How local is the local field potential?

Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

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

Real-time estimation and biofeedback of single-neuron firing rates using local field potentials

The long-term stability and low-frequency composition of local field potentials (LFPs) offer important advantages for robust and efficient neuroprostheses. However, cortical LFPs recorded by multi-electrode arrays are often assumed to contain only redundant information arising from the activity of large neuronal populations. Here we show that multichannel LFPs in monkey motor cortex each contain a slightly different mixture of distinctive slow potentials that accompany neuronal firing. As a result, the firing rates of individual neurons can be estimated with surprising accuracy. We implemented this method in a real-time biofeedback brain–machine interface, and found that monkeys could learn to modulate the activity of arbitrary neurons using feedback derived solely from LFPs. These findings provide a principled method for monitoring individual neurons without long-term recording of action potentials.

The use of local field potential (LFP) brain signals may allow development of more efficient and robust neural prosthetic devices. Here, Hall et al. develop a method for estimation and biofeedback control of single-neuron firing rates using signals extracted from multiple low-frequency LFPs.

The application of electro- and magneto-encephalography in tinnitus research - methods and interpretations

In recent years, there has been a significant increase in the use of electroencephalography (EEG) and magnetoencephalography (MEG) to investigate changes in oscillatory brain activity associated with tinnitus with many conflicting results. Current view of the underlying mechanism of tinnitus is that it results from changes in brain activity in various structures of the brain as a consequence of sensory deprivation. This in turn gives rise to increased spontaneous activity and/or synchrony in the auditory centers but also involves modulation from non-auditory processes from structures of the limbic and paralimbic system. Some of the neural changes associated with tinnitus may be assessed non-invasively in human beings with MEG and EEG (M/EEG) in ways, which are superior to animal studies and other non-invasive imaging techniques. However, both MEG and EEG have their limitations and research results can be misinterpreted without appropriate consideration of these limitations. In this article, I intend to provide a brief review of these techniques, describe what the recorded signals reflect in terms of the underlying neural activity, and their strengths and limitations. I also discuss some pertinent methodological issues involved in tinnitus-related studies and conclude with suggestions to minimize possible discrepancies between results. The overall message is that while MEG and EEG are extremely useful techniques, the interpretation of results from tinnitus studies requires much caution given the individual variability in oscillatory activity and the limits of these techniques.

Beta-coupled high-frequency activity and beta-locked neuronal spiking in the subthalamic nucleus of Parkinson's disease

Beta frequency (13-30 Hz) oscillatory activity in the subthalamic nucleus (STN) of Parkinson's disease (PD) has been shown to influence the temporal dynamics of high-frequency oscillations (HFOs; 200-500 Hz) and single neurons, potentially compromising the functional flexibility of the motor circuit. We examined these interactions by simultaneously recording both local field potential and single-unit activity from the basal ganglia of 15 patients with PD during deep brain stimulation (DBS) surgery of the bilateral STN. Phase-amplitude coupling (PAC) in the STN was specific to beta phase and HFO amplitude, and this coupling was strongest at the dorsal STN border. We found higher beta-HFO PAC near DBS lead contacts that were clinically effective compared with the remaining non-effective contacts, indicating that PAC may be predictive of response to STN DBS. Neuronal spiking was locked to the phase of 8-30 Hz oscillations, and the spatial topography of spike-phase locking (SPL) was similar to that of PAC. Comparisons of PAC and SPL showed a lack of spatiotemporal correlations. Beta-coupled HFOs and field-locked neurons had different preferred phase angles and did not co-occur within the same cycle of the modulating oscillation. Our findings provide additional support that beta-HFO PAC may be central to the pathophysiology of PD and suggest that field-locked neurons alone are not sufficient for the emergence of beta-coupled HFOs.

The use of current source density as electrophysiological correlates in neuropsychiatric disorders: A review of human studies

The use of current source density (CSD), the Laplacian of the scalp surface voltage, to map the electrical activity of the brain is a powerful method in studies of cognitive and affective phenomena. During the last few decades, mapping of CSD has been successfully applied to characterize several neuropsychiatric conditions such as alcoholism, schizophrenia, depression, anxiety disorders, childhood/developmental disorders, and neurological conditions (i.e., epilepsy and brain lesions) using electrophysiological data from resting state and during cognitive performance. The use of CSD and Laplacian measures has proven effective in elucidating topographic and activation differences between groups: i) patients with a specific diagnosis vs. healthy controls, ii) subjects at high risk for a specific diagnosis vs. low risk or normal controls, and iii) patients with specific symptom(s) vs. patients without these symptom(s). The present review outlines and summarizes the studies that have employed CSD measures in investigating several neuropsychiatric conditions. The advantages and potential of CSD-based methods in clinical and research applications along with some of the limitations inherent in the CSD-based methods are discussed in the review, as well as future directions to expand the implementation of CSD to other potential clinical applications. As CSD methods have proved to be more advantageous than using scalp potential data to understand topographic and source activations, its clinical applications offer promising potential, not only for a better understanding of a range of psychiatric conditions, but also for a variety of focal neurological disorders, including epilepsy and other conditions involving brain lesions and surgical interventions.

Alpha- and beta-band oscillations subserve different processes in reactive control of limb movements

The capacity to rapidly suppress a behavioral act in response to sudden instruction to stop is a key cognitive function. This function, called reactive control, is tested in experimental settings using the stop signal task, which requires subjects to generate a movement in response to a go signal or suppress it when a stop signal appears. The ability to inhibit this movement fluctuates over time: sometimes, subjects can stop their response, and at other times, they can not. To determine the neural basis of this fluctuation, we recorded local field potentials (LFPs) in the alpha (6–12 Hz) and beta (13–35 Hz) bands from the dorsal premotor cortex of two nonhuman primates that were performing the task. The ability to countermand a movement after a stop signal was predicted by the activity of both bands, each purportedly representing a distinct neural process. The beta band represents the level of movement preparation; higher beta power corresponds to a lower level of movement preparation, whereas the alpha band supports a proper phasic, reactive inhibitory response: movements are inhibited when alpha band power increases immediately after a stop signal. Our findings support the function of LFP bands in generating the signatures of various neural computations that are multiplexed in the brain.

Generation of field potentials and modulation of their dynamics through volume integration of cortical activity

Field potentials (FPs) recorded within the brain, often called "local field potentials" (LFPs), are useful measures of net synaptic activity in a neuronal ensemble. However, due to volume conduction, FPs spread beyond regions of underlying synaptic activity, and thus an "LFP" signal may not accurately reflect the temporal patterns of synaptic activity in the immediately surrounding neuron population. To better understand the physiological processes reflected in FPs, we explored the relationship between the FP and its membrane current generators using current source density (CSD) analysis in conjunction with a volume conductor model. The model provides a quantitative description of the spatiotemporal summation of immediate local and more distant membrane currents to produce the FP. By applying the model to FPs in the macaque auditory cortex, we have investigated a critical issue that has broad implications for FP research. We have shown that FP responses in particular cortical layers are differentially susceptible to activity in other layers. Activity in the supragranular layers has the strongest contribution to FPs in other cortical layers, and infragranular FPs are most susceptible to contributions from other layers. To define the physiological processes generating FPs recorded in loci of relatively weak synaptic activity, strong effects produced by synaptic events in the vicinity have to be taken into account. While outlining limitations and caveats inherent to FP measurements, our results also suggest specific peak and frequency band components of FPs can be related to activity in specific cortical layers. These results may help improving the interpretability of FPs.

Anisotropy of ongoing neural activity in the primate visual cortex

The mammalian neocortex features distinct anatomical variation in its tangential and radial extents. This review consolidates previously published findings from our group in order to compare and contrast the spatial profile of neural activity coherence across these distinct cortical dimensions. We focus on studies of ongoing local field potential (LFP) data obtained simultaneously from multiple sites in the primary visual cortex in two types of experiments in which electrode contacts were spaced either along the cortical surface or at different laminar positions. These studies demonstrate that across both dimensions the coherence of ongoing LFP fluctuations diminishes as a function of interelectrode distance, although the nature and spatial scale of this falloff is very different. Along the cortical surface, the overall LFP coherence declines gradually and continuously away from a given position. In contrast, across the cortical layers, LFP coherence is discontinuous and compartmentalized as a function of depth. Specifically, regions of high LFP coherence fall into discrete superficial and deep laminar zones, with an abrupt discontinuity between the granular and infragranular layers. This spatial pattern of ongoing LFP coherence is similar when animals are at rest and when they are engaged in a behavioral task. These results point to the existence of partially segregated laminar zones of cortical processing that extend tangentially within the laminar compartments and are thus oriented orthogonal to the cortical columns. We interpret these electrophysiological observations in light of the known anatomical organization of the cortical microcircuit.

Toward more versatile and intuitive cortical brain-machine interfaces

Brain-machine interfaces have great potential for the development of neuroprosthetic applications to assist patients suffering from brain injury or neurodegenerative disease. One type of brain-machine interface is a cortical motor prosthetic, which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using: recordings from cortical areas outside motor cortex; local field potentials as a source of recorded signals; somatosensory feedback for more dexterous control of robotics; and new decoding methods that work in concert to form an ecology of decode algorithms. These new advances promise to greatly accelerate the applicability and ease of operation of motor prosthetics.

Lamina-specific contribution of glutamatergic and GABAergic potentials to hippocampal sharp wave-ripple complexes

The mammalian hippocampus expresses highly organized patterns of neuronal activity which form a neuronal correlate of spatial memories. These memory-encoding neuronal ensembles form on top of different network oscillations which entrain neurons in a state- and experience-dependent manner. The mechanisms underlying activation, timing and selection of participating neurons are incompletely understood. Here we studied the synaptic mechanisms underlying one prominent network pattern called sharp wave-ripple complexes (SPW-R) which are involved in memory consolidation during sleep. We recorded SPW-R with extracellular electrodes along the different layers of area CA1 in mouse hippocampal slices. Contribution of glutamatergic excitation and GABAergic inhibition, respectively, was probed by local application of receptor antagonists into s. radiatum, pyramidale and oriens. Laminar profiles of field potentials show that GABAergic potentials contribute substantially to sharp waves and superimposed ripple oscillations in s. pyramidale. Inhibitory inputs to s. pyramidale and s. oriens are crucial for action potential timing by ripple oscillations, as revealed by multiunit-recordings in the pyramidal cell layer. Glutamatergic afferents, on the other hand, contribute to sharp waves in s. radiatum where they also evoke a fast oscillation at ~200 Hz. Surprisingly, field ripples in s. radiatum are slightly slower than ripples in s. pyramidale, resulting in a systematic shift between dendritic and somatic oscillations. This complex interplay between dendritic excitation and perisomatic inhibition may be responsible for the precise timing of discharge probability during the time course of SPW-R. Together, our data illustrate a complementary role of spatially confined excitatory and inhibitory transmission during highly ordered network patterns in the hippocampus.

An electrocorticographic electrode array for simultaneous recording from medial, lateral, and intrasulcal surface of the cortex in macaque monkeys

BACKGROUND

Electrocorticography (ECoG) permits recording electrical field potentials with high spatiotemporal resolution over a large part of the cerebral cortex. Application of chronically implanted ECoG arrays in animal models provides an opportunity to investigate global spatiotemporal neural patterns and functional connectivity systematically under various experimental conditions. Although ECoG is conventionally used to cover the gyral cortical surface, recent studies have shown the feasibility of intrasulcal ECoG recordings in macaque monkeys.

NEW METHOD

Here we developed a new ECoG array to record neural activity simultaneously from much of the medial and lateral cortical surface of a single hemisphere, together with the supratemporal plane (STP) of the lateral sulcus in macaque monkeys. The ECoG array consisted of 256 electrodes for bipolar recording at 128 sites.

RESULTS

We successfully implanted the ECoG array in the left hemisphere of three rhesus monkeys. The electrodes in the auditory and visual cortex detected robust event related potentials to auditory and visual stimuli, respectively. Bipolar recording from adjacent electrode pairs effectively eliminated chewing artifacts evident in monopolar recording, demonstrating the advantage of using the ECoG array under conditions that generate significant movement artifacts.

COMPARISON WITH EXISTING METHODS

Compared with bipolar ECoG arrays previously developed for macaque monkeys, this array significantly expands the number of cortical target areas in gyral and intralsulcal cortex.

CONCLUSIONS

This new ECoG array provides an opportunity to investigate global network interactions among gyral and intrasulcal cortical areas.

Fast transmission from the dopaminergic ventral midbrain to the sensory cortex of awake primates

Motivated by the increasing evidence that auditory cortex is under control of dopaminergic cell structures of the ventral midbrain, we studied how the ventral tegmental area and substantia nigra affect neuronal activity in auditory cortex. We electrically stimulated 567 deep brain sites in total within and in the vicinity of the two dopaminergic ventral midbrain structures and at the same time, recorded local field potentials and neuronal discharges in cortex. In experiments conducted on three awake macaque monkeys, we found that electrical stimulation of the dopaminergic ventral midbrain resulted in short-latency (~35 ms) phasic activations in all cortical layers of auditory cortex. We were also able to demonstrate similar activations in secondary somatosensory cortex and superior temporal polysensory cortex. The electrically evoked responses in these parts of sensory cortex were similar to those previously described for prefrontal cortex. Moreover, these phasic responses could be reversibly altered by the dopamine D1-receptor antagonist SCH23390 for several tens of minutes. Thus, we speculate that the dopaminergic ventral midbrain exerts a temporally precise, phasic influence on sensory cortex using fast-acting non-dopaminergic transmitters and that their effects are modulated by dopamine on a longer timescale. Our findings suggest that some of the information carried by the neuronal discharges in the dopaminergic ventral midbrain, such as the motivational value or the motivational salience, is transmitted to auditory cortex and other parts of sensory cortex. The mesocortical pathway may thus contribute to the representation of non-auditory events in the auditory cortex and to its associative functions.

Prefrontal cortex reactivity underlies trait vulnerability to chronic social defeat stress

Psychological stress contributes to the onset and exacerbation of nearly all neuropsychiatric disorders. Individual differences in stress-regulatory circuits can therefore dramatically affect vulnerability to these illnesses. Here we identify neural circuit mechanisms underlying individual differences in vulnerability to stress using a murine model of chronic social defeat stress. In chronically stressed mice, we find that the degree of prefrontal cortex (PFC) control of amygdala activity predicts stress-susceptibility in individual mice. Critically, we also find that individual differences in PFC activation (i.e. reactivity) during exposure to an aggressor mouse predict the emergence stress-induced behavioral deficits in stress naïve mice. Finally, we show that naturally occurring differences in PFC reactivity directly correspond to the intrinsic firing rate of PFC neurons. This demonstrates that naturally occurring differences in PFC function underlie individual differences in vulnerability to stress, raising the hypothesis that PFC modulation may prevent stress-induced psychiatric disorders.

Microcircuitry of agranular frontal cortex: testing the generality of the canonical cortical microcircuit

We investigated whether a frontal area that lacks granular layer IV, supplementary eye field, exhibits features of laminar circuitry similar to those observed in primary sensory areas. We report, for the first time, visually evoked local field potentials (LFPs) and spiking activity recorded simultaneously across all layers of agranular frontal cortex using linear electrode arrays. We calculated current source density from the LFPs and compared the laminar organization of evolving sinks to those reported in sensory areas. Simultaneous, transient synaptic current sinks appeared first in layers III and V followed by more prolonged current sinks in layers I/II and VI. We also found no variation of single- or multi-unit visual response latency across layers, and putative pyramidal neurons and interneurons displayed similar response latencies. Many units exhibited pronounced discharge suppression that was strongest in superficial relative to deep layers. Maximum discharge suppression also occurred later in superficial than in deep layers. These results are discussed in the context of the canonical cortical microcircuit model originally formulated to describe early sensory cortex. The data indicate that agranular cortex resembles sensory areas in certain respects, but the cortical microcircuit is modified in nontrivial ways.

Multisensory response modulation in the superficial layers of the superior colliculus

The mammalian superior colliculus (SC) is made up of seven distinct layers. Based on overall differences in neuronal morphology, afferent and efferent projection patterns, physiological properties, and presumptive behavioral role, the upper three layers have been classically grouped together as the superficial layers and the remaining four layers collectively make up the deep layers. Although the superficial layers receive their primary inputs from the retina and primary visual cortex, the deep layers receive inputs from extrastriate visual cortical areas and from auditory, somatosensory, and motor-related structures. In contrast, there is no evidence of monosynaptic nonvisual inputs to the superficial layers. However, more recent studies have revealed anatomical connections between the superficial and deep layers, thus providing the substrate for possible communication between these two functional divisions of the SC. In this study, we provide physiological evidence for auditory influences on visual responses in the superficial layers of the SC. Using extracellular recordings of local field potentials (LFPs) and multiunit activity, we demonstrate multisensory effects in the superficial layers of the cat SC such that subthreshold auditory activity (as seen in the LFP) modulates visual responses (reflected in spiking activity) when the two stimuli are presented together. These results have important implications for our understanding of the functional organization of the SC and for the neural basis of multisensory integration in general.

Long-term decoding stability of local field potentials from silicon arrays in primate motor cortex during a 2D center out task

OBJECTIVE

Many serious concerns exist in the long-term stability of brain-machine interfaces (BMIs) based on spike signals (single unit activity, SUA; multi unit activity, MUA). Some studies showed local field potentials (LFPs) could offer a stable decoding performance. However, the decoding stability of LFPs was examined only when high quality spike signals were recorded. Here we aim to examine the long-term decoding stability of LFPs over a larger time scale when the quality of spike signals was from good to poor or even no spike was recorded.

APPROACH

Neural signals were collected from motor cortex of three monkeys via silicon arrays over 230, 290 and 690 days post-implantation when they performed 2D center out task. To compare long-term stability between LFPs and spike signals, we examined them in neural signals characteristics, directional tuning properties and offline decoding performance, respectively.

MAIN RESULTS

We observed slow decreasing trends in the number of LFP channels recorded and mean LFP power in different frequency bands when spike signals quality decayed over time. The number of significantly directional tuning LFP channels decreased more slowly than that of tuning SUA and MUA. The variable preferred directions for the same signal features across sessions indicated non-stationarity of neural activity. We also found that LFPs achieved better decoding performance than SUA and MUA in retrained decoder when the quality of spike signals seriously decayed. Especially, when no spike was recorded in one monkey after 671 days post-implantation, LFPs still provided some kinematic information. In addition, LFPs outperformed MUA in long-term decoding stability in a static decoder.

SIGNIFICANCE

Our results suggested that LFPs were more durable and could provide better decoding performance when spike signals quality seriously decayed. It might be due to their resistance to recording degradation and their high redundancy among channels.

Undersampled critical branching processes on small-world and random networks fail to reproduce the statistics of spike avalanches

The power-law size distributions obtained experimentally for neuronal avalanches are an important evidence of criticality in the brain. This evidence is supported by the fact that a critical branching process exhibits the same exponent . Models at criticality have been employed to mimic avalanche propagation and explain the statistics observed experimentally. However, a crucial aspect of neuronal recordings has been almost completely neglected in the models: undersampling. While in a typical multielectrode array hundreds of neurons are recorded, in the same area of neuronal tissue tens of thousands of neurons can be found. Here we investigate the consequences of undersampling in models with three different topologies (two-dimensional, small-world and random network) and three different dynamical regimes (subcritical, critical and supercritical). We found that undersampling modifies avalanche size distributions, extinguishing the power laws observed in critical systems. Distributions from subcritical systems are also modified, but the shape of the undersampled distributions is more similar to that of a fully sampled system. Undersampled supercritical systems can recover the general characteristics of the fully sampled version, provided that enough neurons are measured. Undersampling in two-dimensional and small-world networks leads to similar effects, while the random network is insensitive to sampling density due to the lack of a well-defined neighborhood. We conjecture that neuronal avalanches recorded from local field potentials avoid undersampling effects due to the nature of this signal, but the same does not hold for spike avalanches. We conclude that undersampled branching-process-like models in these topologies fail to reproduce the statistics of spike avalanches.

Coupling between gamma-band power and cerebral blood volume during recurrent acute neocortical seizures

Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using non-invasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (>30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2-dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25-90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue.

Identifying and quantifying multisensory integration: a tutorial review

We process information from the world through multiple senses, and the brain must decide what information belongs together and what information should be segregated. One challenge in studying such multisensory integration is how to quantify the multisensory interactions, a challenge that is amplified by the host of methods that are now used to measure neural, behavioral, and perceptual responses. Many of the measures that have been developed to quantify multisensory integration (and which have been derived from single unit analyses), have been applied to these different measures without much consideration for the nature of the process being studied. Here, we provide a review focused on the means with which experimenters quantify multisensory processes and integration across a range of commonly used experimental methodologies. We emphasize the most commonly employed measures, including single- and multiunit responses, local field potentials, functional magnetic resonance imaging, and electroencephalography, along with behavioral measures of detection, accuracy, and response times. In each section, we will discuss the different metrics commonly used to quantify multisensory interactions, including the rationale for their use, their advantages, and the drawbacks and caveats associated with them. Also discussed are possible alternatives to the most commonly used metrics.

Neural dynamics underlying target detection in the human brain

Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses.

Laminar and Columnar Structure of Sensory-Evoked Multineuronal Spike Sequences in Adult Rat Barrel Cortex In Vivo

One of the most relevant questions regarding the function of the nervous system is how sensory information is represented in populations of cortical neurons. Despite its importance, the manner in which sensory-evoked activity propagates across neocortical layers and columns has yet not been fully characterized. In this study, we took advantage of the distinct organization of the rodent barrel cortex and recorded with multielectrode arrays simultaneously from up to 74 neurons localized in several functionally identified layers and columns of anesthetized adult Wistar rats in vivo. The flow of activity within neuronal populations was characterized by temporally precise spike sequences, which were repeatedly evoked by single-whisker stimulation. The majority of the spike sequences representing instantaneous responses were led by a subgroup of putative inhibitory neurons in the principal column at thalamo-recipient layers, thus revealing the presence of feedforward inhibition. However, later spike sequences were mainly led by infragranular excitatory neurons in neighboring columns. Although the starting point of the sequences was anatomically confined, their ending point was rather scattered, suggesting that the population responses are structurally dispersed. Our data show for the first time the simultaneous intra- and intercolumnar processing of information at high temporal resolution.

Subject-specific modulation of local field potential spectral power during brain-machine interface control in primates

OBJECTIVE

Intracortical brain-machine interfaces (BMIs) have predominantly utilized spike activity as the control signal. However, an increasing number of studies have shown the utility of local field potentials (LFPs) for decoding motor related signals. Currently, it is unclear how well different LFP frequencies can serve as features for continuous, closed-loop BMI control.

APPROACH

We demonstrate 2D continuous LFP-based BMI control using closed-loop decoder adaptation, which adapts decoder parameters to subject-specific LFP feature modulations during BMI control. We trained two macaque monkeys to control a 2D cursor in a center-out task by modulating LFP power in the 0-150 Hz range.

MAIN RESULTS

While both monkeys attained control, they used different strategies involving different frequency bands. One monkey primarily utilized the low-frequency spectrum (0-80 Hz), which was highly correlated between channels, and obtained proficient performance even with a single channel. In contrast, the other monkey relied more on higher frequencies (80-150 Hz), which were less correlated between channels, and had greater difficulty with control as the number of channels decreased. We then restricted the monkeys to use only various sub-ranges (0-40, 40-80, and 80-150 Hz) of the 0-150 Hz band. Interestingly, although both monkeys performed better with some sub-ranges than others, they were able to achieve BMI control with all sub-ranges after decoder adaptation, demonstrating broad flexibility in the frequencies that could potentially be used for LFP-based BMI control.

SIGNIFICANCE

Overall, our results demonstrate proficient, continuous BMI control using LFPs and provide insight into the subject-specific spectral patterns of LFP activity modulated during control.

Tuning dissimilarity explains short distance decline of spontaneous spike correlation in macaque V1

Fast spike correlation is a signature of neural ensemble activity thought to underlie perception, cognition, and action. To relate spike correlation to tuning and other factors, we focused on spontaneous activity because it is the common 'baseline' across studies that test different stimuli, and because variations in correlation strength are much larger across cell pairs than across stimuli. Is the probability of spike correlation between two neurons a graded function of lateral cortical separation, independent of functional tuning (e.g. orientation preferences)? Although previous studies found a steep decline in fast spike correlation with horizontal cortical distance, we hypothesized that, at short distances, this decline is better explained by a decline in receptive field tuning similarity. Here we measured macaque V1 tuning via parametric stimuli and spike-triggered analysis, and we developed a generalized linear model (GLM) to examine how different combinations of factors predict spontaneous spike correlation. Spike correlation was predicted by multiple factors including color, spatiotemporal receptive field, spatial frequency, phase and orientation but not ocular dominance beyond layer 4. Including these factors in the model mostly eliminated the contribution of cortical distance to fast spike correlation (up to our recording limit of 1.4mm), in terms of both 'correlation probability' (the incidence of pairs that have significant fast spike correlation) and 'correlation strength' (each pair's likelihood of fast spike correlation). We suggest that, at short distances and non-input layers, V1 fast spike correlation is determined more by tuning similarity than by cortical distance or ocular dominance.

Toward a proper estimation of phase-amplitude coupling in neural oscillations

BACKGROUND

The phase-amplitude coupling (PAC) between distinct neural oscillations is critical to brain functions that include cross-scale organization, selection of attention, routing the flow of information through neural circuits, memory processing and information coding. Several methods for PAC estimation have been proposed but the limitations of PAC estimation as well as the assumptions about the data for accurate PAC estimation are unclear.

NEW METHOD

We define boundary conditions for standard PAC algorithms and propose "oscillation-triggered coupling" (OTC), a parameter-free, data-driven algorithm for unbiased estimation of PAC. OTC establishes a unified framework that treats individual oscillations as discrete events for estimating PAC from a set of oscillations and for characterizing events from time windows as short as a single modulating oscillation.

RESULTS

For accurate PAC estimation, standard PAC algorithms require amplitude filters with a bandwidth at least twice the modulatory frequency. The phase filters must be moderately narrow-band, especially when the modulatory rhythm is non-sinusoidal. The minimally appropriate analysis window is ∼10s. We then demonstrate that OTC can characterize PAC by treating neural oscillations as discrete events rather than continuous phase and amplitude time series.

COMPARISON WITH EXISTING METHODS

These findings show that in addition to providing the same information about PAC as the standard approach, OTC facilitates characterization of single oscillations and their sequences, in addition to explaining the role of individual oscillations in generating PAC patterns.

CONCLUSIONS

OTC allows PAC analysis at the level of individual oscillations and therefore enables investigation of PAC at the time scales of cognitive phenomena.

A roadmap to applying optogenetics in neuroscience

Optogenetics allows for the specific manipulation of the activity of genetically defined cell populations in the CNS. Yet, it requires effective gene delivery, light stimulation, and readout strategies. Here, we provide a roadmap aimed at guiding the experimenter in the process of establishing an optogenetic approach tailored to a given research hypothesis in the field of neuroscience.

Modelling and analysis of local field potentials for studying the function of cortical circuits

The past decade has witnessed a renewed interest in cortical local field potentials (LFPs)--that is, extracellularly recorded potentials with frequencies of up to ~500 Hz. This is due to both the advent of multielectrodes, which has enabled recording of LFPs at tens to hundreds of sites simultaneously, and the insight that LFPs offer a unique window into key integrative synaptic processes in cortical populations. However, owing to its numerous potential neural sources, the LFP is more difficult to interpret than are spikes. Careful mathematical modelling and analysis are needed to take full advantage of the opportunities that this signal offers in understanding signal processing in cortical circuits and, ultimately, the neural basis of perception and cognition.

NMDA receptor antagonist-enhanced high frequency oscillations: are they generated broadly or regionally specific?

Systemic administration of NMDA receptor antagonists, used to model schizophrenia, increase the power of high-frequency oscillations (130-180Hz, HFO) in a variety of neuroanatomical and functionally distinct brain regions. However, it is unclear whether HFO are independently and locally generated or instead spread from a distant source. To address this issue, we used local infusion of tetrodotoxin (TTX) to distinct brain areas to determine how accurately HFO recorded after injection of NMDAR antagonists reflect the activity actually generated at the electrode tip. Changes in power were evaluated in local field potentials (LFPs) recorded from the nucleus accumbens (NAc), prefrontal cortex and caudate and in electrocorticograms (ECoGs) from visual and frontal areas. HFO recorded in frontal and visual cortices (ECoGs) or in the prefrontal cortex, caudate (LFPs) co-varied in power and frequency with observed changes in the NAc. TTX infusion to the NAc immediately and profoundly reduced the power of accumbal HFO which correlated with changes in HFO recorded in distant cortical sites. In contrast, TTX infusion to the prefrontal cortex did not change HFO power recorded locally, although gamma power was reduced. A very similar result was found after TTX infusion to the caudate. These findings raise the possibility that the NAc is an important neural generator. Our data also support existing studies challenging the idea that high frequencies recorded in LFPs are necessarily generated at the recording site.

Convergent approaches toward the study of multisensory perception

Classical analytical approaches for examining multisensory processing in individual neurons have relied heavily on changes in mean firing rate to assess the presence and magnitude of multisensory interaction. However, neurophysiological studies within individual sensory systems have illustrated that important sensory and perceptual information is encoded in forms that go beyond these traditional spike-based measures. Here we review analytical tools as they are used within individual sensory systems (auditory, somatosensory, and visual) to advance our understanding of how sensory cues are effectively integrated across modalities (e.g., audiovisual cues facilitating speech processing). Specifically, we discuss how methods used to assess response variability (Fano factor, or FF), local field potentials (LFPs), current source density (CSD), oscillatory coherence, spike synchrony, and receiver operating characteristics (ROC) represent particularly promising tools for understanding the neural encoding of multisensory stimulus features. The utility of each approach and how it might optimally be applied toward understanding multisensory processing is placed within the context of exciting new data that is just beginning to be generated. Finally, we address how underlying encoding mechanisms might shape-and be tested alongside with-the known behavioral and perceptual benefits that accompany multisensory processing.

Interactions between the lateral habenula and the hippocampus: implication for spatial memory processes

The lateral habenula (LHb) is an epithalamic structure connected with both the basal ganglia and the limbic system and that exerts a major influence on midbrain monoaminergic nuclei. The current view is that LHb receives and processes cortical information in order to select proper strategies in a variety of behavior. Recent evidence indicates that LHb might also be implicated in hippocampus-dependent memory processes. However, if and how LHb functionally interacts with the dorsal hippocampus (dHPC) is still unknown. We therefore performed simultaneous recordings within LHb and dHPC in both anesthetized and freely moving rats. We first showed that a subset of LHb cells were phase-locked to hippocampal theta oscillations. Furthermore, LHb generated spontaneous theta oscillatory activity, which was highly coherent with hippocampal theta oscillations. Using reversible LHb inactivation, we found that LHb might regulate dHPC theta oscillations. In addition, we showed that LHb silencing altered performance in a hippocampus-dependent spatial recognition task. Finally, increased coherence between LHb and dHPC was positively correlated to the memory performance in this test. Collectively, these results suggest that LHb functionally interacts with the hippocampus and is involved in hippocampus-dependent spatial information processing.

A systematic review of the effects of NMDA receptor antagonists on oscillatory activity recorded in vivo

Distinct frequency bands can be differentiated from neuronal ensemble recordings, such as local field potentials or electrocorticogram recordings. Recent years have witnessed a rapid acceleration of research examining how N-methyl-D-aspartate receptor (NMDAR) antagonists influence fundamental frequency bands in cortical and subcortical brain regions. Herein, we systematically review findings from in vivo studies with a focus on delta, theta, gamma and more recently identified high-frequency oscillations. We also discuss some of the current hypotheses that are considered to account for the actions of NMDAR antagonists on these frequency bands. The data emphasize a close relationship between altered oscillatory activity and NMDAR blockade, with both local and large-scale networks accounting for their effects. These findings may have fundamental implications for the psychotomimetic effects produced by NMDAR antagonists.

Assessment of electric field distribution in anisotropic cortical and subcortical regions under the influence of tDCS

The focus of this study is to estimate the contribution of regional anisotropic conductivity on the spatial distribution of an induced electric field across gray matter (GM), white matter (WM), and subcortical regions under transcranial direct current stimulation (tDCS). The assessment was conducted using a passive high-resolution finite element head model with inhomogeneous and variable anisotropic conductivities derived from the diffusion tensor data. Electric field distribution was evaluated across different cortical as well as subcortical regions under four bicephalic electrode configurations. Results indicate that regional tissue heterogeneity and anisotropy cause the pattern of induced fields to vary in orientation and strength when compared to the isotropic scenario. Different electrode montages resulted in distinct distribution patterns with noticeable variations in field strengths. The effect of anisotropy is highly montage dependent and directional conductivity has a more profound effect in defining the strength of the induced field. The inclusion of anisotropy in the GM and subcortical regions has a significant effect on the strength and spatial distribution of the induced electric field. Under the (C3-Fp2) montage, the inclusion of GM and subcortical anisotropy increased the average percentage difference in the electric field strength of brain from 5% to 34% (WM anisotropy only). In terms of patterns distribution, the topographic errors increased from 9.9% to 40% (WM anisotropy only) across the brain.

Early activation of ventral hippocampus and subiculum during spontaneous seizures in a rat model of temporal lobe epilepsy

Temporal lobe epilepsy is the most common form of epilepsy in adults. The pilocarpine-treated rat model is used frequently to investigate temporal lobe epilepsy. The validity of the pilocarpine model has been challenged based largely on concerns that seizures might initiate in different brain regions in rats than in patients. The present study used 32 recording electrodes per rat to evaluate spontaneous seizures in various brain regions including the septum, dorsomedial thalamus, amygdala, olfactory cortex, dorsal and ventral hippocampus, substantia nigra, entorhinal cortex, and ventral subiculum. Compared with published results from patients, seizures in rats tended to be shorter, spread faster and more extensively, generate behavioral manifestations more quickly, and produce generalized convulsions more frequently. Similarities to patients included electrographic waveform patterns at seizure onset, variability in sites of earliest seizure activity within individuals, and variability in patterns of seizure spread. Like patients, the earliest seizure activity in rats was recorded most frequently within the hippocampal formation. The ventral hippocampus and ventral subiculum displayed the earliest seizure activity. Amygdala, olfactory cortex, and septum occasionally displayed early seizure latencies, but not above chance levels. Substantia nigra and dorsomedial thalamus demonstrated consistently late seizure onsets, suggesting their unlikely involvement in seizure initiation. The results of the present study reveal similarities in onset sites of spontaneous seizures in patients with temporal lobe epilepsy and pilocarpine-treated rats that support the model's validity.

Cytoarchitectonic and dynamic origins of giant positive local field potentials in the dentate gyrus

To determine why some pathways but not others produce sizable local field potentials (LFPs) and how far from the source can these be recorded, complementary experimental analyses and realistic modeling of specific brain structures are required. In the present study, we combined multiple in vivo linear recordings in rats and a tridimensional finite element model of the dentate gyrus, a curved structure displaying abnormally large positive LFPs. We demonstrate that the polarized dendritic arbour of granule cells (GCs), combined with the curved layered configuration of the population promote the spatial clustering of GC currents in the interposed hilus and project them through the open side at a distance from cell domains. LFPs grow up to 20 times larger than observed in synaptic sites. The dominant positive polarity of hilar LFPs was only produced by the synchronous activation of GCs in both blades by either somatic inhibition or dendritic excitation. Moreover, the corresponding anatomical pathways must project to both blades of the dentate gyrus as even a mild decrease in the spatial synchronization resulted in a dramatic reduction in LFP power in distant sites, yet not in the GC domains. It is concluded that the activation of layered structures may establish sharply delimited spatial domains where synaptic currents from one or another input appear to be segregated according to the topology of afferent pathways and the cytoarchitectonic features of the target population. These also determine preferred directions for volume conduction in the brain, of relevance for interpretation of surface EEG recordings.

Evidence for differential top-down and bottom-up suppression in posterior parietal cortex

When searching for an object, we usually avoid items that are visually different from the target and objects or places that have been searched already. Previous studies have shown that neural activity in the lateral intraparietal area (LIP) can be used to guide this behaviour; responses to task irrelevant stimuli or to stimuli that have been fixated previously in the trial are reduced compared with responses to potential targets. Here, we test the hypothesis that these reduced responses have a different genesis. Two animals were trained on a visual foraging task, in which they had to find a target among a number of physically identical potential targets (T) and task irrelevant distractors. We recorded neural activity and local field potentials (LFPs) in LIP while the animals performed the task. We found that LFP power was similar for potential targets and distractors but was greater in the alpha and low beta bands when a previously fixated T was in the response field. We interpret these data to suggest that the reduced single-unit response to distractors is a bottom-up feed-forward result of processing in earlier areas and the reduced response to previously fixated Ts is a result of active top-down suppression.

Resting state functional connectivity: its physiological basis and application in neuropharmacology

Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Systems-level network activity can be investigated by resting state magnetic resonance imaging (rsMRI), an emerging neuroimaging technique that assesses the synchrony of the brain's ongoing spontaneous activity. Converging evidence reveals that rsMRI is able to consistently identify distinct spatiotemporal patterns of large-scale brain networks. Dysregulation within and between these networks has been implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer's disease and drug addiction. Despite wide application of this approach in systems neuroscience, the physiological basis of these fluctuations remains incompletely understood. Here we review physiological studies in electrical, metabolic and hemodynamic fluctuations that are most pertinent to the rsMRI signal. We also review recent applications to neuropharmacology - specifically drug effects on resting state fluctuations. We speculate that the mechanisms governing spontaneous fluctuations in regional oxygenation availability likely give rise to the observed rsMRI signal. We conclude by identifying several open questions surrounding this technique. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'.

Coherent delta-band oscillations between cortical areas correlate with decision making

Coherent oscillations in the theta-to-gamma frequency range have been proposed as a mechanism that coordinates neural activity in large-scale cortical networks in sensory, motor, and cognitive tasks. Whether this mechanism also involves coherent oscillations at delta frequencies (1-4 Hz) is not known. Rather, delta oscillations have been associated with slow-wave sleep. Here, we show coherent oscillations in the delta frequency band between parietal and frontal cortices during the decision-making component of a somatosensory discrimination task. Importantly, the magnitude of this delta-band coherence is modulated by the different decision alternatives. Furthermore, during control conditions not requiring decision making, delta-band coherences are typically much reduced. Our work indicates an important role for synchronous activity in the delta frequency band when large-scale, distant cortical networks coordinate their neural activity during decision making.

Quantitative basis for neuroimaging of cortical laminae with calibrated functional MRI

Layer-specific neurophysiologic, hemodynamic, and metabolic measurements are needed to interpret high-resolution functional magnetic resonance imaging (fMRI) data in the cerebral cortex. We examined how neurovascular and neurometabolic couplings vary vertically in the rat's somatosensory cortex. During sensory stimulation we measured dynamic layer-specific responses of local field potential (LFP) and multiunit activity (MUA) as well as blood oxygenation level-dependent (BOLD) signal and cerebral blood volume (CBV) and blood flow (CBF), which in turn were used to calculate changes in oxidative metabolism (CMR(O2)) with calibrated fMRI. Both BOLD signal and CBV decreased from superficial to deep laminae, but these responses were not well correlated with either layer-specific LFP or MUA. However, CBF changes were quite stable across laminae, similar to LFP. However, changes in CMR(O2) and MUA varied across cortex in a correlated manner and both were reduced in superficial lamina. These results lay the framework for quantitative neuroimaging across cortical laminae with calibrated fMRI methods.

Universal organization of resting brain activity at the thermodynamic critical point

Thermodynamic criticality describes emergent phenomena in a wide variety of complex systems. In the mammalian cortex, one type of complex dynamics that spontaneously emerges from neuronal interactions has been characterized as neuronal avalanches. Several aspects of neuronal avalanches such as their size and life time distributions are described by power laws with unique exponents, indicating an underlying critical branching process that governs avalanche formation. Here, we show that neuronal avalanches also reflect an organization of brain dynamics close to a thermodynamic critical point. We recorded spontaneous cortical activity in monkeys and humans at rest using high-density intracranial microelectrode arrays and magnetoencephalography, respectively. By numerically changing a control parameter equivalent to thermodynamic temperature, we observed typical critical behavior in cortical activities near the actual physiological condition, including the phase transition of an order parameter, as well as the divergence of susceptibility and specific heat. Finite-size scaling of these quantities allowed us to derive robust critical exponents highly consistent across monkey and humans that uncover a distinct, yet universal organization of brain dynamics. Our results demonstrate that normal brain dynamics at rest resides near or at criticality, which maximizes several aspects of information processing such as input sensitivity and dynamic range.

Frequency dependence of signal power and spatial reach of the local field potential

Despite its century-old use, the interpretation of local field potentials (LFPs), the low-frequency part of electrical signals recorded in the brain, is still debated. In cortex the LFP appears to mainly stem from transmembrane neuronal currents following synaptic input, and obvious questions regarding the 'locality' of the LFP are: What is the size of the signal-generating region, i.e., the spatial reach, around a recording contact? How far does the LFP signal extend outside a synaptically activated neuronal population? And how do the answers depend on the temporal frequency of the LFP signal? Experimental inquiries have given conflicting results, and we here pursue a modeling approach based on a well-established biophysical forward-modeling scheme incorporating detailed reconstructed neuronal morphologies in precise calculations of population LFPs including thousands of neurons. The two key factors determining the frequency dependence of LFP are the spatial decay of the single-neuron LFP contribution and the conversion of synaptic input correlations into correlations between single-neuron LFP contributions. Both factors are seen to give low-pass filtering of the LFP signal power. For uncorrelated input only the first factor is relevant, and here a modest reduction (<50%) in the spatial reach is observed for higher frequencies (>100 Hz) compared to the near-DC ([Formula: see text]) value of about [Formula: see text]. Much larger frequency-dependent effects are seen when populations of pyramidal neurons receive correlated and spatially asymmetric inputs: the low-frequency ([Formula: see text]) LFP power can here be an order of magnitude or more larger than at 60 Hz. Moreover, the low-frequency LFP components have larger spatial reach and extend further outside the active population than high-frequency components. Further, the spatial LFP profiles for such populations typically span the full vertical extent of the dendrites of neurons in the population. Our numerical findings are backed up by an intuitive simplified model for the generation of population LFP.

Oscillatory correlates of memory in non-human primates

The ability to navigate through our environment, explore with our senses, track the passage of time, and integrate these various components to form the experiences which make up our lives is shared among humans and animals. The use of animal models to study memory, coupled with electrophysiological techniques that permit the direct measurement of neural activity as memories are formed and retrieved, has provided a wealth of knowledge about these mechanisms. Here, we discuss current knowledge regarding the specific role of neural oscillations in memory, with particular emphasis on findings derived from non-human primates. Some of these findings provide evidence for the existence in the primate brain of mechanisms previously identified only in rodents and other lower mammals, while other findings suggest parallels between memory-related activity and processes observed in other cognitive modalities, including attention and sensory perception. Taken together, these results provide insight into how network activity may be organized to promote memory formation, and suggest that key aspects of this activity are similar across species, providing important information about the organization of human memory.

Ready for action: a role for the human midbrain in responding to infant vocalizations

Infant vocalizations are among the most biologically salient sounds in the environment and can draw the listener to the infant rapidly in both times of distress and joy. A region of the midbrain, the periaqueductal gray (PAG), has long been implicated in the control of urgent, survival-related behaviours. To test for PAG involvement in the processing of infant vocalizations, we recorded local field potentials from macroelectrodes implanted in this region in four adults who had undergone deep brain stimulation. We found a significant difference occurring as early as 49 ms after hearing a sound in activity recorded from the PAG in response to infant vocalizations compared with constructed control sounds and adult and animal affective vocalizations. This difference was not present in recordings from thalamic electrodes implanted in three of the patients. Time frequency analyses revealed distinct patterns of activity in the PAG for infant vocalisations, constructed control sounds and adult and animal vocalisations. These results suggest that human infant vocalizations can be discriminated from other emotional or acoustically similar sounds early in the auditory pathway. We propose that this specific, rapid activity in response to infant vocalizations may reflect the initiation of a state of heightened alertness necessary to instigate protective caregiving.

Making waves: initiation and propagation of corticothalamic Ca2+ waves in vivo

Corticothalamic slow oscillations of neuronal activity determine internal brain states. At least in the cortex, the electrical activity is associated with large neuronal Ca(2+) transients. Here we implemented an optogenetic approach to explore causal features of the generation of slow oscillation-associated Ca(2+) waves in the in vivo mouse brain. We demonstrate that brief optogenetic stimulation (3-20 ms) of a local group of layer 5 cortical neurons is sufficient for the induction of global brain Ca(2+) waves. These Ca(2+) waves are evoked in an all-or-none manner, exhibit refractoriness during repetitive stimulation, and propagate over long distances. By local optogenetic stimulation, we demonstrate that evoked Ca(2+) waves initially invade the cortex, followed by a secondary recruitment of the thalamus. Together, our results establish that synchronous activity in a small cluster of layer 5 cortical neurons can initiate a global neuronal wave of activity suited for long-range corticothalamic integration.

Cortical-amygdalar circuit dysfunction in a genetic mouse model of serotonin deficiency

Although the majority of first-line antidepressants increase brain serotonin and rare polymorphisms in tryptophan hydroxlase-2 (Tph2), the rate-limiting enzyme in the brain serotonin synthesis pathway, have been identified in cohorts of subjects with major depressive disorder, the circuit level alterations that results from serotonergic hypofunction remain poorly understood. Here we use chronic multicircuit neurophysiological recordings to characterize functional interactions across cortical and limbic circuits in mice engineered to express a human loss-of-function depression allele Tph2-(R441H) [Tph2 knockin (Tph2KI)]. Our results show that Tph2KI mice exhibit increased intra-network synchrony within medial prefrontal cortex (mPFC) and basal amygdala (AMY) and increased inter-network synchrony between these two brain networks. Moreover, we demonstrate that chronic treatment with fluoxetine reverses several of the circuit alterations observed within Tph2KI mice. Together, our findings establish a functional link between functional hyposerotonergia and altered mPFC-AMY network dynamics.

Microscale inhomogeneity of brain tissue distorts electrical signal propagation

Interpretations of local field potentials (LFPs) are typically shaped on an assumption that the brain is a homogenous conductive milieu. However, microscale inhomogeneities including cell bodies, dendritic structures, axonal fiber bundles and blood vessels are unequivocally present and have different conductivities and permittivities than brain extracellular fluid. To determine the extent to which these obstructions affect electrical signal propagation on a microscale, we delivered electrical stimuli intracellularly to individual cells while simultaneously recording the extracellular potentials at different locations in a rat brain slice. As compared with relatively unobstructed paths, signals were attenuated across frequencies when fiber bundles were in between the stimulated cell and the extracellular electrode. Across group of cell bodies, signals were attenuated at low frequencies, but facilitated at high frequencies. These results show that LFPs do not reflect a democratic representation of neuronal contributions, as certain neurons may contribute to the LFP more than others based on the local extracellular environment surrounding them.