Functional Diversity of Gram-Negative Permeability Barriers Reflected in Antibacterial Activities and Intracellular Accumulation of Antibiotics.

Gram-negative bacteria are notoriously more resistant to antibiotics than Gram-positive bacteria, primarily due to the presence of the outer membrane and a plethora of active efflux pumps. However, the potency of antibiotics also varies dramatically between different Gram-negative pathogens, suggesting major mechanistic differences in how antibiotics penetrate permeability barriers. Two approaches are used broadly to analyze how permeability barriers affect intracellular accumulation of antibiotics. One compares the antibacterial activities of compounds, while the other measures the total intracellular concentrations of compounds in nongrowing cells, with both approaches using strains harboring wild-type or genetically modified efflux systems and permeability barriers. Whether the two assays provide similar mechanistic insights remains unclear. In this study, we analyzed the intracellular accumulation and antibacterial activities of antibiotics representative of major clinical classes in three Gram-negative pathogens of high clinical importance, Pseudomonas aeruginosa, Escherichia coli, and Acinetobacter baumannii. We found that both assays are informative about properties of permeability barriers, but there is no quantitative agreement between the assays. Our results show that the three pathogens differ dramatically in their permeability barriers, with the outer membrane playing the dominant role in E. coli and P. aeruginosa but efflux dominating in A. baumannii. However, even compounds of the same chemotype may use different permeation pathways depending on small chemical modifications. Accordingly, a classification analysis revealed limited conservation of molecular properties that define compound penetration into the three bacteria.

SPRY4-dependent ERK negative feedback demarcates functional adult stem cells in the male mouse germline†.

Niche-derived growth factors support self-renewal of mouse spermatogonial stem and progenitor cells through ERK MAPK signaling and other pathways. At the same time, dysregulated growth factor-dependent signaling has been associated with loss of stem cell activity and aberrant differentiation. We hypothesized that growth factor signaling through the ERK MAPK pathway in spermatogonial stem cells is tightly regulated within a narrow range through distinct intracellular negative feedback regulators. Evaluation of candidate extracellular signal-regulated kinase (ERK) mitogen-activated protein kinase (MAPK)-responsive genes known to dampen downstream signaling revealed robust induction of specific negative feedback regulators, including Spry4, in cultured mouse spermatogonial stem cells in response to glial cell line-derived neurotrophic factor or fibroblast growth factor 2. Undifferentiated spermatogonia in vivo exhibited high levels of Spry4 mRNA. Quantitative single-cell analysis of ERK MAPK signaling in spermatogonial stem cell cultures revealed both dynamic signaling patterns in response to growth factors and disruption of such effects when Spry4 was ablated, due to dysregulation of ERK MAPK downstream of RAS. Whereas negative feedback regulator expression decreased during differentiation, loss of Spry4 shifted cell fate toward early differentiation with concomitant loss of stem cell activity. Finally, a mouse Spry4 reporter line revealed that the adult spermatogonial stem cell population in vivo is demarcated by strong Spry4 promoter activity. Collectively, our data suggest that negative feedback-dependent regulation of ERK MAPK is critical for preservation of spermatogonial stem cell fate within the mammalian testis.

Machine discovery of partial differential equations from spatiotemporal data: A sparse Bayesian learning framework.

This study presents a general framework, namely, Sparse Spatiotemporal System Discovery (S3d), for discovering dynamical models given by Partial Differential Equations (PDEs) from spatiotemporal data. S3d is built on the recent development of sparse Bayesian learning, which enforces sparsity in the estimated PDEs. This approach enables a balance between model complexity and fitting error with theoretical guarantees. The proposed framework integrates Bayesian inference and a sparse priori distribution with the sparse regression method. It also introduces a principled iterative re-weighted algorithm to select dominant features in PDEs and solve for the sparse coefficients. We have demonstrated the discovery of the complex Ginzburg-Landau equation from a traveling-wave convection experiment, as well as several other PDEs, including the important cases of Navier-Stokes and sine-Gordon equations, from simulated data.

A pathway towards a two-dimensional, bore-mounted, volume body coil concept for ultra high-field magnetic resonance imaging.

Lack of a body-sized, bore-mounted, radiofrequency (RF) body coil for ultrahigh field (UHF) magnetic resonance imaging (MRI) is one of the major drawbacks of UHF, hampering the clinical potential of the technology. Transmit field (B1 ) nonuniformity and low specific absorption rate (SAR) efficiencies in UHF MRI are two challenges to be overcome. To address these problems, and ultimately provide a pathway for the full clinical potential of the modality, we have designed and simulated two-dimensional cylindrical high-pass ladder (2D c-HPL) architectures for clinical bore-size dimensions, and demonstrated a simplified proof of concept with a head-sized prototype at 7 T. A new dispersion relation has been derived and electromagnetic simulations were used to verify coil modes. The coefficient of variation (CV) for brain, cerebellum, heart, and prostate tissues after B1 + shimming in silico is reported and compared with previous works. Three prototypes were designed in simulation: a head-sized, body-sized, and long body-sized coil. The head-sized coil showed a CV of 12.3%, a B1 + efficiency of 1.33 µT/√W, and a SAR efficiency of 2.14 µT/√(W/kg) for brain simulations. The body-sized 2D c-HPL coil was compared with same-sized transverse electromagnetic (TEM) and birdcage coils in silico with a four-port circularly polarized mode excitation. Improved B1 + uniformity (26.9%) and SAR efficiency (16% and 50% better than birdcage and TEM coils, respectively) in spherical phantoms was observed. We achieved a CV of 12.3%, 4.9%, 16.7%, and 2.8% for the brain, cerebellum, heart, and prostate, respectively. Preliminary imaging results for the head-sized coil show good agreement between simulation and experiment. Extending the 1D birdcage coil concept to 2D c-HPLs provides improved B1 + uniformity and SAR efficiency.

Characterization of EEG signals revealing covert cognition in the injured brain.

See Boly and Laureys (doi:10.1093/brain/awy080) for a scientific commentary on this article.Patients with severe brain injury are difficult to assess and frequently subject to misdiagnosis. 'Cognitive motor dissociation' is a term used to describe a subset of such patients with preserved cognition as detected with neuroimaging methods but not evident in behavioural assessments. Unlike the locked-in state, cognitive motor dissociation after severe brain injury is prominently marked by concomitant injuries across the cerebrum in addition to limited or no motoric function. In the present study, we sought to characterize the EEG signals used as indicators of cognition in patients with disorders of consciousness and examine their reliability for potential future use to re-establish communication. We compared EEG-based assessments to the results of using similar methods with functional MRI. Using power spectral density analysis to detect EEG evidence of task performance (Two Group Test, P ≤ 0.05, with false discovery rate correction), we found evidence of the capacity to follow commands in 21 of 28 patients with severe brain injury and all 15 healthy individuals studied. We found substantial variability in the temporal and spatial characteristics of significant EEG signals among the patients in contrast to only modest variation in these domains across healthy controls; the majority of healthy controls showed suppression of either 8-12 Hz 'alpha' or 13-40 Hz 'beta' power during task performance, or both. Nine of the 21 patients with EEG evidence of command-following also demonstrated functional MRI evidence of command-following. Nine of the patients with command-following capacity demonstrated by EEG showed no behavioural evidence of a communication channel as detected by a standardized behavioural assessment, the Coma Recovery Scale - Revised. We further examined the potential contributions of fluctuations in arousal that appeared to co-vary with some patients' ability to reliably generate EEG signals in response to command. Five of nine patients with statistically indeterminate responses to one task tested showed a positive response after accounting for variations in overall background state (as visualized in the qualitative shape of the power spectrum) and grouping of trial runs with similar background state characteristics. Our findings reveal signal variations of EEG responses in patients with severe brain injuries and provide insight into the underlying physiology of cognitive motor dissociation. These results can help guide future efforts aimed at re-establishment of communication in such patients who will need customization for brain-computer interfaces.

Sparse learning of partial differential equations with structured dictionary matrix.

This paper presents a "structured" learning approach for the identification of continuous partial differential equation (PDE) models with both constant and spatial-varying coefficients. The identification problem of parametric PDEs can be formulated as an ℓ1/ℓ2-mixed optimization problem by explicitly using block structures. Block-sparsity is used to ensure parsimonious representations of parametric spatiotemporal dynamics. An iterative reweighted ℓ1/ℓ2 algorithm is proposed to solve the ℓ1/ℓ2-mixed optimization problem. In particular, the estimated values of varying coefficients are further used as data to identify functional forms of the coefficients. In addition, a new type of structured random dictionary matrix is constructed for the identification of constant-coefficient PDEs by introducing randomness into a bounded system of Legendre orthogonal polynomials. By exploring the restricted isometry properties of the structured random dictionary matrices, we derive a recovery condition that relates the number of samples to the sparsity and the probability of failure in the Lasso scheme. Numerical examples, such as the Schrödinger equation, the Fisher-Kolmogorov-Petrovsky-Piskunov equation, the Burger equation, and the Fisher equation, suggest that the proposed algorithm is fairly effective, especially when using a limited amount of measurements.

A delayed-feedback filter with negative group delay.

A filter with delay-induced negative group delay is presented. The filter consists of multiple time-delayed feedback terms, which lead to a negative group delay for frequencies in the baseband. It can be used for the real-time prediction of band-limited signals. The filter is universal as it does not rely on a specific model of the signal. Specifically, as long as the signal to be predicted is band-limited with a known cutoff frequency, the filter predicts the signal in real time up to a prediction horizon that depends on the cutoff frequency. How signal prediction arises from the negative group delay of the filter is worked out in detail. Its properties, including stability, are derived analytically and demonstrated by numerical simulations. For chaotic systems, the filter is predictive during phases of high predictability.

A negative group delay model for feedback-delayed manual tracking performance.

We propose that feedback-delayed manual tracking performance is limited by fundamental constraints imposed by the physics of negative group delay. To test this hypothesis, the results of an experiment in which subjects demonstrate both reactive and predictive dynamics are modeled by a linear system with delay-induced negative group delay. Although one of the simplest real-time predictors conceivable, this model explains key components of experimental observations. Most notably, it explains the observation that prediction time linearly increases with feedback delay, up to a certain point when tracking performance deteriorates. It also explains the transition from reactive to predictive behavior with increasing feedback delay. The model contains only one free parameter, the feedback gain, which has been fixed by comparison with one set of experimental observations for the reactive case. Our model provides quantitative predictions that can be tested in further experiments.

The Leaky Integrator with Recurrent Inhibition as a Predictor.

The leaky integrator, the basis for many neuronal models, possesses a negative group delay when a time-delayed recurrent inhibition is added to it. By means of this delay, the leaky integrator becomes a predictor for some frequency components of the input signal. The prediction properties are derived analytically, and an application to a local field potential is provided.

Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients.

Despite advances in resting state functional magnetic resonance imaging investigations, clinicians remain with the challenge of how to implement this paradigm on an individualized basis. Here, we assessed the clinical relevance of resting state functional magnetic resonance imaging acquisitions in patients with disorders of consciousness by means of a systems-level approach. Three clinical centres collected data from 73 patients in minimally conscious state, vegetative state/unresponsive wakefulness syndrome and coma. The main analysis was performed on the data set coming from one centre (Liège) including 51 patients (26 minimally conscious state, 19 vegetative state/unresponsive wakefulness syndrome, six coma; 15 females; mean age 49 ± 18 years, range 11-87; 16 traumatic, 32 non-traumatic of which 13 anoxic, three mixed; 35 patients assessed >1 month post-insult) for whom the clinical diagnosis with the Coma Recovery Scale-Revised was congruent with positron emission tomography scanning. Group-level functional connectivity was investigated for the default mode, frontoparietal, salience, auditory, sensorimotor and visual networks using a multiple-seed correlation approach. Between-group inferential statistics and machine learning were used to identify each network's capacity to discriminate between patients in minimally conscious state and vegetative state/unresponsive wakefulness syndrome. Data collected from 22 patients scanned in two other centres (Salzburg: 10 minimally conscious state, five vegetative state/unresponsive wakefulness syndrome; New York: five minimally conscious state, one vegetative state/unresponsive wakefulness syndrome, one emerged from minimally conscious state) were used to validate the classification with the selected features. Coma Recovery Scale-Revised total scores correlated with key regions of each network reflecting their involvement in consciousness-related processes. All networks had a high discriminative capacity (>80%) for separating patients in a minimally conscious state and vegetative state/unresponsive wakefulness syndrome. Among them, the auditory network was ranked the most highly. The regions of the auditory network which were more functionally connected in patients in minimally conscious state compared to vegetative state/unresponsive wakefulness syndrome encompassed bilateral auditory and visual cortices. Connectivity values in these three regions discriminated congruently 20 of 22 independently assessed patients. Our findings point to the significance of preserved abilities for multisensory integration and top-down processing in minimal consciousness seemingly supported by auditory-visual crossmodal connectivity, and promote the clinical utility of the resting paradigm for single-patient diagnostics.

Frontal networks associated with command following after hemorrhagic stroke.

BACKGROUND AND PURPOSE: Level of consciousness is frequently assessed by command-following ability in the clinical setting. However, it is unclear what brain circuits are needed to follow commands. We sought to determine what networks differentiate command following from noncommand following patients after hemorrhagic stroke. METHODS: Structural MRI, resting-state functional MRI, and electroencephalography were performed on 25 awake and unresponsive patients with acute intracerebral and subarachnoid hemorrhage. Structural injury was assessed via volumetric T1-weighted MRI analysis. Functional connectivity differences were analyzed against a template of standard resting-state networks. The default mode network (DMN) and the task-positive network were investigated using seed-based functional connectivity. Networks were interrogated by pairwise coherence of electroencephalograph leads in regions of interest defined by functional MRI. RESULTS: Functional imaging of unresponsive patients identified significant differences in 6 of 16 standard resting-state networks. Significant voxels were found in premotor cortex, dorsal anterior cingulate gyrus, and supplementary motor area. Direct interrogation of the DMN and task-positive network revealed loss of connectivity between the DMN and the orbitofrontal cortex and new connections between the task-positive network and DMN. Coherence between electrodes corresponding to right executive network and visual networks was also decreased in unresponsive patients. CONCLUSIONS: Resting-state functional MRI and electroencephalography coherence data support a model in which multiple, chiefly frontal networks are required for command following. Loss of DMN anticorrelation with task-positive network may reflect a loss of inhibitory control of the DMN by motor-executive regions. Frontal networks should thus be a target for future investigations into the mechanism of responsiveness in the intensive care unit environment.

Preservation of electroencephalographic organization in patients with impaired consciousness and imaging-based evidence of command-following.

OBJECTIVE: Standard clinical characterization of patients with disorders of consciousness (DOC) relies on observation of motor output and may therefore lead to the misdiagnosis of vegetative state or minimally conscious state in patients with preserved cognition. We used conventional electroencephalographic (EEG) measures to assess a cohort of DOC patients with and without functional magnetic resonance imaging (fMRI)-based evidence of command-following, and correlated the findings with standard clinical behavioral evaluation and brain metabolic activity. METHODS: We enrolled 44 patients with severe brain injury. Behavioral diagnosis was established using standardized clinical assessments. Long-term EEG recordings were analyzed to determine wakeful background organization and presence of elements of sleep architecture. A subset of patients had fMRI testing of command-following using motor imagery paradigms (26 patients) and resting brain metabolism measurement using (18) fluorodeoxyglucose positron emission tomography (31 patients). RESULTS: All 4 patients with fMRI evidence of covert command-following consistently demonstrated well-organized EEG background during wakefulness, spindling activity during sleep, and relative preservation of cortical metabolic activity. In the entire cohort, EEG organization and overall brain metabolism showed no significant association with bedside behavioral testing, except in a few cases when EEG was severely abnormal. INTERPRETATION: These findings suggest that conventional EEG is a simple strategy that complements behavioral and imaging characterization of DOC patients. Preservation of specific EEG features may be used to assess the likelihood of unrecognized cognitive abilities in severely brain-injured patients with very limited or no motor responses.

Therapeutic hypothermia and hypoxia-ischemia in the term-equivalent neonatal rat: characterization of a translational preclinical model.

BACKGROUND: Hypoxic-ischemic encephalopathy (HIE) is a major cause of morbidity in survivors. Therapeutic hypothermia (TH) is the only available intervention, but the protection is incomplete. Preclinical studies of HIE/TH in the rodent have relied on the postnatal day (P) 7 rat whose brain approximates a 32-36 wk gestation infant, less relevant for these studies. We propose that HIE and TH in the term-equivalent P10 rat will be more translational. METHODS: P10-11 rat pups were subjected to unilateral hypoxia-ischemia (HI) and 4 h recovery in normothermic (N) or hypothermic (TH) conditions. Brain damage was assessed longitudinally at 24 h, 2 wk, and 12 wk. Motor function was assessed with the beam walk; recognition memory was measured by novel object recognition. RESULTS: Neuroprotection with TH was apparent at 2 and 12 wk in both moderately and severely damaged animals. TH improved motor function in moderate, but not severe, damage. Impaired object recognition occurred with severe damage with no evidence of protection of TH. CONCLUSION: This adaptation of the immature rat model of HI provides a reproducible platform to further study HIE/TH in which individual animals are followed up longitudinally to provide a useful translational preclinical model.

Dichotomous effects of chronic intermittent hypoxia on focal cerebral ischemic injury.

BACKGROUND AND PURPOSE: Obstructive sleep apnea, a condition associated with chronic intermittent hypoxia (CIH), carries an increased risk of stroke. However, CIH has been reported to either increase or decrease brain injury in models of focal cerebral ischemia. The factors determining the differential effects of CIH on ischemic injury and their mechanisms remain unclear. Here, we tested the hypothesis that the intensity of the hypoxic challenge determines the protective or destructive nature of CIH by modulating mitochondrial resistance to injury. METHODS: Male C57Bl/6J mice were exposed to CIH with 10% or 6% O2 for ≤35 days and subjected to transient middle cerebral artery occlusion. Motor deficits and infarct volume were assessed 3 days later. Intraischemic cerebral blood flow was measured by laser-Doppler flowmetry and resting cerebral blood flow by arterial spin labeling MRI. Ca2+-induced mitochondrial depolarization and reactive oxygen species production were evaluated in isolated brain mitochondria. RESULTS: We found that 10% CIH is neuroprotective, whereas 6% CIH exacerbates tissue damage. No differences in resting or intraischemic cerebral blood flow were observed between 6% and 10% CIH. However, 10% CIH reduced, whereas 6% CIH increased, mitochondrial reactive oxygen species production and susceptibility to Ca2+-induced depolarizations. CONCLUSIONS: The influence of CIH on the ischemic brain is dichotomous and can be attributed, in part, to changes in the mitochondrial susceptibility to injury. The findings highlight a previously unappreciated complexity in the effect of CIH on the brain, which needs to be considered in evaluating the neurological effect of conditions associated with cyclic hypoxia.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks.

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain's long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways.

Pulsatility analysis of the circle of Willis.

Purpose: To evaluate the phenomenological significance of cerebral blood pulsatility imaging in aging research. Methods: N = 38 subjects from 20 to 72 years of age (24 females) were imaged with ultrafast MRI with a sampling rate of 100 ms and simultaneous acquisition of pulse oximetry data. Of these, 28 subjects had acceptable MRI and pulse data, with 16 subjects between 20 and 28 years of age, and 12 subjects between 61 and 72 years of age. Pulse amplitude in the circle of Willis was assessed with the recently developed method of analytic phase projection to extract blood volume waveforms. Results: Arteries in the circle of Willis showed pulsatility in the MRI for both the young and old age groups. Pulse amplitude in the circle of Willis significantly increased with age (p = 0.01) but was independent of gender, heart rate, and head motion during MRI. Discussion and conclusion: Increased pulse wave amplitude in the circle of Willis in the elderly suggests a phenomenological significance of cerebral blood pulsatility imaging in aging research. The physiologic origin of increased pulse amplitude (increased pulse pressure vs. change in arterial morphology vs. re-shaping of pulse waveforms caused by the heart, and possible interaction with cerebrospinal fluid pulsatility) requires further investigation.

Low-level language processing in brain-injured patients.

Assessing cognitive function-especially language processing-in severely brain-injured patients is critical for prognostication, care, and development of communication devices (e.g. brain-computer interfaces). In patients with diminished motor function, language processing has been probed using EEG measures of command-following in motor imagery tasks. While such tests eliminate the need for motor response, they require sustained attention. However, passive listening tasks, with an EEG response measure can reduce both motor and attentional demands. These considerations motivated the development of two assays of low-level language processing-identification of differential phoneme-class responses and tracking of the natural speech envelope. This cross-sectional study looks at a cohort of 26 severely brain-injured patient subjects and 10 healthy controls. Patients' level of function was assessed via the coma recovery scale-revised at the bedside. Patients were also tested for command-following via EEG and/or MRI assays of motor imagery. For the present investigation, EEG was recorded while presenting a 148 s audio clip of Alice in Wonderland. Time-locked EEG responses to phoneme classes were extracted and compared to determine a differential phoneme-class response. Tracking of the natural speech envelope was assessed from the same recordings by cross-correlating the EEG response with the speech envelope. In healthy controls, the dynamics of the two measures were temporally similar but spatially different: a central parieto-occipital component of differential phoneme-class response was absent in the natural speech envelope response. The differential phoneme-class response was present in all patient subjects, including the six classified as vegetative state/unresponsive wakefulness syndrome by behavioural assessment. However, patient subjects with evidence of language processing either by behavioural assessment or motor imagery tests had an early bilateral response in the first 50 ms that was lacking in patient subjects without any evidence of language processing. The natural speech envelope tracking response was also present in all patient subjects and responses in the first 100 ms distinguished patient subjects with evidence of language processing. Specifically, patient subjects with evidence of language processing had a more global response in the first 100 ms whereas those without evidence of language processing had a frontopolar response in that period. In summary, we developed two passive EEG-based methods to probe low-level language processing in severely brain-injured patients. In our cohort, both assays showed a difference between patient subjects with evidence of command-following and those with no evidence of command-following: a more prominent early bilateral response component.

Spontaneous Pituitary Neoplasm in Two Female Geriatric Southern Giant Pouched Rats (Cricetomys ansorgei).

Southern giant pouched rats (Cricetomys ansorgei) are a small muroid species native to the sub-Saharan Africa. Their exceptionally developed olfactory system, trainability, and relatively small size makes them useful working animals for various applications in humanitarian work. At our institution, a breeding colony of Southern giant pouched rats is maintained to study their physiology and utility as scent detectors. This case report describes the occurrence of spontaneous pituitary neoplasms with distinct clinical presentations in 2 geriatric (approximately 7.5 y old) wild-caught female Southern giant pouched rats. The first pouched rat displayed vestibular deficits, including left-sided head tilt, ataxia, disorientation, and circling. MRI revealed a large, focal heterogeneous mass arising from the pituitary fossa. The second pouched rat presented with polyuria, polydipsia, and hyperglycemia but no neurologic signs. Examination after euthanasia revealed a prolactin (PRL)-expressing pituitary carcinoma and adenoma in the first and second pouched rat, respectively, associated with mammary hyperplasia in both animals. This is the first report of spontaneous PRL-producing pituitary tumors in Southern giant pouched rats.

Behavioral and neural properties of social reinforcement learning.

Social learning is critical for engaging in complex interactions with other individuals. Learning from positive social exchanges, such as acceptance from peers, may be similar to basic reinforcement learning. We formally test this hypothesis by developing a novel paradigm that is based on work in nonhuman primates and human imaging studies of reinforcement learning. The probability of receiving positive social reinforcement from three distinct peers was parametrically manipulated while brain activity was recorded in healthy adults using event-related functional magnetic resonance imaging. Over the course of the experiment, participants responded more quickly to faces of peers who provided more frequent positive social reinforcement, and rated them as more likeable. Modeling trial-by-trial learning showed ventral striatum and orbital frontal cortex activity correlated positively with forming expectations about receiving social reinforcement. Rostral anterior cingulate cortex activity tracked positively with modulations of expected value of the cues (peers). Together, the findings across three levels of analysis--social preferences, response latencies, and modeling neural responses--are consistent with reinforcement learning theory and nonhuman primate electrophysiological studies of reward. This work highlights the fundamental influence of acceptance by one's peers in altering subsequent behavior.