◽  
And Behavior

AbstractThe thalamus plays a central role in generating circuit-level neural oscillations believed to coordinate brain activity over large spatiotemporal scales. Such thalamic influences are well-documented for sleep rhythms and in sensory systems, but the relationship between thalamic activity, motor circuit local field potential (LFP) oscillations, and behavior is unknown. We recorded wideband motor thalamic (Mthal) electrophysiology as healthy rats performed a two-alternative forced choice task. The power of delta (1−4 Hz), beta (13−30 Hz), low gamma (30−70 Hz), and high gamma (70−200 Hz) oscillations were strongly modulated by task performance. As in cortex, delta phase predicted beta/low gamma power and reaction time. Furthermore, delta phase differentially predicted spike timing in functionally distinct populations of Mthal neurons, which also predicted task performance and beta power. These complex relationships suggest mechanisms for commonly observed LFP-LFP and spike-LFP interactions, as well as subcortical influences on motor output.

scholarly journals Cell type- and activity-dependent extracellular correlates of intracellular spiking

2015 ◽  
Vol 114 (1) ◽  
pp. 608-623 ◽  
Author(s):  
Costas A. Anastassiou ◽  
Rodrigo Perin ◽  
György Buzsáki ◽  
Henry Markram ◽  
Christof Koch
Keyword(s):  
Brain Activity ◽  
Field Potential ◽  
Synaptic Activity ◽  
Inhibitory Neurons ◽  
Temporal Features ◽  
Temporal Derivative ◽  
The Common ◽  
Rat Somatosensory Cortex ◽  
Activity Dependent ◽  
Local Field Potential Lfp

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remain enigmatic. We performed whole cell patch recordings of excitatory and inhibitory neurons in rat somatosensory cortex slice while positioning a silicon probe in their vicinity to concurrently record intra- and extracellular voltages for spike frequencies under 20 Hz. We characterize biophysical events and properties (intracellular spiking, extracellular resistivity, temporal jitter, etc.) related to EAP recordings at the single-neuron level in a layer-specific manner. Notably, EAP amplitude was found to decay as the inverse of distance between the soma and the recording electrode with similar (but not identical) resistivity across layers. Furthermore, we assessed a number of EAP features and their variability with spike activity: amplitude (but not temporal) features varied substantially (∼30–50% compared with mean) and nonmonotonically as a function of spike frequency and spike order. Such EAP variation only partly reflects intracellular somatic spike variability and points to the plethora of processes contributing to the EAP. Also, we show that the shape of the EAP waveform is qualitatively similar to the negative of the temporal derivative to the intracellular somatic voltage, as expected from theory. Finally, we tested to what extent EAPs can impact the lowpass-filtered part of extracellular recordings, the local field potential (LFP), typically associated with synaptic activity. We found that spiking of excitatory neurons can significantly impact the LFP at frequencies as low as 20 Hz. Our results question the common assertion that the LFP acts as proxy for synaptic activity.

scholarly journals A Beta Oscillation Network in the Rat Olfactory System During a 2-Alternative Choice Odor Discrimination Task

2010 ◽  
Vol 104 (2) ◽  
pp. 829-839 ◽  
Author(s):  
Leslie M. Kay ◽  
Jennifer Beshel
Keyword(s):  
Frequency Band ◽  
Field Potential ◽  
Gamma Oscillations ◽  
Beta Band ◽  
Beta Oscillations ◽  
Odor Discrimination Task ◽  
Beta Power ◽  
Beta Frequency Band ◽  
Alternative Choice ◽  
Beta Frequency

We previously showed that in a two-alternative choice (2AC) task, olfactory bulb (OB) gamma oscillations (∼70 Hz in rats) were enhanced during discrimination of structurally similar odorants (fine discrimination) versus discrimination of dissimilar odorants (coarse discrimination). In other studies (mostly employing go/no-go tasks) in multiple labs, beta oscillations (15–35 Hz) dominate the local field potential (LFP) signal in olfactory areas during odor sampling. Here we analyzed the beta frequency band power and pairwise coherence in the 2AC task. We show that in a task dominated by gamma in the OB, beta oscillations are also present in three interconnected olfactory areas (OB and anterior and posterior pyriform cortex). Only the beta band showed consistently elevated coherence during odor sniffing across all odor pairs, classes (alcohols and ketones), and discrimination types (fine and coarse), with stronger effects in first than in final criterion sessions (>70% correct). In the first sessions for fine discrimination odor pairs, beta power for incorrect trials was the same as that for correct trials for the other odor in the pair. This pattern was not repeated in coarse discrimination, in which beta power was elevated for correct relative to incorrect trials. This difference between fine and coarse odor discriminations may relate to different behavioral strategies for learning to differentiate similar versus dissimilar odors. Phase analysis showed that the OB led both pyriform areas in the beta frequency band during odor sniffing. We conclude that the beta band may be the means by which information is transmitted from the OB to higher order areas, even though task specifics modify dominance of one frequency band over another within the OB.

Information-based decoding of the coupling among human brain activity and movement paths

2021 ◽  
pp. 1-10
Author(s):  
Shahul Mujib Kamal ◽  
Norazryana Mat Dawi ◽  
Hamidreza Namazi
Keyword(s):  
Brain Activity ◽  
Point Of View ◽  
Physiological Signals ◽  
Human Walking ◽  
Eeg Signals ◽  
Rehabilitation Science ◽  
Information Contents ◽  
First Time ◽  
The Brain ◽  
Brain Reaction

BACKGROUND: Walking like many other actions of a human is controlled by the brain through the nervous system. In fact, if a problem occurs in our brain, we cannot walk correctly. Therefore, the analysis of the coupling of brain activity and walking is very important especially in rehabilitation science. The complexity of movement paths is one of the factors that affect human walking. For instance, if we walk on a path that is more complex, our brain activity increases to adjust our movements. OBJECTIVE: This study for the first time analyzed the coupling of walking paths and brain reaction from the information point of view. METHODS: We analyzed the Shannon entropy for electroencephalography (EEG) signals versus the walking paths in order to relate their information contents. RESULTS: According to the results, walking on a path that contains more information causes more information in EEG signals. A strong correlation (p= 0.9999) was observed between the information contents of EEG signals and walking paths. Our method of analysis can also be used to investigate the relation among other physiological signals of a human and walking paths, which has great benefits in rehabilitation science.

scholarly journals The impact of body posture on intrinsic brain activity: The role of beta power at rest

PLoS ONE ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. e0218977
Author(s):  
Brunella Donno ◽  
Daniele Migliorati ◽  
Filippo Zappasodi ◽  
Mauro Gianni Perrucci ◽  
Marcello Costantini
Keyword(s):  
Brain Activity ◽  
Body Posture ◽  
Beta Power ◽  
Intrinsic Brain Activity ◽  
The Impact

Neural Correlates of Mathematical Problem Solving

2015 ◽  
Vol 25 (02) ◽  
pp. 1550004 ◽  
Author(s):  
Chun-Ling Lin ◽  
Melody Jung ◽  
Ying Choon Wu ◽  
Hsiao-Ching She ◽  
Tzyy-Ping Jung
Keyword(s):  
Problem Solving ◽  
Spectral Power ◽  
Mathematical Problem ◽  
Neural Correlates ◽  
Mathematical Problem Solving ◽  
Single Digit ◽  
Beta Power ◽  
First Time ◽  
Anterior Posterior ◽  
Arithmetical Problem Solving

This study explores electroencephalography (EEG) brain dynamics associated with mathematical problem solving. EEG and solution latencies (SLs) were recorded as 11 neurologically healthy volunteers worked on intellectually challenging math puzzles that involved combining four single-digit numbers through basic arithmetic operators (addition, subtraction, division, multiplication) to create an arithmetic expression equaling 24. Estimates of EEG spectral power were computed in three frequency bands — θ (4–7 Hz), α (8–13 Hz) and β (14–30 Hz) — over a widely distributed montage of scalp electrode sites. The magnitude of power estimates was found to change in a linear fashion with SLs — that is, relative to a base of power spectrum, theta power increased with longer SLs, while alpha and beta power tended to decrease. Further, the topographic distribution of spectral fluctuations was characterized by more pronounced asymmetries along the left–right and anterior–posterior axes for solutions that involved a longer search phase. These findings reveal for the first time the topography and dynamics of EEG spectral activities important for sustained solution search during arithmetical problem solving.

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