Activation of brain mechanisms of attention switching as a function of auditory frequency change

Yago, Elena; Corral, María; Escera, Carles

doi:10.1097/00001756-200112210-00046

Cited by 94 publications

(87 citation statements)

References 23 publications

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“…The same pattern of results was found in a similar arrangement with auditory distracters and visual task-relevant stimuli (e.g. Escera et al, 1998;Escera, Yago, Alho, 2001;Yago, Corral, Escera, 2001). These ERPs are usually interpreted in terms of three distraction-related processing stages.…”

Section: Introductionsupporting

confidence: 68%

Preparation interval and cue utilization in the prevention of distraction

Horváth

2013

Exp Brain Res

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Maintaining a selective attention set allows us to efficiently perform sensory tasks despite the multitude of concurrent sensory stimuli. Unpredictably occurring, rare events nonetheless capture our attention, that is, we get distracted. The present study investigated the efficiency of control over distraction as a function of preparation time available before a forthcoming distracter. A random sequence of short and long tones (100 or 200 ms with 50-50% probability) was presented. Independently from tone duration, occasionally (13.3% of the time), the pitch of a tone was changed. Such rare pitch variants (distracters) usually lead to delayed and less precise discrimination responses, and trigger a characteristic series of eventrelated potentials (ERPs) reflecting the stages of distraction-related processing: starting with negative ERPs signaling the sensory registration of the distracter; a P3a -usually interpreted as a reflection of involuntary attention change; and finally the so-called reorienting negativity signaling the restoration of the task-optimal attention set. In separate conditions, 663 or 346 ms before each tone (long or short cue-tone interval) a visual cue was presented, which signaled whether the forthcoming tone was a distracter (rare pitch variant), with 80% validity.As reflected by reduced reaction time delays and P3a amplitudes, valid cues led to the prevention of distraction, but only in the long cue-tone interval condition. The analyses of the cue-related P3b and contingent negative variation showed that participants made more effort to utilize cue-information to prevent distraction in the long cue-tone-, than in the short cuetone interval condition.

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Section: Introductionsupporting

confidence: 68%

Preparation interval and cue utilization in the prevention of distraction

Horváth

2013

Exp Brain Res

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“…In addition, several other similarities exist among SSA, MMN, and P300. The magnitude of all three increases with deviant rarity, it increases with the parametric deviance of the deviant, and they all show long time constants of seconds or tens of seconds (Näätänen, 1992;Cohen and Polich, 1997;Yago et al, 2001;Ulanovsky et al, 2003). On the basis of this, we speculate that at least some of the simpler properties of P300 may be inherited directly from the MMN, which in turn is attributable to SSA in auditory neurons.…”

Section: Mechanisms Of Adaptationmentioning

confidence: 81%

Multiple Time Scales of Adaptation in Auditory Cortex Neurons

Ulanovsky¹,

Las²,

Farkas³

et al. 2004

J. Neurosci.

660

671

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Neurons in primary auditory cortex (A1) of cats show strong stimulus-specific adaptation (SSA). In probabilistic settings, in which one stimulus is common and another is rare, responses to common sounds adapt more strongly than responses to rare sounds. This SSA could be a correlate of auditory sensory memory at the level of single A1 neurons. Here we studied adaptation in A1 neurons, using three different probabilistic designs. We showed that SSA has several time scales concurrently, spanning many orders of magnitude, from hundreds of milliseconds to tens of seconds. Similar time scales are known for the auditory memory span of humans, as measured both psychophysically and using evoked potentials. A simple model, with linear dependence on both short-term and long-term stimulus history, provided a good fit to A1 responses. Auditory thalamus neurons did not show SSA, and their responses were poorly fitted by the same model. In addition, SSA increased the proportion of failures in the responses of A1 neurons to the adapting stimulus. Finally, SSA caused a bias in the neuronal responses to unbiased stimuli, enhancing the responses to eccentric stimuli. Therefore, we propose that a major function of SSA in A1 neurons is to encode auditory sensory memory on multiple time scales. This SSA might play a role in stream segregation and in binding of auditory objects over many time scales, a property that is crucial for processing of natural auditory scenes in cats and of speech and music in humans.

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“…There is a strong body of evidence (e.g., Alho et al, 1997;Andrés et al, 2006;Berti et al, 2004;Berti and Schröger, 2003;Escera et al, 2000Escera et al, , 1998Escera et al, , 2002Corral, 2003, 2007;Gumenyuk et al, 2004Gumenyuk et al, , 2005Jääskeläinen et al, 1996Jääskeläinen et al, , 1999Parmentier, 2008;Polo et al, 2003;Rinne et al, 2006;Roeber et al, 2003;SanMiguel et al, 2008;Schröger, 1996Schröger, , 1997Schröger et al, 2000;Schröger andWolff, 1998a, 1998b;Wetzel et al, 2004;Wetzel et al, 2006;Schröger, 2007a, 2007b;Yago et al, 2001aYago et al, , 2001bYago et al, , 2003 that supports Näätänen (1990, 2011)'s suggestions that the MMN prediction error can serve as a call for attentional resources. In paradigms where participants complete a behavioural task whilst being played a task irrelevant MMN sequence, the elicitation of MMN is found to impact upon the attentional resources required to complete the task, and the degree of this impact is found to be proportional to the size of the MMN Jääskeläinen et al, 1999;Rinne et al, 2006;Roeber et al, 2003;Schröger, 1996).…”

Section: The Function Of Predictive Processing Systemsmentioning

confidence: 99%