Early (M170) activation of face-specific cortex by face-like objects

The tendency to perceive faces in random patterns exhibiting configural properties of faces is an example of pareidolia. Perception of 'real' faces has been associated with a cortical response signal arising at approximately 170 ms after stimulus onset, but what happens when nonface objects are perceived as faces? Using magnetoencephalography, we found that objects incidentally perceived as faces evoked an early (165 ms) activation in the ventral fusiform cortex, at a time and location similar to that evoked by faces, whereas common objects did not evoke such activation. An earlier peak at 130 ms was also seen for images of real faces only. Our findings suggest that face perception evoked by face-like objects is a relatively early process, and not a late reinterpretation cognitive phenomenon. NeuroReport 20:403-407 (C) 2009 Wolters Kluwer Health | Lippincott Williams & Wilkins

Early Category-Specific Cortical Activation Revealed by Visual Stimulus Inversion

Visual categorization may already start within the first 100-ms after stimulus onset, in contrast with the long-held view that during this early stage all complex stimuli are processed equally and that category-specific cortical activation occurs only at later stages. The neural basis of this proposed early stage of high-level analysis is however poorly understood. To address this question we used magnetoencephalography and anatomically-constrained distributed source modeling to monitor brain activity with millisecond-resolution while subjects performed an orientation task on the upright and upside-down presented images of three different stimulus categories: faces, houses and bodies. Significant inversion effects were found for all three stimulus categories between 70–100-ms after picture onset with a highly category-specific cortical distribution. Differential responses between upright and inverted faces were found in well-established face-selective areas of the inferior occipital cortex and right fusiform gyrus. In addition, early category-specific inversion effects were found well beyond visual areas. Our results provide the first direct evidence that category-specific processing in high-level category-sensitive cortical areas already takes place within the first 100-ms of visual processing, significantly earlier than previously thought, and suggests the existence of fast category-specific neocortical routes in the human brain

Early Preferential Responses to Fear Stimuli in Human Right Dorsal Visual Stream - A Meg Study

Emotional expressions of others are salient biological stimuli that automatically capture attention and prepare us for action. We investigated the early cortical dynamics of automatic visual discrimination of fearful body expressions by monitoring cortical activity using magnetoencephalography. We show that right parietal cortex distinguishes between fearful and neutral bodies as early as 80-ms after stimulus onset, providing the first evidence for a fast emotion-attention-action link through human dorsal visual stream

Sensitivity of MEG and EEG to Source Orientation

An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.National Institutes of Health (U.S.) (Grant NS057500)National Institutes of Health (U.S.) (Grant NS037462)National Institutes of Health (U.S.) (Grant HD040712)National Center for Research Resources (U.S.) (P41RR14075)Mind Research Networ

Early Category-Specific Cortical Activation Revealed by Visual Stimulus Inversion

Visual categorization may already start within the first 100-ms after stimulus onset, in contrast with the long-held view that during this early stage all complex stimuli are processed equally and that category-specific cortical activation occurs only at later stages. The neural basis of this proposed early stage of high-level analysis is however poorly understood. To address this question we used magnetoencephalography and anatomically-constrained distributed source modeling to monitor brain activity with millisecond-resolution while subjects performed an orientation task on the upright and upside-down presented images of three different stimulus categories: faces, houses and bodies. Significant inversion effects were found for all three stimulus categories between 70–100-ms after picture onset with a highly category-specific cortical distribution. Differential responses between upright and inverted faces were found in well-established face-selective areas of the inferior occipital cortex and right fusiform gyrus. In addition, early category-specific inversion effects were found well beyond visual areas. Our results provide the first direct evidence that category-specific processing in high-level category-sensitive cortical areas already takes place within the first 100-ms of visual processing, significantly earlier than previously thought, and suggests the existence of fast category-specific neocortical routes in the human brain

Removing Cardiac Artefacts in Magnetoencephalography with Resampled Moving Average Subtraction

Magnetoencephalography (MEG) signals are commonly contaminated by cardiac artefacts (CAs). Principle component analysis and independent component analysis have been widely used for removing CAs, but they typically require a complex procedure for the identification of CA-related components. We propose a simple and efficient method, resampled moving average subtraction (RMAS), to remove CAs from MEG data. Based on an electrocardiogram (ECG) channel, a template for each cardiac cycle was estimated by a weighted average of epochs of MEG data over consecutive cardiac cycles, combined with a resampling technique for accurate alignment of the time waveforms. The template was subtracted from the corresponding epoch of the MEG data. The resampling reduced distortions due to asynchrony between the cardiac cycle and the MEG sampling times. The RMAS method successfully suppressed CAs while preserving both event-related responses and high-frequency (>45 Hz) components in the MEG data

Combining fMRI with EEG and MEG in order to relate patterns of brain activity to cognition

The common factor that underlies several types of functional brain imaging is the electric current of masses of dendrites. The prodigious demands for the energy that is required to drive the dendritic currents are met by hemodynamic and metabolic responses that are visualized with fMRI and PET techniques. The high current densities in parallel dendritic shafts and the broad distributions of the loop currents outside the dendrites generate both the scalp EEG and the magnetic fields seen in the MEG. The measurements of image intensities and potential fields provide state variables for modeling. The relationships between the intensities of current density and the electric, magnetic, and hemodynamic state variables are complex and far from proportionate. The state variables are complementary, because the information they convey comes from differing albeit overlapping neural populations, so that efforts to cross-validate localization of neural activity relating to specified cognitive behaviors have not always been successful. We propose an alternative way to use the three methods in combination through studies of hemisphere-wide, high-resolution spatiotemporal patterns of neural activity recorded non-invasively and analyzed with multivariate statistics. Success in this proposed endeavor requires specification of what patterns to look for. At the present level of understanding, an appropriate pattern is any significant departure from random noise in the spectral, temporal and spatial domains that can be scaled into the coarse-graining of time by fMRI/BOLD and the coarse-graining of space by EEG and MEG. Here the requisite patterns are predicted to be large-scale spatial amplitude modulation (AM) of synchronized neuronal signals in the beta and gamma ranges that are coordinated but not correlated with fMRI intensities

Influence of unfused cranial bones on magnetoencephalography signals in human infants

Objective To clarify the effects of unfused cranial bones on magnetoencephalography (MEG) signals during early development. Methods In a simulation study, we compared the MEG signals over a spherical head model with a circular hole mimicking the anterior fontanel to those over the same head model without the fontanel for different head and fontanel sizes with varying skull thickness and conductivity. Results The fontanel had small effects according to three indices. The sum of differences in signal over a sensor array due to a fontanel, for example, was \u3c 6% of the sum without the fontanel. However, the fontanel effects were extensive for dipole sources deep in the brain or outside the fontanel for larger fontanels. The effects were comparable in magnitude for tangential and radial sources. Skull thickness significantly increased the effect, while skull conductivity had minor effects. Conclusion MEG signal is weakly affected by a fontanel. However, the effects can be extensive and significant for radial sources, thicker skull and large fontanels. The fontanel effects can be intuitively explained by the concept of secondary sources at the fontanel wall. Significance The minor influence of unfused cranial bones simplifies MEG analysis, but it should be considered for quantitative analysis

Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative condition that can lead to severe cognitive and functional deterioration. Functional magnetic resonance imaging (fMRI) revealed abnormalities in AD in intrinsic synchronization between spatially separate regions in the so-called default mode network (DMN) of the brain. To understand the relationship between this disruption in large-scale synchrony and the cognitive impairment in AD, it is critical to determine whether and how the deficit in the low frequency hemodynamic fluctuations recorded by fMRI translates to much faster timescales of memory and other cognitive processes. The present study employed magnetoencephalography (MEG) and a Hidden Markov Model (HMM) approach to estimate spontaneous synchrony variations in the functional neural networks with high temporal resolution. In a group of cognitively healthy (CH) older adults, we found transient (mean duration of 150–250 ms) network activity states, which were visited in a rapid succession, and were characterized by spatially coordinated changes in the amplitude of source-localized electrophysiological oscillations. The inferred states were similar to those previously observed in younger participants using MEG, and the estimated cortical source distributions of the state-specific activity resembled the classic functional neural networks, such as the DMN. In patients with AD, inferred network states were different from those of the CH group in short-scale timing and oscillatory features. The state of increased oscillatory amplitudes in the regions overlapping the DMN was visited less often in AD and for shorter periods of time, suggesting that spontaneous synchronization in this network was less likely and less stable in the patients. During the visits to this state, in some DMN nodes, the amplitude change in the higher-frequency (8–30 Hz) oscillations was less robust in the AD than CH group. These findings highlight relevance of studying short-scale temporal evolution of spontaneous activity in functional neural networks to understanding the AD pathophysiology. Capacity of flexible intrinsic synchronization in the DMN may be crucial for memory and other higher cognitive functions. Our analysis yielded metrics that quantify distinct features of the neural synchrony disorder in AD and may offer sensitive indicators of the neural network health for future investigations. Keywords: Alzheimer's disease, Electrophysiology, Dynamic functional connectivity, Mathematical modeling, ME

Source distribution of the M100 Stimulus Inversion Effect.

<p>A. Anatomically constrained source analysis (average dSPM values across subjects; <i>n</i> = 9) for Upright (top trace) and Inverted Faces (bottom trace) from 70–100-ms after stimulus onset visualized on the inflated cortical surface (gyri appear in light grey, sulci in dark grey). For each time-instant, four different views are presented to depict the whole cortical surface, with left hemisphere on the left and right hemisphere on the right of each quadruplet. The two top images of each quadruplet show the lateral aspects of the brain and a little strip of the ventral aspect (lateral view, 11° tilted towards the bottom view); the two bottom images show the medial and ventral aspects of the brain (medial view, 45° tilted towards bottom view). Only values of dSPM>2.5 are visualized. A grey opaque mask was placed over the midbrain. B. Differential activation related to the Inversion Effects, i.e. the contrast between the Upright and Inverted condition of Faces, Bodies and Houses. Displayed are the largest positive or negative t-values (two-tailed paired <i>t</i>-tests; <i>n</i> = 9; <i>df</i> = 8) at each dipole location occurring within the 70–100-ms time-window. Significant t-values at the level of <i>p</i><0.01 are thresholded with respect to baseline noise and visualized only if the dipole strength exceeds a signal-to-noise ratio of 2.5 (i.e. dSPM>2.5) in at least one of the single stimulus conditions. The red and yellow colors denote locations at which the dipole strength is stronger for Upright than for Inverted stimuli. Blue colors denote locations in which the dipole strength is stronger for the Inverted stimuli. Absolute <i>t</i>-values of 3.35 and larger (red/dark-blue) correspond to <i>p</i><0.01, absolute <i>t</i>-values of 4.8 and larger (yellow/light blue) to <i>p</i><0.001. Abbreviations: mFG = middle Fusiform Gyrus; IOG = Inferior Occipital Gyrus; LOC = Lateral Occipital Cortex; pIFG = posterior Inferior Frontal Gyrus; mOFC = medial OrbitoFrontal Cortex.</p