How do neural processes give rise to cognition? Simultaneously predicting brain and behavior with a dynamic model of visual working memory

There is consensus that activation within distributed functional brain networks underlies human thought. The impact of this consensus is limited, however, by a gap that exists between data-driven correlational analyses that specify where functional brain activity is localized using functional magnetic resonance imaging (fMRI), and neural process accounts that specify how neural activity unfolds through time to give rise to behavior. Here, we show how an integrative cognitive neuroscience approach may bridge this gap. In an exemplary study of visual working memory, we use multilevel Bayesian statistics to demonstrate that a neural dynamic model simultaneously explains behavioral data and predicts localized patterns of brain activity, outperforming standard analytic approaches to fMRI. The model explains performance on both correct trials and incorrect trials where errors in change detection emerge from neural fluctuations amplified by neural interaction. Critically, predictions of the model run counter to cognitive theories of the origin of errors in change detection. Results reveal neural patterns predicted by the model within regions of the dorsal attention network that have been the focus of much debate. The model-based analysis suggests that key areas in the dorsal attention network such as the intraparietal sulcus play a central role in change detection rather than working memory maintenance, counter to previous interpretations of fMRI studies. More generally, the integrative cognitive neuroscience approach used here establishes a framework for directly testing theories of cognitive and brain function using the combined power of behavioral and fMRI data. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Probing the neural systems underlying flexible dimensional attention

Flexibly shifting attention between stimulus dimensions (e.g., shape and color) is a central component of regulating cognition for goal-based behavior. In the present report, we examine the functional roles of different cortical regions by manipulating two demands on task switching that have been confounded in previous studies—shifting attention between visual dimensions and resolving conflict between stimulus-response representations. Dimensional shifting was manipulated by having participants shift attention between dimensions (either shape or color; dimension shift) or keeping the task-relevant dimension the same (dimension same). Conflict between stimulus-response representations was manipulated by creating conflict between response-driven associations from the previous set of trials and the stimulus-response mappings on the current set of trials (e.g., making a leftward response to a red stimulus during the previous task, but being required to make a rightward response to a red stimulus in the current task; stimulus-response conflict), or eliminating conflict by altering the features of the dimension relevant to the sorting rule (stimulus-response no-conflict). These manipulations revealed activation along a network of frontal, temporal, parietal, and occipital cortices. Specifically, dimensional shifting selectively activated frontal and parietal regions. Stimulus-response conflict, on the other hand, produced decreased activation in temporal and occipital cortices. Occipital regions demonstrated a complex pattern of activation that was sensitive to both stimulus-response conflict and dimensional attention switching. These results provide novel information regarding the distinct role that frontal cortex plays in shifting dimensional attention and posterior cortices play in resolving conflict at the stimulus level

Validating a new methodology for optical probe design and image registration in fNIRS studies

Functional near-infrared spectroscopy (fNIRS) is an imaging technique that relies on the principle of shining near-infrared light through tissue to detect changes in hemodynamic activation. An important methodological issue encountered is the creation of optimized probe geometry for fNIRS recordings. Here, across three experiments, we describe and validate a processing pipeline designed to create an optimized, yet scalable probe geometry based on selected regions of interest (ROIs) from the functional magnetic resonance imaging (fMRI) literature. In experiment 1, we created a probe geometry optimized to record changes in activation from target ROIs important for visual working memory. Positions of the sources and detectors of the probe geometry on an adult head were digitized using a motion sensor and projected onto a generic adult atlas and a segmented head obtained from the subject's MRI scan. In experiment 2, the same probe geometry was scaled down to fit a child's head and later digitized and projected onto the generic adult atlas and a segmented volume obtained from the child's MRI scan. Using visualization tools and by quantifying the amount of intersection between target ROIs and channels, we show that out of 21 ROIs, 17 and 19 ROIs intersected with fNIRS channels from the adult and child probe geometries, respectively. Further, both the adult atlas and adult subject-specific MRI approaches yielded similar results and can be used interchangeably. However, results suggest that segmented heads obtained from MRI scans be used for registering children's data. Finally, in experiment 3, we further validated our processing pipeline by creating a different probe geometry designed to record from target ROIs involved in language and motor processing

Longitudinal diffusion changes in prodromal and early HD: Evidence of white-matter tract deterioration

INTRODUCTION: Huntington's disease (HD) is a genetic neurodegenerative disorder that primarily affects striatal neurons. Striatal volume loss is present years before clinical diagnosis; however, white matter degradation may also occur prior to diagnosis. Diffusion-weighted imaging (DWI) can measure microstructural changes associated with degeneration that precede macrostructural changes. DWI derived measures enhance understanding of degeneration in prodromal HD (pre-HD). METHODS: As part of the PREDICT-HD study, N = 191 pre-HD individuals and 70 healthy controls underwent two or more (baseline and 1-5 year follow-up) DWI, with n = 649 total sessions. Images were processed using cutting-edge DWI analysis methods for large multicenter studies. Diffusion tensor imaging (DTI) metrics were computed in selected tracts connecting the primary motor, primary somato-sensory, and premotor areas of the cortex with the subcortical caudate and putamen. Pre-HD participants were divided into three CAG-Age Product (CAP) score groups reflecting clinical diagnosis probability (low, medium, or high probabilities). Baseline and longitudinal group differences were examined using linear mixed models. RESULTS: Cross-sectional and longitudinal differences in DTI measures were present in all three CAP groups compared with controls. The high CAP group was most affected. CONCLUSIONS: This is the largest longitudinal DWI study of pre-HD to date. Findings showed DTI differences, consistent with white matter degeneration, were present up to a decade before predicted HD diagnosis. Our findings indicate a unique role for disrupted connectivity between the premotor area and the putamen, which may be closely tied to the onset of motor symptoms in HD. Hum Brain Mapp 38:1460-1477, 2017. © 2017 Wiley Periodicals, Inc

Neurocognitive features of motor premanifest individuals with myotonic dystrophy type 1

Objective: The goal of the study was to identify brain and functional features associated with premanifest phases of adult-onset myotonic dystrophy type 1 (i.e., PreDM1). Methods: This cross-sectional study included 68 healthy adults (mean age = 43.4 years, SD = 12.9), 13 individuals with PreDM1 (mean age: 47.4 years, SD = 16.3), and 37 individuals with manifest DM1 (mean age = 45.2 years, SD = 9.3). The primary outcome measures included fractional anisotropy (FA), motor measures (Muscle Impairment Rating Scale, Grooved Pegboard, Finger-Tapping Test, and grip force), general cognitive abilities (Wechsler Adult Intelligence Scales), sleep quality (Scales for Outcomes in Parkinson's Disease–Sleep), and apathy (Apathy Evaluation Scale). Results: Individuals with PreDM1 exhibited an intermediate level of white matter FA abnormality, where whole-brain FA was lower relative to healthy controls (difference of the estimated marginal mean [EMMdifference] = 0.02, 95% confidence interval (CI) 0.01–0.03, p < 0.001), but the PreDM1 group had significantly higher FA than did individuals with manifest DM1 (EMMdifference = 0.02, 95% CI 0.009–0.03, p < 0.001). Individuals with PreDM1 exhibited reduced performance on the finger-tapping task relative to control peers (EMMdifference = 5.70, 95% CI 0.51–11.00, p = 0.03), but performance of the PreDM1 group was better than that of the manifest DM1 group (EMMdifference = 5.60, 95% CI 0.11–11.00, p = 0.05). Hypersomnolence in PreDM1 was intermediate between controls (EMMdifference = −1.70, 95% CI −3.10–0.35, p = 0.01) and manifest DM1 (EMMdifference = −2.10, 95% CI −3.50–0.60, p = 0.006). Conclusions: Our findings highlight key CNS and functional deficits associated with PreDM1, offering insight in early disease course