Premotor cortical beta synchronization and the network neuromodulation of externally paced finger tapping in Parkinson's disease.

Parkinson's disease (PD) is characterized by the disruption of repetitive, concurrent and sequential motor actions due to compromised timing-functions principally located in cortex-basal ganglia (BG) circuits. Increasing evidence suggests that motor impairments in untreated PD patients are linked to an excessive synchronization of cortex-BG activity at beta frequencies (13-30 Hz). Levodopa and subthalamic nucleus deep brain stimulation (STN-DBS) suppress pathological beta-band reverberation and improve the motor symptoms in PD. Yet a dynamic tuning of beta oscillations in BG-cortical loops is fundamental for movement-timing and synchronization, and the impact of PD therapies on sensorimotor functions relying on neural transmission in the beta frequency-range remains controversial. Here, we set out to determine the differential effects of network neuromodulation through dopaminergic medication (ON and OFF levodopa) and STN-DBS (ON-DBS, OFF-DBS) on tapping synchronization and accompanying cortical activities. To this end, we conducted a rhythmic finger-tapping study with high-density EEG-recordings in 12 PD patients before and after surgery for STN-DBS and in 12 healthy controls. STN-DBS significantly ameliorated tapping parameters as frequency, amplitude and synchrony to the given auditory rhythms. Aberrant neurophysiologic signatures of sensorimotor feedback in the beta-range were found in PD patients: their neural modulation was weaker, temporally sluggish and less distributed over the right cortex in comparison to controls. Levodopa and STN-DBS boosted the dynamics of beta-band modulation over the right hemisphere, hinting to an improved timing of movements relying on tactile feedback. The strength of the post-event beta rebound over the supplementary motor area correlated significantly with the tapping asynchrony in patients, thus indexing the sensorimotor match between the external auditory pacing signals and the performed taps. PD patients showed an excessive interhemispheric coherence in the beta-frequency range during the finger-tapping task, while under DBS-ON the cortico-cortical connectivity in the beta-band was normalized. Ultimately, therapeutic DBS significantly ameliorated the auditory-motor coupling of PD patients, enhancing the electrophysiological processing of sensorimotor feedback-information related to beta-band activity, and thus allowing a more precise cued-tapping performance.

Functional hierarchies in brain dynamics characterized by signal reversibility in ferret cortex.

Brain signal irreversibility has been shown to be a promising approach to study neural dynamics. Nevertheless, the relation with cortical hierarchy and the influence of different electrophysiological features is not completely understood. In this study, we recorded local field potentials (LFPs) during spontaneous behavior, including awake and sleep periods, using custom micro-electrocorticographic (µECoG) arrays implanted in ferrets. In contrast to humans, ferrets remain less time in each state across the sleep-wake cycle. We deployed a diverse set of metrics in order to measure the levels of complexity of the different behavioral states. In particular, brain irreversibility, which is a signature of non-equilibrium dynamics, captured by the arrow of time of the signal, revealed the hierarchical organization of the ferret's cortex. We found different signatures of irreversibility and functional hierarchy of large-scale dynamics in three different brain states (active awake, quiet awake, and deep sleep), showing a lower level of irreversibility in the deep sleep stage, compared to the other. Irreversibility also allowed us to disentangle the influence of different cortical areas and frequency bands in this process, showing a predominance of the parietal cortex and the theta band. Furthermore, when inspecting the embedded dynamic through a Hidden Markov Model, the deep sleep stage was revealed to have a lower switching rate and lower entropy production. These results suggest functional hierarchies in organization that can be revealed through thermodynamic features and information theory metrics.

Structural basis of envelope and phase intrinsic coupling modes in the cerebral cortex.

Intrinsic coupling modes (ICMs) can be observed in ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted micro-ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are significantly related to SC, except for phase ICMs when using measures removing zero-lag coupling. The correlation between SC and ICMs increases with increasing frequency which is accompanied by reduced delays. Computational models produced results that were highly dependent on the specific parameter settings. The most consistent predictions were derived from measures solely based on SC. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs are both related, albeit to different degrees, to the underlying structural connectivity in the cerebral cortex.

Mathematical Relations Between Measures of Brain Connectivity Estimated From Electrophysiological Recordings for Gaussian Distributed Data.

A large variety of methods exist to estimate brain coupling in the frequency domain from electrophysiological data measured, e.g., by EEG and MEG. Those data are to reasonable approximation, though certainly not perfectly, Gaussian distributed. This work is based on the well-known fact that for Gaussian distributed data, the cross-spectrum completely determines all statistical properties. In particular, for an infinite number of data, all normalized coupling measures at a given frequency are a function of complex coherency. However, it is largely unknown what the functional relations are. We here present those functional relations for six different measures: the weighted phase lag index, the phase lag index, the absolute value and imaginary part of the phase locking value (PLV), power envelope correlation, and power envelope correlation with correction for artifacts of volume conduction. With the exception of PLV, the final results are simple closed form formulas. In an excursion we also discuss differences between short time Fourier transformation and Hilbert transformation for estimations in the frequency domain. We tested in simulations of linear and non-linear dynamical systems and for empirical resting state EEG on sensor level to what extent a model, namely the respective function of coherency, can explain the observed couplings. For empirical data we found that for measures of phase-phase coupling deviations from the model are in general minor, while power envelope correlations systematically deviate from the model for all frequencies. For power envelope correlation with correction for artifacts of volume conduction the model cannot explain the observed couplings at all. We also analyzed power envelope correlation as a function of time and frequency in an event related experiment using a stroop reaction task and found significant event related deviations mostly in the alpha range.

Context-specific modulation of intrinsic coupling modes shapes multisensory processing.

Intrinsically generated patterns of coupled neuronal activity are associated with the dynamics of specific brain states. Sensory inputs are extrinsic factors that can perturb these intrinsic coupling modes, creating a complex scenario in which forthcoming stimuli are processed. Studying this intrinsic-extrinsic interplay is necessary to better understand perceptual integration and selection. Here, we show that this interplay leads to a reconfiguration of functional cortical connectivity that acts as a mechanism to facilitate stimulus processing. Using audiovisual stimulation in anesthetized ferrets, we found that this reconfiguration of coupling modes is context specific, depending on long-term modulation by repetitive sensory inputs. These reconfigured coupling modes lead to changes in latencies and power of local field potential responses that support multisensory integration. Our study demonstrates that this interplay extends across multiple time scales and involves different types of intrinsic coupling. These results suggest a previously unknown large-scale mechanism that facilitates multisensory integration.

Synchrony surfacing: Epicortical recording of correlated action potentials.

Synchronous spiking of multiple neurons is a key phenomenon in normal brain function and pathologies. Recently, approaches to record spikes from the intact cortical surface using small high-density arrays of microelectrodes have been reported. It remained unaddressed how epicortical spiking relates to intracortical unit activity. We introduced a mesoscale approach using an array of 64 electrodes with intermediate diameter (250 µm) and combined large-coverage epicortical recordings in ferrets with intracortical recordings via laminar probes. Empirical data and modelling strongly suggest that our epicortical electrodes selectively captured synchronized spiking of neurons in the cortex beneath. As a result, responses to sensory stimulation were more robust and less noisy compared to intracortical activity, and receptive field properties were well preserved in epicortical recordings. This should promote insights into assembly-coding beyond the informative value of subdural EEG or single-unit spiking, and be advantageous to real-time applications in brain-machine interfacing.

Intrinsic Functional Connectivity Resembles Cortical Architecture at Various Levels of Isoflurane Anesthesia.

Cortical single neuron activity and local field potential patterns change at different depths of general anesthesia. Here, we investigate the associated network level changes of functional connectivity. We recorded ongoing electrocorticographic (ECoG) activity from temporo-parieto-occipital cortex of 6 ferrets at various levels of isoflurane/nitrous oxide anesthesia and determined functional connectivity by computing amplitude envelope correlations. Through hierarchical clustering, we derived typical connectivity patterns corresponding to light, intermediate and deep anesthesia. Generally, amplitude correlation strength increased strongly with depth of anesthesia across all cortical areas and frequency bands. This was accompanied, at the deepest level, by the emergence of burst-suppression activity in the ECoG signal and a change of the spectrum of the amplitude envelope. Normalization of functional connectivity to the distribution of correlation coefficients showed that the topographical patterns remained similar across depths of anesthesia, reflecting the functional association of the underlying cortical areas. Thus, while strength and temporal properties of amplitude co-modulation vary depending on the activity of local neural circuits, their network-level interaction pattern is presumably most strongly determined by the underlying structural connectivity.

Dynamic reconfiguration of cortical functional connectivity across brain states.

Throughout each day, the brain displays transient changes in state, as evidenced by shifts in behavior and vigilance. While the electrophysiological correlates of brain states have been studied for some time, it remains unclear how large-scale cortico-cortical functional connectivity systematically reconfigures across states. Here, we investigate state-dependent shifts in cortical functional connectivity by recording local field potentials (LFPs) during spontaneous behavioral transitions in the ferret using chronically implanted micro-electrocorticographic (µECoG) arrays positioned over occipital, parietal, and temporal cortical regions. To objectively classify brain state, we describe a data-driven approach that projects time-varying LFP spectral properties into brain state space. Distinct brain states displayed markedly different patterns of cross-frequency phase-amplitude coupling and inter-electrode phase synchronization across several LFP frequency bands. The largest across-state differences in functional connectivity were observed between periods of presumed slow-wave and rapid-eye-movement-sleep/active-state, which were characterized by the contrasting phenomena of cortical network fragmentation and global synchronization, respectively. Collectively, our data provide strong evidence that large-scale functional interactions in the brain dynamically reconfigure across behavioral states.

Intrinsic coupling modes reveal the functional architecture of cortico-tectal networks.

In the absence of sensory stimulation or motor output, the brain exhibits complex spatiotemporal patterns of intrinsically generated neural activity. Analysis of ongoing brain dynamics has identified the prevailing modes of cortico-cortical interaction; however, little is known about how such patterns of intrinsically generated activity are correlated between cortical and subcortical brain areas. We investigate the correlation structure of ongoing cortical and superior colliculus (SC) activity across multiple spatial and temporal scales. Ongoing cortico-tectal interaction was characterized by correlated fluctuations in the amplitude of delta, spindle, low gamma, and high-frequency oscillations (>100 Hz). Of these identified coupling modes, topographical patterns of high-frequency coupling were the most consistent with patterns of anatomical connectivity, reflecting synchronized spiking within cortico-tectal networks. Cortico-tectal coupling at high frequencies was temporally parcellated by the phase of slow cortical oscillations and was strongest for SC-cortex channel pairs that displayed overlapping visual spatial receptive fields. Despite displaying a high degree of spatial specificity, cortico-tectal coupling in lower-frequency bands did not match patterns of cortex-to-SC anatomical connectivity. Collectively, our findings demonstrate that neural activity is spontaneously coupled between cortex and SC, with high- and low-frequency modes of coupling reflecting direct and indirect cortico-tectal interactions, respectively.

Auditory and visual interactions between the superior and inferior colliculi in the ferret.

The integration of visual and auditory spatial information is important for building an accurate perception of the external world, but the fundamental mechanisms governing such audiovisual interaction have only partially been resolved. The earliest interface between auditory and visual processing pathways is in the midbrain, where the superior (SC) and inferior colliculi (IC) are reciprocally connected in an audiovisual loop. Here, we investigate the mechanisms of audiovisual interaction in the midbrain by recording neural signals from the SC and IC simultaneously in anesthetized ferrets. Visual stimuli reliably produced band-limited phase locking of IC local field potentials (LFPs) in two distinct frequency bands: 6-10 and 15-30 Hz. These visual LFP responses co-localized with robust auditory responses that were characteristic of the IC. Imaginary coherence analysis confirmed that visual responses in the IC were not volume-conducted signals from the neighboring SC. Visual responses in the IC occurred later than retinally driven superficial SC layers and earlier than deep SC layers that receive indirect visual inputs, suggesting that retinal inputs do not drive visually evoked responses in the IC. In addition, SC and IC recording sites with overlapping visual spatial receptive fields displayed stronger functional connectivity than sites with separate receptive fields, indicating that visual spatial maps are aligned across both midbrain structures. Reciprocal coupling between the IC and SC therefore probably serves the dynamic integration of visual and auditory representations of space.

Asymmetric pallidal neuronal activity in patients with cervical dystonia.

The origin of asymmetric clinical manifestation of symptoms in patients suffering from cervical dystonia (CD) is hitherto poorly understood. Dysregulated neuronal activity in the basal ganglia has been suggested to have a role in the pathophysiology of CD. Here, we re-assessed the question to what extent relative changes occur in the direct vs. indirect basal ganglia pathway in CD, whether these circuit changes are lateralized, and how these alterations relate to CD symptoms. To this end, we recorded ongoing single cell and local field potential (LFP) activity from the external (GPe) and internal pallidal segment (GPi) of 13 CD patients undergoing microelectrode-guided stereotactic surgery for deep brain stimulation in the GPi. We compared pallidal recordings from CD patients operated under local anaesthesia (LA) with those obtained in CD patients operated under general anaesthesia (GA). In awake patients, mean GPe discharge rate (52 Hz) was lower than that of GPi (72 Hz). Mean GPi discharge ipsilateral to the side of head turning was higher than contralateral and correlated with torticollis symptom severity. Lateralized differences were absent at the level of the GPe and in recordings from patients operated under GA. Furthermore, in the GPi of CD patients there was a subpopulation of theta-oscillatory cells with unique bursting characteristics. Power and coherence of GPe- and GPi-LFPs were dominated by a theta peak and also exhibited band-specific interhemispheric differences. Strong cross-frequency coupling of low-gamma amplitude to theta phase was a feature of pallidal LFPs recorded under LA, but not GA. These results indicate that CD is associated with an asymmetric pallidal outflow. Based on the finding of symmetric neuronal discharges in the GPe, we propose that an imbalanced interhemispheric direct pathway gain may be involved in CD pathophysiology.

Laminar profile of visual response properties in ferret superior colliculus.

In the superior colliculus (SC), visual afferent inputs from various sources converge in a highly organized way such that all layers form topographically aligned representations of contralateral external space. Despite this anatomical organization, it remains unclear how the layer-specific termination of different visual input pathways is reflected in the nature of visual response properties and their distribution across layers. To uncover the physiological correlates underlying the laminar organization of the SC, we recorded multiunit and local field potential activity simultaneously from all layers with dual-shank multichannel linear probes. We found that the location of spatial receptive fields was strongly conserved across all visual responsive layers. There was a tendency for receptive field size to increase with depth in the SC, with superficial receptive fields significantly smaller than deep receptive fields. Additionally, superficial layers responded significantly faster than deeper layers to flash stimulation. In some recordings, flash-evoked responses were characterized by the presence of gamma oscillatory activity (40-60 Hz) in multiunit and field potential signals, which was strongest in retinorecipient layers. While SC neurons tended to respond only weakly to full-field drifting gratings, we observed very similar oscillatory responses to the offset of grating stimuli, suggesting gamma oscillations are produced following light offset. Oscillatory spiking activity was highly correlated between horizontally distributed neurons within these layers, with oscillations temporally locked to the stimulus. Together, visual response properties provide physiological evidence reflecting the laminar-specific termination of visual afferent pathways in the SC, most notably characterized by the oscillatory entrainment of superficial neurons.

Predicting stimulus-locked single unit spiking from cortical local field potentials.

The rapidly increasing use of the local field potential (LFP) has motivated research to better understand its relation to the gold standard of neural activity, single unit (SU) spiking. We addressed this in an in vivo, awake, restrained mouse auditory cortical electrophysiology preparation by asking whether the LFP could actually be used to predict stimulus-evoked SU spiking. Implementing a Bayesian algorithm to predict the likelihood of spiking on a trial by trial basis from different representations of the despiked LFP signal, we were able to predict, with high quality and fine temporal resolution (2 ms), the time course of a SU's excitatory or inhibitory firing rate response to natural species-specific vocalizations. Our best predictions were achieved by representing the LFP by its wide-band Hilbert phase signal, and approximating the statistical structure of this signal at different time points as independent. Our results show that each SU's action potential has a unique relationship with the LFP that can be reliably used to predict the occurrence of spikes. This "signature" interaction can reflect both pre- and post-spike neural activity that is intrinsic to the local circuit rather than just dictated by the stimulus. Finally, the time course of this "signature" may be most faithful when the full bandwidth of the LFP, rather than specific narrow-band components, is used for representation.

Inhibitory plasticity in a lateral band improves cortical detection of natural vocalizations.

The interplay between excitation and inhibition in the auditory cortex is crucial for the processing of acoustic stimuli. However, the precise role that inhibition plays in the distributed cortical encoding of natural vocalizations has not been well studied. We recorded single units (SUs) and local field potentials (LFPs) in the awake mouse auditory cortex while presenting pup isolation calls to animals that either do (mothers) or do not (virgins) recognize the sounds as behaviorally relevant. In both groups, we observed substantial call-evoked inhibition. However, in mothers this was earlier, longer, stronger, and more stereotyped compared to virgins. This difference was most apparent for recording sites tuned to tone frequencies lower than the pup calls' high-ultrasonic frequency range. We hypothesize that this auditory cortical inhibitory plasticity improves pup call detection in a relatively specific manner by increasing the contrast between call-evoked responses arising from high-ultrasonic and lateral frequency neural populations.