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Objective We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). Method We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Results Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. Conclusions We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record

Background: Understanding brain function requires knowledge of how one brain region causally influences another. This information is difficult to obtain directly in the human brain, and is instead typically inferred from resting-state fMRI. New method: Here, we demonstrate the safety and scientific promise of a novel and complementary approach: concurrent electrical stimulation and fMRI (es-fMRI) at 3 T in awake neurosurgical patients with implanted depth electrodes. Results: We document the results of safety testing, actual experimental setup, and stimulation parameters, that safely and reliably evoke activation in distal structures through stimulation of amygdala, cingulate, or prefrontal cortex. We compare connectivity inferred from the evoked patterns of activation with that estimated from standard resting-state fMRI in the same patients: while connectivity patterns obtained with each approach are correlated, each method produces unique results. Response patterns were stable over the course of 11 min of es-fMRI runs. Comparison with existing method: es-fMRI in awake humans yields unique information about effective connectivity, complementing resting-state fMRI. Although our stimulations were below the level of inducing any apparent behavioral or perceptual effects, a next step would be to use es-fMRI to modulate task performances. This would reveal the acute network-level changes induced by the stimulation that mediate the behavioral and cognitive effects seen with brain stimulation. Conclusions: es-fMRI provides a novel and safe approach for mapping effective connectivity in the human brain in a clinical setting, and will inform treatments for psychiatric and neurodegenerative disorders that use deep brain stimulation.

Studies of patients with brain damage have highlighted a broad neural network of limbic and prefrontal areas as important for adaptive decision-making. However, some patients with damage outside these regions have impaired decision-making behavior, and the behavioral impairments observed in these cases are often attributed to the general variability in behavior following brain damage, rather than a deficit in a specific brain-behavior relationship. A novel approach, lesion-derived network mapping, uses healthy subject resting-state functional connectivity (RSFC) data to infer the areas that would be connected with each patient's lesion area in healthy adults. Here, we used this approach to investigate whether there was a systematic pattern of connectivity associated with decision-making performance in patients with focal damage in areas not classically associated with decision-making. These patients were categorized a priori into "impaired" or "unimpaired" groups based on their performance on the Iowa Gambling Task (IGT). Lesion-derived network maps based on the impaired patients showed overlap in somatosensory, motor and insula cortices, to a greater extent than patients who showed unimpaired IGT performance. Akin to the classic concept of "diaschisis" (von Monakow, 1914), this focus on the remote effects that focal damage can have on large-scale distributed brain networks has the potential to inform not only differences in decision-making behavior, but also other cognitive functions or neurological syndromes where a distinct phenotype has eluded neuroanatomical classification and brain-behavior relationships appear highly heterogeneous.

There is growing evidence that aerobic exercise protects against age-related cognitive decline and that cardiorespiratory fitness is an important factor for these benefits. Studies also suggest that combining physical activity with cognitive enrichment is beneficial. We further examine these predictions by comparing effects of a nutritional supplement promoting exercise capacity to a lower-intensity activity with cognitive enrichment on functional network and cognitive outcomes that otherwise decline with aging. Inactive healthy older adults were randomized to one of four groups including a low-intensity activity with complex cognitive demands (dancing), walking, walking+supplement, or an active control. Results showed that walking+supplement increased salience network functional connectivity (FC), with less training benefit for default mode network FC. Although cognitive performance did not increase for any training group, participants in the walking+supplement group who were on medication that boosted key neurotransmitters (e.g., selective serotonin reuptake inhibitors) showed improved processing speed. Overall, this study provides new insight into how to boost the protective effects of exercise on brain systems that otherwise deteriorate with aging. NEW & NOTEWORTHY Aerobic exercise effects on brain networks that otherwise decline with aging can be boosted with a nutritional supplement including beta-alanine. Beta-alanine supplementation could enhance the extent to which aerobic adaptations benefit the brain. In contrast, cognitive enrichment with low-intensity physical activity through dance did not affect functional networks. Medications that modulate neurotransmitters affected by aging (e.g., selective serotonin reuptake inhibitors) may modify effects of exercise on cognition.

Studies of individuals with focal brain damage have long been used to expand understanding of the neural basis of psychopathology. However, most previous studies were conducted using small sample sizes and relatively coarse methods for measuring psychopathology or mapping brain-behavior relationships. Here, we examined the factor structure and neural correlates of psychopathology in 232 individuals with focal brain damage, using their responses to the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). Factor analysis and voxel-based lesion symptom mapping were used to examine the structure and neural correlates of psychopathology in this sample. Consistent with existing MMPI-2-RF literature, separate internalizing, externalizing, and psychotic symptom dimensions were found. In addition, a somatic dimension likely reflecting neurological symptoms was identified. Damage to the medial temporal lobe, including the hippocampus, was associated with scales related to both internalizing problems and psychoticism. Damage to the medial temporal lobe and orbitofrontal cortex was associated with both a general distrust of others and beliefs that one is being personally targeted by others. These findings provide evidence for the critical role of dysfunction in specific frontal and temporal regions in the development of psychopathology.

Previous work has provided preliminary indication of sex-related functional asymmetry of the ventromedial prefrontal cortex (vmPFC) in social and emotional functions and complex decision-making. Findings have been inconsistent, and based on small numbers of patients. Given the rarity of these neurological cases, replicable results across studies are important to build evidence for sex-related functional asymmetry of the vmPFC. Here we used a sample of sixteen neurological patients with unilateral damage to the left or right vmPFC and examined differences between men and women on a task that probed decision-making under risk or decision-making under ambiguity. We found that men with right-hemisphere vmPFC damage and women with left-hemisphere vmPFC damage demonstrated significantly reduced aversion to risk and ambiguity. Men with damage to the left vmPFC and women with damage to the right vmPFC showed aversion to risk and ambiguity comparable to participants with left or right-sided brain damage outside the vmPFC, and to comparison participants without brain damage. Our results add to previous findings of sex-related functional asymmetry of the vmPFC in decision-making. Our study also replicates findings of no observable behavioral differences between men and women without neurological damage on tests of decision-making. This pattern of neurobiological divergence but behavioral convergence between men and women may reflect a complex interplay of neuroendocrine, developmental, and psychosocial factors.

Image-based parcellation of the brain often leads to multiple disconnected anatomical structures, which pose significant challenges for analyses of morphological shapes. Existing shape models, such as the widely used spherical harmonic (SPHARM) representation, assume topological invariance, so are unable to simultaneously parameterize multiple disjoint structures. In such a situation, SPHARM has to be applied separately to each individual structure. We present a novel surface parameterization technique using 4D hyperspherical harmonics in representing multiple disjoint objects as a single analytic function, terming it HyperSPHARM. The underlying idea behind Hyper-SPHARM is to stereographically project an entire collection of disjoint 3D objects onto the 4D hypersphere and subsequently simultaneously parameterize them with the 4D hyperspherical harmonics. Hence, HyperSPHARM allows for a holistic treatment of multiple disjoint objects, unlike SPHARM. In an imaging dataset of healthy adult human brains, we apply HyperSPHARM to the hippocampi and amygdalae. The HyperSPHARM representations are employed as a data smoothing technique, while the HyperSPHARM coefficients are utilized in a support vector machine setting for object classification. HyperSPHARM yields nearly identical results as SPHARM, as will be shown in the paper. Its key advantage over SPHARM lies computationally; Hyper-SPHARM possess greater computational efficiency than SPHARM because it can parameterize multiple disjoint structures using much fewer basis functions and stereographic projection obviates SPHARM's burdensome surface flattening. In addition, HyperSPHARM can handle any type of topology, unlike SPHARM, whose analysis is confined to topologically invariant structures.

Functional connectivity, as measured by resting-state fMRI, has proven a powerful method for studying brain systems in the context of behavior, development, and disease states. However, the relationship of functional connectivity to structural connectivity remains unclear. If functional connectivity relies on structural connectivity, then anatomical isolation of a brain region should eliminate functional connectivity with other brain regions. We tested this by measuring functional connectivity of the surgically disconnected temporal pole in resection patients (N=5; mean age 37; 2F, 3M). Functional connectivity was evaluated based on coactivation of whole-brain fMRI data with the average low-frequency BOLD signal from disconnected tissue in each patient. In sharp contrast to our prediction, we observed significant functional connectivity between the disconnected temporal pole and remote brain regions in each disconnection case. These findings raise important questions about the neural bases of functional connectivity measures derived from the fMRI BOLD signal.

Learning to make moral judgements based on considerations beyond self-interest is a fundamental aspect of moral development. A deficit in such learning is associated with poor socialization and criminal behaviour. The neural systems required for the acquisition and maturation of moral competency are not well understood. Here we show in a unique sample of neurological patients that focal lesions involving ventromedial prefrontal cortex, acquired during development, result in an abnormally egocentric pattern of moral judgement. In response to simple hypothetical moral scenarios, the patients were more likely than comparison participants to endorse self-interested actions that involved breaking moral rules or physically harming others in order to benefit themselves. This pattern (which we also found in subjects with psychopathy) differs from that of patients with adult-onset ventromedial prefrontal cortex lesions--the latter group showed normal rejection of egocentric rule violations. This novel contrast of patients with ventromedial prefrontal cortex lesions acquired during development versus during adulthood yields new evidence suggesting that the ventromedial prefrontal cortex is a critical neural substrate for the acquisition and maturation of moral competency that goes beyond self-interest to consider the welfare of others. Disruption to this affective neural system early in life interrupts moral development.

Dysfunction in the prefrontal cortex, amygdala, and hippocampus is believed to underlie the development of much psychopathology. However, to date only limited longitudinal data relate early behavior with neural structure later in life. Our objective was to examine the relationship of early life externalizing behavior with adolescent brain structure. We report here the first longitudinal study linking externalizing behavior during preschool to brain structure during adolescence. We examined the relationship of preschool externalizing behavior with amygdala, hippocampus, and prefrontal cortex volumes at age 15 years in a community sample of 76 adolescents followed longitudinally since their mothers’ pregnancy. A significant gender by externalizing behavior interaction revealed that males—but not females—with greater early childhood externalizing behavior had smaller amygdala volumes at adolescence (t = 2.33, p = .023). No significant results were found for the hippocampus or the prefrontal cortex. Greater early externalizing behavior also related to smaller volume of a cluster including the angular gyrus and tempoparietal junction across genders. Results were not attributable to the impact of preschool anxiety, preschool maternal stress, school-age internalizing or externalizing behaviors, or adolescent substance use. These findings demonstrate a novel, gender-specific relationship between early-childhood externalizing behavior and adolescent amygdala volume, as well as a cross-gender result for the angular gyrus and tempoparietal junction.

The sparse regression framework has been widely used in medical image processing and analysis. However, it has been rarely used in anatomical studies. We present a sparse shape modeling framework using the Laplace-Beltrami (LB) eigenfunctions of the underlying shape and show its improvement of statistical power. Traditionally, the LB-eigenfunctions are used as a basis for intrinsically representing surface shapes as a form of Fourier descriptors. To reduce high frequency noise, only the first few terms are used in the expansion and higher frequency terms are simply thrown away. However, some lower frequency terms may not necessarily contribute significantly in reconstructing the surfaces. Motivated by this idea, we present a LB-based method to filter out only the significant eigenfunctions by imposing a sparse penalty. For dense anatomical data such as deformation fields on a surface mesh, the sparse regression behaves like a smoothing process, which will reduce the error of incorrectly detecting false negatives. Hence the statistical power improves. The sparse shape model is then applied in investigating the influence of age on amygdala and hippocampus shapes in the normal population. The advantage of the LB sparse framework is demonstrated by showing the increased statistical power.

BACKGROUND: Early life stress (ELS) can compromise development, with higher amounts of adversity linked to behavioral problems. To understand this linkage, a growing body of research has examined two brain regions involved with socioemotional functioning—amygdala and hippocampus. Yet empirical studies have reported increases, decreases, and no differences within human and nonhuman animal samples exposed to different forms of ELS. This divergence in findings may stem from methodological factors, nonlinear effects of ELS, or both. METHODS: We completed rigorous hand-tracing of the amygdala and hippocampus in three samples of children who experienced different forms of ELS (i.e., physical abuse, early neglect, or low socioeconomic status). Interviews were also conducted with children and their parents or guardians to collect data about cumulative life stress. The same data were also collected in a fourth sample of comparison children who had not experienced any of these forms of ELS. RESULTS: Smaller amygdala volumes were found for children exposed to these different forms of ELS. Smaller hippocampal volumes were also noted for children who were physically abused or from low socioeconomic status households. Smaller amygdala and hippocampal volumes were also associated with greater cumulative stress exposure and behavioral problems. Hippocampal volumes partially mediated the relationship between ELS and greater behavioral problems. CONCLUSIONS: This study suggests ELS may shape the development of brain areas involved with emotion processing and regulation in similar ways. Differences in the amygdala and hippocampus may be a shared diathesis for later negative outcomes related to ELS.

Here, we describe a novel method for volumetric segmentation of the amygdala from MRI images collected from 35 human subjects. This approach is adapted from open-source techniques employed previously with the hippocampus (Suh et al., 2011; Wang et al., 2011a; Wang et al., 2011b). Using multi-atlas segmentation and machine learning-based correction, we were able to produce automated amygdala segments with high dice (Mean= 0.918 for the left amygdala; 0.916 for the right amygdala) and Jaccard coefficients (Mean= 0.850 for the left; 0.846 for the right) compared to rigorously hand-traced volumes. This automated routine also produced amygdala segments with high intra-class (consistency=.830, absolute agreement =.819 for the left; consistency=. 786, absolute agreement =. 783 for the right) and bivariate (r =.831 for the left; r =0.797 for the right) correlations compared to hand-drawn amygdala. Our results are discussed in relation to results from other cutting-edge segmentation techniques, as well as commonly- available approaches to amygdala segmentation (e.g., Freesurfer). We believe this new technique has broad application to research with large sample sizes for which amygdala quantification might be needed.