Simulation of the motor units control during a fast elbow flexion in the sagittal plane

Analysis of angiotensin II-Induced rat urinary bladder contractions in the presence of angiotensin II receptors blockers

OBJECTIVE

An application of a specific analysis on recordings obtained from urinary bladder (UB) preparations influenced with Angiotensin II (AngII) and AngII receptor (ATR) blockers was performed.

METHODS

UB preparations were divided as follows: group 1 stimulated with AngII only; group 2:PD123319 (ATR type-2 blocker)+AngII; group 3:Losartan (ATR type-1 blocker)+AngII. The averaged time and force parameters of the contractions were processed by a spline interpolation and graphic images of the different patterns of the contractile activity were obtained.

RESULTS

The speed of AngII-induced UB contraction, when PD123319 was administered, was significantly higher than those, registered by the application of AngII alone and Losartan + AngII. The presence of Losartan markedly delayed the speed of the overall AngII-induced contraction.

CONCLUSION

The study indicates the contribution of both ATR subtypes for the development of AngII-induced UB contraction. Our results showed that probably ATR mediate a reciprocal dynamic response to AngII in the bladder.

Variability of the twitch parameters of the rat medial gastrocnemius motor units—experimental and modeling study

In the present study a previously proposed model of a twitch based on an analytical function with four-parameters (lead, contraction and half-relaxation times and maximum force of the twitch) was validated on 115 motor units (MUs), divided into slow (S), fast-fatigue resistant (FR) and fast fatigable (FF) types. The original records were collected from electrophysiological experiments performed on MUs from the medial gastrocnemius muscle of five rats. Besides the easy calculation of the twitch parameters and their variability, the usefulness of the model was confirmed by eliminating artifacts and noise in the original twitch records, as well as by calculations of the velocity of force increase and decrease, the area under force records, and by normalization of all twitches with respect to the maximal force and contraction time. It was concluded that: (1) the four-parameter twitch model describes precisely the individual contractions of various MUs; (2) all physiological twitch parameters are distributed continuously and located within overlapping intervals for different MU types; this distribution is not linear, but exponential; (3) S MUs can be distinguished from fast ones on the basis of some twitch parameters (contraction and half-relaxation times, velocity of contraction), but the same cannot be applied for FF and FR MUs; (4) the analysis of the normalized twitches reveals the differences in shapes for different types of MUs, which shows that twitches of different MUs cannot be obtained from one standard pattern scaled in time and force. These results may have functional implications for studying effectiveness of twitch summation during tetanic contractions and the work performed by various types of MUs.

Variability of successive contractions subtracted from unfused tetanus of fast and slow motor units

Stimulation of motor units (MUs) with repeated pulses evokes tetanic contractions, which consist of overlapping mechanical responses. The summation of these responses into tetanus is a nonlinear process due to the dynamic changes in the amplitudes and time parameters of the successive components. In order to study these changes, two MUs (one fast and one slow) of rat medial gastrocnemius muscle were stimulated with a progressively increasing number of pulses, from one (i=1) to sixteen (i=16) at a frequency of 15 Hz for the slow MU and 60 Hz for the fast MU. The individual responses were calculated by subtracting the (i)th from the (i+1)th tetanus recording. The contractions obtained following subtraction were modeled using a novel 6-parameter analytical function. The main conclusions of this study are (1) the newly presented analytical function is able to precisely describe the variable shape of all subtracted experimental contractions; (2) the shapes of successive contractions are variable and the subtracted contractions differ from the individual twitches; (3) as the pulse number increases, the parameters of the subtracted contractions change in a different manner for the slow and fast MUs: for the slow MU, the maximal forces and the time parameters increase considerably up to the 4th response, after which they remain nearly constant or show only a slight increase; for the fast MU, the maximal forces and durations also increase, whereas the remaining time parameters initially increase and then maintain a constant level or decrease, which explains the sag phenomenon visible in the unfused tetanus of fast MUs.

Modeling investigation of learning a fast elbow flexion in the horizontal plane--prediction of muscle forces and motor units action

Experimental investigation of practicing a dynamic, goal-directed movement reveals significant changes in kinematics. Modeling can provide insight into the alterations in muscle activity, associated with the kinematic adaptations, and reveal the potential motor unit (MU) firing patterns that underlie those changes. In this paper, a previously developed muscle model and software (Raikova and Aladjov, Journal of Biomechanics, 35, 2002) have been used to investigate changes in MU control, while practicing fast elbow flexion to a target in the horizontal plane. The first trial (before practice) and the last trial (after extensive practice) of two subjects have been simulated. The inputs for the simulation were the calculated external moments at the elbow joint. The external moments were countered by the action of three flexor muscles and two extensor ones. The muscles have been modeled as a mixture of MUs of different types. The software has chosen the MU firing times necessary to accomplish the movement. The muscle forces and MUs firing statistics were then calculated. Three hypotheses were tested and confirmed: (1) peak muscle forces and antagonist co-contraction increase during training; (2) there is an increase in the firing frequency and the synchronization between MUs; and (3) the recruitment of fast-twitch MUs dominates the action.

Experimental and modelling investigation of learning a fast elbow flexion in the horizontal plane

Changes in the kinematic and electromyographic characteristics that occur while learning to move as fast as possible have been studied experimentally. Experimental investigation of what happens to the individual motor units (MUs) is more difficult. Access to each MU is impossible, and the recruitment and force developing properties of all individual MUs cannot be known. Thus, what is currently known about MU firing is based on experiments that have recorded relatively few MUs compared to what exists in the entire muscle. A recently developed muscle model (Raikova and Aladjov, 2002, J. Biomechanics, 35, 1123-1135) composed of MUs with different properties can be used for such investigation. The process of learning fast elbow flexion in the horizontal plane was simulated and the results were compared with experimentally measured data. Comparing the simulation results of the very first trial of a particular subject with those of the last trail (at the end of the learning process), it can be concluded that the speed of limb motion and muscle forces increase initially as a result of the more synchronous MUs activation and the increase of firing rate of active MUs. Further improvement necessitated an appreciable reduction in the motor task requirements (i.e. less muscle force and less MUs' activity) set in the computational algorithm by optimization criteria. This forced the next process-inclusion of additional MUs.