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Causal contribution of primate auditory cortex to auditory perceptual decision-making.

Tsunada J, Liu AS, Gold JI, Cohen YE - Nat. Neurosci. (2015)

Bottom Line: However, the specific and causal contributions of different brain regions in this pathway, including the middle-lateral (ML) and anterolateral (AL) belt regions of the auditory cortex, to auditory decisions have not been fully identified.Both ML and AL neural activity was modulated by the frequency content of the stimulus.Together, these findings suggest that AL directly and causally contributes sensory evidence to form this auditory decision.

View Article: PubMed Central - PubMed

Affiliation: Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

ABSTRACT
Auditory perceptual decisions are thought to be mediated by the ventral auditory pathway. However, the specific and causal contributions of different brain regions in this pathway, including the middle-lateral (ML) and anterolateral (AL) belt regions of the auditory cortex, to auditory decisions have not been fully identified. To identify these contributions, we recorded from and microstimulated ML and AL sites while monkeys decided whether an auditory stimulus contained more low-frequency or high-frequency tone bursts. Both ML and AL neural activity was modulated by the frequency content of the stimulus. But, only the responses of the most stimulus-sensitive AL neurons were systematically modulated by the monkeys' choices. Consistent with this observation, microstimulation of AL, but not ML, systematically biased the monkeys' behavior toward the choice associated with the preferred frequency of the stimulated site. Together, these findings suggest that AL directly and causally contributes sensory evidence to form this auditory decision.

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Psychophysical performance on the low-high taskPsychometric (left) and chronometric (right) functions for Monkey T (top) and Monkey A (bottom). Psychometric functions are plotted as the percentage of trials in which monkey chose “high frequency” as a function of signed coherence, where larger negative/positive coherence values indicate more low/high frequency tone bursts. The horizontal dashed grey lines on the psychometric plots indicate lapse rate (errors for strong stimuli, presumably reflecting lapses in attention or inappropriate application of the decision-motor mapping, which were estimated from logistic-model fits indicated as solid blue curves). Chronometric functions are plotted as the mean RT, which was the time interval between stimulus onset and onset of joystick movement, on correct trials as a function of signed coherence. Grey dots are low-frequency choices, and black dots are high-frequency choices. Solid red curves are simultaneous fits of both psychometric and chronometric data to a drift-diffusion model (DDM)18–20, 29–33. The horizontal dashed grey lines on the chronometric plots indicate choice-dependent non-decision times (NDT) estimated by the DDM fits. Decision times (DT) were estimated as the difference between the trial-specific RT and the choice-specific NDT.
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Figure 2: Psychophysical performance on the low-high taskPsychometric (left) and chronometric (right) functions for Monkey T (top) and Monkey A (bottom). Psychometric functions are plotted as the percentage of trials in which monkey chose “high frequency” as a function of signed coherence, where larger negative/positive coherence values indicate more low/high frequency tone bursts. The horizontal dashed grey lines on the psychometric plots indicate lapse rate (errors for strong stimuli, presumably reflecting lapses in attention or inappropriate application of the decision-motor mapping, which were estimated from logistic-model fits indicated as solid blue curves). Chronometric functions are plotted as the mean RT, which was the time interval between stimulus onset and onset of joystick movement, on correct trials as a function of signed coherence. Grey dots are low-frequency choices, and black dots are high-frequency choices. Solid red curves are simultaneous fits of both psychometric and chronometric data to a drift-diffusion model (DDM)18–20, 29–33. The horizontal dashed grey lines on the chronometric plots indicate choice-dependent non-decision times (NDT) estimated by the DDM fits. Decision times (DT) were estimated as the difference between the trial-specific RT and the choice-specific NDT.

Mentions: Monkeys T (n=52 sessions) and A (n=39 sessions) reliably reported whether a sequence of tone bursts contained more low-frequency or high-frequency tone bursts on the low-high task, with performance that depended systematically on stimulus coherence (Fig. 2). When a stimulus contained mostly low- or high-frequency tone bursts (coherences near ±100%), the monkeys almost always reported the correct answer. This high accuracy for high-coherence stimuli, quantified as low lapse rates (dashed lines in the left panels of Fig. 2), implies that the monkeys were attentive and followed the rules of the task. Their choice accuracy decreased systematically as coherence approached zero; that is, for more difficult stimuli. We quantified this dependence by calculating the monkeys’ discrimination thresholds. These discrimination thresholds, which index the steepness of the psychometric (choice) function with respect to coherence and were computed from logistic functions fit to the psychometric data, imply that the monkeys were using relevant information from the auditory stimuli to inform their decisions (blue lines in the left panels of Fig. 2; median [interquartile range, or IQR] values across sessions were for monkey T and for monkey A). The monkeys were also relatively unbiased, making roughly equal numbers of low- and high-frequency choices (choice biases, measured as the coherence value corresponding to 50% high-frequency choices from the logistic fits, were 13 [−5–31]% coherence for monkey T and −22 [−30–7]% coherence for monkey A).


Causal contribution of primate auditory cortex to auditory perceptual decision-making.

Tsunada J, Liu AS, Gold JI, Cohen YE - Nat. Neurosci. (2015)

Psychophysical performance on the low-high taskPsychometric (left) and chronometric (right) functions for Monkey T (top) and Monkey A (bottom). Psychometric functions are plotted as the percentage of trials in which monkey chose “high frequency” as a function of signed coherence, where larger negative/positive coherence values indicate more low/high frequency tone bursts. The horizontal dashed grey lines on the psychometric plots indicate lapse rate (errors for strong stimuli, presumably reflecting lapses in attention or inappropriate application of the decision-motor mapping, which were estimated from logistic-model fits indicated as solid blue curves). Chronometric functions are plotted as the mean RT, which was the time interval between stimulus onset and onset of joystick movement, on correct trials as a function of signed coherence. Grey dots are low-frequency choices, and black dots are high-frequency choices. Solid red curves are simultaneous fits of both psychometric and chronometric data to a drift-diffusion model (DDM)18–20, 29–33. The horizontal dashed grey lines on the chronometric plots indicate choice-dependent non-decision times (NDT) estimated by the DDM fits. Decision times (DT) were estimated as the difference between the trial-specific RT and the choice-specific NDT.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4696881&req=5

Figure 2: Psychophysical performance on the low-high taskPsychometric (left) and chronometric (right) functions for Monkey T (top) and Monkey A (bottom). Psychometric functions are plotted as the percentage of trials in which monkey chose “high frequency” as a function of signed coherence, where larger negative/positive coherence values indicate more low/high frequency tone bursts. The horizontal dashed grey lines on the psychometric plots indicate lapse rate (errors for strong stimuli, presumably reflecting lapses in attention or inappropriate application of the decision-motor mapping, which were estimated from logistic-model fits indicated as solid blue curves). Chronometric functions are plotted as the mean RT, which was the time interval between stimulus onset and onset of joystick movement, on correct trials as a function of signed coherence. Grey dots are low-frequency choices, and black dots are high-frequency choices. Solid red curves are simultaneous fits of both psychometric and chronometric data to a drift-diffusion model (DDM)18–20, 29–33. The horizontal dashed grey lines on the chronometric plots indicate choice-dependent non-decision times (NDT) estimated by the DDM fits. Decision times (DT) were estimated as the difference between the trial-specific RT and the choice-specific NDT.
Mentions: Monkeys T (n=52 sessions) and A (n=39 sessions) reliably reported whether a sequence of tone bursts contained more low-frequency or high-frequency tone bursts on the low-high task, with performance that depended systematically on stimulus coherence (Fig. 2). When a stimulus contained mostly low- or high-frequency tone bursts (coherences near ±100%), the monkeys almost always reported the correct answer. This high accuracy for high-coherence stimuli, quantified as low lapse rates (dashed lines in the left panels of Fig. 2), implies that the monkeys were attentive and followed the rules of the task. Their choice accuracy decreased systematically as coherence approached zero; that is, for more difficult stimuli. We quantified this dependence by calculating the monkeys’ discrimination thresholds. These discrimination thresholds, which index the steepness of the psychometric (choice) function with respect to coherence and were computed from logistic functions fit to the psychometric data, imply that the monkeys were using relevant information from the auditory stimuli to inform their decisions (blue lines in the left panels of Fig. 2; median [interquartile range, or IQR] values across sessions were for monkey T and for monkey A). The monkeys were also relatively unbiased, making roughly equal numbers of low- and high-frequency choices (choice biases, measured as the coherence value corresponding to 50% high-frequency choices from the logistic fits, were 13 [−5–31]% coherence for monkey T and −22 [−30–7]% coherence for monkey A).

Bottom Line: However, the specific and causal contributions of different brain regions in this pathway, including the middle-lateral (ML) and anterolateral (AL) belt regions of the auditory cortex, to auditory decisions have not been fully identified.Both ML and AL neural activity was modulated by the frequency content of the stimulus.Together, these findings suggest that AL directly and causally contributes sensory evidence to form this auditory decision.

View Article: PubMed Central - PubMed

Affiliation: Department of Otorhinolaryngology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

ABSTRACT
Auditory perceptual decisions are thought to be mediated by the ventral auditory pathway. However, the specific and causal contributions of different brain regions in this pathway, including the middle-lateral (ML) and anterolateral (AL) belt regions of the auditory cortex, to auditory decisions have not been fully identified. To identify these contributions, we recorded from and microstimulated ML and AL sites while monkeys decided whether an auditory stimulus contained more low-frequency or high-frequency tone bursts. Both ML and AL neural activity was modulated by the frequency content of the stimulus. But, only the responses of the most stimulus-sensitive AL neurons were systematically modulated by the monkeys' choices. Consistent with this observation, microstimulation of AL, but not ML, systematically biased the monkeys' behavior toward the choice associated with the preferred frequency of the stimulated site. Together, these findings suggest that AL directly and causally contributes sensory evidence to form this auditory decision.

Show MeSH