LFP publications

The brain is a highly organized, dynamic system whose network architecture is often assessed through resting functional magnetic resonance imaging (fMRI) functional connectivity. The functional interactions between brain areas, including those observed during rest, are assumed to stem from the collective influence of action potentials carried by long-range neural projections. However, the contribution of individual neurons to brain-wide functional connectivity has not been systematically assessed. Here we developed a method to concurrently measure and compare the spiking activity of local neurons with fMRI signals measured across the brain during rest. We recorded spontaneous activity from neural populations in cortical face patches in the macaque during fMRI scanning sessions. Individual cells exhibited prominent, bilateral coupling with fMRI fluctuations in a restricted set of cortical areas inside and outside the face patch network, partially matching the pattern of known anatomical projections. Within each face patch population, a subset of neurons was positively coupled with the face patch network and another was negatively coupled. The same cells showed inverse correlations with distinct subcortical structures, most notably the lateral geniculate nucleus and brainstem neuromodulatory centers. Corresponding connectivity maps derived from fMRI seeds and local field potentials differed from the single unit maps, particularly in subcortical areas. Together, the results demonstrate that the spiking fluctuations of neurons are selectively coupled with discrete brain regions, with the coupling governed in part by anatomical network connections and in part by indirect neuromodulatory pathways.

The primate amygdala is a complex consisting of over a dozen nuclei that have been implicated in a host of cognitive functions, individual differences, and psychiatric illnesses. These functions are implemented through distinct connectivity profiles, which have been documented in animals but remain largely unknown in humans. Here we present results from 25 neurosurgical patients who had concurrent electrical stimulation of the amygdala with intracranial electroencephalography (electrical stimulation tract-tracing; es-TT), or fMRI (electrical stimulation fMRI; es-fMRI), methods providing strong inferences about effective connectivity of amygdala subdivisions with the rest of the brain. We quantified functional connectivity with medial and lateral amygdala, the temporal order of these connections on the timescale of milliseconds, and also detail second-order effective connectivity among the key nodes. These findings provide a uniquely detailed characterization of human amygdala functional connectivity that will inform functional neuroimaging studies in healthy and clinical populations.

Animals can capitalize on invariance in the environment by learning and automating highly consistent actions; however, they must also remain flexible and adapt to environmental changes. It remains unclear how primary motor cortex (M1) can drive precise movements, yet also support behavioral exploration when faced with consistent errors. Using a reach-to-grasp task in rats, along with simultaneous electrophysiological monitoring in M1 and dorsolateral striatum (DLS), we find that behavioral exploration to overcome consistent task errors is closely associated with tandem increases in M1 and DLS neural variability; subsequently, consistent ensemble patterning returns with convergence to a new successful strategy. We also show that compared to reliably patterned intracranial microstimulation in M1, variable stimulation patterns result in significantly greater movement variability. Our results thus indicate that motor and striatal areas can flexibly transition between two modes, reliable neural pattern generation for automatic and precise movements versus variable neural patterning for behavioral exploration.

Background To localize sound sources accurately in a reverberant environment, human binaural hearing strongly favors analyzing the initial wave front of sounds. Behavioral studies of this “precedence effect” have so far largely been confined to human subjects, limiting the scope of complementary physiological approaches. Similarly, physiological studies have mostly looked at neural responses in the inferior colliculus, the main relay point between the inner ear and the auditory cortex, or used modeling of cochlear auditory transduction in an attempt to identify likely underlying mechanisms. Studies capable of providing a direct comparison of neural coding and behavioral measures of sound localization under the precedence effect are lacking. Results We adapted a “temporal weighting function” paradigm previously developed to quantify the precedence effect in human for use in laboratory rats. The animals learned to lateralize click trains in which each click in the train had a different interaural time difference. Computing the “perceptual weight” of each click in the train revealed a strong onset bias, very similar to that reported for humans. Follow-on electrocorticographic recording experiments revealed that onset weighting of interaural time differences is a robust feature of the cortical population response, but interestingly, it often fails to manifest at individual cortical recording sites. Conclusion While previous studies suggested that the precedence effect may be caused by early processing mechanisms in the cochlea or inhibitory circuitry in the brainstem and midbrain, our results indicate that the precedence effect is not fully developed at the level of individual recording sites in the auditory cortex, but robust and consistent precedence effects are observable only in the auditory cortex at the level of cortical population responses. This indicates that the precedence effect emerges at later cortical processing stages and is a significantly “higher order” feature than has hitherto been assumed.

Objective. Extracellular microelectrode techniques are the most widely used approach to interrogate neuronal populations. However, regardless of the manufacturing method used, damage to the vasculature and circuit function during probe insertion remains a concern. This issue can be mitigated by minimising the footprint of the probe used. Reducing the size of probes typically requires either a reduction in the number of channels present in the probe, or a reduction in the individual channel area. Both lead to less effective coupling between the probe and extracellular signals of interest. Approach. Here, we show that continuously drawn SiO 2 -insulated ultra-microelectrode fibres offer an attractive substrate to address these challenges. Individual fibres can be fabricated to >10 m continuous stretches and a selection of diameters below 30 µ m with low resistance (<100 Ω mm −1 ) continuously conductive metal core of <10 µ m and atomically flat smooth shank surfaces. To optimize the properties of the miniaturised electrode-tissue interface, we electrodeposit rough Au structures followed by ∼20 nm IrOx film resulting in the reduction of the interfacial impedance to <500 kΩ at 1 kHz. Main results . We demonstrate that these ultra-low impedance electrodes can record and stimulate both single and multi-unit activity with minimal tissue disturbance and exceptional signal-to-noise ratio in both superficial (∼40 µ m) and deep (∼6 mm) structures of the mouse brain. Further, we show that sensor modifications are stable and probe manufacturing is reproducible. Significance. Minimally perturbing bidirectional neural interfacing can reveal circuit function in the mammalian brain in vivo.

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

This study implements the use of Danish Landrace pigs as subjects for the long-term potentiation (LTP)-like pain model. This is accomplished by analyzing changes in the primary somatosensory cortex (S1) in response to electrical stimulation on the ulnar nerve after applying high-frequency electrical stimulation (HFS) on the ulnar nerve. In this study, eight Danish Landrace pigs were electrically stimulated, through the ulnar nerve, to record the cortically evoked response in S1 by a 16-channel microelectrode array (MEA). Six of these pigs were subjected to HFS (four consecutive, 15 mA, 100 Hz, 1000 µs pulse duration) 45 min after the start of the experiment. Two pigs were used as control subjects to compare the cortical response to peripheral electrical stimulation without applying HFS. Low-frequency components of the intracortical signals (0.3-300 Hz) were analyzed using event-related potential (ERP) analysis, where the minimum peak during the first 30-50 ms (N1 component) in each channel was detected. The change in N1 was compared over time across the intervention and control groups. Spectral analysis was used to demonstrate the effect of the intervention on the evoked cortical oscillations computed between 75 ms and 200 ms after stimulus. ERP analysis showed an immediate increase in N1 amplitude that became statistically significant 45 mins after HFS (p < 0.01) for the intervention group. The normalized change in power in frequency oscillations showed a similar trend. The results show that the LTP-like pain model can be effectively implemented in pigs using HFS since the cortical responses are comparable to those described in humans.

When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here, we show in awake macaque area V1 that both repetition-related reductions in firing rate and increases in gamma are specific to the repeated stimulus. These effects show some persistence on the timescale of minutes. Gamma increases are specific to the presented stimulus location. Further, repetition effects on gamma and on firing rates generalize to images of natural objects. These findings support the notion that gamma-band synchronization subserves the adaptive processing of repeated stimulus encounters.

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

Treatment refractory Tourette syndrome has been shown to be improved with deep brain stimulation, but with multiple possible stimulation locations and variable and incomplete benefit. This study presents a single case of complete amelioration of motor and verbal tics in a patient with Tourette syndrome during placement of 12 stereo-EEG electrodes to identify optimal targets for permanent stimulating electrodes. Subsequently, substantial improvement in motor and verbal tic frequency occurred with placement and programming of permanent electrodes in bilateral globus pallidus internus and nucleus accumbens, but without the complete resolution seen during depth electrode placement. We suggest that simultaneous stimulation at multiple patient-specific targets could provide effective control of Tourette symptomatology, but further study will be needed.

The strength of cortical connectivity to the striatum influences the balance between behavioral variability and stability. Learning to consistently produce a skilled action requires plasticity in corticostriatal connectivity associated with repeated training of the action. However, it remains unknown whether such corticostriatal plasticity occurs during training itself or ‘offline’ during time away from training, such as sleep. Here, we monitor the corticostriatal network throughout long-term skill learning in rats and find that non-rapid-eye-movement (NREM) sleep is a relevant period for corticostriatal plasticity. We first show that the offline activation of striatal NMDA receptors is required for skill learning. We then show that corticostriatal functional connectivity increases offline, coupled to emerging consistent skilled movements, and coupled cross-area neural dynamics. We then identify NREM sleep spindles as uniquely poised to mediate corticostriatal plasticity, through interactions with slow oscillations. Our results provide evidence that sleep shapes cross-area coupling required for skill learning.

Significance Humans and animals recognize light tactile stimulations on some occasions while at others miss even stronger stimuli. The explanation of this apparent paradox lies in the competition between spontaneously and externally evoked responses in the brain. Brief bursts of beta-oscillations have been implicated in reduced detection rates, yet the underlying mechanism remained unknown. Here, we report that neural networks exhibit synchronization during beta-bursts, followed by reduced firing rates, thus explaining the diminished detection rate on the single trial level. Through monitoring the brain’s electrical activity before and during tactile stimulation, we found that the masking influence of burst occupancy on perception can be counterbalanced in real time by adjusting the stimulus intensity, thereby overcoming this active inhibition of sensory cortex.

Background Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. Methods We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation. Results Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation. Conclusions Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies’ activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.

Aggregation and self-sorting of cells in three dimensional cultures have been described for non-neuronal cells. Despite increased interest in engineered neural tissues for treating brain injury or for modeling neurological disorders in vitro, little data is available on collective cell movements in neuronal aggregates. Migration and sorting of cells may alter these constructs’ morphology and, therefore, the function of their neural circuitry. In this work, linear, adhered rat and human 3D neuronal-astrocyte cultures were developed to enable the study of aggregation and sorting of these cells. An in silico model of the contraction, clustering, and cell sorting in the 3D cultures was also developed. Experiments and computational modeling showed that aggregation was mainly a neuron mediated process, and formation of astrocyte-rich sheaths in 3D cultures depended on differential attraction between neurons and astrocytes. In silico model predicted formation of self-assembled neuronal layers in disk-shaped 3D cultures. Neuronal activity patterns were found to correlate with local morphological differences. This model of neuronal and astrocyte aggregation and sorting may benefit future design of neuronal constructs.

Cortical spreading depolarization (CSD) is a propagating wave of tissue depolarization characterized by a large increase of extracellular potassium concentration and prolonged subsequent electrical silencing of neurons. Waves of CSD arise spontaneously in various acute neurological settings, including migraine aura and ischemic stroke. Recently, we have reported that pan-inhibition of adrenergic receptors (AdRs) facilitates the normalization of extracellular potassium after acute photothrombotic stroke in mice. Here, we have extended that mechanistic study to ask whether AdR antagonists also modify the dynamics of KCl-induced CSD and post-CSD recovery in vivo. Spontaneous neural activity and KCl-induced CSD were visualized by cortex-wide transcranial Ca 2+ imaging in G-CaMP7 transgenic mice. AdR antagonism decreased the recurrence of CSD waves and accelerated the post-CSD recovery of neural activity. Two-photon imaging revealed that astrocytes exhibited aberrant Ca 2+ signaling after passage of the CSD wave. This astrocytic Ca 2+ activity was diminished by the AdR antagonists. Furthermore, AdR pan-antagonism facilitated the normalization of the extracellular potassium level after CSD, which paralleled the recovery of neural activity. These observations add support to the proposal that neuroprotective effects of AdR pan-antagonism arise from accelerated normalization of extracellular K + levels in the setting of acute brain injury.

It is of great interest in neuroscience to determine what frequency bands in the brain contain common information. However, to date, a comprehensive statistical approach to this question has been lacking. As such, this work presents a novel statistical significance test for correlated power across frequency bands in non-stationary time series. The test accounts for biases that often go untreated in time-frequency analysis, i.e. intra-frequency autocorrelation, inter-frequency non-dyadicity, and multiple testing under dependency. It is used to test all of the inter-frequency correlations between 0.2 and 8500 Hz in continuous intracortical extracellular neural recordings, using a very large, publicly available dataset. The results show that neural processes have signatures across a very broad range of frequency bands. In particular, LFP frequency bands as low as 20 Hz were found to almost always be significantly correlated to kHz frequency ranges. This test also has applications in a broad range of fields, e.g. biological signal processing, economics, finance, climatology, etc. It is useful whenever one wants to robustly determine whether short-term components in a signal are robustly related to long-term trends, or what frequencies contain common information.

When presented with an oscillatory sensory input at a particular frequency, F [Hz], neural systems respond with the corresponding frequency, f [Hz], and its multiples. When the input includes two frequencies ( F1 and F2 ) and they are nonlinearly integrated in the system, responses at intermodulation frequencies (i.e., n1 * f1 + n2 * f2 [Hz], where n1 and n2 are non-zero integers) emerge. Utilizing these properties, the steady state evoked potential (SSEP) paradigm allows us to characterize linear and nonlinear neural computation performed in cortical neurocircuitry. Here, we analyzed the steady state evoked local field potentials (LFPs) recorded from the primary (S1) and secondary (S2) somatosensory cortex of anesthetized cats (maintained with alfaxalone) while we presented slow ( F1 = 23Hz) and fast ( F2 = 200Hz) somatosensory vibration to the contralateral paw pads and digits. Over 9 experimental sessions, we recorded LFPs from N = 1620 and N = 1008 bipolar-referenced sites in S1 and S2 using electrode arrays. Power spectral analyses revealed strong responses at 1) the fundamental ( f1 , f2 ), 2) its harmonic, 3) the intermodulation frequencies, and 4) broadband frequencies (50-150Hz). To compare the computational architecture in S1 and S2, we employed simple computational modeling. Our modeling results necessitate nonlinear computation to explain SSEP in S2 more than S1. Combined with our current analysis of LFPs, our paradigm offers a rare opportunity to constrain the computational architecture of hierarchical organization of S1 and S2 and to reveal how a large-scale SSEP can emerge from local neural population activities.

This work examines how sounds are held in auditory working memory (AWM) in humans by examining oscillatory local field potentials (LFPs) in candidate brain regions. Previous fMRI studies by our group demonstrated blood oxygenation level-dependent (BOLD) response increases during maintenance in auditory cortex, inferior frontal cortex and the hippocampus using a paradigm with a delay period greater than 10s. The relationship between such BOLD changes and ensemble activity in different frequency bands is complex, and the long delay period raised the possibility that long-term memory mechanisms were engaged. Here we assessed LFPs in different frequency bands in six subjects with recordings from all candidate brain regions using a paradigm with a short delay period of 3 s. Sustained delay activity was demonstrated in all areas, with different patterns in the different areas. Enhancement in low frequency (delta) power and suppression across higher frequencies (beta/gamma) were demonstrated in primary auditory cortex in medial Heschl's gyrus (HG) whilst non-primary cortex showed patterns of enhancement and suppression that altered at different levels of the auditory hierarchy from lateral HG to superior- and middle-temporal gyrus. Inferior frontal cortex showed increasing suppression with increasing frequency. The hippocampus and parahippocampal gyrus showed low frequency increases and high frequency decreases in oscillatory activity. This work demonstrates sustained activity patterns during AWM maintenance, with prominent low-frequency increases in medial temporal lobe regions.

There is considerable interest in understanding cortical processing and the function of top-down and bottom-up human neural circuits that control speech production. Research efforts to investigate these circuits are aided by analysis of spectro-temporal response characteristics of neural activity recorded by electrocorticography (ECoG). Further, cortical processing may be altered in the case of hearing-impaired cochlear implant (CI) users, as electric excitation of the auditory nerve creates a markedly different neural code for speech compared with that of the functionally intact hearing system. Studies of cortical activity in CI users typically record scalp potentials and are hampered by stimulus artifact contamination and by spatiotemporal filtering imposed by the skull. We present a unique case of a CI user who required direct recordings from the cortical surface using subdural electrodes implanted for epilepsy assessment. Using experimental conditions where the subject vocalized in the presence (CIs ON) or absence (CIs OFF) of auditory feedback, or listened to playback of self-vocalizations without production, we observed ECoG activity primarily in γ (32-70 Hz) and high γ (70-150 Hz) bands at focal regions on the lateral surface of the superior temporal gyrus (STG). High γ band responses differed in their amplitudes across conditions and cortical sites, possibly reflecting different rates of stimulus presentation and differing levels of neural adaptation. STG γ responses to playback and vocalization with auditory feedback were not different from responses to vocalization without feedback, indicating this activity reflects not only auditory, but also attentional, efference-copy, and sensorimotor processing during speech production.

Cortical synchrony is theorized to contribute to communication between connected networks during executive functioning. To understand the functional role of neural synchrony in cognitive flexibility, we recorded from auditory cortex (AC) and medial prefrontal cortex (mPFC), while mice performed an auditory extinction learning task. We found that while animals gradually showed reduced responding to the unrewarded tone over hundreds of trials, the power of local field potential (LFP) oscillations (8-18 Hz, centered at alpha/beta frequencies) in AC and mPFC exhibited immediate and robust increases, prior to behavioral changes. The strength of LFP alpha/beta power in the mPFC, but not AC, was strongly correlated with the behavioral performance that mice would achieve later in the training session. Further, we found that coherence between AC and mPFC at 8-18Hz was selectively enhanced only after mice learned to suppress licking, and this LFP coherence increase coincided with a reduction in spiking rate for the unrewarded tone in AC. These results reveal that enhanced interactions between PFC and AC is an inherent property of auditory discrimination learning, and that coordinated alpha/beta oscillations contribute to cognitive flexibility.