Mechanisms in World and Mind by Bernd Lindemann

Author:Bernd Lindemann
Language: eng
Format: epub
Tags: Biophysical, mind-body problem, philosophy of mind, neuroscience, perspective dualism, systems theory, consciousness, physicalism, mental
ISBN: 9781845407742
Publisher: Andrews UK Limited 2014
Published: 2014-08-19T00:00:00+00:00

Figure 5.1. Clippings of some universal system levels in neuroscience. Meaning of symbols: Stars: events in neurons, spiking; squares: events in organelles; circles: molecular events; angles: sub-molecular events; dots: basal physical events. Note the change in scale as we move upward, zooming out. Complete coupling of levels is implied since synchronic events at two levels root in the same basic events which occur on each level. Proper grounding is a prerequisite.

5d. Randomness

As the grouping specifies mechanisms of increasing complexity and size, these become macroscopic and are often modelled as deterministic, thematizing ensemble behaviour (sum of single-unit SB) but not the fluctuations associated with them. Therefore it is to be noted that fluctuations remain associated even with large populations. Suppose the single-unit SB of a population of N parallel units is added. Then with increasing N the fluctuations of the ensemble increase (even though less so than the sum of SB). Thus the probabilistic fluctuations do not disappear when we change to a deterministic model of many parallel units.

Yet, as discussed below (Section 6e “Causality-gaps”), the mere presence of random fluctuations does not mean that causality is punctured. For even events of a Markov sequence may be modelled as a gap-less causal chain (Section 2e). The random sequence is constrained by the rules of the STD.

Passing through a network of neurons and neuronal modules we may envisage a sequence of signals fluctuating more or less at each stage. This is not a patchwork of alternating deterministic and probabilistic natural processes (as sometimes claimed [e.g. 46, 47:11]), but a sequence of probabilistic models, specifying randomness adjusted to different degrees from stage to stage.

The virtue of randomness: In the biochemistry of molecules in small number, fluctuations may even exceed the mean SB. They can increase sensitivity, allowing stochastic focussing, with noise facilitating signal detection in nonlinear systems [108]. In neurobiology, transmitter release at cortical synapses typically operates with few synaptic vesicles and a low probability of vesicle discharge, it is highly probabilistic [45, 78:90, 82]. Presumably the design of a random performance is of advantage, as on other locations very reliable synapses are also in evidence. Famously, synaptic strength is use-dependent [59], it is subject to long-term potentiation [78:317]. But not only synaptic signal intensity, also the reliability of vesicle release seems to be varied as a feature in the process of learning. It appears that a point on the scale from probabilistic to to deterministic is chosen by design. Transmitter release of baseline probability 0.1, say, would be increased with use to a probability near unity, “... lack of reliability at low intensity is required to give a synapse its large dynamic range” [78:327].

Randomness is continued in units of higher organisation [45]. It is remarkable that cortical neurons can show a completely random spike pattern as their typical output. In principle the degree of randomness can be tuned by putting more or fewer stochastic elements in parallel, such as ion channels, synaptic vesicles, synapses or neurons. In each case randomness can be varied, it is a ‘feature’.

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