Neuronal correlates of functional magnetic resonance imaging in human temporal cortex

The brain dynamics of visuospatial perspective-taking captured by intracranial EEG

Visuospatial perspective-taking (VPT) is the ability to imagine a scene from a position different from the one used in self-perspective judgments (SPJ). We typically use VPT to understand how others see the environment. VPT requires overcoming the self-perspective, and impairments in this process are implicated in various brain disorders, such as schizophrenia and autism. However, the underlying brain areas of VPT are not well distinguished from SPJ-related ones and from domain-general responses to both perspectives. In addition, hierarchical processing theory suggests that domain-specific processes emerge over time from domain-general ones. It mainly focuses on the sensory system, but outside of it, support for this hypothesis is lacking. Therefore, we aimed to spatiotemporally distinguish brain responses domain-specific to VPT from the specific ones to self-perspective, and domain-general responses to both perspectives. In particular, we intended to test whether VPT- and SPJ specific responses begin later than the general ones. We recorded intracranial EEG data from 30 patients with epilepsy who performed a task requiring laterality judgments during VPT and SPJ, and analyzed the spatiotemporal features of responses in the broad gamma band (50-150 Hz). We found VPT-specific processing in a more extensive brain network than SPJ-specific processing. Their dynamics were similar, but both differed from the general responses, which began earlier and lasted longer. Our results anatomically distinguish VPT-specific from SPJ-specific processing. Furthermore, we temporally differentiate between domain-specific and domain-general processes both inside and outside the sensory system, which serves as a novel example of hierarchical processing.

Timing of Allocentric and Egocentric Spatial Processing in Human Intracranial EEG

Spatial reference frames (RFs) play a key role in spatial cognition, especially in perception, spatial memory, and navigation. There are two main types of RFs: egocentric (self-centered) and allocentric (object-centered). Although many fMRI studies examined the neural correlates of egocentric and allocentric RFs, they could not sample the fast temporal dynamics of the underlying cognitive processes. Therefore, the interaction and timing between these two RFs remain unclear. Taking advantage of the high temporal resolution of intracranial EEG (iEEG), we aimed to determine the timing of egocentric and allocentric information processing and describe the brain areas involved. We recorded iEEG and analyzed broad gamma activity (50-150 Hz) in 37 epilepsy patients performing a spatial judgment task in a three-dimensional circular virtual arena. We found overlapping activation for egocentric and allocentric RFs in many brain regions, with several additional egocentric- and allocentric-selective areas. In contrast to the egocentric responses, the allocentric responses peaked later than the control ones in frontal regions with overlapping selectivity. Also, across several egocentric or allocentric selective areas, the egocentric selectivity appeared earlier than the allocentric one. We identified the maximum number of egocentric-selective channels in the medial occipito-temporal region and allocentric-selective channels around the intraparietal sulcus in the parietal cortex. Our findings favor the hypothesis that egocentric spatial coding is a more primary process, and allocentric representations may be derived from egocentric ones. They also broaden the dominant view of the dorsal and ventral streams supporting egocentric and allocentric space coding, respectively.

Abnormal default mode network could be a potential prognostic marker in patients with disorders of consciousness

OBJECTIVES

The study aimed to investigate disorders of consciousness (DOC) mechanisms of patients with severe traumatic brain injury (sTBI) related to default mode network (DMN) and to introduce a machine learning model that predicts the prognosis of these patients for 6 months.

METHODS

The sTBI patients suffering from DOC and healthy controls underwent functional magnetic resonance imaging. We defined patients with Extended Glasgow Outcome Score ≥ 5 as good outcome group, otherwise they were poor outcome group. The differences of DMN between sTBI and healthy controls and between good and poor outcome groups were compared. Based on the brain regions with altered functional connectivity between good and poor outcome groups, they were divided into 8 regions of interests according to side. The Z values of the regions of interests were extracted by Rest 1.8. Based on Z values, the Subspace K-Nearest Neighbor (Subspace KNN) was conducted to classify prognosis of sTBI patients suffering from DOC.

RESULTS

A total of 84 DMNs derived from patients and 45 DMNs from healthy controls were finally analyzed. The connectivity of the DMN was significantly decreased in sTBI patients suffering from DOC (Alphasim corrected, P < 0.05). In addition, compared with the poor outcome group (DMN samples = 60), the brain regions of DMN with decreased functional connectivity in the good outcome group (DMN samples = 24) the following bilateral areas: brodman Area 11, anterior cingulate and paracingulate gyri, brodman Area 25, olfactory cortex (Alphasim corrected, P < 0.05). The ability of Subspace KNN machine learning to distinguish the prognosis of patients (area under curve) was 0.97.

CONCLUSIONS

The interruption of DMN may be one of the reasons for DOC in patients with sTBI. Furthermore, based on early DMN (1-4 weeks), Subspace KNN machine learning has the potential value to distinguish the prognosis (6 months after brain trauma) of sTBI patients suffering from DOC.

Distinct Neurophysiological Correlates of the fMRI BOLD Signal in the Hippocampus and Neocortex

Functional magnetic resonance imaging (fMRI) is among the foremost methods for mapping human brain function but provides only an indirect measure of underlying neural activity. Recent findings suggest that the neurophysiological correlates of the fMRI blood oxygenation level-dependent (BOLD) signal might be regionally specific. We examined the neurophysiological correlates of the fMRI BOLD signal in the hippocampus and neocortex, where differences in neural architecture might result in a different relationship between the respective signals. Fifteen human neurosurgical patients (10 female, 5 male) implanted with depth electrodes performed a verbal free recall task while electrophysiological activity was recorded simultaneously from hippocampal and neocortical sites. The same patients subsequently performed a similar version of the task during a later fMRI session. Subsequent memory effects (SMEs) were computed for both imaging modalities as patterns of encoding-related brain activity predictive of later free recall. Linear mixed-effects modeling revealed that the relationship between BOLD and gamma-band SMEs was moderated by the lobar location of the recording site. BOLD and high gamma (70-150 Hz) SMEs positively covaried across much of the neocortex. This relationship was reversed in the hippocampus, where a negative correlation between BOLD and high gamma SMEs was evident. We also observed a negative relationship between BOLD and low gamma (30-70 Hz) SMEs in the medial temporal lobe more broadly. These results suggest that the neurophysiological correlates of the BOLD signal in the hippocampus differ from those observed in the neocortex.SIGNIFICANCE STATEMENT The BOLD signal forms the basis of fMRI but provides only an indirect measure of neural activity. Task-related modulation of BOLD signals are typically equated with changes in gamma-band activity; however, relevant empirical evidence comes largely from the neocortex. We examined neurophysiological correlates of the BOLD signal in the hippocampus, where the differing neural architecture might result in a different relationship between the respective signals. We identified a positive relationship between encoding-related changes in BOLD and gamma-band activity in the frontal and parietal cortices. This effect was reversed in the hippocampus, where BOLD and gamma-band effects negatively covaried. These results suggest regional variability in the transfer function between neural activity and the BOLD signal in the hippocampus and neocortex.

Multi-modal Mapping of the Face Selective Ventral Temporal Cortex-A Group Study With Clinical Implications for ECS, ECoG, and fMRI

Face recognition is impaired in patients with prosopagnosia, which may occur as a side effect of neurosurgical procedures. Face selective regions on the ventral temporal cortex have been localized with electrical cortical stimulation (ECS), electrocorticography (ECoG), and functional magnetic resonance imagining (fMRI). This is the first group study using within-patient comparisons to validate face selective regions mapping, utilizing the aforementioned modalities. Five patients underwent surgical treatment of intractable epilepsy and joined the study. Subdural grid electrodes were implanted on their ventral temporal cortices to localize seizure foci and face selective regions as part of the functional mapping protocol. Face selective regions were identified in all patients with fMRI, four patients with ECoG, and two patients with ECS. From 177 tested electrode locations in the region of interest (ROI), which is defined by the fusiform gyrus and the inferior temporal gyrus, 54 face locations were identified by at least one modality in all patients. fMRI mapping showed the highest detection rate, revealing 70.4% for face selective locations, whereas ECoG and ECS identified 64.8 and 31.5%, respectively. Thus, 28 face locations were co-localized by at least two modalities, with detection rates of 89.3% for fMRI, 85.7% for ECoG and 53.6 % for ECS. All five patients had no face recognition deficits after surgery, even though five of the face selective locations, one obtained by ECoG and the other four by fMRI, were within 10 mm to the resected volumes. Moreover, fMRI included a quite large volume artifact on the ventral temporal cortex in the ROI from the anatomical structures of the temporal base. In conclusion, ECS was not sensitive in several patients, whereas ECoG and fMRI even showed activation within 10 mm to the resected volumes. Considering the potential signal drop-out in fMRI makes ECoG the most reliable tool to identify face selective locations in this study. A multimodal approach can improve the specificity of ECoG and fMRI, while simultaneously minimizing the number of required ECS sessions. Hence, all modalities should be considered in a clinical mapping protocol entailing combined results of co-localized face selective locations.

Mapping the Scene and Object Processing Networks by Intracranial EEG

Human perception and cognition are based predominantly on visual information processing. Much of the information regarding neuronal correlates of visual processing has been derived from functional imaging studies, which have identified a variety of brain areas contributing to visual analysis, recognition, and processing of objects and scenes. However, only two of these areas, namely the parahippocampal place area (PPA) and the lateral occipital complex (LOC), were verified and further characterized by intracranial electroencephalogram (iEEG). iEEG is a unique measurement technique that samples a local neuronal population with high temporal and anatomical resolution. In the present study, we aimed to expand on previous reports and examine brain activity for selectivity of scenes and objects in the broadband high-gamma frequency range (50–150 Hz). We collected iEEG data from 27 epileptic patients while they watched a series of images, containing objects and scenes, and we identified 375 bipolar channels responding to at least one of these two categories. Using K-means clustering, we delineated their brain localization. In addition to the two areas described previously, we detected significant responses in two other scene-selective areas, not yet reported by any electrophysiological studies; namely the occipital place area (OPA) and the retrosplenial complex. Moreover, using iEEG we revealed a much broader network underlying visual processing than that described to date, using specialized functional imaging experimental designs. Here, we report the selective brain areas for scene processing include the posterior collateral sulcus and the anterior temporal region, which were already shown to be related to scene novelty and landmark naming. The object-selective responses appeared in the parietal, frontal, and temporal regions connected with tool use and object recognition. The temporal analyses specified the time course of the category selectivity through the dorsal and ventral visual streams. The receiver operating characteristic analyses identified the PPA and the fusiform portion of the LOC as being the most selective for scenes and objects, respectively. Our findings represent a valuable overview of visual processing selectivity for scenes and objects based on iEEG analyses and thus, contribute to a better understanding of visual processing in the human brain.

Decreased resting gamma activity in adult attention deficit/hyperactivity disorder

Objectives: To delineate task-free gamma activity in adult ADHD and healthy control subjects based on high-density EEG recordings. Relationship of gamma activity with symptom severity was also examined, since gamma activity is considered to be an index of network functions in the brain that underlie higher-order cognitive processes.Methods: Spontaneous EEG was recorded in adult ADHD subjects (N = 42; 25 methylphenidate-naïve and 17 on methylphenidate treatment) and controls (N = 59) with eyes open. EEG absolute power gamma was investigated in the gamma₁ (30.25-39 Hz) and gamma₂ (39.25-48 Hz) frequency bands.Results: Gamma₁ and gamma₂ activity was diminished in ADHD compared with healthy control subjects. The difference between ADHD and controls was the most pronounced in the right centroparietal region for both gamma₁ and gamma₂. Inverse associations were found between gamma₁ and gamma₂ activity and ADHD symptoms in centroparietal scalp regions.Conclusions: Gamma activity is reduced in adult ADHD, and the reduction has a predominantly right centroparietal distribution. Our findings are consistent with childhood ADHD literature with respect to diminished posterior gamma activity in patients, which may reflect altered dorsal attention network functions. Gamma abnormalities might provide a link between neurophysiological functioning and neuropsychological deficiencies, thereby offering an opportunity to investigate the neurobiological mechanisms that underlie the clinical symptoms of ADHD.

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.

Neurocognitive Profiles in Childhood Absence Epilepsy

Although neuropsychological studies have demonstrated specific cognitive impairments in children with childhood absence epilepsy (CAE), the potential role of the frontal lobe in these cognitive deficits remains unclear. We therefore evaluated cognitive functions related to and unrelated to the functionality of the frontal lobe in childhood absence epilepsy patients and control subjects. Thirty-seven childhood absence epilepsy patients and 37 age- and gender-matched healthy control subjects were recruited and assessed using a computerized neuropsychological test battery. Childhood absence epilepsy patients, especially a drug-naïve subgroup, showed cognitive deficits in reasoning, visual attention, and executive function, which are typical cognitive functions of the frontal lobe. In contrast, treated childhood absence epilepsy patients only exhibited cognitive deficits in visual attention. There were no significant between-group differences for other cognitive tests. Our findings suggest that frontal lobe-related cognitive deficits represent the characteristic neuropsychological profile associated with childhood absence epilepsy.

Neural Activity Elicited by a Cognitive Task can be Detected in Single-Trials with Simultaneous Intracerebral EEG-fMRI Recordings

Recent studies have shown that it is feasible to record simultaneously intracerebral EEG (icEEG) and functional magnetic resonance imaging (fMRI) in patients with epilepsy. While it has mainly been used to explore the hemodynamic changes associated with epileptic spikes, this approach could also provide new insight into human cognition. However, the first step is to ensure that cognitive EEG components, that have lower amplitudes than epileptic spikes, can be appropriately detected under fMRI. We compared the high frequency activities (HFA, 50-150[Formula: see text]Hz) elicited by a reading task in icEEG-only and subsequent icEEG-fMRI in the same patients ([Formula: see text]), implanted with depth electrodes. Comparable responses were obtained, with 71% of the recording sites that responded during the icEEG-only session also responding during the icEEG-fMRI session. For all the remaining sites, nearby clusters (distant of 7[Formula: see text]mm or less) also demonstrated significant HFA increase during the icEEG-fMRI session. Significant HFA increases were also observable at the single-trial level in icEEG-fMRI recordings. Our results show that low-amplitude icEEG signal components such as cognitive-induced HFAs can be reliably recorded with simultaneous fMRI. This paves the way for the use of icEEG-fMRI to address various fundamental and clinical issues, notably the identification of the neural correlates of the BOLD signal.

Electrocorticographic mapping of expressive language function without requiring the patient to speak: A report of three cases

Objective

Patients requiring resective brain surgery often undergo functional brain mapping during perioperative planning to localize expressive language areas. Currently, all established protocols to perform such mapping require substantial time and patient participation during verb generation or similar tasks. These issues can make language mapping impractical in certain clinical circumstances (e.g., during awake craniotomies) or with certain populations (e.g., pediatric patients). Thus, it is important to develop new techniques that reduce mapping time and the requirement for active patient participation. Several neuroscientific studies reported that the mere auditory presentation of speech stimuli can engage not only receptive but also expressive language areas. Here, we tested the hypothesis that submission of electrocorticographic (ECoG) recordings during a short speech listening task to an appropriate analysis procedure can identify eloquent expressive language cortex without requiring the patient to speak.

Methods

Three patients undergoing temporary placement of subdural electrode grids passively listened to stories while we recorded their ECoG activity. We identified those sites whose activity in the broadband gamma range (70–170 Hz) changed immediately after presentation of the speech stimuli with respect to a prestimulus baseline.

Results

Our analyses revealed increased broadband gamma activity at distinct locations in the inferior frontal cortex, superior temporal gyrus, and/or perisylvian areas in all three patients and premotor and/or supplementary motor areas in two patients. The sites in the inferior frontal cortex that we identified with our procedure were either on or immediately adjacent to locations identified using electrical cortical stimulation (ECS) mapping.

Conclusions

The results of this study provide encouraging preliminary evidence that it may be possible that a brief and practical protocol can identify expressive language areas without requiring the patient to speak. This protocol could provide the clinician with a map of expressive language cortex within a few minutes. This may be useful as an adjunct to ECS interrogation or as an alternative to mapping using functional magnetic resonance imaging (fMRI). In conclusion, with further development and validation in more subjects, the approach presented here could help in identifying expressive language areas in situations where patients cannot speak in response to task instructions.

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are important tools in cognitive and clinical neuroscience. Combined EEG-fMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level-dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (EEG-fMRI mapping), or exploring a range of EEG-derived quantities to determine which best explain colocalised BOLD fluctuations (local EEG-fMRI coupling). While reviewing studies of different forms of brain activity (epileptic and nonepileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations.

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.

Surface-based mixed effects multilevel analysis of grouped human electrocorticography

Electrocorticography (ECoG) in humans yields data with unmatched spatio-temporal resolution that provides novel insights into cognitive operations. However, the broader application of ECoG has been confounded by difficulties in accurately depicting individual data and performing statistically valid population-level analyses. To overcome these limitations, we developed methods for accurately registering ECoG data to individual cortical topology. We integrated this technique with surface-based co-registration and a mixed-effects multilevel analysis (MEMA) to control for variable cortical surface anatomy and sparse coverage across patients, as well as intra- and inter-subject variability. We applied this surface-based MEMA (SB-MEMA) technique to a face-recognition task dataset (n=22). Compared against existing techniques, SB-MEMA yielded results much more consistent with individual data and with meta-analyses of face-specific activation studies. We anticipate that SB-MEMA will greatly expand the role of ECoG in studies of human cognition, and will enable the generation of population-level brain activity maps and accurate multimodal comparisons.

Cerebral, subcortical, and cerebellar activation evoked by selective stimulation of muscle and cutaneous afferents: an fMRI study

Abstract We compared the brain areas that showed significant flow changes induced by selective stimulation of muscle and cutaneous afferents using fMRI BOLD imaging. Afferents arising from the right hand were studied in eight volunteers with electrical stimulation of the digital nerve of the index finger and over the motor point of the FDI muscle. Both methods evoked areas of significant activation cortically, subcortically, and in the cerebellum. Selective muscle afferent stimulation caused significant activation in motor-related areas. It also caused significantly greater activation within the contralateral precentral gyrus, insula, and within the ipsilateral cerebellum as well as greater areas of reduced blood flow when compared to the cutaneous stimuli. We demonstrated separate precentral and postcentral foci of excitation with muscle afferent stimulation. We conclude, contrary to the findings with evoked potentials, that muscle afferents evoke more widespread cortical, subcortical, and cerebellar activation than do cutaneous afferents. This emphasizes the importance, for studies of movement, of matching the kinematic aspects in order to avoid the results being confounded by alterations in muscle afferent activation. The findings are consistent with clinical observations of the movement consequences of sensory loss and may also be the basis for the contribution of disturbed sensorimotor processing to disorders of movement.

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.

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG-fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing.

Functional dysconnectivity in schizophrenia and its relationship to neural synchrony

Schizophrenia is a debilitating disorder of unknown cause. There is increasing momentum to consider functional dysconnectivity as an endophenotype of schizophrenia, and in particular, how it relates to cognition as a core feature of the disorder. Here, the authors review the conceptual models of functional dysconnectivity in schizophrenia to date, the evidence they are based on and some of the limitations of these models. The authors then propose 'neural synchrony' as a potential mechanism for functional dysconnectivity and review the current state of evidence for a link between neural synchrony and cognition in schizophrenia across behavioral, physiological, brain imaging, neurochemical and neurogenetic units of enquiry. The authors conclude by outlining the unmet needs in this field and give an outlook on how to fill these gaps.

Human Temporal Cortical Single Neuron Activity during Language: A Review

Findings from recordings of human temporal cortical single neuron activity during several measures of language, including object naming and word reading are reviewed and related to changes in activity in the same neurons during recent verbal memory and verbal associative learning measures, in studies conducted during awake neurosurgery for the treatment of epilepsy. The proportion of neurons changing activity with language tasks was similar in either hemisphere. Dominant hemisphere activity was characterized by relative inhibition, some of which occurred during overt speech, possibly to block perception of one’s own voice. However, the majority seems to represent a dynamic network becoming active with verbal memory encoding and especially verbal learning, but inhibited during performance of overlearned language tasks. Individual neurons are involved in different networks for different aspects of language, including naming or reading and naming in different languages. The majority of the changes in activity were tonic sustained shifts in firing. Patterned phasic activity for specific language items was very infrequently recorded. Human single neuron recordings provide a unique perspective on the biologic substrate for language, for these findings are in contrast to many of the findings from other techniques for investigating this.

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).

Emergence in the central nervous system

"Emergence" is an idea that has received much attention in consciousness literature, but it is difficult to find characterizations of that concept which are both specific and useful. I will precisely define and characterize a type of epistemic ("weak") emergence and show that it is a property of some neural circuits throughout the CNS, on micro-, meso- and macroscopic levels. I will argue that possession of this property can result in profoundly altered neural dynamics on multiple levels in cortex and other systems. I will first describe emergent neural entities (ENEs) abstractly. I will then show how ENEs function specifically and concretely, and demonstrate some implications of this type of emergence for the CNS.

Characteristic profiles of high gamma activity and blood oxygenation level-dependent responses in various language areas

High gamma activity (HGA) has been shown to be positively correlated with blood oxygenation level-dependent (BOLD) responses in the primary cortices with simple tasks. It is, however, an open question whether the correlation is simply applied to the association areas related to higher cognitive functions. The aim of this study is to investigate quantitative correlation between HGA and BOLD and their spatial and temporal profiles during semantic processing. Thirteen patients with intractable epilepsy underwent fMRI and electrocorticography (ECoG) with a word interpretation task to evoke language-related responses. Percent signal change of BOLD was calculated at each site of ECoG electrode, which has power amplification of high gamma band (60-120 Hz) activity. We transformed locations of individual electrodes and brains to a universal coordination using SPM8 and made the quantitative comparisons on a template brain. HGAs were increased in several language-related areas such as the inferior frontal and middle temporal gyri and were positively correlated with BOLD responses. The most striking finding was different temporal dynamics of HGAs in the different brain regions. Whereas the frontal lobe showed longer-lasting HGA, the HGA-intensity on the temporal lobe quickly declined. The different temporal dynamics of HGA might explain why routine language-fMRI hardly detected BOLD in the temporal lobe. This study clarified different neural oscillation and BOLD response in various brain regions during semantic processing and will facilitate practical utilization of fMRI for evaluating higher-order cognitive functions not only in basic neuroscience, but also in clinical practice.

Independence of early speech processing from word meaning

We combined magnetoencephalography (MEG) with magnetic resonance imaging and electrocorticography to separate in anatomy and latency 2 fundamental stages underlying speech comprehension. The first acoustic-phonetic stage is selective for words relative to control stimuli individually matched on acoustic properties. It begins ∼60 ms after stimulus onset and is localized to middle superior temporal cortex. It was replicated in another experiment, but is strongly dissociated from the response to tones in the same subjects. Within the same task, semantic priming of the same words by a related picture modulates cortical processing in a broader network, but this does not begin until ∼217 ms. The earlier onset of acoustic-phonetic processing compared with lexico-semantic modulation was significant in each individual subject. The MEG source estimates were confirmed with intracranial local field potential and high gamma power responses acquired in 2 additional subjects performing the same task. These recordings further identified sites within superior temporal cortex that responded only to the acoustic-phonetic contrast at short latencies, or the lexico-semantic at long. The independence of the early acoustic-phonetic response from semantic context suggests a limited role for lexical feedback in early speech perception.

Percepts to recollections: insights from single neuron recordings in the human brain

Transformation of experience into memories that can guide future behavior is a common ability across species. However, only humans can declare their perceptions and memories of experienced events (episodes). The medial temporal lobe (MTL) is central to episodic memory, yet the neuronal code underlying the translation from sensory information to memory remains unclear. Recordings from neurons within the brain in patients who have electrodes implanted for clinical reasons provide an opportunity to bridge physiology with cognitive theories. Recent evidence illustrates several striking response properties of MTL neurons. Responses are selective yet invariant, associated with conscious perception, can be internally generated and modulated, and spontaneously retrieved. Representation of information by these neurons is highly explicit, suggesting abstraction of information for future conscious recall.

Long-distance amplitude correlations in the high γ band reveal segregation and integration within the reading network

Reading sentences involves a distributed network of brain regions acting in concert surrounding the left sylvian fissure. The mechanisms of neural communication underlying the extraction and integration of verbal information across subcomponents of this reading network are still largely unknown. We recorded intracranial EEG activity in 12 epileptic human patients performing natural sentence reading and analyzed long-range corticocortical interactions between local neural activations. During a simple task contrasting semantic, phonological, and purely visual processes, we found process-specific neural activity elicited at the single-trial level, characterized by energy increases in a broad gamma band (40-150 Hz). Correlation analysis between task-induced gamma-band activations revealed a selective fragmentation of the network into specialized subnetworks supporting sentence-level semantic analysis and phonological processing. We extend the implications of our results beyond reading, to propose that gamma-band amplitude correlations might constitute a fundamental mechanism for large-scale neural integration during high-level cognition.

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.

Dopamine-related frontostriatal abnormalities in obesity and binge-eating disorder: emerging evidence for developmental psychopathology

Obesity and binge-eating disorder (BED) frequently arise in adolescence, which is a critical developmental time period where self-regulatory processes are formed. Indeed, both obesity and BED are thought to arise partly due to deficits in self-regulatory processes (i.e. lack of inhibitory control to overeat or binge). Recent neuroimaging studies have implicated the frontal cortex, a brain region involved in regulating inhibitory-control, and the striatum, which is thought to be involved in food reward, satiety and pleasure, in mediating responses to food cues and feeding in normal-weight individuals as well as obese and BED subjects. Intriguingly, frontostriatal circuits have been observed to be preferentially modulated in obese adults and similar associations have been observed in obese/overweight adolescents. Furthermore, brain dopamine (DA) is selectively altered in striatum in obese relative to normal-weight individuals, and frontostriatal regions constitute a major component of DA circuitry. The aim of this review will be to present the main findings from neuroimaging studies in obese and BED adults and adolescents, as these relate to frontostriatal circuitry, and to emphasize the potential for using functional neuroimaging in both humans and animals with the scope of obtaining information on developmental and molecular contributions to obesity and BED.

The human brain representation of odor identification

Odor identification (OI) tests are increasingly used clinically as biomarkers for Alzheimer's disease and schizophrenia. The aim of this study was to directly compare the neuronal correlates to identified odors vs. nonidentified odors. Seventeen females with normal olfactory function underwent a functional magnetic resonance imaging (fMRI) experiment with postscanning assessment of spontaneous uncued OI. An event-related analysis was performed to compare within-subject activity to spontaneously identified vs. nonidentified odors at the whole brain level, and in anatomic and functional regions of interest (ROIs) in the medial temporal lobe (MTL). Parameter estimate values and blood oxygenated level-dependent (BOLD) signal curves for correctly identified and nonidentified odors were derived from functional ROIs in hippocampus, entorhinal, piriform, and orbitofrontal cortices. Number of activated voxels and max parameter estimate values were obtained from anatomic ROIs in the hippocampus and the entorhinal cortex. At the whole brain level the correct OI gave rise to increased activity in the left entorhinal cortex and secondary olfactory structures, including the orbitofrontal cortex. Increased activation was also observed in fusiform, primary visual, and auditory cortices, inferior frontal plus inferior temporal gyri. The anatomic MTL ROI analysis showed increased activation in the left entorhinal cortex, right hippocampus, and posterior parahippocampal gyri in correct OI. In the entorhinal cortex and hippocampus the BOLD signal increased specifically in response to identified odors and decreased for nonidentified odors. In orbitofrontal and piriform cortices both identified and nonidentified odors gave rise to an increased BOLD signal, but the response to identified odors was significantly greater than that for nonidentified odors. These results support a specific role for entorhinal cortex and hippocampus in OI, whereas piriform and orbitofrontal cortices are active in both smelling and OI. Moreover, episodic as well as semantic memory systems appeared to support OI.

High-frequency oscillations and other electrophysiological biomarkers of epilepsy: clinical studies

Accurate localization of epileptogenic brain is critical for successful epilepsy surgery. Recent research using wide bandwidth intracranial EEG has demonstrated that interictal high-frequency oscillations are preferentially localized to the brain region generating spontaneous seizures, and are a potential biomarker of epileptogenic brain. The existence of an interictal, electrophysiological biomarker of epileptogenic brain has the potential to significantly advance epilepsy surgery by improving outcomes through improved localization and potentially eliminating the reliance on chronic intracranial EEG monitoring.

Relationships between spike-free local field potentials and spike timing in human temporal cortex

Intracortical recordings comprise both fast events, action potentials (APs), and slower events, known as local field potentials (LFPs). Although it is believed that LFPs mostly reflect local synaptic activity, it is unclear which of their signal components are most closely related to synaptic potentials and would therefore be causally related to the occurrence of individual APs. This issue is complicated by the significant contribution from AP waveforms, especially at higher LFP frequencies. In recordings of single-cell activity and LFPs from the human temporal cortex, we computed quantitative, nonlinear, causal dynamic models for the prediction of AP timing from LFPs, at millisecond resolution, before and after removing AP contributions to the LFP. In many cases, the timing of a significant number of single APs could be predicted from spike-free LFPs at different frequencies. Not surprisingly, model performance was superior when spikes were not removed. Cells whose activity was predicted by the spike-free LFP models generally fell into one of two groups: in the first group, neuronal spike activity was associated with specific phases of low LFP frequencies, lower spike activity at high LFP frequencies, and a stronger linear component in the spike-LFP model; in the second group, neuronal spike activity was associated with larger amplitude of high LFP frequencies, less frequent phase locking, and a stronger nonlinear model component. Spike timing in the first group was better predicted by the sign and level of the LFP preceding the spike, whereas spike timing in the second group was better predicted by LFP power during a certain time window before the spike.

A detailed analysis of functional magnetic resonance imaging in the frontal language area: a comparative study with extraoperative electrocortical stimulation

BACKGROUND

Functional magnetic resonance imaging (fMRI) is a less invasive way of mapping brain functions. The reliability of fMRI for localizing language-related function is yet to be determined.

OBJECTIVE

We performed a detailed analysis of language fMRI reliability by comparing the results of 3-T fMRI with maps determined by extraoperative electrocortical stimulation (ECS).

METHODS

This study was performed on 8 epileptic patients who underwent subdural electrode placement. The tasks performed during fMRI included verb generation, abstract/concrete categorization, and picture naming. We focused on the frontal lobe, which was effectively activated by these tasks. In extraoperative ECS, 4 tasks were combined to determine the eloquent areas: spontaneous speech, picture naming, reading, and comprehension. We calculated the sensitivity and specificity with different Z score thresholds for each task and appropriate matching criteria. For further analysis, we divided the frontal lobe into 5 areas and investigated intergyrus variations in sensitivity and specificity.

RESULTS

The abstract/concrete categorization task was the most sensitive and specific task in fMRI, whereas the picture naming task detected eloquent areas most efficiently in ECS. The combination of the abstract/concrete categorization task and a 3-mm matching criterion gave the best tradeoff (sensitivity, 83%; specificity, 61%) when the Z score was 2.24. As for intergyrus variation, the posterior inferior frontal gyrus showed the best tradeoff (sensitivity, 91%; specificity, 59%), whereas the anterior middle frontal gyrus had low specificity.

CONCLUSION

Despite different tasks for fMRI and extraoperative ECS, the relatively low specificity might be caused by a fundamental discrepancy between the 2 techniques. Reliability of language fMRI activation might differ, depending on the brain region.

Variability of the relationship between electrophysiology and BOLD-fMRI across cortical regions in humans

The relationship between blood oxygenation level-dependent (BOLD) functional MRI (fMRI) signal and the underlying neural electrical activity in humans is a topic of intense interest to systems neuroscience. This relationship has generally been assumed to be invariant regardless of the brain region and the cognitive task being studied. We critically evaluated these assumptions by comparing the BOLD-fMRI response with local field potential (LFP) measurements during visually cued common noun and verb generation in 11 humans in whom 1210 subdural electrodes were implanted. As expected, power in the mid-gamma band (60-120 Hz) correlated positively (r(2) = 0.16, p < 10(-16)) and power in the beta band (13-30 Hz) correlated negatively (r(2) = 0.09, p < 10(-16)) with the BOLD signal change. Beta and mid-gamma band activity independently explain different components of the observed BOLD signal. Importantly, we found that the location (i.e., lobe) of the recording site modulates the relationship between the electrocorticographic (ECoG) signal and the observed fMRI response (p < 10(-16), F(21,1830) = 52.7), while the type of language task does not. Across all brain regions, ECoG activity in the gamma and beta bands explains 22% of the fMRI response, but if the lobar location is considered, 28% of the variance can be explained. Further evaluation of this relationship at the level of individual gyri provides additional evidence of differences in the BOLD-LFP relationship by cortical locus. This spatial variability in the relationship between the fMRI signal and neural activity carries implications for modeling of the hemodynamic response function, an essential step for interregional fMRI comparisons.

Human intracranial recordings and cognitive neuroscience

The ultimate goal of neuroscience research is to understand the operating mechanism of the human brain and to exploit this understanding to devise methods for repair when it malfunctions. A key feature of this operating mechanism is electrical activity of single brain cells and cell assemblies. For obvious ethical reasons, scientists rely mostly on animal research in the study of such signals. Research in humans is often limited to electrical signals that can be recorded at the scalp or to surrogates of electrical activity, namely magnetic source imaging and measures of regional blood flow and metabolism. Invasive brain recordings performed in patients during various clinical procedures provide a unique opportunity to record high-resolution signals in vivo from the human brain-data that are otherwise unavailable. Of special value are the rare opportunities to record in awake humans the activity of single brain cells and small cellular assemblies. These recordings provide a unique view on aspects of human cognition that are impossible to study in animals, including language, imagery, episodic memory, volition, and even consciousness. In the current review we discuss the unique contribution of invasive recordings from patients to the field of cognitive neuroscience.

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

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are primary tools of the psychological neurosciences. It is therefore important to understand the relationship between hemodynamic and electrophysiological responses. An early study by Huettel and colleagues found that the coupling of fMRI blood-oxygen-level-dependent signal (BOLD) and subdurally-recorded signal-averaged event-related potentials (ERPs) was not consistent across brain regions. Instead, a growing body of evidence now indicates that hemodynamic changes measured by fMRI reflect non-phase-locked changes in high frequency power rather than the phase-locked ERP. Here, we revisit the data from Huettel and colleagues and measure event-related spectral perturbations (ERSPs) to examine the time course of frequency changes. We found that, unlike the ERP, γ-ERSP power was consistently coupled with the hemodynamic response across three visual cortical regions. Stimulus duration modulated the BOLD signal and the γ-ERSP in the peri-calcarine and fusiform cortices, whereas there was no such modulation of either physiological signal in the lateral temporal-occipital cortex. This finding reconciles the original report with the more recent literature and demonstrates that the ERP and ERSP reflect dissociable aspects of neural activity.

Neurophysiologic correlates of fMRI in human motor cortex

The neurophysiological underpinnings of functional magnetic resonance imaging (fMRI) are not well understood. To understand the relationship between the fMRI blood oxygen level dependent (BOLD) signal and neurophysiology across large areas of cortex, we compared task related BOLD change during simple finger movement to brain surface electric potentials measured on a similar spatial scale using electrocorticography (ECoG). We found that spectral power increases in high frequencies (65-95 Hz), which have been related to local neuronal activity, colocalized with spatially focal BOLD peaks on primary sensorimotor areas. Independent of high frequencies, decreases in low frequency rhythms (<30 Hz), thought to reflect an aspect of cortical-subcortical interaction, colocalized with weaker BOLD signal increase. A spatial regression analysis showed that there was a direct correlation between the amplitude of the task induced BOLD change on different areas of primary sensorimotor cortex and the amplitude of the high frequency change. Low frequency change explained an additional, different part of the spatial BOLD variance. Together, these spectral power changes explained a significant 36% of the spatial variance in the BOLD signal change (R(2) = 0.36). These results suggest that BOLD signal change is largely induced by two separate neurophysiological mechanisms, one being spatially focal neuronal processing and the other spatially distributed low frequency rhythms.

Neural and BOLD responses across the brain

Functional Magnetic Resonance Imaging (fMRI) has quickly grown into one of the most important tools for studying brain function, especially in humans. Despite its prevalence, we still do not have a clear picture of what exactly the blood oxygenation level dependent (BOLD) signal represents or how it compares to the signals obtained with other methods (e.g., electrophysiology). We particularly refer to single neuron recordings and electroencephalography when we mention 'electrophysiological methods', given that these methods have been used for more than 50 years, and have formed the basis of much of our current understanding of brain function. Brain function involves the coordinated activity of many different areas and many different cell types that can participate in an enormous variety of processes (neural firing, inhibitory and excitatory synaptic activity, neuromodulation, oscillatory activity, etc.). Of these cells and processes, only a subset is sampled with electrophysiological techniques, and their contribution to the recorded signals is not exactly known. Functional imaging signals are driven by the metabolic needs of the active cells, and are most likely also biased toward certain cell types and certain neural processes, although we know even less about which processes actually drive the hemodynamic response. This article discusses the current status on the interpretation of the BOLD signal and how it relates to neural activity measured with electrophysiological techniques. WIREs Cogn Sci 2012, 3:75-86. doi: 10.1002/wcs.153 For further resources related to this article, please visit the WIREs website.

Interictal functional connectivity of human epileptic networks assessed by intracerebral EEG and BOLD signal fluctuations

In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal derived from resting state functional magnetic resonance imaging (fMRI) reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG) and resting-state functional MRI (fMRI) in 5 patients suffering from intractable temporal lobe epilepsy (TLE). Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions) during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband) and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal). This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional connectivity measured by iEEG and BOLD signals give complementary but sometimes inconsistent information in TLE.

The neurocognition of conduct disorder behaviors: specificity to physical aggression and theft after controlling for ADHD symptoms

There is growing evidence that among the different conduct disorder (CD) behaviors, physical aggression, but not theft, links to low neurocognitive abilities. Specifically, physical aggression has consistently been found to be negatively related to neurocognitive abilities, whereas theft has been shown to be either positively or not related to neurocognition. The specificity of these links needs further examination because attention deficit hyperactivity disorder (ADHD) links to both physical aggression and neurocognitive variation. The development of self-reported physical aggression and theft, from age 11 to 17 years, was studied in a prospective at-risk male cohort via a dual process latent growth curve model. Seven neurocognitive tests at age 20 were regressed on the growth parameters of physical aggression and theft. The links between neurocognition and the growth parameters of physical aggression and theft were adjusted for ADHD symptoms at ages 11 and 15 (parent, child and teacher reports). Results indicated that verbal abilities were negatively related to physical aggression while they were positively associated with theft. However, inductive reasoning was negatively associated with increases in theft across adolescence. Symptoms of ADHD accounted for part of the neurocognitive test links with physical aggression but did not account for the associations with theft. These differences emphasize the importance of examining specific CD behaviors to better understand their neurodevelopmental mechanisms. They also suggest that youth who engage in different levels of physical aggression or theft behaviors may require different preventive and corrective interventions.

Selective attention modulates face-specific induced gamma oscillations recorded from ventral occipitotemporal cortex

EEG studies from subdural electrodes have demonstrated a face-specific event-related potential (face-N200) recorded from human ventral occipitotemporal cortex. The insensitivity of face-N200 to task manipulations has supported the proposal that face-N200 reflects an initial obligatory response to faces. This result stands in striking contrast to results of neuroimaging studies that have demonstrated strong task sensitivity of the fusiform hemodynamic response evoked by faces, and thus has created a paradox in the face perception literature. We recorded field potentials directly from the cortical surface of 16 patients while they selectively attended to faces or houses. Here we report that face-specific gamma activity recorded at face-N200 sites is strongly modulated by selective attention, while face-N200 is not. Our results reconcile prior electrophysiological and hemodynamic studies of face perception, and suggest that attentional modulation of the face response follows an initial phase that is largely insensitive to attention.

Identifying robust and sensitive frequency bands for interrogating neural oscillations

Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic ("resting" or "spontaneous") electroencephalogram (EEG) into five bands: delta (1-5Hz), alpha-low (6-9Hz), alpha-high (10-11Hz), beta (12-19Hz), and gamma (>21Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)-based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time-frequency (event-related spectral perturbation, event-related synchronization/desynchronization) domains.

Direct brain recordings fuel advances in cognitive electrophysiology

Electrocorticographic brain recordings in patients with surgically implanted electrodes have recently emerged as a powerful tool for examining the neural basis of human cognition. These recordings measure the electrical activity of the brain directly, and thus provide data with higher temporal and spatial resolution than other human neuroimaging techniques. Here we review recent research in this area and in particular we explain how electrocorticographic recordings have provided insight into the neural basis of human working memory, episodic memory, language, and spatial cognition. In some cases this research has identified patterns of human brain activity that were unexpected on the basis of studies in animals.

How and when the fMRI BOLD signal relates to underlying neural activity: the danger in dissociation

Functional magnetic resonance imaging (fMRI) has become the dominant means of measuring behavior-related neural activity in the human brain. Yet the relation between the blood oxygen-level dependent (BOLD) signal and underlying neural activity remains an open and actively researched question. A widely accepted model, established for sensory neo-cortex, suggests that the BOLD signal reflects peri-synaptic activity in the form of the local field potential rather than the spiking rate of individual neurons. Several recent experimental results, however, suggest situations in which BOLD, spiking, and the local field potential dissociate. Two different models are discussed, based on the literature reviewed to account for this dissociation, a circuitry-based and vascular-based explanation. Both models are found to account for existing data under some testing situations and in certain brain regions. Because both the vascular and local circuitry-based explanations challenge the BOLD-LFP coupling model, these models provide guidance in predicting when BOLD can be expected to reflect neural processing and when the underlying relation with BOLD may be more complex than a direct correspondence.