Periodic Neural Activity Research Articles

Medication-invariant resting aperiodic and periodic neural activity in Parkinson's disease.

Parkinson's disease (PD) has been associated with greater total power in canonical frequency bands (i.e., alpha, beta) of the resting electroencephalogram (EEG). However, PD has also been associated with a reduction in the proportion of total power across all frequency bands. This discrepancy may be explained by aperiodic activity (exponent and offset) present across all frequency bands. Here, we examined differences in the eyes-open (EO) and eyes-closed (EC) resting EEG of PD participants (N = 26) on and off medication, and age-matched healthy controls (CTL; N = 26). We extracted power from canonical frequency bands using traditional methods (total alpha and beta power) and extracted separate parameters for periodic (parameterized alpha and beta power) and aperiodic activity (exponent and offset). Cluster-based permutation tests over spatial and frequency dimensions indicated that total alpha and beta power, and aperiodic exponent and offset were greater in PD participants, independent of medication status. After removing the exponent and offset, greater alpha power in PD (vs. CTL) was only present in EO recordings and no reliable differences in beta power were observed. Differences between PD and CTL in the resting EEG are likely driven by aperiodic activity, suggestive of greater relative inhibitory neural activity and greater neuronal spiking. Our findings suggest that resting EEG activity in PD is characterized by medication-invariant differences in aperiodic activity which is independent of the increase in alpha power with EO. This highlights the importance of considering aperiodic activity contributions to the neural correlates of brain disorders.

Beyond rhythm - a framework for understanding the frequency spectrum of neural activity.

Cognitive and behavioral processes are often accompanied by changes within well-defined frequency bands of the local field potential (LFP i.e., the voltage induced by neuronal activity). These changes are detectable in the frequency domain using the Fourier transform and are often interpreted as neuronal oscillations. However, aside some well-known exceptions, the processes underlying such changes are difficult to track in time, making their oscillatory nature hard to verify. In addition, many non-periodic neural processes can also have spectra that emphasize specific frequencies. Thus, the notion that spectral changes reflect oscillations is likely too restrictive. In this study, we use a simple yet versatile framework to understand the frequency spectra of neural recordings. Using simulations, we derive the Fourier spectra of periodic, quasi-periodic and non-periodic neural processes having diverse waveforms, illustrating how these attributes shape their spectral signatures. We then show how neural processes sum their energy in the local field potential in simulated and real-world recording scenarios. We find that the spectral power of neural processes is essentially determined by two aspects: (1) the distribution of neural events in time and (2) the waveform of the voltage induced by single neural events. Taken together, this work guides the interpretation of the Fourier spectrum of neural recordings and indicates that power increases in specific frequency bands do not necessarily reflect periodic neural activity.

EEG time-warping to study non-strictly-periodic EEG signals related to the production of rhythmic movements

BackgroundMany sensorimotor functions are intrinsically rhythmic, and are underlined by neural processes that are functionally distinct from neural responses related to the processing of transient events. EEG frequency tagging is a technique that is increasingly used in neuroscience to study these processes. It relies on the fact that perceiving and/or producing rhythms generates periodic neural activity that translates into periodic variations of the EEG signal. In the EEG spectrum, those variations appear as peaks localized at the frequency of the rhythm and its harmonics. New methodMany natural rhythms, such as music or dance, are not strictly periodic and, instead, show fluctuations of their period over time. Here, we introduce a time-warping method to identify non-strictly-periodic EEG activities in the frequency domain. ResultsEEG time-warping can be used to characterize the sensorimotor activity related to the performance of self-paced rhythmic finger movements. Furthermore, the EEG time-warping method can disentangle auditory- and movement-related EEG activity produced when participants perform rhythmic movements synchronized to an acoustic rhythm. This is possible because the movement-related activity has different period fluctuations than the auditory-related activity. Comparison with existing methodsWith the classic frequency-tagging approach, rhythm fluctuations result in a spreading of the peaks to neighboring frequencies, to the point that they cannot be distinguished from background noise. ConclusionsThe proposed time-warping procedure is as a simple and effective mean to study natural non-strictly-periodic rhythmic neural processes such as rhythmic movement production, acoustic rhythm perception and sensorimotor synchronization.

Non linear dynamics of mechanosensory flight control in flies

In most animals, rhythmic motion is governed by central pattern generators (CPGs) - neural circuits that generate periodic patterned output. Sensory input to the CPG is not necessary to maintain the periodic neural activity, but is known to strongly influence it. For example, proprioceptive afferent input may entrain the neural CPG rhythm to the mechanical resonance frequency of a limb [1]. CPGs have been shown to govern the locomotor rhythms in vertebrates as well as in insects. A CPG governing the flight rhythm, however, has not been identified in flies, which are known for their remarkable flight maneuverability. In flies, the wingbeat rhythm is generated myogenically by stretch-activated power muscles and hence is not directly controlled by neural input. It is therefore unclear if the insights gained for proprioceptive feedback in CPG-based motor systems [1] likewise apply to flight control in flies. In our study, we investigated if and how proprioceptive feedback influences the rhythm of the myogenic wing beat oscillator. We concentrated on mechanosensory input from the halteres - specialized „gyroscopic sensory organs of flies. The halteres are known to activate the motor neurons of miniscule steering muscles, which in turn modulate the motion of the wings. In our experiments [2], tethered flying fruit flies (Drosophila melanogaster) were vibrated by a piezoelectric actuator to stimulate the haltere mechanosensory pathways. We used a laser Doppler interferometer to measure the vibrations of the tether resulting from the superposition of the piezo-delivered stimulus and the fly's wing beat. We determined the phase relationship between the wing motion and the mechanical stimulus in each wing stroke and applied an automated synchrogram analysis [3] to detect entrainment and higher-order synchronization. The flies synchronized with the stimulus for specific ranges of stimulus amplitude and frequency, revealing the characteristic Arnol'd tongues of a forced limit cycle oscillator. Our analysis shows that the steering muscles (activated by proprioceptive input) act as a mechanical forcing of the central power muscle oscillator. We propose that the mechanical forcing of a myogenic limit cycle oscillator permits flies to avoid the comparatively slow control based on a neural central pattern generator. In the entrainment study described above, flies were attached to tethers with high resonance frequency and damping coefficient. While experimenting with tethers of varying mechanical properties, however, we observed that the fly's behavior was significantly influenced by the properties of the tether. To systematically explore this influence for a given fly, we altered the tether's resonance frequency by clamping the tether at a different point in each distinct flight test. In these experiments, no piezo stimulus was applied. Yet, when the tether resonance frequency was comparable to the wing beat frequency, the forces from the fly lead to large cumulative motion of the tether and activation of the haltere mechanosensors. The fly therefore received delayed feedback dependent on its previous activity. This lead to a variety of observed dynamical regimes, including the locking of the wing beat frequency to the tether resonance frequency when their initial difference was sufficiently small (similar to limb entrainment in [1]). We were able to reproduce most of the observed dynamical features in a simplified mathematical model of two mutually coupled oscillators: a phase-reduced nonlinear oscillator representing the wing beat and a linear oscillator representing the tether dynamics.

Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al. in Spikes: exploring the neural code. MIT Press, Cambridge, 1999; Brenner et al. in Neural Comput 12(7):1531-1552, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.

Electrical Stimulation of the Cochlea to Reduce Tinnitus.

This article reviews possible neural correlates of tinnitus, including an increase in rate, a decrease in rate, periodic activity, synchronous activity across neurons, and an edge between active and inactive neurons. We make some suggestions regarding how electrical current might alter these patterns of neural activity. For example, if tinnitus were represented with periodic neural activity, then electrical stimulation would need to disrupt this periodicity. Some cases of cochlear electrical stimulation are reviewed that show the tinnitus can be reduced or eliminated with cochlear electrical stimulation although it varies across individuals. Finally, after summarizing some key observations, we suggest some next steps to bring this into a clinical application.

Periodic neural activity induced by network complexity

We study a model for neural activity on the small-world topology of Watts and Strogatz and on the scale-free topology of Barabási and Albert. We find that the topology of the network connections may spontaneously induce periodic neural activity, contrasting with nonperiodic neural activities exhibited by regular topologies. Periodic activity exists only for relatively small networks and occurs with higher probability when the rewiring probability is larger. The average length of the periods increases with the square root of the network size.

Subdivisions of the guinea-pig accessory olfactory bulb revealed by the combined method with immunohistochemistry, electrophysiological, and optical recordings

The presence of subgroups in vomeronasal sensory neurons has been known in various animals. To elucidate possible functional subdivisions in the guinea-pig accessory olfactory bulb, the combined studies with GTP-binding protein immunohistochemistry, electrophysiological and optical recordings were carried out. Gi2 α and Go α proteins were immunohistochemically localized, respectively, in the anterior and posterior regions of the vomeronasal nerve and glomerular layers, indicating that the guinea-pig accessory olfactory bulb receives at least two different inputs. This suggests that an anatomical boundary exists in these two layers. A mapping study of field potentials in sagittal slice preparations demonstrated that stimulation of the anterior vomeronasal nerve layer elicited field potentials with weak oscillatory responses exclusively in the anterior region of the external plexiform layer, whereas shocks to the posterior vomeronasal nerve layer provoked distinct oscillatory responses within the posterior one. The damping factors of oscillations in the anterior and posterior regions were 0.064±0.028 and 0.025±0.014, respectively. These electrophysiological results suggest that the accessory olfactory bulb consists of two functionally different subdivisions. Real-time optical imaging showed that anterior vomeronasal nerve layer shocks produced neural activity which spread horizontally from anterior to posterior only within the anterior region of the external plexiform and mitral cell layers, whereas shocks to the posterior vomeronasal nerve layer evoked periodic neural activity which spread horizontally from posterior to anterior only within the posterior region. Furthermore, the most posterior extent of the optical response evoked in the anterior region immediately adjoined the most anterior extent of that evoked in the posterior region. The maximal distance of signal propagation in the granule cell layer corresponded to that in the overlying external plexiform and mitral cell layers, indicating that the granule cell layer also has a similar boundary. Thus, these optical imaging studies not only demonstrated a precise boundary in each layer of the accessory olfactory bulb, which was positioned right beneath the boundary defined by GTP-binding protein immunohistochemistry, but also confirmed the observations from electrophysiological mapping that evoked field potentials are independently distributed in each of two subdivisions. The presence of the functional subdivision in each layer leads us to conclude that the accessory olfactory bulb in the guinea-pig is distinctly segregated into the anterior and posterior subdivisions, and to suggest that there are at least two different input–output pathways in the vomeronasal system.

Respiratory rhythm generation in the in vitro brain stem-spinal cord preparation of the neonatal rat.

An in vitro preparation was described for studying electrical activity of mammalian brain stem and spinal cord. The brain stem and the spinal cord were isolated from 0-4-day-old rats, placed in a bath and perfused with modified Krebs solution. Various reflex responses could be recorded from cranial nerves by stimulation of other cranial nerves. The preparation was viable for more than 7 h. Spontaneous periodic neural activity could be recorded from phrenic, hypoglossal and other spinal nerves. The periodic discharges of phrenic nerves are synchronized with those of ventral roots C4 and the upward movements of the thorax which was isolated together with the spinal cord. The rhythm of periodic activity seems to be generated in the brain stem. The periodic activity was enhanced by perfusion with low pH solution and depressed by high pH solution. It was markedly depressed by opioid compounds such as enkephalin. It is suggested that this periodic activity corresponds to the respiratory rhythm generated in the brain stem of intact animals. The present preparation may be valuable for elucidating cellular mechanisms of generation and control of respiratory rhythm in the mammalian central nervous system.

Human auditory frequency-following responses to a missing fundamental.

Both a complex tone perceived as a 365-hertz "missing fundamental" and a 365-hertz pure tone evoked 365-hertz far-field frequency-following responses. Narrow-band masking noise centered at 365 hertz attenuated the responses to the pure tone but not to the complex tone. Results support the concept that perception of the missing fundamental is based on periodic neural activity.

Periodicity Pitch and Masking in Pathologic Ears

The locus of the periodicity-pitch sensation within the auditory system continues to be a subject of controversy. A recent paper by Small and Campbell supports the thesis that the low-pitch sensation is the result of a periodic neural activity in high-frequency perceptual channels (2000 cps in their experiment). In the present experiment, the methods of Small and Campbell have been used to further investigate this phenomenon by examining the responses of several subjects with severe high-frequency losses (presumably due to cochlear or neural pathology) to a similar pulsed signal. The filter range has been shifted to 4000 cps to coincide with the loss. Narrow-band random noise was used as the masker. Results are compared with normal ears under the same conditions. The data indicate that a narrow-band noise centered at 250 cps, covering the repetition rate, is a more effective musket for the low-pitch sensation than either a similar 2000- or 4000-cps noise.