Dynamics of brain rhythmic and evoked potentials

In this study, the simultaneously recorded and selectively averaged evoked potentials in some of the structures of the auditory pathway (acoustical cortex, medial geniculate nucleus, inferior colliculus), in the reticular formation and the hippocampus of the cat during sleep as well as the simultaneous amplitude frequency characteristics of these structures are given. The power spectral density functions computed from the simultaneously recorded spontaneous activities of these structures are also presented. Using these results, the following analyses are accomplished:(1) determination of the dynamics of potentials simultaneously obtained from various structures, in order to evaluate the common features of their system characteristics; (2) determination of the relationship (or interactions) between rhythmic activity and evoked potentials of the brain.     

Dynamics of brain rhythmic and evoked potentials

In this study, the simultaneously recorded and selectively averaged evoked potentials in some of the structures of the auditory pathway (acoustical cortex, medial geniculate nucleus, inferior colliculus), in the reticular formation and the hippocampus of the awake cat as well as the simultaneous amplitude frequency characteristics of these structures are given. The power spectral density functions computed from the simultaneously recorded spontaneous activity of these structures are also presented. Using these results, the following analyses are accomplished: (1) determination of the dynamics of potentials simultaneously obtained from various brain structures, in order to evaluate the common features of their system characteristics; (2) determination of the relationship (or interactions) between rhythmic activity and evoked potentials of the brain, and (3) elaboration of a working hypothesis for the dynamics of potentials of the brain. Some suggestions and comments are also made for investigators working toward theories or dynamic models of signal transmission in the brain.     

Dynamics of brain rhythmic and evoked potentials

A package of methods and an experimental set-up for the analysis of dynamics of electrical signals from the brain. The methods described and discussed in this study allow detailed and multipurpose analysis of brain potentials both in the time and frequency domains. Special emphasis is given to a new computer-method introduced in this study: A posteriori selective averaging. The selective averaging method is compared with Wiener Filter Estimation of Evoked Potentials.     

Photoperiodism and rhythmic response to light

Abstract. Seedlings of Pharhitis nil show a circadian rhythm in the capacity to flower in response to the timing of a second red light pulse given at various times after a first saturating exposure to red when this is given together with a benzyladeninc spray. There are also changes in the photon irradiance required for half maximum response to the second red pulse. The photochemical properties of phytochrome in the photoperiodically sensitive cotyledons were also shown to change rhythmically. Oscillations in both p_r→ P_fr and P_fr→ P_r photoconversion characteristics persisted over at least two circadian cycles with a periodicity of about 12 h. There were, however, no significant oscillations in either P_fr peak absorbance or in Δ(ΔA). The changes in sensitivity for the photoconversion of P_r→ P_fr did not parallel the much larger changes in sensitivity of the flowering response to red light. The amplitude of the P_r→ P_fr rhythm was at least as great as that for P_r→ P_fr, but the flowering response to far-red light was not rhythmic, nor was there any large change in sensitivity. The changes in photoconversion properties may reflect a basic biochemical oscillation which affects both photoreceptor properties and sensitivity to photoreceptor input. There was also a marked rhythm in the P_fr/P ratio that would be established by a saturating pulse of red light and this too may have affected the flowering response to such a pulse. Far-red light inhibited flowering when given at any time during the inductive night. After 14 h in darkness, P_fr could still be measured in the cotyledons and it was concluded that far-red light inhibited flowering by removing P_fr As red light also inhibited flowering at this time, there may be two pools of phytochrome with different kinetic properties.     

Development of rhythmic pattern generators

In contrast to the wealth of knowledge about the organizational rules of adult central pattern generators, far less is known about how these networks are assembled during development. The basic architecture for adult central pattern generators appears early in development but different generators may follow completely different developmental pathways to reach maturity. Recent evidence suggests that neuromodulatory inputs, in addition to their short-term adaptive control of central pattern generator activity, play a crucial role in both the final developmental tuning and the long-term maintenance of adult network function.     

Serotonin regulates rhythmic whisking

Many rodents explore their environment by rhythmically palpating objects with their mystacial whiskers. These rhythmic whisker movements ("whisking"; 5-9 Hz) are thought to be regulated by an unknown brainstem central pattern generator (CPG). We tested the hypothesis that serotonin (5-HT) inputs to whisking facial motoneurons (wFMNs) are part of this CPG. In response to exogenous serotonin, wFMNs recorded in vitro fire rhythmically at whisking frequencies, and selective 5-HT2 or 5-HT3 receptor antagonists suppress this rhythmic firing. In vivo, stimulation of brainstem serotonergic raphe nuclei evokes whisker movements. Unilateral infusion of selective 5-HT2 or 5-HT3 receptor antagonists suppresses ipsilateral whisking and substantially alters the frequencies and symmetry of whisker movements. These findings suggest that serotonin is both necessary and sufficient to generate rhythmic whisker movements and that serotonergic premotoneurons are part of a whisking CPG.     

Model of brain rhythmic activity

1. A model of a neuronal network has been set up in a digital computer based on histological and biophysical data experimentally obtained from the thalamus; the model includes two populations of neurons interconnected by means of negative feedback; in the model allowance is also made for other sort of interactions.
2. To test the hypothesis that the alpha-rhythm (8–13 Hz rhythmic activity characteristic of the EEG) is a filtered noise signal the simulated neuronal network was stimulated by random trains of pulses with a Poisson distribution. The density of pulses fired by the simulated neurons was computed as well as the oscillations of the mean membrane potential of the population of simulated neurons. The latter was found to be equivalent to the experimentally obtained alpha rhythms.
3. In order to test the hypothesis that several noise sources are responsible for thalamo-cortical coherences three simulated neuronal networks were coupled together using several noise sources as secondary inputs. It was shown that although all the networks produced simulated alpha signals with identical spectra they could have significantly different values of coherence depending on the relation between correlated and uncorrelated input signals.
4. The model was analysed by means of linear systems analysis after introducing the necessary simplifications and approximations. In this way it was possible to evaluate the influence of different physiological or histological parameters upon the statistical properties of the resulting rhythmic activity in an analytical form.
5. By changing the model parameters it was shown that a family of spectral curves could be obtained which simulated the development of the EEG as function of age from a predominantly low frequency to a clearly rhythmic type of signal. This was shown to depend mainly on the feedback coupling parameters.

     

Simulation of rhythmic nervous activities

Zusammenfassung Die überschwellige Dauererregung mehrerer Jenik-Modellneurone würde bei jedem einzelnen zu einer ununterbrochenen Dauerentladung führen. Auf Grund des hier vorgestellten Verschaltungsprinzips der sog. Zyklischen Hemmung sind die Elemente jedoch über Hemmungsleitungen in zyklischer Weise miteinander verkoppelt, wodurch zeitlich definierte, periodisch sich wiederholende, gegenseitige Erregungsunterdrückungen erreicht werden. Das heißt: trotz gleichförmiger Eingangserregung zeigen die Neuronenmodelle am Ausgang ein burst-artiges Entladungsmuster.Der für einen solchen Burst-Generator endlicher Folgefrequenz notwendige Verzögerungsmechanismus ist dadurch gegeben, daß die Modellneurone nach erfolgter Hemmung eine ausreichend lange Erholphase durchlaufen müssen, bevor sie wieder in den aktiven Entladungszustand gelangen. Die Länge dieser Erholphase ist abhängig von den Parametern des Erregungs- und Hemmeinganges (Frequenz, Amplitude, PSP-Zeitkonstante), also von außen steuerbar.Zwei verschiedene Typen von zyklischen Netzwerken werden untersucht. In den einfachen Netzwerken werden Ausgangs- (Erregungs-) und Zwischen- (Hemmungs-) Nervenzelle durch ein und dasselbe Modellneuron repräsentiert. Beliebig viele, jedoch mindestens 3 Einzelelemente umfaßt ein solcher Burst-Generator (N3), wobei jedes Element in Hemmrichtung maximal bis zu M _maxN–2 Nachbarelemente hemmend beeinflussen kann. Diese streng rotationssymmetrische Hemmungsverschaltung garantiert das charakteristische rhythmische Ausgangsmuster der periodischen Erregungsumläufe, indem die Modellneurone entgegen dem Hemmrichtungssinn nacheinander in Bursts entladen.Im Unterschied zu den einfachen Netzwerken wird — als mögliche Annäherung an die physiologischen Gegebenheiten — in den sog. komplexen Netzwerken der Hemmeinfluß jedes Ausgangselementes über ein eigenes Zwischen- (Hemmungs-) Element ausgeübt. Die Vielfalt der Ausgangs-Zeitmuster kann dadurch erheblich gesteigert werden.Die Ausgangsmuster beider Netzwerktypen können bei gegebener Struktur als Funktion der Erholphase errechnet werden. Die Nützlichkeit dieser Netzwerke als biologisches Modell liegt vielleicht gerade darin, daß die das Zeitverhalten bestimmende Erholphase von den Eingangsgrößen direkt gesteuert wird, d. h. die Werte der Eingangsparameter werden in eine Zeitgröße (der Länge der Erholphase) umgesetzt. Mit noch zusätzlicher zeitabhängiger und asymmetrischer Variation dieser Eingangsparameter an den Einzelelementen stellt ein derartiges Netzwerk ein vielseitiges und flexibles Steuerinstrument für die verschiedensten (periodischen) Vorgänge dar.Obwohl es aus der Biologie noch keinen direkten Beweis für das Vorhandensein einer derartigen Hemmungsverkopplung gibt, sind andererseits rückführende Hemmverbindungen und Neurone mit relativ langer Hyperpolarisationsphase bekannt. Im Rückenmark, Septum, Ammonshorn und Thalamus sind in der Literatur ähnliche Neuronenaktivitäten beschrieben, die unsere Modellvorstellung unterstützen.     

Deterministic and stochastic features of rhythmic human movement

The dynamics of rhythmic movement has both deterministic and stochastic features. We advocate a recently established analysis method that allows for an unbiased identification of both types of system components. The deterministic components are revealed in terms of drift coefficients and vector fields, while the stochastic components are assessed in terms of diffusion coefficients and ellipse fields. The general principles of the procedure and its application are explained and illustrated using simulated data from known dynamical systems. Subsequently, we exemplify the method’s merits in extracting deterministic and stochastic aspects of various instances of rhythmic movement, including tapping, wrist cycling and forearm oscillations. In particular, it is shown how the extracted numerical forms can be analysed to gain insight into the dependence of dynamical properties on experimental conditions.     

Modulation of circuits underlying rhythmic behaviors

Summary What have we learned about behavior from neuromodulatory studies of the crustacean stomatogastric system? The emphasis of this paper has been on the analysis of one single class of behaviors (rhythmic) in terms of microcircuitry (synaptic connections between identified neurons). But in the general case, all behaviors result from the generation of spatio-temporal patterns by the central nervous system. How individual nerve cells interact with each other to produce such patterns is of fundamental interest. We know from work on simple networks that it is possible to link the circuitry of the nervous system with behavior in a precise way, and that instead of a large number of dedicated circuits, behaviors can be altered by chemically adjusting the functional properties of the neuronal elements. One circuit can be configured to perform a variety of different behaviors by activating neurons which contain neuromodulatory substances or in response to neurohormones circulating in the hemolymph. At present we know only a few of the ways neuromodulatory neurons are triggered to release their contents onto the neurons making up CPGs.The findings described here raise many questions. What are the parameters which control the distribution of neuromodulatory substances throughout the nervous system? What happens when more than one neuromodulator is present? At the cellular level, what mechanisms are involved in transforming each neuron from one functional state to another, and then how does the entire constellation of changes give rise to a new output? It is important to answer such questions in reduced networks, because there are presently no techniques available to answer them in the more complex networks of the brain. While there is no question that modulatory activity occurs in the brain, whether or not the principles which have been discovered by using simple invertebrate circuits scale up to vertebrate circuits remains an intriguing question.     

Modulation of Hydra Attentuata rhythmic activity

Here we analyse the previous results concerning the effects of photic and electric stimulation on the contraction-relaxation behaviour of Hydra, the existence of a potential difference between the two extremities of the animal, its rhythmic variation in time, its modulation by luminous environmental changes as well as the contraction pulse variations dependent on the luminous stimulation itself and the complex overt behaviour of an electrically stimulated animal. A model of the mechanism responsible for the rhythmic activity, which takes into account the above results as well as the already known anatomical and physiological data, is given. This model is based on the mutual inhibitory interaction of the two pacemaker systems responsible for the contraction and relaxation outputs, on the post inhibitory rebound after the received inhibition, which rebound constitutes the activity phase of each of them, and on the different weight of the activity exerted by each of them.