Visual Discrimination

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Allan J Hobson - One of the best experts on this subject based on the ideXlab platform.

  • Visual Discrimination learning requires sleep after training
    Nature Neuroscience, 2000
    Co-Authors: Robert Stickgold, Latanya James, Allan J Hobson
    Abstract:

    Performance on a Visual Discrimination task showed maximal improvement 48–96 hours after initial training, even without intervening practice. When subjects were deprived of sleep for 30 hours after training and then tested after two full nights of recovery sleep, they showed no significant improvement, despite normal levels of alertness. Together with previous findings11 that subjects show no improvement when retested the same day as training, this demonstrates that sleep within 30 hours of training is absolutely required for improved performance.

  • Visual Discrimination task improvement a multi step process occurring during sleep
    Journal of Cognitive Neuroscience, 2000
    Co-Authors: Robert Stickgold, Dana Whidbee, Beth Schirmer, Vipul Patel, Allan J Hobson
    Abstract:

    Performance on a Visual Discrimination task shows long-term improvement after a single training session. When tested within 24 hr of training, improvement was not observed unless subjects obtained at least 6 hr of post-training sleep prior to retesting, in which case improvement was proportional to the amount of sleep in excess of 6 hr. For subjects averaging 8 hr of sleep, overnight improvement was proportional to the amount of slow wave sleep (SWS) in the first quarter of the night, as well as the amount of rapid eye movement sleep (REM) in the last quarter. REM during the intervening 4 hr did not appear to contribute to improvement. A two-step process, modeling throughput as the product of the amount of early SWS and late REM, accounts for 80 percent of intersubject variance. These results suggest that, in the case of this Visual Discrimination task, both SWS and REM are required to consolidate experience-dependent neuronal changes into a form that supports improved task performance.

James David Jentsch - One of the best experts on this subject based on the ideXlab platform.

Sukhwinder S. Shergill - One of the best experts on this subject based on the ideXlab platform.

  • Clarifying the role of pattern separation in schizophrenia: The role of recognition and Visual Discrimination deficits
    Schizophrenia Research, 2015
    Co-Authors: Cristina Martinelli, Sukhwinder S. Shergill
    Abstract:

    Patients with schizophrenia show marked memory deficits which have a negative impact on their functioning and life quality. Recent models suggest that such deficits might be attributable to defective pattern separation (PS), a hippocampal-based computation involved in the differentiation of overlapping stimuli and their mnemonic representations. One previous study on the topic concluded in favour of pattern separation impairments in the illness. However, this study did not clarify whether more elementary recognition and/or Visual Discrimination deficits could explain observed group differences. To address this limitation we investigated pattern separation in 22 schizophrenic patients and 24 healthy controls with the use of a task requiring individuals to classify stimuli as repetitions, novel or similar compared to a previous familiarisation phase. In addition, we employed a Visual Discrimination task involving perceptual similarity judgments on the same images. Results revealed impaired performance in the patient group; both on baseline measure of pattern separation as well as an index of pattern separation rigidity. However, further analyses demonstrated that such differences could be fully explained by recognition and Visual Discrimination deficits. Our findings suggest that pattern separation in schizophrenia is predicated on earlier recognition and Visual Discrimination problems. Furthermore, we demonstrate that future studies on pattern separation should include appropriate measures of recognition and Visual Discrimination performance for the correct interpretation of their findings.

Robert Stickgold - One of the best experts on this subject based on the ideXlab platform.

  • Visual Discrimination learning requires sleep after training
    Nature Neuroscience, 2000
    Co-Authors: Robert Stickgold, Latanya James, Allan J Hobson
    Abstract:

    Performance on a Visual Discrimination task showed maximal improvement 48–96 hours after initial training, even without intervening practice. When subjects were deprived of sleep for 30 hours after training and then tested after two full nights of recovery sleep, they showed no significant improvement, despite normal levels of alertness. Together with previous findings11 that subjects show no improvement when retested the same day as training, this demonstrates that sleep within 30 hours of training is absolutely required for improved performance.

  • Visual Discrimination task improvement a multi step process occurring during sleep
    Journal of Cognitive Neuroscience, 2000
    Co-Authors: Robert Stickgold, Dana Whidbee, Beth Schirmer, Vipul Patel, Allan J Hobson
    Abstract:

    Performance on a Visual Discrimination task shows long-term improvement after a single training session. When tested within 24 hr of training, improvement was not observed unless subjects obtained at least 6 hr of post-training sleep prior to retesting, in which case improvement was proportional to the amount of sleep in excess of 6 hr. For subjects averaging 8 hr of sleep, overnight improvement was proportional to the amount of slow wave sleep (SWS) in the first quarter of the night, as well as the amount of rapid eye movement sleep (REM) in the last quarter. REM during the intervening 4 hr did not appear to contribute to improvement. A two-step process, modeling throughput as the product of the amount of early SWS and late REM, accounts for 80 percent of intersubject variance. These results suggest that, in the case of this Visual Discrimination task, both SWS and REM are required to consolidate experience-dependent neuronal changes into a form that supports improved task performance.

Buyean Lee - One of the best experts on this subject based on the ideXlab platform.

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