Axonal and synaptic failure suppress the transfer of firing rate oscillations, synchrony and information during high frequency deep brain stimulation

High frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a widely used treatment for Parkinson's disease, but its effects on neural activity in basal ganglia circuits are not fully understood. DBS increases the excitation of STN efferents yet decouples STN spiking patterns from the spiking patterns of STN synaptic targets. We propose that this apparent paradox is resolved by recent studies showing an increased rate of axonal and synaptic failures in STN projections during DBS. To investigate this hypothesis, we combine in vitro and in vivo recordings to derive a computational model of axonal and synaptic failure during DBS. Our model shows that these failures induce a short term depression that suppresses the synaptic transfer of firing rate oscillations, synchrony and rate-coded information from STN to its synaptic targets. In particular, our computational model reproduces the widely reported suppression of parkinsonian β oscillations and synchrony during DBS. Our results support the idea that short term depression is a therapeutic mechanism of STN DBS that works as a functional lesion by decoupling the somatic spiking patterns of STN neurons from spiking activity in basal ganglia output nuclei.

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data.

Short-term synaptic depression and stochastic vesicle dynamics reduce and shape neuronal correlations

Correlated neuronal activity is an important feature in many neural codes, a neural correlate of a variety of cognitive states, as well as a signature of several disease states in the nervous system. The cellular and circuit mechanics of neural correlations is a vibrant area of research. Synapses throughout the cortex exhibit a form of short-term depression where increased presynaptic firing rates deplete neurotransmitter vesicles, which transiently reduces synaptic efficacy. The release and recovery of these vesicles are inherently stochastic, and this stochasticity introduces variability into the conductance elicited by depressing synapses. The impact of spiking and subthreshold membrane dynamics on the transfer of neuronal correlations has been studied intensively, but an investigation of the impact of short-term synaptic depression and stochastic vesicle dynamics on correlation transfer is lacking. We find that short-term synaptic depression and stochastic vesicle dynamics can substantially reduce correlations, shape the timescale over which these correlations occur, and alter the dependence of spiking correlations on firing rate. Our results show that short-term depression and stochastic vesicle dynamics need to be taken into account when modeling correlations in neuronal populations.

Short term synaptic depression imposes a frequency dependent filter on synaptic information transfer

Depletion of synaptic neurotransmitter vesicles induces a form of short term depression in synapses throughout the nervous system. This plasticity affects how synapses filter presynaptic spike trains. The filtering properties of short term depression are often studied using a deterministic synapse model that predicts the mean synaptic response to a presynaptic spike train, but ignores variability introduced by the probabilistic nature of vesicle release and stochasticity in synaptic recovery time. We show that this additional variability has important consequences for the synaptic filtering of presynaptic information. In particular, a synapse model with stochastic vesicle dynamics suppresses information encoded at lower frequencies more than information encoded at higher frequencies, while a model that ignores this stochasticity transfers information encoded at any frequency equally well. This distinction between the two models persists even when large numbers of synaptic contacts are considered. Our study provides strong evidence that the stochastic nature neurotransmitter vesicle dynamics must be considered when analyzing the information flow across a synapse.

β-Adrenergic modulation of spontaneous spatiotemporal activity patterns and synchrony in hyperexcitable hippocampal circuits

A description of healthy and pathological brain dynamics requires an understanding of spatiotemporal patterns of neural activity and characteristics of its propagation between interconnected circuits. However, the structure and modulation of the neural activation maps underlying these patterns and their propagation remain elusive. We investigated effects of β-adrenergic receptor (β-AR) stimulation on the spatiotemporal characteristics of emergent activity in rat hippocampal circuits. Synchronized epileptiform-like activity, such as interictal bursts (IBs) and ictal-like events (ILEs), were evoked by 4-aminopyridine (4-AP), and their dynamics were studied using a combination of electrophysiology and fast voltage-sensitive dye imaging. Dynamic characterization of the spontaneous IBs showed that they originated in dentate gyrus/CA3 border and propagated toward CA1. To determine how β-AR modulates spatiotemporal characteristics of the emergent IBs, we used the β-AR agonist isoproterenol (ISO). ISO significantly reduced the spatiotemporal extent and propagation velocity of the IBs and significantly altered network activity in the 1- to 20-Hz range. Dual whole cell recordings of the IBs in CA3/CA1 pyramidal cells and optical analysis of those regions showed that ISO application reduced interpyramidal and interregional synchrony during the IBs. In addition, ISO significantly reduced duration not only of the shorter duration IBs but also the prolonged ILEs in 4-AP. To test whether the decrease in ILE duration was model dependent, we used a different hyperexcitability model, zero magnesium (0 Mg(2+)). Prolonged ILEs were readily formed in 0 Mg(2+), and addition of ISO significantly reduced their durations. Taken together, these novel results provide evidence that β-AR activation dynamically reshapes the spatiotemporal activity patterns in hyperexcitable circuits by altering network rhythmogenesis, propagation velocity, and intercellular/regional synchronization.

Membrane potential and spike train statistics depend distinctly on input statistics

A description of how the activity of a population of neurons reflects the structure of its inputs is essential for understanding neural coding. Many studies have examined how inputs determine spiking statistics, while comparatively little is known about membrane potentials. We examine how membrane potential statistics are related to input and spiking statistics. Surprisingly, firing rates and membrane potentials are sensitive to input current modulations in distinct regimes. Additionally, the correlation between the membrane potentials of two uncoupled cells and the correlation between their spike trains reflect input correlations in distinct regimes. Our predictions are experimentally testable, provide insight into the filtering properties of neurons, and indicate that care needs to be taken when interpreting neuronal recordings that reflect a combination of subthreshold and spiking activity.

Finite volume and asymptotic methods for stochastic neuron models with correlated inputs

We consider a pair of stochastic integrate and fire neurons receiving correlated stochastic inputs. The evolution of this system can be described by the corresponding Fokker-Planck equation with non-trivial boundary conditions resulting from the refractory period and firing threshold. We propose a finite volume method that is orders of magnitude faster than the Monte Carlo methods traditionally used to model such systems. The resulting numerical approximations are proved to be accurate, nonnegative and integrate to 1. We also approximate the transient evolution of the system using an Ornstein-Uhlenbeck process, and use the result to examine the properties of the joint output of cell pairs. The results suggests that the joint output of a cell pair is most sensitive to changes in input variance, and less sensitive to changes in input mean and correlation.

The effects of pooling on spike train correlations

Neurons integrate inputs from thousands of afferents. Similarly, some experimental techniques record the pooled activity of large populations of cells. When cells in these populations are correlated, the correlation coefficient between the collective activity of two subpopulations is typically much larger than the correlation coefficient between individual cells: The act of pooling individual cell signals amplifies correlations. We give an overview of this phenomenon and present several implications. In particular, we show that pooling leads to synchronization in feedforward networks and that it can amplify and otherwise distort correlations between recorded signals.

Mechanisms that modulate the transfer of spiking correlations

Correlations between neuronal spike trains affect network dynamics and population coding. Overlapping afferent populations and correlations between presynaptic spike trains introduce correlations between the inputs to downstream cells. To understand network activity and population coding, it is therefore important to understand how these input correlations are transferred to output correlations.Recent studies have addressed this question in the limit of many inputs with infinitesimal postsynaptic response amplitudes, where the total input can be approximated by gaussian noise. In contrast, we address the problem of correlation transfer by representing input spike trains as point processes, with each input spike eliciting a finite postsynaptic response. This approach allows us to naturally model synaptic noise and recurrent coupling and to treat excitatory and inhibitory inputs separately.We derive several new results that provide intuitive insights into the fundamental mechanisms that modulate the transfer of spiking correlations.

Assessment and treatment for insomnia and fatigue in the symptomatic menopausal woman with psychiatric comorbidity

Studies and treatments for the symptomatic menopausal woman with sleep complaints have been reviewed elsewhere. This article, as part of the clinical review series on the comorbid symptomatic menopausal woman, aims to examine the evidence for diagnosis and treatment of women who present with distressing sleep symptoms that they attribute to menopause. The etiology of these symptoms may be a psychiatric disorder, a pre- or co-existing problem with sleep, or a dynamic interaction among one of these and/or a symptomatic menopause. The relationship between sleep disturbance and cognitive complaints, mood problems, fatigue and low energy will be reviewed. The new research on sleep, clinical consequences of insomnia of various types, the impact of sleep disturbance on morbidity and functioning--in the context of the midlife woman in the menopausal transition--will be explored along with the evidence for different treatment strategies for these sleep problems.

Robotic extraperitoneal radical prostatectomy: an alternative approach

PURPOSE

Laparoscopic radical prostatectomy with or without a robot has been increasingly performed worldwide, primarily using a transperitoneal approach. We report our experience with daVinci(R) robot assisted extraperitoneal laparoscopic radical prostatectomy.

MATERIALS AND METHODS

A total of 325 patients underwent robot assisted extraperitoneal laparoscopic radical prostatectomy for clinically localized prostate cancer at our center during a 2-year period. Perioperative data, and oncological and functional results were prospectively recorded.

RESULTS

Perioperative demographics included mean age, PSA and Gleason score, which were 60 years (range 42 to 76), 6.6 ng/ml (range 0.6 to 26) and 6 (range 5 to 9), respectively. Preoperative clinical stage was 81%, 16% and 3% for T1c, T2a and T2b, respectively. Average total operative time was 130 minutes (range 80 to 480). Intraoperative data included a mean blood loss of 196 cc with no open conversions. Bilateral, unilateral and nonnerve sparing prostatectomy was performed in 70%, 24% and 6% of patients, respectively. Of the patients 96% were discharged home within 8 to 23 hours of surgery. Pathological stage was pT2a, pT2b, pT3a and pT3b in 18%, 63%, 14% and 5% of all radical prostatectomy specimens, respectively, with an overall positive surgical margin rate of 13%. Two of 92 patients had positive nodal disease after lymph node dissection. Continence and erectile function were measured.

CONCLUSIONS

The extraperitoneal approach offers the advantages of improved dexterity and visualization of the robot, while avoiding the abdominal cavity and potential associated morbidity. As surgeons gain more experience with this new technology, the extraperitoneal approach simulating the standard open retropubic technique is likely to gain popularity.

Neuromuscular complications of connective tissue diseases

The connective tissue diseases, such as rheumatoid arthritis, Sjögren's syndrome, systemic lupus erythematosus, systemic sclerosis, and vasculitis, may cause various disorders of the peripheral nervous system. In this review, the clinical effects of the connective tissues diseases on nerve and muscle are examined with particular attention to mononeuritis multiplex, distal symmetric neuropathy, fulminant motor neuropathy, compression neuropathy, sensory neuronopathy, and trigeminal sensory neuropathy.