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1. An approach to learning the hierarchical organization of the frontal lobe

   Butler, K; Cleveland, D; Mikell; C; Mofakham; Saalmann, Y; Djurić, PM (January 2023, EUSIPCO)

   In neuroscience, hierarchical models of brain connectivity, particularly in the prefrontal cortex (PFC), are used to understand how the brain can process sensory information, make decisions and perform other high level tasks. Despite extensive research, understanding the structure of the PFC remains a crucial challenge. To this end, we propose a data-driven approach to studying brain signals based on Gaussian processes and causal strengths. For discovering causations, we propose a metric referred to as double-averaged differential causal effect. The differential causal effect has been proposed recently, and it can be used to quantify causal strengths in a principled way. We studied real multivariate time series data that represent local field potentials from the frontal lobe. The interest was in finding the causal relationship between the medial and lateral PFC areas of the brain. Our results suggest that the medial PFC causally influences the lateral PFC. 

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2. The Effect of Anxiety on Regional Brain Volumes in the National Alzheimer’s Coordinating Center Uniform Data Set

   https://doi.org/10.1093/geroni/igaa057.1197  

   Burke, Shanna; Li, Tan; Grudzien, Adrienne; Barnes, Christopher; Hanson, Kevin; DeKosky, Steven (December 2020, Innovation in Aging)

   null (Ed.)

   Abstract Anxiety has been associated with greater risk of Alzheimer’s disease (AD) and existing research has identified structural differences in regional brain tissue in anxious compared to healthy samples, but results have been variable and somewhat inconsistent. We sought to determine the effect of anxiety on regional brain volumes by cognitive and apolipoprotein e (APOE) e4 status using data from a large, national dataset. A secondary analysis of the National Alzheimer’s Coordinating Center Uniform (NACC) Data Set was conducted using complete MRI data from 1,371 participants (mean age: 70.5; SD: 11.7). Multiple linear regression was used to estimate the adjusted effect of anxiety (via the Neuropsychiatric Inventory Questionnaire) on regional brain volumes through measurement of 30 structural MRI biomarkers. Anxiety was associated with lower total brain and total cortical gray matter volumes and increased lateral ventricular volume (p<.05). Lower mean volumes were also observed in all hippocampal, frontal lobe, parietal lobe, temporal lobe, and right occipital lobe volumes among participants who reported anxiety. Conversely, greater ventricular volumes were also correlated with anxiety. Findings suggest that anxiety is associated with significant atrophy in multiple brain regions and ventricular enlargement, even after controlling for intracranial volume and demographic covariates. Anxiety-related changes to brain morphology may contribute to greater AD risk. 

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3. Classification of Pretrial vs. Encoding stage for Working Memory Task among Subjects with pFC Lesions and Healthy Controls using Directed Information

   https://doi.org/10.1109/IEEECONF56349.2022.10052005  

   Balaji, Sai Sanjay; Avvaru, S.V. Sandeep; Parhi, Keshab K. (October 2022, Proc. 2022 Asilomar Conference on Signals, Systems and Computers)

   This paper analyzes the scalp electroencephalogram (EEG) recorded from 14 human subjects with pFC lesions and 20 healthy controls while performing lateral visuospatial working memory tasks to identify the directional brain networks responsible for memory encoding. First, we show that effective connectivity features using directed information (DI) are more accurate and robust than the functional connectivity measure of correlation coefficients in classifying the memory encoding stage from the pretrial phase, with a mean accuracy of 99.36%. Second, we identify the functional segregation of memory encoding to a much smaller sub-network by showing that the top 2.5% of the observed DI features can distinguish memory encoding from the pretrial phase with a mean accuracy of 93.1%. Finally, using graph features, we reveal the increased significance of frontocentral, centroparietal, and temporal regions in memory encoding for subjects with pFC lesions and reduced information flow in the prefrontal, frontal and parietooccipital areas when compared to healthy control. 

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4. The Impact of Sleep Disturbance on Regional Brain Volumes

   https://doi.org/10.1093/geroni/igaa057.1521  

   Burke, Shanna; Li, Tan; Grudzien, Adrienne; Barnes, Christopher; Hanson, Kevin; DeKosky, Steven (December 2020, Innovation in Aging)

   null (Ed.)

   Abstract Sleep disruption has been associated with increased beta-amyloid deposition and greater risk for later development of Alzheimer’s disease. Studies indicate that sleep disturbance correlates with regional brain volumes, but data are limited. We sought to determine the effect of sleep disturbance on regional brain volumes by cognitive and apolipoprotein e (APOE) e4 status. We conducted a secondary analysis of the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set using complete structural imaging data from 1,371 participants (mean age: 70.5; SD: 11.7). Multiple linear regression was used to estimate the adjusted effect of sleep disturbance (via Neuropsychiatric Inventory Questionnaire) on regional brain volumes through measurement of 30 structural MRI biomarkers. Sleep disruption was associated with greater volumes in the right and left lateral ventricles and greater volume of total white matter hyperintensities (p<.05). Lower mean volumes in total brain, total gray matter, and total cerebrum grey matter volumes, and in 12 hippocampal, frontal, parietal, and temporal lobe volumes were observed among participants who reported sleep disturbance. Males, Hispanic participants, and those with less education were more likely to report sleep disruption. Cognitive status moderated the relationship between sleep disturbance and lateral ventricular volumes, while APOE e4 moderated the effect between sleep disturbance and parietal lobe volumes. These findings suggest that disrupted sleep is associated with atrophy across multiple brain regions and ventricular hydrocephalus ex vacuo, after controlling for intracranial volume and demographic covariates. The influence of cognition and APOE e4 status indicates that this relationship is affected by co-occurring physiological processes. 

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5. Classifying Patients with pFC Lesions from Healthy Controls Using Directed Information Based Effective Brain Connectivity Measured from the Encoding Phase of Working Memory Task

   https://doi.org/10.1109/ISBI53787.2023.10230817  

   Balaji, Sai Sanjay; Parhi, Keshab K. (April 2023, Proc. of 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI))

   This paper describes a group-level analysis of 14 subjects with prefrontal cortex (pFC) lesions and 20 healthy controls performing multiple lateralized visuospatial working memory (WM) trials. Using effective brain connectivity measures inferred from directed information (DI) during memory encoding, we first show that DI features can correctly classify 18 control subjects and 11 subjects with pFC lesions, providing an overall accuracy of 85.3%. Second, we show that differential DI, the change in DI during the encoding phase from pretrial, can successfully overcome inter-subject variability and correctly identify the class of all 34 subjects (100% accuracy). These accuracy results are based on two-thirds majority thresholding among all trials. Finally, we use Welch’s t-test to identify the crucial differences in the two classes’ sub-networks responsible for memory encoding. While the inflow of information to the prefrontal region is significant among subjects with pFC lesions, the outflow from the prefrontal to the frontal and central regions is diminished compared to the control subjects. We further identify specific neural pathways that are exclusively activated for each group during the encoding phase. 

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