Blood flow velocity changes in anterior cerebral arteries during cognitive tasks performance

Objective

Transcranial Doppler sonography (TCD) enables monitoring of blood flow velocities (BFVs) in basal cerebral arteries during different cognitive tasks performance with great temporal resolution. So far, BFVs changes during mental activity were monitored primarily in middle cerebral arteries (MCAs) and little is known about these changes in anterior cerebral arteries (ACAs).

Aim

To determine the effect of different cognitive tasks performance on BFV changes and hemispheric dominance in ACAs and to assess the most suitable activation test for monitoring of BFV changes in ACAs.

Methods

Fourteen right-handed, healthy subjects aged 20–26 were included in the study. BFVs in both ACAs were recorded simultaneously during performance of cognitive tasks designed to activate frontal lobes: phonemic verbal fluency test (pVFT), Stroop tests and Trail Making Tests (TMTs).

Results

A statistically significant BFV increase was recorded in both ACAs during performance of all cognitive tasks. Statistically significant right ACA dominance was found during performance of pVFT and TMTB. The most significant BFV increase was obtained during performance of TMTB.

Conclusion

Our result addressed cognitive tests with great activation potential for monitoring of ACAs that might be used in distinguishing of healthy individuals and patients with neurovascular or neurodegenerative diseases.     

中国古代小说视野中的民众“仙界”观念

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What's wrong with promising to try?

There is often something wrong with merely promising to try to φ. In this article I explain what is wrong with such promises. I argue that a promise to try to φ, when it is entirely up to us to φ, is always wrong because it hides a possible choice under the veil of our susceptibility to circumstances beyond our control. I furthermore argue that this is often also the case when matters are not entirely up to us. Finally, I contend that sometimes the promise to try places undue burdens on the promisee.     

PROBABILITY DISCORDANCE AND CHOICE REACTION TIME: I. Effects of discordant probability on choice reaction time during prolonged training

Successive development of disinhibitory action over long monotonous training periods was studied with choice RT stimuli possessing discordant properties related to their relative frequency and the direction of movement. The results indicate that stimuli with strong initial proactive interference on ensuing reaction to the critical probe-stimulus become, with prolonged training, the least interfering.     

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Psychological research on pseudo-profound bullshit—randomly assembled buzz words plugged into a syntactic structure—has only recently begun. Most such research has focused on dispositional traits, such as thinking styles or political orientation. However, none has investigated contextual factors. In two studies, we introduce a new paradigm by investigating the contextual effect on pseudo-profound bullshit and meaningful quotes. In Study 1, all participants rated the profundity of statements in three contexts: (a) isolated, (b) as allegedly said by a famous author, or (c) within a vignette (short story). Study 2 serves as a conceptual replication in which participants rated statements in only one of three contexts. Overall, our results demonstrate that although contextual information such as author's name increases the perceived profundity of bullshit, it has an inconsistent effect on meaningful quotes. The present study helps to better understand the bullshit receptivity while offering a new line of research.     

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Work in behavior-based systems focuses on functional modeling, that is, the synthesis of life-like and/or biologically inspired behavior that is robust, repeatable and adaptive. Inspiration from cognitive science, neuroscience and biology drives the development of new methods and models in behavior-based robotics, and the results tie together several related fields including artificial life, evolutionary computation, and multi-agent systems. Ideas from artificial intelligence and engineering continue to be explored actively and applied to behavior-based robots as their role in animal modeling and practical applications is being developed.