“Esta concepción del trabajo de investigación científica disminuye singularmente la distancia entre el maestro y el aprendiz. Ya no nos permite distinguir dos categorías de investigadores, de los cuales unos solo serían peones mientras que los otros tendrían por misión inventar. La invención debe estar en todas partes, hasta en la mas humilde investigación de hecho, hasta en la experiencia más simple. Allí donde no hay un esfuerzo personal, e incluso original, no hay siquiera un comienzo de ciencia. Tal es la gran máxima pedagógica que se desprende de la bota de Claude Bernard.”

“Cette conception du travail de recherche scientifique diminue singulièrement la distance entre le maître et l’apprenti. Elle ne nous permet plus de distinguer deux catégories de chercheurs, dont les uns ne seraient que des manœuvres tandis que les autres auraient pour mission d’inventer. L’invention doit être partout, jusque dans la plus humble recherche de fait, jusque dans l’expérience la plus simple. Là où il n’y a pas un effort personnel, et même original, il n’y a même pas un commencement de science. Telle est la grande maxime pédagogique qui se dégage de l’œuvre de Claude Bernard.”

Henri Bergson

“… we should do well to consider much more seriously than we have hitherto been inclined to do the type of theory which Bergson put forward in connection with memory and sense perception. That suggestion is that the function of the brain and nervous system and sense organs is in the main eliminative and not productive. Each person is at each moment capable of remembering all that has ever happened to him and of perceiving everything that is happening everywhere in the universe. The function of the brain and nervous system is to protect us from being overwhelmed and confused by this mass of largely useless and irrelevant knowledge, by shutting out most of what we should otherwise perceive or remember at any moment, and leaving only that very small and special selection which is likely to be practically useful.”

C. D. Broad

“The objectives of the analysis are to discern the extent to which the splitting of the behavioral stream into discrete events is arbitrary (e.g., whether raised tail and horizontal tail are two different patterns which affect behavior in different ways, or might be included under one pattern: “tail not lower than horizontal”), to determine the degree to which these events are mutually constrained,and to describe their significance in terms of their relatedness to other events.

Jackal behavior is viewed in this paper as a mosaic of discrete behavioral events, though one of the fruits of the analysis is a verification (or refutation) of the significance to the animals themselves of those elements the human observer believes to be “discrete”.

This program also enables us to check to what extent the division of the flux of behavior into events coincides with the division made by the animals themselves.

While the human observer splits this pattern into two distinct events, the jackals apparently refer to them as synonymous (Synonymity is defined here as occurrence in similar system events. The same events may not be synonymous from the point of view of temporal significance)

Conventionally, mammalian behavior is viewed as a sequence of one behavior pattern at a time (e.g.,Altmani 1965). Once a behavior pattern, intuitively conceived as performed by the whole animal, is fractionated (e.g., into tail position, ear position, bristling, etc.), constancy disappears. We then move into what Elasser calls a “highly heterogeneous universe of discourse” (I966) with a high degree of openness. To find regularity in such a fractionated system is difficult because once different sequences with different regularities are brought together into one “pool” and analyzed as one universe of discourse, the different regularities may average each other out and structure”dissolves”into a kind of “behavioral homogenate”. But if each sequence is treated as a separate universe of discourse, its distinct structure will be retained and it will be possible to relate it to other observed regularities.

However, instantaneousness is a complex logical concept, where an instant is conceived as deprived of all temporal extension.

Now that the behavior pattern is fractionated and cut in various directions, the question arises as to the significance of the events that form it.

Operationally, the existence of a change in the extrinsic significance of events means that analysis should be aimed at pointing out the nature of the change rather than to look for non-mutable significances. In order to be able to trace this change, the structural intricacies of significance should be retained, as they are in the pictorial representations of the MSA and not dissolved by general theory-loaded, all-embracing concepts.”

Ilan Golani

(excerpts from  Non-metric analysis of behavioural interaction sequences in captive jackals, 1973)

“Network visualizations are notoriously difficult to interpret. Their canonical representation in a visual form has earned the moniker hairball, and you can probably guess why. If you are unfamiliar with the hairball, or doubt their prevalence in biological sicences, explore what is always a good source of network hairballs: study of yeast and systems biology.

You can already guess that nothing with the name hairball can truly be useful. In general, they are not. These views are at best accidentally informative, and cannot be relied upon to consistently reveal meaningful patterns.

Conventional network visualization is unsuitable for visual analytics of large networks. So-called hairballs earn their moniker by becoming impenetrably complex as your network grows. They are least effective when visualization is most needed — for large networks.

Hairballs turn complex data into visualizations that are just as complex, or even more so. Hairballs can even seduce us to believe that they carry a high information value. But, just because they look complex does not mean that they can communicate complex information. Hairballs are the junk food of network visualization — they have very low nutritional value, leaving the user hungry.

In a hairball, data is subordinate to layout — node and edge positions and lengths depend as much on the layout algorithm (of which there are many), as on the data. The effect of layout rules is difficult to predict, making direct comparisons of these visualizations impossible. For example, imagine trying to compare two scatter plots in which the ordinality of the scales were altered (e.g. x = 1, 2, 3, … in one and x = 3, 1, 2, … in the other).

As a result, a great deal of detail about the structure of a network is irretrievably lost in a hairball and any emergent patterns may be either real (reflected in the data) or accidental (artefact of the layout). Importantly, there is no aesthetic magic sauce added to the layout. If the layout shows a pattern, you can be sure it is due to structure in the underlying data and not on the layout algorithm’s interpretation of how the data should be shown.”
http://www.hiveplot.net

“In this chapter, we begin our more detailed study of the different aspects of physics, having finished our description of things in general. To illustrate the ideas and the kind of reasoning that might be used in theoretical physics, we shall now examine one of the most basic laws of physics, the conservation of energy.

There is a fact, or if you wish, a law, governing all natural phenomena that are known to date. There is no known exception to this law—it is exact so far as we know. The law is called the conservation of energy. It states that there is a certain quantity, which we call energy, that does not change in the manifold changes which nature undergoes. That is a most abstract idea, because it is a mathematical principle; it says that there is a numerical quantity which does not change when something happens. It is not a description of a mechanism, or anything concrete; it is just a strange fact that we can calculate some number and when we finish watching nature go through her tricks and calculate the number again, it is the same. (Something like the bishop on a red square, and after a number of moves—details unknown—it is still on some red square. It is a law of this nature.) Since it is an abstract idea, we shall illustrate the meaning of it by an analogy.”

Richard Feynman

“Certain units of behaviour, such as the crawling and speech of our examples, do not belong to an initial repertoire of operant responses that comes into being with the organism. They do not originally emerge as full-blown behavioural entities in the way that we find unconditioned lever-pressing, for example, occurring at a low but typical rate in Flyer, the chimp. This is why they they appear to be “new”. Their ultimate occurrence depends on the fact that behaviour, in all its features, is variable, and its variations can be reinforced.”

Introduction to the “Essential Works of Pavlov”

Definiçâo I

“A quantidade de matéria é a medida da mesma, oriunda conjuntamente da sua densidade e grandeza.”

Definiçâo II

“A quantidade do movimento é a medida do mesmo, provinda conjuntamente da velocidade e da quantidade da matéria.”

Definiçâo III

“A força inata (ínsita) da matéria é um poder de resistir pelo qual cada corpo, enquanto depende dele, persevera em seu estado, seja de descanso, seja de movimento uniforme em linha reta.”

Isaac Newton

“Surprisingly, given the pervasive popularity of this metaphor, there remains today no well-established evidence of symbolic manipulation or formal logical rules at the neurobiological level in animal physiology. . . . while the computational metaphor often seems to have the status of an established fact, it should be regarded as an hypothetical, and historical, conjecture about the brain. . . . Today’s embrace of the computational metaphor in the cognitive and neural sciences is so widespread and automatic that it begins to appear less like an innovative leap than like a bandwagon phenomenon, of the sort often observed in the sociology and history of science.”

J. G. Daugman