Task reward structure shapes rapid receptive field plasticity in auditory cortex

Abstract

As sensory stimuli and behavioral demands change, the attentive brain quickly identifies task-relevant stimuli and associates them with appropriate motor responses. The effects of attention on sensory processing vary across task paradigms, suggesting that the brain may use multiple strategies and mechanisms to highlight attended stimuli and link them to motor action. To better understand factors that contribute to these variable effects, we studied sensory representations in primary auditory cortex (A1) during two instrumental tasks that shared the same auditory discrimination but required different behavioral responses, either approach or avoidance. In the approach task, ferrets were rewarded for licking a spout when they heard a target tone amid a sequence of reference noise sounds. In the avoidance task, they were punished unless they inhibited licking to the target. To explore how these changes in task reward structure influenced attention-driven rapid plasticity in A1, we measured changes in sensory neural responses during behavior. Responses to the target changed selectively during both tasks but did so with opposite sign. Despite the differences in sign, both effects were consistent with a general neural coding strategy that maximizes discriminability between sound classes. The dependence of the direction of plasticity on task suggests that representations in A1 change not only to sharpen representations of task-relevant stimuli but also to amplify responses to stimuli that signal aversive outcomes and lead to behavioral inhibition. Thus, top-down control of sensory processing can be shaped by task reward structure in addition to the required sensory discrimination.

Fig. 1.

Approach vs. avoidance behaviors. (A) In both tasks, subjects were required to detect a pure tone target (red) after a random number of reference noise sounds (blue). During the approach behavior (timeline, Lower), subjects were positively rewarded with water for licking a water spout 0.1–1.0 s after target onset (green bar) and punished with a timeout for licking earlier (red bar). During avoidance, subjects were rewarded by licking a continuously flowing stream of water during the references and punished with a mild tail shock if they failed to cease licking 0.4 s after target offset. (B) Average behavior during approach experiments, plotted as a function of time after reference (blue) or target onset (red). Shading indicates one SE across sessions. Dashed lines indicate stimulus onset and offset. Licking was minimal during references, because these trials were punished as false alarms; it substantially increased after target onset, and these trials were rewarded as hits. A stereotyped lick rate (five licks per second) is reflected by multiple peaks in the target curve. (C) Average behavior during avoidance experiments, plotted as in B. During references, animals maintained an elevated lick rate to retrieve reward. Licking was attenuated 0.2–0.4 s after target onset until after offset, when licking resulted in punishment for a miss.

Fig. 2.

Examples of spectrotemporal tuning changes during target approach and avoidance behaviors. (A) Data from one neuron during the approach task. The STRF estimated from reference sounds during passive listening (Left) indicates stimulus frequencies and time lags correlated with excited (red) or suppressed (blue) neural spiking. This neuron was excited broadly by 8,000- to 16,000-Hz stimuli, which overlapped the target tone (11,046 Hz). During behavior (Center), a notch appeared at the target frequency in the excitatory region, and the difference between the active and passive STRFs (Right) shows a 23% decrease in gain at the target frequency (“X”). (B) STRF change for a second neuron during approach, plotted as in A. Here the target frequency (11,300 Hz) overlapped an inhibitory subregion of the passive STRF. During behavior, the inhibition grew stronger, producing a net 7% decrease at the target frequency. (C) STRF change for a neuron during avoidance behavior, with the target positioned on the shoulder of an excitatory region of the passive STRF (1,250 Hz). The STRF showed a selective 10% increase at the target frequency during behavior. (D) Data from a second neuron recorded during avoidance, with the target positioned over an inhibitory region (1,350 Hz). The inhibition was mostly abolished during behavior, a 30% increase at the target frequency.

Fig. 3.

Opposite changes in spectrotemporal tuning during approach and avoidance. (A) Average STRF difference between approach behavior and passive listening, aligned at the target frequency and averaged over neurons (Left; n = 270). Red regions indicate frequencies and time lags with increased responsiveness, and blue regions indicate a decrease. The average difference shows a selective decrease in amplitude within 0.25 octave of the target frequency. The histogram (Right) plots the fraction difference at target frequency between each behaving and passive STRF. Filled bars indicate the 86 units showing significant changes (P < 0.05). The mean change across significantly modulated neurons was −24% of peak passive STRF amplitude (median −30%, both significant, P < 0.0001). (B) Average STRF difference for avoidance behavior, plotted as in A (n = 247). In this case, average amplitude increased near the target frequency. The mean change across the 87 significantly modulated neurons was a 20% increase (median 23%, both significant, P < 0.0001).

Fig. 4.

(A) Average STRF change at target frequency during behavior (black bars) and postbehavior (white bars), relative to prebehavior baseline. The opposite sign changes for approach and avoidance largely reversed after behavior was complete. Data are shown for significantly modulated neurons with passive data recorded both before and after behavior (n = 86 approach, 59 avoidance). The gray bar plots the average STRF change during avoidance, after excluding data 150 ms before and after lick events. Error bars indicate 1 SE across neurons. (B) Average STRF change at target, grouped by the difference between neural BF and target frequency. During approach (blue, n = 86), STRF changes tended to be negative for all neurons, but the greatest decrease occurred when BF was within 0.1 octave of the target frequency. During avoidance (red, n = 87), STRF changes were positive for all BF-target frequency distances, and the magnitude was also greatest within 0.1 octave of target.

Fig. 5.

Emergent representation of sound class during behavior. (A) Average fraction change in raw neural response to target (black) and reference (gray) during approach behavior, grouped by BF-target frequency distance (n = 270 neurons with both reference and target data collected during passive listening and behavior). Neurons with BF within 0.1 octave of target frequency showed decreased target vs. reference responses (*P < 0.01), whereas other neurons showed no consistent target response change. Reference responses tended to increase, regardless of BF. (B) Change in raw response during avoidance, plotted as in A (n = 174). Average target responses increased for BF within 0.1 octave of target, whereas reference responses tended to decrease for all neurons. Changes in both A and B are consistent with enhanced reference-target discriminability. (C) Performance of a linear decoder trained to discriminate reference and target sounds from neural responses during approach behavior (red) and passive listening (green, n = 270). Crosses indicate average fraction of correct classifications as a function of the number of neurons in the decoder, fit by a decaying exponential (dashed lines). On average, 11.2 neurons were required to achieve 90% accuracy during behavior, and 16.0 were required during passive listening (bars, Lower, P < 0.001). (D) Performance of a linear decoder trained on avoidance data, plotted as in C (n = 151). During behavior, an average of 13.6 neurons was required to achieve 90% accuracy, and an average of 19.2 was required during passive listening (P < 0.001).