Steven M. Nelson

Prediction of Individual Brain Maturity Using fMRI

Connectivity Map of the Brain The growing appreciation that clinically abnormal behaviors in children and adolescents may be influenced or perhaps even initiated by developmental miscues has stoked an interest in mapping normal human brain maturation. Several groups have documented changes in gray and white matter using structural and functional magnetic resonance imaging (fMRI) in cross-sectional and longitudinal studies. Dosenbach et al. (p. 1358) developed an index of resting-state functional connectivity (that is, how tightly neuronal activities in distinct brain regions are correlated while the subject is at rest or even asleep) from analyses of three independent data sets (each based on fMRI scans of 150 to 200 individuals from ages 6 to 35 years old). Long-range connections increased with age and short-range connections decreased, indicating that networks become sparser and sharper with brain maturation. Multivariate pattern analysis of 5-minute brain scans provides a measure of brain maturity. Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals’ brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain’s major functional networks.

Role of the anterior insula in task-level control and focal attention

In humans, the anterior insula (aI) has been the topic of considerable research and ascribed a vast number of functional properties by way of neuroimaging and lesion studies. Here, we argue that the aI, at least in part, plays a role in domain-general attentional control and highlight studies (Dosenbach et al. 2006; Dosenbach et al. 2007) supporting this view. Additionally, we discuss a study (Ploran et al. 2007) that implicates aI in processes related to the capture of focal attention. Task-level control and focal attention may or may not reflect information processing supported by a single functional area (within the aI). Therefore, we apply a novel technique (Cohen et al. 2008) that utilizes resting state functional connectivity MRI (rs-fcMRI) to determine whether separable regions exist within the aI. rs-fcMRI mapping suggests that the ventral portion of the aI is distinguishable from more dorsal/anterior regions, which are themselves distinct from more posterior parts of the aI. When these regions are applied to functional MRI (fMRI) data, the ventral and dorsal/anterior regions support processes potentially related to both task-level control and focal attention, whereas the more posterior aI regions did not. These findings suggest that there exists some functional heterogeneity within aI that may subserve related but distinct types of higher-order cognitive processing.

Evidence Accumulation and the Moment of Recognition: Dissociating Perceptual Recognition Processes Using fMRI

Decision making can be conceptualized as the culmination of an integrative process in which evidence supporting different response options accumulates gradually over time. We used functional magnetic resonance imaging to investigate brain activity leading up to and during decisions about perceptual object identity. Pictures were revealed gradually and subjects signaled the time of recognition (TR) with a button press. We examined the time course of TR-dependent activity to determine how brain regions tracked the timing of recognition. In several occipital regions, activity increased primarily as stimulus information increased, suggesting a role in lower-level sensory processing. In inferior temporal, frontal, and parietal regions, a gradual buildup in activity peaking in correspondence with TR suggested that these regions participated in the accumulation of evidence supporting object identity. In medial frontal cortex, anterior insula/frontal operculum, and thalamus, activity remained near baseline until TR, suggesting a relation to the moment of recognition or the decision itself. The findings dissociate neural processes that function in concert during perceptual recognition decisions.

Functional System and Areal Organization of a Highly Sampled Individual Human Brain

Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individuals systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals. VIDEO ABSTRACT.

Identifying basal ganglia divisions in individuals using resting-state functional connectivity MRI

Studies in non-human primates and humans reveal that discrete regions (henceforth, “divisions”) in the basal ganglia are intricately interconnected with regions in the cerebral cortex. However, divisions within basal ganglia nuclei (e.g., within the caudate) are difficult to identify using structural MRI. Resting-state functional connectivity MRI (rs-fcMRI) can be used to identify putative cerebral cortical functional areas in humans (Cohen et al., 2008). Here, we determine whether rs-fcMRI can be used to identify divisions in individual human adult basal ganglia. Putative basal ganglia divisions were generated by assigning basal ganglia voxels to groups based on the similarity of whole-brain functional connectivity correlation maps using modularity optimization, a network analysis tool. We assessed the validity of this approach by examining the spatial contiguity and location of putative divisions and whether divisions’ correlation maps were consistent with previously reported patterns of anatomical and functional connectivity. Spatially constrained divisions consistent with the dorsal caudate, ventral striatum, and dorsal caudal putamen could be identified in each subject. Further, correlation maps associated with putative divisions were consistent with their presumed connectivity. These findings suggest that, as in the cerebral cortex, subcortical divisions can be identified in individuals using rs-fcMRI. Developing and validating these methods should improve the study of brain structure and function, both typical and atypical, by allowing for more precise comparison across individuals.

Parcellating an Individual Subject's Cortical and Subcortical Brain Structures Using Snowball Sampling of Resting-State Correlations

We describe methods for parcellating an individual subjects cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability—reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individuals brain into functionally meaningful units.

High Quality but Limited Quantity Perceptual Evidence Produces Neural Accumulation in Frontal and Parietal Cortex

Goal-directed perceptual decisions involve the analysis of sensory inputs, the extraction and accumulation of evidence, and the commitment to a choice. Previous neuroimaging studies of perceptual decision making have identified activity related to accumulation in parietal, inferior temporal, and frontal regions. However, such effects may be related to factors other than the integration of evidence over time, such as changes in the quantity of stimulus input and in attentional demands leading up to a decision. The current study tested an accumulation account using 2 manipulations. First, to test whether patterns of accumulation can be explained by changes in the quantity of sensory information, objects were revealed with a high quality but consistent quantity of evidence throughout the trial. Imaging analysis revealed patterns of accumulation in frontal and parietal regions but not in inferior temporal regions. This result supports a framework in which evidence is processed in sensory cortex and integrated over time in higher order cortical areas. Second, to test whether accumulation signals are driven by attentional demands, task difficulty was increased on some trials. This manipulation did not affect the nature of accumulating functional magnetic resonance imaging signals, indicating that accumulating signals are not necessarily driven by changes in attentional demand.

Individual-specific features of brain systems identified with resting state functional correlations

Abstract Recent work has made important advances in describing the large‐scale systems‐level organization of human cortex by analyzing functional magnetic resonance imaging (fMRI) data averaged across groups of subjects. However, new findings have emerged suggesting that individuals’ cortical systems are topologically complex, containing small but reliable features that cannot be observed in group‐averaged datasets, due in part to variability in the position of such features along the cortical sheet. This previous work has reported only specific examples of these individual‐specific system features; to date, such features have not been comprehensively described. Here we used fMRI to identify cortical system features in individual subjects within three large cross‐subject datasets and one highly sampled within‐subject dataset. We observed system features that have not been previously characterized, but 1) were reliably detected across many scanning sessions within a single individual, and 2) could be matched across many individuals. In total, we identified forty‐three system features that did not match group‐average systems, but that replicated across three independent datasets. We described the size and spatial distribution of each non‐group feature. We further observed that some individuals were missing specific system features, suggesting individual differences in the system membership of cortical regions. Finally, we found that individual‐specific system features could be used to increase subject‐to‐subject similarity. Together, this work identifies individual‐specific features of human brain systems, thus providing a catalog of previously unobserved brain system features and laying the foundation for detailed examinations of brain connectivity in individuals. HighlightsFeatures of brain systems identified in individuals are absent from group averages.These features were both reliable within a single subject and present across subjects.These features were observed across three independent datasets.Some subjects were “missing” system features, suggesting variable system connections.Matching system features between individuals increased inter‐individual similarity.

Dissociating early and late error signals in perceptual recognition

Decisions about object identity follow a period in which evidence is gathered and analyzed. Evidence can consist of both task-relevant external stimuli and internally generated goals and expectations. How the various pieces of information are gathered and filtered into meaningful evidence by the nervous system is largely unknown. Although object recognition is often highly efficient and accurate, errors are common. Errors may be related to faulty evidence gathering arising from early misinterpretations of incoming stimulus information. In addition, errors in task performance are known to elicit late corrective performance monitoring mechanisms that can optimize or otherwise adjust future behavior. In this study, we used functional magnetic resonance imaging (fMRI) in an extended trial paradigm of object recognition to study whether we could identify performance-based signal modulations prior to and following the moment of recognition. The rationale driving the current report is that early modulations in fMRI activity may reflect faulty evidence gathering, whereas late modulations may reflect the presence of performance monitoring mechanisms. We tested this possibility by comparing fMRI activity on correct and error trials in regions of interest (ROIs) that were selected a priori. We found pre- and postrecognition accuracy-dependent modulation in different sets of a priori ROIs, suggesting the presence of dissociable error signals.

Neural Signatures of Test-Potentiated Learning in Parietal Cortex

Testing, or retrieval practice, is beneficial for long-term memory both directly, by enhancing performance on tested information, and indirectly, by facilitating learning from subsequent encounters with the information. Although a wealth of behavioral research has examined the “testing effect,” neuroimaging has provided little insight regarding the potential mechanisms that underlie the benefits of retrieval practice. Here, fMRI was used to examine the effects of retrieval practice on later study trials. Human subjects studied pairs of associated words, which were then tested, restudied, or neither tested nor restudied. All pairs were then studied once more in expectation of a final test. We asked how this Final Study episode was affected by prior history (whether the pair had been previously tested, restudied, or neither). The data revealed striking similarities between responses in lateral parietal cortex in the present study and those in a host of studies explicitly tapping recognition memory processes. Moreover, activity in lateral parietal cortex during Final Study was correlated with a behavioral index of test-potentiated learning. We conclude that retrieval practice may enhance learning by promoting the recruitment of retrieval mechanisms during subsequent study opportunities.