The fMRI BOLD signal tracks electrophysiological spectral perturbations, not event-related potentials

A Functional Magnetic Resonance Imaging Study of Phrase Structure and Subject Island Violations

In principle, functional neuroimaging provides uniquely informative data in addressing linguistic questions, because it can indicate distinct processes that are not apparent from behavioral data alone. This could involve adjudicating the source of unacceptability via the different patterns of elicited brain responses to different ungrammatical sentence types. However, it is difficult to interpret brain activations to syntactic violations. Such responses could reflect processes that have nothing intrinsically related to linguistic representations, such as domain-general executive function abilities. To facilitate the potential use of functional neuroimaging methods to identify the source of different syntactic violations, we conducted a functional magnetic resonance imaging experiment to identify the brain activation maps associated with two distinct syntactic violation types: phrase structure (created by inverting the order of two adjacent words within a sentence) and subject islands (created by extracting a wh-phrase out of an embedded subject). The comparison of these violations to control sentences surprisingly showed no indication of a generalized violation response, with almost completely divergent activation patterns. Phrase structure violations seemingly activated regions previously implicated in verbal working memory and structural complexity in sentence processing, whereas the subject islands appeared to activate regions previously implicated in conceptual-semantic processing, broadly defined. We review our findings in the context of previous research on syntactic and semantic violations using ERPs. Although our results suggest potentially distinct underlying mechanisms underlying phrase structure and subject island violations, our results are tentative and suggest important methodological considerations for future research in this area.

Trimodal brain imaging: A novel approach for simultaneous investigation of human brain function

While advancements have improved the extent to which individual brain imaging approaches capture information regarding spatial or temporal dynamics of brain activity, the connections between these aspects and their relation to psychological functioning remain only partially understood. Acquisition and integration across multiple brain imaging modalities allows for the possible clarification of these connections. The present review provides an overview of three complementary modalities - functional magnetic resonance imaging (fMRI), electroencephalography/event-related potentials (EEG/ERP), and event-related optical signals (EROS) - and discusses progress and considerations for each modality, along with a summary of a novel protocol for acquiring them simultaneously. Initial evidence points to the feasibility of acquiring and integrating multiple measures of brain function that allows for addressing questions in ways not otherwise possible using traditional approaches. Simultaneous trimodal brain imaging in humans provides new possibilities for clarifying spatiotemporal dynamics of brain activity and for identifying multifaceted associations with measures of individual differences and important health outcomes.

Phase synchronization during the processing of taxonomic and thematic relations

Semantic relations include "taxonomic" relations based on shared features and "thematic" relations based on co-occurrence in events. The "dual-hub" account proposes that the anterior temporal lobe (ATL) is functionally specialized for taxonomic relations and the inferior parietal lobule (IPL) for thematic relations. This study examined this claim by analyzing the intra- and inter-region phase synchronization of intracranial EEG data from electrodes in the ATL, IPL, and two subregions of the semantic control network: left inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG). Ten participants with epilepsy completed a semantic relatedness judgment task during intracranial EEG recording and had electrodes in at least one hub and at least one semantic control region. Theta band phase synchronization was partially consistent with the dual-hub account: synchronization between the ATL and IFG/pMTG increased when processing taxonomic relations, and synchronization within the IPL and between IPL and pMTG increased when processing thematic relations.

Transcranial ultrasound stimulation selectively affects cortical neurovascular coupling across neuronal types and LFP frequency bands

Previous studies have affirmed that transcranial ultrasound stimulation (TUS) can influence cortical neurovascular coupling across low-frequency (0-2 Hz)/high-frequency (160-200 Hz) neural oscillations and hemodynamics. Nevertheless, the selectivity of this coupling triggered by transcranial ultrasound stimulation for spike activity (> 300 Hz) and additional frequency bands (4-150 Hz) remains elusive. We applied transcranial ultrasound stimulation to mice visual cortex while simultaneously recording total hemoglobin concentration, spike activity, and local field potentials. Our findings include (1) a significant increase in coupling strength between spike firing rates of putative inhibitory neurons/putative excitatory neurons and total hemoglobin concentration post-transcranial ultrasound stimulation; (2) an ~ 2.1-fold higher Pearson correlation coefficient between putative inhibitory neurons and total hemoglobin concentration compared with putative excitatory neurons and total hemoglobin concentration (*P < 0.05); (3) a notably greater cross-correlation between putative inhibitory neurons and total hemoglobin concentration than that between putative excitatory neurons and total hemoglobin concentration (*P < 0.05); (4) an enhancement of Pearson correlation coefficient between the relative power of γ frequency band (30-80 Hz), hγ frequency band (80-150 Hz) and total hemoglobin concentration following transcranial ultrasound stimulation (*P < 0.05); and (5) strongest cross-correlation observed at negative delay for θ frequency band, and positive delay for α, β, γ, hγ frequency bands. Collectively, these results demonstrate that cortical neurovascular coupling evoked by transcranial ultrasound stimulation exhibits selectivity concerning neuronal types and local field potential frequency bands.

Intracranial recordings reveal high-frequency activity in the human temporal-parietal cortex supporting non-literal language processing

Objective

Non-literal expressions such as sarcasm, metaphor and simile refer to words and sentences that convey meanings or intentions that are different and more abstract than literal expressions. Neuroimaging studies have shown activations in a variety of frontal, parietal and temporal brain regions implicated in non-literal language processing. However, neurophysiological correlates of these brain areas underlying non-literal processing remain underexplored.

Methods

To address this, we investigated patterns of intracranial EEG activity during non-literal processing by leveraging a unique patient population. Seven neurosurgical patients with invasive electrophysiological monitoring of superficial brain activity were recruited. Intracranial neural responses were recorded over the temporal-parietal junction (TPJ) and its surrounding areas while patients performed a language task. Participants listened to vignettes that ended with non-literal or literal statements and were then asked related questions to which they responded verbally.

Results

We found differential neurophysiological activity during the processing of non-literal statements as compared to literal statements, especially in low-Gamma (30-70 Hz) and delta (1-4 Hz) bands. In addition, we found that neural responses related to non-literal processing in the high-gamma band (>70 Hz) were significantly more prominent at TPJ electrodes as compared to non-TPJ (i.e., control) electrodes in most subjects. Moreover, in half of patients, high-gamma activity related to non-literal processing was accompanied by delta-band modulation.

Conclusion

These results suggest that both low- and high-frequency electrophysiological activities in the temporal-parietal junction play a crucial role during non-literal language processing in the human brain. The current investigation, utilizing better spatial and temporal resolution of human intracranial electrocorticography, provides a unique opportunity to gain insights into the localized brain dynamics of the TPJ during the processing of non-literal language expressions.

Invasive Computational Psychiatry

Computational psychiatry, a relatively new yet prolific field that aims to understand psychiatric disorders with formal theories about the brain, has seen tremendous growth in the past decade. Despite initial excitement, actual progress made by computational psychiatry seems stagnant. Meanwhile, understanding of the human brain has benefited tremendously from recent progress in intracranial neuroscience. Specifically, invasive techniques such as stereotactic electroencephalography, electrocorticography, and deep brain stimulation have provided a unique opportunity to precisely measure and causally modulate neurophysiological activity in the living human brain. In this review, we summarize progress and drawbacks in both computational psychiatry and invasive electrophysiology and propose that their combination presents a highly promising new direction-invasive computational psychiatry. The value of this approach is at least twofold. First, it advances our mechanistic understanding of the neural computations of mental states by providing a spatiotemporally precise depiction of neural activity that is traditionally unattainable using noninvasive techniques with human subjects. Second, it offers a direct and immediate way to modulate brain states through stimulation of algorithmically defined neural regions and circuits (i.e., algorithmic targeting), thus providing both causal and therapeutic insights. We then present depression as a use case where the combination of computational and invasive approaches has already shown initial success. We conclude by outlining future directions as a road map for this exciting new field as well as presenting cautions about issues such as ethical concerns and generalizability of findings.

High gamma activity distinguishes frontal cognitive control regions from adjacent cortical networks

Though the lateral frontal cortex is broadly implicated in cognitive control, functional MRI (fMRI) studies suggest fine-grained distinctions within this region. To examine this question electrophysiologically, we placed electrodes on the lateral frontal cortex in patients undergoing awake craniotomy for tumor resection. Patients performed verbal tasks with a manipulation of attentional switching, a canonical control demand. Power in the high gamma range (70-250 Hz) distinguished electrodes based on their location within a high-resolution fMRI network parcellation of the frontal lobe. Electrodes within the canonical fronto-parietal control network showed increased power in the switching condition, a result absent in electrodes within default mode, language and somato-motor networks. High gamma results contrasted with spatially distributed power decreases in the beta range (12-30 Hz). These results confirm the importance of fine-scale functional distinctions within the human frontal lobe, and pave the way for increased precision of functional mapping in tumor surgeries.

Individual finger movement decoding using a novel ultra-high-density electroencephalography-based brain-computer interface system

Brain-Computer Interface (BCI) technology enables users to operate external devices without physical movement. Electroencephalography (EEG) based BCI systems are being actively studied due to their high temporal resolution, convenient usage, and portability. However, fewer studies have been conducted to investigate the impact of high spatial resolution of EEG on decoding precise body motions, such as finger movements, which are essential in activities of daily living. Low spatial sensor resolution, as found in common EEG systems, can be improved by omitting the conventional standard of EEG electrode distribution (the international 10-20 system) and ordinary mounting structures (e.g., flexible caps). In this study, we used newly proposed flexible electrode grids attached directly to the scalp, which provided ultra-high-density EEG (uHD EEG). We explored the performance of the novel system by decoding individual finger movements using a total of 256 channels distributed over the contralateral sensorimotor cortex. Dense distribution and small-sized electrodes result in an inter-electrode distance of 8.6 mm (uHD EEG), while that of conventional EEG is 60 to 65 mm on average. Five healthy subjects participated in the experiment, performed single finger extensions according to a visual cue, and received avatar feedback. This study exploits mu (8-12 Hz) and beta (13-25 Hz) band power features for classification and topography plots. 3D ERD/S activation plots for each frequency band were generated using the MNI-152 template head. A linear support vector machine (SVM) was used for pairwise finger classification. The topography plots showed regular and focal post-cue activation, especially in subjects with optimal signal quality. The average classification accuracy over subjects was 64.8 (6.3)%, with the middle versus ring finger resulting in the highest average accuracy of 70.6 (9.4)%. Further studies are required using the uHD EEG system with real-time feedback and motor imagery tasks to enhance classification performance and establish the basis for BCI finger movement control of external devices.

A multivariate comparison of electroencephalogram and functional magnetic resonance imaging to electrocorticogram using visual object representations in humans

Today, most neurocognitive studies in humans employ the non-invasive neuroimaging techniques functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG). However, how the data provided by fMRI and EEG relate exactly to the underlying neural activity remains incompletely understood. Here, we aimed to understand the relation between EEG and fMRI data at the level of neural population codes using multivariate pattern analysis. In particular, we assessed whether this relation is affected when we change stimuli or introduce identity-preserving variations to them. For this, we recorded EEG and fMRI data separately from 21 healthy participants while participants viewed everyday objects in different viewing conditions, and then related the data to electrocorticogram (ECoG) data recorded for the same stimulus set from epileptic patients. The comparison of EEG and ECoG data showed that object category signals emerge swiftly in the visual system and can be detected by both EEG and ECoG at similar temporal delays after stimulus onset. The correlation between EEG and ECoG was reduced when object representations tolerant to changes in scale and orientation were considered. The comparison of fMRI and ECoG overall revealed a tighter relationship in occipital than in temporal regions, related to differences in fMRI signal-to-noise ratio. Together, our results reveal a complex relationship between fMRI, EEG, and ECoG signals at the level of population codes that critically depends on the time point after stimulus onset, the region investigated, and the visual contents used.

Electrophysiological Correlates of Social Decision-making: An EEG Investigation of a Modified Ultimatum Game

Cooperation behaviors during social decision-making have been shown to be sensitive to manipulations of context. However, it remains unclear how aspects of context in dynamic social interactions, such as observed nonverbal behaviors, may modulate cooperation decisions and the associated neural mechanisms. In this study, participants responded to offers from proposers to split $10 in an Ultimatum Game following observation of proposer approach (friendly) or avoidance (nonfriendly) behaviors, displayed by dynamic whole-body animated avatars, or following a nonsocial interaction control condition. As expected, behavioral results showed that participants tended to have greater acceptance rates for unfair offers following observed nonverbal social interactions with proposers compared with control, suggesting an enhancing effect of social interactions on cooperative decisions. ERP results showed greater N1 and N2 responses at the beginning of social interaction conditions compared with control, and greater sustained and late positivity responses for observed approach and avoidance proposer behaviors compared with control. Event-related spectral perturbation (ERSP) results showed differential sensitivity within theta, alpha, and beta bands during observation of social interactions and offers that was associated with subsequent decision behaviors. Together, these results point to the impact of proposers' nonverbal behaviors on subsequent cooperation decisions at both behavioral and neural levels. The ERP and ERSP findings suggest modulated attention, monitoring, and processing of biological motion during the observed nonverbal social interactions, influencing the participants' responses to offers. These findings shed light on electrophysiological correlates of response to observed social interactions that predict subsequent social decisions.

Multiple Adjoining Word- and Face-Selective Regions in Ventral Temporal Cortex Exhibit Distinct Dynamics

The map of category-selectivity in human ventral temporal cortex (VTC) provides organizational constraints to models of object recognition. One important principle is lateral-medial response biases to stimuli that are typically viewed in the center or periphery of the visual field. However, little is known about the relative temporal dynamics and location of regions that respond preferentially to stimulus classes that are centrally viewed, such as the face- and word-processing networks. Here, word- and face-selective regions within VTC were mapped using intracranial recordings from 36 patients. Partially overlapping, but also anatomically dissociable patches of face- and word-selectivity, were found in VTC. In addition to canonical word-selective regions along the left posterior occipitotemporal sulcus, selectivity was also located medial and anterior to face-selective regions on the fusiform gyrus at the group level and within individual male and female subjects. These regions were replicated using 7 Tesla fMRI in healthy subjects. Left hemisphere word-selective regions preceded right hemisphere responses by 125 ms, potentially reflecting the left hemisphere bias for language, with no hemispheric difference in face-selective response latency. Word-selective regions along the posterior fusiform responded first, then spread medially and laterally, then anteriorally. Face-selective responses were first seen in posterior fusiform regions bilaterally, then proceeded anteriorally from there. For both words and faces, the relative delay between regions was longer than would be predicted by purely feedforward models of visual processing. The distinct time courses of responses across these regions, and between hemispheres, suggest that a complex and dynamic functional circuit supports face and word perception.SIGNIFICANCE STATEMENT Representations of visual objects in the human brain have been shown to be organized by several principles, including whether those objects tend to be viewed centrally or peripherally in the visual field. However, it remains unclear how regions that process objects that are viewed centrally, such as words and faces, are organized relative to one another. Here, invasive and noninvasive neuroimaging suggests that there is a mosaic of regions in ventral temporal cortex that respond selectively to either words or faces. These regions display differences in the strength and timing of their responses, both within and between brain hemispheres, suggesting that they play different roles in perception. These results illuminate extended, bilateral, and dynamic brain pathways that support face perception and reading.

Proof-of-concept evidence for trimodal simultaneous investigation of human brain function

The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof‐of‐concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event‐related potentials (ERPs), and event‐related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.

No Detectable Effect on Visual Responses Using Functional MRI in a Rodent Model of α-Synuclein Expression

Parkinson's disease (PD) is a progressive neurodegenerative disease that is typically diagnosed late in its progression. There is a need for biomarkers suitable for monitoring the disease progression at earlier stages to guide the development of novel neuroprotective therapies. One potential biomarker, α-synuclein, has been found in both the familial cases of PD, as well as the sporadic cases and is considered a key feature of PD. α-synuclein is naturally present in the retina, and it has been suggested that early symptoms of the visual system may be used as a biomarker for PD. Here, we use a viral vector to induce a unilateral expression of human wild-type α-synuclein in rats as a mechanistic model of protein aggregation in PD. We employed functional magnetic resonance imaging (fMRI) to investigate whether adeno-associated virus (AAV) mediated expression of human wild-type α-synuclein alter functional activity in the visual system. A total of 16 rats were injected with either AAV-α-synuclein (n = 7) or AAV-null (n = 9) in the substantia nigra pars compacta (SNc) of the left hemisphere. The expression of α-synuclein was validated by a motor assay and postmortem immunohistochemistry. Five months after the introduction of the AAV-vector, fMRI showed robust blood oxygen level-dependent (BOLD) responses to light stimulation in the visual systems of both control and AAV-α-synuclein animals. However, our results demonstrate that the expression of AAV-α-synuclein does not affect functional activation of the visual system. This negative finding suggests that fMRI-based read-outs of visual responses may not be a sensitive biomarker for PD.

Intracranial EEG evidence of functional specialization for taxonomic and thematic relations

The dual-hub account posits that the neural organization of semantic knowledge is segregated by the type of semantic relation with anterior temporal lobe (ATL) specializing for taxonomic relations and inferior parietal lobule (IPL) for thematic relations. This study critically examined this account by recording intracranial EEG from an array of depth electrodes within ATL, IPL, and two regions within the semantic control network, inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG), while 17 participants with refractory epilepsy completed a semantic relatedness judgment task. We observed a significant difference between relation types in ATL and IPL approximately 600-800 ms after trial presentation, and no significant differences in IFG or pMTG. Within this time window, alpha and theta suppression indexing cognitive effort and memory retrieval was observed in ATL for taxonomic trials and in IPL for thematic trials. These results suggest taxonomic specialization in ATL and thematic specialization in IPL, consistent with the dual-hub account of semantic cognition.

Rapid Cortical Plasticity Induced by Active Associative Learning of Novel Words in Human Adults

Human speech requires that new words are routinely memorized, yet neurocognitive mechanisms of such acquisition of memory remain highly debatable. Major controversy concerns the question whether cortical plasticity related to word learning occurs in neocortical speech-related areas immediately after learning, or neocortical plasticity emerges only on the second day after a prolonged time required for consolidation after learning. The functional spatiotemporal pattern of cortical activity related to such learning also remains largely unknown. In order to address these questions, we examined magnetoencephalographic responses elicited in the cerebral cortex by passive presentations of eight novel pseudowords before and immediately after an operant conditioning task. This associative procedure forced participants to perform an active search for unique meaning of four pseudowords that referred to movements of left and right hands and feet. The other four pseudowords did not require any movement and thus were not associated with any meaning. Familiarization with novel pseudowords led to a bilateral repetition suppression of cortical responses to them; the effect started before or around the uniqueness point and lasted for more than 500 ms. After learning, response amplitude to pseudowords that acquired meaning was greater compared with response amplitude to pseudowords that were not assigned meaning; the effect was significant within 144-362 ms after the uniqueness point, and it was found only in the left hemisphere. Within this time interval, a learning-related selective response initially emerged in cortical areas surrounding the Sylvian fissure: anterior superior temporal sulcus, ventral premotor cortex, the anterior part of intraparietal sulcus and insula. Later within this interval, activation additionally spread to more anterior higher-tier brain regions, and reached the left temporal pole and the triangular part of the left inferior frontal gyrus extending to its orbital part. Altogether, current findings evidence rapid plastic changes in cortical representations of meaningful auditory word-forms occurring almost immediately after learning. Additionally, our results suggest that familiarization resulting from stimulus repetition and semantic acquisition resulting from an active learning procedure have separable effects on cortical activity.

Reconfiguration of functional brain networks and metabolic cost converge during task performance

The ability to solve cognitive tasks depends upon adaptive changes in the organization of whole-brain functional networks. However, the link between task-induced network reconfigurations and their underlying energy demands is poorly understood. We address this by multimodal network analyses integrating functional and molecular neuroimaging acquired concurrently during a complex cognitive task. Task engagement elicited a marked increase in the association between glucose consumption and functional brain network reorganization. This convergence between metabolic and neural processes was specific to feedforward connections linking the visual and dorsal attention networks, in accordance with task requirements of visuo-spatial reasoning. Further increases in cognitive load above initial task engagement did not affect the relationship between metabolism and network reorganization but only modulated existing interactions. Our findings show how the upregulation of key computational mechanisms to support cognitive performance unveils the complex, interdependent changes in neural metabolism and neuro-vascular responses.

iEEG: Dura-lining electrodes

Intracranial electroencephalography (iEEG) is measured from electrodes placed in or on the brain. These measurements have an excellent signal-to-noise ratio and iEEG signals have often been used to decode brain activity or drive brain-computer interfaces (BCIs). iEEG recordings are typically done for seizure monitoring in epilepsy patients who have these electrodes placed for a clinical purpose: to localize both brain regions that are essential for function and others where seizures start. Brain regions not involved in epilepsy are thought to function normally and provide a unique opportunity to learn about human neurophysiology. Intracranial electrodes measure the aggregate activity of large neuronal populations and recorded signals contain many features. Different features are extracted by analyzing these signals in the time and frequency domain. The time domain may reveal an evoked potential at a particular time after the onset of an event. Decomposition into the frequency domain may show narrowband peaks in the spectrum at specific frequencies or broadband signal changes that span a wide range of frequencies. Broadband power increases are generally observed when a brain region is active while most other features are highly specific to brain regions, inputs, and tasks. Here we describe the spatiotemporal dynamics of several iEEG signals that have often been used to decode brain activity and drive BCIs.

A Sparse EEG-Informed fMRI Model for Hybrid EEG-fMRI Neurofeedback Prediction

Measures of brain activity through functional magnetic resonance imaging (fMRI) or electroencephalography (EEG), two complementary modalities, are ground solutions in the context of neurofeedback (NF) mechanisms for brain rehabilitation protocols. While NF-EEG (in which real-time neurofeedback scores are computed from EEG signals) has been explored for a very long time, NF-fMRI (in which real-time neurofeedback scores are computed from fMRI signals) appeared more recently and provides more robust results and more specific brain training. Using fMRI and EEG simultaneously for bi-modal neurofeedback sessions (NF-EEG-fMRI, in which real-time neurofeedback scores are computed from fMRI and EEG) is very promising for the design of brain rehabilitation protocols. However, fMRI is cumbersome and more exhausting for patients. The original contribution of this paper concerns the prediction of bi-modal NF scores from EEG recordings only, using a training phase where EEG signals as well as the NF-EEG and NF-fMRI scores are available. We propose a sparse regression model able to exploit EEG only to predict NF-fMRI or NF-EEG-fMRI in motor imagery tasks. We compared different NF-predictors stemming from the proposed model. We showed that predicting NF-fMRI scores from EEG signals adds information to NF-EEG scores and significantly improves the correlation with bi-modal NF sessions compared to classical NF-EEG scores.

Simultaneous EEG-NIRS Measurement of the Inferior Parietal Lobule During a Reaching Task With Delayed Visual Feedback

We investigated whether the inferior parietal lobule (IPL) responds in real-time to multisensory inconsistency during movement. The IPL is thought to be involved in both the detection of inconsistencies in multisensory information obtained during movement and that obtained during self-other discrimination. However, because of the limited temporal resolution of conventional neuroimaging techniques, it is difficult to distinguish IPL activity during movement from that during self-other discrimination. We simultaneously conducted electroencephalography (EEG) and near-infrared spectroscopy (NIRS) with the goal of examining IPL activity with a high spatiotemporal resolution during single reaching movements. Under a visual feedback-delay condition, gamma event-related synchronization (γ-ERS), i.e., an increase in gamma (31–47 Hz) EEG power occurred during reaching movements. This γ-ERS is considered to reflect processing of information about prediction errors. To integrate this temporal information with spatial information from the NIRS signals, we developed a new analysis technique that enabled estimation of the regions that show a hemodynamic response characterized by EEG fluctuation present in the visual feedback-delay condition. As a result, IPL activity was explained by γ-ERS specific to visual feedback delay during movements. Thus, we succeeded in demonstrating real-time activation of the IPL in response to multisensory inconsistency. However, we did not find any correlation between either IPL activity or γ-ERS with the sense of agency. Therefore, our results suggest that while the IPL is influenced by prediction error signals, it does not engage in direct processing underlying the conscious experience of making a movement, which is the foundation of self-other discrimination.

From eye to face: The impact of face outline, feature number, and feature saliency on the early neural response to faces

The LIFTED model of early face perception postulates that the face-sensitive N170 event-related potential may reflect underlying neural inhibition mechanisms which serve to regulate holistic and featural processing. It remains unclear, however, what specific factors impact these neural inhibition processes. Here, N170 peak responses were recorded whilst adults maintained fixation on a single eye using a gaze-contingent paradigm, and the presence/absence of a face outline, as well as the number and type of parafoveal features within the outline, were manipulated. N170 amplitudes and latencies were reduced when a single eye was fixated within a face outline compared to fixation on the same eye in isolation, demonstrating that the simple presence of a face outline is sufficient to elicit a shift towards a more face-like neural response. A monotonic decrease in the N170 amplitude and latency was observed with increasing numbers of parafoveal features, and the type of feature(s) present in parafovea further modulated this early face response. These results support the idea of neural inhibition exerted by parafoveal features onto the foveated feature as a function of the number, and possibly the nature, of parafoveal features. Specifically, the results suggest the use of a feature saliency framework (eyes > mouth > nose) at the neural level, such that the parafoveal eye may play a role in down-regulating the response to the other eye (in fovea) more so than the nose or the mouth. These results confirm the importance of parafoveal features and the face outline in the neural inhibition mechanism, and provide further support for a feature saliency mechanism guiding early face perception.

A quantitative method for evaluating cortical responses to electrical stimulation

BACKGROUND

Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations.

NEW METHOD

We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4-15 mA) to a total of 64 electrode pairs.

RESULTS

We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations.

CONCLUSIONS

SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning.

Sensitivity to Faces with Typical and Atypical Part Configurations within Regions of the Face-processing Network: An fMRI Study

Perception of faces has been shown to engage a domain-specific set of brain regions, including the occipital face area (OFA) and the fusiform face area (FFA). It is commonly held that the OFA is responsible for the detection of faces in the environment, whereas the FFA is responsible for processing the identity of the face. However, an alternative model posits that the FFA is responsible for face detection and subsequently recruits the OFA to analyze the face parts in the service of identification. An essential prediction of the former model is that the OFA is not sensitive to the arrangement of internal face parts. In the current fMRI study, we test the sensitivity of the OFA and FFA to the configuration of face parts. Participants were shown faces in which the internal parts were presented in a typical configuration (two eyes above a nose above a mouth) or in an atypical configuration (the locations of individual parts were shuffled within the face outline). Perception of the atypical faces evoked a significantly larger response than typical faces in the OFA and in a wide swath of the surrounding posterior occipitotemporal cortices. Surprisingly, typical faces did not evoke a significantly larger response than atypical faces anywhere in the brain, including the FFA (although some subthreshold differences were observed). We propose that face processing in the FFA results in inhibitory sculpting of activation in the OFA, which accounts for this region's weaker response to typical than to atypical configurations.

Real-time detection and discrimination of visual perception using electrocorticographic signals

OBJECTIVE

Several neuroimaging studies have demonstrated that the ventral temporal cortex contains specialized regions that process visual stimuli. This study investigated the spatial and temporal dynamics of electrocorticographic (ECoG) responses to different types and colors of visual stimulation that were presented to four human participants, and demonstrated a real-time decoder that detects and discriminates responses to untrained natural images.

APPROACH

ECoG signals from the participants were recorded while they were shown colored and greyscale versions of seven types of visual stimuli (images of faces, objects, bodies, line drawings, digits, and kanji and hiragana characters), resulting in 14 classes for discrimination (experiment I). Additionally, a real-time system asynchronously classified ECoG responses to faces, kanji and black screens presented via a monitor (experiment II), or to natural scenes (i.e. the face of an experimenter, natural images of faces and kanji, and a mirror) (experiment III). Outcome measures in all experiments included the discrimination performance across types based on broadband γ activity.

MAIN RESULTS

Experiment I demonstrated an offline classification accuracy of 72.9% when discriminating among the seven types (without color separation). Further discrimination of grey versus colored images reached an accuracy of 67.1%. Discriminating all colors and types (14 classes) yielded an accuracy of 52.1%. In experiment II and III, the real-time decoder correctly detected 73.7% responses to face, kanji and black computer stimuli and 74.8% responses to presented natural scenes.

SIGNIFICANCE

Seven different types and their color information (either grey or color) could be detected and discriminated using broadband γ activity. Discrimination performance maximized for combined spatial-temporal information. The discrimination of stimulus color information provided the first ECoG-based evidence for color-related population-level cortical broadband γ responses in humans. Stimulus categories can be detected by their ECoG responses in real time within 500 ms with respect to stimulus onset.

Topography and timing of activity in right inferior frontal cortex and anterior insula for stopping movement

Stopping incipient action activates both the right inferior frontal cortex (rIFC) and the anterior insula (rAI). Controversy has arisen as to whether these comprise a unitary cortical cluster-the rIFC/rAI-or whether rIFC is the primary stopping locus. To address this, we recorded directly from these structures while taking advantage of the high spatiotemporal resolution of closely spaced stereo-electro-encephalographic (SEEG) electrodes. We studied 12 patients performing a stop-signal task. On each trial they initiated a motor response (Go) and tried to stop to an occasional stop signal. Both the rIFC and rAI exhibited an increase in broadband gamma activity (BGA) after the stop signal and within the time of stopping (stop signal reaction time, SSRT), regardless of the success of stopping. The proportion of electrodes with this response was significantly greater in the rIFC than the rAI. Also, the rIFC response preceded that in the rAI. Last, while the BGA increase in rIFC occurred mainly prior to SSRT, the rAI showed a sustained increase in the beta and low gamma bands after the SSRT. In summary, the rIFC was activated soon after the stop signal, prior to and more robustly than the rAI, which on the other hand, showed a more prolonged response after the onset of stopping. Our results are most compatible with the notion that the rIFC is involved in triggering outright stopping in concert with a wider network, while the rAI is likely engaged by other processes, such as arousal, saliency, or behavioral adjustments. Hum Brain Mapp 39:189-203, 2018. © 2017 Wiley Periodicals, Inc.

Cortical representation of persistent visual stimuli

Research into visual neural activity has focused almost exclusively on onset- or change-driven responses and little is known about how information is encoded in the brain during sustained periods of visual perception. We used intracranial recordings in humans to determine the degree to which the presence of a visual stimulus is persistently encoded by neural activity. The correspondence between stimulus duration and neural response duration was strongest in early visual cortex and gradually diminished along the visual hierarchy, such that is was weakest in inferior-temporal category-selective regions. A similar posterior-anterior gradient was found within inferior temporal face-selective regions, with posterior but not anterior sites showing persistent face-selective activity. The results suggest that regions that appear uniform in terms of their category selectivity are dissociated by how they temporally represent a stimulus in support of ongoing visual perception, and delineate a large-scale organizing principle of the ventral visual stream.

Neuronal synchrony and the relation between the blood-oxygen-level dependent response and the local field potential

The most widespread measures of human brain activity are the blood-oxygen-level dependent (BOLD) signal and surface field potential. Prior studies report a variety of relationships between these signals. To develop an understanding of how to interpret these signals and the relationship between them, we developed a model of (a) neuronal population responses and (b) transformations from neuronal responses into the functional magnetic resonance imaging (fMRI) BOLD signal and electrocorticographic (ECoG) field potential. Rather than seeking a transformation between the two measures directly, this approach interprets each measure with respect to the underlying neuronal population responses. This model accounts for the relationship between BOLD and ECoG data from human visual cortex in V1, V2, and V3, with the model predictions and data matching in three ways: across stimuli, the BOLD amplitude and ECoG broadband power were positively correlated, the BOLD amplitude and alpha power (8-13 Hz) were negatively correlated, and the BOLD amplitude and narrowband gamma power (30-80 Hz) were uncorrelated. The two measures provide complementary information about human brain activity, and we infer that features of the field potential that are uncorrelated with BOLD arise largely from changes in synchrony, rather than level, of neuronal activity.

Instantaneous voltage as an alternative to power- and phase-based interpretation of oscillatory brain activity

For decades, oscillatory brain activity has been characterized primarily by measurements of power and phase. While many studies have linked those measurements to cortical excitability, their relationship to each other and to the physiological underpinnings of excitability is unclear. The recently proposed Function-through-Biased-Oscillations (FBO) hypothesis (Schalk, 2015) addressed these issues by suggesting that the voltage potential at the cortical surface directly reflects the excitability of cortical populations, that this voltage is rhythmically driven away from a low resting potential (associated with depolarized cortical populations) towards positivity (associated with hyperpolarized cortical populations). This view explains how oscillatory power and phase together influence the instantaneous voltage potential that directly regulates cortical excitability. This implies that the alternative measurement of instantaneous voltage of oscillatory activity should better predict cortical excitability compared to either of the more traditional measurements of power or phase. Using electrocorticographic (ECoG) data from 28 human subjects, the results of our study confirm this prediction: compared to oscillatory power and phase, the instantaneous voltage explained 20% and 31% more of the variance in broadband gamma, respectively, and power and phase together did not produce better predictions than the instantaneous voltage. These results synthesize the previously separate power- and phase-based interpretations and associate oscillatory activity directly with a physiological interpretation of cortical excitability. This alternative view has implications for the interpretation of studies of oscillatory activity and for current theories of cortical information transmission.

Simultaneous Processing of Noun Cue and to-be-Produced Verb in Verb Generation Task: Electromagnetic Evidence

A long-standing but implicit assumption is that words strongly associated with a presented cue are automatically activated in the memory through rapid spread of activation within brain semantic networks. The current study was aimed to provide direct evidence of such rapid access to words’ semantic representations and to investigate its neural sources using magnetoencephalography (MEG) and distributed source localization technique. Thirty-three neurotypical subjects underwent the MEG recording during verb generation task, which was to produce verbs related to the presented noun cues. Brain responses evoked by the noun cues were examined while manipulating the strength of association between the noun and the potential verb responses. The strong vs. weak noun-verb association led to a greater noun-related neural response at 250–400 ms after cue onset, and faster verb production. The cortical sources of the differential response were localized in left temporal pole, previously implicated in semantic access, and left ventrolateral prefrontal cortex (VLPFC), thought to subserve controlled semantic retrieval. The strength of the left VLPFC’s response to the nouns with strong verb associates was positively correlated to the speed of verbs production. Our findings empirically validate the theoretical expectation that in case of a strongly connected noun-verb pair, successful access to target verb representation may occur already at the stage of lexico-semantic analysis of the presented noun. Moreover, the MEG results suggest that contrary to the previous conclusion derived from fMRI studies left VLPFC supports selection of the target verb representations, even if they were retrieved from semantic memory rapidly and effortlessly. The discordance between MEG and fMRI findings in verb generation task may stem from different modes of neural activation captured by phase-locked activity in MEG and slow changes of blood-oxygen-level-dependent (BOLD) signal in fMRI.

Category-Selectivity in Human Visual Cortex Follows Cortical Topology: A Grouped icEEG Study

Neuroimaging studies suggest that category-selective regions in higher-order visual cortex are topologically organized around specific anatomical landmarks: the mid-fusiform sulcus (MFS) in the ventral temporal cortex (VTC) and lateral occipital sulcus (LOS) in the lateral occipital cortex (LOC). To derive precise structure-function maps from direct neural signals, we collected intracranial EEG (icEEG) recordings in a large human cohort (n = 26) undergoing implantation of subdural electrodes. A surface-based approach to grouped icEEG analysis was used to overcome challenges from sparse electrode coverage within subjects and variable cortical anatomy across subjects. The topology of category-selectivity in bilateral VTC and LOC was assessed for five classes of visual stimuli-faces, animate non-face (animals/body-parts), places, tools, and words-using correlational and linear mixed effects analyses. In the LOC, selectivity for living (faces and animate non-face) and non-living (places and tools) classes was arranged in a ventral-to-dorsal axis along the LOS. In the VTC, selectivity for living and non-living stimuli was arranged in a latero-medial axis along the MFS. Written word-selectivity was reliably localized to the intersection of the left MFS and the occipito-temporal sulcus. These findings provide direct electrophysiological evidence for topological information structuring of functional representations within higher-order visual cortex.

Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change

The link between object perception and neural activity in visual cortical areas is a problem of fundamental importance in neuroscience. Here we show that electrical potentials from the ventral temporal cortical surface in humans contain sufficient information for spontaneous and near-instantaneous identification of a subject's perceptual state. Electrocorticographic (ECoG) arrays were placed on the subtemporal cortical surface of seven epilepsy patients. Grayscale images of faces and houses were displayed rapidly in random sequence. We developed a template projection approach to decode the continuous ECoG data stream spontaneously, predicting the occurrence, timing and type of visual stimulus. In this setting, we evaluated the independent and joint use of two well-studied features of brain signals, broadband changes in the frequency power spectrum of the potential and deflections in the raw potential trace (event-related potential; ERP). Our ability to predict both the timing of stimulus onset and the type of image was best when we used a combination of both the broadband response and ERP, suggesting that they capture different and complementary aspects of the subject's perceptual state. Specifically, we were able to predict the timing and type of 96% of all stimuli, with less than 5% false positive rate and a ~20ms error in timing.

Electrocorticography reveals the temporal dynamics of posterior parietal cortical activity during recognition memory decisions

Theories of the neurobiology of episodic memory predominantly focus on the contributions of medial temporal lobe structures, based on extensive lesion, electrophysiological, and imaging evidence. Against this backdrop, functional neuroimaging data have unexpectedly implicated left posterior parietal cortex (PPC) in episodic retrieval, revealing distinct activation patterns in PPC subregions as humans make memory-related decisions. To date, theorizing about the functional contributions of PPC has been hampered by the absence of information about the temporal dynamics of PPC activity as retrieval unfolds. Here, we leveraged electrocorticography to examine the temporal profile of high gamma power (HGP) in dorsal PPC subregions as participants made old/new recognition memory decisions. A double dissociation in memory-related HGP was observed, with activity in left intraparietal sulcus (IPS) and left superior parietal lobule (SPL) differing in time and sign for recognized old items (Hits) and correctly rejected novel items (CRs). Specifically, HGP in left IPS increased for Hits 300-700 ms poststimulus onset, and decayed to baseline ∼200 ms preresponse. By contrast, HGP in left SPL increased for CRs early after stimulus onset (200-300 ms) and late in the memory decision (from 700 ms to response). These memory-related effects were unique to left PPC, as they were not observed in right PPC. Finally, memory-related HGP in left IPS and SPL was sufficiently reliable to enable brain-based decoding of the participant's memory state at the single-trial level, using multivariate pattern classification. Collectively, these data provide insights into left PPC temporal dynamics as humans make recognition memory decisions.

Face, eye, and body selective responses in fusiform gyrus and adjacent cortex: an intracranial EEG study

Functional MRI (fMRI) studies have investigated the degree to which processing of whole faces, face-parts, and bodies are differentially localized within the fusiform gyrus and adjacent ventral occipitotemporal cortex. While some studies have emphasized the spatial differentiation of processing into discrete areas, others have emphasized the overlap of processing and the importance of distributed patterns of activity. Intracranial EEG (iEEG) recorded from subdural electrodes provides excellent temporal and spatial resolution of local neural activity, and thus provides an alternative method to fMRI for studying differences and commonalities in face and body processing. In this study we recorded iEEG from 12 patients while they viewed images of novel faces, isolated eyes, headless bodies, and flowers. Event-related potential analysis identified 69 occipitotemporal sites at which there was a face-, eye-, or body-selective response when contrasted to flowers. However, when comparing faces, eyes, and bodies to each other at these sites, we identified only 3 face-specific, 13 eye-specific, and 1 body-specific electrodes. Thus, at the majority of sites, faces, eyes, and bodies evoked similar responses. However, we identified ten locations at which the amplitude of the responses spatially varied across adjacent electrodes, indicating that the configuration of current sources and sinks were different for faces, eyes, and bodies. Our results also demonstrate that eye-sensitive regions are more abundant and more purely selective than face- or body-sensitive regions, particularly in lateral occipitotemporal cortex.

Interpretable Semantic Vectors from a Joint Model of Brain- and Text-Based Meaning

Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies.

[Simultaneous EEG-fMRI measurements: insights in applications and challenges]

BACKGROUND

The following article presents an introduction to simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) measurements which have undergone a huge development during the last few years.

OBJECTIVES

The idea behind combining both non-invasive methods is to join the excellent temporal resolution of EEG (ms) together with the superior spatial resolution of fMRI (mm). In this article the status quo of the method and perspectives regarding multimodal imaging are discussed.

MATERIAL AND METHODS

Simultaneous EEG-fMRI measurements are affected by scanner and cardioballistic artifacts. We present common artifact subtraction methods in order to achieve a feasible data quality and outline what to consider when planning and recording EEG and fMRI simultaneously. Moreover, we discuss different analysis strategies.

RESULTS

Combined EEG-fMRI measurements have already increased our knowledge about the underlying relationships between the blood oxygenation level-dependent (BOLD) response and the EEG signal and are applied to answer widespread research questions. Simultaneous measurements are an essential part of multimodal imaging in investigating the underlying processing mechanisms of the brain as well as in advancing our understanding of neuropsychiatric diseases.

CONCLUSIONS

Current developments in multimodal imaging focus on the combination of electrophysiological and MRI parameters within ultra-high field MRI as well as on positron emission tomography (PET) in a trimodal approach.

Repetition suppression of face-selective evoked and induced EEG recorded from human cortex

In functional MRI studies, repetition suppression refers to the reduction of hemodynamic activation to repeated stimulus presentation. For example, the repeated presentation of a face reduces the hemodynamic response evoked by faces in the fusiform gyrus. The neural events that underlie repetition suppression are not well understood. Indeed, in contrast to the hemodynamic response, the face-specific N200 recorded from subdural electrodes on the ventral occipitotemporal cortex, primarily along the fusiform gyrus, has been reported to be insensitive to face-identity repetition. We have previously described a face-specific broadband gamma (30-100 Hz) response at ventral face-specific N200 sites that is functionally dissociable from the N200. In this study, we investigate whether gamma and other components of the electroencephalogram spectrum are affected by face-identity repetition independently of the N200. Participants viewed sequentially presented identical faces. At sites on and around the fusiform gyrus, we found that face repetition modulated alpha (8-12 Hz), low-gamma (30-60 Hz), and high-gamma (60-100 Hz) synchrony, but not the N200. These findings provide evidence of a spatially co-localized progression of face processing. Whereas the N200 reflects an initial obligatory response that is less sensitive to face-identity repetition, the subsequent spectral fluctuations reflect more elaborative face processing and are thus sensitive to face novelty. It is notable that the observed modulations were different for different frequency bands. We observed repetition suppression of broadband gamma, but repetition enhancement of alpha synchrony. This difference is discussed with regard to an existing model of repetition suppression and behavioral repetition priming.

Alternating zones selective to faces and written words in the human ventral occipitotemporal cortex

Recognition of faces and written words is associated with category-specific brain activation in the ventral occipitotemporal cortex (vOT). However, topological and functional relationships between face-selective and word-selective vOT regions remain unclear. In this study, we collected data from patients with intractable epilepsy who underwent high-density recording of surface field potentials in the vOT. "Faces" and "letterstrings" induced outstanding category-selective responses among the 24 visual categories tested, particularly in high-γ band powers. Strikingly, within-hemispheric analysis revealed alternation of face-selective and letterstring-selective zones within the vOT. Two distinct face-selective zones located anterior and posterior portions of the mid-fusiform sulcus whereas letterstring-selective zones alternated between and outside of these 2 face-selective zones. Further, a classification analysis indicated that activity patterns of these zones mostly represent dedicated categories. Functional connectivity analysis using Granger causality indicated asymmetrically directed causal influences from face-selective to letterstring-selective regions. These results challenge the prevailing view that different categories are represented in distinct contiguous regions in the vOT.

BOLD consistently matches electrophysiology in human sensorimotor cortex at increasing movement rates: a combined 7T fMRI and ECoG study on neurovascular coupling

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to measure human brain function and relies on the assumption that hemodynamic changes mirror the underlying neuronal activity. However, an often reported saturation of the BOLD response at high movement rates has led to the notion of a mismatch in neurovascular coupling. We combined BOLD fMRI at 7T and intracranial electrocorticography (ECoG) to assess the relationship between BOLD and neuronal population activity in human sensorimotor cortex using a motor task with increasing movement rates. Though linear models failed to predict BOLD responses from the task, the measured BOLD and ECoG responses from the same tissue were in good agreement. Electrocorticography explained almost 80% of the mismatch between measured- and model-predicted BOLD responses, indicating that in human sensorimotor cortex, a large portion of the BOLD nonlinearity with respect to behavior (movement rate) is well predicted by electrophysiology. The results further suggest that other reported examples of BOLD mismatch may be related to neuronal processes, rather than to neurovascular uncoupling.

Single trial decoding of belief decision making from EEG and fMRI data using independent components features

The complex task of assessing the veracity of a statement is thought to activate uniquely distributed brain regions based on whether a subject believes or disbelieves a given assertion. In the current work, we present parallel machine learning methods for predicting a subject's decision response to a given propositional statement based on independent component (IC) features derived from EEG and fMRI data. Our results demonstrate that IC features outperformed features derived from event related spectral perturbations derived from any single spectral band, yet were similar to accuracy across all spectral bands combined. We compared our diagnostic IC spatial maps with our conventional general linear model (GLM) results, and found that informative ICs had significant spatial overlap with our GLM results, yet also revealed unique regions like amygdala that were not statistically significant in GLM analyses. Overall, these results suggest that ICs may yield a parsimonious feature set that can be used along with a decision tree structure for interpretation of features used in classifying complex cognitive processes such as belief and disbelief across both fMRI and EEG neuroimaging modalities.

Training of affect recognition in schizophrenia patients with violent offences: behavioral treatment effects and electrophysiological correlates

Violent offenders with schizophrenia have a particularly poor performance level in facial affect recognition. Nineteen male schizophrenia patients, who had been committed to psychiatric hospital detention because of violent offences and lack of criminal responsibility, were recruited to receive the Training of Affect Recognition (TAR). Performance in the Pictures of Facial Affect (PFA)-test and event-related potentials (ERPs) were registered in a pre-post-treatment design. TAR was feasible with a very high treatment effect (Cohen's d = 1.88), which persisted for 2 months post-treatment. ERPs remained unchanged post- vs. pre-treatment, while low resolution brain electromagnetic tomography (LORETA) revealed activation decreases in left-hemispheric parietal-temporal-occipital regions at 172 msec and activation increases in right dorsolateral prefrontal cortex and anterior cingulate at 250 msec. Possibly, violent offenders with schizophrenia are particularly amenable to TAR because of a high level of dysfunction at baseline. Post- vs. pre-treatment changes of neural activity (LORETA) may mirror a gain of efficiency in structural face decoding and a shift towards a more reflective mode of emotional face decoding, relying on increased frontal brain activity. Functional magnetic resonance imaging (BOLD-fMRI) -data from another study further supports this notion. TAR treatment might enable subjects with schizophrenia and a disposition to violence to reach a higher degree of deliberation of their reactive behavior to facial affect stimuli.

Probabilistic atlases for face and biological motion perception: an analysis of their reliability and overlap

Neuroimaging research has identified several category-selective regions in visual cortex that respond most strongly when viewing an exemplar image from a preferred category, such as faces. Recent studies, however, have suggested a more complex pattern of activation that has been heretofore unrecognized, e.g., the presence of additional patches of activation to faces beyond the well-studied fusiform face area, and the activation of ostensible face selective regions by animate motion of non-biological forms. Here, we characterize the spatial pattern of brain activity evoked by viewing faces or biological motion in large fMRI samples (N>120). We create probabilistic atlases for both face and biological motion activation, and directly compare their spatial patterns of activation. Our findings support the suggestion that the fusiform face area is composed of at least two separable foci of activation. The face-evoked response in the fusiform and nearby ventral temporal cortex has good reliability across runs; however, we found surprisingly high variability in lateral brain regions by faces, and for all brain regions by biological motion, which had an overall much lower effect size. We found that faces and biological motion evoke substantially overlapping activation distributions in both ventral and lateral occipitotemporal cortices. The peaks of activation for these different categories within these overlapping regions were close but distinct.

Asynchronous broadband signals are the principal source of the BOLD response in human visual cortex

BACKGROUND

Activity in the living human brain can be studied using multiple methods, spanning a wide range of spatial and temporal resolutions. We investigated the relationship between electric field potentials measured with electrocorticography (ECoG) and the blood oxygen level-dependent (BOLD) response measured with functional magnetic resonance imaging (fMRI). We set out to explain the full set of measurements by modeling the underlying neural circuits.

RESULTS

ECoG responses in visual cortex can be separated into two visually driven components. One component is a specific temporal response that follows each stimulus contrast reversal ("stimulus locked"); the other component is an increase in the response variance ("asynchronous"). For electrodes in visual cortex (V1, V2, V3), the two measures respond to stimuli in the same region of visual space, but they have different spatial summation properties. The stimulus-locked ECoG component sums contrast approximately linearly across space; spatial summation in the asynchronous ECoG component is subadditive. Spatial summation measured using BOLD closely matches the asynchronous component. We created a neural simulation that accurately captures the main features of the ECoG time series; in the simulation, the stimulus-locked and asynchronous components arise from different neural circuits.

CONCLUSIONS

These observations suggest that the two ECoG components arise from different neural sources within the same cortical region. The spatial summation measurements and simulations suggest that the BOLD response arises primarily from neural sources that generate the asynchronous broadband ECoG component.

Spatial and object-based attention modulates broadband high-frequency responses across the human visual cortical hierarchy

One of the puzzling aspects in the visual attention literature is the discrepancy between electrophysiological and fMRI findings: whereas fMRI studies reveal strong attentional modulation in the earliest visual areas, single-unit and local field potential studies yielded mixed results. In addition, it is not clear to what extent spatial attention effects extend from early to high-order visual areas. Here we addressed these issues using electrocorticography recordings in epileptic patients. The patients performed a task that allowed simultaneous manipulation of both spatial and object-based attention. They were presented with composite stimuli, consisting of a small object (face or house) superimposed on a large one, and in separate blocks, were instructed to attend one of the objects. We found a consistent increase in broadband high-frequency (30-90 Hz) power, but not in visual evoked potentials, associated with spatial attention starting with V1/V2 and continuing throughout the visual hierarchy. The magnitude of the attentional modulation was correlated with the spatial selectivity of each electrode and its distance from the occipital pole. Interestingly, the latency of the attentional modulation showed a significant decrease along the visual hierarchy. In addition, electrodes placed over high-order visual areas (e.g., fusiform gyrus) showed both effects of spatial and object-based attention. Overall, our results help to reconcile previous observations of discrepancy between fMRI and electrophysiology. They also imply that spatial attention effects can be found both in early and high-order visual cortical areas, in parallel with their stimulus tuning properties.

Relation between functional magnetic resonance imaging (fMRI) and single neuron, local field potential (LFP) and electrocorticography (ECoG) activity in human cortex

The relation between changes in the blood oxygen dependent metabolic changes imaged by functional magnetic resonance imaging (fMRI) and neural events directly recorded from human cortex from single neurons, local field potentials (LFPs) and electrocorticogram (ECoG) is critically reviewed, based on the published literature including findings from the authors' laboratories. All these data are from special populations, usually patients with medically refractory epilepsy, as this provides the major opportunity for direct cortical neuronal recording in humans. For LFP and ECoG changes are often sought in different frequency bands, for single neurons in frequency of action potentials. Most fMRI studies address issues of functional localization. The relation of those findings to localized changes in neuronal recordings in humans has been established in several ways. Only a few studies have directly compared changes in activity from the same sites in the same individual, using the same behavioral measure. More often the comparison has been between fMRI and electrophysiologic changes in populations recorded from the same functional anatomic system as defined by lesion effects; in a few studies those systems have been defined by fMRI changes such as the "default" network. The fMRI-electrophysiologic relationships have been evaluated empirically by colocalization of significant changes, and by quantitative analyses, often multiple linear regression. There is some evidence that the fMRI-electrophysiology relationships differ in different cortical areas, particularly primary motor and sensory cortices compared to association cortex, but also within areas of association cortex. Although crucial for interpretation of fMRI changes as reflecting neural activity in human cortex, controversy remains as to these relationships. Supported by: Dutch Technology Foundation and University of Utrecht Grant UGT7685, ERC-Advanced grant 320708 (NR) and NIH grant NS065186 (JO).

Induced Theta Activity as a Biomarker for a Morbid Effect of Alcoholism on the Brain in Long-Term Abstinent Alcoholics

Event-related, target stimulus-phase-locked (evoked) brain activity in both the time and time-frequency (TF) domains (the P3b ERP; evoked theta oscillations) has been shown to be reduced in alcoholics. Recently, studies have suggested that there is alcohol-related information in the non-stimulus-phase-locked (induced) theta TF activity. We applied TF analysis to target stimulus event-related EEG recorded during an oddball task from 41 long-term abstinent alcoholics (LTAA) and 74 nonalcoholic controls (NAC) to investigate the relationship between P3b, evoked theta, and induced theta activity. Results showed that an event-related synchronization (ERS) of induced theta (1) was larger in LTAA compared to NAC, and (2) was sensitive to differences between LTAA and NAC groups that was independent of the differences accounted for by P3b amplitude or evoked theta. These findings suggest that increased induced theta ERS may likely be a biomarker for a morbid effect of alcohol abuse on brain function.

Proceedings of the Third International Workshop on Advances in Electrocorticography

The Third International Workshop on Advances in Electrocorticography (ECoG) was convened in Washington, DC, on November 10-11, 2011. As in prior meetings, a true multidisciplinary fusion of clinicians, scientists, and engineers from many disciplines gathered to summarize contemporary experiences in brain surface recordings. The proceedings of this meeting serve as evidence of a very robust and transformative field but will yet again require revision to incorporate the advances that the following year will surely bring.

High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research

Human intracranial EEG (iEEG) recordings are primarily performed in epileptic patients for presurgical mapping. When patients perform cognitive tasks, iEEG signals reveal high-frequency neural activities (HFAs, between around 40 Hz and 150 Hz) with exquisite anatomical, functional and temporal specificity. Such HFAs were originally interpreted in the context of perceptual or motor binding, in line with animal studies on gamma-band ('40 Hz') neural synchronization. Today, our understanding of HFA has evolved into a more general index of cortical processing: task-induced HFA reveals, with excellent spatial and time resolution, the participation of local neural ensembles in the task-at-hand, and perhaps the neural communication mechanisms allowing them to do so. This review promotes the claim that studying HFA with iEEG provides insights into the neural bases of cognition that cannot be derived as easily from other approaches, such as fMRI. We provide a series of examples supporting that claim, drawn from studies on memory, language and default-mode networks, and successful attempts of real-time functional mapping. These examples are followed by several guidelines for HFA research, intended for new groups interested by this approach. Overall, iEEG research on HFA should play an increasing role in cognitive neuroscience in humans, because it can be explicitly linked to basic research in animals. We conclude by discussing the future evolution of this field, which might expand that role even further, for instance through the use of multi-scale electrodes and the fusion of iEEG with MEG and fMRI.