Underlying Brain Regions Research Articles

Synaptic and intrinsic plasticity within overlapping lateral amygdala ensembles following fear conditioning.

New learning results in modulation of intrinsic plasticity in the underlying brain regions. Such changes in intrinsic plasticity can influence allocation and encoding of future memories such that new memories encoded during the period of enhanced excitability are linked to the original memory. The temporal window during which the two memories interact depends upon the time course of intrinsic plasticity following new learning. Using the well-characterized lateral amygdala-dependent auditory fear conditioning as a behavioral paradigm, we investigated the time course of changes in intrinsic excitability within lateral amygdala neurons. We found transient changes in the intrinsic excitability of amygdala neurons. Neuronal excitability was increased immediately following fear conditioning and persisted for up to 4 days post-learning but was back to naïve levels 10 days following fear conditioning. We also determined the relationship between learning-induced intrinsic and synaptic plasticity. Synaptic plasticity following fear conditioning was evident for up to 24 h but not 4 days later. Importantly, we demonstrated that the enhanced neuronal intrinsic excitability was evident in many of the same neurons that had undergone synaptic plasticity immediately following fear conditioning. Interestingly, such a correlation between synaptic and intrinsic plasticity following fear conditioning was no longer present 24 h post-learning. These data demonstrate that intrinsic and synaptic changes following fear conditioning are transient and co-localized to the same neurons. Since intrinsic plasticity following fear conditioning is an important determinant for the allocation and consolidation of future amygdala-dependent memories, these findings establish a time course during which fear memories may influence each other.

Are we really targeting and stimulating DLPFC by placing transcranial electrical stimulation (tES) electrodes over F3/F4?

In many clinical trials involving transcranial electrical stimulation (tES), target electrodes are typically placed over DLPFC with the assumption that this will primarily stimulate the underlying brain region. However, our study aimed to evaluate the electric fields (EF) that are actually delivered and identify prefrontal regions that may be inadvertently targeted in DLPFC tES. Head models were generated from the Human Connectome Project database's T1 + T2-weighted MRIs of 80 healthy adults. Two common DLPFC montages were simulated; symmetric-F4/F3, and asymmetric-F4/Fp1. Averaged EF was extracted from (1) the center of the target electrode (F4), and (2) the top 1% of voxels showing the strongest EF in individualized EF maps. Interindividual variabilities were quantified with the standard deviation of EF peak location/value. Similar steps were repeated with 66 participants with methamphetamine use disorder (MUDs) as an independent clinical population. In healthy adults, the group-level location of EF peaks was situated in the medial-frontopolar, and the individualized EF peaks were positioned in a cube with a volume of 29 cm3 /46 cm3 (symmetric/asymmetric montages). EFs in the frontopolar area were significantly higher than EF "under" the target electrode in both symmetric (peak: 0.41 ± 0.06, F4:0.22 ± 0.04) and asymmetric (peak: 0.38 ± 0.04, F4:0.2 ± 0.04) montages (Heges'g > 0.7). Similar results with slight between-group differences were found in MUDs. We highlighted that in common DLPFC tES montages, in addition to interindividual/intergroup variability, the frontopolar received the highest EFs rather than DLPFC as the main target. We specifically recommended considering the potential involvement of the frontopolar area as a mechanism underlying the effectiveness of DLPFC tES protocols.

Brain morphometric features predict depression symptom phenotypes in late-life depression using a deep learning model.

Our objective was to use deep learning models to identify underlying brain regions associated with depression symptom phenotypes in late-life depression (LLD). Diagnosed with LLD (N = 116) and enrolled in a prospective treatment study. Cross-sectional. Structural magnetic resonance imaging (sMRI) was used to predict five depression symptom phenotypes from the Hamilton and MADRS depression scales previously derived from factor analysis: (1) Anhedonia, (2) Suicidality, (3) Appetite, (4) Sleep Disturbance, and (5) Anxiety. Our deep learning model was deployed to predict each factor score via learning deep feature representations from 3D sMRI patches in 34 a priori regions-of-interests (ROIs). ROI-level prediction accuracy was used to identify the most discriminative brain regions associated with prediction of factor scores representing each of the five symptom phenotypes. Factor-level results found significant predictive models for Anxiety and Suicidality factors. ROI-level results suggest the most LLD-associated discriminative regions in predicting all five symptom factors were located in the anterior cingulate and orbital frontal cortex. We validated the effectiveness of using deep learning approaches on sMRI for predicting depression symptom phenotypes in LLD. We were able to identify deep embedded local morphological differences in symptom phenotypes in the brains of those with LLD, which is promising for symptom-targeted treatment of LLD. Future research with machine learning models integrating multimodal imaging and clinical data can provide additional discriminative information.

At the Crossroad Between Resiliency and Fragility: A Neurodevelopmental Perspective on Early-Life Experiences.

Postnatal development of the brain is characterized by sensitive windows during which, local circuitry are drastically reshaped by life experiences. These critical periods (CPs) occur at different time points for different brain functions, presenting redundant physiological changes in the underlying brain regions. Although circuits malleability during CPs provides a valuable window of opportunity for adaptive fine-tuning to the living environment, this aspect of neurodevelopment also represents a phase of increased vulnerability for the development of a variety of disorders. Consistently, accumulating epidemiological studies point to adverse childhood experience as a major risk factor for many medical conditions, especially stress- and anxiety-related conditions. Thanks to creative approaches to manipulate rodents’ rearing environment, neurobiologist have uncovered a pivotal interaction between CPs and early-life experiences, offering an interesting landscape to improve our understanding of brain disorders. In this short review, we discuss how early-life experience impacts cellular and molecular players involved in CPs of development, translating into long-lasting behavioral consequences in rodents. Bringing together findings from multiple laboratories, we delineate a unifying theory in which systemic factors dynamically target the maturation of brain functions based on adaptive needs, shifting the balance between resilience and vulnerability in response to the quality of the rearing environment.

Safety and Tolerability of Accelerated Low-Frequency Repetitive Transcranial Magnetic Stimulation Over the Primary Motor Cortex-A Pilot Study.

Low-frequency repetitive transcranial magnetic stimulation (rTMS) is capable of inducing changes in the functional organization of underlying brain regions, however, often at the cost of long stimulation protocols over several weeks. As these protocols can be difficult to implement in clinical settings, the aim of the present pilot study was to show the feasibility and safety of an accelerated low-frequency rTMS protocol applying multiple sessions daily. To this purpose, nine healthy subjects received 14 sessions of rTMS (1 Hz, 30 min, 110% RMT) to the hand motor hotspot. Subjects received stimulation for either 14 days once daily [classical rTMS (c-rTMS)], 7 days twice daily (accelerated rTMS; a-rTMS), or sham stimulation for 14 days once daily (s-rTMS). Daily stimulation sessions in the a-rTMS group were delivered with a 90-min break in between. In total, 74% of rTMS sessions in the c-rTMS group, 89% in the a-rTMS group, and 98% in the s-rTMS group were free of any side effects. Brief headaches and fatigue in stimulated muscle groups were the most frequent side effects. All side effects were reported to be at maximum mild and of short duration. Thus, accelerated low-frequency rTMS of the motor cortex seems to be a safe and feasible method, previously shown to induce a functional reorganization of the motor system. By shortening treatment duration in days, this approach can potentially make rTMS protocols more accessible to a wider range of patients.

The multidimensional nature of aphasia recovery post-stroke.

Language is not a single function, but instead results from interactions between neural representations and computations that can be damaged independently of each other. Although there is now clear evidence that the language profile in post-stroke aphasia reflects graded variations along multiple underlying dimensions (‘components’), it is still entirely unknown if these distinct language components have different recovery trajectories and rely on the same, or different, neural regions during aphasia recovery. Accordingly, this study examined whether language components in the subacute stage: (i) mirror those observed in the chronic stage; (ii) recover together in a homogeneous manner; and (iii) have recovery trajectories that relate to changing activation in distinct or overlapping underlying brain regions.We analysed longitudinal data from 26 individuals with mild–moderate aphasia following left hemispheric infarct who underwent functional MRI and behavioural testing at ∼2 weeks and ∼4 months post-stroke. The language profiles in early post-stroke aphasia reflected three orthogonal principal components consisting of fluency, semantic/executive function and phonology. These components did not recover in a singular, homogeneous manner; rather, their longitudinal trajectories were uncorrelated, suggesting that aphasia recovery is heterogeneous and multidimensional. Mean regional brain activation during overt speech production in unlesioned areas was compared with patient scores on the three principal components of language at both the early and late time points. In addition, the change in brain activation over time was compared with the change on each of the principal component scores, both before and after controlling for baseline scores. We found that different language components were associated with changing activation in multiple, non-overlapping bilateral brain regions during aphasia recovery. Specifically, fluency recovery was associated with increasing activation in bilateral middle frontal gyri and right temporo-occipital middle temporal gyrus; semantic/executive recovery was associated with reducing activation in bilateral anterior temporal lobes; while phonology recovery was associated with reducing activation in bilateral precentral gyri, dorso-medial frontal poles and the precuneus. Overlapping clusters in the ventromedial prefrontal cortex were positively associated with fluency recovery but negatively associated with semantic/executive and phonology recovery.This combination of detailed behavioural and functional MRI data provides novel insights into the neural basis of aphasia recovery. Because different aspects of language seem to rely on different neural regions for recovery, treatment strategies that target the same neural region in all stroke survivors with aphasia might be entirely ineffective or even impair recovery, depending on the specific language profile of each individual patient.

Variability of EEG electrode positions and their underlying brain regions: visualizing gel artifacts from a simultaneous EEG-fMRI dataset.

IntroductionWe investigated the between‐subject variability of EEG (electroencephalography) electrode placement from a simultaneously recorded EEG‐fMRI (functional magnetic resonance imaging) dataset.MethodsNeuro‐navigation software was used to localize electrode positions, made possible by the gel artifacts present in the structural magnetic resonance images. To assess variation in the brain regions directly underneath electrodes we used MNI coordinates, their associated Brodmann areas, and labels from the Harvard‐Oxford Cortical Atlas. We outline this relatively simple pipeline with accompanying analysis code.ResultsIn a sample of 20 participants, the mean standard deviation of electrode placement was 3.94 mm in x, 5.55 mm in y, and 7.17 mm in z, with the largest variation in parietal and occipital electrodes. In addition, the brain regions covered by electrode pairs were not always consistent; for example, the mean location of electrode PO7 was mapped to BA18 (secondary visual cortex), whereas PO8 was closer to BA19 (visual association cortex). Further, electrode C1 was mapped to BA4 (primary motor cortex), whereas C2 was closer to BA6 (premotor cortex).ConclusionsOverall, the results emphasize the variation in electrode positioning that can be found even in a fixed cap. This may be particularly important to consider when using EEG positioning systems to inform non‐invasive neurostimulation.

Safety and feasibility of accelerated low-frequency repetitive navigated transcranial magnetic stimulation (rnTMS)

Abstract Low frequency repetitive transcranial magnetic stimulation (rTMS) is capable of inducing changes in functional organization of underlying brain regions, however often at the cost of long stimulation protocols over several weeks. As these protocols can be difficult to implement in clinical settings, the aim of the present study was to show the feasibility and safety of an accelerated low-frequency rTMS protocol applying multiple sessions daily. To this purpose, nine healthy subjects (mean age 25.4 years; 1 female) received 14 sessions of rTMS (1 Hz, 30 minutes, 110% RMT) to the hand motor hotspot. Subjects received stimulation for either 14 days once daily (classical rTMS; c-rTMS), 7 days twice-daily (accelerated rTMS; a-rTMS) or sham stimulation for 14 days once-daily (s-rTMS). Daily stimulation sessions in the a-rTMS group were delivered with a 90-minute break in between. In total, 74% of rTMS sessions in the c-rTMS group, 89% in the a-rTMS group and 98% in the s-rTMS group were free of any side effects. Subjects reported occurrence of brief headaches in 14% of sessions in the c-rTMS group, 2% in the a-rTMS group and 0% in the s-rTMS group. Dizziness during stimulation was reported in 5% of sessions in the c-rTMS group, 2% in the a-rTMS group and 0% in the s-rTMS. Subjects reported a feeling of fatigue in the stimulated hand muscles in 2% of all sessions in the c-rTMS group, 7% in the a-rTMS group and 0% in the s-rTMS group. All side effects were reported to be at maximum mild and of short duration. Thus, accelerated low-frequency rTMS of the motor cortex is a safe and feasible method, previously shown to induce a functional reorganisation of the motor system. By shortening treatment duration in days, this approach can potentially make rTMS protocols more accessible to a wider range of patients. Keywords: rTMS, neuromodulation, plasticity, safety

Effectiveness of repetitive transcranial magnetic stimulation (rTMS) for the treatment of obsessive-compulsive disorder (OCD): a meta-analysis

AimsOCD is a chronic and debilitating psychiatric illness. Current first-line treatments include serotonin reuptake inhibitors and cognitive behavioural therapy, but a substantial minority of patients fail to respond adequately, requiring further forms of intervention usually provided in a sequenced algorithm. Repetitive Transcranial Magnetic Stimulation (rTMS) uses magnetic pulses passed through a coil placed on the scalp to stimulate the underlying brain region. Clinical trials of r-TMS in OCD have produced conflicting results, possibly related to the variability in the site of stimulation, protocols used, and variability in the selection of patients. We perform an updated systematic review and meta-analysis of the effectiveness of rTMS for the treatment of OCD aimed to determine whether certain rTMS parameters (i.e. site, duration, protocol etc.) or patients’ characteristics (i.e age, duration of illness, illness severity, treatment resistance etc), are associated with effectiveness. Our overarching aim is to determine the place of rTMS in the sequenced OCD care-pathway.MethodThe meta-analysis is pre-registered in PROSPERO (ID: 241381). Potentially relevant studies will be retrieved using the MEDLINE, PsycINFO, and Cochrane Library databases using the parameters [‘obsessive compulsive disorder’ or ‘OCD’ or ‘obsessions’ or ‘compulsions’] AND [‘transcranial magnetic stimulation’ or ‘TMS’]. The reference lists of retained articles will also be scrutinized for additional relevant publications. Only full text English language articles will be included in the review. The methodological quality of the studies will be assessed using CONSORT criteria. A summary of the study's quality as a randomized clinical trial will be produced.ResultOur preliminary analysis shows some efficacy for r-TMS in non-treatment resistant OCD than treatment resistant OCD. Detailed results will be presented in the poster at the event. Effect measure will be either categorical (e.g. relative risk (RR) or odds ratio (OR) or continuous (mean difference or standardized mean difference - Hedge's g or Cohen's d - when taking into consideration the severity of the disorder as a dimension). These outcomes will be measured through validated instruments, in the form of both self- rated scales and observer rated scales including semi-structured interviews.ConclusionThis meta-analysis will identify the patient, illness and protocol parameters that determine clinical outcomes, as guide to optimizing the role of rTMS in the care of patients with OCD.

Brain network mechanisms of visual shape completion

Visual shape completion recovers object shape, size, and number from spatially segregated edges. Despite being extensively investigated, the process's underlying brain regions, networks, and functional connections are still not well understood. To shed light on the topic, we scanned (fMRI) healthy adults during rest and during a task in which they discriminated pac-man configurations that formed or failed to form completed shapes (illusory and fragmented condition, respectively). Task activation differences (illusory-fragmented), resting-state functional connectivity, and multivariate patterns were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping (ActFlow) was used to evaluate the likely involvement of resting-state connections for shape completion. We identified 36 differentially-active parcels including a posterior temporal region, PH, whose activity was consistent across 95% of observers. Significant task regions primarily occupied the secondary visual network but also incorporated the frontoparietal, dorsal attention, default mode, and cingulo-opercular networks. Each parcel's task activation difference could be modeled via its resting-state connections with the remaining parcels (r=.62, p<10−9), suggesting that such connections undergird shape completion. Functional connections from the dorsal attention network were key in modelling task activation differences in the secondary visual network. Dorsal attention and frontoparietal connections could also model activations in the remaining networks. Taken together, these results suggest that shape completion relies upon a sparsely distributed but densely interconnected network coalition that is centered in the secondary visual network, coordinated by the dorsal attention network, and inclusive of at least three other networks.

Targeting brain regions of interest in functional near-infrared spectroscopy-Scalp-cortex correlation using subject-specific light propagation models.

Targeting specific brain regions of interest by the accurate positioning of optodes (emission and detection probes) on the scalp remains a challenge for functional near‐infrared spectroscopy (fNIRS). Since fNIRS data does not provide any anatomical information on the brain cortex, establishing the scalp‐cortex correlation (SCC) between emission‐detection probe pairs on the scalp and the underlying brain regions in fNIRS measurements is extremely important. A conventional SCC is obtained by a geometrical point‐to‐point manner and ignores the effect of light scattering in the head tissue that occurs in actual fNIRS measurements. Here, we developed a sensitivity‐based matching (SBM) method that incorporated the broad spatial sensitivity of the probe pair due to light scattering into the SCC for fNIRS. The SCC was analyzed between head surface fiducial points determined by the international 10–10 system and automated anatomical labeling brain regions for 45 subject‐specific head models. The performance of the SBM method was compared with that of three conventional geometrical matching (GM) methods. We reveal that the light scattering and individual anatomical differences in the head affect the SCC, which indicates that the SBM method is compulsory to obtain the precise SCC. The SBM method enables us to evaluate the activity of cortical regions that are overlooked in the SCC obtained by conventional GM methods. Together, the SBM method could be a promising approach to guide fNIRS users in designing their probe arrangements and in explaining their measurement data.

Spatial and temporal diversity of glycome expression in mammalian brain

Mammalian brain glycome remains a relatively poorly understood area compared to other large-scale "omics" studies, such as genomics and transcriptomics due to the inherent complexity and heterogeneity of glycan structure and properties. Here, we first performed spatial and temporal analysis of glycome expression patterns in the mammalian brain using a cutting-edge experimental tool based on liquid chromatography-mass spectrometry, with the ultimate aim to yield valuable implications on molecular events regarding brain functions and development. We observed an apparent diversity in the glycome expression patterns, which is spatially well-preserved among nine different brain regions in mouse. Next, we explored whether the glycome expression pattern changes temporally during postnatal brain development by examining the prefrontal cortex (PFC) at different time point across six postnatal stages in mouse. We found that glycan expression profiles were dynamically regulated during postnatal developments. A similar result was obtained in PFC samples from humans ranging in age from 39 d to 49 y. Novel glycans unique to the brain were also identified. Interestingly, changes primarily attributed to sialylated and fucosylated glycans were extensively observed during PFC development. Finally, based on the vast heterogeneity of glycans, we constructed a core glyco-synthesis map to delineate the glycosylation pathway responsible for the glycan diversity during the PFC development. Our findings reveal high levels of diversity in a glycosylation program underlying brain region specificity and age dependency, and may lead to new studies exploring the role of glycans in spatiotemporally diverse brain functions.

Assessing the requirements of prenatal UBE3A expression for rescue of behavioral phenotypes in a mouse model for Angelman syndrome

BackgroundAngelman syndrome (AS) is a rare neurodevelopmental disorder caused by the loss of functional ubiquitin protein ligase E3A (UBE3A). In neurons, UBE3A expression is tightly regulated by a mechanism of imprinting which suppresses the expression of the paternal UBE3A allele. Promising treatment strategies for AS are directed at activating paternal UBE3A gene expression. However, for such strategies to be successful, it is important to know when such a treatment should start, and how much UBE3A expression is needed for normal embryonic brain development.MethodsUsing a conditional mouse model of AS, we further delineated the critical period for UBE3A expression during early brain development. Ube3a gene expression was induced around the second week of gestation and mouse phenotypes were assessed using a behavioral test battery. To investigate the requirements of embryonic UBE3A expression, we made use of mice in which the paternal Ube3a allele was deleted.ResultsWe observed a full behavioral rescue of the AS mouse model phenotypes when Ube3a gene reactivation was induced around the start of the last week of mouse embryonic development. We found that full silencing of the paternal Ube3a allele was not completed till the first week after birth but that deletion of the paternal Ube3a allele had no significant effect on the assessed phenotypes.LimitationsDirect translation to human is limited, as we do not precisely know how human and mouse brain development aligns over gestational time. Moreover, many of the assessed phenotypes have limited translational value, as the underlying brain regions involved in these tasks are largely unknown.ConclusionsOur findings provide further important insights in the requirement of UBE3A expression during brain development. We found that loss of up to 50% of UBE3A protein during prenatal mouse brain development does not significantly impact the assessed mouse behavioral phenotypes. Together with previous findings, our results indicate that the most critical function for mouse UBE3A lies in the early postnatal period between birth and P21.

Endocast structures are reliable proxies for the sizes of corresponding regions of the brain in extant birds.

Endocasts are increasingly relied upon to examine avian brain evolution because they can be used across extant and extinct species. The endocasts of birds appear to be relatively faithful representatives of the external morphology of their brains, but it is unclear how well the size of a surface feature visible on endocasts reflects the volume of the underlying brain region. The optic lobe and the Wulst are two endocast structures that are clearly visible on the external surface of avian endocasts. As they overlie two major visual regions of the brain, the optic tectum and hyperpallium, the surface areas of the optic lobe and Wulst, respectively, are often used to infer visual abilities. To determine whether the surface area of these features reflects the volume of the underlying brain regions, we compared the surface areas of the optic lobes and Wulsts from digital endocasts with the volumes of the optic tecta and hyperpallia from the literature or measured from histological series of brains of the same species. Regression analyses revealed strong, statistically significant correlations between the volumes of the brain regions and the surface areas of the overlying endocast structures. In other words, the size of the hyperpallium and optic tectum can be reliably inferred from the surface areas of the Wulst and optic lobe, respectively. This validation opens the possibility of estimating brain-region volumes for extinct species in order to gain better insights in their visual ecology. It also emphasizes the importance of adopting a quantitative approach to the analysis of endocasts in the study of brain evolution.

Investigating cortico-subcortical circuits during auditory sensory attenuation: A combined magnetoencephalographic and dynamic causal modeling study.

Sensory attenuation refers to the decreased intensity of a sensory percept when a sensation is self‐generated compared with when it is externally triggered. However, the underlying brain regions and network interactions that give rise to this phenomenon remain to be determined. To address this issue, we recorded magnetoencephalographic (MEG) data from 35 healthy controls during an auditory task in which pure tones were either elicited through a button press or passively presented. We analyzed the auditory M100 at sensor‐ and source‐level and identified movement‐related magnetic fields (MRMFs). Regression analyses were used to further identify brain regions that contributed significantly to sensory attenuation, followed by a dynamic causal modeling (DCM) approach to explore network interactions between generators. Attenuation of the M100 was pronounced in right Heschl's gyrus (HES), superior temporal cortex (ST), thalamus, rolandic operculum (ROL), precuneus and inferior parietal cortex (IPL). Regression analyses showed that right postcentral gyrus (PoCG) and left precentral gyrus (PreCG) predicted M100 sensory attenuation. In addition, DCM results indicated that auditory sensory attenuation involved bi‐directional information flow between thalamus, IPL, and auditory cortex. In summary, our data show that sensory attenuation is mediated by bottom‐up and top‐down information flow in a thalamocortical network, providing support for the role of predictive processing in sensory‐motor system.

Electrophysiological Correlates of Basic and Higher Order Cognitive and Affective Theory of Mind Processing in Emerging and Early Adulthood-An Explorative Event-Related Potentials Study to Investigate First-, Second-, and Third-Order Theory of Mind Processing Based on Visual Cues.

Attributing mental states to others in social interactions [Theory of Mind (ToM)] often depends on visual social cues like eye gaze or mimic. This study presents an event-related potentials task (Brainy-ERP) that was developed in order to investigate the electrophysiological correlates of first-, second-, and third-order cognitive and affective ToM processing. The task was based on social visual cues and involved electroencephalographic event-related potential (ERP) analyses and exact low-resolution brain electromagnetic tomography analyses (eLORETA) source localization analyses. Results showed that in cognitive and affective conditions, first-order trials elicited greater Anterior P2 (180–370 ms) amplitudes. In the cognitive condition, third-order trials elicited greatest amplitudes in the broadly distributed early negative slow wave (eNSW, 260–470 ms) and the late NSW (LNSW, 460–1,000 ms). In the affective condition, third-order and second-order trials elicited greatest amplitudes in a broadly distributed NSW (250–1,000 ms). Regarding affective trials in the NSW time span, statistical significant differences and trends were shown regarding activation of underlying brain regions. Third-order trials elicited greatest activation in a number of regions typically associated with the ToM network, especially the posterior cingulate cortex (PCC), cuneus, and temporoparietal junction (TPJ). Furthermore, ToM low performers (participants with high accuracy but longer reaction times) showed by trend smaller Posterior N1 and significantly smaller eNSW amplitudes compared to average and high performers. This study offers new insights into electrophysiological correlates of basic and higher order cognitive and affective ToM processing and its precise time course.

Cytoarchitectonic Characterization and Functional Decoding of Four New Areas in the Human Lateral Orbitofrontal Cortex.

A comprehensive concept of the biological basis of reward, social and emotional behavior, and language requires a deeper understanding of the microstructure and connectivity of the underlying brain regions. Such understanding could provide deeper insights into their role in functional networks, and form the anatomical basis of the functional segregation of this region as shown in recent in vivo imaging studies. Here, we investigated the cytoarchitecture of the lateral orbitofrontal cortex (lateral OFC) in serial histological sections of 10 human postmortem brains by image analysis and a statistically reproducible approach to detect borders between cortical areas. Profiles of the volume fraction of cell bodies were therefore extracted from digitized histological images, describing laminar changes from the layer I/layer II boundary to the white matter. As a result, four new areas, Fo4–7, were identified. Area Fo4 was mainly found in the anterior orbital gyrus (AOG), Fo5 anteriorly in the inferior frontal gyrus (IFG), Fo6 in the lateral orbital gyrus (LOG), and Fo7 in the lateral orbital sulcus. Areas differed in cortical thickness, abundance and size of pyramidal cells in layer III and degree of granularity in layer IV. A hierarchical cluster analysis was used to quantify cytoarchitectonic differences between them. The 3D-reconstructed areas were transformed into the single-subject template of the Montreal Neurological Institute (MNI), where probabilistic maps and a maximum probability map (MPM) were calculated as part of the JuBrain Cytoarchitectonic Atlas. These maps served as reference data to study the functional properties of the areas using the BrainMap database. The type of behavioral tasks that activated them was analyzed to get first insights of co-activation patterns of the lateral OFC and its contribution to cognitive networks. Meta-analytic connectivity modeling (MACM) showed that functional decoding revealed activation in gustatory perception in Fo4; reward and somesthetic perception in Fo5; semantic processing and pain perception in Fo6; and emotional processing and covert reading in Fo7. Together with existing maps of the JuBrain Cytoarchitectonic Atlas, the new maps can now be used as an open-source reference for neuroimaging studies, allowing to further decode brain function.

Using subjective expectations to model the neural underpinnings of proactive inhibition.

Proactive inhibition – the anticipation of having to stop a response – relies on objective information contained in cue‐related contingencies in the environment, as well as on the subjective interpretation derived from these cues. To date, most studies of brain areas underlying proactive inhibition have exclusively considered the objective predictive value of environmental cues, by varying the probability of stop‐signals. However, by only taking into account the effect of different cues on brain activation, the subjective component of how cues affect behavior is ignored. We used a modified stop‐signal response task that includes a measurement for subjective expectation, to investigate the effect of this subjective interpretation. After presenting a cue indicating the probability that a stop‐signal will occur, subjects were asked whether they expected a stop‐signal to occur. Furthermore, response time was used to retrospectively model brain activation related to stop‐expectation. We found more activation during the cue period for 50% stop‐signal probability, when contrasting with 0%, in the mid and inferior frontal gyrus, inferior parietal lobe and putamen. When contrasting expected vs. unexpected trials, we found modest effects in the mid frontal gyrus, parietal, and occipital areas. With our third contrast, we modeled brain activation during the cue with trial‐by‐trial variances in response times. This yielded activation in the putamen, inferior parietal lobe, and mid frontal gyrus. Our study is the first to use the behavioral effects of proactive inhibition to identify the underlying brain regions, by employing an unbiased task‐design that temporally separates cue and response.

The Combined Use of Transcranial Direct Current Stimulation and Robotic Therapy for the Upper Limb.

Neurologic disorders such as stroke and cerebral palsy are leading causes of long-term disability and can lead to severe incapacity and restriction of daily activities due to lower and upper limb impairments. Intensive physical and occupational therapy are still considered main treatments, but new adjunct therapies to standard rehabilitation that may optimize functional outcomes are being studied. Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that polarizes underlying brain regions through the application of weak direct currents through electrodes on the scalp, modulating cortical excitability. Increased interest in this technique can be attributed to its low cost, ease of use, and effects on human neural plasticity. Recent research has been performed to determine the clinical potential of tDCS in diverse conditions such as depression, Parkinson's disease, and motor rehabilitation after stroke. tDCS helps enhance brain plasticity and seems to be a promising technique in rehabilitation programs. A number of robotic devices have been developed to assist in the rehabilitation of upper limb function after stroke. The rehabilitation of motor deficits is often a long process requiring multidisciplinary approaches for a patient to achieve maximum independence. These devices do not intend to replace manual rehabilitation therapy; instead, they were designed as an additional tool to rehabilitation programs, allowing immediate perception of results and tracking of improvements, thus helping patients to stay motivated. Both tDSC and robot-assisted therapy are promising add-ons to stroke rehabilitation and target the modulation of brain plasticity, with several reports describing their use to be associated with conventional therapy and the improvement of therapeutic outcomes. However, more recently, some small clinical trials have been developed that describe the associated use of tDCS and robot-assisted therapy in stroke rehabilitation. In this article, we describe the combined methods used in our institute for improving motor performance after stroke.

A Fast EEG Forecasting Algorithm for Phase-Locked Transcranial Electrical Stimulation of the Human Brain.

A growing body of research suggests that non-invasive electrical brain stimulation can more effectively modulate neural activity when phase-locked to the underlying brain rhythms. Transcranial alternating current stimulation (tACS) can potentially stimulate the brain in-phase to its natural oscillations as recorded by electroencephalography (EEG), but matching these oscillations is a challenging problem due to the complex and time-varying nature of the EEG signals. Here we address this challenge by developing and testing a novel approach intended to deliver tACS phase-locked to the activity of the underlying brain region in real-time. This novel approach extracts phase and frequency from a segment of EEG, then forecasts the signal to control the stimulation. A careful tuning of the EEG segment length and prediction horizon is required and has been investigated here for different EEG frequency bands. The algorithm was tested on EEG data from 5 healthy volunteers. Algorithm performance was quantified in terms of phase-locking values across a variety of EEG frequency bands. Phase-locking performance was found to be consistent across individuals and recording locations. With current parameters, the algorithm performs best when tracking oscillations in the alpha band (8–13 Hz), with a phase-locking value of 0.77 ± 0.08. Performance was maximized when the frequency band of interest had a dominant frequency that was stable over time. The algorithm performs faster, and provides better phase-locked stimulation, compared to other recently published algorithms devised for this purpose. The algorithm is suitable for use in future studies of phase-locked tACS in preclinical and clinical applications.