A dynamical model for the basal ganglia-thalamo-cortical oscillatory activity and its implications in Parkinson’s disease

We propose to investigate brain electrophysiological alterations associated with Parkinson’s disease through a novel adaptive dynamical model of the network of the basal ganglia, the cortex and the thalamus. The model uniquely unifies the influence of dopamine in the regulation of the activity of all basal ganglia nuclei, the self-organised neuronal interdependent activity of basal ganglia-thalamo-cortical circuits and the generation of subcortical background oscillations. Variations in the amount of dopamine produced in the neurons of the substantia nigra pars compacta are key both in the onset of Parkinson’s disease and in the basal ganglia action selection. We model these dopamine-induced relationships, and Parkinsonian states are interpreted as spontaneous emergent behaviours associated with different rhythms of oscillatory activity patterns of the basal ganglia-thalamo-cortical network. These results are significant because: (1) the neural populations are built upon single-neuron models that have been robustly designed to have eletrophysiologically-realistic responses, and (2) our model distinctively links changes in the oscillatory activity in subcortical structures, dopamine levels in the basal ganglia and pathological synchronisation neuronal patterns compatible with Parkinsonian states, this still remains an open problem and is crucial to better understand the progression of the disease.Electronic supplementary materialThe online version of this article (10.1007/s11571-020-09653-y) contains supplementary material, which is available to authorized users.     

Computational modeling of epileptiform activities in medial temporal lobe epilepsy combined with <Emphasis Type="Italic">in vitro</Emphasis> experiments

Electrical stimulation of sub-cortical brain regions (the basal ganglia), known as deep brain stimulation (DBS), is an effective treatment for Parkinson’s disease (PD). Chronic high frequency (HF) DBS in the subthalamic nucleus (STN) or globus pallidus interna (GPi) reduces motor symptoms including bradykinesia and tremor in patients with PD, but the therapeutic mechanisms of DBS are not fully understood. We developed a biophysical network model comprising of the closed loop cortical-basal ganglia-thalamus circuit representing the healthy and parkinsonian rat brain. The network properties of the model were validated by comparing responses evoked in basal ganglia (BG) nuclei by cortical (CTX) stimulation to published experimental results. A key emergent property of the model was generation of low-frequency network oscillations. Consistent with their putative pathological role, low-frequency oscillations in model BG neurons were exaggerated in the parkinsonian state compared to the healthy condition. We used the model to quantify the effectiveness of STN DBS at different frequencies in suppressing low-frequency oscillatory activity in GPi. Frequencies less than 40 Hz were ineffective, low-frequency oscillatory power decreased gradually for frequencies between 50 Hz and 130 Hz, and saturated at frequencies higher than 150 Hz. HF STN DBS suppressed pathological oscillations in GPe/GPi both by exciting and inhibiting the firing in GPe/GPi neurons, and the number of GPe/GPi neurons influenced was greater for HF stimulation than low-frequency stimulation. Similar to the frequency dependent suppression of pathological oscillations, STN DBS also normalized the abnormal GPi spiking activity evoked by CTX stimulation in a frequency dependent fashion with HF being the most effective. Therefore, therapeutic HF STN DBS effectively suppresses pathological activity by influencing the activity of a greater proportion of neurons in the output nucleus of the BG.     

A computational model of how an interaction between the thalamocortical and thalamic reticular neurons transforms the low-frequency oscillations of the globus pallidus

In Parkinson’s disease, neurons of the internal segment of the globus pallidus (GPi) display the low-frequency tremor-related oscillations. These oscillatory activities are transmitted to the thalamic relay nuclei. Computer models of the interacting thalamocortical (TC) and thalamic reticular (RE) neurons were used to explore how the TC-RE network processes the low-frequency oscillations of the GPi neurons. The simulation results show that, by an interaction between the TC and RE neurons, the TC-RE network transforms a low-frequency oscillatory activity of the GPi neurons to a higher frequency of oscillatory activity of the TC neurons (the superharmonic frequency transformation). In addition to the interaction between the TC and RE neurons, the low-threshold calcium current in the RE and TC neurons and the hyperpolarization-activated cation current (I _h) in the TC neurons have significant roles in the superharmonic frequency transformation property of the TC-RE network. The external globus pallidus (GPe) oscillatory activity, which is directly transmitted to the RE nucleus also displays a significant modulatory effect on the superharmonic frequency transformation property of the TC-RE network. Action Editor: John Rinzel     

Pacemaker oscillations in heart and brain: a key role for hyperpolarization-activated cation channels

Rhythmic activity of single cells or multicellular networks is a common feature of all organisms. The oscillatory activity is characterized by time intervals of several seconds up to many hours. Cellular rhythms govern the beating of the heart, the swimming behavior of sperm, cycles of sleep and wakefulness, breathing, and the release of hormones. Many neurons in the brain and cardiac cells are characterized by endogenous rhythmic activity, which relies on a complex interplay between several distinct ion channels. In particular, one type of ion channel plays a prominent role in the control of rhythmic electrical activity since it determines the frequency of the oscillations. The activity of the channels is thus setting the "pace" of the oscillations; therefore, these channels are often referred to as "pacemaker" channels. Despite their obvious important physiological function, it was not until recently that genes encoding pacemaker channels have been identified. Because both hyperpolarization and cyclic nucleotides are key elements that control their activity, pacemaker channels have now been designated hyperpolarization-activated and cyclic nucleotide-gated (HCN) channels. The molecular identification of the channels and the upcoming studies on their properties in heterologous systems will certainly enhance our understanding of "pacemaking" in physiological systems. This review gives a brief insight into the physiological importance of these channels and sums up what we have learned since the first cloning of genes succeeded (for recent reviews, see also Clapham 1998; Luthi and McCormick 1998a; Biel et al. 1999; Ludwig, Zong, Hofmann, et al. 1999; Santoro and Tibbs 1999).     

Weakly Circadian Cells Improve Resynchrony

The mammalian suprachiasmatic nuclei (SCN) contain thousands of neurons capable of generating near 24-h rhythms. When isolated from their network, SCN neurons exhibit a range of oscillatory phenotypes: sustained or damping oscillations, or arrhythmic patterns. The implications of this variability are unknown. Experimentally, we found that cells within SCN explants recover from pharmacologically-induced desynchrony by re-establishing rhythmicity and synchrony in waves, independent of their intrinsic circadian period We therefore hypothesized that a cell''s location within the network may also critically determine its resynchronization. To test this, we employed a deterministic, mechanistic model of circadian oscillators where we could independently control cell-intrinsic and network-connectivity parameters. We found that small changes in key parameters produced the full range of oscillatory phenotypes seen in biological cells, including similar distributions of period, amplitude and ability to cycle. The model also predicted that weaker oscillators could adjust their phase more readily than stronger oscillators. Using these model cells we explored potential biological consequences of their number and placement within the network. We found that the population synchronized to a higher degree when weak oscillators were at highly connected nodes within the network. A mathematically independent phase-amplitude model reproduced these findings. Thus, small differences in cell-intrinsic parameters contribute to large changes in the oscillatory ability of a cell, but the location of weak oscillators within the network also critically shapes the degree of synchronization for the population.     

Changes in P2X<Subscript>3</Subscript> purinoceptors in sensory ganglia of the mouse during embryonic and postnatal development

The expression of the P2X₃ nucleotide receptor in embryonic day 14–18, postnatal day 1–14 and adult mouse sensory ganglia was examined using immunohistochemistry. Nearly all sensory neurons in dorsal root ganglia, trigeminal ganglia and nodose ganglia in embryos at embryonic day 14 expressed P2X₃ receptors, but after birth there was a gradual decline to about 50% of neurons showing positive immunostaining for P2X₃. In embryos there were only small neurons, while from postnatal day 7 both large and small neurons were present. Isolectin B₄ (IB₄)-positive neurons in dorsal, trigeminal and nodose ganglia did not appear until birth, but the numbers increased to about 50% by postnatal day 14 when a high proportion of IB₄-positive neurons were also positively labelled for the P2X₃ receptor. About 10% of neurons in dorsal, trigeminal and nodose ganglia were positive for calcitonin gene-related peptide in embryos, nearly all of which stained for P2X₃ receptors. This increased postnatally to about 35–40% in adults, although only a few colocalised with P2X₃ receptors. Neurofilament 200 was expressed in about 50% of neurons in trigeminal ganglia in the embryo, and this level persisted postnatally. All neurofilament 200-positive neurons stained for P2X₃ in embryonic dorsal root ganglia, trigeminal ganglia and nodose ganglia, but by adulthood this was significantly reduced. The neurons that were positive for calbindin in embryonic dorsal, trigeminal and nodose ganglia showed colocalisation with P2X₃ receptors, but few showed colocalisation postnatally.     

Abnormal oscillatory synchronisation in the motor system leads to impaired movement

Converging data suggest that abnormal synchronised oscillatory activity in the basal ganglia may contribute to bradykinesia in patients with Parkinson's disease. This synchrony preferentially occurs over 10-30 Hz, the so-called beta band. Correlative evidence has been supplemented by experiments in which direct stimulation of the basal ganglia in the beta band slows movement. Yet questions remain regarding the small scale of the latter effects and whether synchrony is an early or even obligatory feature of parkinsonism. Nevertheless, the principle that abnormally synchronised activity in the beta band can disrupt the function finds a precedent in the syndrome of cortical myoclonus. Here, pathologically synchronised discharges of pyramidal neurons are transmitted to the healthy spinal cord. The result is the synchronous discharge of motor units leading to rhythmic jerking.     

Effects of the Activity of the Internal Globus Pallidus-Pedunculopontine Loop on the Transmission of the Subthalamic Nucleus-External Globus Pallidus-Pacemaker Oscillatory Activities to the Cortex

Resting tremor is the most specific sign for idiopathic Parkinson' disease. It has been proposed that parkinsonian tremor results from the activity of the central oscillators. One of the hypotheses, which have been proposed about the possible principles underlying such central oscillations, is the subthalamic nucleus (STN)-external globus pallidus (GPe)-pacemaker hypothesis. Activity from the central oscillator is proposed to be transmitted via trans-cortical pathways to the periphery. A computational model of the basal ganglia (BG) is proposed for simulating the effects of the internal globus pallidus (GPi)-pedunculopontine (PPN) loop activity on the transmission of the STN-GPe-pacemaker oscillatory activities to the cortex, based on known anatomy and physiology of the BG. According to the result of the simulation, the GPi-PPN loop activity can suppress the transmission of the STN-GPe-pacemaker oscillatory activities to the cortex. This suppressive effect is controlled by various factors such as the strength of the synaptic connection from the PPN to the GPi, the strength of the synaptic connection from the GPi to the PPN, the spontaneous tonic activities of the GPi and PPN, the direct excitatory projections from the STN to the PPN, the frequency of the STN oscillatory burst activity, the duration of the STN burst, and the maximum T-type calcium channel conductance in the type-I PPN neurons.     

PACEMAKER OSCILLATIONS IN HEART AND BRAIN: A KEY ROLE FOR HYPERPOLARIZATION-ACTIVATED CATION CHANNELS

Rhythmic activity of single cells or multicellular networks is a common feature of all organisms. The oscillatory activity is characterized by time intervals of several seconds up to many hours. Cellular rhythms govern the beating of the heart, the swimming behavior of sperm, cycles of sleep and wakefulness, breathing, and the release of hormones. Many neurons in the brain and cardiac cells are characterized by endogenous rhythmic activity, which relies on a complex interplay between several distinct ion channels. In particular, one type of ion channel plays a prominent role in the control of rhythmic electrical activity since it determines the frequency of the oscillations. The activity of the channels is thus setting the “pace” of the oscillations; therefore, these channels are often referred to as “pacemaker” channels. Despite their obvious important physiological function, it was not until recently that genes encoding pacemaker channels have been identified. Because both hyperpolarization and cyclic nucleotides are key elements that control their activity, pacemaker channels have now been designated hyperpolarization-activated and cyclic nucleotide–gated (HCN) channels. The molecular identification of the channels and the upcoming studies on their properties in heterologous systems will certainly enhance our understanding of “pacemaking” in physiological systems. This review gives a brief insight into the physiological importance of these channels and sums up what we have learned since the first cloning of genes succeeded (for recent reviews, see also Clapham 1998; Luüthi and McCormick 1998a; Biel et al. 1999; Ludwig, Zong, Hofmann, et al. 1999; Santoro and Tibbs 1999). (Chronobiology International, 17(4), 453–469, 2000)     

Modulation of two oscillatory networks in the peripheral olfactory system by gamma-aminobutyric acid, glutamate, and acetylcholine in the terrestrial slug Limax marginatus

The digit-like extensions (the digits) of the tentacular ganglion of the terrestrial slug Limax marginatus are the cell body rich region in the primary olfactory system, and they contain primary olfactory neurons and projection neurons that send their axons to the olfactory center via the tentacular nerves. Two cell clusters (the cell masses) at the bases of the digits form the other cell body rich regions. Although the spontaneous slow oscillations and odor responses in the tentacular nerve have been studied, the origin of the oscillatory activity is unknown. In the present study, we examined the contribution of the neurons in the digits and cell masses to generation of the tentacular nerve oscillations by surgical removal from the whole tentacle preparations. Both structures contributed to the tentacular oscillations, and surgical isolation of the digits from the whole tentacle preparations still showed spontaneous oscillations. To analyze the dynamics of odor-processing circuits in the digits and tentacular ganglia, we studied the effects of gamma-aminobutyric acid, glutamate, and acetylcholine on the circuit dynamics of the oscillatory network(s) in the peripheral olfactory system. Bath or local puff application of gamma-aminobutyric acid to the cell masses decreased the tentacular nerve oscillations, whereas the bath or local puff application of glutamate and acetylcholine to the digits increased the digits' oscillations. Our results suggest the existence of two intrinsic oscillatory circuits that respond differentially to endogenous neurotransmitters in the primary olfactory system of slugs.     

Failure of Delayed Feedback Deep Brain Stimulation for Intermittent Pathological Synchronization in Parkinson’s Disease

Suppression of excessively synchronous beta-band oscillatory activity in the brain is believed to suppress hypokinetic motor symptoms of Parkinson’s disease. Recently, a lot of interest has been devoted to desynchronizing delayed feedback deep brain stimulation (DBS). This type of synchrony control was shown to destabilize the synchronized state in networks of simple model oscillators as well as in networks of coupled model neurons. However, the dynamics of the neural activity in Parkinson’s disease exhibits complex intermittent synchronous patterns, far from the idealized synchronous dynamics used to study the delayed feedback stimulation. This study explores the action of delayed feedback stimulation on partially synchronized oscillatory dynamics, similar to what one observes experimentally in parkinsonian patients. We employ a computational model of the basal ganglia networks which reproduces experimentally observed fine temporal structure of the synchronous dynamics. When the parameters of our model are such that the synchrony is unphysiologically strong, the feedback exerts a desynchronizing action. However, when the network is tuned to reproduce the highly variable temporal patterns observed experimentally, the same kind of delayed feedback may actually increase the synchrony. As network parameters are changed from the range which produces complete synchrony to those favoring less synchronous dynamics, desynchronizing delayed feedback may gradually turn into synchronizing stimulation. This suggests that delayed feedback DBS in Parkinson’s disease may boost rather than suppress synchronization and is unlikely to be clinically successful. The study also indicates that delayed feedback stimulation may not necessarily exhibit a desynchronization effect when acting on a physiologically realistic partially synchronous dynamics, and provides an example of how to estimate the stimulation effect.     

Modelling of cortical and thalamic 600 Hz activity by means of oscillatory networks

The purpose of this study is to investigate information processing in the primary somatosensory system with the help of oscillatory network modelling. Specifically, we consider interactions in the oscillatory 600 Hz activity between the thalamus and the cortical Brodmann areas 3b and 1. This type of cortical activity occurs after electrical stimulation of peripheral nerves such as the median nerve. Our measurements consist of simultaneous 31-channel MEG and 32-channel EEG recordings and individual 3D MRI data. We perform source localization by means of a multi-dipole model. The dipole activation time courses are then modelled by a set of coupled oscillators, described by linear second-order ordinary delay differential equations (DDEs). In particular, a new model for the thalamic activity is included in the oscillatory network. The parameters of the DDE system are successfully fitted to the data by a nonlinear evolutionary optimization method. To activate the oscillatory network, an individual input function is used, based on measurements of the propagated stimulation signal at the biceps. A significant feedback from the cortex to the thalamus could be detected by comparing the network modelling with and without feedback connections. Our finding in humans is supported by earlier animal studies. We conclude that this type of rhythmic brain activity can be modelled by oscillatory networks in order to disentangle feed forward and feedback information transfer.     

Two coupled oscillators as a model for the coordinated finger tapping by both hands

Recently, it was found that rhythmic movements (e.g. locomotion, swimmeret beating) are controlled by mutually coupled endogeneous neural oscillators (Kennedy and Davis, 1977; Pearson and Iles, 1973; Stein, 1974; Shik and Orlovsky, 1976; Grillner and Zangger, 1979). Meanwhile, it has been found out that the phase resetting experiment is useful to investigate the interaction of neural oscillators (Perkel et al., 1963; Stein, 1974). In the preceding paper (Yamanishi et al., 1979), we studied the functional interaction between the neural oscillator which is assumed to control finger tapping and the neural networks which control some tasks. The tasks were imposed on the subject as the perturbation of the phase resetting experiment. In this paper, we investigate the control mechanism of the coordinated finger tapping by both hands. First, the subjects were instructed to coordinate the finger tapping by both hands so as to keep the phase difference between two hands constant. The performance was evaluated by a systematic error and a standard deviation of phase differences. Second, we propose two coupled neural oscillators as a model for the coordinated finger tapping. Dynamical behavior of the model system is analyzed by using phase transition curves which were measured on one hand finger tapping in the previous experiment (Yamanishi et al., 1979). Prediction by the model is in good agreement with the results of the experiments. Therefore, it is suggested that the neural mechanism which controls the coordinated finger tapping may be composed of a coupled system of two neural oscillators each of which controls the right and the left finger tapping respectively.     

Striatal information signaling and integration in globus pallidus: timing matters

Advances in research on globus pallidus (GP) suggest that this 'long thought to be' relay in the 'indirect pathway' plays a unique and critical role in basal ganglia function. The traditional idea of parallel processing within the basal ganglia is also challenged by recent findings. It is now clear that axons of GP neurons form large, perisomatic baskets around target neurons in all major basal ganglia nuclei, thereby exerting a profound influence on the output of the entire basal ganglia. GP neurons are autonomously active both in vivo and in vitro. It is believed that temporal information carried along the corticostriatopallidal pathway is critical for proper motor execution. The importance of appropriately controlled discharge of GP neurons is highlighted by psychomotor disorders such as Parkinson's disease, in which alterations in the pattern and synchrony of discharge in GP neurons are thought to contribute to motor symptoms. Several lines of evidence suggest that the aberrant activity of GP neurons following dopamine depletion is caused by alteration in the synaptic input from both striatum and subthalamic nucleus. In normal subjects, the capability of striatal input in translating cortical input into precisely timed responses in GP neurons is mediated by (1) the expression of postsynaptic GABA(A) receptor composed of subunits with fast kinetic properties; (2) an effective GABA reuptake system in terminating the action of synaptically released GABA, and (3) the existence of dendritic HCN channels that actively abbreviate the time course of the inhibitory postsynaptic potentials and reset rhythmic discharge. Despite the rapid pace in uncovering the elements that shape the activity along the striatopallidosubthalamic pathway, the origin of rhythmic, synchronized bursting of GP neurons seen in parkinsonism has not been fully established experimentally. Further elucidation of the factors that control the information transfer in the striatopallidal synapses is thus critical to our understanding of basal ganglia function and establishing treatment for Parkinson's disease and other basal ganglia disorders.     

Oscillatory network with self-organized dynamical connections for synchronization-based image segmentation

An oscillatory network of columnar architecture located in 3D spatial lattice was recently designed by the authors as oscillatory model of the brain visual cortex. Single network oscillator is a relaxational neural oscillator with internal dynamics tunable by visual image characteristics - local brightness and elementary bar orientation. It is able to demonstrate either activity state (stable undamped oscillations) or "silence" (quickly damped oscillations). Self-organized nonlocal dynamical connections of oscillators depend on oscillator activity levels and orientations of cortical receptive fields. Network performance consists in transfer into a state of clusterized synchronization. At current stage grey-level image segmentation tasks are carried out by 2D oscillatory network, obtained as a limit version of the source model. Due to supplemented network coupling strength control the 2D reduced network provides synchronization-based image segmentation. New results on segmentation of brightness and texture images presented in the paper demonstrate accurate network performance and informative visualization of segmentation results, inherent in the model.     

Respiratory pattern generator model using Ca++-induced Ca++ release in neurons shows both pacemaker and reciprocal network properties

There are two contradictory explanations for central respiratory rhythmogenesis. One suggests that respiratory rhythm emerges from interaction between inspiratory and expiratory neural semicenters that inhibit each other and thereby provide reciprocal rhythmic activity (Brown 1914). The other uses bursting pacemaker activity of individual neurons to produce the rhythm (Feldman and Cleland 1982). Hybrid models have been developed to reconcile these two seemingly conflicting mechanisms (Smith et al. 2000; Rybak et al. 2001). Here we report computer simulations that demonstrate a unified mechanism of the two types of oscillator. In the model, we use the interaction of Ca⁺⁺-dependent K⁺ channels (Mifflin et al. 1985) with Ca⁺⁺-induced Ca⁺⁺ release from intracellular stores (McPherson and Campbell 1993), which was recently revealed in neurons (Hernandez-Cruz et al. 1997; Mitra and Slaughter 2002a,b; Scornik et al. 2001). Our computations demonstrate that uncoupled neurons with these intracellular mechanisms show conditional pacemaker properties (Butera et al. 1999) when exposed to steady excitatory inputs. Adding weak inhibitory synapses (based on increased K⁺ conductivity) between two model neural pools surprisingly synchronizes the activity of both neural pools. As inhibitory synaptic connections between the two pools increase from zero to higher values, the model produces first dissociated pacemaker activity of individual neurons, then periodic synchronous bursts of all neurons (inspiratory and expiratory), and finally reciprocal rhythmic activity of the neural pools.     

Binding and segmentation of multiple objects through neural oscillators inhibited by contour information

 Temporal correlation of neuronal activity has been suggested as a criterion for multiple object recognition. In this work, a two-dimensional network of simplified Wilson-Cowan oscillators is used to manage the binding and segmentation problem of a visual scene according to the connectedness Gestalt criterion. Binding is achieved via original coupling terms that link excitatory units to both excitatory and inhibitory units of adjacent neurons. These local coupling terms are time independent, i.e., they do not require Hebbian learning during the simulations. Segmentation is realized by a two-layer processing of the visual image. The first layer extracts all object contours from the image by means of “retinal cells” with an “on-center” receptive field. Information on contour is used to selectively inhibit Wilson-Cowan oscillators in the second layer, thus realizing a strong separation among neurons in different objects. Accidental synchronism between oscillations in different objects is prevented with the use of a global inhibitor, i.e., a global neuron that computes the overall activity in the Wilson-Cowan network and sends back an inhibitory signal. Simulations performed in a 50×50 neural grid with 21 different visual scenes (containing up to eight objects + background) with random initial conditions demonstrate that the network can correctly segment objects in almost 100% of cases using a single set of parameters, i.e., without the need to adjust parameters from one visual scene to the next. The network is robust with reference to dynamical noise superimposed on oscillatory neurons. Moreover, the network can segment both black objects on white background and vice versa and is able to deal with the problem of “fragmentation.” The main limitation of the network is its sensitivity to static noise superimposed on the objects. Overcoming this problem requires implementation of more robust mechanisms for contour enhancement in the first layer in agreement with mechanisms actually realized in the visual cortex. Received: 25 October 2001 / Accepted: 26 February 2003 / Published online: 20 May 2003 Correspondence to: Mauro Ursino (e-mail: mursino@deis.unibo.it, Tel.: +39-051-2093008, Fax: +39-051-2093073)     

动态神经网络中的同步振荡

目前有一种假设认为同一视觉对象是由一群神经元的同步振荡活动来表征的。这一神经元发放活动的时间特性,是解决视觉信息处理中“结合问题（Ｂｉｎｄｉｎｇｐｒｏｂｌｅｍ）”的可能机制。本文用我们所提出的一种简化现实性神经网络模型［１］所构造的时滞非线性振子网络［２］,模拟生物神经网络的同步振荡活动。并考虑了振子各参数的设置与振荡活动的关系,以及网络振子间耦联对同步活动的影响．     

Sustained neural rhythms reveal endogenous oscillations supporting speech perception

Rhythmic sensory or electrical stimulation will produce rhythmic brain responses. These rhythmic responses are often interpreted as endogenous neural oscillations aligned (or “entrained”) to the stimulus rhythm. However, stimulus-aligned brain responses can also be explained as a sequence of evoked responses, which only appear regular due to the rhythmicity of the stimulus, without necessarily involving underlying neural oscillations. To distinguish evoked responses from true oscillatory activity, we tested whether rhythmic stimulation produces oscillatory responses which continue after the end of the stimulus. Such sustained effects provide evidence for true involvement of neural oscillations. In Experiment 1, we found that rhythmic intelligible, but not unintelligible speech produces oscillatory responses in magnetoencephalography (MEG) which outlast the stimulus at parietal sensors. In Experiment 2, we found that transcranial alternating current stimulation (tACS) leads to rhythmic fluctuations in speech perception outcomes after the end of electrical stimulation. We further report that the phase relation between electroencephalography (EEG) responses and rhythmic intelligible speech can predict the tACS phase that leads to most accurate speech perception. Together, we provide fundamental results for several lines of research—including neural entrainment and tACS—and reveal endogenous neural oscillations as a key underlying principle for speech perception.

Just as a child on a swing continues to move after the pushing stops, this study reveals similar entrained rhythmic echoes in brain activity after hearing speech and electrical brain stimulation; perturbation with tACS shows that these brain oscillations help listeners to understand speech.     

Cellular principles underlying normal and pathological activity in the subthalamic nucleus

The motor symptoms of Parkinson's disease are associated with abnormal, correlated, low frequency, rhythmic burst activity in the subthalamic nucleus and connected nuclei. Research into the mechanisms controlling the pattern of subthalamic activity has intensified because therapies that manipulate the pattern of subthalamic activity, such as deep brain stimulation and levodopa administration, improve motor function in Parkinson's disease. Recent findings suggest that dopamine denervation of the striatum and extrastriatal basal ganglia profoundly alters the transmission and integration of glutamatergic cortical and GABAergic pallidal inputs to subthalamic neurons, leading to pathological activity that resonates throughout the basal ganglia and wider motor system.