Mutual causality recognizes that there might be a relationship between two things, yet the outcome is contextual and variable, based on multidirectional influences, feedback from other parts, and rule-governed processes that control the system. Iva Lloyd BScH RPP ND, in The Energetics of Health, 2009 Mutual causality Information on drug withdrawal may be lacking or unclear.Ī clinical event, including laboratory test abnormality, with a temporal relationship to drug administration, which makes a causal relationship improbable but not impossible, and in which other drugs, chemicals, or underlying disease provide plausible explanations.Ī clinical event, including laboratory test abnormality, reported as an adverse reaction, about which more data are essential for a proper assessment, or the additional data are under examination.Ī report suggesting an adverse reaction that cannot be judged because information is insufficient or contradictory, and which cannot be supplemented or verified.
Rechallenge information is not required to fulfill this definition.Ī clinical event, including laboratory test abnormality, with a reasonable time sequence to administration of the drug, but which could also be explained by concurrent disease or other drugs or chemicals. Unlikely to be attributed to concurrent disease or other drugs or chemicals, and which follows a clinically reasonable response to withdrawal (dechallenge). The event must be definitive pharmacologically or phenomenologically, i.e., an objective and specific medical disorder or a recognized pharmacological phenomenon, using a satisfactory rechallenge procedure if necessary.Ī clinical event, including laboratory test abnormality, with a reasonable time sequence to the administration of the drug. The response to withdrawal of the drug (dechallenge) should be clinically plausible. Now suppose that in this example the delay between B and C ( Δ t 2 − Δ t 1 ) is ∼5 ms, such a value is far below the expected delay of over 100 ms, which is an indication that direct connectivity doesn't play a role in the observed lead-lag between B and C.Ī clinical event, including laboratory test abnormality, occurring in a plausible time relationship to drug administration, and which cannot be explained by concurrent disease or other drugs or chemicals.
Mutual causality plus#
For example, if we know that areas B and C in Fig. 14.1B are 10 cm apart and that conduction velocities of the fibers between B and C are ∼1 m/s, we can expect delays ∼100 ms plus a few milliseconds for each synapse involved. Because we often know the typical conduction velocity and delays caused by synaptic transmission, we can (at least) recognize unrealistic delays. Often, authors use terms such as “functional connectivity” or “synaptic flow” to (implicitly) indicate the caveats above. Having said this, in many studies in neuroscience this is (conveniently) ignored and timing in signals is frequently used as an argument for connectivity.
So equating lead-lag with causality/connectivity can be incorrect. It would get even worse if we hadn't recorded from A in this example: then we only find B → C and we would be 100% incorrect. We are only partly correct: the two former relationships are correctly inferred but the latter is not.
However, if we measure signals from A, B, and C ( Fig. 14.1B), we conclude that A → B, A → C, and B → C. If we record from areas A and B in Fig. 14.1A, our method of interpreting lead-lag as a causal relationship A → B is correct. We have to start pessimistically by pointing out that translation from lead-lag to causality is not strictly possible-the example in Fig. 14.1 demonstrates this.
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