Event-related Potentials Corresponding to Decision-making Under Uncertain Conditions

BACKGROUND

Decision-making is essential to human functioning, and resolving uncertainty is an essential part of decision-making. Impaired decision-making is present in many pathological conditions, and identifying markers of decision-making under uncertainty will provide a measure of clinical impact in future studies of therapeutic intervention for impaired decision-making.

OBJECTIVE

To describe EEG event-related potentials (ERPs) correlating with decision-making under uncertain conditions when compared with certain conditions.

METHOD

We used a novel card-matching task based on the Wisconsin Card Sorting Test to describe the neural correlates of uncertainty, as measured by EEG, in a group of 27 neurotypical individuals. We evaluated 500-ms intervals in the 2 seconds after card presentation to identify ERPs that are associated with maximal uncertainty compared with maximal certainty.

RESULTS

After correcting for multiple comparisons, we identified an ERP in the 500-1000-ms time frame (certain > uncertain, max amplitude 12.73 µV, latency 914 ms) in the left posterior inferior region of the scalp. We also found a P300-like ERP in the left frontal and parietal regions in the 0-500-ms time frame when the individuals received correct versus incorrect feedback (incorrect feedback > correct feedback, max amplitude 1.625 µV, latency 339 ms).

CONCLUSION

We identified an ERP in the 500-1000-ms time frame (certain > uncertain) that may reflect the resolution of uncertainty, as well as a P300-like ERP when feedback is presented (incorrect feedback > correct feedback). These findings can be used in future studies to improve decision-making and resolve uncertainty on the described markers.

Electric field distribution predicts efficacy of accelerated intermittent theta burst stimulation for late-life depression

Introduction

Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention for late-life depression (LLD) but may have lower rates of response and remission owing to age-related brain changes. In particular, rTMS induced electric field strength may be attenuated by cortical atrophy in the prefrontal cortex. To identify clinical characteristics and treatment parameters associated with response, we undertook a pilot study of accelerated fMRI-guided intermittent theta burst stimulation (iTBS) to the right dorsolateral prefrontal cortex in 25 adults aged 50 or greater diagnosed with LLD and qualifying to receive clinical rTMS.

Methods

Participants underwent baseline behavioral assessment, cognitive testing, and structural and functional MRI to generate individualized targets and perform electric field modeling. Forty-five sessions of iTBS were delivered over 9 days (1800 pulses per session, 50-min inter-session interval). Assessments and testing were repeated after 15 sessions (Visit 2) and 45 sessions (Visit 3). Primary outcome measure was the change in depressive symptoms on the Inventory of Depressive Symptomatology-30-Clinician (IDS-C-30) from Visit 1 to Visit 3.

Results

Overall there was a significant improvement in IDS score with the treatment (Visit 1: 38.6; Visit 2: 31.0; Visit 3: 21.3; mean improvement 45.5%) with 13/25 (52%) achieving response and 5/25 (20%) achieving remission (IDS-C-30 < 12). Electric field strength and antidepressant effect were positively correlated in a subregion of the ventrolateral prefrontal cortex (VLPFC) (Brodmann area 47) and negatively correlated in the posterior dorsolateral prefrontal cortex (DLPFC).

Conclusion

Response and remission rates were lower than in recently published trials of accelerated fMRI-guided iTBS to the left DLPFC. These results suggest that sufficient electric field strength in VLPFC may be a contributor to effective rTMS, and that modeling to optimize electric field strength in this area may improve response and remission rates. Further studies are needed to clarify the relationship of induced electric field strength with antidepressant effects of rTMS for LLD.

Functional brain networks involved in decision-making under certain and uncertain conditions

PURPOSE

The aim of this study was to describe imaging markers of decision-making under uncertain conditions in normal individuals, in order to provide baseline activity to compare to impaired decision-making in pathological states.

METHODS

In this cross-sectional study, 19 healthy subjects ages 18-35 completed a novel decision-making card-matching task using a Phillips T3 Scanner and a 32-channel head coil. Functional data were collected in six functional runs. In one condition of the task, the participant was certain of the rule to apply to match the cards; in the other condition, the participant was uncertain. We performed cluster-based comparison of the two conditions using FSL fMRI Expert Analysis Tool and network-based analysis using MATLAB.

RESULTS

The uncertain > certain comparison yielded three clusters-a midline cluster that extended through the midbrain, the thalamus, bilateral prefrontal cortex, the striatum, and bilateral parietal/occipital clusters. The certain > uncertain comparison yielded bilateral clusters in the insula, parietal and temporal lobe, as well as a medial frontal cluster. A larger, more connected functional network was found in the uncertain condition.

CONCLUSION

The involvement of the insula, parietal cortex, temporal cortex, ventromedial prefrontal cortex, and orbitofrontal cortex of the certain condition reinforces the notion that certainty is inherently rewarding. For the uncertain condition, the involvement of the prefrontal cortex, parietal cortex, striatum, thalamus, amygdala, and hippocampal involvement was expected, as these are areas involved in resolving uncertainty and rule updating. The involvement of occipital cortical involvement and midbrain involvement may be attributed to increased visual attention and increased motor control.

Retained executive abilities in mild cognitive impairment are associated with increased white matter network connectivity

PURPOSE

To describe structural network differences in individuals with mild cognitive impairment (MCI) with high versus low executive abilities, as reflected by measures of white matter connectivity using diffusion tensor imaging (DTI).

MATERIALS AND METHODS

This was a retrospective, cross-sectional study. Of the 128 participants from the Alzheimer's Disease Neuroimaging Initiative database who had both a DTI scan as well as a diagnosis of MCI, we used an executive function score to classify the top 15 scoring patients as high executive ability, and the bottom-scoring 16 patients as low executive ability. Using a regions-of-interest-based analysis, we constructed networks and calculated graph theory measures on the constructed networks. We used automated tractography in order to compare differences in major white matter tracts.

RESULTS

The high executive ability group yielded greater network size, density and clustering coefficient. The high executive ability group reflected greater fractional anisotropy bilaterally in the inferior and superior longitudinal fasciculi.

CONCLUSIONS

The network measures of the high executive ability group demonstrated greater white matter integrity. This suggests that white matter reserve may confer greater protection of executive abilities. Loss of this reserve may lead to greater impairment in the progression to Alzheimer's disease dementia.

KEY POINTS

• The MCI high executive ability group yielded a larger network. • The MCI high executive ability group had greater FA in numerous tracts. • White matter reserve may confer greater protection of executive abilities. • Loss of executive reserve may lead to greater impairment in AD dementia.