Neural Basis of Decision-Making Deficits in Traumatic Brain Injury

National Institute of Neurological Disorders and Stroke (NINDS)45 enrolled

Overview

Background: People with a traumatic brain injury (TBI) can have trouble making the best possible decisions. Researchers want to learn more about the parts of the brain that control decision making. They also want to know how these are different between people. This may help predict how people make decisions after TBI. Objective: To learn more about which parts of the brain are involved in making decisions and how decisions may be hurt after TBI. Eligibility: Adults age 18 to 60. Design: Participants will be screened with medical history and physical exam. They will also take memory, attention, concentration, and thinking tests. Participants will do up to 2 experiments. For Experiment 1, participants may have 3 scans: PET: a chemical is injected through a thin tube into an arm vein. Participants lie on a bed that slides in and out of the scanner. MRI: a strong magnetic field and radio waves take pictures of the brain. Participants lie on a table that slides in and out of a metal cylinder. It makes loud knocking noises. Participants will get earplugs. They might be asked to do a task. A coil will be placed over the head. MEG: a cone with magnetic field detectors is lowered onto participants head. After the scans, participants will perform a decision-making task. For Experiment 2, participants will perform a decision-making task before and after receiving transcranial direct current stimulation (tDCS). tDCS: wet electrode sponges are placed over participants' scalp and forehead. A current passes between the electrodes. It stimulating the brain. Participants will return 24-48 hours later to repeat the decision-making task.

Study Description: Deficits in decision-making are commonly found in individuals after traumatic brain injury (TBI) and can have a severe negative impact on quality of life. Converging evidence from both animal model and human studies suggest that decision-making deficits are linked with abnormal mesocorticolimbic network structure and function, and could potentially be mitigated through interventions that improve function within these neuronal circuits. Objectives: 1. Quantify differences in performance on a decision-making task between TBI patients and healthy volunteers; 2. Determine whether baseline features of mesocorticolimbic network structure and function predict subsequent decision-making performance in both TBI patients and healthy volunteers; and 3. Determine if facilitatory transcranial direct current stimulation (tDCS) applied over the dorsolateral prefrontal cortex (dlPFC), a mesocorticolimbic network region crucially involved in decision-making, improves decision-making after TBI. Endpoints: Primary Endpoint: The primary outcome measure for both Experiment 1 and 2 is performance in a computerized decision-making task. Secondary Endpoints: Secondary outcome measures will include quantitative estimates of structural and functional mesocorticolimbic network features, including MRI-based structural and functional connectivity, MEG-based functional connectivity, baseline dlPFC GABA concentration measured with magnetic resonance spectroscopy (MRS) imaging, dopamine D2 receptor binding potential within mesocorticolimbic subcortical nuclei measured with \[11C\]raclopride PET (Experiment 1). Multimodal data fusion modeling will be used to explore the predictive relationship between baseline mesocorticolimbic network features and decision-making task performance within a unified state-space framework (Experiment 1), as well as the ability of these network features to predict inter-individual differences in the effects of tDCS on decision-making task performance (Experiment 2).

Interventions

tDCSDEVICE

There is no study intervention for Experiment 1. The study intervention for Experiment 2 is tDCS. tDCS is a non-invasive brain stimulation technique that uses electrodes attached to the scalp to deliver very low intensity direct current to the brain. This intervention has been demonstrated to result in neuromodulatory effects.

[11C] RacloprideDRUG

\[11C\] Raclopride is administered under an IND 054135. This IND is sponsored by the NIH Clinical Center and \[11C\] Raclopride is dispensed by the NIH PET Department. Quality Assurance for Radioactive Drug: \[11C\] Raclopride, is assayed for radiochemical purity under the supervision of the NIH PET Department prior to dispensing the drug for administration. Given that IND PET drugs manufactured at the NIH PET Department are used in a single site and that there is no intent for their commercialization, submission of IBs has not been required by FDA for any of the NIH Office of Research Support and Compliance-sponsored IND applications.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 60 YearsHealthy volunteers:

Medical Language ↔ Plain English

* INCLUSION CRITERIA Inclusion Criteria for Healthy Volunteers: * Age 18 to 60 * Able to give consent * Must be able to follow instructions and perform required tasks * Absence of clinically significant abnormalities during neurological examination Inclusion Criteria for TBI: * Age 18 to 60 * Able to give consent * Must be able to follow instructions and perform required tasks. * History of having a sustained, traumatically induced (e.g., collision between the head and an object, or sudden acceleration/deceleration of the brain without direct external trauma to the head) physiological disruption of brain function, as manifested by at least one of the following (based on the American Congress of Rehabilitation Medicine Criteria): * Any period of loss of consciousness * Any loss of memory for events immediately before or after the accident * Focal neurological deficit(s) that may or may not be transient * Any alteration in mental state at the time of the accident (e.g., feeling dazed, disoriented, or confused) * Presentation to a healthcare provider within 24 hours of the injury event * History of self-reported complaints or clinical findings related to planning or decision-making deficits EXCLUSION CRITERIA * Pre-existing and disabling major psychiatric (e.g., schizophrenia, bipolar disorder or post-traumatic stress disorder) or neurological disease (e.g., stroke, dementia, epilepsy, or multiple sclerosis). * Present use of prescribed stimulants (e.g., methylphenidate or amphetamines) * Present use of prescribed dopamine agonists/antagonists other than amantadine * For participants with childbearing capacity, pregnancy (for MRI and PET procedures) or nursing (for PET procedures only) * Contraindication to PET procedures (for PET procedures only) * Contraindication to MRI procedures as per MRI Center screening questionnaire (for MRI procedures only) * Inability to participate in at least two of the imaging procedures (PET, MRI or MEG) due to contraindications * Staff from our section * For TBI patients, history of a penetrating head wound * For healthy volunteers, history of any type of traumatically induced head injury resulting in presentation to an Emergency Department within 24 hours of the injury event

Outcomes

Primary Outcomes

The primary objective of this protocol is to: quantify differences in performance on a decision-making task between TBI patients and healthy volunteers.

The primary outcome measure for both Experiment 1 and 2 is performance in a computerized decision-making task.

Time frame: Participation may be completed over the course of a week, or longer depending on participant s schedule and testing availability. Typically, individuals complete the full study with 4-7 days.

Secondary Outcomes

The secondary objectives of this protocol are to: determine whether baseline features of mesocorticolimbic network structure and function predict subsequent decision-making performance in both TBI patients and healthy volunteers; and determine i...

Secondary outcome measures will include quantitative estimates of structural and functional mesocorticolimbic network features, including MRI-based structural and functional connectivity, MEG-based functional dynamics, baseline dlPFC GABA concentration measured with magnetic resonance spectroscopy (MRS) imaging, dopamine D2 receptor binding potential within mesocorticolimbic subcortical nuclei measured with \[11C\]raclopride PET (Experiment 1). Multimodal data fusion modeling will be used to explore the predictive relationship between baseline mesocorticolimbic network states and decision-making performance within a unified state-space framework (Experiment 1), as well as the ability of these network states to predict inter-individual differences in the effects of tDCS on decision-making performance (Experiment 2).