Intracortical Local Field Potentials Research Articles

Nerve Injury Decreases Hyperacute Resting-State Connectivity Between the Anterior Cingulate and Primary Somatosensory Cortex in Anesthetized Rats.

A better understanding of neural pain processing and of the development of pain over time, is critical to identify objective measures of pain and to evaluate the effect of pain alleviation therapies. One issue is, that the brain areas known to be related to pain processing are not exclusively responding to painful stimuli, and the neuronal activity is also influenced by other brain areas. Functional connectivity reflects synchrony or covariation of activation between groups of neurons. Previous studies found changes in connectivity days or weeks after pain induction. However, less in known on the temporal development of pain. Our objective was therefore to investigate the interaction between the anterior cingulate cortex (ACC) and primary somatosensory cortex (SI) in the hyperacute (minute) and sustained (hours) response in an animal model of neuropathic pain. Intra-cortical local field potentials (LFP) were recorded in 18 rats. In 10 rats the spared nerve injury model was used as an intervention. The intra-cortical activity was recorded before, immediately after, and three hours after the intervention. The interaction was quantified as the calculated correlation and coherence. The results from the intervention group showed a decrease in correlation between ACC and SI activity, which was most pronounced in the hyperacute phase but a longer time frame may be required for plastic changes to occur. This indicated that both SI and ACC are involved in hyperacute pain processing.

Chapter 20 - Local field potentials for BCI control

The gold standard in brain-computer interface (BCI) modalities is multi single-unit recordings in the primary motor cortex. It yields the fastest and most elegant control (i.e., most degrees of freedom and bitrate). Unfortunately, single-unit electrodes are prone to encapsulation, which limit their single-unit recording life. However, encapsulation does not significantly affect intracortical local field potentials (LFPs). LFPs and single-unit activity were recorded from the motor cortices of three monkeys (Macaca fascicularis) while they performed a standard 3D center-out reaching task and a 3D circle-drawing task. The high frequency (HF) (60-200 Hz) spectral amplitudes of a subset of the LFPs were found to be directionally tuned much like single units. In fact, stable isolation of single units on the same electrode increased the likelihood that the HF-LFP would be significantly cosine tuned to hand direction. The presence of significantly tuned single units further increased the likelihood of a tuned HF-LFP, suggesting that this band of HF-LFP activity is at least partially generated by local neuronal action potential currents (i.e., single-unit activity). Given that encapsulation makes recording single units over a long period of time difficult, these results suggest that HF-LFPs may be a more stable and efficient method of monitoring neural activity for BCI applications.

Phase relationship between micro-electrocorticography and cortical neurons

Objective. Electrocorticography (ECoG) is commonly used to map epileptic foci and to implement brain–computer interfaces. Understanding the spatiotemporal correspondence between potentials recorded from the brain’s surface and the firing patterns of neurons within the cortex would inform the interpretation of ECoG signals and the design of (microfabricated) micro-ECoG electrode arrays. Based on the theory that synaptic potentials generated by neurons firing in synchrony superimpose to generate local field potentials (LFPs), we hypothesized that neurons in the cortex would fire at preferential phases of the micro-ECoG signal in a spatially dependent way. Approach. We custom fabricated micro-ECoG electrode arrays with a small opening for silicon arrays (NeuroNexus) to be inserted into the cortex. Main results. We found that the spectral coherence between micro-ECoG signals and intracortical LFPs decreased with distance and frequency, but the coherence with spiking units did not simply decrease over distance, likely due to the structure of the cortex. The majority of sorted units spiked during a preferred phase (usually downward) and frequency (usually below 20 Hz) of the micro-ECoG signal. Their preferred frequency decreased with administration of dexmeditomidine, a sedative commonly used for cortical mapping in patients with epilepsy prior to surgical resection. Dexmedetomidine concomitantly shifted the micro-ECoG spectral density towards lower frequencies. Therefore, the phase relationship between micro-ECoG signals and cortical spiking depends on the state of the brain, and spectrum shifts towards lower frequencies in the electrocorticography signal are a signature of increased spike-phase coupling. However, spike-phase coupling is not a static property since visual stimuli were found to modulate the magnitude of phase coupling at gamma frequency ranges (30–80 Hz), providing empirical evidence that neurons transiently phase-lock. Significance. The phase relationship between intracortical spikes and micro-ECoG signals depends on brain state, site separation, cortical structure, and external stimuli.

Early Detection of Human Epileptic Seizures Based on Intracortical Microelectrode Array Signals.

We examine, for the first time, the use of intracortical microelectrode array (MEA) signals for early detection of human epileptic seizures. 4×4 mm2 96-channel-MEA recordings were obtained during neuro-monitoring preceding resective surgery in five participants. The participant-specific seizure-detection framework consisted of: first, feature extraction from local field potentials (LFPs) and multiunit activity (MUA); second, nonlinear cost-sensitive support vector machine (SVM) classification of ictal and interictal states based on LFP, MUA, and combined LFP-MUA (a SVM was trained for each participant separately); and third, Kalman filter postprocessing of SVM scoring functions. Performance was assessed on data including 17 seizures and 39.0h interictal and preictal recordings. The use of combined LFP-MUA features resulted in 100% sensitivity with short detection latency (average: 2.7 s; median: 2.5 s) and five false alarms (0.13/h). The average detection performance based on the area under the receiver operating characteristic corresponded to 0.97. Importantly, technically false alarms were related to epileptiform activity, subclinical seizures, and recording artifacts. Extreme gradient boosting classifiers ranked features based on LFP spectral coherence or MUA count among the top features for seizures characterized by spike-wave complexes, whereas features related to LFP power spectra were ranked higher for seizures characterized by sustained gamma LFP oscillations. The combination of intracortical LFP and MUA signals may allow reliable detection of human epileptic seizures by improving latency and false alarm rate. Intracortical MEAs provide promising signals for closed-loop seizure-control systems based on seizure early-detection in people with pharmacologically resistant epilepsies.

Directed Interaction Between Monkey Premotor and Posterior Parietal Cortex During Motor-Goal Retrieval from Working Memory.

Goal-directed behavior requires cognitive control of action, putatively by means of frontal-lobe impact on posterior brain areas. We investigated frontoparietal directed interaction (DI) in monkeys during memory-guided rule-based reaches, to test if DI supports motor-goal selection or working memory (WM) processes. We computed DI between the parietal reach region (PRR) and dorsal premotor cortex (PMd) with a Granger-causality measure of intracortical local field potentials (LFP). LFP mostly in the beta (12–32 Hz) and low-frequency ( ranges contributed to DI. During movement withholding, beta-band activity in PRR had a Granger-causal effect on PMd independent of WM content. Complementary, low-frequency PMd activity had a transient Granger-causing effect on PRR specifically during WM retrieval of spatial motor goals, while no DI was associated with preliminary motor-goal selection. Our results support the idea that premotor and posterior parietal cortices interact functionally to achieve cognitive control during goal-directed behavior, in particular, that frontal-to-parietal interaction occurs during retrieval of motor-goal information from spatial WM.

S168 Cortical unit and field activity during sleep cyclicity

Objectives The cortical slow oscillation emerging from the non-rapid eye movement sleep facilitates the long term consolidation of declarative memories, however our knowledge about its neural mechanisms in humans is rather limited. Methods To elucidate the intracortical neuronal mechanisms of slow cortical activity in humans, laminar multichannel microelectrodes were chronically implanted into the cortex of patients with drug resistant focal epilepsy undergoing cortical mapping for seizure focus localization. In addition, similar measurements were taken from acute cortical slices of the patients under in vitro conditions. Results Intracortical laminar local field potential gradient, multiple unit and single unit activities were recorded during slow wave sleep, related to simultaneous electrocorticography, and analyzed with current source density and spectral methods. We have found major supragranular contribution to the total cortical action potential and wide frequency band (10–200 Hz) synaptic/trans-membrane activity accompanied by spatially synchronized and relatively low firing rates. Similar results were obtained from the in vitro studies. Discussion These findings provide evidence that slow cortical activity in humans is characterized by hyperpolarizing currents associated with suppressed firing, alternating with high oscillatory synaptic/trans-membrane activity with increased firing. Our results emphasize the major involvement of supragranular layers. Conclusions The major supragranular activation in humans and the relatively low single firing rates, which has rather synchronous onset across layers are in contrast with results from animal models. Significance Our results indicate that human slow cortical activity may use alternative neuronal mechanisms to accommodate to the demands of higher level cognitive and expanded memory functions.

P370 The thalamo-cortical generators of sleep spindles as revealed by laminar analysis of neocortex

Introduction Sleep spindles are generated in thalamo-cortical networks. Thalamo-cortical projections include core projections to middle and matrix projections to superficial cortical layers. It has been proposed that sleep spindles can be generated in either of these networks. Materials and methods We used electrophysiological data recorded with subdural grid and intracortical multielectrodes in five therapy-resistant epileptic patients undergoing invasive monitoring. Spindles were detected automatically in electrocorticography channels and detection-triggered laminar microelectrode recordings were analyzed. The second spatial derivative of spindle-band filtered (band pass 10–16 Hz, 96 dB) local field potential data allowed to approximate the laminar distribution of the transmembrane generators (current source density, CSD) of spindles. The information regarding the concurrent population cellular activity was obtained by applying a high frequency band filter (500–5000 Hz, 48 dB) on epoched data. Based on the histological reconstructions of laminar electrode tracks, we could identify the precise laminar localization of current sources and sinks. Results Results indicate highly heterogeneous intracortical local field potentials during sleep spindles, and maximum CSD in layer I, II and IV. Multi-unit activity was increased in spindle troughs as it was identified based on the spindle band filtered local field potentials. The single unit analyis revealed preferential firing of most neurons during the positive-negative phase transition of spindles. Conclusions The results confirm that both core and matrix thalamocortical projections contribute to spindle generation, but most spindles appear to be generated by a combination of the two and only a small minority by only one or the other. Neuronal firing tracks the phase of spindles in corticographic channels. Supported by KTIA_NAP_13-1-2013-0001.

Predicting seizures from local field potentials recorded via intracortical microelectrode arrays.

The need for new therapeutic interventions to treat pharmacologically resistant focal epileptic seizures has led recently to the development of closed-loop systems for seizure control. Once a seizure is predicted/detected by the system, electrical stimulation is delivered to prevent seizure initiation or spread. So far, seizure prediction/detection has been limited to tracking non-invasive electroencephalogram (EEG) or intracranial EEG (iEEG) signals. Here, we examine seizure prediction based on local field potentials (LFPs) from a small neocortical patch recorded via a 10×10 microelectrode array implanted in a patient with focal seizures. We formulate the seizure (ictal) prediction problem in terms of discriminating between interictal and preictal neural activity. Using deep Convolutional Neural Networks (CNNs), we show that periods of preictal activity can be successfully discriminated (80% detection; no false positives) from periods of interictal activity several (2-18) minutes prior to seizure onset. CNN input features consisted of the spectral power of LFP channels (1-second time windows) computed in 50 frequency bands (0-100 Hz; 2 Hz steps). Our preliminary results show that intracortical LFPs may be a promising neural signal for seizure prediction in focal epilepsy.

The Primary Visual Cortex Is Differentially Modulated by Stimulus-Driven and Top-Down Attention.

Selective attention can be focused either volitionally, by top-down signals derived from task demands, or automatically, by bottom-up signals from salient stimuli. Because the brain mechanisms that underlie these two attention processes are poorly understood, we recorded local field potentials (LFPs) from primary visual cortical areas of cats as they performed stimulus-driven and anticipatory discrimination tasks. Consistent with our previous observations, in both tasks, we found enhanced beta activity, which we have postulated may serve as an attention carrier. We characterized the functional organization of task-related beta activity by (i) cortical responses (EPs) evoked by electrical stimulation of the optic chiasm and (ii) intracortical LFP correlations. During the anticipatory task, peripheral stimulation that was preceded by high-amplitude beta oscillations evoked large-amplitude EPs compared with EPs that followed low-amplitude beta. In contrast, during the stimulus-driven task, cortical EPs preceded by high-amplitude beta oscillations were, on average, smaller than those preceded by low-amplitude beta. Analysis of the correlations between the different recording sites revealed that beta activation maps were heterogeneous during the bottom-up task and homogeneous for the top-down task. We conclude that bottom-up attention activates cortical visual areas in a mosaic-like pattern, whereas top-down attentional modulation results in spatially homogeneous excitation.

Spatiotemporal Changes of Neuronal Responses in the Primary Somatosensory Cortex to Noxious Tail Stimulation in Awake and Pentobarbital-Anesthetized Rats.

Primary somatosensory cortex (SI) is a key area in the processing of nociceptor inputs to our consciousness. To clarify the columnar and laminar organization of SI for pain processing, we compared spatiotemporal changes in neuronal activities of the primary sensorimotor cortex (SmI) of the rat in response to noxious laser heat stimulation applied to the mid-tail. Longitudinal and vertical array microelectrodes were chronically implanted in the cerebral cortex. Evoked neuronal activities, including intracortical local field potentials (LFP) and ensemble single-unit activity (SU) around SmI were simultaneously recorded. The effect of pentobarbital on the neuronal responses was evaluated in comparison with the neuronal responses in conscious animals to explore the potential substrate of nociceptive processing in the conscious state. The results from the experiment with longitudinal microelectrode arrays indicated that noxious stimulation induced a neuronal response which was spread widely around the SmI of the conscious rat, and the range of neuronal responses was limited to the tail region of the SmI under anesthesia. The results from the experiment with vertical microelectrode arrays showed the universal neuronal responses through all cortical layers of the SmI in conscious rats, and sodium pentobarbital suppressed these neuronal responses in the supragranular layers significantly relative to the deeper layers and basal activity. These results imply that a wider range of cortical activation, both in the horizontal or vertical dimension, might be important for nociceptive processing in the conscious state.

Modulation of the Intracortical LFP during Action Execution and Observation

The activity of mirror neurons in macaque ventral premotor cortex (PMv) and primary motor cortex (M1) is modulated by the observation of another's movements. This modulation could underpin well documented changes in EEG/MEG activity indicating the existence of a mirror neuron system in humans. Because the local field potential (LFP) represents an important link between macaque single neuron and human noninvasive studies, we focused on mirror properties of intracortical LFPs recorded in the PMv and M1 hand regions in two macaques while they reached, grasped and held different objects, or observed the same actions performed by an experimenter. Upper limb EMGs were recorded to control for covert muscle activity during observation.The movement-related potential (MRP), investigated as intracortical low-frequency LFP activity (<9 Hz), was modulated in both M1 and PMv, not only during action execution but also during action observation. Moreover, the temporal LFP modulations during execution and observation were highly correlated in both cortical areas. Beta power in both PMv and M1 was clearly modulated in both conditions. Although the MRP was detected only during dynamic periods of the task (reach/grasp/release), beta decreased during dynamic and increased during static periods (hold).Comparison of LFPs for different grasps provided evidence for partially nonoverlapping networks being active during execution and observation, which might be related to different inputs to motor areas during these conditions. We found substantial information about grasp in the MRP corroborating its suitability for brain-machine interfaces, although information about grasp was generally low during action observation.

Electrophysiological signatures of spontaneous BOLD fluctuations in macaque prefrontal cortex

Spontaneous brain activity is ubiquitous across brain structures and states. Determining the role of these metabolically costly intrinsic events may be critical for understanding the brain's fundamental physiological principles that govern cognition and behavior. To date, most investigations of large-scale fluctuations and their coupling have been conducted using electro- or magneto-encephalography, modalities that are limited in their ability to spatially resolve the origin of the signals. Invasive, electrophysiological local field potential (LFP) recordings are limited in their spatial range and studies combining the approach with functional imaging have been primarily relegated to sensory/motor areas with little basis in which to extrapolate findings to evolutionarily newer prefrontal cortical regions. Here, we acquired spontaneous fMRI data in two anesthetized macaque monkeys (Macaca fascicularis) at 7T together with simultaneous recordings of intracortical LFPs recorded bilaterally from the prefrontal cortex (area 9/46d). High (beta–low gamma) and low (delta–theta) band-limited power (BLP) ranges of the LFP frequencies were anticorrelated in the absence of any explicit stimuli. Beyond the high LFP–BLP signal being correlated with BOLD activity at the recording site, the high and low LFP–BLP envelopes were shown to be significantly correlated with spontaneous BOLD activity recorded from positively and negatively connected prefrontal network regions, respectively. The results suggest that complementary changes in low and high frequency bands may be an intrinsic property of LFPs, that local prefrontal cortical activity is related to spontaneous BOLD fluctuations, and further, that LFP–BLPs may be correlated at a network level.

Effective Connectivity Maps in the Swine Somatosensory Cortex Estimated from Electrocorticography and Validated with Intracortical Local Field Potential Measurements

Macroscopic techniques are increasingly being used to estimate functional connectivity in the brain, which provides valuable information about brain networks. In any such endeavors it is important to understand capabilities and limitations of each technique through direct validation, which is often lacking. This study evaluated a multiple dipole source analysis technique based on electrocorticography (ECOG) data in estimating effective connectivity maps and validated the technique with intracortical local field potential (LFP) recordings. The study was carried out in an animal model (swine) with a large brain to avoid complications caused by spreading of the volume current. The evaluation was carried out for the cortical projections from the trigeminal nerve and corticocortical connectivity from the first rostrum area (R1) in the primary somatosensory cortex. Stimulation of the snout and layer IV of the R1 did not activate all projection areas in each animal, although whenever an area was activated in a given animal, its location was consistent with the intracortical LFP. The two types of connectivity maps based on ECOG analysis were consistent with each other and also with those estimated from the intracortical LFP, although there were small discrepancies. The discrepancies in mean latency based on ECOG and LFP were all very small and nonsignificant: snout stimulation, -1.1-2.0 msec (contralateral hemisphere) and 3.9-8.5 msec (ipsilateral hemisphere); R1 stimulation, -1.4-2.2 msec for the ipsilateral and 0.6-1.4 msec for the contralateral hemisphere. Dipole source analysis based on ECOG appears to be quite useful for estimating effective connectivity maps in the brain.

Spectral factorization-based current source density analysis of ongoing neural oscillations

Current source density (CSD) analysis is widely used in neurophysiological investigations intended to reveal the patterns of localized neuronal activity in terms of current sources and sinks. CSD is based on the second spatial derivatives of multi-electrode electrophysiological recordings, and can be applied to brain activity related to repeated external stimulations (evoked brain activity) or ongoing (spontaneous) brain activity. In evoked brain activity, event-related time-series averages of ensembles are used to compute CSD patterns. However, for ongoing neural activity, the lack of external events requires a different approach other than ensemble averaging. Here, we propose a new spectral factorization-based current source density (SF-CSD) analysis method for ongoing neural oscillations. We validated this new SF-CSD analysis method using simulated data and demonstrated its effectiveness by applying to experimental intra-cortical local field potentials recorded on multi-contact depth electrodes from monkeys performing selective visual attention tasks. The proposed method gives space-unbiased estimates since it does not rely on a reference for CSD calculation in the frequency-domain. The proposed SF-CSD method is expected to be a useful tool for systematic analysis of neural sources and oscillations from multi-site electrophysiological recordings.

Early Detection of Human Epileptic Seizures Based on Intracortical Local Field Potentials.

The unpredictability of re-occurring seizures dramatically impacts the quality of life and autonomy of people with epilepsy. Reliable early seizure detection could open new therapeutic possibilities and thus substantially improve quality of life and autonomy. Though many seizure detection studies have shown the potential of scalp electroencephalogram (EEG) and intracranial EEG (iEEG) signals, reliable early detection of human seizures remains elusive in practice. Here, we examined the use of intracortical local field potentials (LFPs) recorded from 4×4-mm2 96-microelectrode arrays (MEA) for early detection of human epileptic seizures. We adopted a framework consisting of (1) sampling of intracortical LFPs; (2) denoising of LFPs with the Kalman filter; (3) spectral power estimation in specific frequency bands using 1-sec moving time windows; (4) extraction of statistical features, such as the mean, variance, and Fano factor (calculated across channels) of the power in each frequency band; and (5) cost-sensitive support vector machine (SVM) classification of ictal and interictal samples. We tested the framework in one-participant dataset, including 4 seizures and corresponding interictal recordings preceding each seizure. The participant was a 52-year-old woman suffering from complex partial seizures. LFPs were recorded from an MEA implanted in the participant's left middle temporal gyrus. In this participant, spectral power in 0.3-10 Hz, 20-55 Hz, and 125-250 Hz changed significantly between ictal and interictal epochs. The examined seizure detection framework provided an event-wise sensitivity of 100% (4/4) and only one 20-sec-long false positive event in interictal recordings (likely an undetected subclinical event under further visual inspection), and a detection latency of 4.35 ± 2.21 sec (mean ± std) with respect to iEEG-identified seizure onsets. These preliminary results indicate that intracortical MEA recordings may provide key signals to quickly and reliably detect human seizures.

Influence of spiking activity on cortical local field potentials

The intra-cortical local field potential (LFP) reflects a variety of electrophysiological processes including synaptic inputs to neurons and their spiking activity. It is still a common assumption that removing high frequencies, often above 300 Hz, is sufficient to exclude spiking activity from LFP activity prior to analysis. Conclusions based on such supposedly spike-free LFPs can result in false interpretations of neurophysiological processes and erroneous correlations between LFPs and behaviour or spiking activity. Such findings might simply arise from spike contamination rather than from genuine changes in synaptic input activity. Although the subject of recent studies, the extent of LFP contamination by spikes is unclear, and the fundamental problem remains. Using spikes recorded in the motor cortex of the awake monkey, we investigated how different factors, including spike amplitude, duration and firing rate, together with the noise statistic, can determine the extent to which spikes contaminate intra-cortical LFPs. We demonstrate that such contamination is realistic for LFPs with a frequency down to ∼10 Hz. For LFP activity below ∼10 Hz, such as movement-related potential, contamination is theoretically possible but unlikely in real situations. Importantly, LFP frequencies up to the (high-) gamma band can remain unaffected. This study shows that spike–LFP crosstalk in intra-cortical recordings should be assessed for each individual dataset to ensure that conclusions based on LFP analysis are valid. To this end, we introduce a method to detect and to visualise spike contamination, and provide a systematic guide to assess spike contamination of intra-cortical LFPs.

Reconstruction of movement-related intracortical activity from micro-electrocorticogram array signals in monkey primary motor cortex

Subdural electrode arrays provide stable, less invasive electrocorticogram (ECoG) recordings of neural signals than multichannel needle electrodes. Accurate reconstruction of intracortical local field potentials (LFPs) from ECoG signals would provide a critical step for the development of a less invasive, high-performance brain–machine interface; however, neural signals from individual ECoG channels are generally coarse and have limitations in estimating deep layer LFPs. Here, we developed a high-density, 32-channel, micro-ECoG array and applied a sparse linear regression algorithm to reconstruct the LFPs at various depths of primary motor cortex (M1) in a monkey performing a reach-and-grasp task. At 0.2 mm beneath the cortical surface, the real and estimated LFPs were significantly correlated (correlation coefficient (r); 0.66 ± 0.11), and the r at 3.2 mm was still as high as 0.55 ± 0.04. A time-frequency analysis of the reconstructed LFP showed clear transition between resting and movements by the monkey. These methods would be a powerful tool with wide-ranging applicability in neuroscience studies.

EEG Phase Patterns Reflect the Selectivity of Neural Firing

Oscillations are pervasive in encephalographic signals and supposedly reflect cognitive processes and sensory representations. While the relation between oscillation amplitude (power) and sensory-cognitive variables has been extensively studied, recent work reveals that the dynamic oscillation signature (phase pattern) can carry information about such processes to a greater degree than amplitude. To elucidate the neural correlates of oscillatory phase patterns, we compared the stimulus selectivity of neural firing rates and auditory-driven electroencephalogram (EEG) oscillations. We employed the same naturalistic sound stimuli in 2 experiments, one recording scalp EEGs in humans and one recording intracortical local field potentials (LFPs) and single neurons in macaque auditory cortex. Using stimulus decoding techniques, we show that stimulus selective firing patterns imprint on the phase rather than the amplitude of slow (theta band) oscillations in LFPs and EEG. In particular, we find that stimuli which can be discriminated by firing rates can also be discriminated by phase patterns but not by oscillation amplitude and that stimulus-specific phase patterns also persist in the absence of increases of oscillation power. These findings support a neural basis for stimulus selective and entrained EEG phase patterns and reveal a level of interrelation between encephalographic signals and neural firing beyond simple amplitude covariations in both signals.

Origins of 1/f2 scaling in the power spectrum of intracortical local field potential

It has been noted that the power spectrum of intracortical local field potential (LFP) often scales as 1/f(-2). It is thought that LFP mostly represents the spiking-related neuronal activity such as synaptic currents and spikes in the vicinity of the recording electrode, but no 1/f(2) scaling is detected in the spike power. Although tissue filtering or modulation of spiking activity by UP and DOWN states could account for the observed LFP scaling, there is no consensus as to how it arises. We addressed this question by recording simultaneously LFP and single neurons ("single units") from multiple sites in somatosensory cortex of anesthetized rats. Single-unit data revealed the presence of periods of high activity, presumably corresponding to the "UP" states when the neuronal membrane potential is depolarized, and periods of no activity, the putative "DOWN" states when the membrane potential is close to resting. As expected, the LFP power scaled as 1/f(2) but no such scaling was found in the power spectrum of spiking activity. Our analysis showed that 1/f(2) scaling in the LFP power spectrum was largely generated by the steplike transitions between UP and DOWN states. The shape of the LFP signal during these transitions, but not the transition timing, was crucial to obtain the observed scaling. These transitions were probably induced by synchronous changes in the membrane potential across neurons. We conclude that a 1/f(2) scaling in the LFP power indicates the presence of steplike transitions in the LFP trace and says little about the statistical properties of the associated neuronal firing.

Simultaneous recording of ECoG and intracortical neuronal activity using a flexible multichannel electrode-mesh in visual cortex

Electrocorticogram (ECoG) is a well-balanced methodology for stably mapping brain surface local field potentials (LFPs) over a wide cortical region with high signal fidelity and minimal invasiveness to the brain tissue. To directly compare surface ECoG signals with intracortical neuronal activity immediately underneath, we fabricated a flexible multichannel electrode array with mesh-form structure using micro-electro-mechanical systems. A Parylene-C-based “electrode-mesh” for rats contained a 6×6 gold electrode array with 1-mm interval. Specifically, the probe had 800×800μm2 fenestrae in interelectrode spaces, through which simultaneous penetration of microelectrode was capable. This electrode-mesh was placed acutely or chronically on the dural/pial surface of the visual cortex of Long–Evans rats for up to 2weeks. We obtained reliable trial-wise profiles of visually evoked ECoG signals through individual eye stimulation. Visually evoked ECoG signals from the electrode-mesh exhibited as well or larger signal amplitudes as intracortical LFPs and less across-trial variability than conventional silver-ball ECoG. Ocular selectivity of ECoG responses was correlated with that of intracortical spike/LFP activities. Moreover, single-trial ECoG signals carried sufficient information for predicting the stimulated eye with a correct performance approaching 90%, and the decoding was significantly generalized across sessions over 6hours. Electrode impedance or signal quality did not obviously deteriorate for 2weeks following implantation. These findings open up a methodology to directly explore ECoG signals with reference to intracortical neuronal sources and would provide a key to developing minimally invasive next-generation brain–machine interfaces.