Bressler, Steven L.

The dissertation discusses various node identification techniques as well as their downstream effects on network characteristics using task-activated fMRI data from two working memory paradigms: a verbal n-back task and a visual n-back task. The three node identification techniques examined within this work include: a group-aggregated approach, a subject-specific approach, and a voxel wise approach. The first chapters highlight crucial differences between group-aggregated and subject-specific methods of isolating nodes prior to undirected functional connectivity analysis. Results show that the two techniques yield significantly different network interactions and local network characteristics, despite having their network nodes restricted to the same anatomical regions. Prior to the introduction of the third technique, a chapter is dedicated to explaining the differences between a priori approaches (like the previously introduced group-aggregated and subject-specific techniques) and no a priori approaches (like the voxel wise approach). The chapter also discusses two ways to aggregate signal for node representation within a network: using the signal from a single voxel or aggregating signal across a group of neighboring voxels. Subsequently, a chapter is dedicated to introducing a novel processing pipeline which uses a data driven voxel wise approach to identify network nodes. The novel pipeline defines nodes using spatial temporal features generated by a deep learning algorithm and is validated by an analysis showing that the isolated nodes are condition and subject specific. The dissertation concludes by summarizing the main takeaways from each of the three analyses as well as highlighting the advantages and disadvantages of each of the three node identification techniques.

We examine the nature of causality as it exists within large-scale brain networks by first providing a rigorous conceptual analysis of probabilistic causality as distinct from deterministic causality. We then use information-theoretic methods, including the linear autoregressive modeling technique of Wiener-Granger causality (WGC), and Shannonian transfer entropy (TE), to explore and recover causal relations between two neural masses. Time series data were generated by Stefanescu-Jirsa 3D model of two coupled network nodes in The Virtual Brain (TVB), a novel neuroinformatics platform used to model resting state large-scale networks with neural mass models. We then extended this analysis to three nodes to investigate the equivalence of a concept in probabilistic causality known as ‘screening off’ with a method of statistical ablation known as conditional Granger causality. Finally, we review some of the empirical and theoretical work of nonlinear neurodynamics of Walter Freeman, as well as metastable coordination dynamics and investigate what impact they have had on consciousness research.

The endogenous, or voluntary, control of visuospatial attention relies upon
interactions within a frontoparietal dorsal attention network (DAN) and this network’s
top-down influence on visual occipital cortex (VOC). While these interactions have been
shown to occur during attention tasks, they are also known to occur to some extent at rest,
but the degree to which task-related interactions reflect either modulation or
reorganization of such ongoing intrinsic interactions is poorly understood. In addition, it
is known that in spatial neglect—a syndrome following unilateral brain lesions in which
patients fail to attend to the contralesional side of space—symptom severity covaries with
disruptions to intrinsic interhemispheric interactions between left and right homologous
regions of the DAN; however, similar covariance with disruptions to intrahemispheric
interactions within the DAN, and between the DAN and VOC, has not been demonstrated.
These issues are addressed herein via the measurement of both undirected and directed
functional connectivity (UFC, DFC) within the DAN and between the DAN and VOC. UFC and DFC were derived from correlations of, and multivariate vector autoregressive
modeling of, fMRI BOLD time-series, respectively. Time-series were recorded from
individuals performing an anticipatory visuospatial attention task and individuals at rest,
as well as from stroke patients either with or without neglect and age-matched healthy
controls. With regard to the first issue, the results show that relative to rest, top-down
DAN-to-VOC influence and within-DAN coupling are elevated during task performance,
but also that intrinsic connectivity patterns are largely preserved during the task. With
regard to the second issue, results show that interhemispheric imbalances of
intrahemispheric UFC and DFC both within the DAN and between the DAN and VOC
strongly correlate with neglect severity, and may co-occur with functional decoupling of
the hemispheres. This work thus demonstrates that the intrinsic functional integrity of the
DAN and its relationship to VOC is crucial for the endogenous control of visuospatial
attention during tasks, and that the compromise of this integrity due to stroke likely plays
a role in producing spatial neglect.

We sought to better understand human motor control by investigating functional interactions between the Supplementary Motor Area (SMA), dorsal Anterior Cingulate Cortex (dACC), and primary motor cortex (M1) in healthy adolescent participants performing visually coordinated unimanual finger-movement and n-back working memory tasks. We discovered modulation of the SMA by the dACC by analysis of fMRI BOLD time series recorded from the three ROIs (SMA, dACC, and M1) in each participant. Two measures of functional interaction were used: undirected functional connectivity was measured using the Pearson product-moment correlation coefficient (PMCC), and directed functional connectivity was measured from linear autoregressive (AR) models. In the first project, task-specific modulation of the SMA by the dACC was discovered while subjects performed a coordinated unimanual finger-movement task, in which the finger movement was synchronized with an exogenous visual stimulus. In the second project, modulation of the SMA by the dACC was found to be significantly greater in the finger coordination task than in an n-back working memory, in which the same finger movement signified a motor response indicating a 0-back or 2-back working memory match. We thus demonstrated in the first study that the dACC sends task-specific directed signals to the supplementary motor area, suggesting a role for the dACC in top-down motor control. Finally, the second study revealed that these signals were significantly greater in the coordinated motor task than in the n-back working memory task, suggesting that the modulation of the SMA by the dACC was associated with sustained, continuous motor production and/or motor expectation, rather than with the motor movement itself.

Working memory (WM) is a process that allows for the temporary and limited storage of information for an immediate goal or to be stored into a more permanent system. A large number of studies
have led to the widely accepted view that WM is mediated by the frontoparietal network (FPN), consisting
of areas in the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Current evidence suggests that
task specific patterns of neuronal oscillatory activity within the FPN play a fundamental role in WM, and
yet specific spatio-temporal properties of this activity are not well characterized. This study utilized multisite
local field potential (LFP) data recorded from PFC and PPC sites in two macaque monkeys trained to
perform a rule-based, Oculomotor Delayed Match-to-Sample task. The animals were required to learn
which of two rules determined the correct match (Location matching or Identity matching). Following a
500 ms fixation period, a sample stimulus was presented for 500 ms, followed by a randomized delay
lasting 800-1200 ms in which no stimulus was present. At the end of the delay period, a match stimulus
was presented, consisting of two of three possible objects presented at two of three possible locations.
When the match stimulus appeared, the monkey made a saccadic eye movement to the target. The rule in
effect determined which object served as the target. Time-frequency plots of three spectral measures
(power, coherence, and Wiener Granger Causality (WGC) were computed from MultiVariate
AutoRegressive LFP time-series models estimated in a 100-ms window that was slid across each of three
analysis epochs (fixation, sample, and delay). Low (25- 55 Hz) and high gamma (65- 100 Hz) activity were investigated separately due to evidence that they may be functionally distinct. Within each epoch, recording sites in the PPC and PFC were classified into groups according to the similarity of their power t-f plots derived by a K-means clustering algorithm. From the power-based site groups, the corresponding coherence and WGC were analyzed. This classification procedure uncovered spatial, temporal, and frequency dynamics of FPN
involvement in WM and other co-occurring processes, such as sensory and target related processes. These processes were distinguishable by rule and performance accuracy across all three spectral measures- power,
coherence, and WGC. Location and Identity rule were distinguishable by the low and high-gamma range.

Insulin-dependent diabetes mellitus (IDDM) is a metabolic disorder arising from pancreatic dysfunction. For survival, a diabetic must rely upon an exogenous source of insulin to ensure cellular health. Hypoglycemia is a condition that may arise in IDDM patients in which more insulin than glucose is present in the body. Chronic, severe occurrences of this condition have been speculated to incur memory impairment in diabetics. This experiment sought to determine if diabetics performed differently from a non-diabetic population on a delayed matching memory task, and also if those diabetics experiencing hypoglycemia performed more poorly than other diabetics on this task. It was found that IDDM patients do not perform differently from non-diabetics on a matching task, and most diabetics did not perform more poorly than other patients on the same task. One diabetic experiencing severe, chronic hypoglycemia performed more poorly than other experiment participants, suggesting that hypoglycemia may, in fact, be related to memory impairment on this delayed matching task.