Abstract: There have been several studies supporting the notion of a ventral-dorsal distinction in the primate cortex for visual object processing, whereby the ventral stream specializes in object identification, and the dorsal stream is engaged during object localization and interaction. There is also a growing body of evidence supporting a ventral stream that specializes in lexical (i.e., whole-word) reading, and a dorsal stream that is engaged during sub-lexical reading (i.e., phonetic decoding). Here, we consider the extent to which word-reading processes are located in regions either intersecting with, or unique from, regions that sub-serve object processing along these streams. Object identification was contrasted with lexical-based reading, and object interaction processing (i.e., deciding how to interact with an object) was contrasted with sub-lexical reading. Our results suggest that object identification and lexical-based reading are largely ventral and modular, showing mainly unique regions of activation (parahippocampal and occipital-temporal gyri function associated with object identification, and lingual, lateral occipital, and posterior inferior temporal gyri function associated with lexical-based reading) and very little shared activation (posterior inferior frontal gyrus). Object interaction processing and phonetic decoding are largely dorsal, and show both modular regions of activation (more lateralized to the dorsal-frontal right hemisphere for pseudohomophone naming, and more to the dorsal-frontal left hemisphere for the object interaction task) as well as significant shared regions of processing (precentral gyri, left inferior frontal cortex, left postcentral gyrus, left lateral occipital cortex, and superior posterior temporal gyri). Given that the perceptual experimental conditions show primarily modular and very little shared processing, whereas the analytical conditions show both substantial modular and shared processing, we discuss a reconsideration of "modularity of mind" which involves a continuum between strictly modular processing and varying degrees of shared processing, and which also depends on the nature of the tasks compared (i.e., perceptual versus analytical).

Abstract: Acoustic complexity of a stimulus has been shown to modulate the electromagnetic N1 (latency ∼110 ms) and P2 (latency 190 ms) auditory evoked responses. We compared the relative sensitivity of electroencephalography (EEG) and magnetoencephalography (MEG) to these neural correlates of sensation. Simultaneous EEG and MEG were recorded while participants listened to three variants of a piano tone. The piano stimuli differed in their number of harmonics: the fundamental frequency (f0), only, or f0 and the first two or eight harmonics. The root mean square (RMS) of the amplitude of P2 but not N1 increased with spectral complexity of the piano tones in EEG and MEG. The RMS increase for P2 was more prominent in EEG than MEG, suggesting important radial sources contributing to the P2 only in EEG. Source analysis revealing contributions from radial and tangential sources was conducted to test this hypothesis. Source waveforms revealed a significant increase in the P2 radial source amplitude in EEG with increased spectral complexity of piano tones. The P2 of the tangential source waveforms also increased in amplitude with increased spectral complexity in EEG and MEG. The P2␣auditory evoked response is thus represented by both tangential (gyri) and radial (sulci) activities. The radial contribution is expressed preferentially in EEG, highlighting the importance of combining EEG with MEG where complex source configurations are suspected.

Abstract: Static hemodynamic or neuroelectric images of brain regions activated during particular tasks do not convey the information of how these regions communicate to each other. Cortical connectivity estimation aims at describing these interactions as connectivity patterns which hold the direction and strength of the information flow between cortical areas. In this study, we attempted to estimate the causality between distributed cortical systems during a movement volition task in preparation for execution of simple movements by a group of normal healthy subjects and by a group of Spinal Cord Injured (SCI) patients. To estimate the causality between the spatial distributed patterns of cortical activity in the frequency domain, we applied a series of processing steps on the recorded EEG data. From the high-resolution EEG recordings we estimated the cortical waveforms for the regions of interest (ROIs), each representing a selected sensor group population. The solutions of the linear inverse problem returned a series of cortical waveforms for each ROI considered and for each trial analyzed. For each subject, the cortical waveforms were then subjected to Independent Component Analysis (ICA) pre-processing. The independent components obtained by the application of the ThinICA algorithm were further processed by a Partial Directed Coherence algorithm, in order to extract the causality between spatial cortical patterns of the estimated data. The source-target cortical dependencies found in the group of normal subjects were relatively similar in all frequency bands analyzed. For the normal subjects we observed a common source pattern in an ensemble of cortical areas including the right parietal and right lip primary motor areas and bilaterally the primary foot and posterior SMA areas. The target of this cortical network, in the Granger-sense of causality, was shown to be a smaller network composed mostly by the primary foot motor areas and the posterior SMA bilaterally. In the case of the SCI population, both the source and the target cortical patterns had larger sizes than in the normal population. The source cortical areas included always the primary foot and lip motor areas, often bilaterally. In addition, the right parietal area and the bilateral premotor area 6 were also involved. Again, the patterns remained substantially stable across the different frequency bands analyzed. The target cortical patterns observed in the SCI population had larger extensions when compared to the normal ones, since in most cases they involved the bilateral activation of the primary foot movement areas as well as the SMA, the primary lip areas and the parietal cortical areas.

Abstract: EEG background activity was investigated by low resolution brain electromagnetic tomography (LORETA) to test the diurnal alterations of brain electrical activity in healthy adults. Fourteen right-handed healthy male postgraduate medical students were examined four times (8 a.m., 2 p.m., 8 p.m. and next day 2 p.m.). LORETA was computed to localize generators of EEG frequency components. Comparing the EEG activity between 2 p.m. and 8 a.m., increased activity was seen (1) in theta band (6.5-8 Hz) in the left prefrontal, bilateral mesial frontal and anterior cingulate cortex; (2) in alpha2 band (10.5-12 Hz) in the bilateral precuneus and posterior parietal cortex as well as in the right temporo-occipital cortex; (3) in beta1-2-3 band (12.5-30 Hz) in the right hippocampus and parieto-occipital cortex, left frontal and bilateral cingulate cortex. Comparing the brain activity between 8 p.m. and 8 a.m., (1) midline theta activity disappeared; (2) increased alpha2 band activity was seen in the left hemisphere (including the left hippocampus); and (3) increased beta bands activity was found over almost the whole cortex (including both of hippocampi) with the exception of left temporo-occipital region. There were no significant changes between the background activities of 2 p.m. and next day 2 p.m. Characteristic distribution of increased activity of cortex (no change in delta band, and massive changes in the upper frequency bands) may mirror increasing activation of reticular formation and thus evoked thalamocortical feedback mechanisms as a sign of maintenance of arousal.

Abstract: We investigated the variability of electrode positions for a multi-channel, custom electrode cap placed onto participants’ heads without taking scalp measurements. The electrode positions were digitized in a three-dimensional space for 10 young adult participants on three separate occasions. Positional variability was determined for 15 selected electrodes within the three-dimensional preauricular-nasion (PAN) coordinate system and from this system, angular coordinate variability was also determined. The standard deviations of the 15 selected electrodes ranged from 3.0 to 12.7 mm in the PAN system. These data resulted in a variability of 2.0° to 10.4° among the angular coordinates. The measurements indicated slightly greater variability of electrode positions compared to studies when electrodes were placed using scalp measurements. The implication of this study is that the use of electrode caps may not be appropriate when electroencephalographic (EEG) or evoked potential (EP) techniques depend on accurate electrode placement. Additionally, if a longitudinal study is performed, electrode locations should be checked to ensure that they conform with previous sessions.

Abstract: We recorded event-related potentials (ERPs) to investigate the interhemispheric difference of the N170 component for upright and inverted face perception in detail in fifteen healthy subjects. This is the first ERP study focusing on interhemispheric differences for face perception by showing faces in the hemifield. The face inversion effect, the prolonged latency and enhanced amplitude were found in both hemispheres. We found that the peak latency of the N170 following both upright and inverted face stimulation showed no significant difference between each hemisphere, though the N170 latency for the inverted face in the left hemisphere was shorter than that in the right hemisphere. The N170 recorded from the hemisphere ipsilateral to the stimulated hemifield showed unique findings. The interhemispheric time difference of the N170 between the right and the left hemispheres when the inverted face was presented in the left hemifield was significantly shorter than in the other three conditions. This unique finding may indicate that the conduction time from the right to the left for inverted face perception is faster than the other conditions, or that the left hemisphere specifically processed the inverted face very rapidly after receiving signals from the right hemisphere. If the N170 was generated by some, at least two, temporally overlapping activities, the different style of a summation of these activities may cause the unique findings found in this study. In conclusion, by presenting face stimuli in the hemifields, we could identify several new findings regarding the N170 component related to the face inversion effect.

Abstract: Previous studies suggested that there exists different neural networks for different frequency bands of steady-state visual evoked potential (SSVEP). What is the effect of the same cognitive task on different frequency SSVEPs? In this work, when a subject was conducting a graded memory task, a 8.3 or 20 Hz flicker was used as a background stimulation. The recorded EEGs were analyzed by the method of steady-state probe topography (SSPT), the results showed that SSVEPs under these two flicker conditions were similar to each other in the various stages of memory process, and were similar to the result of a high alpha band SSVEP as reported before. However, the SSVEP amplitude and latency in the lower frequency band is more clear and stable than that in the higher frequency band. These results suggest that the same cognitive task affects the different frequency SSVEP in a similar way, and the low frequency flicker is a better choice than the high frequency one in such as working memory study.

Abstract: It would be of the utmost interest to map correlated sources in the working human brain by Event-Related Potentials (ERPs). This work is to develop a new method to map correlated neural sources based on the time courses of the scalp ERPs waveforms. The ERP data are classified first by k-means cluster analysis, and then the Correlation Coefficients (CC) between the original data of each electrode channel and the time course of each cluster centroid are calculated and utilized as the mapping variable on the scalp surface. With a normalized 4-concentric-sphere head model with radius 1, the performance of the method is evaluated by simulated data. CC, between simulated four sources (s 1–s 4) and the estimated cluster centroids (c 1–c 4), and the distances (Ds), between the scalp projection points of the s 1–s 4 and that of the c 1–c 4, are utilized as the evaluation indexes. Applied to four sources with two of them partially correlated (with maximum mutual CC = 0.4892), CC (Ds) between s 1–s 4 and c 1–c 4 are larger (smaller) than 0.893 (0.108) for noise levels NSR≤ 0.2; Applied to four sources with two of them completely correlated, CC (Ds) between s 1–s 4 and c 1–c 4 are larger (smaller) than 0.97367 (0.1898) for a random noise level NSR≤ 0.2; Applied to 128, 64 and 32 recording electrodes, CC (Ds) between s 1–s 4 and c 1–c 4 are larger (smaller) than 0.9557 (0.4251) for a random noise level NSR = 0.15; And applied to the cases of spatially overlapped scalp activities, CC (Ds) between s 1–s 4 and c 1–c 4 are larger (smaller) than 0.9083 (0.4329) for a random noise level NSR = 0.15. Finally, the method successfully decomposed the ERPs collected in a spatial selective attention experiment into three clusters located at left, right occipital and frontal. The estimated vectors of the contra-occipital area demonstrate that attention to the stimulus location produces increased amplitude of the P1 and N1 components over the contra-occipital scalp. The estimated vector in the frontal area displays two large processing negativity waves around 100 ms and 250 ms when subjects are attentive, and there is a small negative wave around 140 ms and a P300 when subjects are unattentive. The results of simulations and real Visual Evoked Potentials (VEPs) data demonstrate the validity of the method in mapping correlated sources. This method may be an objective, heuristic and important tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.

Abstract: Several fMRI studies have been performed to detect the neural correlates of stable bimanual coordination patterns in humans. Only few of those studies were accompanied by the on-line recording of the relative phase of fingers or hands, but none with high space and time resolutions. Conversely, the high-resolution recording of fingers' kinematics during fMRI would permit the quanti- fication of the instantaneous fingers' positions, from which the instant at which transitions between different bimanual coordination patterns occur might be detected. This infor- mation could then be used to analyze fMRI data and detect the neural correlates of pattern transitions. We describe an a-magnetic optic-mechanical device (AMOMeD) able to monitor the fingers' positions during fMRI studies on bimanual coordination with 2 mm space resolution and 1 ms time resolution. From the instantaneous fingers' positions (recorded with an optical fiber system and a dedicated acquisition system), the oscillation amplitude, frequency, velocity and relative phase of fingers' are cal- culated. The signal from the fMRI trigger can be acquired simultaneously to synchronize the behavioral outcomes with the fMRI analysis. The results of our study show that this device does not affect fMRI signals, and that fMRI data can be processed using the simultaneous behavioral infor- mation to detect the brain areas activated during the tran- sitions between different bimanual coordination patterns.

Abstract: Freeman and Baird (5; Freeman WJ, Baird B. Behav Neurosci 1987;101:393-408) recorded from the sur- face of the brain in waking rabbits and found spatial patterns of voltage that covaried with sensory experience. We sim- ulate mathematically the electric fields produced by radial dipoles in cortical gyri and show that patterns with the spatial frequencies observed by Freeman and Baird could be pro- duced by cortical dipoles spaced 3 mm apart. We further calculate that to resolve the patterns produced by such dipole arrays, it is necessary to record less than 2.5 mm above the surface of the cortex. High-pass spatial filters increase this distance to 4.5 mm. Since the human scalp is 15-16 mm above the brain, we conclude that spatial patterns of voltage covarying with sensation are unlikely to be detectable in scalp records. If such patterns do exist in humans, dural or sub-dural electrode arrays, with an inter-electrode spacing of 1 mm or less, will be necessary to record them.

Abstract: The study of large-scale interactions from magnetoencephalographic data based on the magnitude of the complex coherence computed at channel level is a widely used method to track the coupling between neural signals. Traditionally, a measure based on the magnitude of the complex coherence estimated by Fourier analysis, has been used under the assumption that the neural signals are stationary. Here, we split the complex coherence in its real and imaginary parts and focus on the latter with the advantage that the imaginary part is insensitive to spurious connectivity resulting from volume conducted “self interaction”. Furthermore, interacting sources alone contribute to a non-vanishing imaginary part of the complex coherence whereas the contribute of non-interacting sources is also mapped from the magnitude of the complex coherence. Since it has been extensively shown that non-stationary stochastic processes contribute to the generation of neural signals, it is fundamental to be able to define interaction measures that are able to follow the temporal variations in the coupling between neural signals. To this purpose time–frequency domain techniques to estimate the magnitude of the complex coherence have been developed in the past decades. Similarly, we extend the analysis of the imaginary part of complex coherence to the time–frequency domain, by using the short-time Fourier transform to analyze the complex coherence as a function of time. In this way, it is possible to get an indication about the dynamic of the underlying source interaction pattern by looking at channel level interactions without the bias introduced by artifactual self-interaction by volume conduction or by the contribute of non-interacting sources. Furthermore, the corresponding imaginary part of the cross-spectrogram can be used to estimate interactions on a source level by localizing pools of sources interacting at a given frequency and by characterizing their dynamics. The method has been applied to magnetoencephalographic data from a cross-modal visual auditory stimulation and provided evidence for the involvement of temporal and occipital areas in the integrated information processing for simultaneous audio-visual stimulation. Furthermore, the source interaction pattern shows a variation in time that reflects a dynamical synchronization of the involved brain sources in the frequency bands of interest.

Abstract: In this paper, the temporal pattern of activity and approximate locations of brain areas related to selective attention and visual working memory processes were studied with event related potential (ERP) recordings in healthy humans. Three experimental series included pairs of the following conditions: Face comparison (familiar faces), Pattern comparison (abstract dot patterns), and Passive viewing. Participants compared pairs of consecutive targets presented in composite images on a computer screen. Spatio-temporal multiple dipole models were developed for 128-channel ERPs. Keeping dipole locations and orientations constant, we compared the source activities for ERPs recorded (1) in different tasks for task-specificity of activations, (2) after the first and second stimuli in the pair, i.e. on the encoding and comparison stages of the task, and (3) after the first stimulus in different series to compare encoding in different conditions. Sources located in the inferotemporal brain areas, especially in the left hemisphere, showed increased activity after 200 ms from the first stimulus onset that may indicate encoding into visual working memory. The anterior sources, located near midline and showing activity around or after 300 ms, presumably reflect non-specific memory processes and attentional control. Major task-specific differences were observed in the temporo-parieto-occipital region in 250-500 ms.

Abstract: The activity of cortical neurons is influenced by retinal stimulus location and temporal modulation. We investigated how reversal frequency of black-and-white checkerboard patterns presented in different parts of the visual field affects evoked potential topography. Visual evoked potentials were recorded from an array of 16 electrodes over the occipital cortex in 12 healthy adults. A checkerboard reversal stimulus (40' check size) was presented with frequencies between 1.95 reversals/s and 7.81 reversals/s in the center or in the left or right hemiretina. Evoked potential fields displayed the well-known components of pattern reversal evoked activity. Computation of FFT and wavelets displayed electrical brain responses directly related to stimulation frequency. Further analysis showed that both retinal stimulus location and stimulation frequency affected visual evoked activity. Field strength as well as scalp field topography changed significantly with different reversal frequency. In addition, the pattern of lateralization of components also depended on temporal frequency of stimulation. Electrical brain activity elicited by visual stimuli shows globally similar features which are modulated by stimulus location and frequency. Our results indicate that--at least partly--different neuronal assemblies are activated by stimuli of different temporal characteristics.

Abstract: Cross-education of strength is the increase in strength of the untrained contralateral limb after unilateral training of the opposite homologous limb. We investigated central and peripheral neural adaptations associated with cross-education of strength. Twenty-three right-handed females were randomized into a unilateral training group or an imagery group. A sub-sample of eight subjects (four training, four imagery) was assessed with functional magnetic resonance imaging (fMRI) for patterns of cortical activation during exercise. Strength training was 6 weeks of maximal isometric ulnar deviation of the right arm, four times per week. Peak torque, muscle thickness (ultrasound), agonist-antagonist electromyography (EMG), and fMRI were assessed before and after training. Strength training was highly effective for increasing strength in trained (45.3%; P < 0.01) and untrained (47.1%; P < 0.01) limbs. The imagery group showed no increase in strength for either arm. Muscle thickness increased only in the trained arm of the training group (8.4%; P < 0.001). After training, there was an enlarged region of activation in contralateral sensorimotor cortex and left temporal lobe during muscle contractions with the untrained left arm (P < 0.001). Training was associated with a significantly greater change in agonist muscle EMG pooled over both limbs, compared to the imagery group (P < 0.05). These results suggest that cross-education of strength may be partly controlled by adaptations within sensorimotor cortex, consistent with previous studies of motor learning. However, this research demonstrates the involvement of temporal lobe regions that subserve semantic memory for movement, which has not been previously studied in this context. We argue that temporal lobe regions might play a significant role in the cross-education of strength.

Abstract: Accumulating evidence suggests the existence of a shared neural substrate between imagined and executed movements. However, a better understanding of the mechanisms involved in the motor execution and motor imagery requires knowledge of the way the co-activated brain regions interact to each other during the particular (real or imagined) motor task. Within this general framework, the aim of the present study is to investigate the cortical activation and connectivity sub-serving real and imaginary rhythmic finger tapping, from the analysis of multi-channel electroencephalogram (EEG) scalp recordings. A sequence of 250 auditory pacing stimuli has been used for both the real and imagined right finger tapping task, with a constant inter-stimulus interval of 1.5 s length. During the motor execution, healthy subjects were asked to tap in synchrony with the regular sequence of stimulus events, whereas in the imagery condition subjects imagined themselves tapping in time with the auditory cue. To improve the spatial resolution of the scalp fields and suppress unwanted interferences, the EEG data have been spatially filtered. Further, event related synchronization and desynchronization phenomena and phase synchronization analysis have been employed for the study of functionally active brain areas and their connectivity during real and imagery finger tapping. Our results show a fronto-parietal co-activation during both real and imagined movements and similar connectivity patterns among contralateral brain areas. The results support the hypothesis that functional connectivity over the contralateral hemisphere during finger tapping is preserved in imagery. The approach and results can be regarded as indicative evidences of a new strategy for recognizing imagined movements in EEG-based brain computer interface research.

Abstract: Over the last 20 years, a body of techniques known as high resolution EEG has allowed precise estimation of cortical activity from non-invasive EEG measurements. The availability of cortical waveforms from non-invasive EEG recordings allows to have not only the level of activation within a single region of interest (ROI) during a particular task, but also to estimate the causal relationships among activities of several cortical regions. However, interpreting resulting connectivity patterns is still an open issue, due to the difficulty to provide an objective measure of their properties across different subjects or groups. A novel approach addressed to solve this difficulty consists in manipulating these functional brain networks as graph objects for which a large body of indexes and tools are available in literature and already tested for complex networks at different levels of scale (Social, WorldWideWeb and Proteomics). In the present work, we would like to show the suitability of such approach, showing results obtained comparing separately two groups of subjects during the same motor task and two different motor tasks performed by the same group. In the first experiment two groups of subjects (healthy and spinal cord injured patients) were compared when they moved and attempted to move simultaneously their right foot and lips, respectively. The contrast between the foot–lips movement and the simple foot movement was addressed in the second experiment for the population of the healthy subjects. For both the experiments, the main question is whether the “architecture” of the functional connectivity networks obtained could show properties that are different in the two groups or in the two tasks. All the functional connectivity networks gathered in the two experiments showed ordered properties and significant differences from “random” networks having the same characteristic sizes. The proposed approach, based on the use of indexes derived from graph theory, can apply to cerebral connectivity patterns estimated not only from the EEG signals but also from different brain imaging methods.