PER except per-null PDF+ LNv (please refer to Figure 4C of [5]). Taken altogether with all published results, the present results indicate that anticipation behaviors may not be strictly anatom- ically localized, but rather occur likely as a result of network properties of the entire circadian circuit. Specifically, different combinations of lateral and dorsal circadian neurons are capable of organizing behavior in LD cycles. This conclusion is consistent with [62], who show robust morning and evening anticipatory behavior under different environmental conditions in per01 flies that have PER rescue only in small numbers of DN1 dorsal neurons. Further work shows the DN1 neurons as sensitive output neurons for the circadian circuit [63]. Detailed reviews on localized versus network models of circadian circuit organization can be found in [23,24]. Close examination of the slope and amplitude of morning anticipation behavior in pdf/Q128-Htt flies suggests that this behavior is not as robust as seen in genetically matched controls. This indicates that both the large and small LNv likely contribute to morning anticipation behavior. We employed several published AI methods to quantify morning and evening anticipatory locomotor behavior [5,51,55]. While the compar- ative results showed some differences in the details, we found that using both methods that we could measure morning anticipatory behavior of small LNv functionally ablated flies in standard LD conditions. Using the Relative AI method, we found several examples of control genotype flies that exhibited unexpected apparent defects in morning anticipatory behavior that was inconsistent with visual inspection of averaged locomotor actogram records that suggested intact morning anticipatory behavior. Further examination of the Relative AI reveals that the method is highly sensitive to single transient decreases in averaged locomotor behavior in successive bins prior to lights-on. Due to the formula used by the Relative AI algorithm, this circumstance observed commonly even in control flies leads to negative AI values. Furthermore, the Relative AI method does not provide a statistical comparison between control and experimental groups [5]. These difficulties are overcome by the Individual AI method described in [51]. The large and small LNv appear to functionally interact to produce the high amplitude morning startle response that occurs at the onset of light. Recently the large LNv have been shown by direct patch clamp recording to be acutely light-responsive [30,31]. Subsequent behavioral and physiological analysis reveals that the large LNv are light activated arousal neurons that promote wakeful behavior [31]. Several other recently published studies suggest that both LNv sub-groups promote wakeful behavior and that the large LNv act upstream of the small LNv [33]; see also [32]. However, we have demonstrated that the large LNv promote wakeful behavior in the absence of functional small LNv and that the small LNv play a minor role in promoting wakeful behavior [31]. Collectively, the results herein and published observations on the large LNv suggest that these cells contribute to the light-driven high amplitude morning startle response that occurs at the onset of light in addition to contributing to morning anticipation behavior. In the absence of functional small LNv and light onset, the high amplitude morning startle response, but not morning anticipatory behavior, is immediately lost in constant darkness. The loss of the small LNv-dependent morning peak is in agreement with previous studies [41]. We conclude that the small and large LNv have both similar and dissociable functions regulating circadian and arousal behavior and that the Drosophila circadian circuit operating as a network in the absence of the small LNv is capable of mediating morning anticipation behavior. LNv and Morning Anticipation Materials and Methods Transgenic Flies and Genetic Crosses Transgenic Drosophila carrying the 548 amino acids of the human Htt gene downstream of UAS (Upstream Activation Sequence) sites with either a pathogenic polyQ tract of 128 repeats (Htt-Q128) or non-pathogenic form with 0 repeats (Htt-Q0) were obtained from Troy Littleton (MIT, Cambridge, MA). These lines were crossed with LNv specific GAL4- driver line (pdfGAL4,[12]). Behavioral Assays Locomotor activity-rest rhythms were assayed by placing individual male flies in glass tubes supplied with food at one end and a sponge stopper at the other end. The movement of the flies across the tube caused breaks in an infra-red beam when these tubes were placed in an automatic Drosophila Activity Monitor (DAM 2, Trikinetics, Waltham, MA). Activity was recorded in 15 min binning intervals. Flies were subjected to light:dark cycles of 12:12 h for their entire life, or in some cases transferred to constant darkness (DD) Light intensity was between 1000 to 2500 lux during the light phase and below 0 lux during the dark phase and in DD. All assays and rearing of flies were done at 25uC. Raw time series data were obtained from DAM System 3 Data collection software and analyzed using Clocklab software from Actimetrics (Wilmette, IL). Anticipation indices were estimated using two methods – referred to in the text as Stoleru/Relative Index [5] and Harrisingh/Individual Index [51]. To estimate the Stoleru Index, time series data for each life stage (or for all 30 days) of each genotype was averaged across individual flies. Activity counts were binned into 1-hour intervals, then the Relative index was calculated using the formula B21{(B21 – B22) * (B22 – B23)}/ B+1, where Bi corresponds to the activity counts in the ith bin before (2) or after (+) the dark-to-light phase transition for morning anticipation and light-to-dark phase transition for evening anticipation. The Individual Index was calculated for individual flies under LD12:12 by averaging across either 1–30 days and also for each life stage and then determining the proportion of activity counts during the 3 hours preceding the phase transition over the activity during 6 hours preceding phase transition. Statistical analysis was done using Mann-Whitney U test. For the LD to DD transition assay described in Fig. 6, the Morning and evening indices were estimated using the average across all flies of each genotype per day since day-wise individual fly data had too much variation. Electrophysiology Whole-cell patch clamp recordings were performed during various time points on lLNv of flies maintained under standard LD12:12 cycles as mentioned in the text as described previously [17]. Briefly, whole brains were dissected and GFP positive large LNv were identified based on their fluorescence using a BX51 WI microscope (Olympus, Lehigh Valley, PA). 2–3 G V seals were made in cell-attached configuration following which negative pressure was applied to break into whole cell configuration. Recordings reflect a single recording per brain. Current clamp recordings were made using an Axopatch 200B amplifier (Molecular Devices, Palo Alto, CA), digitized using Digidata 1322A acquisition system (Molecular Devices). Pulse protocols were controlled by pClamp 8.2 Clampex software (Molecular Devices). Data analysis was performed by pClamp 8.2 Clampex software (Molecular Devices). Traces were low-pass filtered by the 3-point Boxcar method and electrical interference filtered at 60 Hz. P/N method was used for leak subtraction. PLoS ONE | www.plosone.org 11 July 2010 | Volume 5 | Issue 7 | e11628