The Second Arden Shakespeare Series: A theoretical discussion and analysis

Acute light exposure exerts various effects on physiology and behaviour. Although the effects of light on brain network activity in humans are well demonstrated, the effects of light on cognitive performance are inconclusive, with the size, as well as direction, of the effect depending on the nature of the task. Similarly, in nocturnal rodents, bright light can either facilitate or disrupt performance depending on the type of task employed. Crucially, it is unclear whether the effects of light on behavioural performance are mediated via the classical image-forming rods and cones or the melanopsin-expressing photosensitive retinal ganglion cells. Here, we investigate the modulatory effects of light on memory performance in mice using the non-aversive, spontaneous recognition task. Importantly, we examine which photoreceptors are required to mediate the effects of light on memory performance. By using a cross-over design, we show that object recognition memory is disrupted when the test phase is conducted under a bright light (350 lux), regardless of the light level in the sample phase (10 or 350 lux), demonstrating that exposure to a bright light at the time of test, rather than at the time of encoding, impairs performance. Strikingly, the modulatory effect of light on memory performance is completely abolished in both melanopsin-deficient and rodless–coneless mice. Our findings provide direct evidence that melanopsin-driven and rod/cone-driven photoresponses are integrated in order to mediate the effect of light on memory performance

Behavioral response to ambiguous conditioned fear cues is decreased in adult neurogenesis-deficient mice.

<p>(A) Examples of conditioned fear training and testing protocols. (B) In a cued fear conditioning task, a perfectly predictive tone cue (Reliable) elicited similar freezing in transgenic (TK) mice (<i>n</i> = 8), which lack adult neurogenesis, and wild-type (WT) controls (<i>n</i> = 6) (*, main effect of tone versus baseline F_1,12 = 48.6, <i>p</i> < 0.0001; no other significant effects). (C) A tone that coterminated with a shock only 50% of the time (ambiguous) increased freezing in both WT (<i>n</i> = 7) and TK mice (<i>n</i> = 9; main effect of tone, F_1,14 = 55.9, <i>p</i> < 0.0001; post hoc tests show tone greater than baseline, <i>p</i> < 0.005, in both genotypes). However, the tone increased freezing more in WT mice relative to TK mice (tone x genotype interaction, F_1,14 = 5.0, <i>p</i> = 0.04; †, post hoc testing indicates <i>p</i> < 0.05 for TK versus WT freezing during the tone). (D) Freezing responses to the reliably predictive tone cue (averaged across six trials for each session) were virtually identical in WT (<i>n</i> = 7) and TK (<i>n</i> = 8) mice during all extinction days. (E) After reliable cue training with a weak shock (0.3 mA compared to 0.5 mA in earlier experiments), WT (<i>n</i> = 11) and TK (<i>n</i> = 13) mice showed increased freezing to the tone (main effect of tone F_1,22 = 13.7, <i>p</i> = .001) but equivalent freezing across genotype (main effect of genotype F_1,22 = 0.007, <i>p</i> = .93), suggesting equivalent learning with reliable cues even with a weaker shock training protocol. (F) After fear conditioning, a reliable tone cue increased the startle response similarly in mice of both genotypes (*, main effect of tone F_1,20 = 4.7, <i>p</i> = 0.04, main effect of genotype F_1,20 = 0.016, <i>p</i> = .94; <i>n</i> = 11 for both groups). (G) An ambiguous cue increased startle in WT mice (<i>n</i> = 11) but not TK mice (<i>n</i> = 10) (tone x genotype interaction F_1,19 = 4.5, <i>p</i> = 0.047; †, post hoc testing indicates <i>p</i> < 0.05 versus WT at the same time point). Data are represented as mean ± standard error of the mean (SEM). The numerical data used in all figures can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001154#pbio.2001154.s012" target="_blank">S1 Data</a>.</p

Fear conditioning effects on future behavior depend on cue reliability, adult neurogenesis, and adrenal hormones.

<p>(A) Fear conditioning and anxiodepressive behavior testing timeline. (B) Latency to eat in the novelty-suppressed feeding (NSF) test was increased by reliably cued fear conditioning in TK mice (<i>n</i> = 20), but not wild-type (WT) mice (<i>n</i> = 19), relative to unshocked mice of both genotypes (WT, TK <i>n</i> = 19, 19; training effect F_1,73 = 4.1, <i>p</i> = 0.048; genotype effect F_1,73 = 3.0, <i>p</i> = 0.086; interaction F_1,73 = 2.0, <i>p</i> = 0.165; †, post hoc testing indicates <i>p</i> < 0.05 versus unshocked condition. (C) NSF latency was increased by ambiguous cue training, relative to reliable cue training, in WT mice but not TK mice. WT mice had longer latencies than TK mice after ambiguous cue training but had shorter latencies than TK mice after reliable cue training (predictor type x genotype interaction F_1,77 = 12.3, <i>p</i> = 0.0008; †, post hoc testing indicates <i>p</i> < 0.05 versus WT in the same condition; WT <i>n</i> = 20, 21; TK <i>n</i> = 20, 20 for reliable, ambiguous). (D) When mice were adrenalectomized, latency to eat was longer in TK mice than WT mice regardless of cue type (*, genotype main effect F_1,25 = 11.5, <i>p</i> = 0.002; †, post hoc testing indicates <i>p</i> < 0.05; ††, <i>p</i> < 0.1 versus WT in the same condition; WT <i>n</i> = 7,7; TK <i>n</i> = 9, 6 for reliable, ambiguous). Data are represented as mean ± standard error of the mean (SEM). The numerical data used in all figures can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001154#pbio.2001154.s012" target="_blank">S1 Data</a>.</p

Activation of hippocampal granule and pyramidal neurons by ambiguously conditioned cues is altered in mice lacking adult neurogenesis.

<p>(A) Confocal image of the hippocampus shows neurons that were active (Fos+, red) and inactive (blue counterstain) during fear conditioning in the dentate gyrus (DG), CA3, and CA1. (B) Two hours after the third session of tone-shock pairings, TK mice (<i>n</i> = 8) had fewer Fos+ cells than wild-type (WT) mice (<i>n</i> = 7) in the ambiguous cue condition but not the reliable cue condition (WT, TK <i>n</i> = 6, 5) across all hippocampal regions (cue type x genotype interaction F_1,22 = 6.3, <i>p</i> = 0.020; †, post hoc testing indicates <i>p</i> < 0.05 versus WT in the same condition/region). (C) Confocal image of Fos immunostaining (red) in BrdU+ (green) cell in the granule cell layer (gcl) shows a 4-wk-old granule neuron active during fear conditioning. (D) Adult-born granule neurons, labeled with BrdU, in WT mice were similarly activated by reliable (r) and ambiguous (a) cue training (t₁₀ = 1.1, <i>p</i> = 0.32); TK mice had no new neurons. (E) Confocal image of the amygdala shows Fos staining in the lateral/basolateral (LA/BLA) and central (CeA) nuclei of the amygdala. (F) The number of Fos+ LA/BLA cells was lower in the ambiguous cue condition relative to the reliable cue condition but there was no effect of genotype (main effect of predictor type F_1,22 = 5.0, <i>p</i> = 0.0363; main effect of genotype F_1,22 = 0.09, <i>p</i> = .7628; WT, TK <i>n</i> = 6, 5). No significant differences were observed across cue type or genotype in the CeA (all effects F_1,22 < 1.67, <i>p</i> > 0.2). Data are represented as mean ± standard error of the mean (SEM). The numerical data used in all figures can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001154#pbio.2001154.s012" target="_blank">S1 Data</a>.</p

Electronic Supplementary Material 4: Data In Figures 1, 2, 3, S2, S3, S4, And S5 from Modulation of recognition memory performance by light requires both melanopsin and classical photoreceptors

Acute light exposure exerts various effects on physiology and behaviour. Although the effects of light on brain network activity in humans are well demonstrated, the effects of light on cognitive performance are inconclusive, with the size, as well as direction, of the effect depending on the nature of the task. Similarly, in nocturnal rodents, bright light can either facilitate or disrupt performance depending on the type of task employed. Crucially, it is unclear whether the effects of light on behavioural performance are mediated via the classical image-forming rods and cones or the melanopsin-expressing photosensitive retinal ganglion cells. Here, we investigate the modulatory effects of light on memory performance in mice using the non-aversive, spontaneous recognition task. Importantly, we examine which photoreceptors are required to mediate the effects of light on memory performance. By using a cross-over design, we show that object recognition memory is disrupted when the test phase is conducted under a bright light (350 lux), regardless of the light level in the sample phase (10 or 350 lux), demonstrating that exposure to a bright light at the time of test, rather than at the time of encoding, impairs performance. Strikingly, the modulatory effect of light on memory performance is completely abolished in both melanopsin-deficient and rodless–coneless mice. Our findings provide direct evidence that melanopsin-driven and rod/cone-driven photoresponses are integrated in order to mediate the effect of light on memory performance

Electronic Supplementary Material 1: Figures S1–S6, Supplemental Methods, And Supplemental Results And Discussion from Modulation of recognition memory performance by light requires both melanopsin and classical photoreceptors

Acute light exposure exerts various effects on physiology and behaviour. Although the effects of light on brain network activity in humans are well demonstrated, the effects of light on cognitive performance are inconclusive, with the size, as well as direction, of the effect depending on the nature of the task. Similarly, in nocturnal rodents, bright light can either facilitate or disrupt performance depending on the type of task employed. Crucially, it is unclear whether the effects of light on behavioural performance are mediated via the classical image-forming rods and cones or the melanopsin-expressing photosensitive retinal ganglion cells. Here, we investigate the modulatory effects of light on memory performance in mice using the non-aversive, spontaneous recognition task. Importantly, we examine which photoreceptors are required to mediate the effects of light on memory performance. By using a cross-over design, we show that object recognition memory is disrupted when the test phase is conducted under a bright light (350 lux), regardless of the light level in the sample phase (10 or 350 lux), demonstrating that exposure to a bright light at the time of test, rather than at the time of encoding, impairs performance. Strikingly, the modulatory effect of light on memory performance is completely abolished in both melanopsin-deficient and rodless–coneless mice. Our findings provide direct evidence that melanopsin-driven and rod/cone-driven photoresponses are integrated in order to mediate the effect of light on memory performance

Meta-analysis of adult neurogenesis literature.

<p>Forest plot showing the results of studies examining the relationship between adult neurogenesis and three tests of learning and memory (contextual and cued fear conditioning, the probe trial of the Morris water maze (MWM)), and two tests of anxiety (total activity in the open-field arena (OF) and time spent in the open-arms of an elevated plus maze (EPM)). The figure shows the standardized mean difference for each study, the associated 95% confidence intervals and the pooled estimate, all based on a random-effects (RE) model and Hedge's estimator. Multiple entries for one publication arise when authors report analyses using different ablation methods (irradiation vs genetic for example) or variation in experimental protocols. On the right of each panel is the reference number for each publication, followed by a number that identifies the data set we extracted from the literature. This number refers to an entry in the supplemental table containing details of each data set and relevant covariates <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Revest1" target="_blank">[8]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Shors1" target="_blank">[11]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Santarelli1" target="_blank">[12]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Saxe1" target="_blank">[13]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Snyder2" target="_blank">[17]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Dupret1" target="_blank">[18]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Deng1" target="_blank">[19]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Zhang1" target="_blank">[20]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Jessberger1" target="_blank">[21]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-HernandezRabaza1" target="_blank">[22]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Meshi1" target="_blank">[23]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Winocur1" target="_blank">[24]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Ko1" target="_blank">[25]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Wojtowicz1" target="_blank">[26]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Kitamura1" target="_blank">[32]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Tronel1" target="_blank">[36]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Scobie1" target="_blank">[37]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Jaholkowski1" target="_blank">[49]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Garthe1" target="_blank">[50]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Rola1" target="_blank">[51]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Zhao1" target="_blank">[52]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Shimazu1" target="_blank">[53]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Bergami1" target="_blank">[54]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Ageta1" target="_blank">[55]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Pollak1" target="_blank">[56]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-WarnerSchmidt1" target="_blank">[57]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Denny1" target="_blank">[58]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Drew1" target="_blank">[59]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-David1" target="_blank">[60]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Goodman1" target="_blank">[61]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Fuss2" target="_blank">[62]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Clark1" target="_blank">[74]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Groves1" target="_blank">[75]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Imayoshi2" target="_blank">[76]</a>, <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003718#pgen.1003718-Raber1" target="_blank">[77]</a>.</p

Ablating adult neurogenesis does not affect fear conditioning.

<p><b>A</b> Freezing behavior of GCV-treated wild type (n = 7) and GFAP-TK (n = 10) rats during 60 s preceding a tone previously paired with a shock (Pre Tone) and during the first 20 s of tone presentation (Tone). Data represent % time spent freezing during each time period (± sem). <b>B</b> Freezing behavior of GCV-treated wild type (n = 7) and GFAP-TK (n = 10) rats in a context previously associated with shock presentation. Data represent % time freezing during 4 minutes (60 s time bins; ± sem). *p<0.05 tone significantly different from pre-tone. Wild type data are represented by an open circle connected by an interrupted line, GFAP-TK data are represented by filled squares and a solid line.</p

Ablating adult neurogenesis does not affect spatial working memory in the radial maze.

<p><b>A</b> Arm configuration for radial maze task. <b>B</b> Mean number (± sem) of correct arm entries made during a maximum of 6 entries per trial, by GCV-treated wild type (n = 13) and GFAP-TK (n = 13) rats. <b>C</b> Number of arm entries made before all 6 arms had been visited in a trial, by GCV-treated wild type (n = 13) and GFAP-TK (n = 11) rats. The mean score (± sem) is shown for four sessions (4 trials per session). <b>D</b> Rats made 3 initial arm choices, followed by a 1, 20 or 60 minute delay, followed by 3 final arm choices. Data show the number of errors made during the final 3 arm choices, by GCV-treated WT (n = 13) and GFAP-TK (n = 11) rats. Each data point represents the mean score (± sem) for 3 trials for each rat. <b>E</b> Number of errors made per trial into the single arm, pair of arms and arm trio, by GCV-treated wild type (n = 13) and GFAP-TK (n = 11) rats. Data are adjusted according to the number of arms in each group (e.g. total number of arm entries into the trio was divided by 3). Each data point represents the mean score (± sem) per trial. <b>F</b> Arm configuration for the binary choice delayed non-matching to place radial maze task. <b>G</b> The percentage of trials (± sem) in which the novel arm was correctly chosen, by GCV-treated wild type (n = 11) and GFAP-TK (n = 9) rats in the delayed non-matching to place task. Wild type data are represented by an open circle connected by an interrupted line, GFAP-TK data are represented by filled squares and a solid line. The interrupted horizontal line represents chance levels of performance.</p

Thymidine kinase is expressed in the SVZ and DG, and co-localizes with GFAP positive cells.

<p>Thymidine kinase (TK) positive cells are detected in the subventricular zone (SVZ) and dentate gyrus (DG) of GFAP-TK rats, but not in wild type controls. Panels A and B show controls and panels D and E show GFAP-TK rats, Panel C shows double labeling of TK (red) and glial fibrillary acidic protein (GFAP, green) in the DG of a GFAP-TK rat. Higher magnification of a segment of panel C shows that TK positive (red) cells co-localize with GFAP staining. Scale bar represents 200 µm for panels A, B, D & E.</p