I Hear My Voice; Therefore I Spoke: The Sense of Agency Over Speech Is Enhanced by Hearing One's Own Voice.

The subjective experience of causing an action is known as the sense of agency. Dysfunctional sense of agency over speech has been suggested as a cause of auditory hallucinations. However, agency over speech has not been extensively characterized in previous empirical studies. Here, we manipulated self-voice identity, an indicator of self, embedded in the acoustic quality of voice and examined implicit and explicit measures of the sense of agency. Experiment 1 (N = 29 adults) demonstrated more compression of a perceived interval between action and outcome when participants heard their undistorted voices than their pitch-distorted voices. Experiment 2 (N = 28 adults) revealed a strong top-down effect of self-voice identity: Specifically, the judgment of agency over speech was more resistant than the judgment of agency over hand/limb movement to low-level sensorimotor inconsistency. Our findings provide new insight into the sense of agency over speech and an informative perspective for understanding aberrant experience in auditory hallucinations.

Sense of Agency Beyond Sensorimotor Process: Decoding Self-Other Action Attribution in the Human Brain.

The sense of agency is defined as the subjective experience that "I" am the one who is causing the action. Theoretical studies postulate that this subjective experience is developed through multistep processes extending from the sensorimotor to the cognitive level. However, it remains unclear how the brain processes such different levels of information and constitutes the neural substrates for the sense of agency. To answer this question, we combined two strategies: an experimental paradigm, in which self-agency gradually evolves according to sensorimotor experience, and a multivoxel pattern analysis. The combined strategies revealed that the sensorimotor, posterior parietal, anterior insula, and higher visual cortices contained information on self-other attribution during movement. In addition, we investigated whether the found regions showed a preference for self-other attribution or for sensorimotor information. As a result, the right supramarginal gyrus, a portion of the inferior parietal lobe (IPL), was found to be the most sensitive to self-other attribution among the found regions, while the bilateral precentral gyri and left IPL dominantly reflected sensorimotor information. Our results demonstrate that multiple brain regions are involved in the development of the sense of agency and that these show specific preferences for different levels of information.

Time-dependent neural arbitration between cue associative and episodic fear memories.

After traumatic events, simple cue-threat associative memories strengthen while episodic memories become incoherent. However, how the brain prioritises cue associations over episodic coding of traumatic events remains unclear. Here, we developed an original episodic threat conditioning paradigm in which participants concurrently form two memory representations: cue associations and episodic cue sequence. We discovered that these two distinct memories compete for physiological fear expression, reorganising overnight from an overgeneralised cue-based to a precise sequence-based expression. With multivariate fMRI, we track inter-area communication of the memory representations to reveal that a rebalancing between hippocampal- and prefrontal control of the fear regulatory circuit governs this memory maturation. Critically, this overnight re-organisation is altered with heightened trait anxiety. Together, we show the brain prioritises generalisable associative memories under recent traumatic stress but resorts to selective episodic memories 24 h later. Time-dependent memory competition may provide a unifying account for memory dysfunctions in post-traumatic stress disorders.

Neuroimaging Examination of Driving Mode Switching Corresponding to Changes in the Driving Environment.

Car driving is supported by perceptual, cognitive, and motor skills trained through continuous daily practice. One of the skills that characterize experienced drivers is to detect changes in the driving environment and then flexibly switch their driving modes in response to the changes. Previous functional neuroimaging studies on motor control investigated the mechanisms underlying behaviors adaptive to changes in control properties or parameters of experimental devices such as a computer mouse or a joystick. The switching of multiple internal models mainly engages adaptive behaviors and underlies the interplay between the cerebellum and frontoparietal network (FPN) regions as the neural process. However, it remains unclear whether the neural mechanisms identified in previous motor control studies also underlie practical driving behaviors. In the current study, we measure functional magnetic resonance imaging (fMRI) activities while participants control a realistic driving simulator inside the MRI scanner. Here, the accelerator sensitivity of a virtual car is abruptly changed, requiring participants to respond to this change flexibly to maintain stable driving. We first compare brain activities before and after the sensitivity change. As a result, sensorimotor areas, including the left cerebellum, increase their activities after the sensitivity change. Moreover, after the change, activity significantly increases in the inferior parietal lobe (IPL) and dorsolateral prefrontal cortex (DLPFC), parts of the FPN regions. By contrast, the posterior cingulate cortex, a part of the default mode network, deactivates after the sensitivity change. Our results suggest that the neural bases found in previous experimental studies can serve as the foundation of adaptive driving behaviors. At the same time, this study also highlights the unique contribution of non-motor regions to addressing the high cognitive demands of driving.

Perception and control: individual difference in the sense of agency is associated with learnability in sensorimotor adaptation.

Adaptive motor learning refers to the ability to adjust to novel disturbances in the environment as a way of minimizing sensorimotor errors. It is known that such processes show large individual differences and are linked to multiple perceptual and cognitive processes. On the other hand, the sense of agency refers to the subjective feeling of control during voluntary motor control. Is the sense of agency just a by-product of the control outcome, or is it actually important for motor control and learning? To answer this question, this study takes an approach based on individual differences to investigate the relationship between the sense of agency and learnability in sensorimotor adaptation. Specifically, we use an adaptive motor learning task to measure individual differences in the efficiency of motor learning. Regarding the sense of agency, we measure the perceptual sensitivity of detecting an increase or a decrease in control when the actual level of control gradually increases or decreases, respectively. The results of structure equation modelling reveal a significant influence of perceptual sensitivity to increased control on motor learning efficiency. On the other hand, the link between perceptual sensitivity to decreased control and motor learning is nonsignificant. The results show that the sense of agency in detecting increased control is associated with the actual ability of sensorimotor adaptation: people who are more sensitive in detecting their control in the environment can also more quickly adjust their behaviors to novel disturbances to acquire better control, compared to people who have a less sensitive sense of agency. Finally, the results also reveal that the processes of increasing control and decreasing control may be partially independent.

Categorical Perception of Control.

The self is a distinct entity from the rest of the world, and actions and sensory feedback are our channels of interaction with the external world. This study examined how the sense of control influences people's perception of sensorimotor input under the framework of categorical perception. Twenty human participants (18 males, two females) took part in both experiments. Experiment 1 showed that the sensitivity (d') of detecting a 20% change in control from no change was higher when the changes occurred at the control-category boundary than within each category. Experiment 2 showed that the control categories greatly affected early attention allocation, even when the judgment of control was unnecessary to the task. Taken together, these results showed that our perceptual and cognitive systems are highly sensitive to small changes in control that build up to a determinant change in the control category within a relatively narrow boundary zone between categories, compared with a continuous, gradual physical change in control.

The Active Sensing of Control Difference.

In everyday life, people control objects in the world around them to varying degrees. The processes people actively use to establish their control, while interacting with an environment containing large ambiguity, remain unknown. This study examines how people explore their control over the environment and how they detect small differences in control among objects. In the experimental task, participants moved three dots on a screen and identified one dot over which the level of control is different from that of the other two. The results support a two-step behavior mechanism underlying the sensing of control difference: People first explore their overall control in the environment, and then the results of the initial exploration are used to selectively tune the direction (i.e., either more or less) of the detected control difference, ensuring efficient and rapid detection of the type of control difference that is potentially important for further action selections.

Single-trial prediction of reaction time variability from MEG brain activity.

Neural activity prior to movement onset contains essential information for predictive assistance for humans using brain-machine-interfaces (BMIs). Even though previous studies successfully predicted different goals for upcoming movements, it is unclear whether non-invasive recording signals contain the information to predict trial-by-trial behavioral variability under the same movement. In this paper, we examined the predictability of subsequent short or long reaction times (RTs) from magnetoencephalography (MEG) signals in a delayed-reach task. The difference in RTs was classified significantly above chance from 550 ms before the go-signal onset using the cortical currents in the premotor cortex. Significantly above-chance classification was performed in the lateral prefrontal and the right inferior parietal cortices at the late stage of the delay period. Thus, inter-trial variability in RTs is predictable information. Our study provides a proof-of-concept of the future development of non-invasive BMIs to prevent delayed movements.