Mice learn to associate passive whisker stimulation with shock
The primary somatosensory "barrel" cortex receives tactile information from the whiskers on the facial mystacial pad. This system has been exploited in restrained animals to study cortical plasticity induced by Pavlovian fear conditioning (Das et al., 2001
; Galvez et al., 2007
; Galvez et al., 2006
; Siucinska and Kossut, 1996
), and in freely moving mice to induce associative eye blink conditioning (Galvez et al., 2009
). For our studies, we first determined whether freely exploring mice learn Pavlovian fear conditioning where whisker stimulation is used as a CS.
Passive whisker stimulation in freely behaving mice was accomplished by gluing a small metal grain to a specific whisker and placing the mouse in the bore of an electromagnet (7.7 mT) large enough to permit free exploration (Melzer et al., 1985
) (). In mice conditioned to associate whisker stimulation with shock, 30 seconds of whisker stimulation at 8 Hz immediately preceded a single 0.6 mA, 1.5 second foot-shock (paired group); this pairing was repeated 5 times, with a mean interval of 3 minutes between pairings, in a single day ( top). To control for exposure to these two sensory stimuli, a second group received the same stimuli but explicitly unpaired (unpaired control; middle). Hereafter, we refer to the foot-shock as the unconditional stimulus, or US.
Fear conditioning by passive whisker stimulation
CS-elicited freezing was examined the following day. To avoid any confounding influence of context-elicited freezing, we tested the mice in a novel context. Because cued-fear memories are context independent (Kim and Fanselow, 1992
), this strategy revealed only fear behaviors elicited by the CS and not by the context. Four conditional stimuli were presented (, bottom, "Test") and the amount of time spent motionless (freezing) during each CS was measured and averaged as a behavioral indication of fear (Fanselow and Bolles, 1979
). Paired mice (n=12) froze significantly more than explicitly unpaired control mice (n=12) during testing (, P<0.05), demonstrating a learned association between the CS and the US in which the CS triggers fear. An example movie showing freezing during testing is shown in Movie S1
. This learned association was evident even one month later, when whisker stimulation still induced a 3-fold increase in freezing relative to baseline (n=8) and a significant increase compared to explicitly unpaired controls (, n=9, P<0.05), revealing a long-term memory of the association (see also (Gale et al., 2004
We next examined if the fear response could be evoked by stimulation of either an adjacent or distant, untrained whisker. We found no generalization to a distant, untrained whisker (, compare "CS: Paired trained” with "CS: Paired remote"; paired n=7, unpaired n=7) but did find generalization to an adjacent whisker (, compare "CS: Paired trained" with "CS: Paired adjacent"; paired n=6, unpaired n=5). This is consistent with a former study in which rats were trained to use a single whisker to decide whether to cross a gap. The rats generalized the learning to an adjacent whisker but not to a remote whisker (Harris et al., 1999
We then checked another dimension of generalization - whether the behavior could be evoked by stimulating the whisker at a frequency that is different from that used during training. We found that mice that had been trained at 8 Hz also froze when tested at 33 Hz, indicating that the fear response generalizes to other stimulus frequencies (, paired n=7, unpaired n=7).
Associative fear learning enhances sparse population coding
Does the learned CS-US association affect subsequent encoding of the CS in primary sensory cortex? To examine this we used 2-photon in-vivo
imaging to measure evoked responses of networks of cortical neurons bulk loaded with the calcium-sensitive fluorescent dye OGB-1 (Garaschuk et al., 2006
; Stosiek et al., 2003
). Intrinsic-signal imaging (Grinvald et al., 1986
) was used to target dye injections to the cortical "barrel" column in primary somatosensory cortex that represented the whisker that had been stimulated during training (). Measures were made of the fraction of neurons in the network that responded to whisker stimulation, the response magnitude of each imaged neuron, and the fidelity of neural responses across stimulus trials. For each imaging field, neural responses were imaged to ten whisker stimulations spaced 10 seconds apart. The analyses of changes in fluorescence were restricted to a 2-second window immediately following the onset of whisker stimulation. A total of 816 cells were imaged in 7 fear-conditioned mice, and 833 cells in 6 explicitly unpaired control mice.
Spontaneous activity is unchanged by associative fear learning
Cortical networks are spontaneously active, and this spontaneous activity must be considered when defining evoked responses. To examine spontaneous activity we measured changes in fluorescence in a 2-second time window immediately following each of 10 sham whisker stimulations delivered with the same temporal pattern as during actual trials ( and Movie S2
). We used the resulting statistics of spontaneous activity for two purposes: 1) to examine if associative fear learning affected spontaneous activity, and 2) to define thresholds of response magnitude () and fidelity () above which a neuron was considered responsive in subsequent trials with an actual stimulus. Here, mean response magnitude refers to the average fluorescent change across all 10 sham stimuli, and fidelity refers to the number of sham trials out of 10 that were temporally coincident with a given neuron's spontaneous activity (See ‘Experimental Procedures’). Importantly, there were no significant differences in spontaneous activity between paired and explicitly unpaired groups, as measured by mean response magnitude (: paired 1.17±0.06%; unpaired 1.16±0.03% dF/F, P=0.14), mean response fidelity ( paired 1.61; unpaired 1.66, P=0.48) and network synchrony (Ch'ng and Reid, 2010
; Golshani et al., 2009
) ( 2-way ANOVA training effect F(1,320)=1.4, P=0.24). The values of spontaneous response magnitude (), and fidelity () derived from sham stimuli were then used to determine the threshold for defining with 95% confidence whether a neuron was actually responding to whisker stimulation or simply happened to be spontaneously active at the moment of whisker stimulation. For magnitude of response (dF/F), the 95% cutoff in paired mice was a 3.2% increase in fluorescence above baseline, and for explicitly unpaired mice was 2.7% above baseline (see gray shading in ). For fidelity, the 95% cutoff was 4 - that is, only 5% of cells were spontaneously active during the sham stimulus more than 4 out of 10 trials (gray shading in ). Using these thresholds, neurons could be confidently defined as responsive based on their mean response magnitude or based on the fidelity of their response.
To determine whether associative learning impacts network coding of the CS we imaged cortical responses evoked by stimulation of the trained whisker ( and Movie S3
). The fraction of responding neurons was measured in two ways because learning could change the fraction of neurons that respond to a single stimulus, or change the fraction of neurons recruited across trials, or both. This is due to the fact that trial-to-trial response variability is high in cortical networks, and thus many neurons that can encode a given stimulus often do not respond in a given trial. The pool of neurons recruited to encode a stimulus across trials is therefore significantly larger than the pool responding to a single stimulus.
Relative to explicitly unpaired controls, fear-conditioned mice exhibited significant reductions in both the fraction of neurons recruited across trials to encode the CS as well as the fraction of neurons responding to a single stimulus. When we used the average magnitude of spontaneous activity to define response threshold, we found that 38% fewer neurons responded to whisker stimulation when the CS predicted a foot shock compared to controls, ( paired 42.6±4.6%; unpaired 68.4±6%, P=0.0011). Similarly, 34% fewer neurons responded to the CS relative to unpaired controls when the threshold was based on the fidelity of spontaneous activity (, paired 34.4±4.0%; unpaired 52.07±5.3%, P=0.013). These thresholds, therefore, provide effectively the same value, and both show that, relative to controls, associative learning decreases the pool of neurons used to encode the CS across trials.
Associative fear learning increases both sparse population coding and response strength
Fear conditioning also decreased the fraction of neurons responding to a single trial by 38% relative to controls (, paired: 23±3%, unpaired: 37±4% P=0.029). These measures of fractional response to a single trial are consistent with previous reports in anesthetized mice (Kerr et al., 2007
; Sato et al., 2007
) but see (Crochet et al., 2011
) in awake. Taken together, our data show that fear conditioning enhances sparse population coding of the CS in primary somatosensory cortex.
Associative fear learning increases response strength without altering response fidelity
Associative learning did not alter response fidelity ( right, paired 7.04; unpaired 7.12, P=0.3914), but did significantly increase the strength of response to the CS. The enhanced response was seen both when response magnitude was averaged across all trials, inclusive of failures ( left paired 6.33±0.26%; unpaired 5.31±0.14%, dF/F, P<0.0001) and when failures were excluded ( right paired 10.39±0.30%; unpaired 8.95±1.80% dF/F, P<0.0001).
We next plotted response magnitude as a function of response fidelity () to examine whether there was an interaction effect between training and fidelity. Although there was no interaction (ANOVA F(5, 658) = 1.75, P = 0.12), there was a significant effect of fidelity on response magnitude for both paired and explicitly unpaired groups (ANOVA F(5, 658) = 58.02, P < 0.001), indicating that neurons with the highest response fidelity had stronger responses to each stimulus than neurons responding at lower fidelities.
To examine the effect of associative learning on total network activity we plotted the fraction of neurons in the total population as a function of their mean magnitude of fluorescent change (). This plot includes all neurons, whether responsive or not, and averages their responses across all 10 trials, inclusive of failures. This plot thus provides a view of total cortical activity in layer 2/3. We found a small, but significant decrease (8%) in mean cortical response to whisker stimulation after fear learning ( paired 3.9±0.1, unpaired 4.2±0.1% dF/F, P<0.001). This finding is in agreement with others (Castro-Alamancos, 2004
; Jasinska et al., 2010
; Kinoshita et al., 2009
; Otazu et al., 2009
; Polley et al., 1999
Taken together, results from the associative learning procedure show that fear learning reduces the fraction of neurons responding to the CS, while increasing the strength of responsive neurons. The net effect is an enhancement of sparse population coding with a moderate decrease in total activity.
Non-associative training reduces response strength and enhances response fidelity, but does not affect sparse population coding
Exposure to a non-reinforced stimulus results in non-associative plasticity in primary sensory cortices (Dinse et al., 2003
; Frenkel et al., 2006
; Gilbert, 1998
; Jasinska et al., 2010
; Megevand et al., 2009
; Melzer and Steiner, 1997
), and this has been proposed to be a substrate for perceptual learning (Frenkel et al., 2006
). We used this form of non-associative learning to examine if the effects observed after associative fear conditioning were general to learning per-se
, or were specific to associative fear learning. We measured population responses to whisker stimulation in mice exposed 4–5 days earlier to 5 CS presentations during a single trial with no US (5 mice total of 520 neurons). Hereafter, we refer to this group as ‘stimulated’. Mice not exposed to the CS were used as controls (8 mice total of 789 neurons); hereafter we refer to this group as ‘naïve’.
Measures of spontaneous activity and network synchrony were not significantly different between naive and stimulated mice (, magnitude of fluorescent change: naïve 1.15±0.03%; stimulated 1.16±0.04% dF/F, P=0.28; , sham fidelity: naive 1.56; stimulated 1.49, P=0.28; , network synchrony: 2-way ANOVA training X distance indicated no training effect F(7, 320)=0.81, P=0.58). As above, these measures were used to derive the 95% threshold to define responsive neurons across trials. These values for dF/F were 3.1% for the stimulated group and 3.3% for naive controls. The 95% threshold for measures based on fidelity was 4 responses to 10 trials for both groups.
Spontaneous activity is unchanged by non-associative learning
Mere exposure to a non-reinforced stimulus did not significantly alter the fraction of neurons responding to single-trial whisker stimulation (, naive=33±4%, stimulated=44±6%, P=0.29). Nor were significant changes seen when we analyzed the fraction of neurons recruited across all 10 trials, as described above (: naive=62± 4%, stimulated=68±6%, P=0.56; : naive=47±4%, stimulated=57±7%, P=0.26).
Effects of non-associative training on cortical network responses
Notably, response fidelity, which was unaffected by associative fear learning, was strongly enhanced in stimulated mice (, naïve 6.97, stimulated 8.28, P<0.001). Response magnitude, however, was reduced by stimulus exposure (, 2 way ANOVA main effect of stimulation, F(1,1502)=59.7, P<0.001; means in bins1–9 Naïve 9.87±0.16%, Stimulated 8.31±0.14% dF/F). As in there was a significant main effect of fidelity on response strength – in both the naive and stimulated groups, the neurons that responded with the highest fidelity (10 out of 10 trials) had the largest changes in fluorescence (, F(9,1502)=27.95, P<0.001).
To examine the effect of passive stimulation on total network activity we plotted the fraction of neurons in the total population as a function of their mean magnitude of fluorescent change (). Exposure to a non-reinforced stimulus increased total activity by 32.5% (failures included) relative to naïve controls (, naïve dF/F=4.64±0.13%, stimulated dF/F=6.15±0.24%; P<0.0001).
Taken together, our data indicate that exposure to a non-reinforced stimulus has no effect on population sparsification, but does enhance response fidelity at the expense of response strength.