Prediction and diagnosis: An experimental comparison

Diagnostic tasks differ from predictive tasks in two respects (1) the direction of the inference in diagnosis (from effect to cause) is inverse to that in prediction (from cause to effect), and (2) the event to be inferred is more distal in diagnostic tasks than in predictive tasks. These task features led to the hypothesis that a diagnostic task would be harder to learn than a predictive task. This hypothesis was tested in an experimental situation in which the causal mechanism was random sampling with replacement. Five groups of subjects with 10 subjects in each (two predictive and three diagnostic groups) were run in individual sessions with 100 trials of feedback training. The two predictive groups learned more rapidly and to a higher level compared to the diagnostic groups. Conclusion: the present data support the hypothesis that predictive tasks are easier to learn than comparable diagnostic tasks.     

Why Causation Need Not Follow from Statistical Association: Boundary Conditions for the Evaluation of Generative and Preventive Causal Powers

In experimental design, a tacit principle is that to test whether a candidate cause c (i.e., a manipulation) prevents an effect e, e must occur at least some of the time without the introduction of c. This principle is the preventive analogue of the explicit principle of avoiding a ceiling effect in tests of whether c produces e. Psychological models of causal inference that adopt either the covariation approach or the power approach, among their other problems, fail to explain these principles. The present article reports an experiment that demonstrates the operation of these principles in untutored reasoning. The results support an explanation of these principles according to the power PC theory, a theory that integrates the previous approaches to overcome the problems that cripple each.     

Encouraging children to think counterfactually enhances blocking in a causal learning task

According to a higher order reasoning account, inferential reasoning processes underpin the widely observed cue competition effect of blocking in causal learning. The inference required for blocking has been described as modus tollens (if p then q, not q therefore not p). Young children are known to have difficulties with this type of inference, but research with adults suggests that this inference is easier if participants think counterfactually. In this study, 100 children (51 five-year-olds and 49 six- to seven-year-olds) were assigned to two types of pretraining groups. The counterfactual group observed demonstrations of cues paired with outcomes and answered questions about what the outcome would have been if the causal status of cues had been different, whereas the factual group answered factual questions about the same demonstrations. Children then completed a causal learning task. Counterfactual pretraining enhanced levels of blocking as well as modus tollens reasoning but only for the younger children. These findings provide new evidence for an important role for inferential reasoning in causal learning.     

What Are the “True” Statistics of the Environment?

A widespread assumption in the contemporary discussion of probabilistic models of cognition, often attributed to the Bayesian program, is that inference is optimal when the observer's priors match the true priors in the world—the actual “statistics of the environment.” But in fact the idea of a “true” prior plays no role in traditional Bayesian philosophy, which regards probability as a quantification of belief, not an objective characteristic of the world. In this paper I discuss the significance of the traditional Bayesian epistemic view of probability and its mismatch with the more objectivist assumptions about probability that are widely held in contemporary cognitive science. I then introduce a novel mathematical framework, the observer lattice, that aims to clarify this issue while avoiding philosophically tendentious assumptions. The mathematical argument shows that even if we assume that “ground truth” probabilities actually do exist, there is no objective way to tell what they are. Different observers, conditioning on different information, will inevitably have different probability estimates, and there is no general procedure to determine which one is right. The argument sheds light on the use of probabilistic models in cognitive science, and in particular on what exactly it means for the mind to be “tuned” to its environment.     

Syllogistic: Old Wine in New Bottles

In the late nineteenth century there were two very active lines of research in the field of formal logic. First, logicians (mostly in English-speaking countries) were engaged in formulating a generally traditional logic as an algebra, a part of mathematics; second, logicians (mostly on the continent) were busy building a non-traditional logic that could serve, not as a part of, but as the foundation of, mathematics. By the end of the First World War the former line had been pretty well abandoned while the second continued to expand. However, that old abandoned line, stretching from Aristotle, through the Scholastics and then Leibniz to the nineteenth century algebraists, had not been completely forgotten. One of those logicians who has recently worked on the restoration (and, importantly, the extension) of that line is Fred Sommers. His Term Logic preserves a number of traditional insights (especially involving the theory of logical syntax), while also enjoying a power to account for formal inference at least comparable to that of the standard logic now in place.     

AX+, BX- discrimination learning in the fear-potentiated startle paradigm: possible relevance to inhibitory fear learning in extinction

The neural mechanisms of fear suppression most commonly are studied through the use of extinction, a behavioral procedure in which a feared stimulus (i.e., one previously paired with shock) is nonreinforced repeatedly, leading to a reduction or elimination of the fear response. Although extinction is perhaps the most convenient index of fear inhibition, a great deal of behavioral work suggests that postextinction training conditioned stimuli are both excitatory and inhibitory, making it difficult to determine whether a neural manipulation affects inhibition, excitation, or some combination thereof. For this reason we sought to develop a behavioral procedure that would render a stimulus primarily inhibitory while at the same time avoiding some of the issues raised by the traditional conditioned inhibition paradigm, namely second-order conditioning, external inhibition, and configural learning. Using the fear-potentiated startle paradigm, we adapted an AX+, BX- training procedure in which stimuli A and X were presented simultaneously and paired with shock, and stimuli B and X were presented simultaneously in the absence of shock. In testing, high levels of fear-potentiated startle were seen in the presence of A and AX and much lower levels were seen in the presence of B and AB, as would be predicted if stimulus B were a conditioned inhibitor. We believe this method is a viable alternative to the traditional conditioned inhibition training procedure and will be useful for studying the neural mechanisms of fear inhibition.     

A Duet for one

This paper considers communication in terms of inference about the behaviour of others (and our own behaviour). It is based on the premise that our sensations are largely generated by other agents like ourselves. This means, we are trying to infer how our sensations are caused by others, while they are trying to infer our behaviour: for example, in the dialogue between two speakers. We suggest that the infinite regress induced by modelling another agent – who is modelling you – can be finessed if you both possess the same model. In other words, the sensations caused by others and oneself are generated by the same process. This leads to a view of communication based upon a narrative that is shared by agents who are exchanging sensory signals. Crucially, this narrative transcends agency – and simply involves intermittently attending to and attenuating sensory input. Attending to sensations enables the shared narrative to predict the sensations generated by another (i.e. to listen), while attenuating sensory input enables one to articulate the narrative (i.e. to speak). This produces a reciprocal exchange of sensory signals that, formally, induces a generalised synchrony between internal (neuronal) brain states generating predictions in both agents. We develop the arguments behind this perspective, using an active (Bayesian) inference framework and offer some simulations (of birdsong) as proof of principle.     

网络社会排斥对大学生网络攻击行为及传统攻击行为的影响,疏离感的中介作用

为探讨网络社会排斥、疏离感、大学生网络攻击行为及传统攻击行为间的关系,选取600名大学生为被试,采用网络社会排斥问卷、一般疏离感量表、网络攻击行为量表及大学生攻击行为量表进行测试。结果表明：(1) 网络社会排斥、疏离感、大学生传统攻击行为及网络攻击行为两两之间均呈显著正相关;(2) 网络社会排斥对大学生网络攻击行为和传统攻击行为均具有显著的正向预测作用;(3) 疏离感在网络社会排斥对大学生网络攻击行为和传统攻击行为的影响中均起着部分中介作用。     

The Seeming Interdependence Between the Concepts of Valid Inference and Proof

Topoi - We may try to explain proofs as chains of valid inference, but the concept of validity needed in such an explanation cannot be the traditional one. For an inference to be legitimate in a...     

网络社会排斥对大学生网络攻击行为及传统攻击行为的影响,疏离感的中介作用

为探讨网络社会排斥、疏离感、大学生网络攻击行为及传统攻击行为间的关系,选取600名大学生为被试,采用网络社会排斥问卷、一般疏离感量表、网络攻击行为量表及大学生攻击行为量表进行测试。结果表明：(1) 网络社会排斥、疏离感、大学生传统攻击行为及网络攻击行为两两之间均呈显著正相关;(2) 网络社会排斥对大学生网络攻击行为和传统攻击行为均具有显著的正向预测作用;(3) 疏离感在网络社会排斥对大学生网络攻击行为和传统攻击行为的影响中均起着部分中介作用。     

Examining Associations Between Reading Motivation and Inference Generation Beyond Reading Comprehension Skill

The purpose of this study was to examine the associations between reading motivation and inference generation while reading. Undergraduate participants (N = 69) read two science articles while thinking aloud, completed a standardized reading comprehension assessment, and self reported their habitual reading motivation. Findings indicate that overall reading motivation, one component of intrinsic motivation (reading as a sense of self), and one component of extrinsic motivation (reading to do well in other realms) were positively associated with text-connecting inference generation independent of reading comprehension skill. These findings are discussed in the context of standards of coherence.     

Subjective social stress indicators and the level of reported psychopathology: The case of Israel

This study investigated (on the aggregate level) the relationship between the level of psychopathology in society (monthly rates of inpatient psychiatric admissions) and the population's perception of stress (expressions of worry or dissatisfaction regarding the general, economic, and security situation) and social support (national solidarity expressed as positive attitudes regarding relations between various segments of the population). The subjective indicators were derived from continuing surveys of representative samples of urban Israeli population during 1967-1979. Included were 12 stress indicators and 3 solidarity indicators. As predicted, general stress was positively related to psychiatric admissions, while security stress (due to its cohesive effect) and social solidarity were negatively related to these admissions. Contrary to prediction, economic subjective stress was negatively related to psychiatric admissions. Theoretical implications of the findings are discussed.     

Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?

Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were optimal, employing Bayesian inference based on veridical prior distributions. Although the predictions conformed strikingly to statistics of the world, they reflect averages over many individuals. On the conjecture that the accuracy of the group response is chiefly a consequence of aggregating across individuals, we constructed simple, heuristic approximations to the Bayesian model premised on the hypothesis that individuals have access merely to a sample of k instances drawn from the relevant distribution. The accuracy of the group response reported by Griffiths and Tenenbaum could be accounted for by supposing that individuals each utilize only two instances. Moreover, the variability of the group data is more consistent with this small-sample hypothesis than with the hypothesis that people utilize veridical or nearly veridical representations of the underlying prior distributions. Our analyses lead to a qualitatively different view of how individuals reason from past experience than the view espoused by Griffiths and Tenenbaum.     

Justified inference

This paper proposes a general account of the epistemological significance of inference. This account rests on the assumption that the concept of a ??justified?? belief or inference is a normative concept. It also rests on a conception of belief that distinguishes both (a) between conditional and unconditional beliefs and (b) between enduring belief states and mental events of forming or reaffirming a belief, and interprets all of these different kinds of belief as coming in degrees. Conceptions of ??rational coherence?? and ??competent inference?? are then formulated, in terms of the undefeated instances of certain rules of inference. It is proposed that (non-accidental) rational coherence is a necessary and sufficient condition of justified enduring belief states, while competent inference always results in a justified mental event of some kind. This proposal turns out to tell against the view that there are any non-trivial cases of ??warrant transmission failure??. Finally, it is explained how these proposals can answer the objections that philosophers have raised against the idea that justified belief is ??closed?? under competent inference.     

Inference,practice and theory

Reichenbach held that all scientific inference reduces, via probability calculus, to induction, and he held that induction can be justified. He sees scientific knowledge in a practical context and insists that any rational assessment of actions requires a justification of induction. Gaps remain in his justifying argument; for we can not hope to prove that induction will succeed if success is possible. However, there are good prospects for completing a justification of essentially the kind he sought by showing that while induction may succeed, no alternative is a rational way of trying.Reichenbach's claim that probability calculus, especially via Bayes' Theorem, can help to exhibit the structure of inference to theories is a valuable insight. However, his thesis that the weighting of all hypotheses rests only on frequency data is too restrictive, especially given his scientific realism. Other empirical factors are relevant. Any satisfactory account of scientific inference must be deeply indebted to Reichenbach's foundation work.     

An overview of Bayesian reasoning in the analysis of delay‐discounting data

Statistical inference (including interval estimation and model selection) is increasingly used in the analysis of behavioral data. As with many other fields, statistical approaches for these analyses traditionally use classical (i.e., frequentist) methods. Interpreting classical intervals and p‐values correctly can be burdensome and counterintuitive. By contrast, Bayesian methods treat data, parameters, and hypotheses as random quantities and use rules of conditional probability to produce direct probabilistic statements about models and parameters given observed study data. In this work, we reanalyze two data sets using Bayesian procedures. We precede the analyses with an overview of the Bayesian paradigm. The first study reanalyzes data from a recent study of controls, heavy smokers, and individuals with alcohol and/or cocaine substance use disorder, and focuses on Bayesian hypothesis testing for covariates and interval estimation for discounting rates among various substance use disorder profiles. The second example analyzes hypothetical environmental delay‐discounting data. This example focuses on using historical data to establish prior distributions for parameters while allowing subjective expert opinion to govern the prior distribution on model preference. We review the subjective nature of specifying Bayesian prior distributions but also review established methods to standardize the generation of priors and remove subjective influence while still taking advantage of the interpretive advantages of Bayesian analyses. We present the Bayesian approach as an alternative paradigm for statistical inference and discuss its strengths and weaknesses.     

Inference vs control sentences: are readers able to detect our intended differences?

The reliance of comprehension processes on knowledge to form explanatory inferences has been well established (Grasser, Singer, & Trabasso, 1994), yet the evidence that supports these studies is derived from sentence pairs that are largely unexamined. While some recent studies have suggested that the stimulus sentences utilized in comprehension research need further specification (Shears & Chiarello, 2004), there has been little 'normal reading' data provided that examines what readers are able to detect from traditional inference-requiring vs control sentence pairs. The current study utilized stimuli sentences that have historically been used to support inference research (Singer, 1995) as well as some newly developed sentences, to examine whether readers detect differences between control vs inference conditions, and to further examine whether readers could discern when inference sentences achieved an outcome or goal vs when these sentences did not achieve an outcome or goal.