The Experts below are selected from a list of 261 Experts worldwide ranked by ideXlab platform
Dean V. Buonomano - One of the best experts on this subject based on the ideXlab platform.
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Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing.
Trends in neurosciences, 2018Co-Authors: Helen Motanis, Michael J. Seay, Dean V. BuonomanoAbstract:The ability to detect time Intervals and temporal patterns is critical to some of the most fundamental computations the brain performs, including the ability to communicate and appraise a dynamically changing environment. Many of these computations take place on the scale of tens to hundreds of milliseconds. Electrophysiological evidence shows that some neurons respond selectively to Duration, Interval, rate, or order. Because the time constants of many time-varying neural and synaptic properties, including short-term synaptic plasticity (STP), are also in the range of tens to hundreds of milliseconds, they are strong candidates to underlie the formation of temporally selective neurons. Neurophysiological studies indicate that STP is indeed one of the mechanisms that contributes to temporal selectivity, and computational models demonstrate that neurons embedded in local microcircuits exhibit temporal selectivity if their synapses undergo STP. Converging evidence suggests that some forms of temporal selectivity emerge from the dynamic changes in the balance of excitation and inhibition imposed by STP.
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Learning and Generalization of Auditory Temporal–Interval Discrimination in Humans
The Journal of neuroscience : the official journal of the Society for Neuroscience, 1997Co-Authors: Beverly A. Wright, Dean V. Buonomano, Henry W. Mahncke, Michael M. MerzenichAbstract:The sensory encoding of the Duration, Interval, and order of different stimulus features provides vital information to the nervous system. The present study focuses on the influence of practice on auditory temporal-Interval discrimination. The goals of the experiment were to determine (1) whether practice improved the ability to discriminate a standard Interval of 100 msec bounded by brief 1 kHz tones from longer Intervals, and, if so, (2) whether this improvement generalized to different tonal frequencies or temporal Intervals. Learning was examined in 14 human subjects using an adaptive, two-alternative, forced-choice procedure. One hour of training per day for 10 d led to marked improvements in the ability to discriminate between the standard and longer Intervals. The generalization of learning was evaluated by independently varying the spectral (tonal frequency) and temporal (Interval) components of the stimuli in four conditions tested both before and after the training phase. Remarkably, there was complete generalization to the trained Interval of 100 msec bounded by tones at the untrained frequency of 4 kHz, but no generalization to the untrained Intervals of 50, 200, or 500 msec bounded by tones at the trained frequency of 1 kHz. Thus, these data show that (1) temporal-Interval discrimination using a 100-msec standard undergoes perceptual learning, and (2) the neural mechanisms underlying this learning are temporally, but not spectrally, specific. These results are compared with those from previous investigations of learning in visual spatial tasks, and are discussed in relation to biologically plausible models of temporal processing.
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learning and generalization of auditory temporal Interval discrimination in humans
The Journal of Neuroscience, 1997Co-Authors: Beverly A. Wright, Dean V. Buonomano, Henry W. Mahncke, Michael M. MerzenichAbstract:The sensory encoding of the Duration, Interval, and order of different stimulus features provides vital information to the nervous system. The present study focuses on the influence of practice on auditory temporal-Interval discrimination. The goals of the experiment were to determine (1) whether practice improved the ability to discriminate a standard Interval of 100 msec bounded by brief 1 kHz tones from longer Intervals, and, if so, (2) whether this improvement generalized to different tonal frequencies or temporal Intervals. Learning was examined in 14 human subjects using an adaptive, two-alternative, forced-choice procedure. One hour of training per day for 10 d led to marked improvements in the ability to discriminate between the standard and longer Intervals. The generalization of learning was evaluated by independently varying the spectral (tonal frequency) and temporal (Interval) components of the stimuli in four conditions tested both before and after the training phase. Remarkably, there was complete generalization to the trained Interval of 100 msec bounded by tones at the untrained frequency of 4 kHz, but no generalization to the untrained Intervals of 50, 200, or 500 msec bounded by tones at the trained frequency of 1 kHz. Thus, these data show that (1) temporal-Interval discrimination using a 100-msec standard undergoes perceptual learning, and (2) the neural mechanisms underlying this learning are temporally, but not spectrally, specific. These results are compared with those from previous investigations of learning in visual spatial tasks, and are discussed in relation to biologically plausible models of temporal processing.
Xiaodan Yuan - One of the best experts on this subject based on the ideXlab platform.
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Annual decline in β-cell function in patients with type 2 diabetes in China.
Diabetes-metabolism Research and Reviews, 2020Co-Authors: Zhenxiu Gao, Wei Yan, Zhaohui Fang, Zongjun Zhang, Li Yuan, Xiaoyun Wang, Zhumin Jia, Yuanyuan Zhu, Joshua D. Miller, Xiaodan YuanAbstract:BACKGROUND The aim of this study was to investigate the annual decline of β-cell function correlated with disease Duration in patients with type 2 diabetes in China. METHODS This cross-sectional study included 4792 adults with type 2 diabetes who were recruited from four university hospital diabetes clinics between April 2018 and November 2018. Baseline data were collected from electric medical records. Participants were divided into 21 groups with 1-year diabetes Duration Interval to assess the decline rate of β-cell function. Homeostatic model assessment model (HOMA 2) model was applied to assess β-cell function. Multiple linear regression model was used to evaluate the association between biochemical and clinical variables and β-cell function. RESULTS In Chinese patients with type 2 diabetes, β-cell function declined by 2% annually. Using angiotensin receptor blockade (ARB) (β = .048; P = .011), metformin (β = .138; P = .021), or insulin (β = .142; P = .018) was associated with increased β-cell function. However, increased BMI (β = -.215; P = .022), alcohol consumption (β = -.331; P
Gareth W. Davison - One of the best experts on this subject based on the ideXlab platform.
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Extremely short Duration Interval exercise improves 24-h glycaemia in men with type 2 diabetes
European journal of applied physiology, 2018Co-Authors: Richard S. Metcalfe, Ben Fitzpatrick, Sinead Fitzpatrick, Gary Mcdermott, Noel E. Brick, Conor Mcclean, Gareth W. DavisonAbstract:Reduced-exertion high-intensity Interval training (REHIT) is a genuinely time-efficient exercise intervention that improves aerobic capacity and blood pressure in men with type 2 diabetes. However, the acute effects of REHIT on 24-h glycaemia have not been examined. 11 men with type 2 diabetes (mean ± SD: age, 52 ± 6 years; BMI, 29.7 ± 3.1 kg/m2; HbA1c, 7.0 ± 0.8%) participated in a randomised, four-trial crossover study, with continual interstitial glucose measurements captured during a 24-h dietary-standardised period following either (1) no exercise (CON); (2) 30 min of continuous exercise (MICT); (3) 10 × 1 min at ~ 90 HRmax (HIIT; time commitment, ~ 25 min); and (4) 2 × 20 s ‘all-out’ sprints (REHIT; time commitment, 10 min). Compared to CON, mean 24-h glucose was lower following REHIT (mean ± 95%CI: − 0.58 ± 0.41 mmol/L, p = 0.008, d = 0.55) and tended to be lower with MICT (− 0.37 ± 0.41 mmol/L, p = 0.08, d = 0.35), but was not significantly altered following HIIT (− 0.37 ± 0.59 mmol/L, p = 0.31, d = 0.35). This seemed to be largely driven by a lower glycaemic response (area under the curve) to dinner following both REHIT and MICT (− 11%, p 0.9 for both) but not HIIT (− 4%, p = 0.22, d = 0.38). Time in hyperglycaemia appeared to be reduced with all three exercise conditions compared with CON (REHIT: − 112 ± 63 min, p = 0.002, d = 0.50; MICT: -115 ± 127 min, p = 0.08, d = 0.50; HIIT − 125 ± 122 min, p = 0.04, d = 0.54), whilst indices of glycaemic variability were not significantly altered. REHIT may offer a genuinely time-efficient exercise option for improving 24-h glycaemia in men with type 2 diabetes and warrants further study.
Theresa M Busch - One of the best experts on this subject based on the ideXlab platform.
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noninvasive monitoring of murinetumor blood flow during and after photodynamictherapy provides early assessment of therapeutic efficacy
Clinical Cancer Research, 2005Co-Authors: Guoqiang Yu, Turgut Durduran, Chao Zhou, Hsingwen Wang, Mary E Putt, Mark H Saunders, Chandra M Sehgal, Eli Glatstein, Arjun G Yodh, Theresa M BuschAbstract:Purpose:To monitor tumor blood flow noninvasively during photodynamic therapy (PDT) and to correlate flow responses with therapeutic efficacy. Experimental Design: Diffuse correlation spectroscopy (DCS) was used to measure blood flow continuously in radiation-induced fibrosarcoma murine tumors during Photofrin (5 mg/kg)/ PDT (75 mW/cm 2 ,1 35 J/cm 2 ). Relative blood flow (rBF; i.e., normalized to preillumination values) was compared with tumor perfusion as determined by power Doppler ultrasound and was corre- lated with treatment durability, defined as the time of tumor growth to a volume of 400 mm 3 . Broadband diffuse reflectance spectroscopy concurrently quantified tumor hemoglobin oxygen saturation (SO2). Results: DCS and power Doppler ultrasound measured similar flow decreases in animals treated with identical protocols. DCS measurement of rBF during PDT revealed a series of PDT-induced peaks and declines dominated by an initial steep increase (average F SE: 168.1 F 39.5%) and subsequent decrease (59.2 F 29.1%). The Duration (Interval time; range, 2.2-15.6 minutes) and slope (flow reduction rate; range, 4.4 -45.8% minute � 1 ) of the decrease correlated significantly (P =0 .0001 and 0.0002,r 2 = 0.79 and 0.67, respectively) with treatment durability. A positive, significant (P =0 .016,r 2 = 0.50) association between Interval time and time-to-400 mm 3 was also detected in animals with depressed pre-PDT blood flow due to hydralazine administration. At 3 hours after PDT, rBF and SO2 were predictive (P V 0.015) of treatment durability. Conclusion: These data suggest a role for DCS in real-time monitoring of PDT vascular response as an indicator of treatment efficacy.
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noninvasive monitoring of murine tumor blood flow during and after photodynamic therapy provides early assessment of therapeutic efficacy
Clinical Cancer Research, 2005Co-Authors: Turgut Durduran, Chao Zhou, Hsingwen Wang, Mary E Putt, Mark H Saunders, Chandra M Sehgal, Eli Glatstein, Arjun G Yodh, Theresa M BuschAbstract:Purpose:To monitor tumor blood flow noninvasively during photodynamic therapy (PDT) and to correlate flow responses with therapeutic efficacy. Experimental Design: Diffuse correlation spectroscopy (DCS) was used to measure blood flow continuously in radiation-induced fibrosarcoma murine tumors during Photofrin (5 mg/kg)/ PDT (75 mW/cm 2 ,1 35 J/cm 2 ). Relative blood flow (rBF; i.e., normalized to preillumination values) was compared with tumor perfusion as determined by power Doppler ultrasound and was corre- lated with treatment durability, defined as the time of tumor growth to a volume of 400 mm 3 . Broadband diffuse reflectance spectroscopy concurrently quantified tumor hemoglobin oxygen saturation (SO2). Results: DCS and power Doppler ultrasound measured similar flow decreases in animals treated with identical protocols. DCS measurement of rBF during PDT revealed a series of PDT-induced peaks and declines dominated by an initial steep increase (average F SE: 168.1 F 39.5%) and subsequent decrease (59.2 F 29.1%). The Duration (Interval time; range, 2.2-15.6 minutes) and slope (flow reduction rate; range, 4.4 -45.8% minute � 1 ) of the decrease correlated significantly (P =0 .0001 and 0.0002,r 2 = 0.79 and 0.67, respectively) with treatment durability. A positive, significant (P =0 .016,r 2 = 0.50) association between Interval time and time-to-400 mm 3 was also detected in animals with depressed pre-PDT blood flow due to hydralazine administration. At 3 hours after PDT, rBF and SO2 were predictive (P V 0.015) of treatment durability. Conclusion: These data suggest a role for DCS in real-time monitoring of PDT vascular response as an indicator of treatment efficacy.
Zhenxiu Gao - One of the best experts on this subject based on the ideXlab platform.
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Annual decline in β-cell function in patients with type 2 diabetes in China.
Diabetes-metabolism Research and Reviews, 2020Co-Authors: Zhenxiu Gao, Wei Yan, Zhaohui Fang, Zongjun Zhang, Li Yuan, Xiaoyun Wang, Zhumin Jia, Yuanyuan Zhu, Joshua D. Miller, Xiaodan YuanAbstract:BACKGROUND The aim of this study was to investigate the annual decline of β-cell function correlated with disease Duration in patients with type 2 diabetes in China. METHODS This cross-sectional study included 4792 adults with type 2 diabetes who were recruited from four university hospital diabetes clinics between April 2018 and November 2018. Baseline data were collected from electric medical records. Participants were divided into 21 groups with 1-year diabetes Duration Interval to assess the decline rate of β-cell function. Homeostatic model assessment model (HOMA 2) model was applied to assess β-cell function. Multiple linear regression model was used to evaluate the association between biochemical and clinical variables and β-cell function. RESULTS In Chinese patients with type 2 diabetes, β-cell function declined by 2% annually. Using angiotensin receptor blockade (ARB) (β = .048; P = .011), metformin (β = .138; P = .021), or insulin (β = .142; P = .018) was associated with increased β-cell function. However, increased BMI (β = -.215; P = .022), alcohol consumption (β = -.331; P
