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Learning-related congruent and incongruent changes of excitation and inhibition in distinct cortical areas

['Vahid Esmaeili', 'Laboratory Of Sensory Processing', 'Brain Mind Institute', 'Faculty Of Life Sciences', 'École Polytechnique Fédérale De Lausanne', 'Epfl', 'Lausanne', 'Anastasiia Oryshchuk', 'Reza Asri', 'Keita Tamura']

Date: 2022-06

Excitatory and inhibitory neurons in diverse cortical regions are likely to contribute differentially to the transformation of sensory information into goal-directed motor plans. Here, we investigate the relative changes across mouse sensorimotor cortex in the activity of putative excitatory and inhibitory neurons—categorized as regular or fast spiking (FS) according to their action potential (AP) waveform—comparing before and after learning of a whisker detection task with delayed licking as perceptual report. Surprisingly, we found that the whisker-evoked activity of regular versus FS neurons changed in opposite directions after learning in primary and secondary whisker motor cortices, while it changed similarly in primary and secondary orofacial motor cortices. Our results suggest that changes in the balance of excitation and inhibition in local circuits concurrent with changes in the long-range synaptic inputs in distinct cortical regions might contribute to performance of delayed sensory-to-motor transformation.

Funding: This work was supported by the Swiss National Science Foundation (310030B_166595, 31003A_182010 and CRSII5_177237) (CCHP), the European Research Council (ERC-2011-ADG 293660) (CCHP), European Union’s Marie Skłodowska-Curie Actions (665667, 798617) (KT), the Research Foundation for Opto-science and Technology (KT), the Brain Science Foundation (KT), the Japan Society for the Promotion of Sciences (KT), and the Ichiro Kanehara Foundation (KT). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability: The data used to generate figures that support the findings of this study are freely available in the Open Access CERN database Zenodo: https://doi.org/10.5281/zenodo.6511622 . The Matlab code used to generate figures that support the findings of this study are freely available in the Open Access CERN database Zenodo: https://doi.org/10.5281/zenodo.6511622 .

In the present study, we investigate whether the changes observed during the learning of the whisker detection task with delayed licking are associated with a change in the balance between excitation and inhibition. We used our recently published dataset of high-density silicon probe recordings from 6 cortical regions previously identified to be important during this behavior [ 22 ] and compared the changes in evoked activity of RS and FS units. Interestingly, we found that upon task learning, RS and FS showed opposite changes in some cortical areas, suggesting important changes in local computation, whereas in other regions, RS and FS changed in parallel suggesting rather an overall shift in the synaptic drive to these areas.

Neocortex has regional specializations and a columnar organization divided into layers each containing many classes of neurons varying across diverse features [ 24 – 28 ]. At the most basic level, neocortical neurons can be classified as excitatory (releasing glutamate) or inhibitory (releasing GABA). Many neocortical excitatory neurons send long-range axons projecting to diverse brain regions, whereas most neocortical inhibitory neurons only have local axonal arborizations, thus contributing primarily to the regulation of local microcircuit activity. The balance between excitation and inhibition is likely to have a major impact on neocortical microcircuit computations, and previous work has suggested important changes in this balance across development, brain states, sensorimotor processing and models of brain diseases [ 29 – 36 ]. Inhibitory GABAergic neurons can be further divided into many subclasses, with one of the most prominent being the parvalbumin-expressing (PV) neurons. PV cells provide potent inhibition onto excitatory cells by prominently innervating either the soma and proximal dendrites or the axonal initial segment, thus playing a critical role in controlling the discharge of excitatory neurons. At the millisecond timescale, the PV neurons appear specialized for high-speed synaptic computations with fast membrane time constants and large fast synaptic conductances, receiving substantial excitatory input from many nearby excitatory neurons as well as long-range inputs [ 37 – 42 ]. Within a neocortical microcircuit, PV neurons are likely to play a critical role in controlling the balance between excitation and inhibition. PV cells typically fire at high rates and have short action potential (AP) durations that can be identified from extracellular recordings. In fact, neurons recorded from extracellular recordings are typically classified based of their AP duration, as regular spiking (RS) units, which have broad AP waveforms and correspond mostly to excitatory neurons, and fast spiking (FS) units, which have narrow AP waveforms and largely correspond to inhibitory PV neurons. Previous whisker-related studies have reported experience-dependent plasticity of both excitatory and inhibitory synaptic transmission, with prominent changes reported in PV GABAergic neurons, for example, following whisker deprivation [ 43 , 44 ]. However, it remains unknown how reward-based learning in whisker-dependent tasks might affect the activity of PV neurons, although previous work has revealed prominent changes in PV neuronal activity in mouse motor cortex during learning of a lever press task [ 45 ] and in visual cortex during learning of a visual discrimination task [ 46 ].

Many brain regions are thought to contribute to the performance of goal-directed sensory-to-motor transformations. An increasingly well-defined sensorimotor transformation studied in rodents is the learned association between a whisker sensory input and licking for reward [ 1 – 19 ]. From a cortical perspective considering whisker-dependent tasks requiring licking for perceptual report, sensory processing is prominent in the somatosensory cortices, whereas neuronal activity linked to motor planning during delay periods is primarily found in premotor cortices, and motor commands are more prominent in primary motor cortex [ 20 – 23 ]. We recently showed that in a whisker detection task with delayed licking, the correct execution of the task involves a stereotypical spatiotemporal sequence of whisker deflection-evoked neuronal firing by which sensory cortex appeared to contribute to exciting frontal cortical regions to initiate neuronal delay period activity [ 22 ]. Comparing novice and expert mice, we also found that the learning of the task is accompanied by region- and temporal-specific changes in cortical activity [ 22 ]. These experience-dependent changes in evoked activity likely result from changes in long-range synaptic inputs and changes within local synaptically connected neocortical microcircuits.

Results

Localization and classification of cortical neurons In this study, we further analyzed a data set of extracellular silicon probe recordings of neuronal spiking activity we published recently [22]. We focused our analyses on 6 key neocortical regions: whisker primary somatosensory cortex (wS1), whisker secondary somatosensory cortex (wS2), whisker primary motor cortex (wM1), whisker secondary motor cortex (wM2), anterior lateral motor cortex (ALM) and tongue-jaw primary motor cortex (tjM1) (Fig 1A). These regions participate in a whisker detection task with delayed licking to report perceived stimuli [22]. Mice first went through pretraining to the task structure, which included a brief light flash to indicate trial onset followed 2 seconds later by a brief auditory tone to indicate the beginning of the 1-second reporting period, during which the thirsty mice could lick to receive a water reward (Fig 1B). We recorded from 2 separate groups of mice referred to as “Novice” and “Expert” hereafter, while a brief whisker stimulus was introduced 1 second after the visual cue in a randomized half of the trials, and licking in the reporting window was only rewarded in whisker stimulus trials (Fig 1B and 1C). Expert mice were given additional whisker training through which they learned to lick preferentially in trials with a whisker stimulus (Fig 1B and 1C). However, Novice mice had not learned the stimulus–reward contingency and licked equally in trials with and without whisker stimulus [22]. Through anatomical reconstruction of fluorescently labeled electrode tracks and registration to a digital mouse brain atlas, here, we precisely localize units to specific layers and cortical regions annotated in the Allen Mouse Brain Common Coordinate Framework [47] (Figs 1D and S1). The neuronal location was assigned to the recording site with the largest amplitude spike waveform along the shank of the silicon probe (Fig 1E). Neurons in different cortical regions and layers had diverse firing patterns during task performance (Figs 1F and S1). We further distinguished neurons according to the duration of the AP waveform. In both Novice and Expert mice, we found a bimodal distribution of spike duration, which we labeled as FS units (spike duration below 0.26 ms) and RS units (spike duration above 0.34 ms), according to standard nomenclature [48,49] (Figs 1G and S2). Unexpectedly, we found a larger fraction of FS units in sensory areas compared to frontal areas (S2 Fig), which could in part reflect differential distribution of PV neurons [50] and in part might indicate the known sampling bias of extracellular recordings limited to high-firing neurons, whereas sensory cortex typically has rather sparse activity. During task performance, both FS and RS units had a broad range of baseline firing rates (Fig 1H), which appeared to have a near log-normal distribution in both Novice and Expert mice (S3 Fig). In agreement with previous literature, FS units fired at significantly higher rates than RS units in both Expert and Novice mice (Figs 1I and S3). PPT PowerPoint slide

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TIFF original image Download: Fig 1. Multiarea recordings during delayed whisker detection task and assignment of RS and FS units to cortical subdivisions. (A) Schematic of the whisker detection task with delayed response and the targets of silicon probe recordings. (B) Training paradigm. Novice and Expert mice were first pretrained in a task, where licking after the auditory cue was rewarded. Expert mice were further trained to only lick in whisker trials. (C) Final task structure used during recording sessions (for both groups of mice) and behavioral outcomes. (D) Example coronal section of an Expert mouse brain with fluorescent track of a probe in wS1, registered to the Allen Mouse Brain Atlas, https://mouse.brain-map.org [47]. (E) Reconstructed laminar location of recording sites of the silicon probe shown in (D) according to the Allen Atlas (left); filtered recorded raw data of 7 sites around one detected spike; and average extracted spike waveform for this example neuron (right). After spike sorting, the position of each cluster (i.e., neuron) was assigned to the location of recording site with the largest spike amplitude (filled circle), and spike width was calculated on the average spike waveform from this site. (F) Raster plot and peri-stimulus time histogram for the example neuron shown in (E). Trials are grouped based on outcome. (G) Spike width distribution for neurons recorded in Expert mice. Neurons were categorized as FS (spike width <0.26 ms) or RS (spike width >0.34 ms). Neurons with intermediate spike width (gray bins) were excluded from further analyses. (H) Baseline AP rate in Expert mice. Spike width distribution versus baseline AP rate (left) and overlay of spike rate distribution for RS and FS units. Note the log-normal distribution of baseline firing rates for both RS and FS units. Normal distributions were fitted to the RS and FS histograms (solid lines). (I) Comparison of mean spike rate in RS versus FS neurons of Expert mice. Error bars: SEM. ***: p < 0.001, nonparametric permutation test. (J–O) Opto-tagging GABAergic neurons in VGAT-ChR2 mice. (J) Grand average firing rate of RS (orange, spike width >0.34 ms, 130 neurons from 4 mice) and FS (green, spike width <0.26 ms, 51 neurons from 4 mice) units upon 100-Hz blue light stimulation (shading shows SEM). Note the suppression of activity in RS and the strong increase of activity in FS population. Inset shows the overlay of average spike waveforms for all RS and FS neurons. (K) OMI versus spike width (left) and percentage of modulated neurons (right). Each circle represents one neuron, filled circles indicate neurons with significant OMI (p < 0.05, nonparametric permutation tests). Pie charts show the percentage of neurons in each group with nonsignificant modulation (NS), and significant positive (OMI > 0) or negative (OMI < 0) modulation upon blue light stimulation. (L) Blue light stimulation in VGAT-ChR2 mice increased the activity of narrow-spike neurons labeled as FS, while it suppressed the activity of broad-spike neurons labeled as RS; 100 to 500 ms after light onset. Error bars: SEM; **: p < 0.01; ***: p < 0.001. (M) Raster plot and peri-stimulus time histogram during the first 10 ms of the 100-Hz trains of blue light stimulation for an example opto-tagged neuron. (N) Waffle plots showing broad-spike (orange) and narrow-spike (green) neurons, and the opto-tagged neurons (blue) in each group. Numbers indicate the percentage of opto-tagged neurons in each group. (O) Weighted proportion of neurons with narrow (FS) or broad (RS) spike among opto-tagged neurons in (N). The underlying data for Fig 1 can be found in S1 Data. ALM, anterior lateral motor cortex; AP, action potential; FS, fast spiking; OMI, opto modulation index; RS, regular spiking; tJM1, tongue-jaw primary motor cortex; wM1, whisker primary motor cortex; wM2, whisker secondary motor cortex; wS1, whisker primary somatosensory cortex; wS2, whisker secondary somatosensory cortex. https://doi.org/10.1371/journal.pbio.3001667.g001 To investigate the classification of FS and RS units, we conducted a new set of recordings in which we measured the impact of stimulating genetically defined GABAergic neurons in mice expressing channelrhodopsin-2 (ChR2) under the control of the vesicular GABA transporter (VGAT) [51]. Blue light modulated the firing rate of RS and FS neurons in opposite directions, quantified both at the level of population (Fig 1J) and at the level of individual neurons (Fig 1K). Overall, light stimulation increased the firing rate of FS units (blue light off: 4.3 ± 4.9 Hz; blue light on: 33.9 ± 32.7 Hz; 51 units recorded in 4 mice; nonparametric permutation test, p < 10−4), whereas it decreased the spike rate of RS units (blue light off: 3.2 ± 3.4 Hz; blue light on: 1.3 ± 7.2 Hz; 130 units recorded in 4 mice; nonparametric permutation test, p = 0.009) (Fig 1L). As a second approach, and to avoid network effects of light stimulation [52], we focused only on the first 10-ms window after the onset of light stimulation and identified the opto-tagged neurons based on their fidelity of responses, response onset latency and jitter (Figs 1M–1O and S4). A larger fraction of neurons was opto-tagged among FS neurons compared to RS neurons. These data are therefore consistent with the hypothesis that the majority of FS units are likely to be inhibitory neurons, whereas the majority of RS units are likely to be excitatory neurons.

Strong task modulation of FS neurons Many RS units across all 6 cortical regions change their AP firing rates in response to the whisker deflection [22]. Here, we analyzed the responses of FS units during task performance in Novice and Expert mice (Fig 2). Averaged across cortical areas and quantified over the first 100 ms after whisker deflection, FS neurons in Novice mice increased their firing rate by 4.6 ± 7.9 Hz (392 units recorded in 8 mice), which was significantly higher (Wilcoxon rank-sum test, p = 1 × 10−34) than the increase in firing rate of RS neurons of 1.0 ± 2.4 Hz (1,089 units recorded in 8 mice) (Fig 2A). Task-modulated RS and FS neurons were mainly excited, with only a small fraction showing significant reduction in firing rate (Fig 2B). Similarly, for Expert mice, whisker deflection evoked an increase of FS firing rate of 4.7 ± 9.1 Hz (831 units recorded in 18 mice) which was significantly higher (Wilcoxon rank-sum test, p = 4 × 10−71) than the increase in firing rate of RS neurons of 1.1 ± 3.9 Hz (2,724 units recorded in 18 mice) (Fig 2C). In addition, for Expert mice, FS neurons were more strongly excited during the delay period compared to RS units (change in firing rate of FS neurons: 1.9 ± 4.8 Hz, 831 units recorded in 18 mice; change in firing rate of RS neurons: 0.7 ± 3.2 Hz, 2,724 units recorded in 18 mice; Wilcoxon rank-sum test, p = 1 × 10−30). In Novice mice, there was little delay period activity in either RS or FS units. The largest fraction of modulated neurons during the delay period were FS units in ALM of Expert mice, which were strongly excited (Fig 2D). Analysis of correct rejection trials in Novice and Expert mice revealed that in the absence of the whisker stimulation neuronal activity remained at baseline levels during the delay period in both RS and FS neurons (S5 Fig). Thus, the overall task selectivity of FS unit activity changed in a similar manner across learning compared to our previous quantification of RS units [22], with FS units having overall larger responses. PPT PowerPoint slide

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TIFF original image Download: Fig 2. FS neurons had similar but larger task modulation compared to RS neurons in the same region. (A) Baseline-subtracted (2 seconds prior to visual onset) population firing rates (mean ± SEM) of RS and FS neurons from different regions of Novice mice are superimposed for hit trials. wS1: 73 RS units in 7 mice, 103 FS units in 7 mice; wS2: 120 RS units in 8 mice, 68 FS units in 8 mice; wM1: 147 RS units in 7 mice, 66 FS units in 7 mice; wM2: 244 RS units in 7 mice, 57 FS units in 7 mice; ALM: 234 RS units in 6 mice, 37 FS units in 5 mice; tjM1: 271 RS units in 8 mice, 61 FS units in 8 mice. Average first lick histogram for all Novice mice is shown in the bottom. (B) Percentage of RS (left) and FS (right) neurons in different regions of Novice mice that are positively (top) or negatively (bottom) modulated compared to baseline (nonparametric permutation test, p < 0.025). (C) Similar to (A), but for Expert mice. wS1: 258 RS units in 15 mice, 237 FS units in 15 mice; wS2: 342 RS units in 12 mice, 161 FS units in 12 mice; wM1: 452 RS units in 11 mice, 134 FS units in 11 mice; wM2: 401 RS units in 10 mice, 107 FS units in 10 mice; ALM: 766 RS units in 12 mice, 109 FS units in 12 mice; tjM1: 505 RS units in 11 mice, 83 FS units in 11 mice. Average first lick histogram for all Expert mice is shown in the bottom. (D) Similar to (B), but for Expert mice. Note the difference in color scales for fraction of positively or negatively modulated neurons in b and d. The underlying data for Fig 2 can be found in S2 Data. ALM, anterior lateral motor cortex; FS, fast spiking; RS, regular spiking; tJM1, tongue-jaw primary motor cortex; wM1, whisker primary motor cortex; wM2, whisker secondary motor cortex; wS1, whisker primary somatosensory cortex; wS2, whisker secondary somatosensory cortex. https://doi.org/10.1371/journal.pbio.3001667.g002

Rapid excitation of FS neurons Investigating fast sensory processing evoked by the whisker deflection, we found an overall similar sequential recruitment of RS and FS units across cortical areas in both Novice and Expert mice (Figs 3, S6 and S7). The earliest excitation occurred in wS1 and wS2, followed by wM1 and wM2 (Figs 3A and 3B, S6 and S7). In wS1 and wS2, FS neurons responded at significantly shorter latency than RS units in both Novice and Expert mice (Fig 3C), as described later in more detail. Among the other areas, in Novice mice FS neurons responded with shorter latency than RS units in wM2 (FS: 47.7 ± 38.7 ms, 44/57 units in 8 mice; RS: 61.7 ± 40.7 ms, 126/244 units in 18 mice; Wilcoxon rank-sum test, p = 0.047, false discovery rate (FDR) corrected for multiple comparison), whereas in Expert mice FS neurons responded with shorter latency than RS units in wM1 (FS: 33.1 ± 35.1 ms, 101/134 units in 8 mice; RS: 54.2 ± 48.7 ms, 243/452 units in 18 mice; Wilcoxon rank-sum test, p = 3 × 10−5, FDR-corrected for multiple comparison) (Fig 3C). Comparing Novice and Expert mice, the latency of RS units increased in wM1, but decreased in wM2, upon whisker learning (Figs 3D and S6B) [22]. In contrast, FS units did not significantly change their latency across learning in any of the 6 cortical regions (Figs 3D and S6B). These latency differences reveal that task learning is accompanied by fast dynamic changes in the relative timing of the recruitment of FS and RS units across wM1 and wM2. PPT PowerPoint slide

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TIFF original image Download: Fig 3. Fast propagation of sensory responses across cell classes and cortical regions. (A) Change in firing rate (mean ± SEM) of different cortical regions in the first 100-ms window after whisker deflection for RS (top) and FS (bottom) neurons in Novice (left) and Expert (right) mice (numbers of units and mice are the same as in Fig 2). (B) Whisker-evoked response latency maps. For each silicon probe in Novice (left) and Expert (right) mice, average latency of whisker-evoked response is shown separately for RS and FS units. Circles represent silicon probes and are colored according to the average latency across all responsive neurons recorded on the probe. (C) Comparison of latency of RS versus FS neurons in Novice (left) and Expert (right) mice. (D) Comparison of latency of neurons from Novice versus Expert mice for RS (left) and FS (right) neurons. In (C) and (D), only neurons with a significant whisker response in the first 200 ms (compared to 200 ms before whisker onset, nonparametric permutation test, p < 0.05) were included. Midline represents the median, bottom and top edges show the interquartile range, and whiskers extend to 1.5 times the interquartile range. ***: p < 0.001, **: p < 0.01, *: p < 0.05, ns: p > = 0.05. The underlying data for Fig 3 can be found in S4 and S5 Data. ALM, anterior lateral motor cortex; FS, fast spiking; RS, regular spiking; tJM1, tongue-jaw primary motor cortex; wM1, whisker primary motor cortex; wM2, whisker secondary motor cortex; wS1, whisker primary somatosensory cortex; wS2, whisker secondary somatosensory cortex. https://doi.org/10.1371/journal.pbio.3001667.g003

Fast sensory processing in wS1 and wS2 Having observed the fastest whisker-evoked responses in wS1 and wS2 (Fig 3), we further compared RS and FS units in these areas, by focusing on their response in the first 50-ms window (Fig 4). The whisker-evoked change in firing rates of RS and FS units in wS1 and wS2 remained unchanged across Novice and Expert mice (Fig 4A–4C). However, in both regions and both groups of mice, FS units had larger evoked responses compared to RS units (Novice wS1: 6.0 ± 9.6 Hz for 73 RS units versus 13.9 ± 16.1 Hz for 103 FS units in 8 mice, p < 10−4; Novice wS2: 4.0 ± 4.6 Hz, for 120 RS units versus 12.2 ± 15.8 Hz for 68 FS units in 8 mice, p < 10−4; Expert wS1: 5.3 ± 9.1 Hz for 258 RS units versus 11.9 ± 13.9 Hz for 237 FS units in 18 mice, p < 10−4; Expert wS2: 4.3 ± 8.7 Hz for 342 RS units versus 11.5 ± 13.6 Hz for 161 FS units in 18 mice, p < 10−4; nonparametric permutation tests, FDR-corrected for multiple comparison) (Fig 4C). Neuronal responses in wS1 and wS2 often showed a biphasic response; a fast and sharp evoked response followed by a later secondary wave of spiking activity. While, the fast early response remained unchanged (Fig 2A and 2C), the late response increased across learning in RS and FS units of both wS1 and wS2 areas (S9 Fig), consistent with previous work in wS1 in a whisker detection task without a delay period [6]. PPT PowerPoint slide

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TIFF original image Download: Fig 4. Fast whisker responses in FS neurons of sensory areas. (A) Baseline-subtracted (50 ms prior to whisker onset) population firing rate (mean ± SEM) of RS (left) and FS (right) neurons in wS1 and wS2 of Novice mice. wS1: 73 RS units in 7 mice, 103 FS units in 7 mice; wS2: 120 RS units in 8 mice, 68 FS units in 8 mice. (B) Same as (A) but for Expert mice. wS1: 258 RS units in 15 mice, 237 FS units in 15 mice; wS2: 342 RS units in 12 mice, 161 FS units in 12 mice. (C) Whisker-evoked change in spike rate in the first 50 ms (mean ± SEM) in wS1 and wS2 for RS and FS units and in Novice and Expert mice. ***: p < 0.001. Gray lines show nonsignificant comparisons. (D) Latency of the whisker-evoked response in wS1 and wS2. Only neurons with a significant whisker response in the first 100 ms (compared to 100 ms before whisker onset, nonparametric permutation test, p < 0.05) were included (Novice wS1: 56/73 RS units, 96/103 FS units, 8 mice; Novice wS2: 97/120 RS units, 57/68 FS units, 8 mice; Expert wS1: 190/258 RS units, 210/237 FS units, 18 mice; Expert wS2: 262/342 RS units, 148/161 FS units, 18 mice). Boxplots represent the distribution of the latency defined as the time to reach to half-maximum response. Midline represents the median, bottom and top edges show the interquartile range, and whiskers extend to 1.5 times the interquartile range. ***: p < 0.001, **: p < 0.01. Gray lines show nonsignificant comparisons. (E) Inactivation of wS1 and wS2. Left: Schematic showing the inactivation of wS1 and wS2 areas during whisker stimulus presentation, in VGAT-ChR2 mice [22,51]. Light trials were interleaved with no-light control trials and comprised 1/3 of total trials. Right: Change in hit and FA rate—comparing light and no-light trials—upon optogenetic inactivation of wS1 and wS2. Light colors show individual mice (9 mice), thick lines represent averages, and error bars show SEM. **: p < 0.01, ns: p > = 0.05. The underlying data for Fig 4 can be found in S6 Data. ChR2, channelrhodopsin-2; FA, false alarm; FS, fast spiking; RS, regular spiking; VGAT, vesicular GABA transporter; wS1, whisker primary somatosensory cortex; wS2, whisker secondary somatosensory cortex. https://doi.org/10.1371/journal.pbio.3001667.g004 The latencies of evoked activity in wS1 and wS2 were shorter for FS units compared to RS units for both Novice and Expert mice (Wilcoxon rank-sum tests FDR-corrected for multiple comparison: Novice wS1 p = 1 × 10−7; Novice wS2 p = 1 × 10−3; Expert wS1 p = 1 × 10−10; Expert wS2 p = 9 × 10−6) (Fig 4D). Comparing wS1 and wS2 areas, we found no significant difference in RS units response latencies, whereas FS units in wS1 fired at shorter latencies than FS units in wS2 (Wilcoxon rank-sum test FDR-corrected for multiple comparison, Novice: p = 1 × 10−4, Expert: p = 3 × 10−4). Both wS1 and wS2 therefore responded strongly and similarly to whisker stimulation in both Novice and Expert mice, and no significant change was found in the response of RS or FS units across learning (Fig 4C and 4D). Optogenetic inactivation by applying blue light in VGAT-ChR2 mice to either wS1 and wS2 during the delivery of the whisker stimulus induced a significant decrease in hit rate [22]. Here, we reanalyzed this inactivation data in a direct comparison across these 2 areas and found a significantly stronger deficit induced by inactivation of wS2 compared to wS1 (wS1: Δhit = −0.30 ± 0.13; wS2: Δhit = −0.49 ± 0.12; Wilcoxon signed-rank test, p = 0.0039; 9 mice) (Fig 4E). However, potential differences in the spatial extent of the whisker deflection-evoked responses and the efficacy of optogenetic inactivation in wS1 versus wS2 make it difficult to conclude the relative importance of sensory processing in these 2 areas. Nonetheless, the data suggest that neuronal activity in both wS1 and wS2 is involved in execution of this whisker detection task.

Changes in fast sensory processing in wM1 and wM2 We next investigated the changes in whisker deflection-evoked neuronal activity in wM1 and wM2 across task learning. RS and FS neurons in both wM1 and wM2 and in both Novice and Expert mice showed obvious fast sensory-evoked modulation, dominated by units with increased AP firing (Figs 2 and 3 and 6). However, RS and FS neurons changed their activity patterns differentially across learning in these 2 neighboring cortical areas. In wM1, RS units had a smaller whisker-evoked response in Expert compared to Novice mice (Novice: 1.8 ± 3.0 Hz, 147 units recorded in 7 mice, Expert: 0.9 ± 3.9 Hz, 452 units recorded in 11 mice; nonparametric permutation test, p = 0.002) (Figs 6A and S10), whereas FS units had a larger response in Expert mice (Novice: 3.1 ± 3.6 Hz, 66 units recorded in 7 mice, Expert: 7.3 ± 16.9 Hz, 134 units recorded in 11 mice; nonparametric permutation test, p = 0.0008) (Figs 6B and S10). The ratio of RS to FS firing in wM1 is therefore strongly changed in Expert mice in favor of FS units. PPT PowerPoint slide

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TIFF original image Download: Fig 6. Learning differently modulated sensory responses of RS and FS neurons in wM1 and wM2 areas. (A) Decrease of whisker response in wM1 RS neurons across learning. Top: baseline-subtracted (50 ms prior to whisker onset) population firing rate (mean ± SEM) overlaid for Novice mice (147 neurons in 7 mice) and Expert mice (452 neurons in 11 mice). Bottom: Comparison of whisker-evoked response in Novice and Expert mice. Bar plots showing average population rate in 10- to 90-ms window (mean ± SEM) after whisker onset and statistical comparison using nonparametric permutation test (left) (**: p < 0.01; *: p < 0.05). The fraction of positively (filled bars) or negatively (empty bars) modulated neurons in the same window (right). Modulation of individual neurons compared to a similar window size prior to whisker onset, was identified using nonparametric permutation test (p < 0.005). The fractions of modulated neurons in Novice and Expert were compared using a chi-squared proportion test (*: p < 0.05; ns: p > = 0.05). (B) Increase of whisker response in wM1 FS neurons across learning. Panels are similar to (A) but for wM1 FS neurons in Novice (66 neurons in 7 mice) and Expert mice (134 neurons in 11 mice) (***: p < 0.001). (C) Increase of whisker response in wM2 RS neurons across learning. Panels are similar to (A) but for wM2 RS neurons in Novice (244 neurons in 7 mice) and Expert mice (401 neurons in 10 mice). (D) Decrease of whisker response in wM2 FS neurons across learning. Panels are similar to (A) but for wM2 FS neurons in Novice (57 neurons in 7 mice) and Expert mice (107 neurons in 10 mice). (E) Pair-wise correlation between sensory and motor cortices in Novice and Expert mice. Left: Scatter plot showing the trial-by-trial correlation between the whisker-evoked response of an example pair of neurons in wS2 and wM2. Each circle represents the response of the neuronal pair in one trial. Circles were jittered slightly for the purpose of visualization. Gray line: least-squares regression. Middle: Average pair-wise Pearson correlation of wS1-RS units with wM1-RS (110 neuron pairs in 1 Novice mouse, and 68 neuron pairs in 2 Expert mice) and wS1-RS units with wM1-FS units (44 neuron pairs in 1 Novice mouse, and 89 neuron pairs in 2 Expert mice) separately. Right: Average pair-wise Pearson correlation of wS2-RS units with wM2-RS (876 neuron pairs in 6 Novice mouse, and 583 neuron pairs in 3 Expert mice) and wS2-RS units with wM2-FS units (343 neuron pairs in 6 Novice mouse, and 209 neuron pairs in 3 Expert mice). Error bars: SEM. Statistical comparison between Novice and Expert was performed using Wilcoxon rank-sum test (ns: p > = 0.05; *: p < 0.05; ***: p < 0.001). (F) Interareal functional connectivity identified based on cross-correlograms. Left: Example cross-correlogram between a pair of simultaneously recorded neurons from wS2 and wM2. Red dotted line shows the threshold for detecting sharp peaks. A directional connection from wS2 to wM2 was detected as there is a threshold crossing within the time lags between 0 and 10 ms. Middle: Percentage of detected directional connections from wS1-RS units to wM1-RS and wM1-FS units in 1 Novice and 2 Expert mice. Right: Percentage of detected directional connections from wS2-RS units to wM2-RS and wM2-FS units in 6 Novice and 3 Expert mice. The numbers on each bar represent the number of identified connections and the total number of recorded pairs. The fractions of connections in Novice and Expert were compared using a chi-squared proportion test (ns: p > = 0.05; **: p < 0.01). The underlying data for Fig 6 can be found in S8 Data. FS, fast spiking; RS, regular spiking; wM1, whisker primary motor cortex; wM2, whisker secondary motor cortex. https://doi.org/10.1371/journal.pbio.3001667.g006 In contrast, we found that neuronal activity in wM2 changed in a very different way across learning compared to wM1. In wM2, whisker deflection evoked an increased AP firing in RS units of Expert mice compared to Novice mice (Novice: 1.0 ± 2.2 Hz, 244 units recorded in 7 mice, Expert: 1.5 ± 4.5 Hz, 401 units recorded in 10 mice; nonparametric permutation test, p = 0.016) (Fig 6C and S11), but a decreased firing of FS units (Novice: 4.5 ± 6.8 Hz, 57 units recorded in 7 mice, Expert: 2.7 ± 3.9 Hz, 107 units recorded in 10 mice; nonparametric permutation test, p = 0.021) (Figs 6D and S11). The balance of RS to FS unit activity in wM2 is therefore enhanced in favor of RS units across task learning. To test how the coordination between sensory and motor cortices changed across learning, we quantified interareal interactions between wS1->wM1 and wS2->wM2 in the subset of sessions during which we obtained simultaneous paired recordings from these areas (Fig 6E and 6F). Averaged over individual pairs of neurons, trial-by-trial correlation between evoked activity of wS2-RS units with wM2-RS units increased across learning (Novice: 876 neuron pairs recorded in 6 mice, Expert: 583 neuron pairs recorded in 3 mice; Wilcoxon rank-sum test, p = 0.039) while it decreased between wS2-RS units and wM2-FS units (Novice: 343 neuron pairs recorded in 6 mouse, Expert: 209 neuron pairs recorded in 3 mice; Wilcoxon rank-sum test, p = 2.9 × 10−4). Learning-related changes in firing rates might contribute to these apparent changes in correlations. However, while the activity of wM1-FS units increased across learning, the correlation between wS1-RS units and wM1-FS units did not change significantly, nor did the correlation between wS1-RS units and wM1-RS units. As an additional control, we measured interareal pairwise correlations using the spike time tiling coefficient (STTC) method [60], which is suggested to be insensitive to firing rate (S12B Fig). Quantified using STTC analysis, the only significant increase in correlation across learning was observed between wS2-RS and wM2-RS units (Novice: 3,482 neuron pairs recorded in 6 mice, Expert: 2,461 neuron pairs recorded in 3 mice; Wilcoxon rank-sum test, p = 4.7 × 10−11). Trial-by-trial correlation of the population response showed similar patterns of change across learning in both area pairs as those observed in pair-wise correlation changes (S12A Fig). To further evaluate functional connectivity changes, we identified the number of directional connections (putative direct monosynaptic connections) based on short-latency sharp peaks in the cross-correlograms between pairs of neurons from whisker sensory and whisker motor cortices (Figs 6F and S12C). The percentage of connections between wS2-RS units and wM2-RS units increased significantly across learning (Novice: 3 out of 1,077 pairs in 6 mice, Expert: 17 out of 1,066 pairs in 3 mice; chi-squared proportion test, p = 0.0032). All together, these data suggest that learning might increase the excitation to inhibition ratio of the sensory-evoked response in wM2, but decreases the ratio in wM1 in favor of inhibition. Increased activity of excitatory neurons in wM2 across learning could arise from the increase in functional connectivity between wS2 and wM2 and could, in turn, contribute to driving excitation in other frontal areas including ALM, which is known to be important for the motor planning of licking [20,22].

Neuronal activity in tongue- and jaw-related motor cortices Previous studies have identified motor (tjM1) and premotor (ALM) areas of neocortex associated with licking [20,61]. Whisker deflection evoked a rapid decrease in both RS (Fig 7A) and FS (Fig 7B) neuronal activity in tjM1 of Expert mice (RS Novice: 0.0 ± 1.2 Hz, 271 units recorded in 8 mice, RS Expert: −0.6 ± 1.7 Hz, 505 units recorded in 11 mice; nonparametric permutation test, p < 0.0001; FS Novice: −0.2 ± 2.1 Hz, 61 units recorded in 8 mice, FS Expert: −1.5 ± 2.6 Hz, 83 units recorded in 11 mice; nonparametric permutation test, p = 0.0003). The observed suppression of neuronal activity in tjM1 evoked by the whisker stimulus in Expert mice was present across superficial and deep layers (S13 Fig). The suppression of neuronal activity in tjM1 in Expert mice may help suppress early licking [22]. An active suppression of licking during the response window after the auditory cue is also required in correct rejection trials compared to miss trials, and we previously reported stronger suppression of RS units in correct rejection trials [22]. Here, we similarly observed a larger reduction of activity of FS neurons during the response window in correct rejection trials compared to miss trials (S14 Fig). Thus, in periods when licking should be suppressed, there appears to be a decrease in firing of both RS and FS neurons in tjM1 across learning. PPT PowerPoint slide

PNG larger image

TIFF original image Download: Fig 7. FS neuronal responses in tjM1 and ALM changed similarly to RS neurons. (A) Suppression of tjM1 RS neurons in Expert mice. Top: baseline-subtracted (50 ms before whisker onset) firing rate (mean ± SEM) overlaid for Novice (271 RS units in 8 mice) and Expert mice (505 RS units in 11 mice). Bottom: Comparison of whisker-evoked response in Novice and Expert mice. Bar plots showing population rate in 40- to 90-ms window (mean ± SEM) after whisker onset and statistical comparison using nonparametric permutation test (left, ***: p < 0.001); fraction of positively (filled bars) or negatively (empty bars) modulated neurons in the same window (right). Modulation of individual neurons compared to a similar window size prior to whisker onset, was identified using nonparametric permutation test (p < 0.005). Fraction of modulated neurons in Novice and Expert were compared using a chi-squared proportion test (ns: p > = 0.05). (B) Suppression of tjM1 FS neurons in Expert mice. Panels are similar to (A) but for tjM1 FS neurons in Novice (61 neurons in 8 mice) and Expert mice (83 neurons in 11 mice). (C) Delay activity of RS neurons in Expert mice. Top: baseline-subtracted (1 second before whisker onset) firing rate (mean ± SEM) overlaid for Novice (234 RS units in 6 mice) and Expert mice (766 RS units in 12 mice). Bottom: Comparison of whisker-evoked response in Novice and Expert mice. Bar plots showing population rate in 200- to 1,000-ms window (mean ± SEM) after whisker onset and statistical comparison using nonparametric permutation test (left, ***: p < 0.001); fraction of positively (filled bars) or negatively (empty bars) modulated neurons in the same window (right). Modulation of individual neurons compared to a similar window size prior to whisker onset was identified using nonparametric permutation test (p < 0.005). Chi-squared proportion test: ***: p < 0.001, ns: p > = 0.05. (D) Delay activity of ALM FS neurons in Expert mice. Panels are similar to (C) but for ALM FS neurons in Novice (37 FS units in 5 mice) and Expert mice (109 FS units in 12 mice). The underlying data for Fig 7 can be found in S9 Data. ALM, anterior lateral motor cortex; FS, fast spiking; RS, regular spiking; tJM1, tongue-jaw primary motor cortex. https://doi.org/10.1371/journal.pbio.3001667.g007 Delay period activity emerges in RS units of ALM after task learning and is causally involved in motor planning [22]. Analysis of FS units revealed a similar activity pattern, indicating that in ALM of Expert mice both RS and FS units increased their firing rate after whisker stimulus and remain elevated throughout the delay period (RS Novice: 0.1 ± 0.7 Hz, 234 units recorded in 6 mice, RS Expert: 1.4 ± 4.1 Hz, 766 units recorded in 12 mice; nonparametric permutation test, p = 0.0001; FS Novice: 0.2 ± 1.5 Hz, 37 units recorded in 5 mice, FS Expert: 3.7 ± 6.8 Hz, 109 units recorded in 12 mice; nonparametric permutation test, p = 0.0001). Furthermore, in Expert compared to Novice mice, a larger fraction of RS and FS units were significantly modulated during the delay, primarily with an increase in firing rate (Fig 7C and 7D). The delay period activity was more prominent in deeper layers of ALM for both RS and FS neurons (S15 Fig). Preparatory movements were prominent during delay periods in Expert mice and accounted for a large part of the neuronal activity during the delay period [22]. Nonetheless, investigating the subset of quiet trials without delay period movements, we found that significant neuronal delay period activity still remains in both RS and FS units (S16 Fig). Therefore, both RS and FS units in ALM develop persistent delay period activity across learning, which likely contributes to the storage of a licking motor plan.

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