Common principles underlie the fluctuation of auditory and visual sustained attention

Terashima, Hiroki; Kihara, Ken; Kawahara, Jun; Kondo, Hiroyo

doi:10.1177/1747021820972255

Cited by 11 publications

(16 citation statements)

References 43 publications

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“…Correlations between the task performance and alternation numbers did not reach statistical significance: |r| < 0.36, p > 0.07. The pattern of the results is consistent with previous findings obtained in a laboratory environment (Terashima et al, 2021).…”

Section: Behavioral Performancesupporting

confidence: 91%

“…Stimuli of the auditory gradCPT consisted of sequential narrations by a male (90%) and female (10%) that gradually changed from one to the next (Terashima et al, 2021). Narrations of ten males and ten females chosen from a language database, excluding Japanese narrations, were randomly presented through a run (Figure 1).…”

Section: Stimuli and Proceduresmentioning

confidence: 99%

“…We defined an RT as the relative time from stimulus onset to button press (Esterman et al, 2013;Terashima et al, 2021). The time window to assign the response to each stimulus was set from 70% of the appearance phase to 40% of the disappearing phase.…”

Section: Behavioral Data Analysismentioning

confidence: 99%

“…This functional magnetic resonance imaging (fMRI) study focused on temporal dynamics of brain activity, particularly in an auditory domain. We used an auditory gradCPT, the performance of which was correlated with visual gradCPT performance (Terashima et al, 2021). Participants indicated using a button press whether a voice was male or female for each trial, while listening to a sequence of narrations.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Transitions Between Brain States Predict Auditory Attentional Fluctuations

et al. 2022

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Achievement of task performance is required to maintain a constant level of attention. Attentional level fluctuates over the course of daily activities. However, brain dynamics leading to attentional fluctuation are still unknown. We investigated the underlying mechanisms of sustained attention using functional magnetic resonance imaging (fMRI). Participants were scanned with fMRI while performing an auditory, gradual-onset, continuous performance task (gradCPT). In this task, narrations gradually changed from one to the next. Participants pressed a button for frequent Go trials (i.e., male voices) as quickly as possible and withheld responses to infrequent No-go trials (i.e., female voices). Event-related analysis revealed that frontal and temporal areas, including the auditory cortex, were activated during successful and unsuccessful inhibition of predominant responses. Reaction-time (RT) variability throughout the auditory gradCPT was positively correlated with signal changes in regions of the dorsal attention network: superior frontal gyrus and superior parietal lobule. Energy landscape analysis showed that task-related activations could be clustered into different attractors: regions of the dorsal attention network and default mode network. The number of alternations between RT-stable and erratic periods increased with an increase in transitions between attractors in the brain. Therefore, we conclude that dynamic transitions between brain states are closely linked to auditory attentional fluctuations.

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Section: Behavioral Performancesupporting

confidence: 91%

Section: Stimuli and Proceduresmentioning

confidence: 99%

Section: Behavioral Data Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic Transitions Between Brain States Predict Auditory Attentional Fluctuations

et al. 2022

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“…For completeness, we present the matrices in Figure 3C-D Individual-level stability of predictive network model An ultimate goal of using individual-level approaches in the clinic is to infer future outcomes based on current data. Because the attention network was defined in relation to a statebased cognitive process that itself fluctuates (Cohen and Maunsell 2011;Esterman et al 2013;Esterman et al 2014;Rosenberg et al 2015;Terashima et al 2021), it is possible individual connectivity patterns in the attention network might change over time. Hence, we conducted an exploratory analysis using connectome-based ID and longitudinal datasets with months to years between scans, asking: are connections in the attention network stable enough within individuals to identify a participant from a group?…”

Section: Neuroanatomy Of Cpm Predictive Networkmentioning

confidence: 99%

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth

Horien

Greene

Shen

et al. 2022

Preprint

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Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings for individuals in healthcare settings. Nevertheless, it remains unclear if it is possible to build robust dimensional predictive models of attention in neurodiverse populations. Here, we use five datasets to identify and validate functional connectome-based markers of attention. In dataset one, we use connectome-based predictive modelling and observe successful prediction of performance on an in-scan sustained attention task in a neurodiverse sample of youth. The predictions are not driven by confounds, such as head motion. In dataset two, we find the attention network model defined in dataset one generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets three to five, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attention in neurodiverse youth and support the further development of predictive dimensional models of other clinically-relevant phenotypes.

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Malleability and fluidity of time perception

Kondo,

Gheorghiu,

Pinheiro

2024

Sci Rep

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Time perception is inherently subjective and malleable. We experience a wide range of time scales, from less than a second to decades. In addition, our perception of time can be affected by our attentional and emotional states. Previous psychological and neuroimaging studies have used several paradigms and methods to probe factors that influence time perception. Considering these factors facilitates approaches to improve time management and to enhance sensory experiences. This Collection of time perception studies includes reports that focus on stimulus property, physiological state, cross-modal interaction, attention, learning, age, and environment. These findings help to illuminate the complex mechanisms of time perception. Humans have no absolute sense of time. Time perception is fundamentally subjective and depends on one's experiences and circumstances. Moments of excitement and joy can seem dizzyingly faster, whereas moments of boredom and stress can feel interminable 1 , illustrating how attentional and emotional states affect time perception. Also, time perception has critical effects on many cognitive abilities and motor skills. For instance, we can play the piano with quick movements. Accurate temporal and rhythmic performance are important not only for playing music, but also for multisensory perception, language, and motor planning 2,3 . In addition, we may vividly recall memories from years ago. We have a broad range of time scales 4 . These timings appear to be underpinned by different neural mechanisms 5 . The brain navigates and processes time ranges from subsecond to year, highlighting its remarkable adaptability and complexity.The more often we pay attention to the passage of time, the longer we perceive time to be 6 . Our perception of the passage of time may vary as a function of age and education 7 or mood state 8 . This is probably consistent with the contextual-change hypothesis that the perceived duration of an event is affected by the number of contextual changes 9 . Extending this idea may explain how different age groups perceive time differently. For boys and girls, holiday adventures are hard to come by. Adults have many routine activities and time seems to pass at an accelerated pace. Relative to adults, children may use heuristic methods for duration estimation 10 . However, it should be noted that feeling the passage of time and estimating duration may employ different mechanisms of time perception 11 .A simple explanation for the perceived compression and expansion of time is the event-density hypothesis. This postulates that the number of events occurring during a certain period affects perception of time intervals 12 , assuming that the "internal clock" counts at a constant rhythm 13 . Directing attention to salient stimuli or engaging in complex tasks increases internal pulses, i.e., the density of events, resulting in the perception that time is passing quickly 6 . This hypothesis is consistent with the idea that cellular metabolism and the internal clock are intimately interc...

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Common principles underlie the fluctuation of auditory and visual sustained attention

Cited by 11 publications

References 43 publications

Dynamic Transitions Between Brain States Predict Auditory Attentional Fluctuations

Dynamic Transitions Between Brain States Predict Auditory Attentional Fluctuations

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth

Malleability and fluidity of time perception

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