The folding fingerprint of visual cortex reveals the timing of human V1 and V2

Primate neocortex contains over 30 visual areas. Recent techniques such as functional magnetic resonance imaging (fMRI) have successfully identified many of these areas in the human brain, but have been of limited value for revealing the temporal dynamics between adjacent visual areas, a critical component of understanding visual cognition. The voltages recorded at the scalp, electroencephalography (EEG), is a direct measure of neural activity that reflects the summed activity across all brain areas. Identifying the cortical sources that contribute to the EEG is a difficult problem. We developed an anatomically constrained dipole search method that solves the traditional problems by combining fMRI, EEG and many stimuli that activate small cortical regions. The method provides a means to validate the extracted waveforms. Both V1 and V2 waveforms have similar onset latencies as well as dynamics that can explain previous controversial findings about the responses of these areas

Mind over chatter: plastic up-regulation of the fMRI alertness network by EEG neurofeedback

EEG neurofeedback (NFB) is a brain-computer interface (BCI) approach used to shape brain oscillations by means of real-time feedback from the electroencephalogram (EEG), which is known to reflect neural activity across cortical networks. Although NFB is being evaluated as a novel tool for treating brain disorders, evidence is scarce on the mechanism of its impact on brain function. In this study with 34 healthy participants, we examined whether, during the performance of an attentional auditory oddball task, the functional connectivity strength of distinct fMRI networks would be plastically altered after a 30-min NFB session of alpha-band reduction (n=17) versus a sham-feedback condition (n=17). Our results reveal that compared to sham, NFB induced a specific increase of functional connectivity within the alertness/salience network (dorsal anterior and mid cingulate), which was detectable 30 minutes after termination of training. Crucially, these effects were significantly correlated with reduced mind-wandering 'on-task' and were coupled to NFB-mediated resting state reductions in the alpha-band (8-12 Hz). No such relationships were evident for the sham condition. Although group default-mode network (DMN) connectivity was not significantly altered following NFB, we observed a positive association between modulations of resting alpha amplitude and precuneal connectivity, both correlating positively with frequency of mind-wandering. Our findings demonstrate a temporally direct, plastic impact of NFB on large-scale brain functional networks, and provide promising neurobehavioral evidence supporting its use as a noninvasive tool to modulate brain function in health and disease

With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging

In patients with medically refractory focal epilepsy who are candidates for epilepsy surgery, concordant non-invasive neuroimaging data are useful to guide invasive electroencephalographic recordings or surgical resection. Simultaneous electroencephalography and functional magnetic resonance imaging recordings can reveal regions of haemodynamic fluctuations related to epileptic activity and help localize its generators. However, many of these studies (40-70%) remain inconclusive, principally due to the absence of interictal epileptiform discharges during simultaneous recordings, or lack of haemodynamic changes correlated to interictal epileptiform discharges. We investigated whether the presence of epilepsy-specific voltage maps on scalp electroencephalography correlated with haemodynamic changes and could help localize the epileptic focus. In 23 patients with focal epilepsy, we built epilepsy-specific electroencephalographic voltage maps using averaged interictal epileptiform discharges recorded during long-term clinical monitoring outside the scanner and computed the correlation of this map with the electroencephalographic recordings in the scanner for each time frame. The time course of this correlation coefficient was used as a regressor for functional magnetic resonance imaging analysis to map haemodynamic changes related to these epilepsy-specific maps (topography-related haemodynamic changes). The method was first validated in five patients with significant haemodynamic changes correlated to interictal epileptiform discharges on conventional analysis. We then applied the method to 18 patients who had inconclusive simultaneous electroencephalography and functional magnetic resonance imaging studies due to the absence of interictal epileptiform discharges or absence of significant correlated haemodynamic changes. The concordance of the results with subsequent intracranial electroencephalography and/or resection area in patients who were seizure free after surgery was assessed. In the validation group, haemodynamic changes correlated to voltage maps were similar to those obtained with conventional analysis in 5/5 patients. In 14/18 patients (78%) with previously inconclusive studies, scalp maps related to epileptic activity had haemodynamic correlates even when no interictal epileptiform discharges were detected during simultaneous recordings. Haemodynamic changes correlated to voltage maps were spatially concordant with intracranial electroencephalography or with the resection area. We found better concordance in patients with lateral temporal and extratemporal neocortical epilepsy compared to medial/polar temporal lobe epilepsy, probably due to the fact that electroencephalographic voltage maps specific to lateral temporal and extratemporal epileptic activity are more dissimilar to maps of physiological activity. Our approach significantly increases the yield of simultaneous electroencephalography and functional magnetic resonance imaging to localize the epileptic focus non-invasively, allowing better targeting for surgical resection or implantation of intracranial electrode array

Minor and Unsystematic Cortical Topographic Changes of Attention Correlates between Modalities

In this study we analyzed the topography of induced cortical oscillations in 20 healthy individuals performing simple attention tasks. We were interested in qualitatively replicating our recent findings on the localization of attention-induced beta bands during a visual task [1], and verifying whether significant topographic changes would follow the change of attention to the auditory modality. We computed corrected latency averaging of each induced frequency bands, and modeled their generators by current density reconstruction with Lp-norm minimization. We quantified topographic similarity between conditions by an analysis of correlations, whereas the inter-modality significant differences in attention correlates were illustrated in each individual case. We replicated the qualitative result of highly idiosyncratic topography of attention-related activity to individuals, manifested both in the beta bands, and previously studied slow potential distributions [2]. Visual inspection of both scalp potentials and distribution of cortical currents showed minor changes in attention-related bands with respect to modality, as compared to the theta and delta bands, known to be major contributors to the sensory-related potentials. Quantitative results agreed with visual inspection, supporting to the conclusion that attention-related activity does not change much between modalities, and whatever individual changes do occur, they are not systematic in cortical localization across subjects. We discuss our results, combined with results from other studies that present individual data, with respect to the function of cortical association areas

Spatiotemporal Analysis of Multichannel EEG: CARTOOL

This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way

A Novel Synergistic Model Fusing Electroencephalography and Functional Magnetic Resonance Imaging for Modeling Brain Activities

Study of the human brain is an important and very active area of research. Unraveling the way the human brain works would allow us to better understand, predict and prevent brain related diseases that affect a significant part of the population. Studying the brain response to certain input stimuli can help us determine the involved brain areas and understand the mechanisms that characterize behavioral and psychological traits. In this research work two methods used for the monitoring of brain activities, Electroencephalography (EEG) and functional Magnetic Resonance (fMRI) have been studied for their fusion, in an attempt to bridge together the advantages of each one. In particular, this work has focused in the analysis of a specific type of EEG and fMRI recordings that are related to certain events and capture the brain response under specific experimental conditions. Using spatial features of the EEG we can describe the temporal evolution of the electrical field recorded in the scalp of the head. This work introduces the use of Hidden Markov Models (HMM) for modeling the EEG dynamics. This novel approach is applied for the discrimination of normal and progressive Mild Cognitive Impairment patients with significant results. EEG alone is not able to provide the spatial localization needed to uncover and understand the neural mechanisms and processes of the human brain. Functional Magnetic Resonance imaging (fMRI) provides the means of localizing functional activity, without though, providing the timing details of these activations. Although, at first glance it is apparent that the strengths of these two modalities, EEG and fMRI, complement each other, the fusion of information provided from each one is a challenging task. A novel methodology for fusing EEG spatiotemporal features and fMRI features, based on Canonical Partial Least Squares (CPLS) is presented in this work. A HMM modeling approach is used in order to derive a novel feature-based representation of the EEG signal that characterizes the topographic information of the EEG. We use the HMM model in order to project the EEG data in the Fisher score space and use the Fisher score to describe the dynamics of the EEG topography sequence. The correspondence between this new feature and the fMRI is studied using CPLS. This methodology is applied for extracting features for the classification of a visual task. The results indicate that the proposed methodology is able to capture task related activations that can be used for the classification of mental tasks. Extensions on the proposed models are examined along with future research directions and applications