Implementing random time effects in neural networks has been a challenge for neural network researchers. In this paper, we propose a neurophysiologically inspired temporal summation mechanism to reflect real-time random dynamic processing in neural networks. According to the physiology of neuronal firing, a presynaptic neuron sends out a burst of random spikes to a postsynaptic neuron. In the postsynaptic neuron, spikes arriving at different points in time are summed until the postsynaptic membrane potential exceeds a threshold, thus initiating postsynaptic firing. This temporal summation process can be used as a metric for deriving time predictions in neural networks. To demonstrate potential applications of temporal summation, we have employed a feedforward, two-layer network featuring a Hebbian learning rule to perform simulations using the semantic priming experimental paradigm. W e are able to successfully reproduce not only the basic patterns of observed response time data (e.g., positively skewed response time distributions and speed-accuracy trade-offs) but also the semantic priming effect and the time-course of priming as a function of stimulus-onset-asynchrony. These results suggest that the proposed temporal summation mechanism may be a promising candidate for incorporating real-time, random time effects into neural network modeling of human cognition.

This study investigated the model selection problem in cognitive psychology: How should one decide between two computational models of cognition? The focus was on model "faithfulness, " which refers to the degree to which a model's behavior originates from the theoretical principles that it embodies. The guiding principle is that among a set of models that simulate human performance equally well, the model whose behavior is most stable or robust with variation in parameter values should be favored. This is because such a model is likely to have captured the underlying mental process in the least complex way while at the same time being faithful to the theoretical principles that guided the model's development. Sensitivity analysis is introduced as a tool for assessing model faithfulness. Its application is demonstrated in the context of two localist connectionist models of speech perception, TRACE and MERGE.

A general state-space model of prototype learning was formulated Interms of a set of Internal states and nonlinear Input-output mappings. The general model Includes several previous models as special cases such as Hintzman's (1986) multiple trace model, Metcalf's (1982) holographic model,and two parallel distributive memory models (Knapp & Anderson, 1984;McClelland & Rumelhart, 1985). Two basic properties common to the threemodels were defined in terms of this general model--addltivlty and time Invarlance. An experiment was conducted to test the basic properties using random spectral patterns as stimuli allowing possible nonlinear input and output distortions. Especially, ordinal tests of addltivlty were performed with few assumptions about Internal features that subjects may use to encode the stimulus Information. The results support addltivlty but tlme-Invarlance was clearly violated. Implications of these findings for models of the human memory system are discussed.

Background

This manuscript summarizes consensus reached by the International Anorectal Physiology Working Group (IAPWG) for the performance, terminology used, and interpretation of anorectal function testing including anorectal manometry (focused on high-resolution manometry), the rectal sensory test, and the balloon expulsion test. Based on these measurements, a classification system for disorders of anorectal function is proposed.

Methods

Twenty-nine working group members (clinicians/academics in the field of gastroenterology, coloproctology, and gastrointestinal physiology) were invited to six face-to-face and three remote meetings to derive consensus between 2014 and 2018.

Key recommendations

The IAPWG protocol for the performance of anorectal function testing recommends a standardized sequence of maneuvers to test rectoanal reflexes, anal tone and contractility, rectoanal coordination, and rectal sensation. Major findings not seen in healthy controls defined by the classification are as follows: rectoanal areflexia, anal hypotension and hypocontractility, rectal hyposensitivity, and hypersensitivity. Minor and inconclusive findings that can be present in health and require additional information prior to diagnosis include anal hypertension and dyssynergia.

Conclusions and inferences

This framework introduces the IAPWG protocol and the London classification for disorders of anorectal function based on objective physiological measurement. The use of a common language to describe results of diagnostic tests, standard operating procedures, and a consensus classification system is designed to bring much-needed standardization to these techniques.