John D. Van Horn

Consequences, Action, and Intention as Factors in Moral Judgments: An fMRI Investigation

The traditional philosophical doctrines of Consequentialism, Doing and Allowing, and Double Effect prescribe that moral judgments and decisions should be based on consequences, action (as opposed to inaction), and intention. This study uses functional magnetic resonance imaging to investigate how these three factors affect brain processes associated with moral judgments. We find the following: (1) Moral scenarios involving only a choice between consequences with different amounts of harm elicit activity in similar areas of the brain as analogous nonmoral scenarios; (2) Compared to analogous nonmoral scenarios, moral scenarios in which action and inaction result in the same amount of harm elicit more activity in areas associated with cognition (such as the dorsolateral prefrontal cortex) and less activity in areas associated with emotion (such as the orbitofrontal cortex and temporal pole); (3) Compared to analogous nonmoral scenarios, conflicts between goals of minimizing harm and of refraining from harmful action elicit more activity in areas associated with emotion (orbitofrontal cortex and temporal pole) and less activity in areas associated with cognition (including the angular gyrus and superior frontal gyrus); (4) Compared to moral scenarios involving only unintentional harm, moral scenarios involving intentional harm elicit more activity in areas associated with emotion (orbitofrontal cortex and temporal pole) and less activity in areas associated with cognition (including the angular gyrus and superior frontal gyrus). These findings suggest that different kinds of moral judgment are preferentially supported by distinguishable brain systems.

Thinking about Human Abilities

When one looks for a studied moment at the myriad of abilities that humans display, it’s as if one were to look into the heavens on a clear night and become stirred by the ceaseless drift of the clouds of the Milky Way. On such a night one might be dimly aware that there is order and system in the celestial white. But where among the drifting haze might one draw dimensions to represent this order? At first there is no answer to this question, only befuddlement. The same is true for human abilities. They appear as free-floating swarms emerging from spaces of unknown many dimensions. Is there genuine order in this throng, or can one at least impose an order that will not do great injustice to the complexity and still enable one to organize thinking and talking about it? That is the major question of this chapter.

Effect of nicotine on brain activation during performance of a working memory task

Nicotine influences cognition and behavior, but the mechanisms by which these effects occur are unclear. By using positron emission tomography, we measured cognitive activation (increases in relative regional cerebral blood flow) during a working memory task [2-back task (2BT)] in 11 abstinent smokers and 11 ex-smokers. Assays were performed both after administration of placebo gum and 4-mg nicotine gum. Performance on the 2BT did not differ between groups in either condition, and the pattern of brain activation by the 2BT was consistent with reports in the literature. However, in the placebo condition, activation in ex-smokers predominated in the left hemisphere, whereas in smokers, it occurred in the right hemisphere. When nicotine was administered, activation was reduced in smokers but enhanced in ex-smokers. The lateralization of activation as a function of nicotine dependence suggests that chronic exposure to nicotine or withdrawal from nicotine affects cognitive strategies used to perform the memory task. Furthermore, the lack of enhancement of activation after nicotine administration in smokers likely reflects tolerance.

Mapping White Matter Integrity and Neurobehavioral Correlates in Children with Fetal Alcohol Spectrum Disorders

Brain structural abnormalities and neurocognitive dysfunction have been observed in individuals with fetal alcohol spectrum disorders (FASDs). Little is known about how white matter integrity is related to these functional and morphological deficits. We used a combination of diffusion tensor and T1-weighted magnetic resonance imaging to evaluate white matter integrity in individuals with FASDs and related these findings to neurocognitive deficits. Seventeen children and adolescents with FASDs were compared with 19 typically developing age-and gender-matched controls. Lower fractional anisotropy (FA) was observed in individuals with FASDs relative to controls in the right lateral temporal lobe and bilaterally in the lateral aspects of the splenium of the corpus callosum. White matter density was also lower in some, but not all regions in which FA was lower. FA abnormalities were confirmed to be in areas of white matter in post hoc region of interest analyses, further supporting that less myelin or disorganized fiber tracts are associated with heavy prenatal alcohol exposure. Significant correlations between performance on a test of visuomotor integration and FA in bilateral splenium, but not temporal regions were observed within the FASD group. Correlations between the visuomotor task and FA within the splenium were not significant within the control group, and were not significant for measures of reading ability. This suggests that this region of white matter is particularly susceptible to damage from prenatal alcohol exposure and that disruption of splenial fibers in this group is associated with poorer visuomotor integration.

Extensive Individual Differences in Brain Activations Associated with Episodic Retrieval are Reliable Over Time

The localization of brain functions using neuroimaging techniques is commonly dependent on statistical analyses of groups of subjects in order to identify sites of activation, particularly in studies of episodic memory. Exclusive reliance on group analysis may be to the detriment of understanding the true underlying cognitive nature of brain activations. In the present study, we found that the patterns of brain activity associated with episodic retrieval are very distinct for individual subjects from the patterns of brain activity at the group level. These differences go beyond the relatively small variations due to cyctoarchitectonic differences or spatial normalization. We quantify this individual variability by cross-correlating volumes of brain images. We demonstrate that individual patterns of brain activity are reliable over time despite their extensive variability. We suggest that varied but reliable individual patterns of significant brain activity may be indicative of different cognitive strategies used to produce a recognition response. We believe that individual analysis in conjunction with group analysis may be critical to fully understanding the relationship between retrieval processes and underlying brain regions.

Neural substrates of visuomotor learning based on improved feedback control and prediction

Motor skills emerge from learning feedforward commands as well as improvements in feedback control. These two components of learning were investigated in a compensatory visuomotor tracking task on a trial-by-trial basis. Between-trial learning was characterized with a state-space model to provide smoothed estimates of feedforward and feedback learning, separable from random fluctuations in motor performance and error. The resultant parameters were correlated with brain activity using magnetic resonance imaging. Learning related to the generation of a feedforward command correlated with activity in dorsal premotor cortex, inferior parietal lobule, supplementary motor area and cingulate motor area, supporting a role of these areas in retrieving and executing a predictive motor command. Modulation of feedback control was associated with activity in bilateral posterior superior parietal lobule as well as right ventral premotor cortex. Performance error correlated with activity in a widespread cortical and subcortical network including bilateral parietal, premotor and rostral anterior cingulate cortex as well as the cerebellar cortex. Finally, trial-by-trial changes of kinematics, as measured by mean absolute hand acceleration, correlated with activity in motor cortex and anterior cerebellum. The results demonstrate that incremental, learning-dependent changes can be modeled on a trial-by-trial basis and neural substrates for feedforward control of novel motor programs are localized to secondary motor areas.

Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimers Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu.

Resting-state fMRI can reliably map neural networks in children

Resting-state MRI (rs-fMRI) is a powerful procedure for studying whole-brain neural connectivity. In this study we provide the first empirical evidence of the longitudinal reliability of rs-fMRI in children. We compared rest-retest measurements across spatial, temporal and frequency domains for each of six cognitive and sensorimotor intrinsic connectivity networks (ICNs) both within and between scan sessions. Using KendallsW, concordance of spatial maps ranged from .60 to .86 across networks, for various derived measures. The Pearson correlation coefficient for temporal coherence between networks across all Time 1-Time 2 (T1/T2) z-converted measures was .66 (p<.001). There were no differences between T1/T2 measurements in low-frequency power of the ICNs. For the visual network, within-session T1 correlated with the T2 low-frequency power, across participants. These measures from resting-state data in children were consistent across multiple domains (spatial, temporal, and frequency). Resting-state connectivity is therefore a reliable method for assessing large-scale brain networks in children.

Efficient, distributed and interactive neuroimaging data analysis using the LONI pipeline

The LONI Pipeline is a graphical environment for construction, validation and execution of advanced neuroimaging data analysis protocols (Rex et al., 2003). It enables automated data format conversion, allows Grid utilization, facilitates data provenance, and provides a significant library of computational tools. There are two main advantages of the LONI Pipeline over other graphical analysis workflow architectures. It is built as a distributed Grid computing environment and permits efficient tool integration, protocol validation and broad resource distribution. To integrate existing data and computational tools within the LONI Pipeline environment, no modification of the resources themselves is required. The LONI Pipeline provides several types of process submissions based on the underlying server hardware infrastructure. Only workflow instructions and references to data, executable scripts and binary instructions are stored within the LONI Pipeline environment. This makes it portable, computationally efficient, distributed and independent of the individual binary processes involved in pipeline data-analysis workflows. We have expanded the LONI Pipeline (V.4.2) to include server-to-server (peer-to-peer) communication and a 3-tier failover infrastructure (Grid hardware, Sun Grid Engine/Distributed Resource Management Application API middleware, and the Pipeline server). Additionally, the LONI Pipeline provides three layers of background-server executions for all users/sites/systems. These new LONI Pipeline features facilitate resource-interoperability, decentralized computing, construction and validation of efficient and robust neuroimaging data-analysis workflows. Using brain imaging data from the Alzheimers Disease Neuroimaging Initiative (Mueller et al., 2005), we demonstrate integration of disparate resources, graphical construction of complex neuroimaging analysis protocols and distributed parallel computing. The LONI Pipeline, its features, specifications, documentation and usage are available online (http://Pipeline.loni.ucla.edu).

Mapping the human connectome.

Knowledge of the properties of white matter fiber tracts isa crucial and necessary step toward a precise understanding of the functional architecture of the living human brain. Previously, this knowledge was severely limited, as it was difficult to visualize these structures or measure their functions in vivo. The HCP has recently generated considerable interest because of its potential to explore connectivity and its relationship with genetics and behavior. For neuroscientists and the lay public alike, the ability to assess, measure, and explore this wealth of layered information concerning how the brain is wired is a much sought after prize.The navigation of the human connectome and the discovery of how it is affected through genetics, and in a range of neurological and psychiatric diseases, have far reaching implications. From a range of ongoing connectomics related activities, the systematic characterization of brain connectedness and the resulting functional aspects of such connectivity will not only realize the work of Ramón y Cajal and others, but will also greatly expand our understanding of the brain, the mind, and what it is to be truly human. The similarities and differences that mark normal diversity will help us to understand variation among people and set the stage to chart genetic influences on typical brain development and decline during aging. What is more, an understanding of how brains might become disordered will shed light on autism, schizophrenia, Alzheimer’s, and other diseases that exact a tremendous and terrible social and economic toll.