Scale and frequency chauvinism in brain dynamics: too much emphasis on γ band oscillations

Focal changes in alpha oscillations during short-term memorization of pain: a high-density electroencephalogram study with source localization

Memories of painful events constitute the basis for assessing patients' pain. This study explores the brain oscillatory activity during short-term memorization of a nociceptive stimulus. High-density EEG activity (128 electrodes) was recorded in 13 healthy subjects during a match-to-sample sensory discrimination task, whereby participants compared the intensity of a thumb-located electric shock (S2) with a prior stimulus to the same location (S1) delivered 8-10 s earlier. Stimuli were above or below the individual nociceptive threshold. EEG activity with intracortical source localization via LORETA source reconstruction was analysed during the inter-stimuli period and contrasted with a non-memory-related control task. The inter-stimulus memorization phase was characterized by a focal alpha-activity enhancement, significant during the nociceptive condition only, which progressed from bilateral occipital regions (cuneus and mid-occipital gyri) during the first encoding-memorization phase towards the right-superior and right mid-temporal gyri during the 2-4 s immediately preceding S2. Initial alpha enhancement in occipital areas/cuneus is consistent with rapid non-specific inhibition of task-irrelevant visual processing during initial stimulus encoding. Its transfer to the right-temporal regions was concomitant to the temporary upholding of the stimulus perceptual representation, previous to receiving S2, and suggests an active and local blockade of external interferences while these regions actively maintain internal information. These results add to a growing field indicating that alpha oscillations, while indicating local inhibitory processes, can also indirectly reveal active stimulus handling, including maintenance in short-term memory buffers, by objectivizing the filtering out of irrelevant and potentially disrupting inputs in brain regions engaged in internally driven operations.

Fields or firings? Comparing the spike code and the electromagnetic field hypothesis

Where is consciousness? Neurobiological theories of consciousness look primarily to synaptic firing and "spike codes" as the physical substrate of consciousness, although the specific mechanisms of consciousness remain unknown. Synaptic firing results from electrochemical processes in neuron axons and dendrites. All neurons also produce electromagnetic (EM) fields due to various mechanisms, including the electric potential created by transmembrane ion flows, known as "local field potentials," but there are also more meso-scale and macro-scale EM fields present in the brain. The functional role of these EM fields has long been a source of debate. We suggest that these fields, in both their local and global forms, may be the primary seat of consciousness, working as a gestalt with synaptic firing and other aspects of neuroanatomy to produce the marvelous complexity of minds. We call this assertion the "electromagnetic field hypothesis." The neuroanatomy of the brain produces the local and global EM fields but these fields are not identical with the anatomy of the brain. These fields are produced by, but not identical with, the brain, in the same manner that twigs and leaves are produced by a tree's branches and trunk but are not the same as the branches and trunk. As such, the EM fields represent the more granular, both spatially and temporally, aspects of the brain's structure and functioning than the neuroanatomy of the brain. The brain's various EM fields seem to be more sensitive to small changes than the neuroanatomy of the brain. We discuss issues with the spike code approach as well as the various lines of evidence supporting our argument that the brain's EM fields may be the primary seat of consciousness. This evidence (which occupies most of the paper) suggests that oscillating neural EM fields may make firing in neural circuits oscillate, and these oscillating circuits may help unify and guide conscious cognition.

Sensing local field potentials with a directional and scalable depth electrode array

Objective. A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (a) access to all cortical regions in a minimally invasive manner; (b) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (c) access to spatially distant multiple brain regions that constitute distributed cognitive networks.Approach.We modeled, designed, and demonstrated a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode and combined with radially distributed microelectrodes.Main results. Electro-quasistatic models demonstrate that the lead body amplifies and shields LFP sources based on direction, enablingdirectional sensitivity andscalability, referred to as thedirectional andscalable (DISC) array.In vivo,DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critical for future translation, DISC demonstrated a higher signal to noise ratio (SNR) than virtual ring electrodes and a noise floor approaching that of large ring electrodes in an unshielded environment after common average referencing. DISC also revealed independent, stereoscopic current source density measures whose direction was verified after histology.Significance. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting.

Resting-state electroencephalographic correlates of cognitive reserve: Moderating the age-related worsening in cognitive function

This exploratory study aimed to investigate the resting-state electroencephalographic (rsEEG) correlates of the cognitive reserve from a life span perspective. Current source density (CSD) and lagged-linear connectivity (LLC) measures were assessed to this aim. We firstly explored the relationship between rsEEG measures for the different frequency bands and a socio-behavioral proxy of cognitive reserve, the Cognitive Reserve Index (CRI). Secondly, we applied moderation analyses to assess whether any of the correlated rsEEG measures showed a moderating role in the relationship between age and cognitive function. Moderate negative correlations were found between the CRI and occipital CSD of delta and beta 2. Moreover, inter- and intrahemispheric LLC measures were correlated with the CRI, showing a negative association with delta and positive associations with alpha 1, beta 1, and beta 2. Among those correlated measures, just two rsEEG variables were significant moderators of the relationship between age and cognition: occipital delta CSD and right hemispheric beta 2 LLC between occipital and limbic regions. The effect of age on cognitive performance was stronger for higher values of both measures. Therefore, lower values of occipital delta CSD and lower beta 2 LLC between right occipital and limbic regions might protect or compensate for the effects of age on cognition. Results of this exploratory study might be helpful to allocate more preventive efforts to curb the progression of cognitive decline in adults with less CR, possibly characterized by these rsEEG parameters at a neural level. However, given the exploratory nature of this study, more conclusive work on these rsEEG measures is needed to firmly establish their role in the cognition-age relationship, for example, verifying if these measures moderate the relationship between brain structure and cognition.

Site-dependent shaping of field potential waveforms

The activity of neuron populations gives rise to field potentials (FPs) that extend beyond the sources. Their mixing in the volume dilutes the original temporal motifs in a site-dependent manner, a fact that has received little attention. And yet, it potentially rids of physiological significance the time-frequency parameters of individual waves (amplitude, phase, duration). This is most likely to happen when a single source or a local origin is erroneously assumed. Recent studies using spatial treatment of these signals and anatomically realistic modeling of neuron aggregates provide convincing evidence for the multisource origin and site-dependent blend of FPs. Thus, FPs generated in primary structures like the neocortex and hippocampus reach far and cross-contaminate each other but also, they add and even impose their temporal traits on distant regions. Furthermore, both structures house neurons that act as spatially distinct (but overlapped) FP sources whose activation is state, region, and time dependent, making the composition of so-called local FPs highly volatile and strongly site dependent. Since the spatial reach cannot be predicted without source geometry, it is important to assess whether waveforms and temporal motifs arise from a single source; otherwise, those from each of the co-active sources should be sought.

EEG changes reflecting pain: is alpha suppression better than gamma enhancement?

OBJECTIVE

Suppression of alpha and enhancement of gamma electroencephalographic (EEG) power have both been suggested as objective indicators of cortical pain processing. While gamma activity has been emphasized as the best potential marker, its spectral overlap with pain-related muscular responses is a potential drawback. Since muscle contractions are almost universal concomitants of physical pain, here we investigated alpha and gamma scalp-recorded activities during either tonic pain or voluntary facial grimaces mimicking those triggered by pain.

METHODS

High-density EEG (128 electrodes) was recorded while 14 healthy participants either underwent a cold pressor test (painful hand immersion in 10 °C water) or produced stereotyped facial/nuchal contractions (grimaces) mimicking those evoked by pain. The scalp distribution of spectral EEG changes was quantified via vector-transformation of maps and compared between the pain and grimacing conditions by calculating the cosine of the angle between the two corresponding topographies.

RESULTS

Painful stimuli significantly enhanced gamma power bilaterally in fronto-temporal regions and decreased alpha power in the contralateral central scalp. Sustained cervico-facial contractions (grimaces) gave also rise to significant gamma power increase in fronto-temporal regions but did not decrease central scalp alpha. While changes in alpha topography significantly differed between the pain and grimace situations, the scalp topography of gamma power was statistically indistinguishable from that occurring during grimaces.

CONCLUSION

Gamma power induced by painful stimuli or voluntary facial-cervical muscle contractions had overlapping topography. Pain-related alpha decrease in contralateral central scalp was less disturbed by muscle activity and may therefore prove more discriminant as an ancillary pain biomarker.

A multimodal magnetoencephalography 7 T fMRI and 7 T proton MR spectroscopy study in first episode psychosis

We combined magnetoencephalography (MEG), 7 T proton magnetic resonance spectroscopy (MRS), and 7 T fMRI during performance of a task in a group of 23 first episode psychosis (FEP) patients and 26 matched healthy controls (HC). We recorded both the auditory evoked response to 40 Hz tone clicks and the resting state in MEG. Neurometabolite levels were obtained from the anterior cingulate cortex (ACC). The fMRI BOLD response was obtained during the Stroop inhibitory control task. FEP showed a significant increase in resting state low frequency theta activity (p < 0.05; Cohen d = 0.69), but no significant difference in the 40 Hz auditory evoked response compared to HC. An across-groups whole brain analysis of the fMRI BOLD response identified eight regions that were significantly activated during task performance (p < 0.01, FDR-corrected); the mean signal extracted from those regions was significantly different between the groups (p = 0.0006; d = 1.19). In the combined FEP and HC group, there was a significant correlation between the BOLD signal during task performance and MEG resting state low frequency activity (p < 0.05). In FEP, we report significant alteration in resting state low frequency MEG activity, but no alterations in auditory evoked gamma band response, suggesting that the former is a more robust biomarker of early psychosis. There were no correlations between gamma oscillations and GABA levels in either HC or FEP. Finally, in this study, each of the three imaging modalities differentiated FEP from HC; fMRI with good and MEG and MRS with moderate effect size.

Theta Oscillations in Human Memory

Theta frequency (4-8 Hz) fluctuations of the local field potential have long been implicated in learning and memory. Human studies of episodic memory, however, have provided mixed evidence for theta's role in successful learning and remembering. Re-evaluating these conflicting findings leads us to conclude that: (i) successful memory is associated both with increased narrow-band theta oscillations and a broad-band tilt of the power spectrum; (ii) theta oscillations specifically support associative memory, whereas the spectral tilt reflects a general index of activation; and (iii) different cognitive contrasts (generalized versus specific to memory), recording techniques (invasive versus noninvasive), and referencing schemes (local versus global) alter the balance between the two phenomena to make one or the other more easily detectable.

Recovery of information from latent memory stores decreases over time

Working memory (WM) performance can be enhanced by an informative cue presented during storage. This effect, termed a retrocue benefit, can be used to explore how observers prioritize information stored in WM. Recent studies have demonstrated that neural representations of task-relevant memoranda are strengthened following a retrocue, suggesting that participants can supplement active memory traces with information from other memory stores. We sought to better understand these additional store(s) by asking whether they are subject to the same temporal degradation seen in active memory representations during storage. We tested this possibility by reconstructing and quantifying representations of remembered positions from EEG activity while varying the interval separating an encoding display and retrocue during a spatial WM task. We observed a significant increase in the quality of location-specific representations following a retrocue, but the magnitude of this benefit was linearly and inversely related to the timing of the retrocue such that later cues yielded smaller increases. This result suggests that participants' ability to supplement active memory representations with information from additional memory stores is not static: the information maintained in these stores may be subject to temporal degradation, or these stores may become more difficult to access over time.

Multi-Scale Neural Sources of EEG: Genuine, Equivalent, and Representative. A Tutorial Review

A biophysical framework needed to interpret electrophysiological data recorded at multiple spatial scales of brain tissue is developed. Micro current sources at membrane surfaces produce local field potentials, electrocorticography, and electroencephalography (EEG). We categorize multi-scale sources as genuine, equivalent, or representative. Genuine sources occur at the micro scale of cell surfaces. Equivalent sources provide identical experimental outcomes over a range of scales and applications. In contrast, each representative source distribution is just one of many possible source distributions that yield similar experimental outcomes. Macro sources ("dipoles") may be defined at the macrocolumn (mm) scale and depend on several features of the micro sources-magnitudes, micro synchrony within columns, and distribution through the cortical depths. These micro source properties are determined by brain dynamics and the columnar structure of cortical tissue. The number of representative sources underlying EEG data depends on the spatial scale of neural tissue under study. EEG inverse solutions (e.g. dipole localization) and high resolution estimates (e.g. Laplacian, dura imaging) have both strengths and limitations that depend on experimental conditions. The proposed theoretical framework informs studies of EEG source localization, source characterization, and low pass filtering. It also facilitates interpretations of brain dynamics and cognition, including measures of synchrony, functional connections between cortical locations, and other aspects of brain complexity.

Brief Introduction to Electroencephalography

Electroencephalography (EEG) has a long history in neuroscience starting with its original description in humans by Hans Berger in 1929 (Berger, 1932). Investigations of EEG under anesthesia started soon after in the mid-1930s (Gibbs, 1937). No single methodology paper can credibly cover all of the issues relating to this rich field. The purpose of this chapter is to introduce some caveats that complicate and inform analysis of the EEG. Special emphasis will be given to common issues such as choice of reference electrode, filtering, artifact rejection, and spectral analysis. We will specifically emphasize high-density EEG recordings that have become the norm due to technological improvement in electrode and data acquisition design methods. In the last section we will discuss some applications of EEG analysis techniques to the study of the effects of anesthetics on the nervous system.

Increased gamma band activity for lateral interactions in humans

Collinear facilitation of contrast sensitivity supported by lateral interactions within primary visual cortex is implicated in contour and object perception, with neural correlates in several frequency bands. Although higher component of the ERP power spectrum, the gamma-band, is postulated to reflect object representation, attention and memory, its neuronal source has been questioned, suggesting it is an artifact reflecting saccadic eye movements. Here we explored the gamma-band activity during collinear facilitation with no saccade-related confounds. We used single-trial spectral analysis of ERP in occipital channels in a time-window of nearly complete saccadic suppression and discarded sporadic trials containing saccades, in order to avoid saccadic artifacts. Although converging evidence suggests that gamma-band oscillations emerge from local excitatory–inhibitory balance involving GABAergic inhibition, here we show activity amplification during facilitatory collinear interactions, presumably dominated by excitations, in the gamma-band 150–350 milliseconds following onset of low near-threshold contrast stimulus. This result highlights the potential role of gamma-band oscillations in neuronal encoding of basic processes in visual perception. Thus, our findings suggest that gamma-band ERP spectrum analysis may serve as a useful and reliable tool for exploring basic perception, both in normal adults and in special populations.

Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model

How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals.

Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide “entry points” to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits.

Reliability of event-related EEG functional connectivity during visual entrainment: magnitude squared coherence and phase synchrony estimates

There is an increasing trend towards using noninvasive electroencephalography (EEG) to quantify functional brain connectivity. However, little is known about the psychometrics of commonly used functional connectivity indices. We examined the internal consistency of two different connectivity metrics: magnitude squared coherence and phase synchrony. EEG was recorded during visual entrainment to elicit a strong oscillatory component of known frequency. We found acceptable to good split-half reliability for the connectivity metrics when computing all possible pairwise interactions and after selecting an a priori seed reference. We also compared reliability estimates when using average referenced sensor versus reference independent current source density EEG data. Additional considerations were given to determining how reliability was influenced by factors including trial number, signal-to-noise ratio, and frequency content.

Sensory and cognitive neurophysiology in rats, Part 1: Controlled tactile stimulation and micro-ECoG recordings in freely moving animals

BACKGROUND

We have developed a setup for rats that allows for controlled sensory input to an animal engaged in a task while recording both electrophysiological signals and behavioral output.

NEW METHOD

We record electrophysiological signals using a novel high-density micro-electrocorticography (micro-ECoG) grid that covers almost the whole somatosensory system. We dealt with the well-known difficulty that the rat uses its whisker system in an active (motor-controlled) way to explore its environment by designing a head-mounted device that stimulates the rat's snout in a way unaffected by whisker movements.

RESULTS

We replicate the spatial specificity of early evoked responses in somatosensory and auditory cortex. In a companion paper (Cognitive Neurophysiology in Rats, Part 2: Validation and Demonstration) we validate our setup and show for the first time that the ECoG can be used to record evoked responses in a signal that reflects neural output (spiking activity).

COMPARISON WITH EXISTING METHODS

Compared with high-density wire recordings, micro-ECoG offers a much more stable signal without readjustments, and a much better scalability. Compared with head-fixed preparations, our head-mounted stimulator allows to stay closer to the rat's natural way of collecting sensory information.

CONCLUSIONS

For perceptual and cognitive research, our setup provides a unique combination of possibilities that cannot be achieved in other setups for rodents.

EEG functional connectivity, axon delays and white matter disease

OBJECTIVE

Both structural and functional brain connectivities are closely linked to white matter disease. We discuss several such links of potential interest to neurologists, neurosurgeons, radiologists, and non-clinical neuroscientists.

METHODS

Treatment of brains as genuine complex systems suggests major emphasis on the multi-scale nature of brain connectivity and dynamic behavior. Cross-scale interactions of local, regional, and global networks are apparently responsible for much of EEG's oscillatory behaviors. Finite axon propagation speed, often assumed to be infinite in local network models, is central to our conceptual framework.

RESULTS

Myelin controls axon speed, and the synchrony of impulse traffic between distant cortical regions appears to be critical for optimal mental performance and learning. Several experiments suggest that axon conduction speed is plastic, thereby altering the regional and global white matter connections that facilitate binding of remote local networks.

CONCLUSIONS

Combined EEG and high resolution EEG can provide distinct multi-scale estimates of functional connectivity in both healthy and diseased brains with measures like frequency and phase spectra, covariance, and coherence.

SIGNIFICANCE

White matter disease may profoundly disrupt normal EEG coherence patterns, but currently these kinds of studies are rare in scientific labs and essentially missing from clinical environments.

Cortical brain states and corticospinal synchronization influence TMS-evoked motor potentials

Transcranial magnetic stimulation (TMS) influences cortical processes. Recent findings indicate, however, that, in turn, the efficacy of TMS depends on the state of ongoing cortical oscillations. Whereas power and phase of electromyographic (EMG) activity recorded from the hand muscles as well as neural synchrony between cortex and hand muscles are known to influence the effect of TMS, to date, no study has shown an influence of the phase of cortical oscillations during wakefulness. We applied single-pulse TMS over the motor cortex and recorded motor-evoked potentials along with the electroencephalogram (EEG) and EMG. We correlated phase and power of ongoing EEG and EMG signals with the motor-evoked potential (MEP) amplitude. We also investigated the functional connectivity between cortical and hand muscle activity (corticomuscular coherence) with the MEP amplitude. EEG and EMG power and phase in a frequency band around 18 Hz correlated with the MEP amplitude. High beta-band (∼34 Hz) corticomuscular coherence exhibited a positive linear relationship with the MEP amplitude, indicating that strong synchrony between cortex and hand muscles at the moment when TMS is applied entails large MEPs. Improving upon previous studies, we demonstrate a clear dependence of TMS-induced motor effects on the state of ongoing EEG phase and power fluctuations. We conclude that not only the sampling of incoming information but also the susceptibility of cortical communication flow depends cyclically on neural phase.

The maturation of cortical sleep rhythms and networks over early development

OBJECTIVE

Although neuronal activity drives all aspects of cortical development, how human brain rhythms spontaneously mature remains an active area of research. We sought to systematically evaluate the emergence of human brain rhythms and functional cortical networks over early development.

METHODS

We examined cortical rhythms and coupling patterns from birth through adolescence in a large cohort of healthy children (n=384) using scalp electroencephalogram (EEG) in the sleep state.

RESULTS

We found that the emergence of brain rhythms follows a stereotyped sequence over early development. In general, higher frequencies increase in prominence with striking regional specificity throughout development. The coordination of these rhythmic activities across brain regions follows a general pattern of maturation in which broadly distributed networks of low-frequency oscillations increase in density while networks of high frequency oscillations become sparser and more highly clustered.

CONCLUSION

Our results indicate that a predictable program directs the development of key rhythmic components and physiological brain networks over early development.

SIGNIFICANCE

This work expands our knowledge of normal cortical development. The stereotyped neurophysiological processes observed at the level of rhythms and networks may provide a scaffolding to support critical periods of cognitive growth. Furthermore, these conserved patterns could provide a sensitive biomarker for cortical health across development.

Dissociating neuronal gamma-band activity from cranial and ocular muscle activity in EEG

EEG is the most common technique for studying neuronal dynamics of the human brain. However, electromyogenic artifacts from cranial muscles and ocular muscles executing involuntary microsaccades compromise estimates of neuronal activity in the gamma band (>30 Hz). Yet, the relative contributions and practical consequences of these artifacts remain unclear. Here, we systematically dissected the effects of these different artifacts on studying visual gamma-band activity with EEG on the sensor and source level, and show strategies to cope with these confounds. We found that cranial muscle activity prevented a direct investigation of neuronal gamma-band activity at the sensor level. Furthermore, we found prolonged microsaccade-related artifacts beyond the well-known transient EEG confounds. We then show that if electromyogenic artifacts are carefully accounted for, the EEG nonetheless allows for studying visual gamma-band activity even at the sensor level. Furthermore, we found that source analysis based on spatial filtering does not only map the EEG signals to the cortical space of interest, but also efficiently accounts for cranial and ocular muscle artifacts. Together, our results clarify the relative contributions and characteristics of myogenic artifacts confounding visual gamma-band activity in EEG, and provide practical guidelines for future experiments.

Inducing γ oscillations and precise spike synchrony by operant conditioning via brain-machine interface

Neural oscillations in the low-gamma range (30-50 Hz) have been implicated in neuronal synchrony, computation, behavior, and cognition. Abnormal low-gamma activity, hypothesized to reflect impaired synchronization, has been evidenced in several brain disorders. Thus, understanding the relations between gamma oscillations, neuronal synchrony and behavior is a major research challenge. We used a brain-machine interface (BMI) to train monkeys to specifically increase low-gamma power in selected sites of motor cortex to move a cursor and obtain a reward. The monkeys learned to robustly generate oscillatory gamma waves, which were accompanied by a dramatic increase of spiking synchrony of highly precise spatiotemporal patterns. The findings link volitional control of LFP oscillations, neuronal synchrony, and the behavioral outcome. Subjects' ability to directly modulate specific patterns of neuronal synchrony provides a powerful approach for understanding neuronal processing in relation to behavior and for the use of BMIs in a clinical setting.

Identifying the synaptic origin of ongoing neuronal oscillations through spatial discrimination of electric fields

Although intracerebral field potential oscillations are commonly used to study information processing during cognition and behavior, the cellular and network processes underlying such events remain unclear. The limited spatial resolution of standard single-point recordings does not clarify whether field oscillations reflect the activity of one or many afferent presynaptic populations. However, multi-site recording devices now provide high-resolution spatial profiles of local field potentials (LFPs) and when coupled to modern mathematical analyses that discriminate signals with distinct but overlapping spatial distributions, they open the door to better understand these potentials. Here we review recent insights that help disentangle certain pathway-specific activities. Accordingly, some oscillatory patterns can now be viewed as a periodic succession of synchronous synaptic currents that reflect the time envelope of spiking activity in given presynaptic populations. These analyses modify our concept of brain rhythms as abstract entities, molding them into mechanistic representations of network activity and allowing us to work in the time domain, reducing the loss of information inherent to data-chopping frequency treatment.

Physical model of coherent potentials measured with different electrode recording site sizes

A question that still complicates interpretation of local field potentials (LFPs) is how electrode properties like impedance, size, and shape affect recorded LFPs. In addition, how any such effects should be considered when comparing LFP, electroencephalogram (EEG), or electrocorticogram (ECoG) data has not been clearly described. A generally accepted concrete physical model describes that an electrode records the spatial average of the voltage across its uninsulated tip, yet the effects of this spatial averaging on recorded coherence have never been modeled. Using simulations based on this physical model, we show here that for any effects to occur, a spatial voltage gradient on a scale smaller than an electrode's recording site must exist over the site's surface. When this occurs, larger electrodes on average report higher coherence between locations, with the effect continuously increasing as the voltage profile over the extent of the recording site is increasingly nonuniform. We quantitatively compared published coherence estimates of LFP, ECoG, and EEG data across a range of studies and found a possible modest effect of electrode size in published ECoG data only. We used the model to quantify the expected coherence for any electrode size in relation to any given spatial frequency of a voltage profile. From this and existing estimates of the spread of voltages underlying each of these data types, our simulations quantitatively agree with the published data and importantly suggest that LFP coherence will be independent of recording site size within the range of microelectrodes typically used for extracellular recordings.

Lateralization of frequency-specific networks for covert spatial attention to auditory stimuli

We conducted a cued spatial attention experiment to investigate the time-frequency structure of human EEG induced by attentional orientation of an observer in external auditory space. Seven subjects participated in a task in which attention was cued to one of two spatial locations at left and right. Subjects were instructed to report the speech stimulus at the cued location and to ignore a simultaneous speech stream originating from the uncued location. EEG was recorded from the onset of the directional cue through the offset of the inter-stimulus interval (ISI), during which attention was directed toward the cued location. Using a wavelet spectrum, each frequency band was then normalized by the mean level of power observed in the early part of the cue interval to obtain a measure of induced power related to the deployment of attention. Topographies of band specific induced power during the cue and inter-stimulus intervals showed peaks over symmetric bilateral scalp areas. We used a bootstrap analysis of a lateralization measure defined for symmetric groups of channels in each band to identify specific lateralization events throughout the ISI. Our results suggest that the deployment and maintenance of spatially oriented attention throughout a period of 1,100 ms is marked by distinct episodes of reliable hemispheric lateralization ipsilateral to the direction in which attention is oriented. An early theta lateralization was evident over posterior parietal electrodes and was sustained throughout the ISI. In the alpha and mu bands punctuated episodes of parietal power lateralization were observed roughly 500 ms after attentional deployment, consistent with previous studies of visual attention. In the beta band these episodes show similar patterns of lateralization over frontal motor areas. These results indicate that spatial attention involves similar mechanisms in the auditory and visual modalities.