Intra-V1 functional networks and classification of observed stimuli.

Introduction: Previous studies suggest that co-fluctuations in neural activity within V1 (measured with fMRI) carry information about observed stimuli, potentially reflecting various cognitive mechanisms. This study explores the neural sources shaping this information by using different fMRI preprocessing methods. The common response to stimuli shared by all individuals can be emphasized by using inter-subject correlations or de-emphasized by deconvolving the fMRI with hemodynamic response functions (HRFs) before calculating the correlations. The latter approach shifts the balance towards participant-idiosyncratic activity. Methods: Here, we used multivariate pattern analysis of intra-V1 correlation matrices to predict the Level or Shape of observed Navon letters employing the types of correlations described above. We assessed accuracy in inter-subject prediction of specific conjunctions of properties, and attempted intra-subject cross-classification of stimulus properties (i.e., prediction of one feature despite changes in the other). Weight maps from successful classifiers were projected onto the visual field. A control experiment investigated eye-movement patterns during stimuli presentation. Results: All inter-subject classifiers accurately predicted the Level and Shape of specific observed stimuli. However, successful intra-subject cross-classification was achieved only for stimulus Level, but not Shape, regardless of preprocessing scheme. Weight maps for successful Level classification differed between inter-subject correlations and deconvolved correlations. The latter revealed asymmetries in visual field link strength that corresponded to known perceptual asymmetries. Post-hoc measurement of eyeball fMRI signals did not find differences in gaze between stimulus conditions, and a control experiment (with derived simulations) also suggested that eye movements do not explain the stimulus-related changes in V1 topology. Discussion: Our findings indicate that both inter-subject common responses and participant-specific activity contribute to the information in intra-V1 co-fluctuations, albeit through distinct sub-networks. Deconvolution, that enhances subject-specific activity, highlighted interhemispheric links for Global stimuli. Further exploration of intra-V1 networks promises insights into the neural basis of attention and perceptual organization.

Recurrent Quantification Analysis Based Study of Wide-Field Calcium Imaging Data in Relation to Brain's Wake/Sleep Condition

Wide-Field Calcium Images (WFCI) directly reflect neuronal excitation, but their poor frame rate could be a drawback for time series analysis. This work was aimed at exploring the diagnostic capability retained by a time series obtained from calcium imaging data. To that purpose, we analyzed publicly available data from 2.88 hour continuous recordings of calcium images obtained from seven mice at different wake/sleep stages. Data were obtained from the Physionet portal and were submitted to Recurrence Quantification Analysis (RQA). The association between retrosplenial and parietal areas was also assessed. Nonlinear RQA analysis allowed to identify the right retrosplenial and parietal areas as particularly sensitive to changes in sleep walking condition. Specifically, our results suggested that the RQA feature lmean decreases in non-REM sleep_1 stage as compared to waking stage. Sleep (both sleep_1 stage and REM) apparently elicits an increase in the association between retrosplenial and parietal areas. Overall, these results suggest that RQA and association analysis are appropriate to assess modifications associated to changes in brain condition, in spite of the low sampling rate of WFCI signals.

Las Imágenes de Calcio de Campo Ancho (Wide-Field Calcium Images, WFCI) reflejan directamente la excitación neuronal, pero su escasa resolución temporal pudiera resultar un impedimento para el análisis de series temporales. El presente trabajo tuvo por finalidad explorar la capacidad diagnostica que retiene una serie temporal extraída de imágenes de calcio. Para ello, se estudió una base de datos disponible en la red que contiene registros de 2.88 horas de duración de imágenes de calcio correspondientes a 7 ratones transgénicos a diferentes estadios de sueño/vigilia. Los datos fueron descargados del portal Physionet y sometidos a Análisis de Cuantificación Recurrente (Recurrent Quantification Analysis, RQA). La asociación entre las áreas retrosplenial y parietal derechas fue también evaluada. El análisis no lineal mediante RQA permitió identificar las áreas retrosplenial y parietal derechas como zonas particularmente sensibles a cambios en el estado de sueño/vigilia. Específicamente, nuestros resultados sugieren que el índice l mean se redujo en el estadio 1 de sueño no REM en comparación con el estado de vigilia. El estado de sueño, tanto REM como no-REM aparentemente induce un reforzamiento en la apreciación entre las áreas retrosplenial y parietal derechas. En su conjunto, estos resultados apuntan que el análisis de RQA y de asociación entre áreas son pertinentes para sensar las modificaciones asociadas a cambios en el estado del cerebro, a pesar de la baja resolución temporal de las señales WFCI.

Transdiagnostic alterations in neural emotion regulation circuits - neural substrates of cognitive reappraisal in patients with depression and post-traumatic stress disorder.

BACKGROUND: Impaired cognitive reappraisal, associated with the social functioning and well-being of patients affected by mood or anxiety disorders, is characterized by distinct neural activation patterns across clinical populations. To date, studies dedicated to identifying common and distinct neural activation profiles need to be clarified. The aim of the present study was to investigate transdiagnostic differences and commonalities in brain activation patterns during reappraisal-mediated downregulation of emotions. METHODS: Cognitive reappraisal of negative images was contrasted with maintaining emotions during a control viewing condition. Brain activation in 35 patients with major depressive disorder (MDD), 20 patients with post-traumatic stress disorder (PTSD), and 34 healthy controls (HC) during cognitive reappraisal was compared. Moreover, the neural circuitry of emotion regulation in these clinical populations was examined using seed-to-voxel and voxel-to-voxel functional connectivity analyses. RESULTS: Whole-brain fMRI analyses showed less right-lateralized activation of the inferior, middle, and superior frontal gyrus during cognitive reappraisal compared to viewing of negative images in MDD and PTSD patients compared to HCs. Right IFG activation was negatively correlated with the severity of anxiety and depressive symptomatology. In addition, increased seed-to-voxel connectivity of the right IFG as well as increased voxel-to-voxel connectivity was observed in PTSD patients compared to HCs and MDD patients. CONCLUSIONS: FMRI results therefore suggested a common deficit of depression and anxiety symptomatology reflected by reduced activation in right IFG during cognitive reappraisal as well as diagnosis specific effects in patients with PTSD based on seed-to-voxel and voxel-to-voxel connectivity showing an overactive and hyperconnected salience network. Findings highlight the role of transdiagnostic research to identify disorder specific brain patterns as well as patterns common across disorders.

Data-Driven Approach to the Analysis of Real-Time FMRI Neurofeedback Data: Disorder-Specific Brain Synchrony in PTSD.

Brain-computer interfaces (BCIs) can be used in real-time fMRI neurofeedback (rtfMRI NF) investigations to provide feedback on brain activity to enable voluntary regulation of the blood-oxygen-level dependent (BOLD) signal from localized brain regions. However, the temporal pattern of successful self-regulation is dynamic and complex. In particular, the general linear model (GLM) assumes fixed temporal model functions and misses other dynamics. We propose a novel data-driven analyses approach for rtfMRI NF using intersubject covariance (ISC) analysis. The potential of ISC was examined in a reanalysis of data from 21 healthy individuals and nine patients with post-traumatic stress-disorder (PTSD) performing up-regulation of the anterior cingulate cortex (ACC). ISC in the PTSD group differed from healthy controls in a network including the right inferior frontal gyrus (IFG). In both cohorts, ISC decreased throughout the experiment indicating the development of individual regulation strategies. ISC analyses are a promising approach to reveal novel information on the mechanisms involved in voluntary self-regulation of brain signals and thus extend the results from GLM-based methods. ISC enables a novel set of research questions that can guide future neurofeedback and neuroimaging investigations.

Objects seen as scenes: Neural circuitry for attending whole or parts.

Depending on our goals, we pay attention to the global shape of an object or to the local shape of its parts, since it's difficult to do both at once. This typically effortless process can be impaired in disease. However, it is not clear which cortical regions carry the information needed to constrain shape processing to a chosen global/local level. Here, novel stimuli were used to dissociate functional MRI responses to global and local shapes. This allowed identification of cortical regions containing information about level (independent from shape). Crucially, these regions overlapped part of the cortical network implicated in scene processing. As expected, shape information (independent of level) was mainly located in category-selective areas specialized for object- and face-processing. Regions with the same informational profile were strongly linked (as measured by functional connectivity), but were weak when the profiles diverged. Specifically, in the ventral-temporal-cortex (VTC) regions favoring level and shape were consistently separated by the mid-fusiform sulcus (MFS). These regions also had limited crosstalk despite their spatial proximity, thus defining two functional pathways within VTC. We hypothesize that object hierarchical level is processed by neural circuitry that also analyses spatial layout in scenes, contributing to the control of the spatial-scale used for shape recognition. Use of level information tolerant to shape changes could guide whole/part attentional selection but facilitate illusory shape/level conjunctions under impoverished vision.

Recurrent Activation of Neural Circuits during Attention to Global and Local Visual Information.

The attentional selection of different hierarchical level within compound (Navon) figures has been studied with event related potentials (ERPs), by controlling the ERPs obtained during attention to the global or the local echelon. These studies, using the canonical Navon figures, have produced contradictory results, with doubts regarding the scalp distribution of the effects. Moreover, the evidence about the temporal evolution of the processing of these two levels is not clear. Here, we unveiled global and local letters at distinct times, which enabled separation of their ERP responses. We combine this approach with the temporal generalization methodology, a novel multivariate technique which facilitates exploring the temporal structure of these ERPs. Opposite lateralization patterns were obtained for the selection negativities generated when attending global and local distracters (D statistics, p < .005), with maxima in right and left occipito-temporal scalp regions, respectively (η2 = .111, p < .01; η2 = .042, p < .04). However, both discrimination negativities elicited when comparing targets and distractors at the global or the local level were lateralized to the left hemisphere (η2 = .25, p < .03 and η2 = .142, p < .05 respectively). Recurrent activation patterns were found for both global and local stimuli, with scalp topographies corresponding to early preparatory stages reemerging during the attentional selection process, thus indicating recursive attentional activation. This implies that selective attention to global and local hierarchical levels recycles similar neural correlates at different time points. These neural correlates appear to be mediated by visual extra-striate areas.

Dynamic Causal Modeling of Preclinical Autosomal-Dominant Alzheimer's Disease.

Dynamic causal modeling (DCM) is a framework for making inferences about changes in brain connectivity using neuroimaging data. We fitted DCMs to high-density EEG data from subjects performing a semantic picture matching task. The subjects are carriers of the PSEN1 mutation, which leads to early onset Alzheimer's disease, but at the time of EEG acquisition in 1999, these subjects were cognitively unimpaired. We asked 1) what is the optimal model architecture for explaining the event-related potentials in this population, 2) which connections are different between this Presymptomatic Carrier (PreC) group and a Non-Carrier (NonC) group performing the same task, and 3) which network connections are predictive of subsequent Mini-Mental State Exam (MMSE) trajectories. We found 1) a model with hierarchical rather than lateral connections between hemispheres to be optimal, 2) that a pathway from right inferotemporal cortex (IT) to left medial temporal lobe (MTL) was preferentially activated by incongruent items for subjects in the PreC group but not the NonC group, and 3) that increased effective connectivity among left MTL, right IT, and right MTL was predictive of subsequent MMSE scores.

Recurrent activation of neural circuits during attention to global and local visual information

The attentional selection of different hierarchical level within compound (Navon) figures has been studied with event related potentials (ERPs), by controlling the ERPs obtained during attention to the global or the local echelon. These studies, using the canonical Navon figures, have produced contradictory results, with doubts regarding the scalp distribution of the effects. Moreover, the evidence about the temporal evolution of the processing of these two levels is not clear. Here, we unveiled global and local letters at distinct times, which enabled separation of their ERP responses. We combine this approach with the temporal generalization methodology, a novel multivariate technique which facilitates exploring the temporal structure of these ERPs. Opposite lateralization patterns were obtained for the selection negativities generated when attending global and local distracters (D statistics, p < .005), with maxima in right and left occipito-temporal scalp regions, respectively (η2 = .111, p < .01; η2 = .042, p < .04). However, both discrimination negativities elicited when comparing targets and distractors at the global or the local level were lateralized to the left hemisphere (η2 = .25, p < .03 and η2 = .142, p < .05 respectively). Recurrent activation patterns were found for both global and local stimuli, with scalp topographies corresponding to early preparatory stages reemerging during the attentional selection process, thus indicating recursive attentional activation. This implies that selective attention to global and local hierarchical levels recycles similar neural correlates at different time points. These neural correlates appear to be mediated by visual extra-striate areas

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Asynchronous presentation of global and local information reveals effects of attention on brain electrical activity specific to each level.

The neural basis of selective attention within hierarchically organized Navon figures has been extensively studied with event related potentials (ERPs), by contrasting responses obtained when attending the global and the local echelons. The findings are inherently ambiguous because both levels are always presented together. Thus, only a mixture of the brain responses to two levels can be observed. Here, we use a method that allows unveiling of global and local letters at distinct times, enabling estimation of separate ERPs related to each level. Two interspersed oddball streams were presented, each using letters from one level and comprised of frequent distracters and rare targets. Previous work and our Experiment 1 show that it is difficult to divide attention between two such streams of stimuli. ERP recording in Experiment 2 evinced an early selection negativity (SN, with latencies to the 50% area of about 266 ms for global distracters and 276 ms for local distracters) that was larger for attended relative to unattended distracters. The SN was larger over right posterior occipito-temporal derivations for global stimuli and over left posterior occipito-temporal derivations for local stimuli (although the latter was less strongly lateralized). A discrimination negativity (DN, accompanied by a P3b) was larger for attended targets relative to attended distracters, with latencies to the 50% area of about 316 ms for global stimuli and 301 ms for local stimuli, which presented a similar distribution for both levels over left temporo-parietal electrodes. The two negativities apparently index successive stages in the processing of a selected level within a compound figure. By resolving the ambiguity of traditional designs, our method allowed us to observe the effects of attention for each hierarchical level on its own.

Attentional selection of levels within hierarchically organized figures is mediated by object-files.

Objects frequently have a hierarchical organization (tree-branch-leaf). How do we select the level to be attended? This has been explored with compound letters: a global letter built from local letters. One explanation, backed by much empirical support, is that attentional competition is biased toward certain spatial frequency (SF) bands across all locations and objects (a SF filter). This view assumes that the global and local letters are carried respectively by low and high SF bands, and that the bias can persist over time. Here we advocate a complementary view in which perception of hierarchical level is determined by how we represent letters in object-files. Although many properties bound to an object-file (i.e., position, color, even shape) can mutate without affecting its persistence over time, we posit that same object-file cannot be used to store information from different hierarchical levels. Thus, selection of level would be independent from locations but not from the way objects are represented at each moment. These views were contrasted via an attentional blink paradigm that presented letters within compound figures, but only one level at a time. Attending to two letters in rapid succession was easier if they were at the same-compared to different-levels, as predicted by both accounts. However, only the object-file account was able to explain why it was easier to report two targets on the same moving object compared to the same targets on distinct objects. The interference of different masks on target recognition was also easier to predict by the object-file account than by an SF filter. The methods introduced here allowed us to investigate attention to hierarchical levels and to object-files within the same empirical framework. The data suggests that SF information is used to structure the internal organization of object representations, a process understood best by integrating object-file theory with previous models of hierarchical perception.