A new three-component reaction, namely condensation-anti-Michael addition-aromatization, enabling the construction of benzylic compounds is disclosed. This reaction can not only act as an alternative approach to regioselective Csp-H trifluoromethylation of arenes through an "aromatic to be" strategy, but also provides a simple, convenient, step-economic, and practical strategy for the in situ generation of electrophilic p-(trifluoromethyl)benzyl species under extremely mild conditions.

The ability to adjust our behavior flexibly depending on situational demands and changes in the environment is an important characteristic of cognitive control. Previous studies have proved that this type of adaptive control plays a crucial role in selective attention, but have barely explored whether and how attentional networks support adaptive control. In the present study, a Stroop task with a different proportion of incongruent trials was used to investigate the brain activity and connectivity of six typical attentional control networks (i.e., the fronto-parietal network (FPN), cingulo-opercular network (CON), default mode network (DMN), dorsal attention network (DAN), and ventral attention network/salience network (VAN/SN)) in the environment with changing control demand. The behavioral analysis indicated a decreased Stroop interference (incongruent vs. congruent trial response time [RT]) with the increase in the proportion of incongruent trials within a block, indicating that cognitive control was improved there. The fMRI data revealed that the attenuate Stroop interference was accompanied by the activation of frontal and parietal regions, such as bilateral dorsolateral prefrontal cortex and anterior cingulate cortex. Crucially, the improved cognitive control induced by the increased proportion of incongruent trials was associated with the enhanced functional connectivity within the five networks, and a greater connection between CON with the DAN/SN, and between DMN with the CON/DAN/SN. Meanwhile, however, the functional coupling between the FPN and VAN was decreased. These results suggest that flexible regulations of cognitive control are implemented by the large-scale reconfiguration of connectivity patterns among the attentional networks.

BackgroundCognitive flexibility is a core cognitive control function supported by the brain networks of the whole-brain. Schizophrenic patients show deficits in cognitive flexibility in conditions such as task-switching. A large number of neuroimaging studies have revealed abnormalities in local brain activations associated with deficits in cognitive flexibility in schizophrenia, but the relationship between impaired cognitive flexibility and the whole-brain functional connectivity (FC) pattern is unclear.MethodWe investigated the task-based functional connectivity of the whole-brain in patients with schizophrenia and healthy controls during task-switching. Multivariate pattern analysis (MVPA) was utilized to investigate whether the FC pattern can be used as a feature to discriminate schizophrenia patients from healthy controls. Graph theory analysis was further used to quantify the degrees of integration and segregation in the whole-brain networks to interpret the different reconfiguration patterns of brain networks in schizophrenia patients and healthy controls.ResultsThe results showed that the FC pattern classified schizophrenia patients and healthy controls with significant accuracy. Moreover, the altered whole-brain functional connectivity pattern was driven by a lower degree of network integration and segregation in schizophrenia, indicating that both global and local information transfers at the entire-network level were less efficient in schizophrenia patients than in healthy controls during task-switching processing.ConclusionThese results investigated the group differences in FC profiles during task-switching and not only elucidated that FC patterns are changed in schizophrenic patients, suggesting that task-based FC could be used as a potential neuromarker to discriminate schizophrenia patients from healthy controls in cognitive flexibility but also provide increased insight into the brain network organization that may contribute to impaired cognitive flexibility.

Choices between smaller certain reward and larger riskier reward are referred to as risky decision making. Numerous functional magnetic resonance imaging (fMRI) studies have investigated the neural substrates of risky decision making via conventional univariate analytical approaches, revealing dissociable activation of decisions involving certain rewards and risky rewards. However, it is still unclear how the patterns of brain activity predict the choice that the individual will make. With the help of multi-voxel pattern analyses, which is more sensitive for evaluating information encoded in spatially distributed patterns, we showed that fMRI activity patterns represent viable signatures of certain and risky choice and individual differences. Notably, the regions involved in representation of value and risk and cognitive control play prominent roles in differentiating certain and risky choices as well as individuals with distinct risk preference. These results deepen our understanding of the neural correlates of risky decision making as well as emphasize the important roles of regions involved in representation of value and risk cognitive control in predicting risky decision making and individual differences.

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Cognitive control refers to two critical processes: signal monitoring and inhibitory control. Before executing inhibitory control, the individual first monitors the signal of conflict or warning. However, whether the reward influences signal monitoring or inhibitory control remains poorly understood. In addition, some literature employed pretask reward cueing to study the effect of reward, but the role of pretask reward cueing on cognitive control was influenced by response strategies rather than stimulus processing.To address the above issues, the present study designed three novel variants of the classical stop signal task that combined the reward with certain stimuli or stimulus features and held stimulus-processing demands constant while varying attention demands. For experiment 1, participants tried to cancel responses on trials that were interrupted by the infrequent triangle but not to slow the initiation of the response. The results indicated that the SSRTs could be further accelerated if successful response inhibition were rewarded. Experiment 2 involved separation of signal monitoring from the stop signal task. Participants responded by pressing the left or right button when the trials were interrupted by the infrequent triangle. The results showed that participants could monitor a signal faster when the signal was associated with reward and conflicted with current behavior tendencies. Accordingly, we considered that the individual could more quickly activate behavior in correspondence with the signal and control the conflict because the signal monitoring was enhanced by reward, which indicated that the process needs more attention. Experiment 3 is the same as the second experiment, except that when trials were interrupted by an inverse triangle, participants made a dual button press. We found that the reaction time of the reward-related signal was shorter than that of the reward-unrelated signal in Go trials, even though the processing of the stop signal depletes the attention resource. These findings indicate that the reward-related signal captures more attention and enhances signal monitoring.In summary, these findings show that the reward-related signal captures more attention than bias for the enhancement of signal monitoring, thereby leading to more efficient stimulus processing and improving cognitive control.

It is generally assumed that task switching involves working memory, yet some behavioral studies question the relationship between working memory and task switching ability. This debate can be resolved by directly comparing the brain activity pattern in task switching and working memory processes. If the task switching involves working memory, the neural activity patterns evoked by such two tasks would exhibit higher similarity. Here, we employed the task switching task and working memory to investigate the characteristic of the neural representation in such two cognitive processes. A conjunction analysis showed that the bilateral superior parietal lobule (SPL), bilateral insula, bilateral middle frontal gyrus (MFG), bilateral dorsal lateral prefrontal cortex (DLPFC) and pre-supplementary motor area (pre-SMA) were commonly and significantly activated in both task switching and working memory task. Critically, we found that task switching and working memory processing elicited similar activity patterns in bilateral SPL, right insula, left MFG, left DLPFC and pre-SMA, consistent with common neural processes for both tasks. These results not only suggest that the task switching process involves working memory from the perspective of neural representation, but also provide major new insights into the neurocognitive links between task switching and working memory.

Offset compensation is an indispensable functional module in the current CNC system. But offset compensation is not only used to improve machining accuracy, but also can be used to modify path. This paper first discusses the origin of the curve offset in the CNC system, and points out that the essence of the offset curve is a method of path modification. Then the general formula for offset compensation of plane curve is obtained through normalization. Then the classification of offset compensation is explained. Finally, line segments, arcs and B-spline curves are taken as examples to verify the feasibility and practicability of the offset compensation method applied to path processing. The offset compensation method is a flexible and effective path modification method.