Electrophysiological evidence of sustained spatial attention effects over anterior cortex:Possible contribution of the anterior insula

Spatial attention can improve performance in terms of speed and accuracy; this advantage may be mediated by brain processes at both poststimulus (reactive) and prestimulus (proactive) stages. Here, we studied how visuospatial attention affects both proactive and reactive brain functions using event-related potentials (ERPs). At reactive stage, effects of attention on parietal-occipital components are well documented; little data are available on anterior components. Seventeen participants performed simple and discriminative response tasks, while voluntarily and steadily attending either the left or right visual hemifield throughout one block. Response speed was faster for the attended side. At ERP level, attending to one hemifield did not produce lateralization of proactive components—that is, the BP and the pN. As for poststimulus components, we confirmed the well-known amplitude effects on the P1, N1, and P3. More interesting are results for the prefrontal components previously neglected in tasks modulating spatial attention. Previous studies suggest that these components reflect perceptual and sensory-motor awareness (pN1 and pP1 components), and stimulus-response mapping (pP2 component) associated to anterior insular activity. Spatial attention enhanced the pN1 and the pP1 amplitude but had no effect on the pP2. Overall, results extend knowledge on spatial attention, showing that sustained spatial attention affects the activity of anterior areas, such as the anterior insula, in addition to the known influence on occipital-parietal areas. Top-down spatial attention is likely mediated by increased sensory and sensory-motor awareness for attended events; this effect is evident in reactive, not proactive, brain activity.</p

State dependency of inhibitory control performance: an electrical neuroimaging study

Behavioral and brain responses to stimuli not only depend on their physical features but also on the individuals' neurocognitive states before stimuli onsets. While the influence of pre-stimulus fluctuations in brain activity on low-level perceptive processes is well established, the state dependency of high-order executive processes remains unclear. Using a classical inhibitory control Go/NoGo task, we examined whether and how fluctuations in the brain activity during the period preceding the stimuli triggering inhibition influenced inhibitory control performance. Seventeen participants completed the Go/NoGo task while 64-channel electroencephalogram was recorded. We compared the event-related potentials preceding the onset of the NoGo stimuli associated with inhibition failures false alarms (FA) vs. successful inhibition correct rejections (CR) with data-driven statistical analyses of global measures of the topography and strength of the scalp electric field. Distributed electrical source estimations were used to localize the origin of the event-related potentials modulations. We observed differences in the global field power of the event-related potentials (FA > CR) without concomitant topographic modulations over the 40 ms period immediately preceding NoGo stimuli. This result indicates that the same brain networks were engaged in the two conditions, but more strongly before FA than CR. Source estimations revealed that this effect followed from a higher activity before FA than CR within bilateral inferior frontal gyri and the right inferior parietal lobule. These findings suggest that uncontrolled quantitative variations in pre-stimulus activity within attentional and control brain networks influence inhibition performance. The present data thereby demonstrate the state dependency of cognitive processes of up to high- order executive levels

State dependency of inhibitory control performance: an electrical neuroimaging study

Behavioral and brain responses to stimuli not only depend on their physical features but also on the individuals' neurocognitive states before stimuli onsets. While the influence of pre-stimulus fluctuations in brain activity on low-level perceptive processes is well established, the state dependency of high-order executive processes remains unclear. Using a classical inhibitory control Go/NoGo task, we examined whether and how fluctuations in the brain activity during the period preceding the stimuli triggering inhibition influenced inhibitory control performance. Seventeen participants completed the Go/NoGo task while 64-channel electroencephalogram was recorded. We compared the event-related potentials preceding the onset of the NoGo stimuli associated with inhibition failures false alarms (FA) vs. successful inhibition correct rejections (CR) with data-driven statistical analyses of global measures of the topography and strength of the scalp electric field. Distributed electrical source estimations were used to localize the origin of the event-related potentials modulations. We observed differences in the global field power of the event-related potentials (FA > CR) without concomitant topographic modulations over the 40 ms period immediately preceding NoGo stimuli. This result indicates that the same brain networks were engaged in the two conditions, but more strongly before FA than CR. Source estimations revealed that this effect followed from a higher activity before FA than CR within bilateral inferior frontal gyri and the right inferior parietal lobule. These findings suggest that uncontrolled quantitative variations in pre-stimulus activity within attentional and control brain networks influence inhibition performance. The present data thereby demonstrate the state dependency of cognitive processes of up to high- order executive levels

State-Dependent Visual Processing

The temporal dynamics and anatomical correlates underlying human visual cognition are traditionally assessed as a function of stimulus properties and task demands. Any non-stimulus related activity is commonly dismissed as noise and eliminated to extract an evoked signal that is only a small fraction of the magnitude of the measured signal. We review studies that challenge this view by showing that non-stimulus related activity is not mere noise but that it has a well-structured organization which can largely determine the processing of upcoming stimuli. We review recent evidence from human electrophysiology that shows how different aspects of pre-stimulus activity such as pre-stimulus EEG frequency power and phase and pre-stimulus EEG microstates can determine qualitative and quantitative properties of both lower and higher-level visual processing. These studies show that low-level sensory processes depend on the momentary excitability of sensory cortices whereas perceptual processes leading to stimulus awareness depend on momentary pre-stimulus activity in higher-level non-visual brain areas. Also speed and accuracy of stimulus identification have likewise been shown to be modulated by pre-stimulus brain states

Dynamic Construction of Stimulus Values in the Ventromedial Prefrontal Cortex

Signals representing the value assigned to stimuli at the time of choice have been repeatedly observed in ventromedial prefrontal cortex (vmPFC). Yet it remains unknown how these value representations are computed from sensory and memory representations in more posterior brain regions. We used electroencephalography (EEG) while subjects evaluated appetitive and aversive food items to study how event-related responses modulated by stimulus value evolve over time. We found that value-related activity shifted from posterior to anterior, and from parietal to central to frontal sensors, across three major time windows after stimulus onset: 150–250 ms, 400–550 ms, and 700–800 ms. Exploratory localization of the EEG signal revealed a shifting network of activity moving from sensory and memory structures to areas associated with value coding, with stimulus value activity localized to vmPFC only from 400 ms onwards. Consistent with these results, functional connectivity analyses also showed a causal flow of information from temporal cortex to vmPFC. Thus, although value signals are present as early as 150 ms after stimulus onset, the value signals in vmPFC appear relatively late in the choice process, and seem to reflect the integration of incoming information from sensory and memory related regions

Electroencephalographic evidence of vector inversion in antipointing

Mirror-symmetrical reaching movements (i.e., antipointing) produce a visual-field-specific pattern of endpoint bias consistent with a perceptual representation of visual space (Heath et al. in Exp Brain Res 192:275-286, 2009a; J Mot Behav 41:383-392 2009b). The goal of the present investigation was to examine the concurrent behavioural and event-related brain potentials (ERP) of pro- and antipointing to determine whether endpoint bias in the latter task is related to a remapping of the environmental parameters of a target (i.e., vector inversion hypothesis) or a shift of visual attention from a veridical to a cognitively represented target location (i.e., reallocation of attention hypothesis). As expected, results for antipointing-but not propointing-yielded a visual-field-specific pattern of endpoint bias. In terms of the ERP findings, an early component (i.e., the N100) related to the orienting of visuospatial attention was comparable across pro- and antipointing. In contrast, a later occurring component (i.e., the P300) demonstrated a reliable between-task difference in amplitude. Notably, the P300 has been linked to the revision of a 'mental model' when a mismatch is noted between a stimulus and a required task goal (so-called context-updating). Thus, we propose that the between-task difference in the P300 indicates that antipointing is associated with a remapping of a target's veridical location in mirror-symmetrical space (i.e., vector inversion). Moreover, our combined behavioural and ERP findings provide evidence that vector inversion is mediated via perception-based visual networks

Dorsolateral Prefrontal Transcranial Direct Current Stimulation Modulates Language Processing but Does Not Facilitate Overt Second Language Word Production.

Word retrieval in bilingual speakers partly depends on executive control systems in the left prefrontal cortex - including dorsolateral prefrontal cortex (DLPFC). We tested the hypothesis that DLPFC modulates word production of words specifically in a second language (L2) by measuring the effects of anodal transcranial direct current stimulation (anodal-tDCS) over the DLPFC on picture naming and word translation and on event-related potentials (ERPs) and their sources. Twenty-six bilingual participants with "unbalanced" proficiency in two languages were given 20 min of 1.5 mA anodal or sham tDCS (double-blind stimulation design, counterbalanced stimulation order, 1-week intersession delay). The participants then performed the following tasks: verbal and non-verbal fluency during anodal-tDCS stimulation and first and second language (L1 and L2) picture naming and translation [forward (L1 → L2) and backward (L2 → L1)] immediately after stimulation. The electroencephalogram (EEG) was recorded during picture naming and translation. On the behavioral level, anodal-tDCS had an influence on non-verbal fluency but neither on verbal fluency, nor on picture naming and translation. EEG measures revealed significant interactions between Language and Stimulation on picture naming around 380 ms post-stimulus onset and Translation direction and Stimulation on translation around 530 ms post-stimulus onset. These effects suggest that L2 phonological retrieval and phoneme encoding are spatially and temporally segregated in the brain. We conclude that anodal-tDCS stimulation has an effect at a neural level on phonological processes and, critically, that DLPFC-mediated activation is a constraint on language production specifically in L2

Local spatial analysis: an easy-to-use adaptive spatial EEG filter

Spatial EEG filters are widely used to isolate event-related potential (ERP) components. The most commonly used spatial filters (e.g., the average reference and the surface Laplacian) are "stationary." Stationary filters are conceptually simple, easy to use, and fast to compute, but all assume that the EEG signal does not change across sensors and time. Given that ERPs are intrinsically nonstationary, applying stationary filters can lead to misinterpretations of the measured neural activity. In contrast, "adaptive" spatial filters (e.g., independent component analysis, ICA; and principal component analysis, PCA) infer their weights directly from the spatial properties of the data. They are, thus, not affected by the shortcomings of stationary filters. The issue with adaptive filters is that understanding how they work and how to interpret their output require advanced statistical and physiological knowledge. Here, we describe a novel, easy-to-use, and conceptually simple adaptive filter (local spatial analysis, LSA) for highlighting local components masked by large widespread activity. This approach exploits the statistical information stored in the trial-by-trial variability of stimulus-evoked neural activity to estimate the spatial filter parameters adaptively at each time point. Using both simulated data and real ERPs elicited by stimuli of four different sensory modalities (audition, vision, touch, and pain), we show that this method outperforms widely used stationary filters and allows to identify novel ERP components masked by large widespread activity. Implementation of the LSA filter in MATLAB is freely available to download.NEW & NOTEWORTHY EEG spatial filtering is important for exploring brain function. Two classes of filters are commonly used: stationary and adaptive. Stationary filters are simple to use but wrongly assume that stimulus-evoked EEG responses (ERPs) are stationary. Adaptive filters do not make this assumption but require solid statistical and physiological knowledge. Bridging this gap, we present local spatial analysis (LSA), an adaptive, yet computationally simple, spatial filter based on linear regression that separates local and widespread brain activity (https://www.iannettilab.net/lsa.html or https://github.com/rorybufacchi/LSA-filter)

Biophysical Source Modeling of Some Exogenous and Endogenous Components of the Human Event-Related Potential

Methods of dipole localization were applied to human scalp-recorded electrical activity associated with a simple auditory cognitive discrimination task. Human neuroanatomy and neurophysiology were reviewed from a biophysical standpoint in order to describe the probable neurogenesis of electrical activity in the brain and on the surface of the head. Topographic electroencephalography (EEG) analysis and source localization methods were historically reviewed in detail, followed by a brief review of the history of non-invasive evoked potential (EP) and magnetic field measurements of human central nervous system activity. Four well known simple cognitive tasks were considered that were known to elicit non-obligatory brain responses, and the odd-ball task chosen. Three subjects listened to a series of two tones, one frequent and one rare, and counted the rare tones. During task performance, 40 to 46 channels of EEG activity were recorded from their scalps. From the EEG data, average evoked potentials (aEP) were calculated for the frequent and rare conditions. From these a difference response was calculated. All three of these EPs were plotted as equipotential maps over a schematic of a head for topographic display and the major distribution features discussed. These aEPs and maps matched those previously reported in the literature. From estimates of the spatial electrical power over the head, four peak components were selected for analysis by equivalent source modeling (ESM). These were designated the FP40, FP100, FP200, and FP350, where FP stands for field power. ESM demonstrated that one centrally located point dipole or two bilaterally symmetric dipoles could model the empirical data quite well. These results were discussed in relation to other topographic studies, as well as studies of intracranial recordings, lesions, and animal models. The source locations found were consistent with auditory cortical locations for the obligatory sensory peaks (FP40, FP100, FP200) and with brainstem locations as the source of the FP350 cognitive event-related peak.</p

Functional Neuroanatomy of Dynamic Visuo-Spatial Imagery

The aim of this thesis was the examination of the neural bases of dynamic visuo-spatial imagery. In addition to the assessment of brain activity during dy-namic visuo-spatial imagery using single-trial functional magnetic resonance im-aging (fMRI) and slow cortical potentials (SCPs), several methodological issues have been investigated. The theoretical part of this thesis consists of a selective overview of fMRI and SCPs, and of the advantages of their combination for functional neuroimaging (chapter 2). The methodological and empirical chapters include: Ø the presentation of a new, highly accurate and practicable method for the co-registration of MRI- and EEG-data (chapter 3), Ø the description of the increase in the accuracy of SCP mapping resulting from the use of individual electrode coordinates and realistic head models (chapter 4), Ø the description of regional differences in the consistency of brain activity across several executions of the same task type, as assessed by a new analysis con-cept based on single-trial fMRI data (chapter 5), Ø the demonstration of the involvement of premotor regions in dynamic visuo-spatial imagery, as assessed via a combination of single-trial fMRI and SCPs (chapter 6), Ø the description of a combined fMRI-SCP investigation in which earlier findings concerning individual differences in neural efficiency during dynamic imagery could not be replicated (chapter 7)