How local is the local field potential?

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

In a healthy state, pain plays an important role in natural biofeedback loops and helps to detect and prevent potentially harmful stimuli and situations. However, pain can become chronic and as such a pathological condition, losing its informative and adaptive function. Efficient pain treatment remains a largely unmet clinical need. One promising route to improve the characterization of pain, and with that the potential for more effective pain therapies, is the integration of different data modalities through cutting edge computational methods. Using these methods, multiscale, complex, and network models of pain signaling can be created and utilized for the benefit of patients. Such models require collaborative work of experts from different research domains such as medicine, biology, physiology, psychology as well as mathematics and data science. Efficient work of collaborative teams requires developing of a common language and common level of understanding as a prerequisite. One of ways to meet this need is to provide easy to comprehend overviews of certain topics within the pain research domain. Here, we propose such an overview on the topic of pain assessment in humans for computational researchers. Quantifications related to pain are necessary for building computational models. However, as defined by the International Association of the Study of Pain (IASP), pain is a sensory and emotional experience and thus, it cannot be measured and quantified objectively. This results in a need for clear distinctions between nociception, pain and correlates of pain. Therefore, here we review methods to assess pain as a percept and nociception as a biological basis for this percept in humans, with the goal of creating a roadmap of modelling options.

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.

Ferromagnetic Flexible Electronics for Brain-Wide Selective Neural Recording

Flexible microelectronics capable of straightforward implantation, remotely controlled navigation, and stable long-term recording hold great promise in diverse medical applications, particularly in deciphering complex functions of neural circuits in the brain. Existing flexible electronics, however, are often limited in bending and buckling during implantation, and unable to access a large brain region. Here, an injectable class of electronics with stable recording, omnidirectional steering, and precise navigating capabilities based on magnetic actuation is presented. After simple transcriptional injection, the rigid coatings are biodegraded quickly and the bundles of magnetic-nanoparticles-coated microelectrodes become separated, ultra-flexible, and magnetic actuated for further minimally invasive three-dimensional interpenetration in the brain. As proof of concept, this paradigm-shifting approach is demonstrated for selective and multiplexed neural activities recording across distant regions in the deep rodent brains. Coupling with optogenetic neural stimulation, the unique capabilities of this platform in electrophysiological readouts of projection dynamics in vivo are also demonstrated. The ability of these miniaturized, remotely controllable, and biocompatible ferromagnetic flexible electronics to afford minimally invasive manipulations in the soft tissues of the mammalian brain foreshadows applications in other organ systems, with great potential for broad utility in biomedical science and engineering.

Heterozygous disruption of beclin 1 alleviates neurotoxicity induced by sub-chronic exposure of arsenite in mice

Arsenite is a well-documented neurotoxicant that widely exists in the environment. However, the detailed mechanisms of arsenite neurotoxicity are not fully clarified. Autophagy has been reported to be involved in many neurological problems induced by arsenite. Since beclin 1 is an essential mediator of autophagy, we herein used both adult wild-type (beclin 1^+/+) and heterozygous disruption of beclin 1 (beclin 1^+/-) mice for chronic administration of 50 mg/L arsenite via drinking water for 3 months. Our results demonstrated that exposure of arsenite caused the working memory deficit, anxiety-like behavior and motor coordination disorder in beclin 1^+/+ mice, accompanied with pathological changes in morphology and electrophysiology in the cortical tissues. This treatment of arsenite significantly reduced the number of neuronal cells and induced microglia activation and synaptic transmission disorders in the wild-type mice as compared with vehicle controls. Intriguingly, by using beclin 1^+/- mice, we found that heterozygous disruption of beclin 1 profoundly attenuated these neurotoxic effects induced by arsenite, mainly manifested by improvements in the neurobehavioral impairments, abnormal electrophysiologic alterations as well as dysregulation of synaptic transmission. These findings together indicate that regulation of autophagy via beclin 1 would be a potential strategy for treatment against arsenite neurotoxicity.

LFP polarity changes across cortical and eccentricity in primary visual cortex

Local field potentials (LFPs) can evaluate neural population activity in the cortex and their interaction with other cortical areas. Analyzing current source density (CSD) rather than LFPs is very significant due to the reduction of volume conduction effects. Current sinks are construed as net inward transmembrane currents, while current sources are net outward ones. Despite extensive studies of LFPs and CSDs, their morphology in different cortical layers and eccentricities are still largely unknown. Because LFP polarity changes provide a measure of neural activity, they can be useful in implanting brain-computer interface (BCI) chips and effectively communicating the BCI devices to the brain. We hypothesize that sinks and sources analyses could be a way to quantitatively achieve their characteristics in response to changes in stimulus size and layer-dependent differences with increasing eccentricities. In this study, we show that stimulus properties play a crucial role in determining the flow. The present work focusses on the primary visual cortex (V1). In this study, we investigate a map of the LFP-CSD in V1 area by presenting different stimulus properties (e.g., size and type) in the visual field area of Macaque monkeys. Our aim is to use the morphology of sinks and sources to measure the input and output information in different layers as well as different eccentricities. According to the value of CSDs, the results show that the stimuli smaller than RF's size had lower strength than the others and the larger RF's stimulus size showed smaller strength than the optimized stimulus size, which indicated the suppression phenomenon. Additionally, with the increased eccentricity, CSD's strengths were increased across cortical layers.

Multimodal monitoring of human cortical organoids implanted in mice reveal functional connection with visual cortex

Human cortical organoids, three-dimensional neuronal cultures, are emerging as powerful tools to study brain development and dysfunction. However, whether organoids can functionally connect to a sensory network in vivo has yet to be demonstrated. Here, we combine transparent microelectrode arrays and two-photon imaging for longitudinal, multimodal monitoring of human cortical organoids transplanted into the retrosplenial cortex of adult mice. Two-photon imaging shows vascularization of the transplanted organoid. Visual stimuli evoke electrophysiological responses in the organoid, matching the responses from the surrounding cortex. Increases in multi-unit activity (MUA) and gamma power and phase locking of stimulus-evoked MUA with slow oscillations indicate functional integration between the organoid and the host brain. Immunostaining confirms the presence of human-mouse synapses. Implantation of transparent microelectrodes with organoids serves as a versatile in vivo platform for comprehensive evaluation of the development, maturation, and functional integration of human neuronal networks within the mouse brain.

Local Field Potential-Guided Contact Selection Using Chronically Implanted Sensing Devices for Deep Brain Stimulation in Parkinson's Disease

Intra- and perioperatively recorded local field potential (LFP) activity of the nucleus subthalamicus (STN) has been suggested to guide contact selection in patients undergoing deep brain stimulation (DBS) for Parkinson's disease (PD). Despite the invention of sensing capacities in chronically implanted devices, a comprehensible algorithm that enables contact selection using such recordings is still lacking. We evaluated a fully automated algorithm that uses the weighted average of bipolar recordings to determine effective monopolar contacts based on elevated activity in the beta band. LFPs from 14 hemispheres in seven PD patients with newly implanted directional DBS leads of the STN were recorded. First, the algorithm determined the stimulation level with the highest beta activity. Based on the prior determined level, the directional contact with the highest beta activity was chosen in the second step. The mean clinical efficacy of the contacts chosen using the algorithm did not statistically differ from the mean clinical efficacy of standard contact selection as performed in clinical routine. All recording sites were projected into MNI standard space to investigate the feasibility of the algorithm with respect to the anatomical boundaries of the STN. We conclude that the proposed algorithm is a first step towards LFP-based contact selection in STN-DBS for PD using chronically implanted devices.

Neural modulations in the auditory cortex during internal and external attention tasks: A single-patient intracranial recording study

Brain sensory processing is not passive, but is rather modulated by our internal state. Different research methods such as non-invasive imaging methods and intracranial recording of the local field potential (LFP) have been used to study to what extent sensory processing and the auditory cortex in particular are modulated by selective attention. However, at the level of the single- or multi-units the selective attention in humans has not been tested. In addition, most previous research on selective attention has explored externally-oriented attention, but attention can be also directed inward (i.e., internal attention), like spontaneous self-generated thoughts and mind-wandering. In the present study we had a rare opportunity to record multi-unit activity (MUA) in the auditory cortex of a patient. To complement, we also analyzed the LFP signal of the macro-contact in the auditory cortex. Our experiment consisted of two conditions with periodic beeping sounds. The participants were asked either to count the beeps (i.e., an "external attention" condition) or to recall the events of the previous day (i.e., an "internal attention" condition). We found that the four out of seven recorded units in the auditory cortex showed increased firing rates in "external attention" compared to "internal attention" condition. The beginning of this attentional modulation varied across multi-units between 30-50 msec and 130-150 msec from stimulus onset, a result that is compatible with an early selection view. The LFP evoked potential and induced high gamma activity both showed attentional modulation starting at about 70-80 msec. As the control, for the same experiment we recorded MUA activity in the amygdala and hippocampus of two additional patients. No major attentional modulation was found in the control regions. Overall, we believe that our results provide new empirical information and support for existing theoretical views on selective attention and spontaneous self-generated cognition.

Weakly Correlated Local Cortical State Switches under Anesthesia Lead to Strongly Correlated Global States

During recovery from anesthesia, brain activity switches abruptly between a small set of discrete states. Surprisingly, this switching also occurs under constant doses of anesthesia, even in the absence of stimuli. These metastable states and the transitions between them are thought to form a "scaffold" that ultimately guides the brain back to wakefulness. The processes that constrain cortical activity patterns to these states and govern how states are coordinated between different cortical regions are unknown. If state transitions were driven by subcortical modulation, different cortical sites should exhibit near-synchronous state transitions. Conversely, spatiotemporal heterogeneity would suggest that state transitions are coordinated through corticocortical interactions. To differentiate between these hypotheses, we quantified synchrony of brain states in male rats exposed to a fixed isoflurane concentration. States were defined from spectra of local field potentials recorded across layers of visual and motor cortices. A transition synchrony measure shows that most state transitions are highly localized. Furthermore, while most pairs of cortical sites exhibit statistically significant coupling of both states and state transition times, coupling strength is typically weak. States and state transitions in the thalamic input layer (L4) are particularly decoupled from those in supragranular and infragranular layers. This suggests that state transitions are not imposed on the cortex by broadly projecting modulatory systems. Although each pairwise interaction is typically weak, we show that the multitude of such weak interactions is sufficient to confine global activity to a small number of discrete states.SIGNIFICANCE STATEMENT The brain consistently recovers to wakefulness after anesthesia, but this process is poorly understood. Previous work revealed that, during recovery from anesthesia, corticothalamic activity falls into one of several discrete patterns. The neuronal mechanisms constraining the cortex to just a few discrete states remain unknown. Global states could be coordinated by fluctuations in subcortical nuclei that project broadly to the cortex. Alternatively, these states may emerge from interactions within the cortex itself. Here, we provide evidence for the latter possibility by demonstrating that most pairs of cortical sites exhibit weak coupling. We thereby lay groundwork for future investigations of the specific cellular and network mechanisms of corticocortical activity state coupling.

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

GRINtrode: a neural implant for simultaneous two-photon imaging and extracellular electrophysiology in freely moving animals

Significance

In vivo imaging and electrophysiology are powerful tools to explore neuronal function that each offer unique complementary information with advantages and limitations. Capturing both data types from the same neural population in the freely moving animal would allow researchers to take advantage of the capabilities of both modalities and further understand how they relate to each other.

Aim

Here, we present a head-mounted neural implant suitable for in vivo two-photon imaging of neuronal activity with simultaneous extracellular electrical recording in head-fixed or fiber-coupled freely moving animals.

Approach

A gradient refractive index (GRIN) lens-based head-mounted neural implant with extracellular electrical recording provided by tetrodes on the periphery of the GRIN lens was chronically implanted. The design of the neural implant allows for recording from head-fixed animals, as well as freely moving animals by coupling the imaging system to a coherent imaging fiber bundle.

Results

We demonstrate simultaneous two-photon imaging of GCaMP and extracellular electrophysiology of neural activity in awake head-fixed and freely moving mice. Using the collected information, we perform correlation analysis to reveal positive correlation between optical and local field potential recordings.

Conclusion

Simultaneously recording neural activity using both optical and electrical methods provides complementary information from each modality. Designs that can provide such bi-modal recording in freely moving animals allow for the investigation of neural activity underlying a broader range of behavioral paradigms.

Decoding of attentional state using local field potentials

We review recent efforts to decode visual spatial attention from different types of brain signals, such as spikes and local field potentials (LFPs). Combining signals from more electrodes improves decoding, but the pattern of improvement varies considerably depending on the signal as well as the task (for example, decoding of sensory stimulus/motor intention versus location of attention). We argue that this pattern of results conveys important information not only about the usefulness of a particular brain signal for decoding attention, but also about the spatial scale over which attention operates in the brain. The spatial scale, in turn, likely depends on the extent of underlying mechanisms such as normalization, gain control via excitation-inhibition interactions, and neuromodulatory regulation of attention.

Updates to the guinea pig animal model for in-vivo auditory neuroscience in the low-frequency hearing range

For gaining insight into general principles of auditory processing, it is critical to choose model organisms whose set of natural behaviors encompasses the processes being investigated. This reasoning has led to the development of a variety of animal models for auditory neuroscience research, such as guinea pigs, gerbils, chinchillas, rabbits, and ferrets; but in recent years, the availability of cutting-edge molecular tools and other methodologies in the mouse model have led to waning interest in these unique model species. As laboratories increasingly look to include in-vivo components in their research programs, a comprehensive description of procedures and techniques for applying some of these modern neuroscience tools to a non-mouse small animal model would enable researchers to leverage unique model species that may be best suited for testing their specific hypotheses. In this manuscript, we describe in detail the methods we have developed to apply these tools to the guinea pig animal model to answer questions regarding the neural processing of complex sounds, such as vocalizations. We describe techniques for vocalization acquisition, behavioral testing, recording of auditory brainstem responses and frequency-following responses, intracranial neural signals including local field potential and single unit activity, and the expression of transgenes allowing for optogenetic manipulation of neural activity, all in awake and head-fixed guinea pigs. We demonstrate the rich datasets at the behavioral and electrophysiological levels that can be obtained using these techniques, underscoring the guinea pig as a versatile animal model for studying complex auditory processing. More generally, the methods described here are applicable to a broad range of small mammals, enabling investigators to address specific auditory processing questions in model organisms that are best suited for answering them.

Plasticity after cognitive training reflected in prefrontal local field potentials

Learning to perform a new cognitive task induces plasticity of the prefrontal cortex generally involving activation of more neurons and increases in firing rate; however, its effects on single neurons are diverse and complex. We sought to understand how training affects global measures of neural activity by recording and analyzing local field potentials (LFPs) in monkeys before and after they learned to perform working memory tasks. LFP power after training was characterized by a reduction in power in 20-40 Hz during the stimulus presentations and delay periods of the task. Both evoked power, synchronized to task events, and induced power exhibited this decrease after training. The effect was consistent across tasks requiring memory of spatial location and stimulus shape. Error trials were characterized by a lack of LFP power ramping around the fixation onset. Our results reveal signatures of cortical plasticity in LFPs associated with learning to perform cognitive tasks.

Ipsilateral auditory cortex responses to the intact ear after unilateral noise trauma in juvenile rats

BACKGROUND

While ear stimulation produces a robust response in the contralateral auditory cortex (AC), it produces only a weak response in the ipsilateral AC, known as interhemispheric asymmetry. Unilateral deafness can lead to AC plastic changes, resulting in reduced interhemispheric asymmetry and auditory perceptual consequences. However, the unilateral hearing loss-associated plastic changes are far from fully understood. The purpose of this study was to investigate AC responses to the ipsilateral unimpaired ear after noise injury to the contralateral ear in juvenile rats.

METHODS

Rats (50 days) were monaurally exposed to an intense noise (10.0-12.5 kHz, 126 dB SPL) for 2 hours. The unexposed ear-induced ipsilateral AC responses were recorded 2 days and 4 months after exposure and compared between groups.

RESULTS

The noise exposure resulted in complete hearing loss in the exposed ear, but normal function in the other. Two days after exposure, the ipsilateral AC response induced by the intact ear was significantly enhanced and the threshold decreased (the early-onset effect). Four months after noise exposure, in addition to the increased response amplitude, the "slow-increasing" firing pattern of the neurons in the ipsilateral AC turned into the contralateral-AC-response-like "sharp-increasing" pattern (the late-onset effect) with shortened response latency.

DISCUSSION

The early-onset effect can result from release of inhibition due to decreased contralateral input, while the late-onset effect may imply the formation of direct connections in the ipsilateral auditory pathway. The enhanced AC response may help maintain loudness perception and monaural sound localization after unilateral deafness.

Structure-function models of temporal, spatial, and spectral characteristics of non-invasive whole brain functional imaging

We review recent advances in using mathematical models of the relationship between the brain structure and function that capture features of brain dynamics. We argue the need for models that can jointly capture temporal, spatial, and spectral features of brain functional activity. We present recent work on spectral graph theory based models that can accurately capture spectral as well as spatial patterns across multiple frequencies in MEG reconstructions.

The Spatial Reach of Neuronal Coherence and Spike-Field Coupling across the Human Neocortex

Neuronal coherence is thought to be a fundamental mechanism of communication in the brain, where synchronized field potentials coordinate synaptic and spiking events to support plasticity and learning. Although the spread of field potentials has garnered great interest, little is known about the spatial reach of phase synchronization, or neuronal coherence. Functional connectivity between different brain regions is known to occur across long distances, but the locality of synchronization across the neocortex is understudied. Here we used simultaneous recordings from electrocorticography (ECoG) grids and high-density microelectrode arrays to estimate the spatial reach of neuronal coherence and spike-field coherence (SFC) across frontal, temporal, and occipital cortices during cognitive tasks in humans. We observed the strongest coherence within a 2-3 cm distance from the microelectrode arrays, potentially defining an effective range for local communication. This range was relatively consistent across brain regions, spectral frequencies, and cognitive tasks. The magnitude of coherence showed power law decay with increasing distance from the microelectrode arrays, where the highest coherence occurred between ECoG contacts, followed by coherence between ECoG and deep cortical local field potential (LFP), and then SFC (i.e., ECoG > LFP > SFC). The spectral frequency of coherence also affected its magnitude. Alpha coherence (8-14 Hz) was generally higher than other frequencies for signals nearest the microelectrode arrays, whereas delta coherence (1-3 Hz) was higher for signals that were farther away. Action potentials in all brain regions were most coherent with the phase of alpha oscillations, which suggests that alpha waves could play a larger, more spatially local role in spike timing than other frequencies. These findings provide a deeper understanding of the spatial and spectral dynamics of neuronal synchronization, further advancing knowledge about how activity propagates across the human brain.SIGNIFICANCE STATEMENT Coherence is theorized to facilitate information transfer across cerebral space by providing a convenient electrophysiological mechanism to modulate membrane potentials in spatiotemporally complex patterns. Our work uses a multiscale approach to evaluate the spatial reach of phase coherence and spike-field coherence during cognitive tasks in humans. Locally, coherence can reach up to 3 cm around a given area of neocortex. The spectral properties of coherence revealed that alpha phase-field and spike-field coherence were higher within ranges <2 cm, whereas lower-frequency delta coherence was higher for contacts farther away. Spatiotemporally shared information (i.e., coherence) across neocortex seems to reach farther than field potentials alone.

Running speed and REM sleep control two distinct modes of rapid interhemispheric communication

Rhythmic gamma-band communication within and across cortical hemispheres is critical for optimal perception, navigation, and memory. Here, using multisite recordings in both rats and mice, we show that even faster ~140 Hz rhythms are robustly anti-phase across cortical hemispheres, visually resembling splines, the interlocking teeth on mechanical gears. Splines are strongest in superficial granular retrosplenial cortex, a region important for spatial navigation and memory. Spline-frequency interhemispheric communication becomes more coherent and more precisely anti-phase at faster running speeds. Anti-phase splines also demarcate high-activity frames during REM sleep. While splines and associated neuronal spiking are anti-phase across retrosplenial hemispheres during navigation and REM sleep, gamma-rhythmic interhemispheric communication is precisely in-phase. Gamma and splines occur at distinct points of a theta cycle and thus highlight the ability of interhemispheric cortical communication to rapidly switch between in-phase (gamma) and anti-phase (spline) modes within individual theta cycles during both navigation and REM sleep.

Gamma-rhythmic communication within and across cortical hemispheres is critical for optimal perception, navigation, and memory. Here, Ghosh et al. identify even faster ~140 Hz rhythms, named splines, that reflect anti-phase neuronal synchrony across hemispheres. The balance of anti-phase spline and in-phase gamma communication is dynamically controlled by behavior and sleep.

Cross-modal activation of the primary visual cortex by auditory stimulation in RCS rats: considerations in visual prosthesis

An important brain re-wiring, the so-called cross-modal plasticity, occurs during progression of retinal degenerative diseases to compensate for lack of visual input. The visual cortex does not go 'unused', instead it is devoted to processing other sensory modalities. In this study we recorded, in the visual cortex, visual- and auditory-evoked potentials in an anesthetized murine model of retinal degeneration. The latency to the first peak of the recorded local field potentials was used to assess the speed of the response. Visual responses occurred significantly faster in the control group. Conversely, auditory responses appeared significantly faster in animals with retinal degeneration. This suggests the compensatory neural rewiring is optimizing the performance of other sensory modalities, hearing in this case. This phenomenon may play an important role in visual neuro-rehabilitation. Whether or not it can promote or deter the interpretation of artificially encoded neural signals from a visual prosthesis remains to be studied.

Spike-Gamma Phase Relationship in the Visual Cortex

Gamma oscillations (30-70 Hz) have been hypothesized to play a role in cortical function. Most of the proposed mechanisms involve rhythmic modulation of neuronal excitability at gamma frequencies, leading to modulation of spike timing relative to the rhythm. I first show that the gamma band could be more privileged than other frequencies in observing spike-field interactions even in the absence of genuine gamma rhythmicity and discuss several biases in spike-gamma phase estimation. I then discuss the expected spike-gamma phase according to several hypotheses. Inconsistent with the phase-coding hypothesis (but not with others), the spike-gamma phase does not change with changes in stimulus intensity or attentional state, with spikes preferentially occurring 2-4 ms before the trough, but with substantial variability. However, this phase relationship is expected even when gamma is a byproduct of excitatory-inhibitory interactions. Given that gamma occurs in short bursts, I argue that the debate over the role of gamma is a matter of semantics. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Attention differentially modulates multiunit activity in the lateral geniculate nucleus and V1 of macaque monkeys

Attention promotes the selection of behaviorally relevant sensory signals from the barrage of sensory information available. Visual attention modulates the gain of neuronal activity in all visual brain areas examined, although magnitudes of gain modulations vary across areas. For example, attention gain magnitudes in the dorsal lateral geniculate nucleus (LGN) and primary visual cortex (V1) vary tremendously across fMRI measurements in humans and electrophysiological recordings in behaving monkeys. We sought to determine whether these discrepancies are due simply to differences in species or measurement, or more nuanced properties unique to each visual brain area. We also explored whether robust and consistent attention effects, comparable to those measured in humans with fMRI, are observable in the LGN or V1 of monkeys. We measured attentional modulation of multiunit activity in the LGN and V1 of macaque monkeys engaged in a contrast change detection task requiring shifts in covert visual spatial attention. Rigorous analyses of LGN and V1 multiunit activity revealed robust and consistent attentional facilitation throughout V1, with magnitudes comparable to those observed with fMRI. Interestingly, attentional modulation in the LGN was consistently negligible. These findings demonstrate that discrepancies in attention effects are not simply due to species or measurement differences. We also examined whether attention effects correlated with the feature selectivity of recorded multiunits. Distinct relationships suggest that attentional modulation of multiunit activity depends upon the unique structure and function of visual brain areas.

Alpha and broadband high-frequency activity track task dynamics and predict performance in controlled decision-making

Intracranial recordings in human subjects provide a unique, fine-grained temporal and spatial resolution inaccessible to conventional non-invasive methods. A prominent signal in these recordings is broadband high-frequency activity (approx. 70-150 Hz), generally considered to reflect neuronal excitation. Here we explored the use of this broadband signal to track, on a single-trial basis, the temporal and spatial distribution of task-engaged areas involved in decision-making. We additionally focused on the alpha rhythm (8-14 Hz), thought to regulate the (dis)engagement of neuronal populations based on task demands. Using these signals, we characterized activity across cortex using intracranial recordings in patients with intractable epilepsy performing the Multi-Source Interference Task, a Stroop-like decision-making paradigm. We analyzed recordings both from grid electrodes placed over cortical areas including frontotemporal and parietal cortex, and depth electrodes in prefrontal regions, including cingulate cortex. We found a widespread negative relationship between alpha power and broadband activity, substantiating the gating role of alpha in regions beyond sensory/motor cortex. Combined, these signals reflect the spatio-temporal pattern of task-engagement, with alpha decrease signifying task-involved regions and broadband increase temporally locking to specific task aspects, distributed over cortical sites. We report sites that only respond to stimulus presentation or to the decision report and, interestingly, sites that reflect the time-on-task. The latter predict the subject's reaction times on a trial-by-trial basis. A smaller subset of sites showed modulation with task condition. Taken together, alpha and broadband signals allow tracking of neuronal population dynamics across cortex on a fine temporal and spatial scale.

Developments in Deep Brain Stimulators for Successful Aging Towards Smart Devices—An Overview

This work provides an overview of the present state-of-the-art in the development of deep brain Deep Brain Stimulation (DBS) and how such devices alleviate motor and cognitive disorders for a successful aging. This work reviews chronic diseases that are addressable via DBS, reporting also the treatment efficacies. The underlying mechanism for DBS is also reported. A discussion on hardware developments focusing on DBS control paradigms is included specifically the open- and closed-loop “smart” control implementations. Furthermore, developments towards a “smart” DBS, while considering the design challenges, current state of the art, and constraints, are also presented. This work also showcased different methods, using ambient energy scavenging, that offer alternative solutions to prolong the battery life of the DBS device. These are geared towards a low maintenance, semi-autonomous, and less disruptive device to be used by the elderly patient suffering from motor and cognitive disorders.

Astrocyte regulation of neural circuit activity and network states

Astrocytes are known to influence neuronal activity through different mechanisms, including the homeostatic control of extracellular levels of ions and neurotransmitters and the exchange of signaling molecules that regulate synaptic formation, structure, and function. While a great effort done in the past has defined many molecular mechanisms and cellular processes involved in astrocyte-neuron interactions at the cellular level, the consequences of these interactions at the network level in vivo have only relatively recently been identified. This review describes and discusses recent findings on the regulatory effects of astrocytes on the activity of neuronal networks in vivo. Accumulating but still limited, evidence indicates that astrocytes regulate neuronal network rhythmic activity and synchronization as well as brain states. These studies demonstrate a critical contribution of astrocytes to brain activity and are paving the way for a more thorough understanding of the cellular bases of brain function.

Modelling neuron fiber interaction and coupling in non-myelinated bundled fiber

Understanding the local dynamics of a neural network relies heavily on local field potential and cell-field interaction. But it is still unclear how local the local potential is and what kinds of consequences the trans-membrane current flow and produced electric field have on the local neural fiber. Mimicking signal transmission in neighboring nerve fiber, a simulation model is built to analyze local behavior due to trans-membrane current, cell-field interactions, and their repercussions on the bundled fiber system. Simulation studies reveal that depending on the coupling parameters, activity in one fiber can depolarize or hyper-polarize adjacent fibers. The suggested cell-field interaction model was tested using an orientation-selective coupled retinal ganglion cell network, which was compared to its uncoupled counterpart. The proposed work has been used to model and simulate local signal dynamics in a bundled fiber system of an orientation-selective RGC network due to cell-field interaction, as well as to gain insight into the possible significance of dendritic fiber coupling in orientation selectivity bandwidth adjustment.

Protective effect of curcumin against rotenone-induced substantia nigra pars compacta neuronal dysfunction

Rotenone is involved in the degeneration of dopaminergic neurons, and curcumin may prevent or effectively slow the progression of Parkinson's disease (PD). Previous research has shown that the naturally occurring phenolic compound curcumin can reduce inflammation and oxidation, making it a potential therapeutic agent for neurodegenerative diseases. The present study involves investigation of rotenone-induced histological changes in the brain area, hippocampus using Nissl staining after 35 day of subcutaneous injection of rotenone in adult male rats. We sought to determine whether curcumin could protect against rotenone-induced dopaminergic neurotoxicity in a rat model by in vivo electrical recording from Substantia nigra pars compacta (SNc). Curcumin treatment significantly improved electrical activity of neurons in the SNc of rotenone-induced PD model rats. The pattern of histological alterations corresponds with electrophysiological manifestations.

Breaking Down a Rhythm: Dissecting the Mechanisms Underlying Task-Related Neural Oscillations

A century worth of research has linked multiple cognitive, perceptual and behavioral states to various brain oscillations. However, the mechanistic roles and circuit underpinnings of these oscillations remain an area of active study. In this review, we argue that the advent of optogenetic and related systems neuroscience techniques has shifted the field from correlational to causal observations regarding the role of oscillations in brain function. As a result, studying brain rhythms associated with behavior can provide insight at different levels, such as decoding task-relevant information, mapping relevant circuits or determining key proteins involved in rhythmicity. We summarize recent advances in this field, highlighting the methods that are being used for this purpose, and discussing their relative strengths and limitations. We conclude with promising future approaches that will help unravel the functional role of brain rhythms in orchestrating the repertoire of complex behavior.

SEEG in 3D: Interictal Source Localization From Intracerebral Recordings

BACKGROUND

Stereo-electroencephalography (SEEG) uses a three-dimensional configuration of depth electrodes to localize epileptiform activity, but traditional analysis of SEEG is spatially restricted to the point locations of the electrode contacts. Interpolation of brain activity between contacts might allow for three-dimensional representation of epileptiform activity and avoid pitfalls of SEEG interpretation.

OBJECTIVE

The goal of this study was to validate SEEG-based interictal source localization and assess the ability of this technique to monitor far-field activity in non-implanted brain regions.

METHODS

Interictal epileptiform discharges were identified on SEEG in 26 patients who underwent resection, ablation, or disconnection of the suspected epileptogenic zone. Dipoles without (free) and with (scan) gray matter restriction, and current density (sLORETA and SWARM methods), were calculated using a finite element head model. Source localization results were compared to the conventional irritative zone (IZ) and the surgical treatment volumes (TV) of seizure-free vs. non-seizure-free patients.

RESULTS

The median distance from dipole solutions to the nearest contact in the conventional IZ was 7 mm (interquartile range 4-15 mm for free dipoles and 4-14 mm for scan dipoles). The IZ modeled with SWARM predicted contacts within the conventional IZ with 83% (75-100%) sensitivity and 94% (88-100%) specificity. The proportion of current within the TV was greater in seizure-free patients (P = 0.04) and predicted surgical outcome with 45% sensitivity and 93% specificity. Dipole solutions and sLORETA results did not correlate with seizure outcome. Addition of scalp EEG led to more superficial modeled sources (P = 0.03) and negated the ability to predict seizure outcome (P = 0.23). Removal of near-field data from contacts within the TV resulted in smearing of the current distribution (P = 0.007) and precluded prediction of seizure freedom (P = 0.20).

CONCLUSIONS

Source localization accurately represented interictal discharges from SEEG. The proportion of current within the TV distinguished between seizure-free and non-seizure-free patients when near-field recordings were obtained from the surgical target. The high prevalence of deep sources in this cohort likely obscured any benefit of concurrent scalp EEG. SEEG-based interictal source localization is useful in illustrating and corroborating the epileptogenic zone. Additional techniques are needed to localize far-field epileptiform activity from non-implanted brain regions.

Laminar microcircuitry of visual cortex producing attention-associated electric fields

Cognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the neural circuitry giving rise to these signals remains unknown because the functional architecture of cortical columns producing attention-associated electric fields has not been explored. Here, we detail the laminar cortical circuitry underlying an attention-associated electric field measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Last, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field that can be measured extracortically with the relative contribution of each column depending upon the underlying functional architecture.

Multi-Region Local Field Potential Signatures in Response to the Formalin-induced Inflammatory Stimulus in Male Rats

Pain can be ignited by noxious chemical (e.g., acid), mechanical (e.g., pressure), and thermal (e.g., heat) stimuli and generated by the activation of sensory neurons and their axonal terminals called nociceptors in the periphery. Nociceptive information transmitted from the periphery is projected to the central nervous system (thalamus, somatosensory cortex, insular, anterior cingulate cortex, amygdala, periaqueductal grey, prefrontal cortex, etc.) to generate a unified experience of pain. Local field potential (LFP) recording is one of the neurophysiological tools to investigate the combined neuronal activity, ranging from several hundred micrometers to a few millimeters (radius), located around the embedded electrode. The advantage of recording LFP is that it provides stable simultaneous activities in various brain regions in response to external stimuli. In this study, differential LFP activities from the contralateral anterior cingulate cortex (ACC), ventral tegmental area (VTA), and bilateral amygdala in response to peripheral noxious formalin injection were recorded in anesthetized male rats. The results indicated increased power of delta, theta, alpha, beta, and gamma bands in the ACC and amygdala but no change of gamma-band in the right amygdala. Within the VTA, intensities of the delta, theta, and beta bands were only enhanced significantly after formalin injection. It was found that the connectivity (i.t. the coherence) among these brain regions reduced significantly under the formalin-induced nociception, which suggests a significant interruption within the brain. With further study, it will sort out the key combination of structures that will serve as the signature for pain state.

Rhythmicity of Prefrontal Local Field Potentials after Nucleus Basalis Stimulation

The action of acetylcholine in the cortex is critical for cognitive functions and cholinergic drugs can improve functions such as attention and working memory. An alternative means of enhancing cholinergic neuromodulation in primates is the intermittent electrical stimulation of the cortical source of acetylcholine, the nucleus basalis (NB) of Meynert. NB stimulation generally increases firing rate of neurons in the prefrontal cortex, however its effects on single neurons are diverse and complex. We sought to understand how NB stimulation affects global measures of neural activity by recording and analyzing local field potentials (LFPs) in monkeys as they performed working memory tasks. NB stimulation primarily decreased power in the alpha frequency range during the delay interval of working memory tasks. The effect was consistent across variants of the task. No consistent modulation in the delay interval of the task was observed in the gamma frequency range, which has previously been implicated in the maintenance of working memory. Our results reveal global effects of cholinergic neuromodulation via deep brain stimulation, an emerging intervention for the improvement of cognitive function.

Pop-out search instigates beta-gated feature selectivity enhancement across V4 layers

Visual search is a workhorse for investigating how attention interacts with processing of sensory information. Attentional selection has been linked to altered cortical sensory responses and feature preferences (i.e., tuning). However, attentional modulation of feature selectivity during search is largely unexplored. Here we map the spatiotemporal profile of feature selectivity during singleton search. Monkeys performed a search where a pop-out feature determined the target of attention. We recorded laminar neural responses from visual area V4. We first identified "feature columns" which showed preference for individual colors. In the unattended condition, feature columns were significantly more selective in superficial relative to middle and deep layers. Attending a stimulus increased selectivity in all layers but not equally. Feature selectivity increased most in the deep layers, leading to higher selectivity in extragranular layers as compared to the middle layer. This attention-induced enhancement was rhythmically gated in phase with the beta-band local field potential. Beta power dominated both extragranular laminar compartments, but current source density analysis pointed to an origin in superficial layers, specifically. While beta-band power was present regardless of attentional state, feature selectivity was only gated by beta in the attended condition. Neither the beta oscillation nor its gating of feature selectivity varied with microsaccade production. Importantly, beta modulation of neural activity predicted response times, suggesting a direct link between attentional gating and behavioral output. Together, these findings suggest beta-range synaptic activation in V4's superficial layers rhythmically gates attentional enhancement of feature tuning in a way that affects the speed of attentional selection.

Real-time removal of stimulation artifacts in closed-loop deep brain stimulation

Objective.Closed-loop deep brain stimulation (DBS) with neural feedback has shown great potential in improving the therapeutic effect and reducing side effects. However, the amplitude of stimulation artifacts is much larger than the local field potentials, which remains a bottleneck in developing a closed-loop stimulation strategy with varied parameters.Approach.We proposed an irregular sampling method for the real-time removal of stimulation artifacts. The artifact peaks were detected by applying a threshold to the raw recordings, and the samples within the contaminated period of the stimulation pulses were excluded and replaced with the interpolation of the samples prior to and after the stimulation artifact duration. This method was evaluated with both simulation signals andin vivoclosed-loop DBS applications in Parkinsonian animal models.Main results. The irregular sampling method was able to remove the stimulation artifacts effectively with the simulation signals. The relative errors between the power spectral density of the recovered and true signals within a wide frequency band (2-150 Hz) were 2.14%, 3.93%, 7.22%, 7.97% and 6.25% for stimulation at 20 Hz, 60 Hz, 130 Hz, 180 Hz, and stimulation with variable low and high frequencies, respectively. This stimulation artifact removal method was verified in real-time closed-loop DBS applicationsin vivo, and the artifacts were effectively removed during stimulation with frequency continuously changing from 130 Hz to 1 Hz and stimulation adaptive to beta oscillations.Significance.The proposed method provides an approach for real-time removal in closed-loop DBS applications, which is effective in stimulation with low frequency, high frequency, and variable frequency. This method can facilitate the development of more advanced closed-loop DBS strategies.

The significance of neural inter-frequency power correlations

It is of great interest in neuroscience to determine what frequency bands in the brain have covarying power. This would help us robustly identify the frequency signatures of neural processes. However to date, to the best of the author's knowledge, a comprehensive statistical approach to this question that accounts for intra-frequency autocorrelation, frequency-domain oversampling, and multiple testing under dependency has not been undertaken. As such, this work presents a novel statistical significance test for correlated power across frequency bands for a broad class of non-stationary time series. It is validated on synthetic data. It is then used to test all of the inter-frequency power correlations between 0.2 and 8500 Hz in continuous intracortical extracellular neural recordings in Macaque M1, using a very large, publicly available dataset. The recordings were Current Source Density referenced and were recorded with a Utah array. The results support previous results in the literature that show that neural processes in M1 have power signatures across a very broad range of frequency bands. In particular, the power in LFP frequency bands as low as 20 Hz was found to almost always be statistically significantly correlated to the power in kHz frequency ranges. It is proposed that this test can also be used to discover the superimposed frequency domain signatures of all the neural processes in a neural signal, allowing us to identify every interesting neural frequency band.

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

Cross-population coupling of neural activity based on Gaussian process current source densities

Because local field potentials (LFPs) arise from multiple sources in different spatial locations, they do not easily reveal coordinated activity across neural populations on a trial-to-trial basis. As we show here, however, once disparate source signals are decoupled, their trial-to-trial fluctuations become more accessible, and cross-population correlations become more apparent. To decouple sources we introduce a general framework for estimation of current source densities (CSDs). In this framework, the set of LFPs result from noise being added to the transform of the CSD by a biophysical forward model, while the CSD is considered to be the sum of a zero-mean, stationary, spatiotemporal Gaussian process, having fast and slow components, and a mean function, which is the sum of multiple time-varying functions distributed across space, each varying across trials. We derived biophysical forward models relevant to the data we analyzed. In simulation studies this approach improved identification of source signals compared to existing CSD estimation methods. Using data recorded from primate auditory cortex, we analyzed trial-to-trial fluctuations in both steady-state and task-evoked signals. We found cortical layer-specific phase coupling between two probes and showed that the same analysis applied directly to LFPs did not recover these patterns. We also found task-evoked CSDs to be correlated across probes, at specific cortical depths. Using data from Neuropixels probes in mouse visual areas, we again found evidence for depth-specific phase coupling of primary visual cortex and lateromedial area based on the CSDs.

Trial-to-Trial Variability of Spiking Delay Activity in Prefrontal Cortex Constrains Burst-Coding Models of Working Memory

A hallmark neuronal correlate of working memory (WM) is stimulus-selective spiking activity of neurons in PFC during mnemonic delays. These observations have motivated an influential computational modeling framework in which WM is supported by persistent activity. Recently, this framework has been challenged by arguments that observed persistent activity may be an artifact of trial-averaging, which potentially masks high variability of delay activity at the single-trial level. In an alternative scenario, WM delay activity could be encoded in bursts of selective neuronal firing which occur intermittently across trials. However, this alternative proposal has not been tested on single-neuron spike-train data. Here, we developed a framework for addressing this issue by characterizing the trial-to-trial variability of neuronal spiking quantified by Fano factor (FF). By building a doubly stochastic Poisson spiking model, we first demonstrated that the burst-coding proposal implies a significant increase in FF positively correlated with firing rate, and thus loss of stability across trials during the delay. Simulation of spiking cortical circuit WM models further confirmed that FF is a sensitive measure that can well dissociate distinct WM mechanisms. We then tested these predictions on datasets of single-neuron recordings from macaque PFC during three WM tasks. In sharp contrast to the burst-coding model predictions, we only found a small fraction of neurons showing increased WM-dependent burstiness, and stability across trials during delay was strengthened in empirical data. Therefore, reduced trial-to-trial variability during delay provides strong constraints on the contribution of single-neuron intermittent bursting to WM maintenance.SIGNIFICANCE STATEMENT There are diverging classes of theoretical models explaining how information is maintained in working memory by cortical circuits. In an influential model class, neurons exhibit persistent elevated memorandum-selective firing, whereas a recently developed class of burst-coding models suggests that persistent activity is an artifact of trial-averaging, and spiking is sparse in each single trial, subserved by brief intermittent bursts. However, this alternative picture has not been characterized or tested on empirical spike-train data. Here we combine mathematical analysis, computational model simulation, and experimental data analysis to test empirically these two classes of models and show that the trial-to-trial variability of empirical spike trains is not consistent with burst coding. These findings provide constraints for theoretical models of working memory.

Different binaural processing of the envelope component and the temporal fine structure component of a narrowband noise in rat inferior colliculus

Complex broadband sounds are decomposed by peripheral auditory filters into a series of relatively narrowband signals, each with a slowly varying envelope (ENV) and a rapidly fluctuating temporal fine structure (TFS). ENV and TFS information at the bilateral ears contribute differentially to auditory perception. However, whether the difference could attribute to mechanisms of binaural integration remains an open question. As a potential neural correlate, subsets of neurons in the central nucleus of the inferior colliculus (ICC) are known to integrate binaural information with binaural inhibition or binaural summation. Therefore, we recorded the frequency-following responses (FFRs) to the ENV and TFS components of narrowband noises in the ICC of anesthetized rats and examined changes in FFR amplitude and stimulus-response coherence under various sound-delivery settings. We showed that binaural FFR_ENV was predominantly elicited by contralateral inputs and inhibited by ipsilateral inputs, exhibiting a "binaural-inhibition" like property. On the other hand, binaural FFR_TFS received a balanced contribution from both sides, echoing the "binaural-summation" mechanism. What is more, binaural FFR_ENV was significantly correlated with contralateral-evoked but not ipsilateral-evoked FFR_ENV, while binaural FFR_TFS correlated with both contralateral- and ipsilateral-evoked FFR_TFS. Overall, these results suggest distinct binaural processing of ENV and TFS information at the midbrain level.

Inferring entire spiking activity from local field potentials

Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) and spikes. Previous studies have shown that spikes, in the form of single-unit activity (SUA) or multiunit activity (MUA), can be inferred solely from LFPs with moderately good accuracy. SUA and MUA are typically extracted via threshold-based technique which may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). Another type of spiking activity, referred to as entire spiking activity (ESA), can be extracted by a threshold-less, fast, and automated technique and has led to better performance in several tasks. However, its relationship with the LFPs has not been investigated. In this study, we aim to address this issue by inferring ESA from LFPs intracortically recorded from the motor cortex area of three monkeys performing different tasks. Results from long-term recording sessions and across subjects revealed that ESA can be inferred from LFPs with good accuracy. On average, the inference performance of ESA was consistently and significantly higher than those of SUA and MUA. In addition, local motor potential (LMP) was found to be the most predictive feature. The overall results indicate that LFPs contain substantial information about spiking activity, particularly ESA. This could be useful for understanding LFP-spike relationship and for the development of LFP-based BMIs.

Cross Laminar Traveling Components of Field Potentials due to Volume Conduction of Non-Traveling Neuronal Activity in Macaque Sensory Cortices

Field potentials (FPs) reflect neuronal activities in the brain, and often exhibit traveling peaks across recording sites. While traveling FPs are interpreted as propagation of neuronal activity, not all studies directly reveal such propagating patterns of neuronal activation. Neuronal activity is associated with transmembrane currents that form dipoles and produce negative and positive fields. Thereby, FP components reverse polarity between those fields and have minimal amplitudes at the center of dipoles. Although their amplitudes could be smaller, FPs are never flat even around these reversals. What occurs around the reversal has not been addressed explicitly, although those are rationally in the middle of active neurons. We show that sensory FPs around the reversal appeared with peaks traveling across cortical laminae in macaque sensory cortices. Interestingly, analyses of current source density did not depict traveling patterns but lamina-delimited current sinks and sources. We simulated FPs produced by volume conduction of a simplified 2 dipoles' model mimicking sensory cortical laminar current source density components. While FPs generated by single dipoles followed the temporal patterns of the dipole moments without traveling peaks, FPs generated by concurrently active dipole moments appeared with traveling components in the vicinity of dipoles by superimposition of individually non-traveling FPs generated by single dipoles. These results indicate that not all traveling FP are generated by traveling neuronal activity, and that recording positions need to be taken into account to describe FP peak components around active neuronal populations.SIGNIFICANCE STATEMENT Field potentials (FPs) generated by neuronal activity in the brain occur with fields of opposite polarity. Likewise, in the cerebral cortices, they have mirror-imaged waveforms in upper and lower layers. We show that FPs appear like traveling across the cortical layers. Interestingly, the traveling FPs occur without traveling components of current source density, which represents transmembrane currents associated with neuronal activity. These seemingly odd findings are explained using current source density models of multiple dipoles. Concurrently active, non-traveling dipoles produce FPs as mixtures of FPs produced by individual dipoles, and result in traveling FP waveforms as the mixing ratio depends on the distances from those dipoles. The results suggest that not all traveling FP components are associated with propagating neuronal activity.

Mesoscopic physiological interactions in the human brain reveal small-world properties

Cognition depends on rapid and robust communication between neural circuits spanning different brain areas. We investigated the mesoscopic network of cortico-cortical interactions in the human brain in an extensive dataset consisting of 6,024 h of intracranial field potential recordings from 4,142 electrodes in 48 subjects. We evaluated communication between brain areas at the network level across different frequency bands. The interaction networks were validated against known anatomical measurements and neurophysiological interactions in humans and monkeys. The resulting human brain interactome is characterized by a broad and spatially specific, dynamic, and extensive network. The physiological interactome reveals small-world properties, which we conjecture might facilitate efficient and reliable information transmission. The interaction dynamics correlate with the brain sleep/awake state. These results constitute initial steps toward understanding how the interactome orchestrates cortical communication and provide a reference for future efforts assessing how dysfunctional interactions may lead to mental disorders.

Cognition relies on rapid and robust communication between brain areas. Wang et al. leverage multi-day intracranial field potential recordings to characterize the human mesoscopic functional interactome. They validated the methods using monkey anatomical and physiological data. The human interactome reveals small-world properties and is modulated by sleep versus awake state.

Detection of human white matter activation and evaluation of its function in movement decoding using stereo-electroencephalography (SEEG)

Objective. White matter tissue takes up approximately 50% of the human brain volume and it is widely known as a messenger conducting information between areas of the central nervous system. However, the characteristics of white matter neural activity and whether white matter neural recordings can contribute to movement decoding are often ignored and still remain largely unknown. In this work, we make quantitative analyses to investigate these two important questions using invasive neural recordings.Approach. We recorded stereo-electroencephalography (SEEG) data from 32 human subjects during a visually-cued motor task, where SEEG recordings can tap into gray and white matter electrical activity simultaneously. Using the proximal tissue density method, we identified the location (i.e. gray or white matter) of each SEEG contact. Focusing on alpha oscillatory and high gamma activities, we compared the activation patterns between gray matter and white matter. Then, we evaluated the performance of such white matter activation in movement decoding.Main results. The results show that white matter also presents activation under the task, in a similar way with the gray matter but at a significantly lower amplitude. Additionally, this work also demonstrates that combing white matter neural activities together with that of gray matter significantly promotes the movement decoding accuracy than using gray matter signals only.Significance. Taking advantage of SEEG recordings from a large number of subjects, we reveal the response characteristics of white matter neural signals under the task and demonstrate its enhancing function in movement decoding. This study highlights the importance of taking white matter activities into consideration in further scientific research and translational applications.

Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters

In invasive electrophysiological recordings, a variety of neural oscillations can be detected across the cortex, with overlap in space and time. This overlap complicates measurement of neural oscillations using standard referencing schemes, like common average or bipolar referencing. Here, we illustrate the effects of spatial mixing on measuring neural oscillations in invasive electrophysiological recordings and demonstrate the benefits of using data-driven referencing schemes in order to improve measurement of neural oscillations. We discuss referencing as the application of a spatial filter. Spatio-spectral decomposition is used to estimate data-driven spatial filters, a computationally fast method which specifically enhances signal-to-noise ratio for oscillations in a frequency band of interest. We show that application of these data-driven spatial filters has benefits for data exploration, investigation of temporal dynamics and assessment of peak frequencies of neural oscillations. We demonstrate multiple use cases, exploring between-participant variability in presence of oscillations, spatial spread and waveform shape of different rhythms as well as narrowband noise removal with the aid of spatial filters. We find high between-participant variability in the presence of neural oscillations, a large variation in spatial spread of individual rhythms and many non-sinusoidal rhythms across the cortex. Improved measurement of cortical rhythms will yield better conditions for establishing links between cortical activity and behavior, as well as bridging scales between the invasive intracranial measurements and noninvasive macroscale scalp measurements.

Fascicle localisation within peripheral nerves through evoked activity recordings: A comparison between electrical impedance tomography and multi-electrode arrays

BACKGROUND

The lack of understanding of fascicular organisation in peripheral nerves limits the potential of vagus nerve stimulation therapy. Two promising methods may be employed to identify the functional anatomy of fascicles within the nerve: fast neural electrical impedance tomography (EIT), and penetrating multi-electrode arrays (MEA). These could provide a means to image the compound action potential within fascicles in the nerve.

NEW METHOD

We compared the ability to localise fascicle activity between silicon shanks (SS) and carbon fibre (CF) multi-electrode arrays and fast neural EIT, with micro-computed tomography (MicroCT) as an independent reference. Fast neural EIT in peripheral nerves was only recently developed and MEA technology has been used only sparingly in nerves and not for source localisation. Assessment was performed in rat sciatic nerves while evoking neural activity in the tibial and peroneal fascicles.

RESULTS

Recorded compound action potentials were larger with CF compared to SS (∼700 μV vs ∼300 μV); however, background noise was greater (6.3 μV vs 1.7 μV) leading to lower SNR. Maximum spatial discrimination between Centres-of-Mass of fascicular activity was achieved by fast neural EIT (402 ± 30 μm) and CF MEA (414 ± 123 μm), with no statistical difference between MicroCT (625 ± 17 μm) and CF (p > 0.05) and between CF and EIT (p > 0.05). Compared to CF MEAs, SS MEAs had a lower discrimination power (103 ± 51 μm, p < 0.05).

COMPARISON WITH EXISTING METHODS

EIT and CF MEAs showed localisation power closest to MicroCT. Silicon MEAs adopted in this study failed to discriminate fascicle location. Re-design of probe geometry may improve results.

CONCLUSIONS

Nerve EIT is an accurate tool for assessment of fascicular position within nerves. Accuracy of EIT and CF MEA is similar to the reference method. We give technical recommendations for performing multi-electrode recordings in nerves.

Visual Influences on Auditory Behavioral, Neural, and Perceptual Processes: A Review

In a naturalistic environment, auditory cues are often accompanied by information from other senses, which can be redundant with or complementary to the auditory information. Although the multisensory interactions derived from this combination of information and that shape auditory function are seen across all sensory modalities, our greatest body of knowledge to date centers on how vision influences audition. In this review, we attempt to capture the state of our understanding at this point in time regarding this topic. Following a general introduction, the review is divided into 5 sections. In the first section, we review the psychophysical evidence in humans regarding vision's influence in audition, making the distinction between vision's ability to enhance versus alter auditory performance and perception. Three examples are then described that serve to highlight vision's ability to modulate auditory processes: spatial ventriloquism, cross-modal dynamic capture, and the McGurk effect. The final part of this section discusses models that have been built based on available psychophysical data and that seek to provide greater mechanistic insights into how vision can impact audition. The second section reviews the extant neuroimaging and far-field imaging work on this topic, with a strong emphasis on the roles of feedforward and feedback processes, on imaging insights into the causal nature of audiovisual interactions, and on the limitations of current imaging-based approaches. These limitations point to a greater need for machine-learning-based decoding approaches toward understanding how auditory representations are shaped by vision. The third section reviews the wealth of neuroanatomical and neurophysiological data from animal models that highlights audiovisual interactions at the neuronal and circuit level in both subcortical and cortical structures. It also speaks to the functional significance of audiovisual interactions for two critically important facets of auditory perception-scene analysis and communication. The fourth section presents current evidence for alterations in audiovisual processes in three clinical conditions: autism, schizophrenia, and sensorineural hearing loss. These changes in audiovisual interactions are postulated to have cascading effects on higher-order domains of dysfunction in these conditions. The final section highlights ongoing work seeking to leverage our knowledge of audiovisual interactions to develop better remediation approaches to these sensory-based disorders, founded in concepts of perceptual plasticity in which vision has been shown to have the capacity to facilitate auditory learning.

Modular Data Acquisition System for Recording Activity and Electrical Stimulation of Brain Tissue Using Dedicated Electronics

In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat’s brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.

Correlating Beta Oscillations from Intraoperative Microelectrode and Postoperative Implanted Electrode in Patients Undergoing Subthalamic Nucleus Deep Brain Stimulation for Parkinson Disease; A Feasibility Study

OBJECTIVE

We sought to investigate the feasibility of intraoperative local field potential (LFP) recording from the microelectrode during deep brain stimulation surgery for patients with Parkinson disease.

METHODS

Sixteen subthalamic nucleus recordings from 10 Parkinson disease patients who underwent deep brain stimulation surgery were included in this study. Signals from microelectrodes were amplified and differently filtered to display real-time single-unit neuronal activity and LFP simultaneously during surgery. LFP recordings were also recorded postoperatively from the implanted macroelectrodes and, power spectral density and peak frequency of beta oscillation of LFP (beta LFP) between 2 conditions were compared.

RESULTS

Stable intraoperative beta LFP were observed in 68.75% (11 of 16) cases. There was no significant difference of peak frequency between intraoperative and postoperative beta-LFP but significant difference of mean percentage of beta LFP was noted between 2 conditions.

CONCLUSIONS

Despite low signal-to-noise ratio and susceptibility to noises from external sources, this study shows that intraoperative recording of beta LFP using microelectrode is feasible. And, given that no significant difference in peak frequency of beta LFP between intraoperative and postoperative LFP was found, we suggest that not only intraoperative beta LFP can be used as a reliable surrogate for postoperative beta LFP, but it can also provide us an information for estimating the location with maximal power of beta oscillation within the subthalamic nucleus.

Neuronal selectivity to complex vocalization features emerges in the superficial layers of primary auditory cortex

Early in auditory processing, neural responses faithfully reflect acoustic input. At higher stages of auditory processing, however, neurons become selective for particular call types, eventually leading to specialized regions of cortex that preferentially process calls at the highest auditory processing stages. We previously proposed that an intermediate step in how nonselective responses are transformed into call-selective responses is the detection of informative call features. But how neural selectivity for informative call features emerges from nonselective inputs, whether feature selectivity gradually emerges over the processing hierarchy, and how stimulus information is represented in nonselective and feature-selective populations remain open question. In this study, using unanesthetized guinea pigs (GPs), a highly vocal and social rodent, as an animal model, we characterized the neural representation of calls in 3 auditory processing stages-the thalamus (ventral medial geniculate body (vMGB)), and thalamorecipient (L4) and superficial layers (L2/3) of primary auditory cortex (A1). We found that neurons in vMGB and A1 L4 did not exhibit call-selective responses and responded throughout the call durations. However, A1 L2/3 neurons showed high call selectivity with about a third of neurons responding to only 1 or 2 call types. These A1 L2/3 neurons only responded to restricted portions of calls suggesting that they were highly selective for call features. Receptive fields of these A1 L2/3 neurons showed complex spectrotemporal structures that could underlie their high call feature selectivity. Information theoretic analysis revealed that in A1 L4, stimulus information was distributed over the population and was spread out over the call durations. In contrast, in A1 L2/3, individual neurons showed brief bursts of high stimulus-specific information and conveyed high levels of information per spike. These data demonstrate that a transformation in the neural representation of calls occurs between A1 L4 and A1 L2/3, leading to the emergence of a feature-based representation of calls in A1 L2/3. Our data thus suggest that observed cortical specializations for call processing emerge in A1 and set the stage for further mechanistic studies.

The mouse prefrontal cortex: Unity in diversity

The prefrontal cortex (PFC) is considered to constitute the highest stage of neural integration and to be devoted to representation and production of actions. Studies in primates have laid the foundation for theories regarding the principles of prefrontal function and provided mechanistic insights. The recent surge of studies of the PFC in mice holds promise for evolvement of present theories and development of novel concepts, particularly regarding principles shared across mammals. Here we review recent empirical work on the mouse PFC capitalizing on the experimental toolbox currently privileged to studies in this species. We conclude that this line of research has revealed cellular and structural distinctions of the PFC and neuronal activity with direct relevance to theories regarding the functions of the PFC. We foresee that data-rich mouse studies will be key to shed light on the general prefrontal architecture and mechanisms underlying cognitive aspects of organized actions.