The information age can be dated to the work of Norbert Wiener and Claude Shannon in the 1940s. Their work on cybernetics and information theory, and many subsequent developments, had a profound influence on reshaping the field of psychology from what it was prior to the 1950s. Contemporaneously, advances also occurred in experimental design and inferential statistical testing stemming from the work of Ronald Fisher, Jerzy Neyman, and Egon Pearson. These interdisciplinary advances from outside of psychology provided the conceptual and (...) methodological tools for what is often called the cognitive revolution but is more accurately described as the information-processing revolution. Cybernetics set the stage with the idea that everything ranging from neurophysiological mechanisms to societal activities can be modeled as structured control systems with feedforward and feedback loops. Information theory offered a way to quantify entropy and information, and promoted theorizing in terms of information flow. Statistical theory provided means for making scientific inferences from the results of controlled experiments and for conceptualizing human decision making. With those three pillars, a cognitive psychology adapted to the information age evolved. The growth of technology in the information age has resulted in human lives being increasingly interweaved with the cyber environment, making cognitive psychology an essential part of interdisciplinary research on such interweaving. Continued engagement in interdisciplinary research at the forefront of technology development provides a chance for psychologists not only to refine their theories but also to play a major role in the advent of a new age of science. (shrink)

Information about positions, from which differences in position are computed (as proposed in the vector-integration-to-endpoint model), provides a more plausible perceptual basis for the control of goal-directed arm movements than information about distance (as proposed in the kinematic model).

Control consciousness is the awareness or experience of seeming to be in control of one’s actions. One view, which I will be arguing against in the present paper, is that control consciousness is a form of sensory consciousness. In such a view, control consciousness is exhausted by sensory elements such as tactile and proprioceptive information. An opposing view, which I will be arguing for, is that sensory elements cannot be the whole story and must be supplemented by direct contributions of (...) nonsensory, motor elements. More specifically, I will be arguing for the view that the neural basis of control consciousness is constituted by states of recurrent activation in relatively intermediate levels of the motor hierarchy. (shrink)

Speech and music reflect extraordinary aspects of human cognitive abilities. Pitch, as an important parameter in the auditory domain, has been the focus of previous research on the relations between speech and music. The present study continues this line of research by focusing on two aspects of pitch processing: pitch prominence and melodic expectation. Specifically, we examined the perceived boundary of prominence for focus/accent in speech and music, plus the comparison between the pitch expectation patterns of music and speech. Speech (...) (Mandarin Chinese) and music stimuli were created with different interval steps that increased from 1 semitone to 12 semitones from the third to the fourth word/note of a sentence/melody. The results showed that ratings of both accent/focus and expectation/surprise increased with increasing semitone distance from the baseline (though this pattern was mixed with tonal stability profiles for the melodies). Nevertheless, the perceived boundary of prominence was different for music and speech, with the boundary for detecting prominence in speech higher than that in music. Expectation also showed different patterns for speech and music. The results thus favor the suggestion that speech prosody and music melody tend to require specialized pitch patterns unique to their own respective communication purposes. (shrink)

The processes underlying motor decision-making have recently caught considerable amount of scientific attention, focusing on the integration of empirical evidence from sensorimotor control research with psychological theories and computational models on decision-making. Empirical studies on motor decision-making suggest that the kinematics of goal-directed reaching movements are sensitive to the level of target uncertainty during movement planning. However, the source of uncertainty as a relevant factor influencing the process of motor decision-making has not been sufficiently considered, yet. In this study, we (...) test the assumption that the source of target uncertainty has an effect on motor decision-making, which can be proven by analyzing movement variability during the time course of movement execution. Ten healthy young adults performed three blocks with 66 trials of goal-directed reaching movements in each block, across which the source and level of reach target uncertainty at movement onset were manipulated (“no uncertainty”, “extrinsic uncertainty”, “intrinsic uncertainty”). Fingertip position of the right index finger was recorded using an optical motion tracking system. Standard kinematic measures (i.e. path length and movement duration) as well as variability of fingertip position across the time course of movement execution and at movement end were analyzed. In line with previous studies, we found that a high level of extrinsic target uncertainty leads to increased overall movement duration, which could be attributed to increased path length in this condition, as compared to intrinsic and no target uncertainty (all p <.001). Movement duration and path length did not show any differences between the latter two conditions. However, the time course analysis of movement variability revealed significant differences between these two conditions, with increased variability of fingertip position in the presence of intrinsic target uncertainty (Condition × Sampling point: p =.01), though considerably less than under high extrinsic target uncertainty (p ≤.001). These findings suggest that both the level and source of uncertainty have a significant effect on the processing of potential action plans during motor decision-making, which can be revealed through the analysis of the time course of movement variability at the end-effector level. (shrink)

Human decision making shows systematic simplifications and deviations from the tenets of rationality (‘heuristics’) that may lead to suboptimal decisional outcomes (‘cognitive biases’). There are currently three prevailing theoretical perspectives on the origin of heuristics and cognitive biases: a cognitive-psychological, an ecological and an evolutionary perspective. However, these perspectives are mainly descriptive and none of them provides an overall explanatory framework for the underlying mechanisms of cognitive biases. To enhance our understanding of cognitive heuristics and biases we propose a neural (...) network framework for cognitive biases, which explains why our brain systematically tends to default to heuristic (‘Type 1’) decision making. We argue that many cognitive biases arise from intrinsic brain mechanisms that are fundamental for the working of biological neural networks. In order to substantiate our viewpoint, we discern and explain four basic neural network principles: (1) Association, (2) Compatibility (3) Retainment, and (4) Focus. These principles are inherent to (all) neural networks which were originally optimized to perform concrete biological, perceptual, and motor functions. They form the basis for our inclinations to associate and combine (unrelated) information, to prioritize information that is compatible with our present state (such as knowledge, opinions and expectations), to retain given information that sometimes could better be ignored, and to focus on dominant information while ignoring relevant information that is not directly activated. The supposed mechanisms are complementary and not mutually exclusive. For different cognitive biases they may all contribute in varying degrees to distortion of information. The present viewpoint not only complements the earlier three viewpoints, but also provides a unifying and binding framework for many cognitive bias phenomena. (shrink)

Introduction: The effect of promoting a physical reaction by the described action is called the action-sentence compatibility effect. It has been verified that physical motion changes depending on the time phase and grammatical expression. However, it is unclear how adverbs and onomatopoeia change motion simulations and subsequent movements.Methods: The subjects were 35 healthy adults. We prepared 20 sentences each, expressing actions related to hands and feet. These were converted into 80 sentences, with the words “Slow” or “Quick” added to the (...) words related to the speed of movement, and 80 sentences with the words “Fast” and onomatopoeia “Satto” added. Additionally, 20 unnatural sentences were prepared for each stimulus set as pseudo sentences. Choice reaction time was adopted; subjects pressed the button with their right hand only when the presented text was correctly understood. The reaction time and the number of errors were recorded and compared.Results: As a result of a two-way repeated ANOVA, an interaction effect was observed in RTs and NoE in set A. “Hand and Fast” had significantly faster RTs than “Hand and Slow” and “Foot and Fast.” Furthermore, “Hand and Fast” had a significantly higher NoE than others. In set B, the main effects were observed in both RTs and NoE. “Hand” and “Satto” had significantly faster RTs than “Foot” and “Quick,” respectively. Additionally, an interaction effect was observed in NoE, wherein “Foot and Satto” was significantly higher than “Hand and Satto” and “Foot and Quick.”Conclusion: In this study, the word “Fast” promoted hand response, reaffirming ACE. The onomatopoeia “Satto” was a word that conveys the speed of movement, but it was suggested that the degree of understanding may be influenced by the body part and the attributes of the subject. (shrink)

Evidence for a dichotomy between the planning of an action and its on-line control in humans is reviewed. This evidence suggests that planning and control each serve a specialized purpose utilizing distinct visual representations. Evidence from behavioral studies suggests that planning is influenced by a large array of visual and cognitive information, whereas control is influenced solely by the spatial characteristics of the target, including such things as its size, shape, orientation, and so forth. Evidence from brain imaging and neuropsychology (...) suggests that planning and control are subserved by separate visual centers in the posterior parietal lobes, each constituting part of a larger network for planning and control. Planning appears to rely on phylogenetically newer regions in the inferior parietal lobe, along with the frontal lobes and basal ganglia, whereas control appears to rely on older regions in the superior parietal lobe, along with the cerebellum. Key Words: action; apraxia; control; illusions; optic ataxia; PET; planning; reaching;. (shrink)

The tradeoff hypothesis in the speech–gesture relationship claims that (a) when gesturing gets harder, speakers will rely relatively more on speech, and (b) when speaking gets harder, speakers will rely relatively more on gestures. We tested the second part of this hypothesis in an experimental collaborative referring paradigm where pairs of participants (directors and matchers) identified targets to each other from an array visible to both of them. We manipulated two factors known to affect the difficulty of speaking to assess (...) their effects on the gesture rate per 100 words. The first factor, codability, is the ease with which targets can be described. The second factor, repetition, is whether the targets are old or new (having been already described once or twice). We also manipulated a third factor, mutual visibility, because it is known to affect the rate and type of gesture produced. None of the manipulations systematically affected the gesture rate. Our data are thus mostly inconsistent with the tradeoff hypothesis. However, the gesture rate was sensitive to concurrent features of referring expressions, suggesting that gesture parallels aspects of speech. We argue that the redundancy between speech and gesture is communicatively motivated. (shrink)

Different disciplines converge to trace language evolution from motor skills. The human ability to use tools has been advocated as a fundamental step toward the emergence of linguistic processes in the brain. Neuropsychological and neuroimaging research has established that linguistic functions and tool-use are mediated by partially overlapping brain networks. Yet, scholars still theoretically debate whether the relationship between tool-use and language is contingent or functionally relevant, since empirical evidence is critically missing. Here, we measured both linguistic production and tool-use (...) abilities in the same participants, as well as manual and linguistic motor skills. A path analysis ruling out unspecific contributions from manual or linguistic motor skills, showed that motor proficiency using a tool lawfully predicts differences in individual linguistic production. In addition, more complex tool-use reveals stronger association between linguistic production and tool mastery. These findings establish the existence of shared cognitive processes between tool-use and language. (shrink)

Predictable somatosensory feedback leads to a reduction in tactile sensitivity. This phenomenon, called tactile suppression, relies on a mechanism that uses an efference copy of motor commands to help select relevant aspects of incoming sensory signals. We investigated whether tactile suppression is modulated by the task-relevancy of the predicted consequences of movement and the intensity of related somatosensory feedback signals. Participants reached to a target region in the air in front of a screen; visual or tactile feedback indicated the reach (...) was successful. Furthermore, tactile feedback intensity varied across two groups of participants. We measured tactile suppression by comparing detection thresholds for a probing vibration applied to the finger either early or late during reach and at rest. As expected, we found an overall decrease in late-reach suppression, as no touch was involved at the end of the reach. We observed an increase in the degree of tactile suppression when strong tactile feedback was given at the end of the reach, compared to when weak tactile feedback or visual feedback was given. Our results suggest that the extent of tactile suppression can be adapted to different demands of somatosensory processing. Downregulation of this mechanism is invoked only when the consequences of missing a weak movement sequence are severe for the task. The decisive factor for the presence of tactile suppression seems not to be the predicted action effect as such, but the need to detect and process anticipated feedback signals occurring during movement. (shrink)

Behaviour is often described as the computation of a response to a stimulus. This description is incomplete in an important way because it only examines what occurs between the reception of stimulus information and the generation of an action. Behaviour is more correctly described as a control process where actions are performed in order to affect perceptions. This closed-loop nature of behaviour is de-emphasized in modern discussions of brain function, leading to a number of artificial mysteries. A notable example is (...) the ‘symbol grounding problem'. When behaviour is viewed as a control process, it is natural to explain how internal representations, even symbols, can have meaning for an organism, and how actions can be motivated by organic needs. (shrink)