Local Field Potential Power Research Articles

Cardiac Arrest-Induced Global Brain Hypoxia-Ischemia during Development Affects Spontaneous Activity Organization in Rat Sensory and Motor Thalamocortical Circuits during Adulthood.

Normal maturation of sensory information processing in the cortex requires patterned synaptic activity during developmentally regulated critical periods. During early development, spontaneous synaptic activity establishes required patterns of synaptic input, and during later development it influences patterns of sensory experience-dependent neuronal firing. Thalamocortical neurons occupy a critical position in regulating the flow of patterned sensory information from the periphery to the cortex. Abnormal thalamocortical inputs may permanently affect the organization and function of cortical neuronal circuits, especially if they occur during a critical developmental window. We examined the effect of cardiac arrest (CA)-associated global brain hypoxia-ischemia in developing rats on spontaneous and evoked firing of somatosensory thalamocortical neurons and on large-scale correlations in the motor thalamocortical circuit. The mean spontaneous and sensory-evoked firing rate activity and variability were higher in CA injured rats. Furthermore, spontaneous and sensory-evoked activity and variability were correlated in uninjured rats, but not correlated in neurons from CA rats. Abnormal activity patterns of ventroposterior medial nucleus (VPm) neurons persisted into adulthood. Additionally, we found that neurons in the entopeduncular nucleus (EPN) in the basal ganglia had lower firing rates yet had higher variability and higher levels of burst firing after injury. Correlated levels of power in local field potentials (LFPs) between the EPN and the motor cortex (MCx) were also disrupted by injury. Our findings indicate that hypoxic-ischemic injury during development leads to abnormal spontaneous and sensory stimulus-evoked input patterns from thalamus to cortex. Abnormal thalamic inputs likely permanently and detrimentally affect the organization of cortical circuitry and processing of sensory information. Hypoxic-ischemic injury also leads to abnormal single neuron and population level activity in the basal ganglia that may contribute to motor dysfunction after injury. Combination of deficits in sensory and motor thalamocortical circuit function may negatively impact sensorimotor integration in CA survivors. Modulation of abnormal activity patterns post-injury may represent a novel therapeutic target to improve neurologic function in survivors.

Effect of l-DOPA on local field potential relationship between the pedunculopontine nucleus and primary motor cortex in a rat model of Parkinson’s disease

Levodopa (l-DOPA) has been proved to reverse the pathologic neuron activities in many brain regions related to Parkinson’s disease (PD). But little is known about the effect of l-DOPA on the altered electrophysiological coherent activities between pedunculopontine nucleus (PPN) and motor cortex. To investigate this, local field potentials (LFPs) of PPN and primary motor cortex (M1) were recorded simultaneously in control, 6-hydroxydopamine lesioned and lesioned rats with l-DOPA chronic treatment. The results revealed that in resting state, chronic l-DOPA treatment could correct the suppressed power of LFPs in PPN and M1 in low-frequency band (1–7Hz) and the enhanced power in high-frequency band (7–70Hz in PPN and 12–70Hz in M1) of lesioned rats. In locomotor state, l-DOPA treatment could correct the alterations in most of frequency bands except the δ band in PPN and α band in M1. Moreover, l-DOPA could also reverse the altered coherent relationships caused by dopamine depletion in resting state between PPN and M1 in β band. And in locomotor state, l-DOPA had therapeutic effect on the alterations in δ and β bands but not in the α band. These findings provide evidence that l-DOPA can reverse the altered LFP activities in PPN and M1 and their relationships in a rat model of PD, which contributes to better understanding the electrophysiological mechanisms of the pathophysiology and therapy of PD.

EP 48. Local field potential oscillations of the globus pallidus in cervical and tardive dystonia

Reports about neural oscillatory activity in the globus pallidus internus (GPi) have targeted general (GD) and cervical (CD) dystonia, however they are nonexistent for tardive dystonia (TD). Sensory tricks (geste antagoniste) emphasize a role of sensory processing in CD rather than TD, however neural oscillatory correlates of that phenomenon have not been investigated. Here, we recorded local field potentials (LFPs) from seven CD and five TD patients intraoperatively. We compared LFP power in thetadelta, alpha and beta band during rest and sensory palmar stimulation (SPS) in patients with general anesthesia and local/analgo sedation. We found prominent thetadelta power activity in both CD and TD. Unlike TD, a significant difference between rest and SPS was revealed for CD. Our data support the presence of LFP oscillatory activity in CD and TD, while emphasizing thetadelta modulation of LFP power in CD as a putative signature of sensory tricks.

SP 4. Distribution of oscillatory activities in MRI confirmed subthalamic nucleus subregions

Objective To explore the differences and similarities of oscillatory activity between subregions of the subthalamic nucleus (STN). Background In Parkinson’s disease (PD), treatment driven changes in bradykinesia and rigidity are associated with changes in exaggerated local field potential (LFP) beta (13–30 Hz) power. The power of these oscillations has recently successfully been applied as a biomarker for adaptive deep brain stimulation. However, it is not yet known where in the STN beta can be best recorded, and it remains unclear whether this activity correlates with OFF-state impairment, as opposed to changes in impairment with treatment. Methods In 39 patients with advanced PD who underwent MRI-guided and MRI-verified STN DBS surgery, 229 bipolar LFP’s were recorded in the postoperative week in the OFF dopaminergic state during rest. The location of the electrode in the visualized STN was divided into 5 subregions: superior, dorsolateral, central, anteromedial and inferior. LFP power spectra were obtained by using fast Fourier transformations and were sequentially normalised, log-transformed and divided into alpha (8–13 Hz) and beta band power. Results 95 (41%) of the LFP’s contacts had one or more contacts in the inferior part of the STN. For the anteromedial, central, dorsolateral and superior part of the STN these numbers were 15 (7%), 112 (49%), 66 (29%) and 92 (40%), respectively (Fig. 1). Maximum LFP beta power showed a significant correlation (r = 0.40, p < 0.0005) with the pre-operative assessment of contra-lateral bradykinesia and rigidity (Fig. 2). This was not the case for maximum alpha peak power (r = 0.03, p = 0.89). Beta peak power (33 ± 38%) was significantly (Z = 7.89, p < 0.0001) higher than alpha peak (6 ± 10%) power. Neither activity predominated in one or more STN subregions (for beta Chi-sq4,,370 = 6.01, p = 0.19, for alpha Chi-sq4,,370 = 5.83, p = 0.21) Conclusions Normalised LFP beta power is robustly correlated with contra-lateral bradykinesia and rigidity but is not limited to the presumed dorsolateral STN.

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Active subthreshold dendritic conductances shape the local field potential.

Key points The local field potential (LFP), the low‐frequency part of extracellular potentials recorded in neural tissue, is often used for probing neural circuit activity. Interpreting the LFP signal is difficult, however.While the cortical LFP is thought mainly to reflect synaptic inputs onto pyramidal neurons, little is known about the role of the various subthreshold active conductances in shaping the LFP.By means of biophysical modelling we obtain a comprehensive qualitative understanding of how the LFP generated by a single pyramidal neuron depends on the type and spatial distribution of active subthreshold currents.For pyramidal neurons, the h‐type channels probably play a key role and can cause a distinct resonance in the LFP power spectrum.Our results show that the LFP signal can give information about the active properties of neurons and imply that preferred frequencies in the LFP can result from those cellular properties instead of, for example, network dynamics. The main contribution to the local field potential (LFP) is thought to stem from synaptic input to neurons and the ensuing subthreshold dendritic processing. The role of active dendritic conductances in shaping the LFP has received little attention, even though such ion channels are known to affect the subthreshold neuron dynamics. Here we used a modelling approach to investigate the effects of subthreshold dendritic conductances on the LFP. Using a biophysically detailed, experimentally constrained model of a cortical pyramidal neuron, we identified conditions under which subthreshold active conductances are a major factor in shaping the LFP. We found that, in particular, the hyperpolarization‐activated inward current, I h, can have a sizable effect and cause a resonance in the LFP power spectral density. To get a general, qualitative understanding of how any subthreshold active dendritic conductance and its cellular distribution can affect the LFP, we next performed a systematic study with a simplified model. We found that the effect on the LFP is most pronounced when (1) the synaptic drive to the cell is asymmetrically distributed (i.e. either basal or apical), (2) the active conductances are distributed non‐uniformly with the highest channel densities near the synaptic input and (3) when the LFP is measured at the opposite pole of the cell relative to the synaptic input. In summary, we show that subthreshold active conductances can be strongly reflected in LFP signals, opening up the possibility that the LFP can be used to characterize the properties and cellular distributions of active conductances.

Activation of D2 autoreceptors alters cocaine-induced locomotion and slows down local field oscillations in the rat ventral tegmental area

Psychoactive substances affecting the dopaminergic system induce locomotor activation and, in high doses, stereotypies. Network mechanisms underlying the shift from an active goal-directed behavior to a “seemingly purposeless” stereotypic locomotion remain unclear. In the present study we sought to determine the relationships between the behavioral effects of dopaminergic drugs and their effects on local field potentials (LFPs), which were telemetrically recorded within the ventral tegmental area (VTA) of freely moving rats. We used the D2/D3 agonist quinpirole in a low, autoreceptor-selective (0.1 mg/kg, i.p.) and in a high (0.5 mg/kg, i.p.) dose, and a moderate dose of cocaine (10 mg/kg, i.p.). In the control group, power spectrum analysis revealed a prominent peak of LFP power in the theta frequency range during active exploration. Cocaine alone stimulated locomotion, but had no significant effect on the peak of the LFP power. In contrast, co-administration of low dose quinpirole with cocaine markedly altered the pattern of locomotion, from goal-directed exploratory behavior to recurrent motion resembling locomotor stereotypy. This behavioral effect was accompanied by a shift of the dominant theta power toward a significantly lower (by ∼15%) frequency. High dose quinpirole also provoked an increased locomotor activity with signs of behavioral stereotypies, and also induced a shift of the dominant oscillation frequency toward the lower range. These results demonstrate a correlation between the LFP oscillation frequency within the VTA and a qualitative aspect of locomotor behavior, perhaps due to a variable level of coherence of this region with its input or output areas.

Effects of Arc/Arg3.1 gene deletion on rhythmic synchronization of hippocampal CA1 neurons during locomotor activity and sleep

The activity-regulated cytoskeletal-associated protein/activity regulated gene (Arc/Arg3.1) is crucial for long-term synaptic plasticity and memory formation. However, the neurophysiological substrates of memory deficits occurring in the absence of Arc/Arg3.1 are unknown. We compared hippocampal CA1 single-unit and local field potential (LFP) activity in Arc/Arg3.1 knockout and wild-type mice during track running and flanking sleep periods. Locomotor activity, basic firing and spatial coding properties of CA1 cells in knockout mice were not different from wild-type mice. During active behavior, however, knockout animals showed a significantly shifted balance in LFP power, with a relative loss in high-frequency (beta-2 and gamma) bands compared to low-frequency bands. Moreover, during track-running, knockout mice showed a decrease in phase locking of spiking activity to LFP oscillations in theta, beta and gamma bands. Sleep architecture in knockout mice was not grossly abnormal. Sharp-wave ripples, which have been associated with memory consolidation and replay, showed only minor differences in dynamics and amplitude. Altogether, these findings suggest that Arc/Arg3.1 effects on memory formation are not only manifested at the level of molecular pathways regulating synaptic plasticity, but also at the systems level. The disrupted power balance in theta, beta and gamma rhythmicity and concomitant loss of spike-field phase locking may affect memory encoding during initial storage and memory consolidation stages.

Altered neuronal activity in the pedunculopontine nucleus: An electrophysiological study in a rat model of Parkinson’s disease

The pedunculopontine nucleus (PPN) is a new deep brain stimulation target for treating Parkinson’s disease (PD). But the alterations of the PPN electrophysiological activities in PD are still debated. To investigate these potential alterations, extracellular single unit and local field potential (LFP) activities in the PPN were recorded in unilateral hemispheric 6-hydroxydopamine (6-OHDA) lesioned rats and in control rats, respectively. The spike activity results revealed two types of neurons (Type I and Type II) with distinct electrophysiological characteristics in the PPN. Both types of neurons had increased firing rate and changed firing pattern in lesioned rats when compared to control rats. Specifically, Type II neurons showed an increased firing rate when the rat state was switched from rest to locomotion. The LFP results demonstrated that lesioned rats had lower LFP power at 0.7–12Hz and higher power at 12–30Hz than did control animals in either resting or locomotor state. These findings provide a better understanding of the effects of 6-OHDA lesion on neuronal activities in the PPN and also provide a proof of the link between this structure and locomotion, which contributes to better understanding the mechanisms of the PPN functioning in the pathophysiology of PD.

Phase Locking of Multiple Single Neurons to the Local Field Potential in Cat V1.

The local field potential (LFP) is thought to reflect a temporal reference for neuronal spiking, which may facilitate information coding and orchestrate the communication between neural populations. To explore this proposed role, we recorded the LFP and simultaneously the spike activity of one to three nearby neurons in V1 of anesthetized cats during the presentation of drifting sinusoidal gratings, binary dense noise stimuli, and natural movies. In all stimulus conditions and during spontaneous activity, the average LFP power at frequencies >20 Hz was higher when neurons were spiking versus not spiking. The spikes were weakly but significantly phase locked to all frequencies of the LFP. The average spike phase of the LFP was stable across high and low levels of LFP power, but the strength of phase locking at low frequencies (≤10 Hz) increased with increasing LFP power. In a next step, we studied how strong stimulus responses of single neurons are reflected in the LFP and the LFP-spike relationship. We found that LFP power was slightly increased and phase locking was slightly stronger during strong compared with weak stimulus-locked responses. In summary, the coupling strength between high frequencies of the LFP and spikes was not strongly modulated by LFP power, which is thought to reflect spiking synchrony, nor was it strongly influenced by how strongly the neuron was driven by the stimulus. Furthermore, a comparison between neighboring neurons showed no clustering of preferred LFP phase. We argue that hypotheses on the relevance of phase locking in their current form are inconsistent with our findings.

Subthalamic local field potentials in Parkinson's disease and isolated dystonia: An evaluation of potential biomarkers

Local field potentials (LFP) recorded from the subthalamic nucleus in patients with Parkinson's disease (PD) demonstrate prominent oscillations in the beta (13–30Hz) frequency range, and reduction of beta band spectral power by levodopa and deep brain stimulation (DBS) is correlated with motor symptom improvement. Several features of beta activity have been theorized to be specific biomarkers of the parkinsonian state, though these have rarely been studied in non-parkinsonian conditions. To compare resting state LFP features in PD and isolated dystonia and evaluate disease-specific biomarkers, we recorded subthalamic LFPs from 28 akinetic-rigid PD and 12 isolated dystonia patients during awake DBS implantation. Spectral power and phase-amplitude coupling characteristics were analyzed. In 26/28 PD and 11/12 isolated dystonia patients, the LFP power spectrum had a peak in the beta frequency range, with similar amplitudes between groups. Resting state power did not differ between groups in the theta (5–8Hz), alpha (8–12Hz), beta (13–30Hz), broadband gamma (50–200Hz), or high frequency oscillation (HFO, 250–350Hz) bands. Analysis of phase-amplitude coupling between low frequency phase and HFO amplitude revealed significant interactions in 19/28 PD and 6/12 dystonia recordings without significant differences in maximal coupling or preferred phase. Two features of subthalamic LFPs that have been proposed as specific parkinsonian biomarkers, beta power and coupling of beta phase to HFO amplitude, were also present in isolated dystonia, including focal dystonias. This casts doubt on the utility of these metrics as disease-specific diagnostic biomarkers.

Simultaneous recording of brain extracellular glucose, spike and local field potential in real time using an implantable microelectrode array with nano-materials

Glucose is the main substrate for neurons in the central nervous system. In order to efficiently characterize the brain glucose mechanism, it is desirable to determine the extracellular glucose dynamics as well as the corresponding neuroelectrical activity in vivo. In the present study, we fabricated an implantable microelectrode array (MEA) probe composed of platinum electrochemical and electrophysiology microelectrodes by standard micro electromechanical system (MEMS) processes. The MEA probe was modified with nano-materials and implanted in a urethane-anesthetized rat for simultaneous recording of striatal extracellular glucose, local field potential (LFP) and spike on the same spatiotemporal scale when the rat was in normoglycemia, hypoglycemia and hyperglycemia. During these dual-mode recordings, we observed that increase of extracellular glucose enhanced the LFP power and spike firing rate, while decrease of glucose had an opposite effect. This dual mode MEA probe is capable of examining specific spatiotemporal relationships between electrical and chemical signaling in the brain, which will contribute significantly to improve our understanding of the neuron physiology.

Local field potential power of subthalamic nucleus in human brain is not related to scalp EEG topography dynamics in rest

Objective Subthalamic nucleus (STN) is known to have central position in basal ganglia-thalamocortical circuits. Subthalamo-cortical interactions, however, are not precisely known yet. While intracranial EEG directly explores STN, scalp EEG informs about dynamics of cortical activity, which in rest displays discrete periods of electrical stability-functional microstates. To assess subthalamo-cortical relationship, we analyzed STN and scalp EEG signals. Methods Simultaneous scalp (51–60 electrodes) and intracranial (from STNs) EEG was obtained from four Parkinson disease patients in rest. Topographic analysis was conducted to identify microstate dynamics. Correlations between scalp and STN signals were calculated. Results Time course of mean scalp power significantly correlated with that of local field potential power of both STNs (STN-LFP power) in delta, theta, alpha, beta, gamma, and 1–40 Hz frequency bands in all subjects ( r -value from 0.07 to 0.72). Microstate analysis identified typical four scalp topographies in all subjects. No correlations were found between time course of spatial correlation coefficients of template topographic maps and that of STN-LFP power in any frequency band ( r -value Conclusion While STN-LFP power was related to scalp EEG power in rest, it was not related to occurrence of scalp topographies. Key message Although maybe related to cortical activity, STN activity might not be related to occurrence of microstates.

Noninvasive transcranial focused ultrasonic-magnetic stimulation for modulating brain oscillatory activity

A novel technique, transcranial focused ultrasonic-magnetic stimulation (tFUMS), has been developed for noninvasive brain modulation in vivo. tFUMS has a higher spatial resolution (<2 mm) and a higher penetration depth than other noninvasive neuromodulation methods. The in vivo animal experimental results show that tFUMS can not only increase the power of local field potentials and the firing rate of the neurons, but also enhance the effect of transcranial focused ultrasound stimulation on the neuromodulation. The results demonstrate that tFUMS can modulate brain oscillatory activities by stimulating brain tissues.

On the photovoltaic effect in local field potential recordings.

Optogenetics allows light activation of genetically defined cell populations and the study of their link to specific brain functions. While it is a powerful method that has revolutionized neuroscience in the last decade, the shortcomings of directly stimulating electrodes and living tissue with light have been poorly characterized. Here, we assessed the photovoltaic effects in local field potential (LFP) recordings of the mouse hippocampus. We found that light leads to several artifacts that resemble genuine LFP features in animals with no opsin expression, such as stereotyped peaks at the power spectrum, phase shifts across different recording channels, coupling between low and high oscillation frequencies, and sharp signal deflections that are detected as spikes. Further, we tested how light stimulation affected hippocampal LFP recordings in mice expressing channelrhodopsin 2 in parvalbumin neurons (PV/ChR2 mice). Genuine oscillatory activity at the frequency of light stimulation could not be separated from light-induced artifacts. In addition, light stimulation in PV/ChR2 mice led to an overall decrease in LFP power. Thus, genuine LFP changes caused by the stimulation of specific cell populations may be intermingled with spurious changes caused by photovoltaic effects. Our data suggest that care should be taken in the interpretation of electrophysiology experiments involving light stimulation.

Electrophoretic deposition of ligand-free platinum nanoparticles on neural electrodes affects their impedance in vitro and in vivo with no negative effect on reactive gliosis.

BackgroundElectrodes for neural stimulation and recording are used for the treatment of neurological disorders. Their features critically depend on impedance and interaction with brain tissue. The effect of surface modification on electrode impedance was examined in vitro and in vivo after intracranial implantation in rats. Electrodes coated by electrophoretic deposition with platinum nanoparticles (NP; <10 and 50 nm) as well as uncoated references were implanted into the rat’s subthalamic nucleus. After postoperative recovery, rats were electrostimulated for 3 weeks. Impedance was measured before implantation, after recovery and then weekly during stimulation. Finally, local field potential was recorded and tissue-to-implant reaction was immunohistochemically studied.ResultsCoating with NP significantly increased electrode’s impedance in vitro. Postoperatively, the impedance of all electrodes was temporarily further increased. This effect was lowest for the electrodes coated with particles <10 nm, which also showed the most stable impedance dynamics during stimulation for 3 weeks and the lowest total power of local field potential during neuronal activity recording. Histological analysis revealed that NP-coating did not affect glial reactions or neural cell-count.ConclusionsCoating with NP <10 nm may improve electrode’s impedance stability without affecting biocompatibility. Increased impedance after NP-coating may improve neural recording due to better signal-to-noise ratio.

Repetition suppression for visual actions in the macaque superior temporal sulcus

In many brain areas, repetition of a stimulus usually weakens the neural response. This "adaptation" or repetition suppression effect has been observed with mass potential measures such as event-related potentials (ERPs), in fMRI BOLD responses, and locally with local field potentials (LFPs) and spiking activity. Recently, it has been reported that macaque F5 mirror neurons do not show repetition suppression of their spiking activity for single repetitions of hand actions, which disagrees with human fMRI adaptation studies. This finding also contrasts with numerous studies showing repetition suppression in macaque inferior temporal cortex, including the rostral superior temporal sulcus (STS). Since the latter studies employed static stimuli, we assessed here whether the use of dynamic action stimuli abolishes repetition suppression in the awake macaque STS. To assess adaptation effects in the STS, we employed the same hand action movies as used when examining adaptation in F5. The upper bank STS neurons showed repetition suppression during the approaching phase of the hand action, which corresponded to the phase of the action for which these neurons responded overall the strongest. The repetition suppression was present for the spiking activity measured in independent single-unit and multiunit recordings as well as for the LFP power at frequencies > 50 Hz. Together with previous data in F5, these findings suggest that adaptation effects differ between F5 mirror neurons and the STS neurons.

Attention Decreases Phase-Amplitude Coupling, Enhancing Stimulus Discriminability in Cortical Area MT.

Local field potentials (LFPs) in cortex reflect synchronous fluctuations in the synaptic activity of local populations of neurons. The power of high frequency (>30 Hz) oscillations in LFPs is locked to the phase of low frequency (<30 Hz) oscillations, an effect known as phase-amplitude coupling (PAC). While PAC has been observed in a variety of cortical regions and animal models, its functional role particularly in primate visual cortex is largely unknown. Here, we document PAC for LFPs recorded from extra-striate area MT of macaque monkeys, an area specialized for the processing of visual motion. We further show that directing spatial attention into the receptive field of MT neurons decreases the coupling between the low frequency phase and high frequency power of LFPs. This attentional suppression of PAC increases neuronal discriminability for attended visual stimuli. Therefore, we hypothesize that visual cortex uses PAC to regulate inter-neuronal correlations and thereby enhances the coding of relevant stimuli.

Frequency-Dependent Representation of Reinforcement-Related Information in the Human Medial and Lateral Prefrontal Cortex.

The feedback-related negativity (FRN) is a commonly observed potential in scalp electroencephalography (EEG) studies related to the valence of feedback about a subject's performance. This potential classically manifests as a negative deflection in medial frontocentral EEG contacts following negative feedback. Recent work has shown prominence of theta power in the spectral composition of the FRN, placing it within the larger class of "frontal midline theta" cognitive control signals. Although the dorsal anterior cingulate cortex (dACC) is thought to be the cortical generator of the FRN, conclusive data regarding its origin and propagation are lacking. Here we examine intracranial electrophysiology from the human medial and lateral prefrontal cortex (PFC) to better understand the anatomical localization and communication patterns of the FRN. We show that the FRN is evident in both low- and high-frequency local field potentials (LFPs) recorded on electrocorticography. The FRN is larger in medial compared with lateral PFC, and coupling between theta band phase and high-frequency LFP power is also greater in medial PFC. Using Granger causality and conditional mutual information analyses, we provide evidence that feedback-related information propagates from medial to lateral PFC, and that this information transfer oscillates with theta-range periodicity. These results provide evidence for the dACC as the cortical source of the FRN, provide insight into the local computation of frontal midline theta, and have implications for reinforcement learning models of cognitive control.

Spiking network modeling of neuronal dynamics in individual rats

Many researchers base their neuronal models on experimental data, but few systematically calibrate to it, and even fewer use unpooled data from multiple subjects. Some (partial) exceptions are [1], where one model parameter was calibrated to data pooled across four macaques; and [2], where five model parameters were calibrated to unpooled data from 292 humans. To our knowledge, no one has previously calibrated spiking network models to individual subjects - likely because a single model iteration typically takes considerable computational time, compounded by the formidable number of iterations required to perform optimizations on a statistically meaningful number of subjects. In this study, we calibrate and validate a mesoscopic spiking network model against data from individual rats, then use these fits to infer differences in the rats' physiologies. We recorded data from microelectrode arrays implanted in the somatosensory cortices of nine male rats, each of whom received touch stimuli to his left forepaw. The spiking network models consisted of 20,000 Izhikevich neurons, representing a 2x2 mm patch of cortex sampled at approximately 10% true cell density, with cell types (15 across six layers) and connectivities based on empirical data. We calibrated key model parameters (including connection probability and weight, tonic background activity, and the ratio of thalamic to cortical input) to experimental data (including average firing rates and coefficients of variation) using a nonlinear optimization algorithm [3]. The calibrations were validated using the exponents of the local field potential (LFP) power spectra from 5-50 Hz, which were not used for calibration. Changes in the information processing properties of the (simulated) networks were then quantified via interlaminar Granger causality. Experimentally, we found large differences between subjects. Cortical firing rates varied from 3.8 Hz to 19.6 Hz (median 11.9 Hz); coefficients of variation, 0.4 to 1.2 (median 0.9); and peristimulus time histogram peak amplitudes, 48 Hz to 73 Hz (median 62 Hz). Inter-subject differences were significantly greater than intra-subject differences across both sessions and electrodes. The calibrated models reproduced experimental data with an average mismatch of 16%, compared to 30% when uncalibrated. Experimentally, the LFP power spectra exponents varied from -1.4 to -2.7 (median -2.2). While the models had uniformly steeper exponents (range -2.8 to -3.6), calibration reduced mismatch in eight of the nine subjects. Inter-subject differences could be largely accounted for by differences in average synaptic connection probability (which varied by a mean of 24% between subjects, compared to <8% for other fitted parameters). Parameter differences produced changes in how these networks process information - for example, there were significant and complex differences in the patterns of interlaminar information flow between subjects, including reversals in the dominant direction of information flow for some layer pairs. In summary, we found that (1) significant differences exist between individual subjects, (2) these differences can be captured by calibrating spiking network models to data from each individual, and (3) modeling suggests that these differences affect how individuals process information across cortical layers.