Event-related Brain Responses Research Articles

The relation between implicit statistical learning and proactivity as revealed by EEG

Environmental events often occur on a probabilistic basis but can sometimes be predicted based on specific cues and thus approached proactively. Incidental statistical learning enables the acquisition of knowledge about probabilistic cue-target contingencies. However, the neural mechanisms of statistical learning about contingencies (SLC), the required conditions for successful learning, and the role of implicit processes in the resultant proactive behavior are still debated. We examined changes in behavior and cortical activity during an SLC task in which subjects responded to visual targets. Unbeknown to them, there were three types of target cues associated with high-, low-, and zero target probabilities. About half of the subjects spontaneously gained explicit knowledge about the contingencies (contingency-aware group), and only they showed evidence of proactivity: shortened response times to predictable targets and enhanced event-related brain responses (cue-evoked P300 and contingent negative variation, CNV) to high probability cues. The behavioral and brain responses were strictly associated on a single-trial basis. Source reconstruction of the brain responses revealed activation of fronto-parietal brain regions associated with cognitive control, particularly the anterior cingulate cortex and precuneus. We also found neural correlates of SLC in the contingency-unaware group, but these were restricted to post-target latencies and visual association areas. Our results document a qualitative difference between explicit and implicit learning processes and suggest that in certain conditions, proactivity may require explicit knowledge about contingencies.

The effect of neural pre-stimulus oscillations on post-stimulus somatosensory event-related potentials in disorders of consciousness.

Brain activity of people in a disorder of consciousness (DoC) is diffuse and different from healthy people. In order to get a better understanding of their cognitive processes and functions, electroencephalographic activity has often been examined in patients with DoC, including detection of event-related potentials (ERPs) and spectral power analysis. However, the relationship between pre-stimulus oscillations and post-stimulus ERPs has rarely been explored in DoC, although it is known from healthy participants that pre-stimulus oscillations predispose subsequent stimulus detection. Here, we examine to what extent pre-stimulus electroencephalography band power in DoC relates to post-stimulus ERPs in a similar way as previously documented in healthy people. 14 DoC patients in an unresponsive wakefulness syndrome (UWS, N = 2) or a minimally conscious state (MCS, N = 12) participated in this study. In an active oddball paradigm patients received vibrotactile stimuli. Significant post-stimulus differences between brain responses to deviant and standard stimulation could be found in six MCS patients (42.86%). Regarding relative pre-stimulus frequency bands, delta oscillations predominated in most patients, followed by theta and alpha, although two patients showed a relatively normal power spectrum. The statistical analysis of the relationship between pre-stimulus power and post-stimulus event-related brain response showed multiple significant correlations in five out of the six patients. Individual results sometimes showed similar correlation patterns as in healthy subjects primarily between the relative pre-stimulus alpha power and post-stimulus variables in later time-intervals. However, opposite effects were also found, indicating high inter-individual variability in DoC patients´ functional brain activity. Future studies should determine on an individual level to what extent the relationship between pre- and post-stimulus brain activity could relate to the course of the disorder.

Electrophysiological underpinnings of dysfunctional inhibitory control in adults with attention-deficit/hyperactivity disorder: evidence for reduced NoGo anteriorization

Our aim was to delineate the electrophysiological basis of dysfunctional inhibitory control of adult ADHD via investigating the anteriorization of the P3 component of the event-related brain response associated with the NoGo task condition (i.e., NoGo anteriorization, NGA). NGA is a neurophysiological measure of brain topography for cognitive response control, which indexes an overall shift of the brain’s electrical activity in anterior direction towards the prefrontal areas. While the NoGo P3 received considerable attention in the adult ADHD literature, the brain topography of this component, which reflects the inhibitory process, remains largely unaddressed. EEG recordings were obtained during a Go/NoGo task from 51 subjects (n = 26 adult patients with ADHD, n = 25 healthy controls) using a high-density, 128-channel BioSemi ActiveTwo recording system. ADHD patients had significantly lower P3 NGA response compared to controls. The decrease in NGA was related to impulsivity scores as measured by the Conners’ Adult ADHD Rating Scale: patients with higher impulsivity scores had significantly lower NGA. Treatment with stimulant medication, as compared to the lack of such treatment, was associated with a correction of the lower NGA response in ADHD patients. The current study revealed a lower NGA in adult ADHD, a finding which is consistent with the inhibitory control and frontal lobe dysfunctions described in the disorder. Our finding of the inverse relationship between NGA and impulsivity suggests that clinically more severe impulsivity is linked to a more pronounced frontal dysfunction in adult ADHD subjects.

Self-processing in coma, unresponsive wakefulness syndrome and minimally conscious state.

Behavioral and cerebral dissociation has been now clearly established in some patients with acquired disorders of consciousness (DoC). Altogether, these studies mainly focused on the preservation of high-level cognitive markers in prolonged DoC, but did not specifically investigate lower but key-cognitive functions to consciousness emergence, such as the ability to take a first-person perspective, notably at the acute stage of coma. We made the hypothesis that the preservation of self-recognition (i) is independent of the behavioral impairment of consciousness, and (ii) can reflect the ability to recover consciousness. Hence, using bedside Electroencephalography (EEG) recordings, we acquired, in a large cohort of 129 severely brain damaged patients, the brain response to the passive listening of the subject's own name (SON) and unfamiliar other first names (OFN). One hundred and twelve of them (mean age ± SD = 46 ± 18.3 years, sex ratio M/F: 71/41) could be analyzed for the detection of an individual and significant discriminative P3 event-related brain response to the SON as compared to OFN ('SON effect', primary endpoint assessed by temporal clustering permutation tests). Patients were either coma (n = 38), unresponsive wakefulness syndrome (UWS, n = 30) or minimally conscious state (MCS, n = 44), according to the revised version of the Coma Recovery Scale (CRS-R). Overall, 33 DoC patients (29%) evoked a 'SON effect'. This electrophysiological index was similar between coma (29%), MCS (23%) and UWS (34%) patients (p = 0.61). MCS patients at the time of enrolment were more likely to emerged from MCS (EMCS) at 6 months than coma and UWS patients (p = 0.013 for comparison between groups). Among the 72 survivors' patients with event-related responses recorded within 3 months after brain injury, 75% of the 16 patients with a SON effect were EMCS at 6 months, while 59% of the 56 patients without a SON effect evolved to this favorable behavioral outcome. About 30% of severely brain-damaged patients suffering from DoC are capable to process salient self-referential auditory stimuli, even in case of absence of behavioral detection of self-conscious processing. We suggest that self-recognition covert brain ability could be an index of consciousness recovery, and thus could help to predict good outcome.

DC-tCNN: A Deep Model for EEG-Based Detection of Dim Targets.

Dim target detection in remote sensing images is a significant and challenging problem. In this work, we seek to explore event-related brain responses of dim target detection tasks and extend the brain-computer interface (BCI) systems to this task for efficiency enhancement. We develop a BCI paradigm named Asynchronous Visual Evoked Paradigm (AVEP), in which subjects are required to search the dim targets within satellite images when their scalp electroencephalography (EEG) signals are simultaneously recorded. In the paradigm, stimulus onset time and target onset time are asynchronous because subjects need enough time to confirm whether there are targets of interest in the presented serial images. We further propose a Domain adaptive and Channel-wise attention-based Time-domain Convolutional Neural Network (DC-tCNN) to solve the single-trial EEG classification problem for the AVEP task. In this model, we design a multi-scale CNN module combined with a channel-wise attention module to effectively extract event-related brain responses underlying EEG signals. Meanwhile, domain adaptation is proposed to mitigate cross-subject distribution discrepancy. The results demonstrate the superior performance and better generalizability of this model in classifying the single-trial EEG data of AVEP task in contrast to typical EEG deep learning networks. Visualization analyses of spatiotemporal features also illustrate the effectiveness and interpretability of our proposed paradigm and learning model. The proposed paradigm and model can effectively explore ambiguous event-related brain responses on EEG-based dim target detection tasks. Our work can provide a valuable reference for BCI-based image detection of dim targets.

Event-related brain response to visual cues in individuals with Internet gaming disorder: relevance to attentional bias and decision-making

This study investigated attentional bias toward game-related cues in Internet gaming disorder (IGD) using electrophysiological markers of late positive potential (LPP) and identifying the sources of LPP. In addition, the association between LPP and decision-making ability was investigated. The IGD (n = 40) and healthy control (HC; n = 39) participants viewed a series of game-related and neutral pictures, while their event-related potentials (ERPs) were recorded. LPPs were calculated as the mean amplitudes between 400 and 700 ms at the centro-parietal (CP3, CP1, Cpz, CP2, and CP4) and parietal (P3, P1, Pz, P2, and P4) electrode sites. The source activations of LPP were estimated using standardized low-resolution brain electromagnetic tomography (sLORETA). In addition, decision-making ability was evaluated by the Cambridge Gambling Task. Higher LPP amplitudes were found for game-related cues in the IGD group than in the HC group. sLORETA showed that the IGD group was more active in the superior and middle temporal gyri, which are involved in social perception, than in the HC group, whereas it was less active in the frontal area. Individuals with IGD have deficits in decision-making ability. In addition, in the HC group, the lower the LPP when looking at the game-related stimuli, the better the quality of decision-making, but not in the IGD group. Enhanced LPP amplitudes are associated with emotional arousal to gaming cues and decision-making deficits in IGD. In addition, source activities suggest that patients with IGD perceive game-related cues as social stimuli. LPP can be used as a neurophysiological marker of IGD.

Reducing Calibration Efforts in RSVP Tasks With Multi-Source Adversarial Domain Adaptation

Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an efficient information detection technology by detecting event-related brain responses evoked by target visual stimuli. However, a time-consuming calibration procedure is needed before a new user can use this system. Thus, it is important to reduce calibration efforts for BCI applications. In this article, we propose a multi-source conditional adversarial domain adaptation with the correlation metric learning (mCADA-C) framework that utilizes data from other subjects to reduce the data requirement from the new subject for training the model. This model utilizes adversarial training to enable a CNN-based feature extraction network to extract common features from different domains. A correlation metric learning (CML) loss is proposed to constrain the correlation of features based on class and domain to maximize the intra-class similarity and minimize inter-class similarity. Also, a multi-source framework with a source selection strategy is adopted to integrate the results of multiple domain adaptation. We constructed an RSVP-based dataset that includes 11 subjects each performing three RSVP experiments on three different days. The experimental results demonstrate that our proposed method can achieve 87.72% cross-subject balanced-accuracy under one block calibration. The results indicate our method can realize a higher performance with less calibration efforts.

A Transfer Learning Framework for RSVP-based Brain Computer Interface.

Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface (BCI) is an efficient information detection technology by detecting event-related brain responses evoked by target visual stimuli. However, a time-consuming calibration procedure is needed before a new user can use this system. Thus, it is important to reduce calibration efforts for BCI applications. In this paper, we collect an RSVP-based electroencephalogram (EEG) dataset, which includes 11 subjects. The experimental task is image retrieval. Also, we propose a multi-source transfer learning framework by utilizing data from other subjects to reduce the data requirement on the new subject for training the model. A source-selection strategy is firstly adopted to avoid negative transfer. And then, we propose a transfer learning network based on domain adversarial training. The convolutional neural network (CNN)-based network is designed to extract common features of EEG data from different subjects, while the discriminator tries to distinguish features from different subjects. In addition, a classifier is added for learning semantic information. Also, conditional information and gradient penalty are added to enable stable training of the adversarial network and improve performance. The experimental results demonstrate that our proposed method outperforms a series of state-of-the-art and baseline approaches.

Magnetoencephalography and Language.

This article provides an overview of research that uses magnetoencephalography to understand the brain basis of human language. The cognitive processes and brain networks that have been implicated in written and spoken language comprehension and production are discussed in relation to different methodologies: we review event-related brain responses, research on the coupling of neural oscillations to speech, oscillatory coupling between brain regions (eg, auditory-motor coupling), and neural decoding approaches in naturalistic language comprehension.

Changes in event-related brain responses and habituation during child development – A systematic literature review

ObjectiveThis systematic review highlights the influence of developmental changes of the central nervous system on habituation assessment during child development. Therefore, studies on age dependant changes in event-related brain responses as well as studies on behavioural and neurophysiological habituation during child development are compiled and discussed. MethodsTwo PubMed searches with terms “(development evoked brain response (fetus OR neonate OR children) (electroencephalography OR magnetoencephalography))” and with terms “(psychology habituation (fetal OR neonate OR children) (human brain))” were performed to identify studies on developmental changes in event-related brain responses as well as habituation studies during child development. ResultsBoth search results showed a wide diversity of subjects’ ages, stimulation protocols and examined behaviour or components of event-related brain responses as well as a demand for more longitudinal study designs. ConclusionsA conclusive statement about clear developmental trends in event-related brain responses or in neurophysiological habituation studies is difficult to draw. Future studies should implement longitudinal designs, combination of behavioural and neurophysiological habituation measurement and more complex habituation paradigms to assess several habituation criteria. SignificanceThis review emphasizes that event-related brain responses underlie certain changes during child development which should be more considered in the context of neurophysiological habituation studies.

Neural evidence for the impact of facial trustworthiness on object processing in a gaze-cueing task in 7-month-old infants

ABSTRACTHumans automatically judge a person’s trustworthiness solely based on facial features and use these judgments to inform subsequent behavior. While recent studies demonstrate that already infants are sensitive to variance in facial trustworthiness, it remains unclear whether this variance also influences subsequent socio-cognitive processes. We investigated event-related brain responses (ERPs) to faces varying in trustworthiness in a gaze-cueing paradigm in 7-month-old infants. Our analysis focused on the ERP responses to cued or un-cued objects shown in isolation after the gaze-cue was presented. We observed an enhanced occipital positive slow wave (PSW) to un-cued compared to cued objects, suggesting a gaze-cueing effect irrespective of facial trustworthiness. Furthermore, objects in the un-cued condition elicited a larger fronto-central Nc when the gaze cue was provided by trustworthy compared to untrustworthy faces. This pattern suggests that while gaze cueing occurs irrespective of facial trustworthiness, allocation of attention, as indexed by modulation of the Nc amplitude, varies as a function of trustworthiness. Taken together, our results show that facial trustworthiness impacts object processing in the context of a gaze cueing paradigm, adding to the notion that it serves as an important social cue from early in ontogeny.

An advanced bispectrum features for EEG-based motor imagery classification

Motor imagery (MI)-related brain activities can be effectively described by frequency analysis. Bispectrum is developed to overcome the drawback of power spectrum that the estimation of power spectrum discards the phase relationship among frequency components. However, the widely used bispectral features extraction method adds up all bispectral values as one feature, which could lead to the loss of effective information and increase of the sensitivity to non-linear and non-Gaussian noises. Thus, the representative bispectral features extraction method may be inefficient for MI classification. In addition, recent research suggests that the variations of EEG signals could provide more useful underlying information of event-related brain responses. This paper presents an advanced variations based bispectral feature extraction method to improve the performance of MI classification. The proposed method calculates the variations of MI-related EEG signals as input to bispectrum estimation. Besides, a new segmented bispectral sum features are developed to reduce the influence of non-linear and non-Gaussian noises and emphasize the valuable information for MI classification. The dataset collected in our laboratory and BCI Competition IV dataset 2b were adopted to validate the proposed method. The results indicate that the proposed method outperforms the power spectrum based methods and the representative bispectral features based methods. Moreover, compared to other state-of-the-art works, our approach also achieves the greater performance for MI classification.

Electrical Neuroimaging of Music Processing in Pianists With and Without True Absolute Pitch.

True absolute pitch (AP), labeling of pitches with semitone precision without a reference, is classically studied using isolated tones. However, AP is acquired and has its function within complex dynamic musical contexts. Here we examined event-related brain responses and underlying cerebral sources to endings of short expressive string quartets, investigating a homogeneous population of young highly trained pianists with half of them possessing true-AP. The pieces ended regularly or contained harmonic transgressions at closure that participants appraised. Given the millisecond precision of ERP analyses, this experimental plan allowed examining whether AP alters music processing at an early perceptual, or later cognitive level, or both, and which cerebral sources underlie differences with non-AP musicians. We also investigated the impact of AP on general auditory cognition. Remarkably, harmonic transgression sensitivity did not differ between AP and non-AP participants, and differences for auditory cognition were only marginal. The key finding of this study is the involvement of a microstate peaking around 60 ms after musical closure, characterizing AP participants. Concurring sources were estimated in secondary auditory areas, comprising the planum temporale, all transgression conditions collapsed. These results suggest that AP is not a panacea to become a proficient musician, but a rare perceptual feature.

Family History of Diabetes Is Associated With Delayed Fetal Postprandial Brain Activity.

Introduction: We have previously shown that fetuses of mothers with gestational diabetes mellitus (GDM) and insulin resistance exhibit a prolongation of fetal auditory event-related brain responses (fAER) compared to fetuses of normal glucose tolerant women during an oral glucose tolerance test (oGTT). This implies that maternal metabolism may program the developing fetal brain. We now asked whether a family history of type 2 diabetes without metabolic programing also impacts fetal brain activity. We therefore investigated brain activity in fetuses of normal glucose tolerant mothers with and without family history of type 2 diabetes (FHD+ and FHD–).Methods: A 75 g oGTT was performed in healthy pregnant women. Plasma glucose and insulin levels were measured after 0, 60, and 120 min. Each blood draw was preceded by fetal magnetoencephalographic (fMEG) recordings of fAER. From a group of 167 participants, a subsample of 52 metabolically healthy women, 37 with a negative, and 15 with a positive FHD (at least one first- or second-degree relative) was carefully selected based on the following inclusion criteria: inconspicuous pregnancy, no GDM, BMI 18.5–30 kg/m2, no preterm birth and at least two fMEG with detectable fetal responses during oGTT.Results: An ANOVA showed a significant interaction between fMEG measurement time during the oGTT and FHD on fAER latency [F(2) = 4.163, p = 0.018]. Fetuses of mothers with FHD+ had a prolonged fAER (273 ± 113 ms) compared to fetuses of mothers with FHD– (219 ± 69 ms) at 60 min during the oGTT [F(1) = 4.902, p = 0.032]. There were no significant differences in age, BMI before pregnancy, weight gain during pregnancy and gestational age between the groups. Maternal glucose levels and insulin sensitivity were also not significantly different.Discussion: In addition to the previously shown influence of maternal metabolism on fetal brain activity, maternal family history of diabetes (FHD) is also linked to fetal postprandial brain activity. This indicates that genetic and/or epigenetic factors modulate the postprandial brain response of the developing fetus.

Mapping the Spatiotemporal Evolution of Emotional Processing: An MEG Study Across Arousal and Valence Dimensions.

Electrophysiological and functional neuroimaging findings indicate that the neural mechanisms underlying the processing of emotional dimensions (i.e., valence, arousal) constitute a spatially and temporally distributed emotional network, modulated by the arousal and/or valence of the emotional stimuli. We examined the time course and source distribution of gamma time-locked magnetoencephalographic activity in response to a series of emotional stimuli viewed by healthy adults. We used a beamformer and a sliding window analysis to generate a succession of spatial maps of event-related brain responses across distinct levels of valence (pleasant/unpleasant) and arousal (high/low) in 30–100 Hz. Our results show parallel emotion-related responses along specific temporal windows involving mainly dissociable neural pathways for valence and arousal during emotional picture processing. Pleasant valence was localized in the left inferior frontal gyrus, while unpleasant valence in the right occipital gyrus, the precuneus, and the left caudate nucleus. High arousal was processed by the left orbitofrontal cortex, amygdala, and inferior frontal gyrus, as well as the right middle temporal gyrus, inferior parietal lobule, and occipital gyrus. Pleasant by high arousal interaction was localized in the left inferior and superior frontal gyrus, as well as the right caudate nucleus, putamen, and gyrus rectus. Unpleasant by high arousal interaction was processed by the right superior parietal gyrus. Valence was prioritized (onset at ∼60 ms) to all other effects, while pleasant valence was short lived in comparison to unpleasant valence (offsets at ∼110 and ∼320 ms, respectively). Both arousal and valence × arousal interactions emerged relatively early (onset at ∼150 ms, and ∼170 ms, respectively). Our findings support the notion that brain regions differentiate between valence and arousal, and demonstrate, for the first time, that these brain regions may also respond to distinct combinations of these two dimensions within specific time windows.

Relationships Between Behavioral And Single-Trial Target Detection Performance With Magnetoencephalography.

Target detection during serial visual presentation tasks is an active research topic in the brain-computer interface (BCI) community as this type of paradigm allows to take advantage of event-related potentials (ERPs) through electroencephalography (EEG) recordings to enhance the accuracy of target detection. The detection of brain evoked responses at the single-trial level remains a challenging task and can be exploited in various applications. Typical non-invasive BCIs based on event-related brain responses use EEG. In clinical settings, brain signals recorded with magnetoencephalography (MEG) can be advantageously used thanks to their high spatial and temporal resolution. In this study, we address the problem of the relationships between behavioral performance and single-trial detection by considering a task with different levels of difficulty. We consider images of faces with six different facial expressions (anger, disgust, fear, neutrality, sadness, and happiness). We consider MEG signals recorded on ten healthy participants in six sessions where targets were one of the six types of facial expressions in each session. The results support the conclusion that a high performance can be obtained at the single-trial level $( {AUC }= 0 . 903 \pm 0 .045)$, and that the performance is correlated with the behavioral performance (reaction time and hit rate).

When to Take a Gesture Seriously: On How We Use and Prioritize Communicative Cues.

When people talk, their speech is often accompanied by gestures. Although it is known that co-speech gestures can influence face-to-face communication, it is currently unclear to what extent they are actively used and under which premises they are prioritized to facilitate communication. We investigated these open questions in two experiments that varied how pointing gestures disambiguate the utterances of an interlocutor. Participants, whose event-related brain responses were measured, watched a video, where an actress was interviewed about, for instance, classical literature (e.g., Goethe and Shakespeare). While responding, the actress pointed systematically to the left side to refer to, for example, Goethe, or to the right to refer to Shakespeare. Her final statement was ambiguous and combined with a pointing gesture. The P600 pattern found in Experiment 1 revealed that, when pointing was unreliable, gestures were only monitored for their cue validity and not used for reference tracking related to the ambiguity. However, when pointing was a valid cue (Experiment 2), it was used for reference tracking, as indicated by a reduced N400 for pointing. In summary, these findings suggest that a general prioritization mechanism is in use that constantly monitors and evaluates the use of communicative cues against communicative priors on the basis of accumulated error information.

Single-trial detection of event-related fields in MEG from the presentation of happy faces: Results of the Biomag 2016 data challenge.

The recognition of brain evoked responses at the single-trial level is a challenging task. Typical non-invasive brain-computer interfaces based on event-related brain responses use eletroencephalograhy. In this study, we consider brain signals recorded with magnetoencephalography (MEG), and we expect to take advantage of the high spatial and temporal resolution for the detection of targets in a series of images. This study was used for the data analysis competition held in the 20th International Conference on Biomagnetism (Biomag) 2016, wherein the goal was to provide a method for single-trial detection of even-related fields corresponding to the presentation of happy faces during the rapid presentation of images of faces with six different facial expressions (anger, disgust, fear, neutrality, sadness, and happiness). The datasets correspond to 204 gradiometers signals obtained from four participants. The best method is based on the combination of several approaches, and mainly based on Riemannian geometry, and it provided an area under the ROC curve of 0.956±0.043. The results show that a high recognition rate of facial expressions can be obtained at the signal-trial level using advanced signal processing and machine learning methodologies.

Right hemisphere pitch-mismatch negativity reduction in patients with major depression: An MEG study

BackgroundThe mismatch negativity (MMN) component of the event-related potential and its magnetic counterpart, the MMNm, are generated by a mismatch between the physical features of a deviant stimulus and a neuronal sensory-memory trace produced by repetitive standard stimuli. Deficits in the MMN/MMNm have been reported in patients with major depression; however, the results are inconsistent. The present study investigated the pitch-MMNm in patients with major depression using whole-head 306-channel magnetoencephalography (MEG). MethodsTwenty patients with major depression and 36 healthy subjects participated in this study. Subjects were presented with two sequences of auditory stimuli. One consisted of 1000Hz standard signals (probability=90%) and 1200Hz deviant signals (probability=10%), while the other consisted of 1200Hz standard (90%) and 1000Hz deviant signals (10%). Event-related brain responses to standard tones were subtracted from responses to deviant tones. ResultsMajor depressive patients showed significantly reduced magnetic global field power (GFP) of MMNm in the right hemisphere (p=0.02), although no significant MMNm reduction was observed in the left hemisphere (p=0.81). Additionally, patients with major depression showed significantly earlier bilateral MMNm peak latencies (p=0.004). No significant associations were observed between MMNm variables and demographic data/clinical variables within the patients. LimitationsWe could not exclude the effects of antidepressants, mood stabilizers, or neuroleptics on the MMNm abnormalities found in patients with major depression. Sample size was also insufficient to permit subgroup analyses. ConclusionsPatients with major depression exhibited reduced GFP of MMNm in the right hemisphere. The present study suggested that patients with major depression may have right hemispheric dominant preattentive dysfunction.

Neural responses to negative outcomes predict success in community-based substance use treatment.

Patterns of brain activation have demonstrated promise as prognostic indicators in substance dependent individuals (SDIs) but have not yet been explored in SDIs typical of community-based treatment settings. Prospective clinical outcome design, evaluating baseline functional magnetic resonance imaging data from the Balloon Analogue Risk Task (BART) as a predictor of 3-month substance use treatment outcomes. Community-based substance use programs in Bloomington, Indiana, USA. Twenty-three SDIs (17 male, aged 18-43years) in an intensive outpatient or residential treatment program; abstinent 1-4weeks at baseline. Event-related brain response, BART performance and self-report scores at treatment onset, substance use outcome measure (based on days of use). Using voxel-level predictive modeling and leave-one-out cross-validation, an elevated response to unexpected negative feedback in bilateral amygdala and anterior hippocampus (Amyg/aHipp) at baseline successfully predicted greater substance use during the 3-month study interval (P≤0.006, cluster-corrected). This effect was robust to inclusion of significant non-brain-based covariates. A larger response to negative feedback in bilateral Amyg/aHipp was also associated with faster reward-seeking responses after negative feedback (r(23) =-0.544, P=0.007; r(23) =-0.588, P=0.003). A model including Amyg/aHipp activation, faster reward-seeking after negative feedback and significant self-report scores accounted for 45% of the variance in substance use outcomes in our sample. An elevated response to unexpected negative feedback in bilateral amygdala and anterior hippocampus (Amyg/aHipp) appears to predict relapse to substance use in people attending community-based treatment.