Role of local field potentials in encoding hand movement kinematics

2011 ◽  
Vol 106 (4) ◽  
pp. 1601-1603 ◽  
Author(s):  
Matthias Witte
Keyword(s):  
Local Field ◽  
Hand Movement ◽  
Three Dimensional ◽  
Local Field Potentials ◽  
Movement Planning ◽  
Field Potentials ◽  
Brain Signals ◽  
Reach And Grasp ◽  
The Brain

How the brain orchestrates the musculoskeletal system to produce complex three-dimensional movements is still poorly understood. Despite first promising results in brain-machine interfaces that translate cortical activity to control output, there is an ongoing debate about which brain signals provide richest information related to movement planning and execution. Novel results by Bansal and colleagues (2011) now suggest that neuronal spiking and local field potentials jointly encode kinematics during skilled reach and grasp movements.

7 Converging evidence from local field potentials and acute stimulation for subthalamic nucleus theta involvement in internally generated decisions to initiate or withhold actions

2020 ◽  
Vol 91 (8) ◽  
pp. e10.3-e11
Author(s):  
Luis Manssuer ◽  
Valerie Voon ◽  
Chen Cheng Zhang ◽  
Linbin Wang
Keyword(s):  
Subthalamic Nucleus ◽  
Local Field ◽  
Visual Cues ◽  
Local Field Potentials ◽  
Theta Activity ◽  
Field Potentials ◽  
Theta Frequency ◽  
The Right ◽  
Deep Brain

Objectives/AimsTo examine the causal role of the subthalamic nucleus (STN) in externally cued or internally generated decisions to execute or withhold an action by recording and stimulating neural activity in this region using deep brain stimulation (DBS) electrodes implanted for the treatment of Parkinson’s disease (PD).Methods20 PD patients completed an intentional inhibition task in which they were instructed by visual cues to go, stop or choose to go or stop. Each cue was on the screen until the patient pressed a button with their left thumb or for a maximum of 1500 ms and was preceded by a fixation cross for 1000–1500 ms. Local field potentials (LFP) were simultaneously recorded from the left STN and stimulated in the right STN at the clinical frequency of 130Hz or theta frequency 7Hz for 500 ms prior to the onset of the cue on half of the choice trials.ResultsOn non-stimulation choice trials, analysis of the LFP’s showed a significant decrease in theta activity when patients chose to stop compared to go. This difference began prior to the onset of the response. Behaviourally, patients chose to respond less when the STN was stimulated at a frequency of 7 hz for 500 ms prior to the onset of the cue but not at 130 Hz.On non-stimulation choice trials, analysis of the LFP’s also showed that there was a significant decrease in theta activity when patients chose to stop compared to go. This difference began prior to the onset of the response.ConclusionsThe findings suggest that pre-existing theta activity in the STN may bias one’s pre-disposition to choose to initiate an action and that stimulation of this activity may interfere with this process.

scholarly journals mPFC spindle cycles organize sparse thalamic activation and recently active CA1 cells during non-REM sleep

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Carmen Varela ◽  
Matthew A Wilson
Keyword(s):  
Local Field ◽  
Rem Sleep ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Temporal Window ◽  
Sharp Wave ◽  
Memory Traces ◽  
Limbic Thalamus ◽  
Spatial Exploration

Sleep oscillations in the neocortex and hippocampus are critical for the integration of new memories into stable generalized representations in neocortex. However, the role of the thalamus in this process is poorly understood. To determine the thalamic contribution to non-REM oscillations (sharp-wave ripples, SWRs; slow/delta; spindles), we recorded units and local field potentials (LFPs) simultaneously in the limbic thalamus, mPFC, and CA1 in rats. We report that the cycles of neocortical spindles provide a key temporal window that coordinates CA1 SWRs with sparse but consistent activation of thalamic units. Thalamic units were phase-locked to delta and spindles in mPFC, and fired at consistent lags with other thalamic units within spindles, while CA1 units that were active during spatial exploration were engaged in SWR-coupled spindles after behavior. The sparse thalamic firing could promote an incremental integration of recently acquired memory traces into neocortical schemas through the interleaved activation of thalamocortical cells.

scholarly journals 2327 Decoding/encoding somatosensation from the hand area of the human primary somatosensory (S1) cortex for a closed-loop motor/sensory brain-machine interface (BMI)

2018 ◽  
Vol 2 (S1) ◽  
pp. 8-8
Author(s):  
Brian Lee ◽  
Richard Andersen ◽  
Helena Chui ◽  
William Mack
Keyword(s):  
Local Field ◽  
Closed Loop ◽  
Local Field Potentials ◽  
Injured Patient ◽  
Brain Machine Interface ◽  
Field Potentials ◽  
Initial Surgery ◽  
Cord Injury ◽  
Machine Interface ◽  
The Brain

OBJECTIVES/SPECIFIC AIMS: A brain-machine interface (BMI) is a device implanted into the brain of a paralyzed or injured patient to control an external assistive device, such as a cursor on a computer screen, a motorized wheelchair, or a robotic limb. We hypothesize we can utilize electrical stimulation of subdural electrocorticography (ECoG) electrodes as a method of generating the percepts of somatosensation such as vibration, temperature, or proprioception. METHODS/STUDY POPULATION: There will be 10 subjects, who are informed, willing, and consented epilepsy patients undergoing initial surgery for placement of subdural ECoG electrodes in the brain for seizure monitoring. ECoG will be used as a platform for recording high-resolution local field potentials during real-touch behavioral tasks. In addition, ECoG will also be used to electrically stimulate the human cerebral cortex in order to map and understand how varying stimulation parameters produce percepts of sensation. RESULTS/ANTICIPATED RESULTS: To determine how tactile and proprioceptive signals are integrated in S1, we will perform spectral analysis of the broadband local field potentials to look for increased power in specific frequency bands in the ECoG recordings while touching or moving the hand. To explore generating artificial sensation, the subject will be asked to perform a variety of tasks with and without the aid of stimulation. We anticipate the subject’s performance will be enhanced with the addition of artificial sensation. DISCUSSION/SIGNIFICANCE OF IMPACT: Many patients might benefit from a BMI, such as those with stroke, amputation, spinal cord injury, or brain trauma. The current generation of BMI devices are guided by visual feedback alone. However, without somatosensory feedback, even the most basic limb movements are difficult to perform in a fluid and natural manner. The results from this project will be crucial to developing a closed loop motor/sensory BMI.

scholarly journals A Biophysically Detailed Model of Neocortical Local Field Potentials Predicts the Critical Role of Active Membrane Currents

Neuron ◽  
2013 ◽  
Vol 79 (2) ◽  
pp. 375-390 ◽  
Author(s):  
Michael W. Reimann ◽  
Costas A. Anastassiou ◽  
Rodrigo Perin ◽  
Sean L. Hill ◽  
Henry Markram ◽  
...  
Keyword(s):  
Local Field ◽  
Critical Role ◽  
Local Field Potentials ◽  
Membrane Currents ◽  
Field Potentials ◽  
Detailed Model ◽  
Active Membrane

scholarly journals Multiscale Autoregressive Identification of Neuroelectrophysiological Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-5
Author(s):  
Timothy P. Gilmour ◽  
Thyagarajan Subramanian ◽  
Constantino Lagoa ◽  
W. Kenneth Jenkins
Keyword(s):  
Local Field ◽  
Signal To Noise Ratio ◽  
Local Field Potentials ◽  
Parametric Models ◽  
Field Potentials ◽  
Signal To Noise ◽  
Arx Model ◽  
Optimal Amount ◽  
The Brain ◽  
Selection Of

Electrical signals between connected neural nuclei are difficult to model because of the complexity and high number of paths within the brain. Simple parametric models are therefore often used. A multiscale version of the autoregressive with exogenous input (MS-ARX) model has recently been developed which allows selection of the optimal amount of filtering and decimation depending on the signal-to-noise ratio and degree of predictability. In this paper, we apply the MS-ARX model to cortical electroencephalograms and subthalamic local field potentials simultaneously recorded from anesthetized rodent brains. We demonstrate that the MS-ARX model produces better predictions than traditional ARX modeling. We also adapt the MS-ARX results to show differences in internuclei predictability between normal rats and rats with 6OHDA-induced parkinsonism, indicating that this method may have broad applicability to other neuroelectrophysiological studies.

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