A face-selective neural signal is reliably found in humans with functional MRI and event-related potential (ERP) measures, which provide complementary information about the spatial and temporal properties of the neural response. However, because most neuroimaging studies so far have studied ERP and fMRI face-selective markers separately, the relationship between them is still unknown. Here we simultaneously recorded fMRI and ERP responses to faces and chairs to examine the correlations across subjects between the magnitudes of fMRI and ERP face-selectivity measures. Findings show that the face-selective responses in the temporal lobe (i.e., fusiform gyrus--FFA) and superior temporal sulcus (fSTS), but not the face-selective response in the occipital cortex (OFA), were highly correlated with the face-selective N170 component. In contrast, the OFA was correlated with earlier ERPs at about 110 ms after stimulus-onset. Importantly, these correlations reveal a temporal dissociation between the face-selective area in the occipital lobe and face-selective areas in the temporal lobe. Despite the very different time-scale of the fMRI and EEG signals, our data show that a correlation analysis across subjects may be informative with respect to the latency in which different brain regions process information.
The analysis of cross-frequency coupling (CFC) has become popular in studies involving intracranial and scalp EEG recordings in humans. It has been argued that some cases where CFC is mathematically present may not reflect an interaction of two distinct yet functionally coupled neural sources with different frequencies. Here we provide two empirical examples from intracranial recordings where CFC can be shown to be driven by the shape of a periodic waveform rather than by a functional interaction between distinct sources. Using simulations, we also present a generalized and realistic scenario where such coupling may arise. This scenario, which we term waveform-dependent CFC, arises when sharp waveforms (e.g., cortical potentials) occur throughout parts of the data, in particular if they occur rhythmically. Since the waveforms contain both low- and high-frequency components, these components can be inherently phase-aligned as long as the waveforms are spaced with appropriate intervals. We submit that such behavior of the data, which seems to be present in various cortical signals, cannot be interpreted as reflecting functional modulation between distinct neural sources without additional evidence. In addition, we show that even low amplitude periodic potentials that cannot be readily observed or controlled for, are sufficient for significant CFC to occur.
Neural selectivity to specific object categories has been demonstrated in extrastriate cortex with both functional MRI [1-3] and event-related potential (ERP) [4, 5]. Here we tested for a causal relationship between the activation of category-selective areas and ERP to their preferred categories. Electroencephalogram (EEG) was recorded while participants observed faces and headless bodies. Concurrently with EEG recording, we delivered two pulses of transcranial magnetic stimulation (TMS) over the right occipital face area (OFA) or extrastriate body area (EBA) at 60 and 100 ms after stimulus onset. Results showed a clear dissociation between the stimulated site and the stimulus category on ERP modulation: stimulation of the OFA significantly increased the N1 amplitude to faces but not to bodies, whereas stimulation of the EBA significantly increased the N1 amplitude to bodies but not to faces. These findings provide the first evidence for a specific and causal link between activity in category-selective networks and scalp-recorded ERP to their preferred categories. This result also demonstrates that the face and body N1 reflects several nonoverlapping neural sources, rather than changes in face-selective mechanisms alone. Lastly, because early stimulation (60-100 ms) affected selectivity of a later ERP component (150-200 ms), the results could imply a feed-forward connection between occipital and temporal category-selective areas.
Background: The clinical diagnosis and management of patients with sport-related concussion is largely dependent on subjectively reported symptoms, clinical examinations, cognitive, balance, vestibular and oculomotor testing. Consequently, there is an unmet need for objective assessment tools that can identify the injury from a physiological perspective and add an important layer of information to the clinician’s decision-making process.
Objective: The goal of the study was to evaluate the clinical utility of the EEG-based tool named Brain Network Activation (BNA) as a longitudinal assessment method of brain function in the management of young athletes with concussion.
Methods: Athletes with concussion (n = 86) and age-matched controls (n = 81) were evaluated at four time points with symptom questionnaires and BNA. BNA scores were calculated by comparing functional networks to a previously defined normative reference brain network model to the same cognitive task.
Results: Subjects above 16 years of age exhibited a significant decrease in BNA scores immediately following injury, as well as notable changes in functional network activity, relative to the controls. Three representative case studies of the tested population are discussed in detail, to demonstrate the clinical utility of BNA.
Conclusion: The data support the utility of BNA to augment clinical examinations, symptoms and additional tests by providing an effective method for evaluating objective electrophysiological changes associated with sport-related concussions.
BNA methodology can help differentiate between ADHD and healthy controls based on functional brain connectivity. The data support the utility of the tool to augment clinical examinations by objective evaluation of electrophysiological changes associated with ADHD. Results also support a network-based approach to the study of ADHD.
Faces and bodies are processed by distinct category-selective brain areas. Neuroimaging studies have so far presented isolated faces and headless bodies, and therefore little is known on whether and where faces and headless bodies are grouped together to one object, as they appear in the real world. The current study examined whether a face presented above a body are represented as two separate images or as an integrated face-body representation in face and body-selective brain areas by employing a fMRI competition paradigm. This paradigm has been shown to reveal higher fMRI response to sequential than simultaneous presentation of multiple stimuli (i.e., the competition effect), indicating competitive interactions among simultaneously presented multiple stimuli. We therefore hypothesized that if a face above a body is integrated to an image of a person whereas a body above a face is represented as two separate objects, the competition effect will be larger for the latter than the former. Consistent with our hypothesis, our findings reveal a competition effect when a body is presented above a face, but not when a face is presented above a body, suggesting that a body above a face is represented as two separate objects whereas a face above a body is represented as an integrated image of a person. Interestingly, this integration of a face and a body to an image of a person was found in the fusiform, but not the lateral-occipital face and body areas. We conclude that faces and bodies are processed separately at early stages and are integrated to a unified image of a person at mid-level stages of object processing.
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