Models in neuroendocrinology

Abstract

The neuroendocrine systems of the hypothalamus are critical for survival and reproduction, and are highly conserved throughout vertebrate evolution. Their roles in controlling body metabolism, growth and body composition, stress, electrolyte balance and reproduction have been intensively studied, and have yielded a rich crop of original and challenging insights into neuronal function, insights that circumscribe a vision of the brain that is quite different from conventional views. Despite the diverse physiological roles of pituitary hormones, most are secreted in a pulsatile pattern, but arising through a variety of mechanisms. An important exception is vasopressin which uses bursting neural activity, but produces a graded secretion response to osmotic pressure, a sustained robust linear response constructed from noisy, nonlinear components. Neuroendocrine systems have many features such as multiple temporal scales and nonlinearity that make their underlying mechanisms hard to understand without mathematical modelling. The models presented here cover the wide range of temporal scales involved in these systems, including models of single cell electrical activity and calcium dynamics, receptor signalling, gene expression, coordinated activity of neuronal networks, whole-organism hormone dynamics and feedback loops, and the menstrual cycle. Many interesting theoretical approaches have been applied to these systems, but important problems remain, at the core the question of what is the true advantage of pulsatility.

Mathematical Modelling of Endocrine Systems

“…Some of these benefits have been already described in several reviews. The review in [1] covers general principles of modelling in neuroendocrinology using the growth hormone system as an example, while a recent review by the same authors addresses the contributions of modelling to hypothalamic–pituitary neurosecretory systems [2]. The review in [3] describes in detail several mathematical modelling tools such as types of equations, analysis of their dynamic behaviour (e.g., bistability , oscillations), and approaches to deal with biological noise and systems with multiple timescales in view of applications in endocrinology.…”

State-dependent activity dynamics of hypothalamic stress effector neurons

“…6L ), confirming that they were indeed action potentials. Moreover, we found that in magnocellular (non-CRH) neuroendocrine neurons of the PVN, which are known to have ex vivo intrinsic properties (Luther et al, 2002) and in vivo firing patterns (Leng and MacGregor, 2018) different from CRH PVN neurons, the identical network current failed to trigger the RB ( Fig. 6M, N ).…”

Mathematical modeling approaches of cellular endocrinology within the hypothalamo-pituitary-gonadal axis

“…We refer the reader to a former review (Yvinec et al, 2018) for other interesting biomathematical issues raised by the HPG, such as (i) the detection and possible reconstruction of pulsatile secretion events, and (ii) the modeling of hormonal blood levels in males or females (ovarian cycle). We also mention recent reviews dealing with related topics: mathematical neuroendocrinology (Bertram, 2015;Leng and MacGregor, 2018), electrophysiology in pituitary cells (Fletcher et al, 2018), and general modeling issues in endocrine systems (Zavala et al, 2019).…”

“…As such, they undergo a process of excitation-secretion coupling underlain by electrophysiological steps. There is a huge literature in electrophysiological modeling, amongst which numerous studies have been dedicated to either GnRH neurons or gonadotrophs (most of them are reviewed in (Bertram, 2015), (Fletcher et al, 2018) or (Leng and MacGregor, 2018)). We will just pick-up some instances that can give a flavor of more comprehensive descriptions.…”