To test this theory, we administered a decision-making exercise (an iterated dictator game) to about half of the youth in our second BAM study. This exercise made youth think they had been provoked by a classmate and then gave them a chance to retaliate. Our theory predicts BAM youth should slow down and spend more time thinking about how to respond. Our theory does not predict how they will respond, since that depends on what situation they construe themselves to be in. Consistent with our theory, BAM increased decision-making time in response to the provocation by 80%. In terms of the amount of retaliation administered, we found few differences between BAM youth and controls, which does not seem consistent with mechanisms that emphasize changes in factors that would make youth uniformly more pro-social across all situations.
thinking fast and slow epub 33
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Your brain has two systems of thinking. One system is fast, but it can't be trusted. The second system is slow and can be accurate, but it's also lazy and happily trusts the other system most of the time.
Polysomnographic characteristics of a patient with Disorders of Arousal (DOA) and a healthy adult. a: The hypnogram shows an excessive amount of Slow Wave Sleep (SWS) interruptions, frequently characterized by slow/mixed post-arousal EEG activity. Three SWS interruptions are accompanied by complex behavioral manifestations defining parasomniac episodes (lower panel). During such interruption, the polysomnography reveals slow or mixed sleep-wake features, with motor and autonomic activations (upper panel). b: By contrast, SWS continuity is preserved in healthy subjects with rare interruptions (lower panel). The polysomnography reveals a fast post-arousal EEG activity during SWS interruption (upper panel)
A study on 38 adults presenting with injurious SW and ST analyzed post-arousal EEG characteristics of arousals in SWS, associated or not with DOA episodes. The authors confirmed the presence of a slow EEG pattern, characterized by predominant diffuse and synchronous slow delta activity. They also described two other EEG patterns, one characterized by diffuse and irregular, moderate-to-high voltage delta and theta activity intermixed with alpha and beta activity (Fig. 2) and the other characterized by prominent alpha and beta activity, at times intermixed with moderate voltage theta activity. Irrespective of specific EEG patterns, delta activity was present in 44% of the post-arousal EEGs (Schenck et al. 1998). These EEG patterns were subsequently confirmed by other studies and revealed that the slower patterns were more likely to accompany progressive onset rather than abrupt onset DOA episodes. The diagnostic value of these EEG patterns was recently assessed in a case control study. The authors classified each SWS interruption according to the predominant slow, mixed or fast EEG activity during the first three seconds of the motor behavior. They calculated three indices being the sum of all SWS interruptions classified as fast, mixed, or slow patterns per hour of SWS. They found a higher slow/mixed arousal index in DOA patients in comparison with healthy controls (7.0/h versus 1.6/h). They proposed two pathological thresholds, the lower (2.5/h) having an excellent sensitivity of 94% and the higher (6/h) a specificity of 100%. This assessment, however, requires scoring skills and time and appears to be a more appropriate scoring method for research settings rather than for clinical routine (Lopez et al. 2018).
Unimpaired readers process words incredibly fast and hence it was assumed that top-down processing, such as predicting upcoming words, would be too slow to play an appreciable role in reading. This runs counter the major postulate of the predictive coding framework that our brain continually predicts probable upcoming sensory events. This means, it may generate predictions about the probable upcoming word during reading (dubbed forward inferences). Trying to asses these contradictory assumptions, we evaluated the effect of the predictability of words in sentences on eye movement control during silent reading. Participants were a group of fluent (i.e., fast) and a group of speed-impaired (i.e., slow) readers. The findings indicate that fast readers generate forward inferences, whereas speed-impaired readers do so to a reduced extent - indicating a significant role of predictive coding for fluent reading.
Figure 2 depicts the effect of predictability of wordn and wordn+1 on SFD. As evident from the left panel of the Figure, the fast readers exhibited little effect of wordn predictability, whereas the slow readers exhibited increasingly shorter SFD with increasing predictability. The right panel of Figure 2 shows that the fast readers exhibited increasingly longer SFD with increasing predictability of wordn+1. This effect was less pronounced in the slow readers. The fixed effects of wordn and wordn+1 predictability on FFD, SFD and GD are shown by a coefficient plot in Figure 3. As evident from the Figure, the slow readers exhibited reliable facilitatory effects of wordn predictability for every measure, but the effect was particularly pronounced for GD. For the fast readers, wordn predictability exerted a reliable facilitatory effect only for GD. Their effects of wordn+1 predictability, in contrast, were reliable for each measure: Their FFD, SFD and GD on wordn were increasingly longer with increasing wordn+1 predictability. Within the group of slow readers, this effect was markedly less pronounced. The group differences of the effect of wordn and wordn+1 predictability were all significant (group by wordn and group by wordn+1 predictability: all ts > 3.2). Put differently, we found significantly higher facilitation of wordn predictability, but significantly lower effects of wordn+1 predictability in the group of slow readers compared to the fast readers.
This coefficient plot shows the fixed effect (vertical bars) of logit-predictability on the log-transformed first fixation duration (FFD), single fixation duration (SFD) and gaze duration (GD) for wordn and wordn+1 of the slow and the fast readers.
This coefficient plot shows the fixed effects (vertical bars) of predictability of wordn and wordn+1 for short, medium and long first fixation duration (S, M and L, respectively) of the fast and the slow readers.
The main objective of the present eye movement study was to assess to what extent fast and slow reader exhibit evidence for generating forward inferences during reading. The generation of forward inferences, a term adopted from the predictive coding framework10,11, refers to predicting upcoming words. Accordingly, we assessed the relation between various eye movement measures with word predictability. The measures were the probability with which words are skipped or processed with a single fixation and the duration of first fixations, single fixations and gazes (FFD, SFD and GD). We examined effects of the predictability of the current (wordn) and of the upcoming word (wordn+1). Moreover, we assessed the relation of the individual effects of word predictability with the reading rate of our participants and examined the time-course of the predictability effect.
In brief, our findings indicate that readers generate forward inferences about the probable identity of upcoming words, but slow readers do so to a smaller extent than fast readers. In the latter group, the individual effects of word predictability were strongly associated with reading rate: The most speed-impaired readers exhibited the strongest facilitation by the predictability of the currently fixated word, whereas they exhibited the least effect of the predictability of the upcoming word. Moreover, the effect of predictability emerged late in the slow readers. They exhibited the strongest effects of wordn predictability for the measure of GD (a measure which captures late effects; Ref. 37) and the effect was more expressed in long compared to short FFD. In the group of the fast readers, we found that a word's predictability has a reliable effect before the word is encountered (i.e., the effect of wordn+1 predictability). This finding shows that, in fast readers, predictability exerts an early influence during silent reading. However, the influence of the predictability of wordn+1 was only evident in long FFD (on wordn). This finding indicates that generating forward inferences about the identity of upcoming words occurs when the processing of the currently fixated word is well-advanced. Now we proceed to a detailed discussion of these findings and their implications.
A further indication that predictability had a strong, but comparatively late effect in the slow readers is that their probability of recognizing a word with a single fixation steeply increased with increasing predictability of wordn. For the most predictable words (which were very often skipped by the fast readers), the slow readers exhibited a single fixation probability which was similar to the average single fixation probability of the fast readers (i.e., for all words regardless of predictability). In a nutshell, the slow readers processed those words with a single fixation which the fast readers skipped. This finding indicates that, in the slow readers, predictability exerted its effect often too late to warrant word skipping, but facilitated word recognition when the word was fixated. Accordingly, we observed reliable facilitatory effects of wordn predictability on the FFD, SFD and GD of the slow readers. The effect was least pronounced for FFD and most pronounced for GD. This pattern also supports the notion that the predictability effect emerges late in the slow readers, because FFD is a sensitive measure for early effects, whereas GD also captures late effects37.
We can only speculate on the cause-and-effect relationship between the, compared to the fast readers, limited generation of forward inferences during reading and the speed-impaired bottom-up processing in slow readers. An interpretation in terms of causality would require an experimental study with beginning readers. However, we confirmed a core assumption of the lexical quality hypothesis, that is, that fast readers efficiently process even the most unpredictable words (i.e., mostly by a single fixation). To illustrate, the fast readers singly fixated approx. 60% of the words which had a predictability of p = 0. The slow readers, to the contrary, recognized less than 30% of these words with a single fixation. Thus, in fast readers word recognition is evidently effortless even when the processing of a word must proceed bottom-up. For the slow readers, to the contrary, this process is more effortful and much more time consuming. Thus, it is plausible that the difficulties with processing the currently fixated word prevent preprocessing the upcoming word. This interpretation coincides with the foveal load hypothesis47 and the notion of a dynamic perceptual span48. In brief, the perceptual span is the effective field of vision from which information is extracted during a fixation49. The span is dynamic which means that its size is adjusted depending on the difficulty of the currently fixated word (i.e., the foveal load; Ref. 47). The perceptual span of slow readers may be, on average, smaller than that of a fast reader due to their frequent difficulties with visual word recognition (i.e., they need to devote more of their attentional resources to the foveal words). A small span would prevent obtaining (coarse) visual information from the upcoming word which would support the generation of forward inferences by interacting with context-based predictions50. It has been shown that beginning readers have a smaller perceptual span than skilled (adult) readers51,52 and there is recent evidence that, during reading, dyslexic readers53 and less experienced readers54 obtain less parafoveal information than unimpaired, experienced readers. 2ff7e9595c
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