Diagnostic Classification of ADHD Versus Control: Support Vector Machine Classification Using Brief Neuropsychological Assessment.

Objective: Common methods for clinical diagnosis include clinical interview, behavioral questionnaires, and neuropsychological assessment. These methods rely on clinical interpretation and have variable reliability, sensitivity, and specificity. The goal of this study was to evaluate the utility of machine learning in the prediction and classification of children with ADHD-Combined presentation (ADHD-C) using brief neuropsychological measures (d2 Test of Attention, Children with ADHD-C and typically developing control children completed semi-structured clinical interviews and measures of attention/concentration and parents completed symptom severity questionnaires. Method: We used a forward feature selection method to identify the most informative neuropsychological features for support vector machine (SVM) classification and a decision tree model to derive a rule-based model. Results: The SVM model yielded excellent classification accuracy (100%) of individual children with and without ADHD (1.0). Decision tree algorithms identified individuals with and without ADHD-C with 100% sensitivity and specificity. Conclusion:This study observed highly accurate statistical diagnostic classification, at the individual level, in a sample of children with ADHD-C. The findings suggest data-driven behavioral algorithms based on brief neuropsychological data may present an efficient and accurate diagnostic tool for clinicians.

Using electromagnetic articulography with a tongue lateral sensor to discriminate manner of articulation.

This study examined the contributions of the tongue tip (TT), tongue body (TB), and tongue lateral (TL) sensors in the electromagnetic articulography (EMA) measurement of American English alveolar consonants. Thirteen adults produced /ɹ/, /l/, /z/, and /d/ in /ɑCɑ/ syllables while being recorded with an EMA system. According to statistical analysis of sensor movement and the results of a machine classification experiment, the TT sensor contributed most to consonant differences, followed by TB. The TL sensor played a complementary role, particularly for distinguishing /z/.

An integrated feature ranking and selection framework for ADHD characterization.

Today, diagnosis of attention deficit hyperactivity disorder (ADHD) still primarily relies on a series of subjective evaluations that highly rely on a doctor's experiences and intuitions from diagnostic interviews and observed behavior measures. An accurate and objective diagnosis of ADHD is still a challenge and leaves much to be desired. Many children and adults are inappropriately labeled with ADHD conditions, whereas many are left undiagnosed and untreated. Recent advances in neuroimaging studies have enabled us to search for both structural (e.g., cortical thickness, brain volume) and functional (functional connectivity) abnormalities that can potentially be used as new biomarkers of ADHD. However, structural and functional characteristics of neuroimaging data, especially magnetic resonance imaging (MRI), usually generate a large number of features. With a limited sample size, traditional machine learning techniques can be problematic to discover the true characteristic features of ADHD due to the significant issues of overfitting, computational burden, and interpretability of the model. There is an urgent need of efficient approaches to identify meaningful discriminative variables from a higher dimensional feature space when sample size is small compared with the number of features. To tackle this problem, this paper proposes a novel integrated feature ranking and selection framework that utilizes normalized brain cortical thickness features extracted from MRI data to discriminate ADHD subjects against healthy controls. The proposed framework combines information theoretic criteria and the least absolute shrinkage and selection operator (Lasso) method into a two-step feature selection process which is capable of selecting a sparse model while preserving the most informative features. The experimental results showed that the proposed framework generated the highest/comparable ADHD prediction accuracy compared with the state-of-the-art feature selection approaches with minimum number of features in the final model. The selected regions of interest in our model were consistent with recent brain-behavior studies of ADHD development, and thus confirmed the validity of the selected features by the proposed approach.

The neural circuits recruited for the production of signs and fingerspelled words.

Signing differs from typical non-linguistic hand actions because movements are not visually guided, finger movements are complex (particularly for fingerspelling), and signs are not produced as holistic gestures. We used positron emission tomography to investigate the neural circuits involved in the production of American Sign Language (ASL). Different types of signs (one-handed (articulated in neutral space), two-handed (neutral space), and one-handed body-anchored signs) were elicited by asking deaf native signers to produce sign translations of English words. Participants also fingerspelled (one-handed) printed English words. For the baseline task, participants indicated whether a word contained a descending letter. Fingerspelling engaged ipsilateral motor cortex and cerebellar cortex in contrast to both one-handed signs and the descender baseline task, which may reflect greater timing demands and complexity of handshape sequences required for fingerspelling. Greater activation in the visual word form area was also observed for fingerspelled words compared to one-handed signs. Body-anchored signs engaged bilateral superior parietal cortex to a greater extent than the descender baseline task and neutral space signs, reflecting the motor control and proprioceptive monitoring required to direct the hand toward a specific location on the body. Less activation in parts of the motor circuit was observed for two-handed signs compared to one-handed signs, possibly because, for half of the signs, handshape and movement goals were spread across the two limbs. Finally, the conjunction analysis comparing each sign type with the descender baseline task revealed common activation in the supramarginal gyrus bilaterally, which we interpret as reflecting phonological retrieval and encoding processes.

Effects of Anxiety on Caloric Intake and Satiety-Related Brain Activation in Women and Men.

OBJECTIVE: To test the relationship of anxiety to caloric intake and food cue perception in women and men. METHODS: Fifty-five twins (26 complete, 3 incomplete pairs; 51% women) underwent 2 functional magnetic resonance imaging (fMRI) scans (before and after a standardized meal) and then ate at an ad libitum buffet to objectively assess food intake. State and trait anxiety were assessed using the State-Trait Anxiety Inventory. During the fMRI scans, participants viewed blocks of fattening and nonfattening food images, and nonfood objects. RESULTS: In women, higher trait anxiety was associated with a higher body mass index (BMI) (r = 0.40, p = .010). Trait anxiety was positively associated with kilocalories consumed at the buffet (r = 0.53, p = .005) and percent kilocalories consumed from fat (r = 0.30, p = .006), adjusted for BMI. In within-pair models, which control for shared familial and genetic factors, higher trait anxiety remained associated with kilocalories consumed at the buffet (p = .66, p = .014), but not with BMI. In men, higher state anxiety was related to macronutrient choices, but not to total caloric intake or BMI. FMRI results revealed that women with high trait anxiety did not suppress activation by fattening food cues across brain regions associated with satiety perception after eating a standardized meal (low anxiety, mean difference = -15.4, p < .001; high anxiety, mean difference = -1.53, p = .82, adjusted for BMI). CONCLUSIONS: In women, trait anxiety may promote excess caloric consumption through altered perception of high-calorie environmental food cues, placing women with genetic predispositions toward weight gain at risk of obesity. TRIAL REGISTRATION: Clinicaltrials.govidentifier:NCT02483663.

Brain regulation of appetite in twins.

BACKGROUND: Neural responses to highly energetic food cues are robust and are suppressed by eating. It is not known if neural responsiveness to food cues is an inherited trait and possibly even one that mediates the genetic influences on body weight that have been previously observed. OBJECTIVE: We investigated the inherited influence on brain responses to high-calorie visual food cues before and after a meal. DESIGN: With the use of a monozygotic twin study design, 21 healthy monozygotic twin pairs consumed a standardized breakfast and, 3.5 h later, underwent the first of 2 functional MRI (fMRI) scans with the use of visual food cues. After the first fMRI session, twins consumed a standardized meal, which was followed by the second fMRI. Serial ratings of appetite and food appeal were obtained. An ad libitum buffet was used to measure total caloric and macronutrient intakes. Intraclass correlations (ICCs) were used to test for inherited influences by comparing whether intrapair similarity was greater than interpair similarity. RESULTS: Body mass index was highly correlated within twin pairs (ICC: 0.96; P < 0.0001). ICCs also showed a strong intrapair similarity for the meal-induced change in hunger (ICC: 0.41; P = 0.03), fullness (ICC: 0.39; P = 0.04), and the appeal of fattening food (ICC: 0.57; P < 0.001). Twins ate a similar number of kilocalories at the buffet (ICC: 0.43; P = 0.02). Before the meal, the global brain activation across regions involved in satiety processing was not more similar in twins than in unrelated individuals. However, significant ICCs were present after the meal (ICC: 0.39; P = 0.04) and for the meal-induced change in activation by high-calorie visual food cues (ICC: 0.52; P < 0.01). CONCLUSION: Inherited factors influence both satiety perception and the effect of a meal to alter regional brain responses to images of highly energetic food. This trial was registered at clinicaltrials.gov as NCT02483663.

Segregation of anterior temporal regions critical for retrieving names of unique and non-unique entities reflects underlying long-range connectivity.

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category-specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus (UNC) was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus (ILF) was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing and semantic hub sectors.

Visual Feedback of Tongue Movement for Novel Speech Sound Learning.

Pronunciation training studies have yielded important information concerning the processing of audiovisual (AV) information. Second language (L2) learners show increased reliance on bottom-up, multimodal input for speech perception (compared to monolingual individuals). However, little is known about the role of viewing one's own speech articulation processes during speech training. The current study investigated whether real-time, visual feedback for tongue movement can improve a speaker's learning of non-native speech sounds. An interactive 3D tongue visualization system based on electromagnetic articulography (EMA) was used in a speech training experiment. Native speakers of American English produced a novel speech sound (/ɖ/; a voiced, coronal, palatal stop) before, during, and after trials in which they viewed their own speech movements using the 3D model. Talkers' productions were evaluated using kinematic (tongue-tip spatial positioning) and acoustic (burst spectra) measures. The results indicated a rapid gain in accuracy associated with visual feedback training. The findings are discussed with respect to neural models for multimodal speech processing.

Anatomically informed metrics for connectivity-based cortical parcellation from diffusion MRI.

Connectivity information derived from diffusion MRI can be used to parcellate the cerebral cortex into anatomically and functionally meaningful subdivisions. Acquisition and processing parameters can significantly affect parcellation results, and there is no consensus on best practice protocols. We propose a novel approach for evaluating parcellation based on measuring the degree to which parcellation conforms to known principles of brain organization, specifically cortical field homogeneity and interhemispheric homology. The proposed metrics are well behaved on morphologically generated whole-brain parcels, where they correctly identify contralateral homologies and give higher scores to anatomically versus arbitrarily generated parcellations. The measures show that individual cortical fields have characteristic connectivity profiles that are compact and separable, and that the topological arrangement of such fields is strongly conserved between hemispheres and individuals. The proposed metrics can be used to evaluate the quality of parcellations at the subject and group levels and to improve acquisition and data processing for connectivity-based cortical parcellation.

What affects detectability of lesion-deficit relationships in lesion studies?

Elucidating the brain basis for psychological processes and behavior is a fundamental aim of cognitive neuroscience. The lesion method, using voxel-based statistical analysis, is an important approach to this goal, identifying neural structures that are necessary for the support of specific mental operations, and complementing the strengths of functional imaging techniques. Lesion coverage in a population is by nature spatially heterogeneous and biased, systematically affecting the ability of lesion-deficit correlation methods to detect and localize functional associations. We have developed a simulator that allows investigators to model parameters in a lesion-deficit study and characterize the statistical bias in lesion deficit detection coverage that will result from specific assumptions. We used the simulator to assess the signal detection properties and localization accuracy of standard lesion-deficit correlation methods, under a simple truth model - that a critical region of interest (CR), when damaged, gives rise to a deficit. We considered voxel-based lesion-symptom mapping (VLSM) and proportional MAP-3 (PM3). Using regression analysis, we examined if the pattern of outcome statistics can be explained by simulation parameters, factors that are inherent to anatomic parcels, and lesion coverage of the population, which consisted of a representative sample of 351 subjects drawn from the Iowa Patient Registry. We examined the effect of using nonparametric versus parametric statistics to obtain thresholded maps and the effect of correcting for multiple comparisons using false discovery rate or cluster-based correction. Our results, which are derived from samples of realistic lesions, indicate that even a simple truth model yields localization errors that are systematic and pervasive, averaging 2 cm in the standard anatomic space, and tending to be directed towards areas of greater anatomic coverage. This displacement positions the center of mass of the detected region in a different anatomical region 87% of the time. This basic result is not affected by the choice of PM3 vs VLSM as the fundamental approach, nor is localization error ameliorated by incorporation of lesion size as a covariate in the VLSM approach, or by data distribution-driven approaches to controlling multiple spatial comparisons (false discovery rate or cluster-based correction approaches). Our simulations offer a quantitative basis for interpreting lesion studies in cognitive neuroscience. We suggest ways in which lesion simulation and analysis frameworks could be productively extended.

Phase I/II randomized trial of aerobic exercise in Parkinson disease in a community setting.

OBJECTIVES: To (1) investigate effects of aerobic walking on motor function, cognition, and quality of life in Parkinson disease (PD), and (2) compare safety, tolerability, and fitness benefits of different forms of exercise intervention: continuous/moderate intensity vs interval/alternating between low and vigorous intensity, and individual/neighborhood vs group/facility setting. METHODS: Initial design was a 6-month, 2 × 2 randomized trial of different exercise regimens in independently ambulatory patients with PD. All arms were required to exercise 3 times per week, 45 minutes per session. RESULTS: Randomization to group/facility setting was not feasible because of logistical factors. Over the first 2 years, we randomized 43 participants to continuous or interval training. Because preliminary analyses suggested higher musculoskeletal adverse events in the interval group and lack of difference between training methods in improving fitness, the next 17 participants were allocated only to continuous training. Eighty-one percent of 60 participants completed the study with a mean attendance of 83.3% (95% confidence interval: 77.5%-89.0%), exercising at 46.8% (44.0%-49.7%) of their heart rate reserve. There were no serious adverse events. Across all completers, we observed improvements in maximum oxygen consumption, gait speed, Unified Parkinson's Disease Rating Scale sections I and III scores (particularly axial functions and rigidity), fatigue, depression, quality of life (e.g., psychological outlook), and flanker task scores (p < 0.05 to p < 0.001). Increase in maximum oxygen consumption correlated with improvements on the flanker task and quality of life (p < 0.05). CONCLUSIONS: Our preliminary study suggests that aerobic walking in a community setting is safe, well tolerated, and improves aerobic fitness, motor function, fatigue, mood, executive control, and quality of life in mild to moderate PD. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that in patients with PD, an aerobic exercise program improves aerobic fitness, motor function, fatigue, mood, and cognition.

How sensory-motor systems impact the neural organization for language: direct contrasts between spoken and signed language.

To investigate the impact of sensory-motor systems on the neural organization for language, we conducted an H2 (15)O-PET study of sign and spoken word production (picture-naming) and an fMRI study of sign and audio-visual spoken language comprehension (detection of a semantically anomalous sentence) with hearing bilinguals who are native users of American Sign Language (ASL) and English. Directly contrasting speech and sign production revealed greater activation in bilateral parietal cortex for signing, while speaking resulted in greater activation in bilateral superior temporal cortex (STC) and right frontal cortex, likely reflecting auditory feedback control. Surprisingly, the language production contrast revealed a relative increase in activation in bilateral occipital cortex for speaking. We speculate that greater activation in visual cortex for speaking may actually reflect cortical attenuation when signing, which functions to distinguish self-produced from externally generated visual input. Directly contrasting speech and sign comprehension revealed greater activation in bilateral STC for speech and greater activation in bilateral occipital-temporal cortex for sign. Sign comprehension, like sign production, engaged bilateral parietal cortex to a greater extent than spoken language. We hypothesize that posterior parietal activation in part reflects processing related to spatial classifier constructions in ASL and that anterior parietal activation may reflect covert imitation that functions as a predictive model during sign comprehension. The conjunction analysis for comprehension revealed that both speech and sign bilaterally engaged the inferior frontal gyrus (with more extensive activation on the left) and the superior temporal sulcus, suggesting an invariant bilateral perisylvian language system. We conclude that surface level differences between sign and spoken languages should not be dismissed and are critical for understanding the neurobiology of language.

Voxel selection framework in multi-voxel pattern analysis of FMRI data for prediction of neural response to visual stimuli.

Multi-voxel pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data is an emerging approach for probing the neural correlates of cognition. MVPA allows cognitive states to be modeled as distributed patterns of neural activity and classified according to stimulus conditions. In practice, building a robust, generalizable classification model can be challenging because the number of voxels (features) far exceeds the number of stimulus instances/data observations. To avoid model overfitting, there is a need to select informative voxels before building a classification model. In this paper, we propose a robust feature (voxel) selection framework using mutual information (MI) and partial least square regression (PLS) to establish an informativeness index for prioritizing selection of voxels based on the degree of their association to the experimental conditions. We evaluated the robustness of our proposed framework by assessing performance of standard classification algorithms, when combined with our feature selection approach, in a publicly-available fMRI dataset of object-level representation widely used to benchmark MVPA performance (Haxby, 2001). The computational results suggest that our feature selection framework based on MI and PLS drastically improves the classification accuracy relative to those previously reported in the literature. Our results also suggest that highly informative voxels may provide meaningful insight into the functional-anatomic relationship of brain activity and stimulus conditions.

An epidural blood patch causing acute neurologic dysfunction necessitating a decompressive laminectomy.

OBJECTIVES: One risk with placement of an epidural blood patch (EDBP) is spinal cord or nerve root compression resulting from the epidural blood volume injected, a complication necessitating immediate surgical decompression. We could not find a previous report of this in the literature. Here, we review and discuss one such case. CASE REPORT: A patient was treated with 2 EDBPs for a presumptive cerebrospinal fluid leak 3 weeks after an epidural steroid injection. The second EDBP was performed under direct fluoroscopic guidance, yet resulted in spinal cord compression with radiologic evidence of an epidural hematoma. The patient developed acute cauda equina syndrome and required an emergent decompressive laminectomy resulting in partial resolution of neurological symptoms. One year after the procedure, the patient has recovered most of her motor function but with some persistent numbness below the left knee and a left foot drop. CONCLUSIONS: A cauda equina syndrome from an epidural hematoma may occur as a rare complication of an EDBP, even with direct fluoroscopic guidance. Early diagnosis of symptoms and prompt surgical evacuation of an epidural hematoma is essential and may result in the resolution of symptoms. This complication remains a rare occurrence and should not deter the performance of an EDBP, when indicated.

Homology and topology based metrics for evaluating cortical parcellations generated using diffusion MRI.

When using diffusion MRI for segmenting the cerebral cortex, the modality of information used and workflow procedural factors can have significant effects on the resulting parcellation. There is as yet no consensus on best practice processing protocols, and no ground truth is available in vivo. Converging indirect evidence has been used to compare parcellation outcomes, including: (1) comparison of cortical parcellations based on different modalities; (2) reproducibility across independent acquisitions; (3) consistency across modality or subject; and (4) the extent to which the segmented regions are functionally distinct based on task or rsfMRI data. To these we add an additional strategy wherein parcellation results are assessed based on known organizational principles of the brain, specifically inter-hemispheric homology and topology, thereby permitting assessment of results per subject independently of another imaging modality or acquisition. We propose these measures to guide improvements in acquisition, reconstruction, and/or clustering approaches during the process of diffusion MRI parcellation.

Patient injuries from anesthesia gas delivery equipment: a closed claims update.

BACKGROUND: Improvements in anesthesia gas delivery equipment and provider training may increase patient safety. The authors analyzed patient injuries related to gas delivery equipment claims from the American Society of Anesthesiologists Closed Claims Project database over the decades from 1970s to the 2000s. METHODS: After the Institutional Review Board approval, the authors reviewed the Closed Claims Project database of 9,806 total claims. Inclusion criteria were general anesthesia for surgical or obstetric anesthesia care (n = 6,022). Anesthesia gas delivery equipment was defined as any device used to convey gas to or from (but not involving) the airway management device. Claims related to anesthesia gas delivery equipment were compared between time periods by chi-square test, Fisher exact test, and Mann-Whitney U test. RESULTS: Anesthesia gas delivery claims decreased over the decades (P < 0.001) to 1% of claims in the 2000s. Outcomes in claims from 1990 to 2011 (n = 40) were less severe, with a greater proportion of awareness (n = 9, 23%; P = 0.003) and pneumothorax (n = 7, 18%; P = 0.047). Severe injuries (death/permanent brain damage) occurred in supplemental oxygen supply events outside the operating room, breathing circuit events, or ventilator mishaps. The majority (85%) of claims involved provider error with (n = 7) or without (n = 27) equipment failure. Thirty-five percent of claims were judged as preventable by preanesthesia machine check. CONCLUSIONS: Gas delivery equipment claims in the Closed Claims Project database decreased in 1990-2011 compared with earlier decades. Provider error contributed to severe injury, especially with inadequate alarms, improvised oxygen delivery systems, and misdiagnosis or treatment of breathing circuit events.

Operating room fires: a closed claims analysis.

BACKGROUND: To assess patterns of injury and liability associated with operating room (OR) fires, closed malpractice claims in the American Society of Anesthesiologists Closed Claims Database since 1985 were reviewed. METHODS: All claims related to fires in the OR were compared with nonfire-related surgical anesthesia claims. An analysis of fire-related claims was performed to identify causative factors. RESULTS: There were 103 OR fire claims (1.9% of 5,297 surgical claims). Electrocautery was the ignition source in 90% of fire claims. OR fire claims more frequently involved older outpatients compared with other surgical anesthesia claims (P < 0.01). Payments to patients were more often made in fire claims (P < 0.01), but payment amounts were lower (median $120,166) compared to nonfire surgical claims (median $250,000, P < 0.01). Electrocautery-induced fires (n = 93) increased over time (P < 0.01) to 4.4% claims between 2000 and 2009. Most (85%) electrocautery fires occurred during head, neck, or upper chest procedures (high-fire-risk procedures). Oxygen served as the oxidizer in 95% of electrocautery-induced OR fires (84% with open delivery system). Most electrocautery-induced fires (n = 75, 81%) occurred during monitored anesthesia care. Oxygen was administered via an open delivery system in all high-risk procedures during monitored anesthesia care. In contrast, alcohol-containing prep solutions and volatile compounds were present in only 15% of OR fires during monitored anesthesia care. CONCLUSIONS: Electrocautery-induced fires during monitored anesthesia care were the most common cause of OR fires claims. Recognition of the fire triad (oxidizer, fuel, and ignition source), particularly the critical role of supplemental oxygen by an open delivery system during use of the electrocautery, is crucial to prevent OR fires. Continuing education and communication among OR personnel along with fire prevention protocols in high-fire-risk procedures may reduce the occurrence of OR fires.

The biology of linguistic expression impacts neural correlates for spatial language.

Biological differences between signed and spoken languages may be most evident in the expression of spatial information. PET was used to investigate the neural substrates supporting the production of spatial language in American Sign Language as expressed by classifier constructions, in which handshape indicates object type and the location/motion of the hand iconically depicts the location/motion of a referent object. Deaf native signers performed a picture description task in which they overtly named objects or produced classifier constructions that varied in location, motion, or object type. In contrast to the expression of location and motion, the production of both lexical signs and object type classifier morphemes engaged left inferior frontal cortex and left inferior temporal cortex, supporting the hypothesis that unlike the location and motion components of a classifier construction, classifier handshapes are categorical morphemes that are retrieved via left hemisphere language regions. In addition, lexical signs engaged the anterior temporal lobes to a greater extent than classifier constructions, which we suggest reflects increased semantic processing required to name individual objects compared with simply indicating the type of object. Both location and motion classifier constructions engaged bilateral superior parietal cortex, with some evidence that the expression of static locations differentially engaged the left intraparietal sulcus. We argue that bilateral parietal activation reflects the biological underpinnings of sign language. To express spatial information, signers must transform visual-spatial representations into a body-centered reference frame and reach toward target locations within signing space.

Regional brain response to visual food cues is a marker of satiety that predicts food choice.

BACKGROUND: Neuronal processes that underlie the subjective experience of satiety after a meal are not well defined. OBJECTIVE: We investigated how satiety alters the perception of and neural response to visual food cues. DESIGN: Normal-weight participants (10 men, 13 women) underwent 2 fMRI scans while viewing images of high-calorie food that was previously rated as incompatible with weight loss and "fattening" and low-calorie, "nonfattening" food. After a fasting fMRI scan, participants ate a standardized breakfast and underwent reimaging at a randomly assigned time 15-300 min after breakfast to vary the degree of satiety. Measures of subjective appetite, food appeal, and ad libitum food intake (measured after the second fMRI scan) were correlated with activation by "fattening" (compared with "nonfattening") food cues in a priori regions of interest. RESULTS: Greater hunger correlated with higher appeal ratings of "fattening" (r = 0.46, P = 0.03) but not "nonfattening" (r = -0.20, P = 0.37) foods. Fasting amygdalar activation was negatively associated with fullness (left: r = -0.52; right: r = -0.58; both P ≤ 0.01), whereas postbreakfast fullness was positively correlated with activation in the dorsal striatum (right: r = 0.44; left: r = 0.45; both P < 0.05). After breakfast, participants with greater activation in 4 regions-medial orbital frontal cortex (r = 0.49, P < 0.05), left amygdala (r = 0.49, P < 0.05), left insula (r = 0.47, P < 0.05), and nucleus accumbens (right: r = 0.57, P < 0.01; left: r = 0.43, P < 0.05)-chose buffet foods with higher fat content. CONCLUSIONS: Postmeal satiety is shown in regional brain activation by images of high-calorie foods. Regions including the amygdala, nucleus accumbens, and dorsal striatum may alter perception of, and reduce motivation to consume, energy-rich foods, ultimately driving food choice. This trial was registered at clinicaltrials.gov as NCT01631045.

Changes in cortical morphology resulting from long-term amygdala damage.

The amygdala's contribution to emotion, cognition and behavior depends on its interactions with subcortical and cortical regions. Amygdala lesions result in altered functional activity in connected regions, but it is not known whether there might be long-term structural sequelae as well. We hypothesized that developmental bilateral amygdala lesions would be associated with specific gray matter morphometric abnormalities in the ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC) and the ventral visual stream. We conducted regions of interest and vertex-based analyses of structural MRI data acquired in two patients with long-standing focal bilateral amygdala lesions (S.M. and A.P.), compared to gender- and age-matched healthy comparison subjects. Both patients showed significant proportional increases in gray matter volume of the vmPFC. Cortical thickness was increased in the vmPFC and ACC and decreased in the ventral visual stream. There were no morphometric changes in dorsolateral prefrontal cortex or dorsal visual stream cortices. These findings support the hypothesis that cortical regions strongly connected with the amygdala undergo morphometric changes with long-standing amygdala damage. This is the first evidence in humans of the remote alteration of brain morphology in association with amygdala lesions, and will help in interpreting the structural and functional consequences of amygdala pathology in neuropsychiatric disorders.