Effects of prepulse intensity, duration, and bandwidth on perceived intensity of startling acoustic stimuli

Swerdlow, Neal R.; Blumenthal, Terry D.; Sutherland, Ashley; Weber, Erica; Talledo, Jo

doi:10.1016/j.biopsycho.2006.10.001

Cited by 25 publications

(19 citation statements)

References 24 publications

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“…In contrast, the model that implicitly underlies the PPI ratio metric does not describe scaling of the startle sound. Previous work has observed changes in perceived sound after a prepulse [66][67][68], but this has been conceptualized as a separate phenomenon from PPI, often measured using self-report scales. Our model unifies startle and sound scaling, revealing them to be two components of the phenomenon of PPI, both of which can be observed in the acoustic startle data.…”

Section: Discussionmentioning

confidence: 99%

“…The median normalized error of the two-parameter model was 0.13 lower than the median normalized error of the one-parameter model, meaning that our model with both startle scaling and sound scaling was a better fit to the data by~13% of the standard error of the data points when compared with the model that implicitly underlies PPI ratio with just startle scaling. This new model could also explain the known dependencies of PPI ratio on prepulse condition [1,65], and of self-reported sound intensity on prepulse condition [66,67].…”

Section: A New Analytical Model For Ppimentioning

confidence: 99%

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Robust and replicable measurement for prepulse inhibition of the acoustic startle response

et al. 2020

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Measuring animal behavior in the context of experimental manipulation is critical for modeling, and understanding neuropsychiatric disease. Prepulse inhibition of the acoustic startle response (PPI) is a behavioral phenomenon studied extensively for this purpose, but the results of PPI studies are often inconsistent. As a result, the utility of this phenomenon remains uncertain. Here, we deconstruct the phenomenon of PPI and confirm several limitations of the methodology traditionally utilized to describe PPI, including that the underlying startle response has a non-Gaussian distribution, and that the traditional PPI metric changes with different stimuli. We then develop a novel model that reveals PPI to be a combination of the previously appreciated scaling of the startle response, as well as a scaling of sound processing. Using our model, we find no evidence for differences in PPI in a rat model of Fragile-X Syndrome (FXS) compared with wild-type controls. These results in the rat provide a reliable methodology that could be used to clarify inconsistent PPI results in mice and humans. In contrast, we find robust differences between wild-type male and female rats. Our model allows us to understand the nature of these differences, and we find that both the startle-scaling and sound-scaling components of PPI are a function of the baseline startle response. Males and females differ specifically in the startle-scaling, but not the sound-scaling, component of PPI. These findings establish a robust experimental and analytical approach that has the potential to provide a consistent biomarker of brain function.

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Section: Discussionmentioning

confidence: 99%

Section: A New Analytical Model For Ppimentioning

confidence: 99%

Robust and replicable measurement for prepulse inhibition of the acoustic startle response

et al. 2020

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“…The ASR may be modified quantitatively or qualitatively by a range of natural and experimental conditions (Swerdlow et al, 2000;Bell et al, 2003), a feature that reflects the plasticity of this reflex. The ASR can be diminished by habituation (Gonzalez-Lima et al, 1989;Pilz and Schnitzler, 1996), a previous stimulus (Hoffman and Fleshler, 1963;Braff et al, 2001;Fendt et al, 2001;Swerdlow et al, 2007), positive stimuli (Koch, 1999), and by administration of certain drugs (Swerdlow and Geyer, 1993;Bakshi et al, 1994;Geyer et al, 2001). Conversely, the ASR may also be increased during situations of fear potentiation (Anisman et al, 2000;Davis, 2006;Winslow et al, 2007), anxiety (Kaviani et al, 2004;Prehn et al, 2006), and stress (Andreski et al, 1998;Stam, 2007).…”

Section: Introductionmentioning

confidence: 99%

Neurochemistry of the afferents to the rat cochlear root nucleus: Possible synaptic modulation of the acoustic startle

et al. 2008

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Afferents to the primary startle circuit are essential for the elicitation and modulation of the acoustic startle reflex (ASR). In the rat, cochlear root neurons (CRNs) comprise the first component of the acoustic startle circuit and play a crucial role in mediating the ASR. Nevertheless, the neurochemical pattern of their afferents remains unclear. To determine the distribution of excitatory and inhibitory inputs, we used confocal microscopy to analyze the immunostaining for vesicular glutamate and GABA transporter proteins (VGLUT1 and VGAT) on retrogradely labeled CRNs. We also used reverse transcription-polymerase chain reaction (RT-PCR) and immunohistochemistry to detect and localize specific neurotransmitter receptor subunits in the cochlear root. Our results show differential distributions of VGLUT1- and VGAT-immunoreactive endings around cell bodies and dendrites. The RT-PCR data showed a positive band for several ionotropic glutamate receptor subunits, M1-M5 muscarinic receptor subtypes, the glycine receptor alpha1 subunit (GlyRalpha1), GABAA, GABAB, and subunits of alpha2 and beta-noradrenergic receptors. By immunohistochemistry, we confirmed that CRN cell bodies exhibit positive immunoreaction for the glutamate receptor (GluR) 3 and NR1 GluR subunits. Cell bodies and dendrites were also positive for M2 and M4, and GlyRalpha1. Other subunits, such as GluR1 and GluR4 of the AMPA GluRs, were observed in glial cells neighboring unlabeled CRN cell bodies. We further confirmed the existence of noradrenergic afferents onto CRNs from the locus coeruleus by combining tyrosine hydroxylase immunohistochemistry and tract-tracing experiments. Our results provide valuable information toward understanding how CRNs might integrate excitatory and inhibitory inputs, and hence how they could elicit and modulate the ASR.

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“…This new model could also explain the known dependencies of PPIratio on prepulse condition 1,62 and of self-reported sound intensity on prepulse condition 63,64 . Prepulse conditions with greater magnitude prepulse sounds and shorter delays produced greater scaling of the baseline startle curve ( Fig.…”

Section: A New Analytical Model For Ppimentioning

confidence: 86%

“…In contrast, the model that implicitly underlies the PPIratio metric does not describe scaling of the startle sound. Previous work has observed changes in perceived sound after a prepulse 63,64,67 , but this has been conceptualized as a separate phenomenon from PPI, often measured using self-report scales. Our model unifies startle-scaling and sound-scaling, revealing them to be two components of the PPI phenomenon, both of which can be observed in the acoustic startle data.…”

Section: Benefits Of a New Model Of Ppimentioning

confidence: 99%

Robust and replicable measurement for prepulse inhibition of the acoustic startle response

Miller¹,

Kastner²,

Grzybowski

et al. 2019

Preprint

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Measuring animal behavior in the context of experimental manipulation is critical for modeling and understanding neuro-psychiatric disease. Prepulse inhibition of the acoustic startle response (PPI) is a behavioral paradigm used extensively for this purpose, but the results of PPI studies are often inconsistent. As a result, the utility of this metric remains uncertain. Here we deconstruct the phenomenon of PPI. We first confirm several limitations of the traditional PPI metric, including that the underlying startle response has a non-Gaussian distribution and that the traditional PPI metric changes with different stimulus condition. We then develop a novel model that reveals PPI to be a combination of the previously appreciated scaling of the startle response, as well as a scaling of sound perception. Using our model, we find no evidence for differences in PPI in a rat model of Fragile-X Syndrome (FXS) compared to wild-type controls. These results in the rat provide a reliable methodology that could be used to clarify inconsistent PPI results in mice and humans. In addition, we find robust differences between wild-type male and female rats. Our model allows us to understand the nature of these differences, and we find that both the startle-scaling and sound-scaling components of PPI are a function of the baseline startle response. Males and females differ specifically in the startle-scaling, but not the sound-scaling, component of PPI. These findings establish a robust experimental and analytical approach that has the potential to provide a consistent biomarker of brain function.state 41 , habituation 42 , socialization 43,44 , and the baseline startle response 45 . Consequently, there is a pressing need for an approach that could consistently identify real differences among groups. We therefore sought to deconstruct the phenomenon of PPI to develop a more accurate methodology for capturing the way in which a prepulse stimulus modifies the acoustic startle response.The traditional methodology for PPI makes four assumptions: 1) the startle response can be accurately measured with a small number of trials per animal; 2) the startle response has an approximately Gaussian distribution, allowing the use of the mean startle response as the basis of the PPI metric; 3) PPI is stable across startle sound levels, enabling the measurement of PPI at a single startle level instead of necessitating a full measurement of the startle function; and 4) PPI is independent of the baseline startle response, allowing for a direct combination of PPI results between animals.Using data from 72 rats across more than 100 stimulus conditions, for a total of over 300,000 trials, we replicated previous work demonstrating that the aforementioned assumptions do not hold. Specifically, our findings confirm: 1) the startle response is highly variable 46 ; 2) the startle response has a non-Gaussian distribution that is better represented by a log-normal distribution 47 ; 3) the traditional metric used for PPI systematically decreases as a functio...

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Effects of prepulse intensity, duration, and bandwidth on perceived intensity of startling acoustic stimuli

Cited by 25 publications

References 24 publications

Robust and replicable measurement for prepulse inhibition of the acoustic startle response

Robust and replicable measurement for prepulse inhibition of the acoustic startle response

Neurochemistry of the afferents to the rat cochlear root nucleus: Possible synaptic modulation of the acoustic startle

Robust and replicable measurement for prepulse inhibition of the acoustic startle response

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