Neuromodulation influences synchronization and intrinsic read-out

Background: The roles of neuromodulation in a neural network, such as in a cortical microcolumn, are still incompletely understood. Neuromodulation influences neural processing by presynaptic and postsynaptic regulation of synaptic efficacy. Neuromodulation also affects ion channels and intrinsic excitability.

Methods: Synaptic efficacy modulation is an effective way to rapidly alter network density and topology. We alter network topology and density to measure the effect on spike synchronization. We also operate with differently parameterized neuron models which alter the neuron's intrinsic excitability, i.e., activation function.

Results: We find that (a) fast synaptic efficacy modulation influences the amount of correlated spiking in a network. Also, (b) synchronization in a network influences the read-out of intrinsic properties. Highly synchronous input drives neurons, such that differences in intrinsic properties disappear, while asynchronous input lets intrinsic properties determine output behavior. Thus, altering network topology can alter the balance between intrinsically vs. synaptically driven network activity.

Conclusion: We conclude that neuromodulation may allow a network to shift between a more synchronized transmission mode and a more asynchronous intrinsic read-out mode. This has significant implications for our understanding of the flexibility of cortical computations.

Neuromodulation influences synchronization and intrinsic read-out

Background: The roles of neuromodulation in a neural network, such as in a cortical microcolumn, are still incompletely understood. Neuromodulation influences neural processing by presynaptic and postsynaptic regulation of synaptic efficacy. Neuromodulation also affects ion channels and intrinsic excitability. Methods: Synaptic efficacy modulation is an effective way to rapidly alter network density and topology. We alter network topology and density to measure the effect on spike synchronization. We also operate with differently parameterized neuron models which alter the neuron's intrinsic excitability, i.e., activation function. Results: We find that (a) fast synaptic efficacy modulation influences the amount of correlated spiking in a network. Also, (b) synchronization in a network influences the read-out of intrinsic properties. Highly synchronous input drives neurons, such that differences in intrinsic properties disappear, while asynchronous input lets intrinsic properties determine output behavior. Thus, altering network topology can alter the balance between intrinsically vs. synaptically driven network activity. Conclusion: We conclude that neuromodulation may allow a network to shift between a more synchronized transmission mode and a more asynchronous intrinsic read-out mode. This has significant implications for our understanding of the flexibility of cortical computations.

Logarithmic distributions prove that intrinsic learning is Hebbian

In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas examined. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears to be a general, functional property in all cases analyzed. We then created a generic neural model to investigate adaptive learning rules that create and maintain lognormal distributions. We conclusively demonstrate that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This provides a solution to the long-standing question about the type of plasticity exhibited by intrinsic excitability.

Logarithmic distributions prove that intrinsic learning is Hebbian

In this paper, we document lognormal distributions for spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears as a functional property that is present everywhere.  Secondly, we created a generic neural model to show that Hebbian learning will create and maintain lognormal distributions. We could prove with the model that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This settles a long-standing question about the type of plasticity exhibited by intrinsic excitability.

Ist 91Zr-Festkörper-Kernresonanzspektroskopie praktikabel?

91Zr solid state NMR spectra have been observed for samples possessing different zirconium local-site environments (e.g. phosphates, fluorides). Depending on the quadrupole coupling, different NMR experiments have been utilized. In case of weak quadrupole coupling, magic angle spinning (MAS) is suitable. Otherwise, spin echo techniques are necessary to overcome “acoustic ringing’’ and receiver dead-time limitations. Using the step echo method, the detection of the very broad 91Zr signals is not limited by non-uniform spectral excitation. The obtained 91Zr chemical shifts range from -246 ppm to 208 ppm, the quadrupole coupling frequencies from 50 kHz to 2.7 MHz..

Self-organization of signal transduction

We propose a model of parameter learning for signal transduction, where the objective function is defined by signal transmission efficiency. We apply this to learn kinetic rates as a form of evolutionary learning, and look for parameters which satisfy the objective. This is a novel approach compared to the usual technique of adjusting parameters only on the basis of experimental data. The resulting model is self-organizing, i.e. perturbations in protein concentrations or changes in extracellular signaling will automatically lead to adaptation. We systematically perturb protein concentrations and observe the response of the system. We find compensatory or co-regulation of protein expression levels. In a novel experiment, we alter the distribution of extracellular signaling, and observe adaptation based on optimizing signal transmission. We also discuss the relationship between signaling with and without transients. Signaling by transients may involve maximization of signal transmission efficiency for the peak response, but a minimization in steady-state responses. With an appropriate objective function, this can also be achieved by concentration adjustment. Self-organizing systems may be predictive of unwanted drug interference effects, since they aim to mimic complex cellular adaptation in a unified way.

Transfer functions for protein signal transduction: application to a model of striatal neural plasticity

We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of “source” species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the “target” species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.

Learning intrinsic excitability in medium spiny neurons

We present an unsupervised, local activation-dependent learning rule for intrinsic plasticity (IP) which affects the composition of ion channel conductances for single neurons in a use-dependent way. We use a single-compartment conductance-based model for medium spiny striatal neurons in order to show the effects of parameterization of individual ion channels on the neuronal membrane potential-curent relationship (activation function). We show that parameter changes within the physiological ranges are sufficient to create an ensemble of neurons with significantly different activation functions. We emphasize that the effects of intrinsic neuronal modulation on spiking behavior require a distributed mode of synaptic input and can be eliminated by strongly correlated input. We show how modulation and adaptivity in ion channel conductances can be utilized to store patterns without an additional contribution by synaptic plasticity (SP). The adaptation of the spike response may result in either "positive" or "negative" pattern learning. However, read-out of stored information depends on a distributed pattern of synaptic activity to let intrinsic modulation determine spike response. We briefly discuss the implications of this conditional memory on learning and addiction.

Spatial intralobar correlation of spike and slow wave activity localisations in focal epilepsies: A MEG analysis

12 patients with focal epilepsy were examined by magnetoencephalography (MEG). Source localisations of interictal epileptiform activity (spikes) yielded clear results. Slow wave dipole density in the frequency range from 2 to 6 Hz, using time selections from an automatic principal component analysis (PCA), was calculated. Results of spike and slow wave dipole density localisations were superimposed on MR-images of each patient. Slow wave dipole densities were increased close to spike localisations. Distances between spike center of mass and slow wave maxima were calculated, average mean distance was 2.0 cm. Independant of the localisation in either TLE or ETLE a concordance of slow wave and spike localisations were found. Slow wave localisations were found in patients with lesions in MRI and patients with no abnormalities on the MRI. In comparison to healthy subjects, slow wave dipole density in patients with epilepsy was clearly increased. The localisation of slow wave dipole density yielded additional important information and may contribute to defining the irritative zone.

Periventricular nodular heterotopia: A challenge for epilepsy surgery

Pharmacoresistant focal epilepsies due to periventricular nodular heterotopia are a diagnostic and therapeutic challenge because of the need of invasive presurgical diagnostics and the selection of an optimal surgical approach. Invasive investigations in previous studies showed that focal epileptic activity can be correlated predominantly either with one of the nodular heterotopia or with neocortical epileptogenic zones distant to the periventricular nodules. Up to now, invasive recordings were required for localization of epileptic activity and its correlation to heterotopia. The following case presentation reports on a non-invasive approach using magnetic source imaging (MSI) combined with intraoperative ECoG. MSI combines preoperative data from magnetic resonance imaging (MRI) with magnetoencephalography (MEG). The MSI data for definition of the localization of the epileptic activity and functional important areas were coregistered with the intraoperative high-field-MRI and diffusion tensor imaging-based fiber tracking (DTI) of the visual pathway using a neuronavigational system. A neuronavigation-guided surgical resection of the epileptogenic area was performed leaving the heterotopia and the visual tract fibers intact. Postoperatively preservation of the visual fields was documented and the frequency of seizures was markedly reduced.

Magnetoencephalography (MEG) predicts focal epileptogenicity in cavernomas

OBJECTIVE

The aim of this study was to identify the irritative epileptic zone in patients with cavernomas by means of magnetoencephalography (MEG).

METHOD

Among 82 patients operated for epilepsy, whose presurgical evaluation had included MEG, histological assessment of the tissue removed had confirmed cavernomas in eight. These eight patients had epilepsy since 18.6 (SD 12.7) years on average. The monitoring lasted about 2.1 (SD 1.3) hours and a median 20.9 (SD 14.3) spikes per hour were recorded. Spontaneous brain activity was recorded by means of a 74 channel dual unit MEG system (Magnes II, 4-D Neuroimaging) with simultaneous EEG recording (31 scalp electrodes). Spike analysis was performed using different source (moving dipole, current density reconstruction) and head models (spherical shells, BEM). Co-registration of neurophysiological and imaging data (MRI) was based upon anatomical landmarks.

RESULTS

In 6/8 patients co-localisation from the cavernoma and epileptic zone was found. In two patients the focus was localised in the parieto-occipital lobe, in three patients in the frontal lobe and in three patients in the temporal lobe. In one case of temporal and one case of frontal lobe focus localisation there was no spatial relationship to the cavernoma.

CONCLUSION

In cases of focal seizures due to a single cavernoma, MEG may precisely delineate the epileptogenic tissue bordering the lesion. In patients with multiple cavernomas or dual pathology, MSI may reveal the complexity of the case, and contribute to the decision about further invasive diagnostics and more sophisticated therapeutic measures. MEG is a promising method for prediction of the epileptic zone in cavernoma related epilepsies, and thus it can contribute to decision making about and planning of epilepsy surgery.

Regulation of neuromodulator receptor efficacy—implications for whole-neuron and synaptic plasticity

Membrane receptors for neuromodulators (NM) are highly regulated in their distribution and efficacy-a phenomenon which influences the individual cell's response to central signals of NM release. Even though NM receptor regulation is implicated in the pharmacological action of many drugs, and is also known to be influenced by various environmental factors, its functional consequences and modes of action are not well understood. In this paper we summarize relevant experimental evidence on NM receptor regulation (specifically dopamine D1 and D2 receptors) in order to explore its significance for neural and synaptic plasticity. We identify the relevant components of NM receptor regulation (receptor phosphorylation, receptor trafficking and sensitization of second-messenger pathways) gained from studies on cultured cells. Key principles in the regulation and control of short-term plasticity (sensitization) are identified, and a model is presented which employs direct and indirect feedback regulation of receptor efficacy. We also discuss long-term plasticity which involves shifts in receptor sensitivity and loss of responsivity to NM signals. Finally, we discuss the implications of NM receptor regulation for models of brain plasticity and memorization. We emphasize that a realistic model of brain plasticity will have to go beyond Hebbian models of long-term potentiation and depression. Plasticity in the distribution and efficacy of NM receptors may provide another important source of functional plasticity with implications for learning and memory.

Epilepsy surgery, resection volume and MSI localization in lesional frontal lobe epilepsy

To verify whether interictal noninvasive information detected by magnetoencephalography (MEG) recordings can contribute to localize focal epileptic activity relevant for seizure generation in lesional frontal lobe epilepsy, magnetic source imaging (MSI) localizations of epileptic discharges were compared to the extent of neurosurgical resection and postoperative outcome. Preoperative MEG spike localizations were displayed in postoperative magnetic resonance imaging (MRI) scans to check whether dipole sites were located within the resection cavity. Moreover, MEG localizations were compared with results of prolonged video-EEG monitoring and, in three cases, with invasive EEG recordings. Our results in five cases with lesional frontal lobe epilepsy showed that good surgical outcome could be achieved in those patients where the majority of MEG spike localizations were located within the resected brain volume.

Magnetic brain source imaging of focal epileptic activity: a synopsis of 455 cases

Epilepsy surgery is based upon the minute assessment of brain tissue generating epileptic activity. A number of diagnostic methods are employed in the process of presurgical evaluation, supplying information on various morphological and functional aspects, ultimately integrated into the general result fundamental to the final treatment decision. Magnetic source imaging (MSI), combining structural (MRI) and functional (MEG) data, has been playing an increasingly important role among the tools of presurgical epilepsy evaluation. However, in spite of a considerable number of publications, the samples used have hardly exceeded 50 cases. Therefore, we present a synopsis of 455 epilepsy patients who underwent MSI investigations. Analysis of this substantial data revealed that the average sensitivity of MEG for specific epileptic activity was 70%. Among 131 patients who underwent surgical therapy in addition to antiepileptic drug medication, MSI identified the lobe to be treated in 89%, with results for extratemporal cases being even superior to those with temporal lobe surgery. Introducing a measure to quantify the contribution of MSI to the general result of presurgical evaluation that was applied to 104 patients, the results showed that MSI supplied additional information in 35% and information crucial to final decision making in 10%. Accuracy as well as contribution findings underlined MSI appropriateness even for extratemporal epilepsies, which otherwise frequently prove difficult with respect to focus localization.

The musician's brain: functional imaging of amateurs and professionals during performance and imagery

We compared activation maps of professional and amateur violinists during actual and imagined performance of Mozart's violin concerto in G major (KV216). Execution and imagination of (left hand) fingering movements of the first 16 bars of the concerto were performed. Electromyography (EMG) feedback was used during imagery training to avoid actual movement execution and EMG recording was employed during the scanning of both executed and imagined musical performances. We observed that professional musicians generated higher EMG amplitudes during movement execution and showed focused cerebral activations in the contralateral primary sensorimotor cortex, the bilateral superior parietal lobes, and the ipsilateral anterior cerebellar hemisphere. The finding that professionals exhibited higher activity of the right primary auditory cortex during execution may reflect an increased strength of audio-motor associative connectivity. It appears that during execution of musical sequences in professionals, a higher economy of motor areas frees resources for increased connectivity between the finger sequences and auditory as well as somatosensory loops, which may account for the superior musical performance. Professionals also demonstrated more focused activation patterns during imagined musical performance. However, the auditory-motor loop was not involved during imagined performances in either musician group. It seems that the motor and auditory systems are coactivated as a consequence of musical training but only if one system (motor or auditory) becomes activated by actual movement execution or live musical auditory stimuli.

Determination of distributions of the quadrupole interaction in amorphous solids by 27Al satellite transition spectroscopy

27Al Satellite transition spectroscopy (SATRAS) has been used to extract both the quadrupole interaction and its distribution width from MAS spectra of glasses. Using this method a measurement at a single magnetic field strength allows one to obtain the true chemical shifts and the quadrupole interaction (and its distributions) with high accuracy, including quantification of the results. In contrast to earlier investigations the central transition MAS lineshapes can be described without assumptions and give correct relative proportions of differently coordinated Al species in glasses. The distribution model for the quadrupole interaction and the resulting MAS lineshapes are discussed in detail including a description of the experimental requirements. Experimental results of 27Al SATRAS spectra of a ternary Al2O3-B2O3-P2O5 glass exhibiting 4-, 5-, and 6-coordinated aluminum species clearly prove different mean values and distribution widths for the quadrupole interaction in the various AlOx polyhedra.