Analyzing functional connectivity in the brain using cross-correlation analysis of local field potentials

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.

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Multiscale Autoregressive Identification of Neuroelectrophysiological Systems

Computational and Mathematical Methods in Medicine ◽

10.1155/2012/580795 ◽

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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Transient loss of interhemispheric functional connectivity following unilateral cortical spreading depression in awake rats

Cephalalgia ◽

10.1177/0333102420970172 ◽

2020 ◽

pp. 033310242097017

Author(s):

Lyudmila V Vinogradova ◽

Elena M Suleymanova ◽

Tatiana M Medvedeva

Keyword(s):

Functional Connectivity ◽

Local Field ◽

Cortical Spreading Depression ◽

Spreading Depression ◽

Critical Role ◽

Local Field Potentials ◽

Abnormal Behavior ◽

Field Potentials ◽

Freely Behaving

Objective Growing evidence shows a critical role of network disturbances in the pathogenesis of migraine. Unilateral pattern of neurological symptoms of aura suggests disruption of interhemispheric interactions during the early phase of a migraine attack. Using local field potentials data from the visual and motor cortices, this study explored effects of unilateral cortical spreading depression, the likely pathophysiological mechanism of migraine aura, on interhemispheric functional connectivity in freely behaving rats. Methods Temporal evolution of the functional connectivity was evaluated using mutual information and phase synchronization measures applied to local field potentials recordings obtained in homotopic points of the motor and visual cortices of the two hemispheres in freely behaving rats after induction of a single unilateral cortical spreading depression in the somatosensory S1 cortex and sham cortical stimulation. Results Cortical spreading depression was followed by a dramatic broadband loss of interhemispheric functional connectivity in the visual and motor regions of the cortex. The hemispheric disconnection started after the end of the depolarization phase of cortical spreading depression, progressed gradually, and terminated by 5 min after initiation of cortical spreading depression. The network impairment had region- and frequency-specific characteristics and was more pronounced in the visual cortex than in the motor cortex. The period of impaired neural synchrony coincided with post-cortical spreading depression electrographic aberrant activation of the ipsilateral cortex and abnormal behavior. Conclusion The study provides the first evidence that unilateral cortical spreading depression induces a reversible loss of functional hemispheric connectivity in the cortex of awake animals. Given a critical role of long-distance cortical synchronization in sensory processing and sensorimotor integration, the post-cortical spreading depression breakdown of functional connectivity may contribute to neuropathological mechanisms of aura generation.

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Role of local field potentials in encoding hand movement kinematics

Journal of Neurophysiology ◽

10.1152/jn.00269.2011 ◽

2011 ◽

Vol 106 (4) ◽

pp. 1601-1603 ◽

Cited By ~ 1

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.

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