'Homeostasis' stems from Greek, meaning same stand or same state. The term was coined by Cannon: '.The coordinated physiological processes which maintain most of the steady states in the organism are so complex and so peculiar to living beings ... that I have suggested a special designation for these states, homeostasis. The word does not imply something set and immobile, a stagnation. It means a condition—a condition which may vary, but which is relatively constant' (Cannon 1932). Antecedents of the concept of'homeostasis' can be traced back to ancient Greece (Adolph 1961). In the nineteenth century, the identification of a variety of physiological regulatory mechanisms has led to the notion that the body maintains a stable internal environment, for example stable temperature, blood pressure, or sugar level, in spite of changing conditions (Cannon 1932; Adolph 1961; Brazier 1988). Most notable was Claude Bernard's conclusion: '... all the vital mechanisms... have only one object, that of preserving constant the conditions of life in the internal environment' (1878, translated and cited in Cannon 1929; Olmsted 1938). This idea that a stable internal milieu is characteristic of, and essential for, life became a tenet of biology (Jones 1973; Houk 1980a,b). It is also central to discussions of adaptive control in artificial systems (Wiener 1961). Unfortunately, that biological systems are inherently homeostatic is not always properly remembered by students of the nervous system; too frequently authors disregard the possibility that the goal of a neuronal change might not be to bring about a long-lasting alteration in the system, but rather, on the contrary, to prevent it.
Brain scientists are bound to encounter home-ostasis, and face the delicate interplay between stability and change, in many branches of the neuroscience, ranging from the study of membrane properties, via neuro"development, up to widespread autonomic regulation, drives, motivation, emotion, cognition, and behaviour (for selected discussions, see Blessing 1997; McEwen 1997; Risold et al. 1997; Zhou et al. 1997; Davis and Goodman 1998; Fanselow 1998; Mattson 1998; Damasio 1999). All the aforementioned manifestations of homeostasis are relevant to learning. Here we will focus briefly on one aspect of homeostasis only, which is not yet sufficiently elaborated in the current literature. This is the potential relevance of homeostasis to candidate cellular mechanisms of learning and memory, and to the interpretation of data and "models.
For our purpose, suffice it to reiterate that in order to fulfil their basic roles in "perceiving the world and reacting to it, nervous systems must maintain relative stability that ensures sustainment of input-output relationships ('gain control') within a desired limit. This is done under conditions in which the system is 'open', i.e. exchanges materials and energy with the world, and the world itself is in an ever-lasting flux. Homeostatic mechanisms that secure emission of a given range of behavioural response to a given range of stimuli include various types of feedback and forward regulation (Jones 1973; Houk 1980). Such mechanisms usually involve comparison of output with a 'reference' signal, or 'set point', which represents the desired value of the output. In some 'innate' or reflexive behaviours, which had been moulded in evolution to allow fast reaction and survival ("a priori), the 'set point' by which the system judges the aptness of its "performance is rather rigid. In such cases, use-dependent modifications in the operation of local nodes in the system, e.g. "synapses, may represent the operation of the regulatory mechanisms that restore proper operational conditions, keep the system stable, and at most perform some fine tuning. Thus, although a local change is observed, its role might be to prevent a lasting overall alteration in the performance of the system rather than promote it.
One way of construing neuronal "plasticity in learning and development is to regard it as a process that involves a lasting modification in the set point of the homeostatic system (definition 2 in "plasticity; also Bienenstock et al. 1982; Bear 1995; "metaplasticity). In such case, the use-dependent neuronal modifications detected by the experimenter might indeed constitute lasting changes in "internal representations, hence be causally related to learning and memory.1 Alternatively, however, the observed modification might still reflect only a homeostatic, restorative process in the circuit, which does not culminate in a lasting representational change. The distinction between these two types of change is important but not easy. For it to be made, one should be able to identify the representation encoded in the circuit, and prove that the observed molecular, cellular, or morphological modification indeed subserves a lasting change in the internal representation. What makes life even more complicated, is that in complex systems, modification of individual components is not necessarily informative as far as alteration in the properties of the system as a whole is concerned. This means that, although some local changes in synapses and neurons, such as use-dependent change in "receptor availability or "neurotransmitter release, are plausible candidates for subserving representational change in the circuit—they may not do so, after all.
The distinction between the role of candidate synaptic plasticity mechanisms, such as unveiled in "LTP, in homeostatic control as opposed to lasting representational change, is thus one of the current challenges of the cellular biology of learning.
Selected associations: Persistence, Plasticity, System
1One could come up with the remark that even if the circuit is altered to encode a new lasting representation, hence a new memory is formed, the ultimate goal of this memory is to retain the steady state of the organism as such in its milieu. In other words, the goal of learning is to maintain homeostasis. This reflects the importance of defining the *level of discussion.
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