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Project

Field potentials and behavior analysis in rat models of abnormal brain cavities and compulsion

Brain damage is caused by loss or deterioration of brain cells and it is a prevalent type of injury that may be fatal, or may result in severe impairments, with devastating consequences on the quality of life of survivors. Loss of neural cells may lead to the formation of abnormal brain cavities (aBC), that are most often  the result of stroke and traumatic brain injuries (TBI), but can also occur after surgical resection of tumors or abscesses.

The chronic debilitating symptoms caused by neuronal damage are currently untreatable and largely depend on the degree and location of damage. In this work, we investigated the potential of neuromodulation as a treatment option, driven in a novel target – directly within the aBC wall, so as to alter aBC-related symptoms, and to improve behavioral outcome after neurological damage.

We used a generic model for brain damage, developed in a rat model. A foldable electrode array was implanted against the aBC wall, in a motor cortical rat model. The electrode implant was used both to interact with neural populations as well as record their activity. Much of the current understanding about motor system function is based on correlations between brain and behavioral tasks. Thus, the general objective of this thesis was to develop algorithms that identify behavioral and neural signal features with multiple aims: (i) to validate the aBC wall as a target for recording meaningful brain activity, (ii) to better quantify motor impairments and (iii) to investigate how modulating brain activity can improve behavioral outcome.

In a first step, we recorded electrical brain activity, as field potentials (FPs) on the surface of motor cortical aBC  of freely moving rats. We showed that FPs are dominated by oscillatory activity in the theta range (4-9 Hz) and gamma range (30-100 Hz) and can be an informative biomarker for behavioral features, as it allowed us to discriminate between behavioral state: active versus resting.

In a second step, we analyzed in detail impairment state. We developed an automated computer algorithm for analyzing reaching and grasping in impaired animals, subsequent to induction of a motor cortical aBC. The algorithm automatically tracks the movement of the rat’s forelimb using image processing methods. We classified endpoint behavior, achieving accuracy rates of 86%-92%. With this extended analysis we captured perturbation of skill after a motor cortical lesion was induced. Kinematics of reaching revealed that rats developed individual strategies to achieve the task.

In a third phase, we used the automatic algorithm to evaluate kinematics and endpoint outcome of skilled reaching during stimulation in different targets within the lesion wall. We stimulated either over the entire 16-electrode array (non-selective stimulation) or over subsets of electrodes (selective stimulation), proving that both strategies could alter kinematics of movement, with selective stimulation being at least as effective as non-selective stimulation.

Neurostimulation has been proven effective in the past recent years in  treating psychiatric disorders.  Finally, we used a rat model of obsessive compulsive disorder (OCD) in which deep brain stimulation was used to diminish compulsive symptoms. We showed that responders to deep brain stimulation presented specific brain modulations in the frequency bands of delta (1- 4 Hz), theta (4-8 Hz), beta (12-30 Hz), and lower gamma (30-45 Hz) that were otherwise not present in the non-responders or in the control subjects.

Our strategy is not limited by the cause of insult, be it ischemic stroke or traumatic brain injury, and allows direct interaction with the lesion wall via an invasive array of electrodes that can be used both for stimulation and for recording brain electrical activity. Access to neural activity allowed us to investigate neural mechanisms that may be relevant for impaired brain function, both in rat models of motor disability and psychiatric disorders. Finally, our strategy aims for an individual-focus treatment, that circumvents patient-dependent differences like severity and location of the brain damage. 

Date:1 Oct 2013 →  19 Nov 2018
Keywords:Brain stimulation, Signal analysis, Bio-control
Disciplines:Control systems, robotics and automation, Design theories and methods, Mechatronics and robotics, Computer theory
Project type:PhD project