Ih tunes theta/gamma oscillations and cross-frequency coupling in an in silico CA3 model.

Ih channels are uniquely positioned to act as neuromodulatory control points for tuning hippocampal theta (4-12 Hz) and gamma (25 Hz) oscillations, oscillations which are thought to have importance for organization of information flow. contributes to neuronal membrane resonance and resting membrane potential, and is modulated by second messengers. We investigated oscillatory control using a multiscale computer model of hippocampal CA3, where each cell class (pyramidal, basket, and oriens-lacunosum moleculare cells), contained type-appropriate isoforms of . Our model demonstrated that modulation of pyramidal and basket allows tuning theta and gamma oscillation frequency and amplitude. Pyramidal also controlled cross-frequency coupling (CFC) and allowed shifting gamma generation towards particular phases of the theta cycle, effected via 's ability to set pyramidal excitability. Our model predicts that in vivo neuromodulatory control of allows flexibly controlling CFC and the timing of gamma discharges at particular theta phases.

A translational platform for prototyping closed-loop neuromodulation systems.

While modulating neural activity through stimulation is an effective treatment for neurological diseases such as Parkinson's disease and essential tremor, an opportunity for improving neuromodulation therapy remains in automatically adjusting therapy to continuously optimize patient outcomes. Practical issues associated with achieving this include the paucity of human data related to disease states, poorly validated estimators of patient state, and unknown dynamic mappings of optimal stimulation parameters based on estimated states. To overcome these challenges, we present an investigational platform including: an implanted sensing and stimulation device to collect data and run automated closed-loop algorithms; an external tool to prototype classifier and control-policy algorithms; and real-time telemetry to update the implanted device firmware and monitor its state. The prototyping system was demonstrated in a chronic large animal model studying hippocampal dynamics. We used the platform to find biomarkers of the observed states and transfer functions of different stimulation amplitudes. Data showed that moderate levels of stimulation suppress hippocampal beta activity, while high levels of stimulation produce seizure-like after-discharge activity. The biomarker and transfer function observations were mapped into classifier and control-policy algorithms, which were downloaded to the implanted device to continuously titrate stimulation amplitude for the desired network effect. The platform is designed to be a flexible prototyping tool and could be used to develop improved mechanistic models and automated closed-loop systems for a variety of neurological disorders.

Ketamine disrupts θ modulation of γ in a computer model of hippocampus.

Abnormalities in oscillations have been suggested to play a role in schizophrenia. We studied theta-modulated gamma oscillations in a computer model of hippocampal CA3 in vivo with and without simulated application of ketamine, an NMDA receptor antagonist and psychotomimetic. Networks of 1200 multicompartment neurons [pyramidal, basket, and oriens-lacunosum moleculare (OLM) cells] generated theta and gamma oscillations from intrinsic network dynamics: basket cells primarily generated gamma and amplified theta, while OLM cells strongly contributed to theta. Extrinsic medial septal inputs paced theta and amplified both theta and gamma oscillations. Exploration of NMDA receptor reduction across all location combinations demonstrated that the experimentally observed ketamine effect occurred only with isolated reduction of NMDA receptors on OLMs. In the ketamine simulations, lower OLM activity reduced theta power and disinhibited pyramidal cells, resulting in increased basket cell activation and gamma power. Our simulations predict the following: (1) ketamine increases firing rates; (2) oscillations can be generated by intrinsic hippocampal circuits; (3) medial-septum inputs pace and augment oscillations; (4) pyramidal cells lead basket cells at the gamma peak but lag at trough; (5) basket cells amplify theta rhythms; (6) ketamine alters oscillations due to primary blockade at OLM NMDA receptors; (7) ketamine alters phase relationships of cell firing; (8) ketamine reduces network responsivity to the environment; (9) ketamine effect could be reversed by providing a continuous inward current to OLM cells. We suggest that this last prediction has implications for a possible novel treatment for cognitive deficits of schizophrenia by targeting OLM cells.

Advancing neuromodulation using a dynamic control framework.

The current state of neuromodulation can be cast in a classical dynamic control framework such that the nervous system is the classical "plant", the neural stimulator is the controller, tools to collect clinical data are the sensors, and the physician's judgment is the state estimator. This framework characterizes the types of opportunities available to advance neuromodulation. In particular, technology can potentially address two dominant factors limiting the performance of the control system: "observability," the ability to observe the state of the system from output measurements, and "controllability," the ability to drive the system to a desired state using control actuation. Improving sensors and actuation methods are necessary to address these factors. Equally important is improving state estimation by understanding the neural processes underlying diseases. Development of enabling technology to utilize control theory principles facilitates investigations into improving intervention as well as research into the dynamic properties of the nervous system and mechanisms of action of therapies. In this paper, we provide an overview of the control system framework for neuromodulation, its practical challenges, and investigational devices applying this framework for limited applications. To help motivate future efforts, we describe our chronically implantable, low-power neural stimulation system, which integrates sensing, actuation, and state estimation. This research system has been implanted and used in an ovine to address novel research questions.

Ketamine modulates theta and gamma oscillations.

Ketamine, an N-methyl-D-aspartate (NMDA) receptor glutamatergic antagonist, has been studied as a model of schizophrenia when applied in subanesthetic doses. In EEG studies, ketamine affects sensory gating and alters the oscillatory characteristics of neuronal signals in a complex manner. We investigated the effects of ketamine on in vivo recordings from the CA3 region of mouse hippocampus referenced to the ipsilateral frontal sinus using a paired-click auditory gating paradigm. One issue of particular interest was elucidating the effect of ketamine on background network activity, poststimulus evoked and induced activity. We find that ketamine attenuates the theta frequency band in both background activity and in poststimulus evoked activity. Ketamine also disrupts a late, poststimulus theta power reduction seen in control recordings. In the gamma frequency range, ketamine enhances both background and evoked power, but decreases relative induced power. These findings support a role for NMDA receptors in mediating the balance between theta and gamma responses to sensory stimuli, with possible implications for dysfunction in schizophrenia.

Synaptic noise and physiological coupling generate high-frequency oscillations in a hippocampal computational model.

There is great interest in the role of coherent oscillations in the brain. In some cases, high-frequency oscillations (HFOs) are integral to normal brain function, whereas at other times they are implicated as markers of epileptic tissue. Mechanisms underlying HFO generation, especially in abnormal tissue, are not well understood. Using a physiological computer model of hippocampus, we investigate random synaptic activity (noise) as a potential initiator of HFOs. We explore parameters necessary to produce these oscillations and quantify the response using the tools of stochastic resonance (SR) and coherence resonance (CR). As predicted by SR, when noise was added to the network the model was able to detect a subthreshold periodic signal. Addition of basket cell interneurons produced two novel SR effects: 1) improved signal detection at low noise levels and 2) formation of coherent oscillations at high noise that were entrained to harmonics of the signal frequency. The periodic signal was then removed to study oscillations generated only by noise. The combined effects of network coupling and synaptic noise produced coherent, periodic oscillations within the network, an example of CR. Our results show that, under normal coupling conditions, synaptic noise was able to produce gamma (30-100 Hz) frequency oscillations. Synaptic noise generated HFOs in the ripple range (100-200 Hz) when the network had parameters similar to pathological findings in epilepsy: increased gap junctions or recurrent synaptic connections, loss of inhibitory interneurons such as basket cells, and increased synaptic noise. The model parameters that generated these effects are comparable with published experimental data. We propose that increased synaptic noise and physiological coupling mechanisms are sufficient to generate gamma oscillations and that pathologic changes in noise and coupling similar to those in epilepsy can produce abnormal ripples.

Sensitivity to motion features in point light displays of biological motion.

Psychophysical experiments are described that measure the sensitivity to motion features in point light displays of biological motion. Three motion features were investigated: the relative motion of the thighs, the relative motion of the thigh and leg, and the velocity profile of the leg. The perceptual threshold for discriminating a change in each motion feature was compared in upright and inverted point light displays. We find that subjects are more sensitive to two of the motion features in the upright display configuration (relative motion of thighs, relative motion of thigh and leg), but more sensitive to the third feature (velocity profile of the leg) in the inverted configuration. We propose that perceptual sensitivity to features used in biological motion perception should be greater in upright versus inverted displays. The results suggest that motion features differ in salience in biological motion perception.

NMDA/AMPA ratio impacts state transitions and entrainment to oscillations in a computational model of the nucleus accumbens medium spiny projection neuron.

We describe a computational model of the principal cell in the nucleus accumbens (NAcb), the medium spiny projection (MSP) neuron. The model neuron, constructed in NEURON, includes all of the known ionic currents in these cells and receives synaptic input from simulated spike trains via NMDA, AMPA, and GABAA receptors. After tuning the model by adjusting maximal current conductances in each compartment, the model cell closely matched whole-cell recordings from an adult rat NAcb slice preparation. Synaptic inputs in the range of 1000-1300 Hz are required to maintain an "up" state in the model. Cell firing in the model required concurrent depolarization of several dendritic branches, which responded independently to afferent input. Depolarization from action potentials traveled to the tips of the dendritic branches and increased Ca2+ influx through voltage-gated Ca2+ channels. As NMDA/AMPA current ratios were increased, the membrane showed an increase in hysteresis of "up" and "down" state dwell times, but intrinsic bistability was not observed. The number of oscillatory inputs required to entrain the model cell was determined to be approximately 20% of the "up" state inputs. Altering the NMDA/AMPA ratio had a profound effect on processing of afferent input, including the ability to entrain to oscillations in afferent input in the theta range (4-12 Hz). These results suggest that afferent information integration by the NAcb MSP cell may be compromised by pathology in which the NMDA current is altered or modulated, as has been proposed in both schizophrenia and addiction.

Quantitative morphometry of hippocampal pyramidal cells: differences between anatomical classes and reconstructing laboratories.

The dendritic trees of hippocampal pyramidal cells play important roles in the establishment and regulation of network connectivity, synaptic plasticity, and firing dynamics. Several laboratories routinely reconstruct CA3 and CA1 dendrites to correlate their three-dimensional structure with biophysical, electrophysiological, and anatomical observables. To integrate and assess the consistency of the quantitative data available to the scientific community, we exhaustively analyzed 143 completely reconstructed neurons intracellularly filled and digitized in five different laboratories from 10 experimental conditions. Thirty morphometric parameters, including the most common neuroanatomical measurements, were extracted from all neurons. A consistent fraction of parameters (11 of 30) was significantly different between CA3 and CA1 cells. A considerably large number of parameters was also found that discriminated among neurons within the same morphological class, but reconstructed in different laboratories. These interlaboratory differences (8 of 30 parameters) far outweighed the differences between experimental conditions within a single lab, such as aging or preparation method (at most two significant parameters). The set of morphometrics separating anatomical regions and that separating reconstructing laboratories were almost entirely nonoverlapping. CA3 and CA1 neurons could be distinguished by global quantities such as branch order and Sholl distance. Differences among laboratories were largely due to local variables such as branch diameter and local bifurcation angles. Only one parameter (a ratio of branch diameters) separated both morphological classes and reconstructing laboratories. Compartmental simulations of electrophysiological activity showed that both differences between anatomical classes and reconstructing laboratories could dramatically affect the firing rate of these neurons under different experimental conditions.

Principal component analysis of temporal and spatial information for human gait recognition.

Principal component analysis was applied to human gait patterns to investigate the role and relative importance of temporal versus spatial features. Datasets consisted of various limb and body angles sampled over increasingly long time intervals. We find that spatial and temporal cues may be useful for different aspects of recognition. Temporal cues contain information that can distinguish the phase of the gait cycle; spatial cues are useful for distinguishing running from walking. PCA and related techniques may be useful for identifying features used by the visual system for recognizing biological motion.

A new bursting model of CA3 pyramidal cell physiology suggests multiple locations for spike initiation.

We introduce a novel computational model of hippocampal pyramidal cells physiology based on an up-to-date, detailed description of passive and active biophysical properties and real dendritic morphology. This model constitutes a modification of a previous (1995) model which included complex calcium dynamics and Na(+), K(+), and Ca(2+) currents. Changes reflect recently acquired experimental knowledge regarding the types and spatial distributions of these currents. The updated model responds to simulated somatic current clamp stimulation with a train of spikes (burst). The shape of the burst reproduces the characteristic behavior observed experimentally, similarly to the previous model. However, an analysis of dendritic membrane voltage distribution during the burst shows that the mechanisms underlying this somatic behavior are dramatically different in the two models. In the previous model, all spikes were generated in the soma and backpropagated in the dendrites. In the updated model, in contrast, only the first spike is initiated somatically. The second somatic spike is preceded by a dendritic spike (triggered by the first spike backpropagation), which propagates both backward and forward, reaching the soma just before the rise of the second somatic spike. The third and fourth spikes are similarly caused by a complex spatio-temporal interplay between somatic and dendritic depolarization. These results suggest that the distribution of ionic currents recently characterized in hippocampal pyramidal cells can support both somatic and dendritic spike initiation. In addition, these simulations demonstrate that models with considerably different distributions of active conductances can reproduce the same experimental bursting behavior with distinct biophysical mechanisms.