Closed-loop stimulation in periods with less epileptiform activity drives improved epilepsy outcomes.

In patients with drug-resistant epilepsy, electrical stimulation of the brain in response to epileptiform activity can make seizures less frequent and debilitating. This therapy, known as closed-loop responsive neurostimulation (RNS), aims to directly halt seizure activity via targeted stimulation of a burgeoning seizure. Rather than immediately stopping seizures as they start, many RNS implants produce slower, long-lasting changes in brain dynamics that better predict clinical outcomes. Here we hypothesize that stimulation during brain states with less epileptiform activity drives long-term changes that restore healthy brain networks. To test this, we quantified stimulation episodes during low- and high-risk brain states-that is, stimulation during periods with a lower or higher risk of generating epileptiform activity-in a cohort of 40 patients treated with RNS. More frequent stimulation in tonic low-risk states and out of rhythmic high-risk states predicted seizure reduction. Additionally, stimulation events were more likely to be phase-locked to prolonged episodes of abnormal activity for intermediate and poor responders when compared to super-responders, consistent with the hypothesis that improved outcomes are driven by stimulation during low-risk states. These results support the hypothesis that stimulation during low-risk periods might underlie the mechanisms of RNS, suggesting a relationship between temporal patterns of neuromodulation and plasticity that facilitates long-term seizure reduction.

A Fluid Self-Concept: How the Brain Maintains Coherence and Positivity across an Interconnected Self-Concept While Incorporating Social Feedback.

People experience instances of social feedback as interdependent with potential implications for their entire self-concept. How do people maintain positivity and coherence across the self-concept while updating self-views from feedback? We present a network model describing how the brain represents the semantic dependency relations among traits and uses this information to avoid an overall loss of positivity and coherence. Both male and female human participants received social feedback during a self-evaluation task while undergoing functional magnetic resonance imaging. We modeled self-belief updating by incorporating a reinforcement learning model within the network structure. Participants learned more rapidly from positive than negative feedback and were less likely to change self-views for traits with more dependencies in the network. Further, participants back propagated feedback across network relations while retrieving prior feedback on the basis of network similarity to inform ongoing self-views. Activation in ventromedial prefrontal cortex (vmPFC) reflected the constrained updating process such that positive feedback led to higher activation and negative feedback to less activation for traits with more dependencies. Additionally, vmPFC was associated with the novelty of a trait relative to previously self-evaluated traits in the network, and angular gyrus was associated with greater certainty for self-beliefs given the relevance of prior feedback. We propose that neural computations that selectively enhance or attenuate social feedback and retrieve past relevant experiences to guide ongoing self-evaluations may support an overall positive and coherent self-concept.SIGNIFICANCE STATEMENT We humans experience social feedback throughout our lives, but we do not dispassionately incorporate feedback into our self-concept. The implications of feedback for our entire self-concept plays a role in how we either change or retain our prior self-beliefs. In a neuroimaging study, we find that people are less likely to change their beliefs from feedback when the feedback has broader implications for the self-concept. This resistance to change is reflected in processing in the ventromedial prefrontal cortex, a region that is central to self-referential and social cognition. These results are broadly applicable given the role that maintaining a positive and coherent self-concept plays in promoting mental health and development throughout the lifespan.

Circadian changes in aperiodic activity are correlated with seizure reduction in patients with mesial temporal lobe epilepsy treated with responsive neurostimulation.

OBJECTIVES: Responsive neurostimulation (RNS) is an established therapy for drug-resistant epilepsy that delivers direct electrical brain stimulation in response to detected epileptiform activity. However, despite an overall reduction in seizure frequency, clinical outcomes are variable, and few patients become seizure-free. The aim of this retrospective study was to evaluate aperiodic electrophysiological activity, associated with excitation/inhibition balance, as a novel electrographic biomarker of seizure reduction to aid early prognostication of the clinical response to RNS. METHODS: We identified patients with intractable mesial temporal lobe epilepsy who were implanted with the RNS System between 2015 and 2021 at the University of Utah. We parameterized the neural power spectra from intracranial RNS System recordings during the first 3 months following implantation into aperiodic and periodic components. We then correlated circadian changes in aperiodic and periodic parameters of baseline neural recordings with seizure reduction at the most recent follow-up. RESULTS: Seizure reduction was correlated significantly with a patient's average change in the day/night aperiodic exponent (r = .50, p = .016, n = 23 patients) and oscillatory alpha power (r = .45, p = .042, n = 23 patients) across patients for baseline neural recordings. The aperiodic exponent reached its maximum during nighttime hours (12 a.m. to 6 a.m.) for most responders (i.e., patients with at least a 50% reduction in seizures). SIGNIFICANCE: These findings suggest that circadian modulation of baseline broadband activity is a biomarker of response to RNS early during therapy. This marker has the potential to identify patients who are likely to respond to mesial temporal RNS. Furthermore, we propose that less day/night modulation of the aperiodic exponent may be related to dysfunction in excitation/inhibition balance and its interconnected role in epilepsy, sleep, and memory.

Changes in pupil size track self-control failure.

People are more likely to perform poorly on a self-control task following a previous task requiring self-control (ego-depletion), but the mechanism for this effect remains unclear. We used pupillometry to test the role of attentional effort in ego-depletion. We hypothesized that an elevated pupil diameter (PD)-a common physiological measure of effort-during an initial task requiring self-control should be negatively associated with performance on a subsequent control task. To test this hypothesis, participants were first assigned to either a high- or low-demand attention task (manipulation; a standard ego-depletion paradigm), after which all participants completed the same Stroop task. We then separately extracted both sustained (low-frequency) and phasic (high-frequency) changes in PD from both tasks to evaluate possible associations with lapses of cognitive control on the Stroop task. We first show that in the initial task, sustained PD was larger among participants who were assigned to the demanding attention condition. Furthermore, ego-depletion effects were serially mediated by PD: an elevated PD response emerged rapidly among the experimental group during the manipulation, persisted as an elevated baseline response during the Stroop task, and predicted worse accuracy on incongruent trials, revealing a potential indirect pathway to ego-depletion via sustained attention. Secondary analyses revealed another, independent and direct pathway via high levels of transient attentional control: participants who exhibited large phasic responses during the manipulation tended to perform worse on the subsequent Stroop task. We conclude by exploring the neuroscientific implications of these results within the context of current theories of self-control.

Australian sexually transmitted infection (STI) management guidelines for use in primary care 2022 update.

The 'Australian Sexually Transmitted Infection (STI) Management Guidelines For Use In Primary Care' (www.sti.guidelines.org.au ) provide evidence-based, up-to-date guidance targeted at use in primary care settings. A major review of the guidelines was undertaken in 2020-22. All content was reviewed and updated by a multi-disciplinary group of clinical and non-clinical experts, and assessed for appropriateness of recommendations for key affected populations and organisational and jurisdictional suitability. The guidelines are divided into six main sections: (1) standard asymptomatic check-up; (2) sexual history; (3) contact tracing; (4) STIs and infections associated with sex; (5) STI syndromes; and (6) populations and situations. This paper highlights important aspects of the guidelines and provides the rationale for significant changes made during this major review process.

Bidirectional Associations Between Physical Activity and Pain Among Older Adults: An Ecological Momentary Assessment Study.

This paper examines the within-day, bidirectional associations between physical activity and self-reported pain among older adults. Older adults (N = 104; range: 60-98 years) participated in a 10-day Ecological Momentary Assessment (EMA) study. Participants received six EMA prompts/day with a single item assessing pain. Participants wore an activPAL monitor measuring step counts. At the within-person level, on occasions when participants took more steps than usual in the 30 min before the EMA prompt, they were more likely to experience pain at the prompt (ß^02=0.0003, p < .03). At the between-person level, greater step counts in the 30 min before the EMA prompt, on average, were associated with less pain on occasions when pain was experienced (ß^01=-0.0005, p < .04). Pain was not related to subsequent stepping. Bidirectional associations between physical activity and pain were not documented, but physical activity did appear to be related to subsequent pain.

Site-Specific Conjugation Quantitation of a Cysteine-Conjugated Antibody-Drug Conjugate Using Stable Isotope Labeling Peptide Mapping LC-MS/MS Analysis.

Drug-load (DL) characterization of antibody-drug conjugates (ADCs) is an important analytical task due to its designation as a critical quality attribute (CQA) affecting potency and stability. Intact and subunit liquid chromatography-mass spectrometry (LC-MS) analyses can determine global drug-to-antibody ratios (DARs) that correlate well with other orthogonal analytical methods; however, peptide mapping liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis has struggled to provide complementary site-specific quantitation of drug conjugation sites. The peptide mapping method described herein utilizes stable isotope labeling to accurately quantitate the site-specific conjugation levels of a cysteine-conjugated ADC to provide "bottom-up" DAR characterization in parallel with protein sequence and post-translational modification (PTM) characterization in one multi-attribute analytical method (MAM).

Learning About the Self: Motives for Coherence and Positivity Constrain Learning From Self-Relevant Social Feedback.

People learn about themselves from social feedback, but desires for coherence and positivity constrain how feedback is incorporated into the self-concept. We developed a network-based model of the self-concept and embedded it in a reinforcement-learning framework to provide a computational account of how motivations shape self-learning from feedback. Participants (N = 46 adult university students) received feedback while evaluating themselves on traits drawn from a causal network of trait semantics. Network-defined communities were assigned different likelihoods of positive feedback. Participants learned from positive feedback but dismissed negative feedback, as reflected by asymmetries in computational parameters that represent the incorporation of positive versus negative outcomes. Furthermore, participants were constrained in how they incorporated feedback: Self-evaluations changed less for traits that have more implications and are thus more important to the coherence of the network. We provide a computational explanation of how motives for coherence and positivity jointly constrain learning about the self from feedback, an explanation that makes testable predictions for future clinical research.

Patient-specific structural connectivity informs outcomes of responsive neurostimulation for temporal lobe epilepsy.

OBJECTIVE: Responsive neurostimulation is an effective therapy for patients with refractory mesial temporal lobe epilepsy. However, clinical outcomes are variable, few patients become seizure-free, and the optimal stimulation location is currently undefined. The aim of this study was to quantify responsive neurostimulation in the mesial temporal lobe, identify stimulation-dependent networks associated with seizure reduction, and determine if stimulation location or stimulation-dependent networks inform outcomes. METHODS: We modeled patient-specific volumes of tissue activated and created probabilistic stimulation maps of local regions of stimulation across a retrospective cohort of 22 patients with mesial temporal lobe epilepsy. We then mapped the network stimulation effects by seeding tractography from the volume of tissue activated with both patient-specific and normative diffusion-weighted imaging. We identified networks associated with seizure reduction across patients using the patient-specific tractography maps and then predicted seizure reduction across the cohort. RESULTS: Patient-specific stimulation-dependent connectivity was correlated with responsive neurostimulation effectiveness after cross-validation (p = .03); however, normative connectivity derived from healthy subjects was not (p = .44). Increased connectivity from the volume of tissue activated to the medial prefrontal cortex, cingulate cortex, and precuneus was associated with greater seizure reduction. SIGNIFICANCE: Overall, our results suggest that the therapeutic effect of responsive neurostimulation may be mediated by specific networks connected to the volume of tissue activated. In addition, patient-specific tractography was required to identify structural networks correlated with outcomes. It is therefore likely that altered connectivity in patients with epilepsy may be associated with the therapeutic effect and that utilizing patient-specific imaging could be important for future studies. The structural networks identified here may be utilized to target stimulation in the mesial temporal lobe and to improve seizure reduction for patients treated with responsive neurostimulation.

The Double Bind of Communicating About Zoonotic Origins: Describing Exotic Animal Sources of COVID-19 Increases Both Healthy and Discriminatory Avoidance Intentions.

Many novel diseases are of zoonotic origin, likely including COVID-19. Describing diseases as originating from a diverse range of animals is known to increase risk perceptions and intentions to engage in preventative behaviors. However, it is also possible that communications depicting use of exotic animals as food sources may activate stereotypes of cultures at the origin of a disease, increasing discriminatory behaviors and disease stigma. We used general linear modeling and mediation analysis to test experimental data on communications about zoonotic disease origins from the critical first two months leading up to the declaration of a global pandemic. Results suggest that communications about potential familiar food origins (pigs) affected people's risk perceptions, health behaviors, and COVID-19 stigma compared to more exotic food sources (e.g., snakes). Participants (N = 707) who read descriptions of exotic origins viewed the virus as riskier and reported stronger intentions to engage in preventative behaviors than those who read about familiar origins (pigs). However, reading exotic origin descriptions was also associated with stronger intentions to avoid Asian individuals and animal products. These results are critical for both theory and public policy. For theory, they are the first to experimentally demonstrate that zoonotic origin descriptions can impact intentions to engage in discriminatory behaviors for cultures viewed as the origin of a novel infectious disease. For policy, they offer clear, actionable insights on how to communicate about risks associated with a novel zoonosis while managing the potential impact on discriminatory behaviors and stigma.

Delayed Judgments of Learning Are Associated With Activation of Information From Past Experiences: A Neurobiological Examination.

Research in metacognition suggests that the information people use to predict their memory performance can vary depending on the contexts in which they make their predictions. For example, if people judge their memories after a delay from initial encoding, they may be more likely to use retrieved information about the past encoding experience than if they judged memories immediately after encoding. Although this seems intuitive, past behavioral and neuroimaging work has not tested whether delayed memory judgments are more strongly coupled with information about past experiences than immediate memory judgments. We scanned participants using functional MRI while they encoded paired associates and made predictions about their future memory performance either immediately after encoding or after a delay. Consistent with the hypothesis that people use retrieved information about past experiences to inform delayed memory judgments, our results showed that activation patterns associated with past experience were more strongly coupled with delayed memory judgments than with immediate ones.

Discriminability of multiple cutaneous and proprioceptive hand percepts evoked by intraneural stimulation with Utah slanted electrode arrays in human amputees.

BACKGROUND: Electrical stimulation of residual afferent nerve fibers can evoke sensations from a missing limb after amputation, and bionic arms endowed with artificial sensory feedback have been shown to confer functional and psychological benefits. Here we explore the extent to which artificial sensations can be discriminated based on location, quality, and intensity. METHODS: We implanted Utah Slanted Electrode Arrays (USEAs) in the arm nerves of three transradial amputees and delivered electrical stimulation via different electrodes and frequencies to produce sensations on the missing hand with various locations, qualities, and intensities. Participants performed blind discrimination trials to discriminate among these artificial sensations. RESULTS: Participants successfully discriminated cutaneous and proprioceptive sensations ranging in location, quality and intensity. Performance was significantly greater than chance for all discrimination tasks, including discrimination among up to ten different cutaneous location-intensity combinations (15/30 successes, p < 0.0001) and seven different proprioceptive location-intensity combinations (21/40 successes, p < 0.0001). Variations in the site of stimulation within the nerve, via electrode selection, enabled discrimination among up to five locations and qualities (35/35 successes, p < 0.0001). Variations in the stimulation frequency enabled discrimination among four different intensities at the same location (13/20 successes, p < 0.0005). One participant also discriminated among individual stimulation of two different USEA electrodes, simultaneous stimulation on both electrodes, and interleaved stimulation on both electrodes (20/24 successes, p < 0.0001). CONCLUSION: Electrode location, stimulation frequency, and stimulation pattern can be modulated to evoke functionally discriminable sensations with a range of locations, qualities, and intensities. This rich source of artificial sensory feedback may enhance functional performance and embodiment of bionic arms endowed with a sense of touch.

Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.

BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculature. Continuous decoders can provide more intuitive prosthesis control using multi-channel neural or electromyographic recordings. Three components influence continuous decoder performance: the data used to train the algorithm, the algorithm, and smoothing filters on the algorithm's output. Individual groups often focus on a single decoder, so very few studies compare different decoders using otherwise similar experimental conditions. METHODS: We completed a two-phase, head-to-head comparison of 12 continuous decoders using activities of daily living. In phase one, we compared two training types and a smoothing filter with three algorithms (modified Kalman filter, multi-layer perceptron, and convolutional neural network) in a clothespin relocation task. We compared training types that included only individual digit and wrist movements vs. combination movements (e.g., simultaneous grasp and wrist flexion). We also compared raw vs. nonlinearly smoothed algorithm outputs. In phase two, we compared the three algorithms in fragile egg, zipping, pouring, and folding tasks using the combination training and smoothing found beneficial in phase one. In both phases, we collected objective, performance-based (e.g., success rate), and subjective, user-focused (e.g., preference) measures. RESULTS: Phase one showed that combination training improved prosthesis control accuracy and speed, and that the nonlinear smoothing improved accuracy but generally reduced speed. Phase one importantly showed simultaneous movements were used in the task, and that the modified Kalman filter and multi-layer perceptron predicted more simultaneous movements than the convolutional neural network. In phase two, user-focused metrics favored the convolutional neural network and modified Kalman filter, whereas performance-based metrics were generally similar among all algorithms. CONCLUSIONS: These results confirm that state-of-the-art algorithms, whether linear or nonlinear in nature, functionally benefit from training on more complex data and from output smoothing. These studies will be used to select a decoder for a long-term take-home trial with implanted neuromyoelectric devices. Overall, clinical considerations may favor the mKF as it is similar in performance, faster to train, and computationally less expensive than neural networks.

Examining nonprescription syringe sales in Massachusetts and Rhode Island community pharmacies.

BACKGROUND: The role pharmacies play in addressing the opioid crisis and drug-related risks such as injection drug use is evolving. Estimating the prevalence of injection drug use at the community level is challenging because of the stigma of drug use. Many community pharmacies sell nonprescription sterile syringes; thus, pharmacy-level sales of injection equipment may be an indicator of drug-related harms and unmet needs of high-risk populations. OBJECTIVES: To describe, compare, and assess the convergent validity of staff-reported nonprescription syringe (NPS) sales volume and NPS administrative sales data from community pharmacies in Massachusetts (MA) and Rhode Island (RI). METHODS: This study employed both prospective cross-sectional survey data collection and utilization of administrative pharmacy sales data. Between November 2017 and January 2018, we administered a telephone-based survey to estimate average weekly NPS type and volume for 191 chain pharmacies (CVS Health) located in communities experiencing fatal opioid overdoses above the state's 2015 annual median rate. For the same time period, we obtained NPS sales data from surveyed pharmacies and all CVS Health pharmacies in the 2 states. We calculated Spearman correlations to assess convergence of average weekly volume between pharmacy staff reports and sales data. RESULTS: All pharmacies responded to the survey. Most (98.4%) pharmacies surveyed sold NPS, but 42.0% reported running out of stock monthly or more frequently. Pharmacy staff tended to under-report syringe sales. Staff-reported weekly NPS sales volume was 67,922 versus 70,962 syringes from administrative pharmacy sales data. Spearman correlation between reported and actual NPS sales was 0.40 (95% CI 0.27-0.51). CONCLUSION: The counts of administrative pharmacy syringe sales data in MA and RI indicate high need, substantial volume, and notable access at community pharmacies. Future research should use NPS sales data rather than self-report data to track emerging trends and tailor local responses.

Brain Mechanisms of Concept Learning.

Concept learning, the ability to extract commonalities and highlight distinctions across a set of related experiences to build organized knowledge, is a critical aspect of cognition. Previous reviews have focused on concept learning research as a means for dissociating multiple brain systems. The current review surveys recent work that uses novel analytical approaches, including the combination of computational modeling with neural measures, focused on testing theories of specific computations and representations that contribute to concept learning. We discuss in detail the roles of the hippocampus, ventromedial prefrontal, lateral prefrontal, and lateral parietal cortices, and how their engagement is modulated by the coherence of experiences and the current learning goals. We conclude that the interaction of multiple brain systems relating to learning, memory, attention, perception, and reward support a flexible concept-learning mechanism that adapts to a range of category structures and incorporates motivational states, making concept learning a fruitful research domain for understanding the neural dynamics underlying complex behaviors.

Selective Decrease in Allodynia With High-Frequency Neuromodulation via High-Electrode-Count Intrafascicular Peripheral Nerve Interface After Brachial Plexus Injury.

OBJECTIVES: Kilohertz high-frequency alternating current (KHFAC) electrical nerve stimulation produces a reversible nerve block in peripheral nerves in human patients with chronic pain pathologies. Although this stimulation methodology has been verified with nonselective extrafascicular electrodes, the effectiveness of producing a selective nerve block with more-selective intrafascicular electrodes has not been well documented. The objective of this study was to examine whether intrafascicular electrodes can block painful stimuli while preserving conduction of other neural activity within the implanted nerve. MATERIALS AND METHODS: We analyzed the effects of various stimulation waveforms delivered through Utah Slanted Electrode Arrays (USEAs) implanted in the median nerve of a male human subject with a left brachial plexus injury. We compared KHFAC stimulation with a sham control. RESULTS: KHFAC stimulation through USEA electrodes produced a reduction in pain sensitivity in the palmar aspect of the left middle finger. KHFAC had limited effects on the patient's ability to feel tactile probing in the same area or move the digits of his left hand. Other tested stimulation parameters either increased or showed no reduction in pain. CONCLUSIONS: KHFAC stimulation in peripheral nerves through intrafascicular electrodes demonstrated a selective reduction in pain sensitivity while preserving other nerve functions. This treatment may benefit patient populations who have chronic pain originating from peripheral nerves, but who do not want to block whole-nerve function in order to preserve sensory and motor function reliant on the implanted nerve. Furthermore, KHFAC may benefit patients who respond negatively to other forms of peripheral nerve stimulation therapy.

The evaluative role of rostrolateral prefrontal cortex in rule-based category learning.

Category learning is a critical neurobiological function that allows organisms to simplify a complex world. Rostrolateral prefrontal cortex (rlPFC) is often active in neurobiological studies of category learning; however, the specific role this region serves in category learning remains uncertain. Previous category learning studies have hypothesized that the rlPFC is involved in switching between rules, whereas others have emphasized rule abstraction and evaluation. We aimed to clarify the role of rlPFC in category learning and dissociate switching and evaluation accounts using two common types of category learning tasks: matching and classification. The matching task involved matching a reference stimulus to one of four target stimuli. In the classification task, participants were shown a single stimulus and learned to classify it into one of two categories. Matching and classification are similar but place different demands on switching and evaluation. In matching, a rule can be known with certainty after a single correct answer. In classification, participants may need to evaluate evidence for a rule even after an initial correct response. This critical difference allows isolation of evaluative functions from switching functions. If the rlPFC is primarily involved in switching between representations, it should cease to be active once participants settle on a given rule in both tasks. If the rlPFC is involved in rule evaluation, its activation should persist in the classification task, but not matching. The results revealed that rlPFC activation persisted into correct trials in classification, but not matching, suggesting that it continues to be involved in the evaluations of evidence for a rule even after participants have arrived at the correct rule.

Rule activation and ventromedial prefrontal engagement support accurate stopping in self-paced learning.

When weighing evidence for a decision, individuals are continually faced with the choice of whether to gather more information or act on what has already been learned. The present experiment employed a self-paced category learning task and fMRI to examine the neural mechanisms underlying stopping of information search and how they contribute to choice accuracy. Participants learned to classify triads of face, object, and scene cues into one of two categories using a rule based on one of the stimulus dimensions. After each trial, participants were given the option to explicitly solve the rule or continue learning. Representational similarity analysis (RSA) was used to examine activation of rule-relevant information on trials leading up to a decision to solve the rule. We found that activation of rule-relevant information increased leading up to participants' stopping decisions. Stopping was associated with widespread activation that included medial prefrontal cortex and visual association areas. Engagement of ventromedial prefrontal cortex (vmPFC) was associated with accurate stopping, and activation in this region was functionally coupled with signal in dorsolateral prefrontal cortex (dlPFC). Results suggest that activating rule information when deciding whether to stop an information search increases choice accuracy, and that the response profile of vmPFC during such decisions may provide an index of effective learning.

From Concrete Examples to Abstract Relations: The Rostrolateral Prefrontal Cortex Integrates Novel Examples into Relational Categories.

The ability to form relational categories for objects that share few features in common is a hallmark of human cognition. For example, anything that can play a preventative role, from a boulder to poverty, can be a "barrier." However, neurobiological research has focused solely on how people acquire categories defined by features. The present functional magnetic resonance imaging study examines how relational and feature-based category learning compare in well-matched learning tasks. Using a computational model-based approach, we observed a cluster in left rostrolateral prefrontal cortex (rlPFC) that tracked quantitative predictions for the representational distance between test and training examples during relational categorization. Contrastingly, medial and dorsal PFC exhibited graded activation that tracked decision evidence during both feature-based and relational categorization. The results suggest that rlPFC computes an alignment signal that is critical for integrating novel examples during relational categorization whereas other PFC regions support more general decision functions.

Is hunger important to model in fMRI visual food-cue reactivity paradigms in adults with obesity and how should this be done?

We considered 1) influence of self-reported hunger in behavioral and fMRI food-cue reactivity (fMRI-FCR) 2) optimal methods to model this. Adults (N = 32; 19-60 years; F = 21; BMI 30-39.9 kg/m2) participated in an fMRI-FCR task that required rating 240 images of food and matched objects for 'appeal'. Hunger, satiety, thirst, fullness and emptiness were measured pre- and post-scan (visual analogue scales). Hunger, satiety, fullness and emptiness were combined to form a latent factor (appetite). Post-vs. pre-scores were compared using paired t-tests. In mixed-effects models, appeal/fMRI-FCR responses were regressed on image (i.e. food/objects), with random intercepts and slopes of image for functional runs nested within subjects. Each of hunger, satiety, thirst, fullness, emptiness and appetite were added as covariates in 4 forms (separate models): 1) change; 2) post- and pre-mean; 3) pre-; 4) change and pre-. Satiety decreased (Δ = -13.39, p = 0.001) and thirst increased (Δ = 11.78, p = 0.006) during the scan. Changes in other constructs were not significant (p's > 0.05). Including covariates did not influence food vs. object contrast of appeal ratings/fMRI-FCR. Significant image X covariate interactions were observed in some fMRI models. However, including these constructs did not improve the overall model fit. While some subjective, self-reported hunger, satiety and related constructs may be moderating fMRI-FCR, these constructs do not appear to be salient influences on appeal/fMRI-FCR in people with obesity undergoing fMRI.