Methods for Determining Frequency- and Region-Dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

Plastic vasomotion entrainment

The presence of global synchronization of vasomotion induced by oscillating visual stimuli was identified in the mouse brain. Endogenous autofluorescence was used and the vessel 'shadow' was quantified to evaluate the magnitude of the frequency-locked vasomotion. This method allows vasomotion to be easily quantified in non-transgenic wild-type mice using either the wide-field macro-zoom microscopy or the deep-brain fiber photometry methods. Vertical stripes horizontally oscillating at a low temporal frequency (0.25 Hz) were presented to the awake mouse, and oscillatory vasomotion locked to the temporal frequency of the visual stimulation was induced not only in the primary visual cortex but across a wide surface area of the cortex and the cerebellum. The visually induced vasomotion adapted to a wide range of stimulation parameters. Repeated trials of the visual stimulus presentations resulted in the plastic entrainment of vasomotion. Horizontally oscillating visual stimulus is known to induce horizontal optokinetic response (HOKR). The amplitude of the eye movement is known to increase with repeated training sessions, and the flocculus region of the cerebellum is known to be essential for this learning to occur. Here, we show a strong correlation between the average HOKR performance gain and the vasomotion entrainment magnitude in the cerebellar flocculus. Therefore, the plasticity of vasomotion and neuronal circuits appeared to occur in parallel. Efficient energy delivery by the entrained vasomotion may contribute to meeting the energy demand for increased coordinated neuronal activity and the subsequent neuronal circuit reorganization.

Neural signatures of visuo-motor integration during human-robot interactions

Visuo-motor integration shapes our daily experience and underpins the sense of feeling in control over our actions. The last decade has seen a surge in robotically and virtually mediated interactions, whereby bodily actions ultimately result in an artificial movement. But despite the growing number of applications, the neurophysiological correlates of visuo-motor processing during human-machine interactions under dynamic conditions remain scarce. Here we address this issue by employing a bimanual robotic interface able to track voluntary hands movement, rendered in real-time into the motion of two virtual hands. We experimentally manipulated the visual feedback in the virtual reality with spatial and temporal conflicts and investigated their impact on (1) visuo-motor integration and (2) the subjective experience of being the author of one's action (i.e., sense of agency). Using somatosensory evoked responses measured with electroencephalography, we investigated neural differences occurring when the integration between motor commands and visual feedback is disrupted. Our results show that the right posterior parietal cortex encodes for differences between congruent and spatially-incongruent interactions. The experimental manipulations also induced a decrease in the sense of agency over the robotically-mediated actions. These findings offer solid neurophysiological grounds that can be used in the future to monitor integration mechanisms during movements and ultimately enhance subjective experience during human-machine interactions.

Astrocytes regulate ultra-slow arteriole oscillations via stretch-mediated TRPV4-COX-1 feedback

Very-low-frequency oscillations in microvascular diameter cause fluctuations in oxygen delivery that are important for fueling the brain and for functional imaging. However, little is known about how the brain regulates ongoing oscillations in cerebral blood flow. In mouse and rat cortical brain slice arterioles, we find that selectively enhancing tone is sufficient to recruit a TRPV4-mediated Ca2+ elevation in adjacent astrocyte endfeet. This endfoot Ca2+ signal triggers COX-1-mediated "feedback vasodilators" that limit the extent of evoked vasoconstriction, as well as constrain fictive vasomotion in slices. Astrocyte-Ptgs1 knockdown in vivo increases the power of arteriole oscillations across a broad range of very low frequencies (0.01-0.3 Hz), including ultra-slow vasomotion (∼0.1 Hz). Conversely, clamping astrocyte Ca2+in vivo reduces the power of vasomotion. These data demonstrate bidirectional communication between arterioles and astrocyte endfeet to regulate oscillatory microvasculature activity.

Increased Neural Strength and Reliability to Audiovisual Stimuli at the Boundary of Peripersonal Space

The actionable space surrounding the body, referred to as peripersonal space (PPS), has been the subject of significant interest of late within the broader framework of embodied cognition. Neurophysiological and neuroimaging studies have shown the representation of PPS to be built from visuotactile and audiotactile neurons within a frontoparietal network and whose activity is modulated by the presence of stimuli in proximity to the body. In contrast to single-unit and fMRI studies, an area of inquiry that has received little attention is the EEG characterization associated with PPS processing. Furthermore, although PPS is encoded by multisensory neurons, to date there has been no EEG study systematically examining neural responses to unisensory and multisensory stimuli, as these are presented outside, near, and within the boundary of PPS. Similarly, it remains poorly understood whether multisensory integration is generally more likely at certain spatial locations (e.g., near the body) or whether the cross-modal tactile facilitation that occurs within PPS is simply due to a reduction in the distance between sensory stimuli when close to the body and in line with the spatial principle of multisensory integration. In the current study, to examine the neural dynamics of multisensory processing within and beyond the PPS boundary, we present auditory, visual, and audiovisual stimuli at various distances relative to participants' reaching limit—an approximation of PPS—while recording continuous high-density EEG. We question whether multisensory (vs. unisensory) processing varies as a function of stimulus–observer distance. Results demonstrate a significant increase of global field power (i.e., overall strength of response across the entire electrode montage) for stimuli presented at the PPS boundary—an increase that is largest under multisensory (i.e., audiovisual) conditions. Source localization of the major contributors to this global field power difference suggests neural generators in the intraparietal sulcus and insular cortex, hubs for visuotactile and audiotactile PPS processing. Furthermore, when neural dynamics are examined in more detail, changes in the reliability of evoked potentials in centroparietal electrodes are predictive on a subject-by-subject basis of the later changes in estimated current strength at the intraparietal sulcus linked to stimulus proximity to the PPS boundary. Together, these results provide a previously unrealized view into the neural dynamics and temporal code associated with the encoding of nontactile multisensory around the PPS boundary.

Electrical Neuroimaging of Music Processing in Pianists With and Without True Absolute Pitch

True absolute pitch (AP), labeling of pitches with semitone precision without a reference, is classically studied using isolated tones. However, AP is acquired and has its function within complex dynamic musical contexts. Here we examined event-related brain responses and underlying cerebral sources to endings of short expressive string quartets, investigating a homogeneous population of young highly trained pianists with half of them possessing true-AP. The pieces ended regularly or contained harmonic transgressions at closure that participants appraised. Given the millisecond precision of ERP analyses, this experimental plan allowed examining whether AP alters music processing at an early perceptual, or later cognitive level, or both, and which cerebral sources underlie differences with non-AP musicians. We also investigated the impact of AP on general auditory cognition. Remarkably, harmonic transgression sensitivity did not differ between AP and non-AP participants, and differences for auditory cognition were only marginal. The key finding of this study is the involvement of a microstate peaking around 60 ms after musical closure, characterizing AP participants. Concurring sources were estimated in secondary auditory areas, comprising the planum temporale, all transgression conditions collapsed. These results suggest that AP is not a panacea to become a proficient musician, but a rare perceptual feature.

Sounds enhance visual completion processes

Everyday vision includes the detection of stimuli, figure-ground segregation, as well as object localization and recognition. Such processes must often surmount impoverished or noisy conditions; borders are perceived despite occlusion or absent contrast gradients. These illusory contours (ICs) are an example of so-called mid-level vision, with an event-related potential (ERP) correlate at ∼100-150 ms post-stimulus onset and originating within lateral-occipital cortices (the IC_effect). Presently, visual completion processes supporting IC perception are considered exclusively visual; any influence from other sensory modalities is currently unknown. It is now well-established that multisensory processes can influence both low-level vision (e.g. detection) as well as higher-level object recognition. By contrast, it is unknown if mid-level vision exhibits multisensory benefits and, if so, through what mechanisms. We hypothesized that sounds would impact the IC_effect. We recorded 128-channel ERPs from 17 healthy, sighted participants who viewed ICs or no-contour (NC) counterparts either in the presence or absence of task-irrelevant sounds. The IC_effect was enhanced by sounds and resulted in the recruitment of a distinct configuration of active brain areas over the 70-170 ms post-stimulus period. IC-related source-level activity within the lateral occipital cortex (LOC), inferior parietal lobe (IPL), as well as primary visual cortex (V1) were enhanced by sounds. Moreover, the activity in these regions was correlated when sounds were present, but not when absent. Results from a control experiment, which employed amodal variants of the stimuli, suggested that sounds impact the perceived brightness of the IC rather than shape formation per se. We provide the first demonstration that multisensory processes augment mid-level vision and everyday visual completion processes, and that one of the mechanisms is brightness enhancement. These results have important implications for the design of treatments and/or visual aids for low-vision patients.

Steady-state evoked potentials distinguish brain mechanisms of self-paced versus synchronization finger tapping

Sensorimotor synchronization (SMS) requires aligning motor actions to external events and represents a core part of both musical and dance performances. In the current study, to isolate the brain mechanisms involved in synchronizing finger tapping with a musical beat, we compared SMS to pure self-paced finger tapping and listen-only conditions at different tempi. We analyzed EEG data using frequency domain steady-state evoked potentials (SSEPs) to identify sustained electrophysiological brain activity during repetitive tasks. Behavioral results revealed different timing modes between SMS and self-paced finger tapping, associated with distinct scalp topographies, thus suggesting different underlying brain sources. After subtraction of the listen-only brain activity, SMS was compared to self-paced finger tapping. Resulting source estimations showed stronger activation of the left inferior frontal gyrus during SMS, and stronger activation of the bilateral inferior parietal lobule during self-paced finger tapping. These results point to the left inferior frontal gyrus as a pivot for perception-action coupling. We discuss our findings in the context of the ongoing debate about SSEPs interpretation given the variety of brain events contributing to SSEPs and similar EEG frequency responses.

Brain mechanisms for perceiving illusory lines in humans

Illusory contours (ICs) are perceptions of visual borders despite absent contrast gradients. The psychophysical and neurobiological mechanisms of IC processes have been studied across species and diverse brain imaging/mapping techniques. Nonetheless, debate continues regarding whether IC sensitivity results from a (presumably) feedforward process within low-level visual cortices (V1/V2) or instead are processed first within higher-order brain regions, such as lateral occipital cortices (LOC). Studies in animal models, which generally favour a feedforward mechanism within V1/V2, have typically involved stimuli inducing IC lines. By contrast, studies in humans generally favour a mechanism where IC sensitivity is mediated by LOC and have typically involved stimuli inducing IC forms or shapes. Thus, the particular stimulus features used may strongly contribute to the model of IC sensitivity supported. To address this, we recorded visual evoked potentials (VEPs) while presenting human observers with an array of 10 inducers within the central 5°, two of which could be oriented to induce an IC line on a given trial. VEPs were analysed using an electrical neuroimaging framework. Sensitivity to the presence vs. absence of centrally-presented IC lines was first apparent at ∼200 ms post-stimulus onset and was evident as topographic differences across conditions. We also localized these differences to the LOC. The timing and localization of these effects are consistent with a model of IC sensitivity commencing within higher-level visual cortices. We propose that prior observations of effects within lower-tier cortices (V1/V2) are the result of feedback from IC sensitivity that originates instead within higher-tier cortices (LOC).

Contributions of Intraindividual and Interindividual Differences to Multisensory Processes

Most evidence on the neural and perceptual correlates of sensory processing derives from studies that have focused on only a single sensory modality and averaged the data from groups of participants. Although valuable, such studies ignore the substantial interindividual and intraindividual differences that are undoubtedly at play. Such variability plays an integral role in both the behavioral/perceptual realms and in the neural correlates of these processes, but substantially less is known when compared with group-averaged data. Recently, it has been shown that the presentation of stimuli from two or more sensory modalities (i.e., multisensory stimulation) not only results in the well-established performance gains but also gives rise to reductions in behavioral and neural response variability. To better understand the relationship between neural and behavioral response variability under multisensory conditions, this study investigated both behavior and brain activity in a task requiring participants to discriminate moving versus static stimuli presented in either a unisensory or multisensory context. EEG data were analyzed with respect to intraindividual and interindividual differences in RTs. The results showed that trial-by-trial variability of RTs was significantly reduced under audiovisual presentation conditions as compared with visual-only presentations across all participants. Intraindividual variability of RTs was linked to changes in correlated activity between clusters within an occipital to frontal network. In addition, interindividual variability of RTs was linked to differential recruitment of medial frontal cortices. The present findings highlight differences in the brain networks that support behavioral benefits during unisensory versus multisensory motion detection and provide an important view into the functional dynamics within neuronal networks underpinning intraindividual performance differences.

Electrical Neuroimaging of Music Processing Reveals Mid-Latency Changes with Level of Musical Expertise

This original research focused on the effect of musical training intensity on cerebral and behavioral processing of complex music using high-density event-related potential (ERP) approaches. Recently we have been able to show progressive changes with training in gray and white matter, and higher order brain functioning using (f)MRI [(functional) Magnetic Resonance Imaging], as well as changes in musical and general cognitive functioning. The current study investigated the same population of non-musicians, amateur pianists and expert pianists using spatio-temporal ERP analysis, by means of microstate analysis, and ERP source imaging. The stimuli consisted of complex musical compositions containing three levels of transgression of musical syntax at closure that participants appraised. ERP waveforms, microstates and underlying brain sources revealed gradual differences according to musical expertise in a 300–500 ms window after the onset of the terminal chords of the pieces. Within this time-window, processing seemed to concern context-based memory updating, indicated by a P3b-like component or microstate for which underlying sources were localized in the right middle temporal gyrus, anterior cingulate and right parahippocampal areas. Given that the 3 expertise groups were carefully matched for demographic factors, these results provide evidence of the progressive impact of training on brain and behavior.

The role of auditory cortices in the retrieval of single-trial auditory-visual object memories

Single-trial encounters with multisensory stimuli affect both memory performance and early-latency brain responses to visual stimuli. Whether and how auditory cortices support memory processes based on single-trial multisensory learning is unknown and may differ qualitatively and quantitatively from comparable processes within visual cortices due to purported differences in memory capacities across the senses. We recorded event-related potentials (ERPs) as healthy adults (n = 18) performed a continuous recognition task in the auditory modality, discriminating initial (new) from repeated (old) sounds of environmental objects. Initial presentations were either unisensory or multisensory; the latter entailed synchronous presentation of a semantically congruent or a meaningless image. Repeated presentations were exclusively auditory, thus differing only according to the context in which the sound was initially encountered. Discrimination abilities (indexed by d') were increased for repeated sounds that were initially encountered with a semantically congruent image versus sounds initially encountered with either a meaningless or no image. Analyses of ERPs within an electrical neuroimaging framework revealed that early stages of auditory processing of repeated sounds were affected by prior single-trial multisensory contexts. These effects followed from significantly reduced activity within a distributed network, including the right superior temporal cortex, suggesting an inverse relationship between brain activity and behavioural outcome on this task. The present findings demonstrate how auditory cortices contribute to long-term effects of multisensory experiences on auditory object discrimination. We propose a new framework for the efficacy of multisensory processes to impact both current multisensory stimulus processing and unisensory discrimination abilities later in time.

EEG-fMRI integration for the study of human brain function

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have proved to be extremely valuable tools for the non-invasive study of human brain function. Moreover, due to a notable degree of complementarity between the two modalities, the combination of EEG and fMRI data has been actively sought in the last two decades. Although initially focused on epilepsy, EEG-fMRI applications were rapidly extended to the study of healthy brain function, yielding new insights into its underlying mechanisms and pathways. Nevertheless, EEG and fMRI have markedly different spatial and temporal resolutions, and probe neuronal activity through distinct biophysical processes, many aspects of which are still poorly understood. The remarkable conceptual and methodological challenges associated with EEG-fMRI integration have motivated the development of a wide range of analysis approaches over the years, each relying on more or less restrictive assumptions, and aiming to shed further light on the mechanisms of brain function along with those of the EEG-fMRI coupling itself. Here, we present a review of the most relevant EEG-fMRI integration approaches yet proposed for the study of brain function, supported by a general overview of our current understanding of the biophysical mechanisms coupling the signals obtained from the two modalities.

Oscillatory serotonin function in depression

Oscillations in brain activities with periods of minutes to hours may be critical for normal mood behaviors. Ultradian (faster than circadian) rhythms of mood behaviors and associated central nervous system activities are altered in depression. Recent data suggest that ultradian rhythms in serotonin (5HT) function also change in depression. In two separate studies, 5HT metabolites in cerebrospinal fluid (CSF) were measured every 10 min for 24 h before and after chronic antidepressant treatment. Antidepressant treatments were associated with enhanced ultradian amplitudes of CSF metabolite levels. Another study used resting-state functional magnetic resonance imaging (fMRI) to measure amplitudes of dorsal raphé activation cycles following sham or active dietary depletions of the 5HT precursor (tryptophan). During depletion, amplitudes of dorsal raphé activation cycles increased with rapid 6 s periods (about 0.18 Hz) while functional connectivity weakened between dorsal raphé and thalamus at slower periods of 20 s (0.05 Hz). A third approach studied MDMA (ecstasy, 3,4-methylenedioxy-N-methylamphetamine) users because of their chronically diminished 5HT function compared with non-MDMA polysubstance users (Karageorgiou et al., 2009). Compared with a non-MDMA using cohort, MDMA users showed diminished fMRI intra-regional coherence in motor regions along with altered functional connectivity, again suggesting effects of altered 5HT oscillatory function. These data support a hypothesis that qualities of ultradian oscillations in 5HT function may critically influence moods and behaviors. Dysfunctional 5HT rhythms in depression may be a common endpoint and biomarker for depression, linking dysfunction of slow brain network oscillators to 5HT mechanisms affected by commonly available treatments. 5HT oscillatory dysfunction may define illness subtypes and predict responses to serotonergic agents. Further studies of 5HT oscillations in depression are indicated.

Power shifts track serial position and modulate encoding in human episodic memory

The first events in a series exert a powerful influence on cognition and behavior in both humans and animals. This is known as the law of primacy. Here, we analyze the neural correlates of primacy in humans by analyzing electrocorticographic recordings in 84 neurosurgical patients as they studied and subsequently recalled lists of common words. We found that spectral power in the gamma frequency band (28-100 Hz) was elevated at the start of the list and gradually subsided, whereas lower frequency (2-8 Hz) delta and theta band power exhibited the opposite trend. This gradual shift in the power spectrum was found across a widespread network of brain regions. The degree to which the subsequent memory effect was modulated by list (serial) position was most pronounced in medial temporal lobe structures. These results suggest that globally increased gamma and decreased delta-theta spectral powers reflect a brain state that predisposes medial temporal lobe structures to enhance the encoding and maintenance of early list items.

Monkey in the middle: why non-human primates are needed to bridge the gap in resting-state investigations

Resting-state investigations based on the evaluation of intrinsic low-frequency fluctuations of the BOLD fMRI signal have been extensively utilized to map the structure and dynamics of large-scale functional network organization in humans. In addition to increasing our knowledge of normal brain connectivity, disruptions of the spontaneous hemodynamic fluctuations have been suggested as possible diagnostic indicators of neurological and psychiatric disease states. Though the non-invasive technique has been received with much acclamation, open questions remain regarding the origin, organization, phylogenesis, as well as the basis of disease-related alterations underlying the signal patterns. Experimental work utilizing animal models, including the use of neurophysiological recordings and pharmacological manipulations, therefore, represents a critical component in the understanding and successful application of resting-state analysis, as it affords a range of experimental manipulations not possible in human subjects. In this article, we review recent rodent and non-human primate studies and based on the examination of the homologous brain architecture propose the latter to be the best-suited model for exploring these unresolved resting-state concerns. Ongoing work examining the correspondence of functional and structural connectivity, state-dependency and the neuronal correlates of the hemodynamic oscillations are discussed. We then consider the potential experiments that will allow insight into different brain states and disease-related network disruptions that can extend the clinical applications of resting-state fMRI (RS-fMRI).

Cortical dynamics of human scalp EEG origins in a visually guided motor execution

The EEG mu rhythm is often used as an index of activation in the sensorimotor cortex. However, the blur caused by volume conduction makes it difficult to identify the exact origin of the EEG rhythm in the brain using only the human scalp EEG. In this study, simultaneous fMRI and EEG measurements were performed during a visually guided motor execution task in order to investigate whether the mu rhythm in the scalp EEG is an indication of the activity in the sensorimotor cortex. In addition, a new method was proposed for reconstruction of the cortical EEG activity through the fusion of fMRI and EEG data. A suppression of mu rhythm appeared around the lateral central electrode sites, just above the sensorimotor cortex, in association with the activity in that region. During a visually guided motor execution task, the alpha rhythms at the occipital electrode sites and the alpha rhythm at the central electrode sites also showed a correlation with the fMRI signal in the occipital and the supplementary motor cortices, respectively. This method allows the investigation of the scalp EEG origin with the spatial precision of fMRI, while retaining dynamic properties of the cortex with the temporal precision of EEG.

Looming signals reveal synergistic principles of multisensory integration

Multisensory interactions are a fundamental feature of brain organization. Principles governing multisensory processing have been established by varying stimulus location, timing and efficacy independently. Determining whether and how such principles operate when stimuli vary dynamically in their perceived distance (as when looming/receding) provides an assay for synergy among the above principles and also means for linking multisensory interactions between rudimentary stimuli with higher-order signals used for communication and motor planning. Human participants indicated movement of looming or receding versus static stimuli that were visual, auditory, or multisensory combinations while 160-channel EEG was recorded. Multivariate EEG analyses and distributed source estimations were performed. Nonlinear interactions between looming signals were observed at early poststimulus latencies (∼75 ms) in analyses of voltage waveforms, global field power, and source estimations. These looming-specific interactions positively correlated with reaction time facilitation, providing direct links between neural and performance metrics of multisensory integration. Statistical analyses of source estimations identified looming-specific interactions within the right claustrum/insula extending inferiorly into the amygdala and also within the bilateral cuneus extending into the inferior and lateral occipital cortices. Multisensory effects common to all conditions, regardless of perceived distance and congruity, followed (∼115 ms) and manifested as faster transition between temporally stable brain networks (vs summed responses to unisensory conditions). We demonstrate the early-latency, synergistic interplay between existing principles of multisensory interactions. Such findings change the manner in which to model multisensory interactions at neural and behavioral/perceptual levels. We also provide neurophysiologic backing for the notion that looming signals receive preferential treatment during perception.

Increased phase synchronization during continuous face integration measured simultaneously with EEG and fMRI

OBJECTIVE

Gamma zero-lag phase synchronization has been measured in the animal brain during visual binding. Human scalp EEG studies used a phase locking factor (trial-to-trial phase-shift consistency) or gamma amplitude to measure binding but did not analyze common-phase signals so far. This study introduces a method to identify networks oscillating with near zero-lag phase synchronization in human subjects.

METHODS

We presented unpredictably moving face parts (NOFACE) which - during some periods - produced a complete schematic face (FACE). The amount of zero-lag phase synchronization was measured using global field synchronization (GFS). GFS provides global information on the amount of instantaneous coincidences in specific frequencies throughout the brain.

RESULTS

Gamma GFS was increased during the FACE condition. To localize the underlying areas, we correlated gamma GFS with simultaneously recorded BOLD responses. Positive correlates comprised the bilateral middle fusiform gyrus and the left precuneus.

CONCLUSIONS

These areas may form a network of areas transiently synchronized during face integration, including face-specific as well as binding-specific regions and regions for visual processing in general.

SIGNIFICANCE

Thus, the amount of zero-lag phase synchronization between remote regions of the human visual system can be measured with simultaneously acquired EEG/fMRI.

Dynamic changes in brain functional connectivity during concurrent dual-task performance

This study investigated the spatial, spectral, temporal and functional proprieties of functional brain connections involved in the concurrent execution of unrelated visual perception and working memory tasks. Electroencephalography data was analysed using a novel data-driven approach assessing source coherence at the whole-brain level. Three connections in the beta-band (18–24 Hz) and one in the gamma-band (30–40 Hz) were modulated by dual-task performance. Beta-coherence increased within two dorsofrontal-occipital connections in dual-task conditions compared to the single-task condition, with the highest coherence seen during low working memory load trials. In contrast, beta-coherence in a prefrontal-occipital functional connection and gamma-coherence in an inferior frontal-occipitoparietal connection was not affected by the addition of the second task and only showed elevated coherence under high working memory load. Analysis of coherence as a function of time suggested that the dorsofrontal-occipital beta-connections were relevant to working memory maintenance, while the prefrontal-occipital beta-connection and the inferior frontal-occipitoparietal gamma-connection were involved in top-down control of concurrent visual processing. The fact that increased coherence in the gamma-connection, from low to high working memory load, was negatively correlated with faster reaction time on the perception task supports this interpretation. Together, these results demonstrate that dual-task demands trigger non-linear changes in functional interactions between frontal-executive and occipitoparietal-perceptual cortices.

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.

Impaired early visual response modulations to spatial information in chronic schizophrenia

Early visual processing stages have been demonstrated to be impaired in schizophrenia patients and their first-degree relatives. The amplitude and topography of the P1 component of the visual evoked potential (VEP) are both affected; the latter of which indicates alterations in active brain networks between populations. At least two issues remain unresolved. First, the specificity of this deficit (and suitability as an endophenotype) has yet to be established, with evidence for impaired P1 responses in other clinical populations. Second, it remains unknown whether schizophrenia patients exhibit intact functional modulation of the P1 VEP component; an aspect that may assist in distinguishing effects specific to schizophrenia. We applied electrical neuroimaging analyses to VEPs from chronic schizophrenia patients and healthy controls in response to variation in the parafoveal spatial extent of stimuli. Healthy controls demonstrated robust modulation of the VEP strength and topography as a function of the spatial extent of stimuli during the P1 component. By contrast, no such modulations were evident at early latencies in the responses from patients with schizophrenia. Source estimations localized these deficits to the left precuneus and medial inferior parietal cortex. These findings provide insights on potential underlying low-level impairments in schizophrenia.

Neurovascular coupling is brain region-dependent

Despite recent advances in alternative brain imaging technologies, functional magnetic resonance imaging (fMRI) remains the workhorse for both medical diagnosis and primary research. Indeed, the number of research articles that utilise fMRI have continued to rise unabated since its conception in 1991, despite the limitation that recorded signals originate from the cerebral vasculature rather than neural tissue. Consequently, understanding the relationship between brain activity and the resultant changes in metabolism and blood flow (neurovascular coupling) remains a vital area of research. In the past, technical constraints have restricted investigations of neurovascular coupling to cortical sites and have led to the assumption that coupling in non-cortical structures is the same as in the cortex, despite the lack of any evidence. The current study investigated neurovascular coupling in the rat using whole-brain blood oxygenation level-dependent (BOLD) fMRI and multi-channel electrophysiological recordings and measured the response to a sensory stimulus as it proceeded through brainstem, thalamic and cortical processing sites - the so-called whisker-to-barrel pathway. We found marked regional differences in the amplitude of BOLD activation in the pathway and non-linear neurovascular coupling relationships in non-cortical sites. The findings have important implications for studies that use functional brain imaging to investigate sub-cortical function and caution against the use of simple, linear mapping of imaging signals onto neural activity.

BOLD responses to different temporal frequency stimuli in the lateral geniculate nucleus and visual cortex: insights into the neural basis of fMRI

The neural basis of the blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) remains largely unknown after decades of research. To investigate this issue, the unique property of the temporal frequency tuning that could separate neural input and output in the primary visual cortex was used as a model. During moving grating stimuli of 1, 2, 10 and 20Hz temporal frequencies, we measured 9.4-T BOLD fMRI responses simultaneously in the primary visual cortex of area 17 (A17) and area 18 (A18), and the lateral geniculate nucleus (LGN) of isoflurane-anesthetized cat. Our results showed that preferred temporal frequencies of the BOLD responses for A17, A18 and LGN were 3.1Hz, 4.5Hz and 6.0Hz, respectively, which were comparable to the previously reported electrophysiological data. Additionally, the difference of BOLD response onset time between LGN and A17 was 0.5s, which is 18 times larger than the difference of neural activity onset time between these areas. We then compared the frequency-dependent BOLD fMRI response of A17 with tissue partial pressure of oxygen (pO(2)) and electrophysiological data of the same animal model reported by Viswanathan and Freeman (Nature Neuroscience, 2007). The BOLD tuning curve resembled the low frequency band (<12Hz) of local field potential (LFP) tuning curve rather than spiking activity, gamma band (25-90Hz) of LFP, and tissue pO(2) tuning curves, suggesting that the BOLD fMRI signal relates closer to low frequency LFP.

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.

Frequency-specific electrocorticographic correlates of working memory delay period fMRI activity

Electrocorticography (ECoG) and functional MRI (BOLD-fMRI) have been used previously to measure brain activity during working memory delay periods. These studies have separately reported oscillation changes in the theta (4-8 Hz) band and BOLD-fMRI increases during delay periods when information is maintained in memory. However, it is not known how intracranial cortical field potential (CFP) changes relate to BOLD-fMRI responses during delay periods. To answer this question, fMRI was obtained from six epilepsy patients during a visual working memory task. Then, following subdural macroelectrode implant, continuous ECoG was used to record CFPs during the same task. Time-frequency analyses showed delay period gamma band oscillation amplitude increases on electrodes located near fMRI activity, while in the theta band changes were higher for electrodes located away from fMRI activation. The amplitude of the ECoG gamma band response was significantly positively correlated with the fMRI response, while a negative correlation was found for the theta band. The findings are consistent with previous reports of local field potential (LFP) coupling in the gamma band with BOLD-fMRI responses during visual stimulation in monkeys, but are novel in that the relationship reported here persists after the disappearance of visual stimuli while information is being maintained in memory. We conclude that there is a relationship between BOLD-fMRI increases and human working memory delay period gamma oscillation increases and theta decreases. The spectral profile change provides a basis for comparison of working memory delay period BOLD-fMRI with field potential recordings in animals and other human intracranial EEG studies.

Voxel-wise information theoretic EEG-fMRI feature integration

We have recently proposed the evaluation of a set of information theoretic quantities (ITQs) for the integration of simultaneously acquired EEG-fMRI data (Ostwald, D., Porcaro, C., Bagshaw, A.P., 2010. An information theoretic approach to EEG-fMRI integration of visually evoked responses. Neuroimage. 49, 498-516). In our previous experimental evaluation of the information theoretic framework, we defined the data subsets from which to calculate the ITQs using a priori constraints. In the case of EEG, this meant that data were extracted from a single electrode, while for fMRI the analysed data came from voxels contained within a sphere surrounding the most responsive voxel of visual cortex. While this approach was a natural starting point for the evaluation of the framework in the application to combined EEG-fMRI data sets, a more principled approach to data selection is desirable. Here, we propose to combine standard fMRI data pre-processing and low-resolution electromagnetic tomography (LORETA) for the evaluation of ITQs across the entire three-dimensional brain space. We apply the proposed method to a simultaneous EEG-fMRI data set acquired during checkerboard stimulation and assess the topographical informativeness of EEG (time and frequency domain) and fMRI features with respect to the stimulus and each other. The resulting information theoretic effect size maps are supplemented with a statistical evaluation based on Gaussian null model simulations using a false-discovery rate procedure. Given the contamination of EEG recordings by artefacts induced by the MR scanning environment we further assessed the influence of different advanced EEG pre-processing methods (independent component analysis and functional source separation) on the information topography. The results of this analysis provide evidence for the topographically focussed informativeness of both EEG and fMRI features with respect to the stimulus, but for the current feature selection do not detect EEG-fMRI activity dependence. More advanced EEG data pre-processing rendered the feature distributions more stimulus-informative, but did not alter the EEG-fMRI activity and conditional dependencies.

Comparisons of the dynamics of local field potential and multiunit activity signals in macaque visual cortex

The local field potential (LFP) and multiunit activity (MUA) are extracellularly recorded signals that describe local neuronal network dynamics. In our experiments, the LFP and MUA, recorded from the same electrode in macaque primary visual cortex V1 in response to drifting grating visual stimuli, were evaluated on coarse timescales (∼1-5 s) and fine timescales (<0.1 s). On coarse timescales, MUA and the LFP both produced sustained visual responses to optimal and non-optimal oriented visual stimuli. The sustainedness of the two signals across the population of recording sites was correlated (correlation coefficient, ∼0.4). At most recording sites, the MUA was at least as sustained as the LFP and significantly more sustained for optimal orientations. In previous literature, the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging studies was found to be more strongly correlated with the LFP than with the MUA as a result of the lack of sustained response in the MUA signal. Because we found that MUA was as sustained as the LFP, MUA may also be correlated with BOLD. On fine timescales, we computed the coherence between the LFP and MUA over the frequency range 10-150 Hz. The LFP and MUA were weakly but significantly coherent (∼0.14) in the gamma band (20-90 Hz). The amount of gamma-band coherence was correlated with the power in the gamma band of the LFP. The data were consistent with the proposal that the LFP and MUA are generated in a noisy, resonant cortical network.

Adaptive tracking of EEG oscillations

Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception. However, measuring this activity and its influence requires precise extraction of frequency components. This processing is not straightforward. Particularly, difficulties with extracting oscillations arise due to their time-varying characteristics. Moreover, when phase information is needed, it is of the utmost importance to extract narrow-band signals. This paper presents a novel method using adaptive filters for tracking and extracting these time-varying oscillations. This scheme is designed to maximize the oscillatory behavior at the output of the adaptive filter. It is then capable of tracking an oscillation and describing its temporal evolution even during low amplitude time segments. Moreover, this method can be extended in order to track several oscillations simultaneously and to use multiple signals. These two extensions are particularly relevant in the framework of EEG data processing, where oscillations are active at the same time in different frequency bands and signals are recorded with multiple sensors. The presented tracking scheme is first tested with synthetic signals in order to highlight its capabilities. Then it is applied to data recorded during a visual shape discrimination experiment for assessing its usefulness during EEG processing and in detecting functionally relevant changes. This method is an interesting additional processing step for providing alternative information compared to classical time-frequency analyses and for improving the detection and analysis of cross-frequency couplings.

The functional consequences of cortical circuit abnormalities on gamma oscillations in schizophrenia: insights from computational modeling

Schizophrenia is characterized by cortical circuit abnormalities, which might be reflected in γ-frequency (30–100 Hz) oscillations in the electroencephalogram. Here we used a computational model of cortical circuitry to examine the effects that neural circuit abnormalities might have on γ generation and network excitability. The model network consisted of 1000 leaky integrate-and-fire neurons with realistic connectivity patterns and proportions of neuron types [pyramidal cells (PCs), regular-spiking inhibitory interneurons, and fast-spiking interneurons (FSIs)]. The network produced a γ oscillation when driven by noise input. We simulated reductions in: (1) recurrent excitatory inputs to PCs; (2) both excitatory and inhibitory inputs to PCs; (3) all possible connections between cells; (4) reduced inhibitory output from FSIs; and (5) reduced NMDA input to FSIs. Reducing all types of synaptic connectivity sharply reduced γ power and phase synchrony. Network excitability was reduced when recurrent excitatory connections were deleted, but the network showed disinhibition effects when inhibitory connections were deleted. Reducing FSI output impaired γ generation to a lesser degree than reducing synaptic connectivity, and increased network excitability. Reducing FSI NMDA input also increased network excitability, but increased γ power. The results of this study suggest that a multimodal approach, combining non-invasive neurophysiological and structural measures, might be able to distinguish between different neural circuit abnormalities in schizophrenia patients. Computational modeling may help to bridge the gaps between post-mortem studies, animal models, and experimental data in humans, and facilitate the development of new therapies for schizophrenia and neuropsychiatric disorders in general.

Relating BOLD fMRI and neural oscillations through convolution and optimal linear weighting

The exact relationship between neural activity and BOLD fMRI is unknown. However, several recent findings, recorded invasively in both humans and monkeys, show a positive correlation of BOLD to high-frequency (30-150 Hz) oscillatory power changes and a negative correlation to low-frequency (8-30 Hz) power changes arising from cortical areas. In this study, we computed the time series correlation between BOLD GE-EPI fMRI at 7 T and neural activity measures from noninvasive MEG, using a time-frequency beam former for source localisation. A sinusoidal drifting grating was presented visually for 4 s followed by a 20 s rest period in both recording modalities. The MEG time series were convolved with either a measured or canonical haemodynamic response function (HRF) for comparison with the measured BOLD data, and the BOLD data were deconvolved with either a measured or a canonical HRF for comparison with the measured MEG. In the visual cortex, the higher frequencies (mid-gamma=52-75 Hz and high-gamma=75-98 Hz) were positively correlated with BOLD whilst the lower frequencies (alpha=8-12 Hz and beta=12-25 Hz) were negatively correlated with BOLD. Furthermore, regression including all frequency bands predicted BOLD better than stimulus timing alone, although no individual frequency band predicted BOLD as well as stimulus timing. For this paradigm, there was, in general, no difference between using the SPM canonical HRF compared to the subject-specific measured HRF. In conclusion, MEG replicates findings from invasive recordings with regard to time series correlations with BOLD data. Conversely, deconvolution of BOLD data provides a neural estimate which correlates well with measured neural effects as a function of neural oscillation frequency.

Topographic ERP analyses: a step-by-step tutorial review

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.