James Loughead

An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data.

Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed.

Impact of In-Scanner Head Motion on Multiple Measures of Functional Connectivity: Relevance for Studies of Neurodevelopment in Youth

It has recently been reported (Van Dijk et al., 2011) that in-scanner head motion can have a substantial impact on MRI measurements of resting-state functional connectivity. This finding may be of particular relevance for studies of neurodevelopment in youth, confounding analyses to the extent that motion and subject age are related. Furthermore, while Van Dijk et al. demonstrated the effect of motion on seed-based connectivity analyses, it is not known how motion impacts other common measures of connectivity. Here we expand on the findings of Van Dijk et al. by examining the effect of motion on multiple types of resting-state connectivity analyses in a large sample of children and adolescents (n=456). Following replication of the effect of motion on seed-based analyses, we examine the influence of motion on graphical measures of network modularity, dual-regression of independent component analysis, as well as the amplitude and fractional amplitude of low frequency fluctuation. In the entire sample, subject age was highly related to motion. Using a subsample where age and motion were unrelated, we demonstrate that motion has marked effects on connectivity in every analysis examined. While subject age was associated with increased within-network connectivity even when motion was accounted for, controlling for motion substantially attenuated the strength of this relationship. The results demonstrate the pervasive influence of motion on multiple types functional connectivity analysis, and underline the importance of accounting for motion in studies of neurodevelopment.

Classifying spatial patterns of brain activity with machine learning methods: Application to lie detection

Patterns of brain activity during deception have recently been characterized with fMRI on the multi-subject average group level. The clinical value of fMRI in lie detection will be determined by the ability to detect deception in individual subjects, rather than group averages. High-dimensional non-linear pattern classification methods applied to functional magnetic resonance (fMRI) images were used to discriminate between the spatial patterns of brain activity associated with lie and truth. In 22 participants performing a forced-choice deception task, 99% of the true and false responses were discriminated correctly. Predictive accuracy, assessed by cross-validation in participants not included in training, was 88%. The results demonstrate the potential of non-linear machine learning techniques in lie detection and other possible clinical applications of fMRI in individual subjects, and indicate that accurate clinical tests could be based on measurements of brain function with fMRI.

Telling truth from lie in individual subjects with fast event‐related fMRI

Deception is a clinically important behavior with poorly understood neurobiological correlates. Published functional MRI (fMRI) data on the brain activity during deception indicates that, on a multisubject group level, lie is distinguished from truth by increased prefrontal and parietal activity. These findings are theoretically important; however, their applied value will be determined by the accuracy of the discrimination between single deceptive and truthful responses in individual subjects. This study presents the first quantitative estimate of the accuracy of fMRI in conjunction with a formal forced‐choice paradigm in detecting deception in individual subjects. We used a paradigm balancing the salience of the target cues to elicit deceptive and truthful responses and determined the accuracy of this model in the classification of single lie and truth events. The relative salience of the task cues affected the net activation associated with lie in the superior medial and inferolateral prefrontal cortices. Lie was discriminated from truth on a single‐event level with an accuracy of 78%, while the predictive ability expressed as the area under the curve (AUC) of the receiver operator characteristic curve (ROC) was 85%. Our findings confirm that fMRI, in conjunction with a carefully controlled query procedure, could be used to detect deception in individual subjects. Salience of the task cues is a potential confounding factor in the fMRI pattern attributed to deception in forced choice deception paradigms. Hum Brain Mapp, 2005.

Age-related differences in brain activation during emotional face processing

Advancing age is associated with significant declines on neurobehavioral tasks that demand substantial mental effort. Functional imaging studies of mental abilities indicate that older adults faced with cognitive challenges tend to activate more regions, particularly frontal, than their younger counterparts, and that this recruitment of additional regions may reflect an attempt to compensate for inefficiency in cortical networks. The neural basis of emotion processing in aging has received little attention, and the goal of the present study was to use functional magnetic resonance imaging (fMRI) to examine the influence of age on facial emotion processing and activation in cortical and limbic regions. Participants (eight old and eight young adults) viewed facial displays of happiness, sadness, anger, fear, disgust, and neutrality in alternating blocks of emotion and age discrimination. We predicted that in response to an emotion discrimination task, older adults would demonstrate increased use of frontal regions relative to younger adults, perhaps combined with diminished use of regions recruited by younger adults, such as temporo-limbic regions. During the emotion discrimination task, young participants activated, visual, frontal and limbic regions, whereas older participants activated parietal, temporal and frontal regions. A direct comparison between emotion and age discrimination revealed that while younger adults activated the amygdala and surrounding temporo-limbic regions, older adults activated left frontal regions. The results of this study suggest that older adults may rely on different cortical networks to perceive emotional facial expressions than do their younger counterparts.

Neural substrates for functionally discriminating self-face from personally familiar faces

Understanding the neurobiological substrates of self‐recognition yields important insight into socially and clinically critical cognitive functions such as theory of mind. Experimental evidence suggests that right frontal and parietal lobes preferentially process self‐referent information. Recognition of ones own face is an important parameter of self‐recognition, but well‐controlled experimental data on the brain substrates of self‐face recognition is limited. The goal of this study was to characterize the activation specific to self‐face in comparison with control conditions of two levels of familiarity: unknown unfamiliar face and the more stringent control of a personally familiar face. We studied 12 healthy volunteers who made “unknown,” “familiar,” and “self” judgments about photographs of three types of faces: six different novel faces, a personally familiar face (participants fraternity brother), and their own face during an event‐related functional MRI (fMRI) experiment. Contrasting unknown faces with baseline showed activation of the inferior occipital lobe, which supports previous findings suggesting the presence of a generalized face‐processing area within the inferior occipital‐temporal region. Activation in response to a familiar face, when contrasted with an unknown face, invoked insula, middle temporal, inferior parietal, and medial frontal lobe activation, which is consistent with an existing hypothesis suggesting familiar face recognition taps neural substrates that are different from those involved in general facial processing. Brain response to self‐face, when contrasted with familiar face, revealed activation in the right superior frontal gyrus, medial frontal and inferior parietal lobes, and left middle temporal gyrus. The contrast familiar vs. self produced activation only in the anterior cingulate gyrus. Our results support the existence of a bilateral network for both perceptual and executive aspects of self‐face processing that cannot be accounted for by a simple hemispheric dominance model. This network is similar to those implicated in social cognition, mirror neuron matching, and face‐name matching. Our findings also show that some regions of the medial frontal and parietal lobes are specifically activated by familiar faces but not unknown or self‐faces, indicating that these regions may serve as markers of face familiarity and that the differences between activation associated with self‐face recognition and familiar face recognition are subtle and appear to be localized to lateral frontal, parietal, and temporal regions. Hum. Brain Mapping, 2005.

Varenicline Improves Mood and Cognition during Smoking Abstinence

BACKGROUND Neuronal nicotinic acetylcholine receptors (nAChRs) are a key target in medication development for various neuropsychiatric disorders, including nicotine dependence. Varenicline, a partial agonist at the alpha4beta2 nAChRs, is a new, efficacious medication for nicotine dependence. Its effects on the affective and cognitive dimensions of nicotine withdrawal have yet to be well characterized. METHODS Sixty-seven treatment-seeking smokers were administered varenicline (x 21 days) and placebo (x 21 days) in a double-blind within-subject crossover design. Following medication run-up (Days 1-10), there was a 3-day mandatory smoking abstinence phase (Days 11-13) during which subjective symptoms and cognitive performance were assessed. Participants were reexposed to a scheduled smoking lapse (Day 14) and followed for days to lapse (Days 15-21) in each medication period. RESULTS In the varenicline period, compared with placebo, withdrawal symptoms (p = .04), smoking urges (p < .001), and negative affect (p = .01) during manditory abstinence were significantly lower, and levels of positive affect (p = .046), sustained attention (p = .018), and working memory (p = .001) were significantly greater. Varenicline also significantly reduced subjective rewarding effects of the scheduled smoking lapse (e.g., satisfaction, relief, liking; p = .003). Medication effects on days to lapse following the scheduled smoking lapse were dependent on treatment order (p = .001); among participants who received placebo in the first period, varenicline increased days of abstinence in the follow-up period. CONCLUSIONS These data identify novel affective and cognitive effects of varenicline and may have implications for medication development for other neuropsychiatric conditions.

Baby schema modulates the brain reward system in nulliparous women

Ethologist Konrad Lorenz defined the baby schema (“Kindchenschema”) as a set of infantile physical features, such as round face and big eyes, that is perceived as cute and motivates caretaking behavior in the human, with the evolutionary function of enhancing offspring survival. The neural basis of this fundamental altruistic instinct is not well understood. Prior studies reported a pattern of brain response to pictures of children, but did not dissociate the brain response to baby schema from the response to children. Using functional magnetic resonance imaging and controlled manipulation of the baby schema in infant faces, we found that baby schema activates the nucleus accumbens, a key structure of the mesocorticolimbic system mediating reward processing and appetitive motivation, in nulliparous women. Our findings suggest that engagement of the mesocorticolimbic system is the neurophysiologic mechanism by which baby schema promotes human caregiving, regardless of kinship.

Neuroimaging of the Philadelphia neurodevelopmental cohort.

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1445 adolescents ages 8-21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and the measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development.

Working memory deficits predict short-term smoking resumption following brief abstinence.

As many as one-half of smokers relapse in the first week following a quit attempt, and subjective reports of cognitive deficits in early abstinence are associated with increased relapse risk. This study examined whether objective cognitive performance after 3 days of abstinence predicts smoking resumption in a 7-day simulated quit attempt. Sixty-seven treatment-seeking smokers received either varenicline or placebo (randomized double-blind) for 21 days. Following medication run-up (days 1-10), there was a 3-day mandatory (biochemically confirmed) abstinence period (days 11-13) during which working memory (Letter-N-Back Task) and sustained attention (Continuous Performance Task) were assessed (day 13). Participants were then exposed to a scheduled smoking lapse and instructed to try to remain abstinent for the next 7 days (days 15-21). Poorer cognitive performance (slower correct reaction time on Letter-N-Back task) during abstinence predicted more rapid smoking resumption among those receiving placebo (p=0.038) but not among those receiving varenicline. These data lend further support for the growing recognition that cognitive deficits involving working memory are a core symptom of nicotine withdrawal and a potential target for the development of pharmacological and behavioral treatments.