Biology subjects

Tanaka, D.

Publications and source records attributed to Tanaka, D..

3 recordsLinked to original sources

bioRxiv2022

An excitatory-inhibitory fronto-cerebellar loop resolves the Stroop effect

The Stroop effect is a well-known behavioral phenomenon in humans that refers to robust interference between language and color information. Although this effect has long been studied, it remains unclear when the interference occurs and how it is resolved in the brain. By manipulating the verbality of stimulus perception and response generation, here we show that the Stroop effect occurs during perception of color-word stimuli and is resolved by a cross-hemispheric, excitatory-inhibitory functional loop involving the lateral prefrontal cortex and cerebellum. Humans performed a Stroop task and a control task in which the stimulus did not contain verbal information, and made a response either vocally or manually. The resolution of Stroop interference involved the lateral prefrontal cortex in the left hemisphere and the cerebellum in the right hemisphere, independently of whether the response was made vocally or manually. In contrast, such cross-hemispheric lateralization was absent during the non-verbal control task. Moreover, the prefrontal cortex amplified cerebellar activity, whereas the cerebellum suppressed prefrontal activity, and these effects were enhanced during interference resolution. These results suggest that this fronto-cerebellar loop involving language and cognitive systems regulates goal-relevant information to resolve the interference occurring during simultaneous perception of a word and color.

neuroscience↗

bioRxiv2021

Anticipatory dynamics in the human brain guide foraging for primary rewards

Deciding whether to wait for a future reward is crucial for acquiring rewards in an uncertain world and involves anticipating future reward attainment. While seeking for a reward in natural environments, behavioral agents constantly face a trade-off between staying in their current environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here we show that anticipatory brain activity in the anterior prefrontal cortex (aPFC) and hippocampus underpins continuous stay-leave decision making. Human participants awaited for real liquid rewards available after tens of seconds, and continuous decision was tracked by monitoring dynamic patterns of brain activity. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When dynamic activity reflecting the anticipation of a future reward was enhanced in the aPFC, participants remained in their current environment, but when this activity diminished, they left the environment for a new one. The anticipatory activity in the aPFC and hippocampus was associated with distinct decision strategies; aPFC activity was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced activity in the hippocampus. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision making while anticipating a future reward.

neuroscience↗

bioRxiv2018

ReALLEN: structural variation discovery in cancer genome by sensitive analysis of single-end reads.

BackgroundThe structural abnormalities in chromosomes are important issues in cancer genomics. Next generation sequencing technologies have big potentials to detect the structural variations precisely and comprehensively. Nevertheless, it is still difficult problem to detect large structural variations from short read sequence data. Major efforts have been achieved with paired-end reads, since discordant pairs directly reflect the existence of large rearrangement. Furthermore, approaches to detect structural variations from single-end reads are still worthwhile challenge because they allow wide choices of sequencing platforms.\n\nResultWe present ReALLEN, a series of tools to detect genomic rearrangement with base-pair resolution from single-end reads provided by next generation sequencing. We examined the performance of ReALLEN using simulated dataset and real dataset sequenced by Ion Torrent systems. In most cases on the simulated dataset, ReALLEN showed nearly 100% precision and better sensitivity than other major tools. Notably, ReALLEN showed stable scores even if it was on some unfavorable conditions, for example, low coverage or small variant size. On the real dataset sequenced by Ion Torrent systems, ReALLEN accurately found an insertional translocation that was crucial for the diagnosis of chronic myeloid leukemia.\n\nConclusionReALLEN is useful to researchers in finding genomic rearrangements. It will contribute to discovery of cancer-specific fusion proteins, precise diagnosis of known types of cancers, and understanding of genetic diseases caused by abnormal chromosomes.

bioinformatics↗