Scaling Our World View: How Monoamines Can Put Context Into Brain Circuitry

Human short-latency reflexes show precise short-term gain adaptation after prior motion

The central nervous system adapts the gain of short-latency reflex loops to changing conditions. Experiments on biomimetic robots showed that reflex modulation could substantially increase energy efficiency and stability of periodic motions if, unlike known mechanisms, the reflex modulation both acted precisely on the muscles involved and lasted after the motion. This study tests the presence of such a mechanism by having participants repeatedly rotate either their right elbow or shoulder joint before perturbing either joint. The results demonstrate a mechanism that modulates short-latency reflex gains after prior motion with joint-specific precision. Enhanced gains were observed hundreds of milliseconds after movement cessation, a timescale well suited to quickly adapt overall periodic motion cycles. A serotonin antagonist significantly decreased these postmovement gains diffusely across joints. But blocking serotonin did not affect the joint specificity of the gain scaling more than a placebo, suggesting that serotonin sets the overall reflex gain across joints after movement by an effect that is modulated in a joint-specific manner by an unidentified neural circuit. These results confirm the existence of a new, joint-specific, fast, persistent adaptation of short-latency reflex loops induced by motion in human arms.NEW & NOTEWORTHY Our results expose a new spinal cord mechanism that modulates motoneuron gains, uniquely equipped to adapt movement in changing environments: it acts with joint-specific precision, reacts quickly to mechanical changes, and still persists long enough to accumulate information across movement cycles. The overall motoneuron gain across joints can be scaled down by an antagonist to serotonergic neuromodulation, whereas its joint specificity is unaffected by the antagonist and thus due to a complementary, unknown spinal mechanism.

An LC-MS/MS method for simultaneous analysis of up to six monoamines from brain tissues

Monoamines are a class of neuromodulators that are crucial for a variety of brain functions, including control of mood, movement, sleep and cognition. From mammals to insects, the nervous system is enriched in monoamines such as dopamine, serotonin and melatonin, analytes which range from being highly polar to non-polar. Here we developed a method using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to quantify in a single run the amounts of six distinct monoamines in extracts from dissected Drosophila and mouse brain tissues. The measured monoamines were dopamine (DA), serotonin (also known as 5-hydroxytryptamine (5-HT)), octopamine (OA, an insect equivalent of norepinephrine), tyramine (TA), melatonin (MT) and N-acetylserotonin (NAS). The analytical range of these monoamines was between 0.25 and 5.0 ng/mL. This quantitative LC-MS/MS methodology has important use for simultaneous measurement of distinct neuroactive monoamines from precious biological specimens.

The effects of α-lactalbumin supplementation and handgrip contraction on soleus motoneuron excitability

INTRODUCTION

We tested two strategies that hypothetically increase serotonin availability (α-lactalbumin consumption and a remote submaximal handgrip contraction) on estimates of persistent inward currents (PICs) amplitude of soleus muscle in healthy participants.

METHODS

With a randomised, double-blind, and cross-over design, 13 healthy participants performed triangular-shaped ramp contractions with their plantar flexors (20% of maximal torque), followed by a 30-s handgrip sustained contraction (40% of maximal force) and consecutive repeated triangular-shaped contractions. This was performed before and after the consumption of either 40 g of α-lactalbumin, an isonitrogenous beverage (Zein) or an isocaloric beverage (Corn-starch). Soleus motor units discharge rates were analysed from high-density surface electromyography signals. PICs were estimated by calculating the delta frequency (ΔF) of motor unit train spikes using the paired motor unit technique.

RESULTS

ΔF (0.19 pps; p = 0.001; d = 0.30) and peak discharge rate (0.20 pps; p < 0.001; d = 0.37) increased after the handgrip contraction, irrespective of the consumed supplement. No effects of α-lactalbumin were observed.

CONCLUSIONS

Our results indicate that 40 g of α-lactalbumin was unable to modify intrinsic motoneuron excitability. However, performing a submaximal handgrip contraction before the plantar flexion triangular contraction was capable of increasing ΔF and discharge rates on soleus motor units. These findings highlight the diffused effects of serotonergic input, its effects on motoneuron discharge behaviour, and suggest a cross-effector effect within human motoneurons.

Effects of α-lactalbumin on strength, fatigue and psychological parameters: a randomised double-blind cross-over study

PURPOSE

The neurotransmitter serotonin has a strong effect on behaviour and motor control. Regarding motor control, serotonin contributes to the development of fatigue and is also involved in the ability of motor neurones to operate across a large range of forces (gain control). The consumption of tryptophan-rich supplements (such as α-lactalbumin) is of interest because this amino acid is the only precursor for brain serotonin synthesis. Therefore, the purpose of this study was to determine the effects of α-lactalbumin supplementation on neuromuscular performance.

METHODS

Using a randomised double-blind cross-over design, 16 healthy participants performed plantar flexor and handgrip maximal voluntary contractions, a 30-s submaximal handgrip contraction, and a plantar flexor fatigue protocol before and 90 min after consuming either 40 g of α-lactalbumin, an isonitrogenous beverage (Zein) or an isocaloric beverage (corn-starch). Sleepiness, mood, and cognition were assessed to evaluate any psychological effects.

RESULTS

α-Lactalbumin decreased force steadiness by 25% during the sustained submaximal handgrip contraction (p < 0.01) and induced greater fatigue (15% reduction in total torque-time integral, p = 0.01) during the fatigue protocol. These effects were not observed for the other control beverages. No effects were found for maximal or explosive strength, or psychological measurements.

CONCLUSIONS

40 g of α-lactalbumin increased handgrip force variability and reduced performance during fatiguing muscle contractions but did not influence brief maximal contractions or psychological parameters in healthy individuals. These findings support the hypothesis that the consumption of α-lactalbumin can increase motor neurone input-output gain and exacerbate central fatigue during sustained maximal exercise.

Adapting Highly-Dynamic Compliant Movements to Changing Environments: A Benchmark Comparison of Reflex- vs. CPG-Based Control Strategies

To control highly-dynamic compliant motions such as running or hopping, vertebrates rely on reflexes and Central Pattern Generators (CPGs) as core strategies. However, decoding how much each strategy contributes to the control and how they are adjusted under different conditions is still a major challenge. To help solve this question, the present paper provides a comprehensive comparison of reflexes, CPGs and a commonly used combination of the two applied to a biomimetic robot. It leverages recent findings indicating that in mammals both control principles act within a low-dimensional control submanifold. This substantially reduces the search space of parameters and enables the quantifiable comparison of the different control strategies. The chosen metrics are motion stability and energy efficiency, both key aspects for the evolution of the central nervous system. We find that neither for stability nor energy efficiency it is favorable to apply the state-of-the-art approach of a continuously feedback-adapted CPG. In both aspects, a pure reflex is more effective, but the pure CPG allows easy signal alteration when needed. Additionally, the hardware experiments clearly show that the shape of a control signal has a strong influence on energy efficiency, while previous research usually only focused on frequency alignment. Both findings suggest that currently used methods to combine the advantages of reflexes and CPGs can be improved. In future research, possible combinations of the control strategies should be reconsidered, specifically including the modulation of the control signal's shape. For this endeavor, the presented setup provides a valuable benchmark framework to enable the quantitative comparison of different bioinspired control principles.

Hybrid Parallel Compliance Allows Robots to Operate With Sensorimotor Delays and Low Control Frequencies

Animals locomote robustly and agile, albeit significant sensorimotor delays of their nervous system and the harsh loading conditions resulting from repeated, high-frequent impacts. The engineered sensorimotor control in legged robots is implemented with high control frequencies, often in the kilohertz range. Consequently, robot sensors and actuators can be polled within a few milliseconds. However, especially at harsh impacts with unknown touch-down timing, controllers of legged robots can become unstable, while animals are seemingly not affected. We examine this discrepancy and suggest and implement a hybrid system consisting of a parallel compliant leg joint with varying amounts of passive stiffness and a virtual leg length controller. We present systematic experiments both in computer simulation and robot hardware. Our system shows previously unseen robustness, in the presence of sensorimotor delays up to 60 ms, or control frequencies as low as 20 Hz, for a drop landing task from 1.3 leg lengths high and with a compliance ratio (fraction of physical stiffness of the sum of virtual and physical stiffness) of 0.7. In computer simulations, we report successful drop-landings from 3.8 leg lengths (1.2 m) for a 2 kg quadruped robot with 100 Hz control frequency and a sensorimotor delay of 35 ms.

The Continuum Between Temperament and Mental Illness as Dynamical Phases and Transitions

The full range of biopsychosocial complexity is mind-boggling, spanning a vast range of spatiotemporal scales with complicated vertical, horizontal, and diagonal feedback interactions between contributing systems. It is unlikely that such complexity can be dealt with by a single model. One approach is to focus on a narrower range of phenomena which involve fewer systems but still cover the range of spatiotemporal scales. The suggestion is to focus on the relationship between temperament in healthy individuals and mental illness, which have been conjectured to lie along a continuum of neurobehavioral regulation involving neurochemical regulatory systems (e.g., monoamine and acetylcholine, opiate receptors, neuropeptides, oxytocin), and cortical regulatory systems (e.g., prefrontal, limbic). Temperament and mental illness are quintessentially dynamical phenomena, and need to be addressed in dynamical terms. A meteorological metaphor suggests similarities between temperament and chronic mental illness and climate, between individual behaviors and weather, and acute mental illness and frontal weather events. The transition from normative temperament to chronic mental illness is analogous to climate change. This leads to the conjecture that temperament and chronic mental illness describe distinct, high level, dynamical phases. This suggests approaching biopsychosocial complexity through the study of dynamical phases, their order and control parameters, and their phase transitions. Unlike transitions in physical systems, these biopsychosocial phase transitions involve information and semiotics. The application of complex adaptive dynamical systems theory has led to a host of markers including geometrical markers (periodicity, intermittency, recurrence, chaos) and analytical markers such as fluctuation spectroscopy, scaling, entropy, recurrence time. Clinically accessible biomarkers, in particular heart rate variability and activity markers have been suggested to distinguish these dynamical phases and to signal the presence of transitional states. A particular formal model of these dynamical phases will be presented based upon the process algebra, which has been used to model information flow in complex systems. In particular it describes the dual influences of energy and information on the dynamics of complex systems. The process algebra model is well-suited for dealing with the particular dynamical features of the continuum, which include transience, contextuality, and emergence. These dynamical phases will be described using the process algebra model and implications for clinical practice will be discussed.