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Mental time travel (MTT), a cornerstone of human cognition, enables individuals to mentally project themselves into their past or future. It was shown that this self-projection may extend beyond the temporal domain to the spatial and social domains. What about higher cognitive domains? Twenty-eight participants underwent functional magnetic resonance imaging (fMRI) while self-projecting to different political, moral and temporal perspectives. For each domain, participants were asked to judge their relationship to various people (politicians, moral figures, personal acquaintances) from their actual or projected self-location. Findings showed slower, less accurate responses during self-projection across all domains. fMRI analysis revealed self-projection elicited brain activity at the precuneus, medial and dorsolateral prefrontal cortex, temporoparietal junction and anterior insula, bilaterally and right lateral temporal cortex. Notably, 23.5% of active voxels responded to all three domains and 27% to two domains, suggesting a shared brain system for self-projection. For ordinality judgement (self-reference), 52.5% of active voxels corresponded to the temporal domain specifically. Self-projection activity overlapped mostly with the frontoparietal control network, followed by the default mode network, while self-reference showed a reversed pattern, demonstrating MTT's implication in spontaneous brain activity. MTT may thus be regarded as a 'mental-experiential travel', with self-projection as a domain-general construct and self-reference related mostly to time. This article is part of the theme issue 'Elements of episodic memory: lessons from 40 years of research'.

Drug treatments for pain often do not outperform placebo, and a better understanding of placebo mechanisms is needed to improve treatment development and clinical practice. In a large-scale fMRI study (N = 392) with pre-registered analyses, we tested whether placebo analgesic treatment modulates nociceptive processes, and whether its effects generalize from conditioned to unconditioned pain modalities. Placebo treatment caused robust analgesia in conditioned thermal pain that generalized to unconditioned mechanical pain. However, placebo did not decrease pain-related fMRI activity in brain measures linked to nociceptive pain, including the Neurologic Pain Signature (NPS) and spinothalamic pathway regions, with strong support for null effects in Bayes Factor analyses. In addition, surprisingly, placebo increased activity in some spinothalamic regions for unconditioned mechanical pain. In contrast, placebo reduced activity in a neuromarker associated with higher-level contributions to pain, the Stimulus Intensity Independent Pain Signature (SIIPS), and affected activity in brain regions related to motivation and value, in both pain modalities. Individual differences in behavioral analgesia were correlated with neural changes in both modalities. Our results indicate that cognitive and affective processes primarily drive placebo analgesia, and show the potential of neuromarkers for separating treatment influences on nociception from influences on evaluative processes., (© 2024. The Author(s).)

Self-defining memories are highly significant personal memories that contribute to an individual's life story and identity. Previous research has identified 4 key subcomponents of self-defining memories: content, affect, specificity, and self-reflection. However, these components were not tested under functional neuroimaging. In this study, we first explored how self-defining memories distinguish themselves from everyday memories (non-self-defining) through their associated brain activity. Next, we evaluated the different self-defining memory subcomponents through their activity in the underlying brain system. Participants recalled both self-defining and non-self-defining memories under functional MRI and evaluated the 4 subcomponents for each memory. Multivoxel pattern analysis uncovered a brain system closely related to the default mode network to discriminate between self-defining and non-self-defining memories. Representational similarity analysis revealed the neural coding of each subcomponent. Self-reflection was coded mainly in the precuneus, middle and inferior frontal gyri, and cingulate, lateral occipital, and insular cortices. To a much lesser extent, content coding was primarily in the left angular gyrus and fusiform gyrus. No region was found to represent information on affect and specificity. Our findings highlight the marked difference in brain processing between significant and non-significant memories, and underscore self-reflection as a predominant factor in the formation and maintenance of self-defining memories, inviting a reassessment of what constitutes significant memories., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM to a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders. Importantly, the generalizability of cross-sectional models was demonstrated in an external validation sample. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level., (© 2024. The Author(s), under exclusive licence to American College of Neuropsychopharmacology.)

Numerous studies have identified traveling waves in the cortex and suggested they play important roles in brain processing. These waves are most often measured using macroscopic methods that are unable to assess the local spiking activity underlying wave dynamics. Here, we investigated the possibility that waves may not be traveling at the single neuron scale. We first show that sequentially activating two discrete brain areas can appear as traveling waves in EEG simulations. We next reproduce these results using an analytical model of two sequentially activated regions. Using this model, we were able to generate wave-like activity with variable directions, velocities, and spatial patterns, and to map the discriminability limits between traveling waves and modular sequential activations. Finally, we investigated the link between field potentials and single neuron excitability using large-scale measurements from turtle cortex ex vivo. We found that while field potentials exhibit wave-like dynamics, the underlying spiking activity was better described by consecutively activated spatially adjacent groups of neurons. Taken together, this study suggests caution when interpreting phase delay measurements as continuously propagating wavefronts in two different spatial scales. A careful distinction between modular and wave excitability profiles across scales will be critical for understanding the nature of cortical computations., Competing Interests: YO, AR, RP, YL, PB, MS No competing interests declared, (© 2023, Orsher et al.)

Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging., (© 2024. The Author(s).)

Objectives: Traumatic stress has been associated with increased risk for brain alterations and development of anxiety disorders. Studies conducted in posttraumatic patients have shown white-mater volume and diffusion alterations in the corpus-callosum. Decreased cognitive performance has been demonstrated in acute stress disorder and posttraumatic patients. However, whether cognitive alterations result from stress related neuropathology or reflect a predisposition is not known. In the current study, we examined in healthy controls, whether individual differences in anxiety are associated with those cognitive and brain alterations reported in stress related pathologies., Methods: Twenty healthy volunteers were evaluated for anxiety using the state-trait inventory (STAI), and were tested for memory performance. Brain imaging was employed to extract volumetric and diffusion characteristics of the corpus-callosum., Results: Significant correlations were found between trait anxiety and all three diffusion parameters (fractional-anisotropy, mean and radial-diffusivity). Associative-memory performance and corpus-callosum volume were also significantly correlated., Conclusion: We suggest that cognitive and brain alterations, as tested in the current work and reported in stress related pathologies, are present early and possibly persist throughout life. Our findings support the hypothesis that individual differences in trait anxiety predispose individuals towards negative cognitive outcomes and brain alterations, and potentially to stress related disorders., (© 2022 The Authors. International Journal of Methods in Psychiatric Research published by John Wiley & Sons Ltd.)

A fundamental characteristic of the human brain that supports behavior is its capacity to create connections between brain regions. A promising approach holds that during social behavior, brain regions not only create connections with other brain regions within a brain, but also coordinate their activity with other brain regions of an interaction partner. Here we ask whether between-brain and within-brain coupling contribute differentially to movement synchronization. We focused on coupling between the inferior frontal gyrus (IFG), a brain region associated with the observation-execution system, and the dorsomedial prefrontal cortex (dmPFC), a region associated with error-monitoring and prediction. Participants, randomly divided into dyads, were simultaneously scanned with functional near infra-red spectroscopy (fNIRS) while performing an open-ended 3D hand movement task consisting of three conditions: back-to-back movement, free movement, or intentional synchronization. Results show that behavioral synchrony was higher in the intentional synchrony compared with the back-to-back and free movement conditions. Between-brain coupling in the IFG and dmPFC was evident in the free movement and intentional synchrony conditions but not in the back-to-back condition. Importantly, between-brain coupling was found to positively predict intentional synchrony, while within-brain coupling was found to predict synchronization during free movement. These results indicate that during intentional synchronization, brain organization changes such that between-brain networks, but not within-brain connections, contribute to successful communication, pointing to shift from a within-brain feedback loop to a two-brains feedback loop., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Many studies have associated mental imagery with motor control mechanisms by showing mutually active brain areas and functions, as well as similar temporal patterns of imagining and executing the same motor actions. One of the main conjectured mutual mechanisms is the Cerebellar forward-model, commonly believed to generate sensory predictions as part of both motor control and mental imagery processes. Nevertheless, trials to associate one's overall individual mental and motor capacities have shown only mild and inconsistent correlations, hence challenging the mutual mechanism assumption. We hypothesized that one cause to this inconsistency is the forward-model's dominance in the motor-planning stage only when adapting to novel sensorimotor environments, while the inverse-model is gradually taking the lead along the adaptation, and therefore biasing most attempts to measure motor-mental overlapping functions and correlate these measurements under regular circumstances. Our current study aimed to tackle and explore this gap using immersive virtual embodiment, by applying an experience of a fundamental sensorimotor conflict, thereby manipulating the sensory prediction mechanism, and presumably forcing an increased involvement of the forward-model in the motor planning stage throughout the experiment. In the study, two groups of subjects (n = 48) performed mental and manual rotation within an immersive, motion-captured, virtual reality environment, while the sensorimotor dynamics of only the test group were altered by physical-virtual speed re-mapping making the virtual hand move twice as fast as the physical hand controlling it. Individual mental imagery capacities were assessed before and after three blocks of manual-rotation, where motor planning durations were measured as the time until motion onset. The results show that virtual sensorimotor alteration extremely increases the correlation of mental imagery and motor planning (r = 0.9, p < .0001) and leads to higher mental imagery performance improvement following the physical blocks. We particularly show that virtual embodiment manipulation affects the motor planning stage to change and functionally overlap with imagery mechanisms, rather than the other way around, which supports our conjecture of an increased sensory-prediction forward-model involvement. Our results shed new light on the embodied nature of mental imagery, support the view of the predictive forward-model as a key mechanism mutually underlying motor control and imagery, and suggest virtual sensorimotor alteration as a novel methodology to increase physical-mental convergence. These findings also suggest the applicability of using existing motion-tracked virtual environments for continuous cognitive evaluation and treatment, through kinematic analysis of ongoing natural motor behaviors., (© 2022. The Author(s).)

The coronavirus disease 2019 (COVID-19) outbreak introduced unprecedented health-risks, as well as pressure on the economy, society, and psychological well-being due to the response to the outbreak. In a preregistered study, we hypothesized that the intense experience of the outbreak potentially induced stress-related brain modifications in the healthy population, not infected with the virus. We examined volumetric changes in 50 participants who underwent MRI scans before and after the COVID-19 outbreak and lockdown in Israel. Their scans were compared with those of 50 control participants who were scanned twice prior to the pandemic. Following COVID-19 outbreak and lockdown, the test group participants uniquely showed volumetric increases in bilateral amygdalae, putamen, and the anterior temporal cortices. Changes in the amygdalae diminished as time elapsed from lockdown relief, suggesting that the intense experience associated with the pandemic induced transient volumetric changes in brain regions commonly associated with stress and anxiety. The current work utilizes a rare opportunity for real-life natural experiment, showing evidence for brain plasticity following the COVID-19 global pandemic. These findings have broad implications, relevant both for the scientific community as well as the general public., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2021. Published by Elsevier Inc.)

Resting-state fluctuations are ubiquitous and widely studied phenomena of the human brain, yet we are largely in the dark regarding their function in human cognition. Here we examined the hypothesis that resting-state fluctuations underlie the generation of free and creative human behaviors. In our experiment, participants were asked to perform three voluntary verbal tasks: a verbal fluency task, a verbal creativity task, and a divergent thinking task, during functional magnetic resonance imaging scanning. Blood oxygenation level dependent (BOLD)-activity during these tasks was contrasted with a control- deterministic verbal task, in which the behavior was fully determined by external stimuli. Our results reveal that all voluntary verbal-generation responses displayed a gradual anticipatory buildup that preceded the deterministic control-related responses. Critically, the time-frequency dynamics of these anticipatory buildups were significantly correlated with resting-state fluctuations' dynamics. These correlations were not a general BOLD-related or verbal-response related result, as they were not found during the externally determined verbal control condition. Furthermore, they were located in brain regions known to be involved in language production, specifically the left inferior frontal gyrus. These results suggest a common function of resting-state fluctuations as the neural mechanism underlying the generation of free and creative behaviors in the human cortex., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

The female predominance in the prevalence of depression is partially accounted by reactivity to hormonal fluctuations. Premenstrual dysphoric disorder (PMDD) is a reproductive subtype of depression characterized by cyclic emotional and somatic symptoms that recur before menstruation. Despite the growing understanding that most psychiatric disorders arise from dysfunctions in distributed brain circuits, the brain's functional connectome and its network properties of segregation and integration were not investigated in PMDD. To this end, we examined the brain's functional network organization in PMDD using graph theoretical analysis. 24 drug naïve women with PMDD and 27 controls without premenstrual symptoms underwent 2 resting-state fMRI scans, during the mid-follicular and late-luteal menstrual cycle phases. Functional connectivity MRI, graph theory metrics, and levels of sex hormones were computed during each menstrual phase. Altered network topology was found in PMDD across symptomatic and remitted stages in major graph metrics (characteristic path length, clustering coefficient, transitivity, local and global efficiency, centrality), indicating decreased functional network segregation and increased functional network integration. In addition, PMDD patients exhibited hypoconnectivity of the anterior temporal lobe and hyperconnectivity of the basal ganglia and thalamus, across menstrual phases. Furthermore, the relationship between difficulties in emotion regulation and PMDD was mediated by specific patterns of functional connectivity, including connections of the striatum, thalamus, and prefrontal cortex. The shifts in the functional connectome and its topology in PMDD may suggest trait vulnerability markers of the disorder., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

An emerging body of hyperscanning functional near-infrared spectroscopy (fNIRS) research shows interbrain neural synchrony (IBS) during different forms of social interaction. Here we review the recent literature and propose several factors that facilitate IBS, leading us to ask the following question: In a world full of people and opportunities to synchronize with them, what directs our neural and behavioral alignment with anyone specific? We suggest that IBS between what we deem the "mutual social attention systems" of interacting partners-that is, the coupling between participants' temporoparietal junctions and/or prefrontal cortices-facilitates and enhances the ability to tune in to the specific interaction, its participants and its goals. We propose that this process is linked to social alignment, reinforcing one another to facilitate successful and lucrative social interactions. We further suggest that neurochemical mechanisms of dopamine and oxytocin underlie the activation of this suggested loop. Finally, we suggest possible directions for future studies, emphasizing the need to develop a brain-to-brain neurofeedback system with IBS between the mutual social attention systems of the participants as the direct regulating target.

Behavioral change studies and interventions focus on self-control and external reinforcements to influence preferences. Cue-approach training (CAT) has been shown to induce preference changes lasting months by merely associating items with neutral cues and speeded responses. We utilized this paradigm to study neural representation of preferences and their modification without external reinforcements. We scanned 36 participants with fMRI during a novel passive viewing task before, after and 30 days following CAT. We preregistered the predictions that activity in memory, top-down attention, and value-processing regions will underlie preference modification. While most theories associate preferences with prefrontal regions, we found that "bottom-up" perceptual mechanisms were associated with immediate change, whereas reduced "top-down" parietal activity was related to long-term change. Activity in value-related prefrontal regions was enhanced immediately after CAT for trained items and 1 month after for all items. Our findings suggest a novel neural mechanism of preference representation and modification. We suggest that nonreinforced change of preferences occurs initially in perceptual representation of items, putatively leading to long-term changes in "top-down" processes. These findings offer implementation of bottom-up instead of top-down targeted interventions for long-lasting behavioral change., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Acute disseminated encephalomyelitis (ADEM) is an uncommon, treatable, primarily pediatric, immune-mediated disease. Diagnosis of ADEM requires two essential elements: typical clinical presentation and magnetic resonance imaging (MRI) findings. The aim of this study was to evaluate how clinical findings in the initial emergency department (ED) presentation influenced the timing of MRI., Methods: A retrospective chart review was conducted of children diagnosed with ADEM, over a 12-year period, in a tertiary care pediatric center. Clinical presentation at ED admission was recorded and patients who underwent an MRI as part of their ED evaluation (early MRI) with those who had MRI performed during ward hospitalization (late MRI) were compared., Results: 30 patients were diagnosed with ADEM during the study period. Encephalopathy and polyfocal neurological signs were described in 80% and 50% of patients ED charts, respectively. Seven patients underwent early MRI and polyfocal neurological signs were more common in this group (p = 0.006). Fever was more common in the late MRI group (p = 0.02). Following diagnosis, all patients were treated with immune-modulation therapy, improved clinically, and were discharged., Conclusion: 20% of ADEM patients were not encephalopathic at ED presentation. Polyfocal neurological signs and absence of fever at ED presentation were related to earlier MRI utilization and thus earlier diagnosis and treatment. Familiarity with the ADEM constellation of signs, and a high index of suspicion, may help the ED clinician in early diagnosis and treatment of this rare disease., (Copyright © 2019. Published by Elsevier Inc.)

Social interactions are essential to our daily life. We tested the hypothesis that social interactions during joint attention (JA) require bidirectional communication, each with a different mechanism. We used a novel multivariate functional connectivity analysis, which enables obtaining directed pathways between four regions at each time-frequency point, with hyper-scanning MRI data of real-time JA interaction. Constructing multiple "4-regional directed pathways" and counting the number of times, regions engaged in feedforward or feedback processes in the 'sender' or the 'receiver brains, we obtained the following. (1) There were more regions in feedforward than in feedback processes (125 versus 99). (2) The right hemisphere was more involved in feedforward (74 versus 33), while the left hemisphere in feedback (66 versus 51). (3) The dmPFC was more engaged in feedforward (73 versus 44) while the TPJ in both (49 versus 45). (4) The dmPFC was more involved in the sending processes (i.e. initiation of feedforward and feedback) while the TPJ in the receiving processes. (5) JA interaction was involved with high MRI frequencies (0.04-0.1 Hz), while continues interactions by low MRI frequencies (0.01-0.04 Hz). (6) Initiation and responding to JA (i.e. IJA and RJA) evolved with composite neural systems: similar systems for pathways that included the dmPFC, vmPFC and the STS, and different systems for pathways that included the TPJ, vmPFC, PCC and the STS. These findings have important consequences in the basic understanding of social interaction and could help in diagnose and follow-up of social impairments., (Copyright © 2019 Elsevier Inc. All rights reserved.)

There is an ongoing debate about the replicability of neuroimaging research. It was suggested that one of the main reasons for the high rate of false positive results is the many degrees of freedom researchers have during data analysis. In the Neuroimaging Analysis Replication and Prediction Study (NARPS), we aim to provide the first scientific evidence on the variability of results across analysis teams in neuroscience. We collected fMRI data from 108 participants during two versions of the mixed gambles task, which is often used to study decision-making under risk. For each participant, the dataset includes an anatomical (T1 weighted) scan and fMRI as well as behavioral data from four runs of the task. The dataset is shared through OpenNeuro and is formatted according to the Brain Imaging Data Structure (BIDS) standard. Data pre-processed with fMRIprep and quality control reports are also publicly shared. This dataset can be used to study decision-making under risk and to test replicability and interpretability of previous results in the field.

Depression, anxiety and apathy are distinct neuropsychiatric symptoms that highly overlap in Parkinson's disease (PD). It remains unknown whether each symptom is uniquely associated with a functional network dysfunction. Here, we examined whether individual differences in each neuropsychiatric symptom predict functional connectivity patterns in PD patients while controlling for all other symptoms and motor function. Resting-state functional connectivity MRI were acquired from 27 PD patients and 29 healthy controls. Widespread reduced functional connectivity was identified in PD patients and explained by either the neuropsychiatric or motor symptoms. Depression in PD predicted increased functional connectivity between the orbitofrontal, hippocampal complex, cingulate, caudate and thalamus. Apathy in PD predicted decreased caudate-thalamus and orbitofrontal-parahippocampal connectivity. Anxiety in PD predicted three distinct types of functional connectivity not described before: (i) increased limbic-orbitofrontal cortex; (ii) decreased limbic-dorsolateral prefrontal cortex and orbitofrontal-dorsolateral prefrontal cortices and (iii) decreased sensorimotor-orbitofrontal cortices. The first two types of functional connectivity suggest less voluntary and more automatic emotion regulation. The last type is argued to be specific to PD and reflect an impaired ability of the orbitofrontal cortex to guide goal-directed motor actions in anxious PD patients.

Network analysis is increasingly advancing the field of neuroimaging. Neural networks are generally constructed from pairwise interactions with an assumption of linear relations between them. Here, a high-order statistical framework to calculate directed functional connectivity among multiple regions, using wavelet analysis and spectral coherence has been presented. The mathematical expression for 4 regions was derived and used to characterize a quartet of regions as a linear, combined (nonlinear), or disconnected network. Phase delays between regions were used to obtain network's temporal hierarchy and directionality. The validity of the mathematical derivation along with the effects of coupling strength and noise on its outcomes were studied by computer simulations of the Kuramoto model. The simulations demonstrated correct directionality for a large range of coupling strength and low sensitivity to Gaussian noise compared with pairwise coherences. The analysis was applied to resting-state fMRI data of 40 healthy young subjects to characterize the ventral visual system, motor system and default mode network (DMN). It was shown that the ventral visual system was predominantly composed of linear networks while the motor system and the DMN were composed of combined (nonlinear) networks. The ventral visual system exhibits its known temporal hierarchy, the motor system exhibits center ↔ out hierarchy and the DMN has dorsal ↔ ventral and anterior ↔ posterior organizations. The analysis can be applied in different disciplines such as seismology, or economy and in a variety of brain data including stimulus-driven fMRI, electrophysiology, EEG, and MEG, thus open new horizons in brain research. Hum Brain Mapp 38:1374-1386, 2017. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

The multivariate construct of impulsivity is examined through neural systems and connections that comprise the executive functioning system. It is proposed that cognitive and behavioral components of impulsivity can be divided into two distinct groups, mediated by (1) the cognitive control system: deficits in top-down cognitive control processes referred to as action/cognitive impulsivity and (2) the socioemotional system: related to bottom-up affective/motivational processes referred to as affective impulsivity. Examination of impulsivity from a developmental viewpoint can guide future research, potentially enabling the selection of more effective interventions for impulsive individuals, based on the cognitive components requiring improvement.

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Introduction: Anterior shoulder apprehension is a commonly reported complaint in anterior shoulder instability, which may lead to patient morbidity and impede shoulder function. It is the result of a cognitively complex mechanism, which includes anxiety, salience, fear, and anticipation., Purpose: The aim of this prospective case-control study was to correlate five clinically established scores using functional magnetic resonance imaging to assess brain activation patterns in patients with apprehension related to anterior shoulder instability., Methods: This study includes 28 consecutive male right-handed patients (mean ± SEM, 26.8 ± 1.2 yr) with positive shoulder apprehension test and 10 healthy matched control participants without apprehension or a history of instability. Task-related and functional connectivity functional magnetic resonance imaging activation patterns occurring during apprehension video cue stimulation were correlated with five clinical tests and scores: Visual Analog Scale (VAS), Rowe score for instability, Simple Shoulder Test, Subjective Shoulder Value (SSV), and Western Ontario Shoulder Instability (WOSI)., Results: Rowe, pain VAS, and WOSI scores correlated with prefrontal cortex, dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, somatosensory area, and parieto-occipital and temporal areas (default mode network). Rowe score additionally correlated with frontal pole, anterior midcingulate cortex, and visual areas. Moreover, SSV correlated with task-related brain activity in the bilateral precentral gyrus, bilateral postcentral gyrus, and bilateral superior parietal lobe., Conclusions: Overall, Rowe score provides the strongest link between shoulder apprehension and brain level alterations as it correlates with the highest number of independent components involving areas responsible for both motor and cognitive functions, whereas pain VAS and WOSI occupy an intermediately strong link recruiting less brain networks. Finally, Simple Shoulder Test and SSV have the weakest link at the brain level.

Patients with posttraumatic stress disorder (PTSD) display abnormal emotional processing and bias towards emotional content. Most neurophysiological studies in PTSD found higher amplitudes of event-related potentials (ERPs) in response to trauma-related visual content. Here we aimed to characterize brain electrical activity in PTSD subjects in response to non-trauma-related emotion-laden pictures (positive, neutral and negative). A combined behavioral-ERP study was conducted in 14 severe PTSD patients and 14 controls. Response time in PTSD patients was slower compared with that in controls, irrespective to emotional valence. In both PTSD and controls, response time to negative pictures was slower compared with that to neutral or positive pictures. Upon ranking, both control and PTSD subjects similarly discriminated between pictures with different emotional valences. ERP analysis revealed three distinctive components (at ~300, ~600 and ~1000 ms post-stimulus onset) for emotional valence in control subjects. In contrast, PTSD patients displayed a similar brain response across all emotional categories, resembling the response of controls to negative stimuli. We interpret these findings as a brain-circuit response tendency towards negative overgeneralization in PTSD., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)

Disturbance in the blood supply to the brain causes a stroke or cerebrovascular accident. This can be due to ischemia caused by blockage (thrombosis, arterial embolism) or a hemorrhage. In this study, the feasibility of basic electrical impedance technique for monitoring such damage was analyzed using a computerized model. Simulations were conducted on a realistic 3D numerical model of the head. Tissues were assumed to act as linear isotropic volume conductors, and the quasi-static approximation was applied. Electrical potentials were calculated by solving Poisson's equation, using the finite volume method and the successive over relaxation method. Left-right asymmetry was calculated for several conductivities and volumes of the damaged region. The results were compared with the left-right asymmetry in a head model with normal brain. A negative asymmetry was revealed for blockage (i.e. the potential amplitude over the ischemic hemisphere was greater than that over the intact hemisphere). In case of hemorrhage, a positive asymmetry was found. Furthermore, correlation was found between the location of the damaged region and the electrodes with significant asymmetry. The 3D numerical simulations revealed that the electrical conductivity and the size of the damaged tissue have an effect on the left-right asymmetry of the surface potential., (Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.)

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Purpose: Most seizure monitoring units use the Gotman algorithm or a variation on it for EEG spike detection, but the effect of various detection parameters on its accuracy has not been well established. The authors report sensitivities and false-positive rates for several different sets of detection parameters., Methods: Nine patients were studied. For each patient, 6 hours of EEG data were analyzed using five different sets of spike detection parameters including combinations of amplitude thresholds, state-dependent spike detection and advanced artifact rejection. Automated spike detections were compared with spikes found on visual EEG review., Results: Mean spike detection sensitivities for the different parameter sets ranged from 0.09 to 0.34. The highest sensitivity occurred with an amplitude threshold of 4, state-dependent spike detection turned on and advanced artifact rejection turned off. Mean rates of false-positives ranged from 4.2 to 48.6 per hour. The highest false-positive rate occurred with the same set of detection parameters that produced the highest sensitivity., Conclusions: The sensitivity of spike detection with the Gotman algorithm is relatively low. The data favor using a lower amplitude threshold and not using advanced artifact rejection. The false-positive rate increases with improved sensitivity, but it is still within an acceptable range for clinical application.

A classical question in neuroscience is which features of a stimulus or of an action are represented in brain activity. When several features are interdependent either at a given point in time or at distinct points in time, neural activity related to one feature appears to be correlated with other features. Thus techniques that simultaneously consider multiple features cannot account for delayed interdependencies between features. The result is an ambiguity with respect to the encoded features. Here, we resolve this ambiguity by applying a novel statistical method based on partial cross-correlations. The method yields estimates of linear correlations between neural activity and a given feature that are not affected by linear correlations with other features at multiple time delays. The method also provides a graphical output measured on a scale that allows for comparisons between different features, neurons, and experiments. We use real movement data and neural activity simulated according to a wide range of tuning models to illustrate the method. When applied to real neural activity, the procedure yields results that indicate which of the considered features the neural activity is related to and at what time delays.