Mouse behaviour exhibits the hallmarks of spatial attention
To investigate the neuronal correlates of spatial attention in the vibrissal system of mice, we developed a head-fixed behavioural paradigm. This paradigm involved the presentation of a pseudorandomised sequence of vibration stimuli (Fig. 1a), each vibration delivered either to the left or right whisker pad. Mice were trained to lick a reward spout in response to the whisker vibration to receive a droplet of sucrose solution. Crucially, only responses to vibrations delivered on one whisker pad (the ‘rewarded side’) were met with a droplet of sucrose solution (Fig. 1a green panel). Responses to vibrations on the opposite whisker pad (the ‘unrewarded side’) were not rewarded (Fig. 1a red panel). The identity (left or right) of the rewarded stimulus was alternated across sessions.
The reward contingency manipulation was effective in recruiting spatial attention: although mice typically responded to both stimuli, they exhibited greater responses to the vibrations on the rewarded side (Fig. 1b). Spatial attention was manifest in increased hit rates on the rewarded side. As illustrated in the example mouse, the differential hit rate became increasingly prominent with the number of rewards collected on the attended side (Fig. 1c). The behavioural correlates of spatial attention generalised across mice and were quantified in the following ways; (i) mice exhibited significantly greater hit rates for the rewarded stimulus compared with the unrewarded stimulus (Fig.S1c, grand mean ± SE: ΔHR = 4.41 ± 1.01%, p = 1.4e-3, paired t-test, n = 11 mice); (ii) mice exhibited statistically significant positive correlations between their hit rates on the rewarded side (rewarded hit rate) and the cumulative rewards collected (Fig. 1d, mean ± SD: r = 0.66 ± 0.27, p = 9.98e-6, one sampled t-test, n = 11, Fig.S1d); (iii) in contrast, no reliable statistically significant correlation was found between cumulative rewards collected and hit rate on the unrewarded side (Fig. 1d, mean ± SD: r = -0.11 ± 0.47, p = 0.44, one sampled t-test, n = 11); (iv) the correlations between cumulative rewards collected and rewarded hit rates were also significantly larger than those with unrewarded hit rates (Fig. 1e, mean ± SD: Δr = 0.77 ± 0.53, p = 6.51e-4, paired t-test, n = 11).
To better understand the temporal dynamics of spatial attention in behaviour, we characterised how trial history impacted the way mice responded to stimuli. To this end, we calculated the conditional probabilities of responding given the collection of a reward on a single trial. The collection of a reward was associated with a spatially selective increase in hit rates for epochs on the order of four trials in duration (Fig. 1f for the example mouse and Fig. 1g for the average mouse, Fig.S1g). Specifically, the collection of a reward was associated with a significantly greater subsequent increase in hit rate on the rewarded side than on the unrewarded side. In contrast, unrewarded responses did not herald an epoch of spatially selective responses (Fig.S1h). More broadly, hit rates fluctuated over the course of epochs on the order of 10–20 trials as a function of recent history (Fig. 1g, Fig.S1f). The broad effect of the reward-induced enhanced hit rates affected performance on both attended and unattended sides (Fig. 1g, Fig.S1g). Importantly, however, attended hit rates were especially elevated immediately following the collection of a reward (Fig. 1g, Fig.S1g), suggesting that rewards induced both a long-lasting bilateral tendency to respond as well as a transient, spatially selective enhanced sensitivity.
We next quantified spatial attention using the framework of signal detection theory 22. Eleven of the twelve mice we exposed to the behavioural training protocol demonstrated significant perceptual sensitivity to the attended stimulus (p < 0.05, Fig.S1i). Consistent with earlier results, perceptual sensitivity was significantly elevated with spatial attention and this was statistically significant both for the example mouse (Fig. 1i, mean ± SD: d’Rew – d’Unrew = 0.18 ± 0.77, paired t-test, n = 110 sessions) and across mice (Fig. 1i, grand mean ± SE: d’Rew – d’Unrew = 0.11 ± 0.03, p = 7.8e-3, paired t-test, n = 11 mice, Fig.S1j,k). The side rewarded (left or right) did not significantly affect the degree of spatial attention observed (Fig.S2a, grand mean ± SE: Δd’Right – Δd’Left = 0.04 ± 0.12, p = 0.75, paired t-test, n = 11 mice).
Neuronal responses to whisker vibrations are modulated by behavioural state
We recorded extracellular neuronal activity in the primary vibrissal somatosensory cortex (vS1) as mice performed the behavioural task. Before quantifying the effects of spatial attention on neuronal activity, we first characterised how vS1 neurons responded to vibrations applied to the contralateral whiskers and how these responses were modulated by behavioural choice. Of the 3505 neurons recorded across 5 mice, 1461 exhibited statistically significant responses to the contralateral stimulus (“responsive units”, e.g. Figure 2a,b, see Methods). Neuronal responses were typically characterised by a pronounced increase in firing rate following the onset of whisker vibrations (e.g., Fig. 2a,b). The onset of the first whisker deflection was usually associated with the greatest increase in firing rate (Fig. 2a,b), but in many cases subsequent whisker deflections also elicited increases in firing rate (e.g., Fig. 2b).
Neurons were modulated by choice probability 23: i.e. they exhibited elevated responses in trials associated with behavioural responses (e.g. Figure 2c, Fig.S3a-c). However, as illustrated in Fig. 2d, the correlation between neuronal activity and behaviour became apparent at later stages of response, around 100ms post stimulus onset. At 120 ms post stimulus onset, the cumulative difference between hit and miss trials was statistically significant (Fig. 2d; p < 0.05). The difference between hit and miss trials could not be attributed to the generation of the behavioural action (i.e. licking) as we only included neuronal activity prior to the first lick (see Methods). By this time following stimulus onset, licks had been detected in approximately 15% of hit trials. The effect of choice probability was evident at the neuronal level both within recording sessions (Fig. 2e, unit mean ± SD: ΔResponse = 0.31 ± 0.83 spikes/s, p = 4.74e-7, paired t-test, n = 189 units) and also across sessions (Fig.S3d, unit median, interquartile range: ΔResponse = 1.46% of range, [-1.42%, 3.70%], p = 0.01, Wilcoxon ranked sum test, n = 1461 units). It also generalised to the level of population responses across recordings (Fig. 2f: population mean ± SD: ΔResponse = 3.42 ± 6.09% of range, p = 0.047, paired t-test, n = 15 recordings).
Consistent with prior research 24 and behavioural data suggesting fluctuations in task engagement (e.g. Figure 1f,g, Fig.S1f-h), neuronal encoding of choice probability was heightened following a recent behavioural response (Fig.S3e, median unit, interquartile range: ((Hit – Miss)|Hit) = 2.3% of range, [-2.18%, 5.77%], ((Hit – Miss)|Miss) = 1.2% of range, [-2.56%, 4.99%], ((Hit – Miss)|Hit) – ((Hit – Miss)|Miss) = 0.87% of range, [-4.36%, 5.65%], p = 4.44e-4, Wilcoxon signed rank test, n = 1461 units). Curiously, this behavioural state-dependent modulation of choice probability coincided with a reduction in the neuronal responses associated with miss trials (Fig.S3f, median unit, interquartile range: (Miss|Hit) – (Miss|Miss) = -1.04% of range, [-4.07%, 1.55%], p = 1.02e-23, Wilcoxon signed rank test, n = 1461 units), without a significant change in hit trials (median unit, interquartile range: (Hit|Hit) – (Hit|Miss) = -0.14% of range, [-4.43%, 3.72%], p = 0.055, Wilcoxon signed rank test, n = 1461 units).
Behavioural response to a reversal in reward contingencies
In a second block of trials, we reversed the reward contingencies such that the initially rewarded stimulus became unrewarded (and vice versa, Fig. 3a). This allowed us to behaviourally test the strength of the association created at the outset of the session, and additionally ensured that neurons would be recorded in both rewarded and unrewarded states. Consistent with the formation of a strong association in the first block, mice struggled to behaviourally differentiate the rewarded and unrewarded stimuli following the switch in reward contingencies (Fig.S2b,c). In block 2, mice responded with statistically equivalent hit rates to the rewarded and unrewarded stimuli (Fig.S2d, block 2 grand mean ± SE: ΔHR = -0.46 ± 0.74%, p = 0.54, paired t-test, n = 11 mice).
Nevertheless, mice did adjust their behaviour to novel evidence. The correlations between hit rate and rewards collected for the previously rewarded and unrewarded stimuli reversed in block 2 (Fig.S2e-g, Rewarded mean ± SD: r = 0.69 ± 0.20, p = 5.25e-7, one sampled t-test; Unrewarded mean ± SD: r = 0.12 ± 0.50, p = 0.44, one-sampled t-test, n = 11; Rewarded – Unrewarded mean ± SD: Δr = 0.57 ± 0.54, p = 6.3e-3, paired t-test, n = 11). However, mice generally responded less to both vibration stimuli in the second block. In the second block, hit rates were lower on both the previously rewarded (Fig.S1c, Fig.S2d, grand mean ± SE: ΔHR(B1Rew – B2Unrew) = 14.11% ± 2.23%, p = 8.76e-5, paired t-test, n = 11 mice) and unrewarded sides (Fig.S1c, Fig.S2d, grand mean ± SE: ΔHR(B1Unrew – B2Rew) = 10.16% ± 1.96%, p = 4.16e-4, paired t-test, n = 11 mice); although this reduction was significantly greater for the previously rewarded side (grand mean ± SE: ΔHR(B1Rew – B2Unrew) – ΔHR(B1Unrew – B2Rew) = 3.95% ± 1.44%, p = 0.02, paired t-test, n = 11 mice). In parallel, fewer rewards were collected in the second block (Fig.S1d, Fig.S2h, Block 1 grand mean ± SE: Rewards = 10.85 ± 1.37; Block 2 grand mean ± SE: Rewards = 7.66 ± 1.21; Block 1 – Block 2, grand mean ± SE: ΔRewards = 3.19 ± 0.53, p = 1.33e-4, paired t-test, n = 11 mice).
Overall, there were no statistically significant differences in perceptual sensitivity between the rewarded and unrewarded stimuli in block 2 either at the level of the example mouse (Fig.S2i, block 2 mean ± SD: Δd’ = -0.09 ± 0.84, p = 0.28, paired t-test, n = 110 sessions) or the average mouse (Fig.S2j, grand mean ± SE: Δd’ = -0.01 ± 0.02, p = 0.60, paired t-test, n = 11 mice, see also Fig.S2k-l). Curiously, mice only significantly reduced their perceptual sensitivity to the initially rewarded stimulus in block 2 (mean ± SE: Δd’(B2Unrew – B1Rew) = -0.24 ± 0.05, p = 9.54e-4, paired t-test, n = 11 mice); they did not significantly change their perceptual sensitivity to the initially unrewarded stimulus (Fig.S2f, mean ± SE: Δd’(B2Rew – B1Unrew) = -0.07 ± 0.06, p = 0.30, paired t-test, n = 11 mice).
Distinct neural signatures for behavioural performance and spatial attention
We aimed to establish whether activity in vS1 differentiates between non-specific changes in behavioural state i.e. fluctuations in overall performance, 11 and spatially specific changes induced by attention (i.e. fluctuations in spatial preference). Overall behavioural state and degree of spatial attention are among the factors reflected in the observed differences between the two blocks. These factors are further complicated by fluctuation in the level of motivation 24 and the presence of contradictory evidence in the second block. We therefore do not consider the classification of trials into block 1 and 2 to be a well-controlled symmetrical measure of spatial attention. Figure 3b clearly illustrates the asymmetry between the two blocks. Here, we indexed spatial attention with Pref, which captures the local preference of the mouse for one side over the other (Pref: the difference in hit rates between the left and right sides; see Eq. 1). A spatial preference was established in block 1, and while this preference reversed in block 2, the degree of reversal was not as prominent.
To better capture the observed behaviour, we distinguished Pref from Perf, which quantifies the local non-specific performance of the mouse in vibrissal target detection (Perf: the average hit rate across the two sides; see Eq. 2). The local nature of these indices (10–15 trials) is consistent with the observation that both behaviour (e.g. Figure 1g) and evoked neuronal activity (Fig.S3e,f) fluctuated on rapid timescales as a function of recent history. To characterise the effect of fluctuations in both overall performance and spatial preference on neuronal activity, we indexed all contralateral whisker vibrations according to their associated Perf and Pref, yielding a distribution of trials within a behavioural state space (Fig. 3c). Note that at the extremes of behavioural performance, spatial preference is necessarily close to 0. Nevertheless, as illustrated in Fig. 3c, there were sufficient trials to dissociate different levels of performance from different levels of preference.
We classified each contralateral trial for every responsive neuron (n = 1461) according to the local Perf and Pref indices. Separating trials into quartiles along both dimensions revealed that evoked activity was positively correlated with spatial preference (Fig. 3d, r = 0.97, p = 0.03, Pearson’s correlation coefficient) and not with performance (Fig. 3d, r = 0.77, p = 0.23, Pearson’s correlation coefficient). In other words, the more attentive mice were to the contralateral stimulus relative to the ipsilateral stimulus, the greater the evoked responses of the average unit on the average trial. The positive correlation with spatial preference cannot be attributed to choice probability (Hit vs. Miss) for two reasons: (i) such a correlation would also be present with performance (higher performance indicates higher hit rate), (ii) when we limited the analysis to hit trials, the positive correlation remained highly significant (Fig. 3e, r = 0.98, p = 0.01, Pearson’s correlation coefficient). No significant correlation was observed between spatial preference and evoked responses in miss trials (r=-0.67, p = 0.33, Pearson’s correlation coefficient). Thus, spatial attention increased the gain of neuronal responses in the absence of any differences in sensory input or motor output.
The relationship between neuronal activity and spatial attention can be quantified more simply by comparing the responses of neurons on trials in which mice exhibited opposite attentive preferences of any magnitude. To this end, we divided trials into contralaterally attended (PrefC/L: Pref > 0) and contralaterally unattended (PrefI/L: Pref < 0). The attended trials were associated with significantly greater evoked responses than the unattended trials (mean unit ± SD: PrefC/L – PrefI/L = 1.04 ± 4.93% of range, p = 1.96e-15, paired t-test, n = 1461 units, Fig.S4a-c,g,i). In contrast, high (PerfHigh: Perf > 0.5) and low (PerfLow: Perf < 0.5) performance trials were not associated with significantly different evoked responses (median unit, interquartile range: PerfHigh – PerfLow = 0.16% of range, [-3.19%, 2.80%], p = 0.56, Wilcoxon signed rank test, n = 1461 units, Fig.S4d-f,h,i). Additionally, attentional modulation was significantly greater in hit trials (Fig.S5a,g, median unit, interquartile range: ΔHits(PrefC/L – PrefI/L) = 1.30% of range, [-3.47%, 7.01%], p = 4.31e-13, Wilcoxon signed rank test, n = 1461 units) than in miss trials (Fig.S5b,h, median unit, interquartile range: ΔMisses(PrefC/L – PrefI/L) = 0.40% of range, [-2.96%, 3.95%], p = 2.17e-3, Wilcoxon signed rank test, n = 1442 units; ΔHits(PrefC/L – PrefI/L) – ΔMisses(PrefC/L – PrefI/L) = 1.21% of range, [-5.39%, 7.54%], p = 8.86e-5, Wilcoxon signed rank test, n = 1442 units).
Behavioural and neuronal time-course of spatial attention
The temporal profile of behavioural and neuronal responses can be as informative as their magnitude or frequency. For instance, the time-course of the elevated firing rate observed (Fig. 2d) in the late-stage neuronal responses of hit trials is consistent with previous findings which suggested a causal role for such activity in perception 23. Spatial attention has been shown to elevate neuronal activity even before stimulus onset 25. On a behavioural level, attention is typically associated with accelerated reaction times (e.g. 26, but see also 2). With such findings in mind, we characterised the temporal profile of spatial attention in our behavioural and neuronal data. The behavioural responses of the average mouse to vibrissal stimulation followed a characteristic profile (Fig. 4a), with the first-lick frequency deviating from baseline at ~ 100 ms and reaching its peak at ~ 250 ms after stimulus onset. The perceptual sensitivities (d’) followed a similar time course (Fig. 4b). However, the fastest behavioural responses were not those associated with the highest degree of spatial attention: the differences in perceptual sensitivity (Fig. 4c), although present at short latencies (mean ± SE: Δd’250ms = 0.058 ± 0.017, p = 0.007, one-sampled t-test, n = 11 mice), became more prominent later (e.g. mean ± SE: Δd’750ms = 0.124 ± 0.028, p = 1.14e-3, one-sampled t-test, n = 11 mice).
At the neuronal level, we observed elevated baseline firing rates during the attended state (Fig. 4d; median [interquartile range] ΔSp/s = 0.1486 [-0.1270 0.5052] Sp/s, p = 0.0064, Wilcoxon ranked sum test, n = 1461 units). The sensory evoked responses were also elevated with spatial attention, with gain modulation being most evident at the later stages of evoked response. Intriguingly, attention-induced gain modulation was present even when we subtracted baseline activity from the post-stimulus responses (Fig. 4e) and controlled for behavioural output by limiting the analysis to hit trials only. Even the early (~ 200 ms post-stimulus onset) evoked responses revealed an increased firing rate to attended compared with unattended stimuli (see Fig. 4f, median [interquartile range]: ΔResponse1 ≤ ms≤200 = 0.25 [-1.05 1.30] sp/s, p = 4.74e-4, Wilcoxon signed rank test, n = 1461 units). The difference in firing rate increased in later-stage activity (Fig. 4f, ~ 300 ms post-stimulus onset, median [interquartile range]: ΔResponse201 ≤ ms≤400 = 0.58 [-0.72 2.04] sp/s, p = 2.80e-27, Wilcoxon signed rank test, n = 1461 units; ΔResponse201 ≤ ms≤400 - ΔResponse1 ≤ ms≤200 = 0.30 [-1.24 2.11] sp/s, p = 1.29e-8, Wilcoxon signed rank test, n = 1461 units) and remained high even ~ 500 ms post-stimulus (Fig. 4f, median [interquartile range]: ΔResponse401 ≤ ms≤600 = 0.32 [-1.11 1.87] sp/s, p = 1.12e-8, Wilcoxon signed rank test, n = 1350; ΔResponse401 ≤ ms≤600 - ΔResponse1 ≤ ms≤200 = 0.15 [-1.60 1.98] sp/s, p = 2.37e-3, n = 1350 units). Beyond 600 ms, the difference was no longer statistically significant (Fig. 4f, median [interquartile range]: ΔResponse> 600ms = -0.11 [-1.87 1.76] sp/s, p = 0.19, n = 1461 units).