The background was subtracted using the fluorescence intensity outside of the Golgi area. Immunocytochemistry of surface GFP-tagged receptors was performed using an anti-GFP antibody under a nonpermeabilized condition. Glycosylation assays were performed as described previously by Standley et al. (1998). Briefly, mouse whole brain (postnatal day 16) was homogenized with 1 ml homogenizing buffer (50 mM

Tris-HCl [pH 7.6], 5 mM EDTA, and 10% sucrose) including a Protease Inhibitor Cocktail (Roche). Homogenates were first centrifuged at 1,000 × g for 10 min to yield the nuclear fraction (P1), and then the supernatant (S1) was centrifuged at 10,000 × g for 20 min to yield the mitochondrial PD173074 mw fraction (P2). After resuspending the P2 fraction with the same volume of homogenizing buffer, the lysates were subjected to enzyme digestion for more than 12 hr according to the manufacturer’s instructions. Both EndoH and

PNGaseF were purchased from New England BioLabs (Ipswich, MA, USA). We are grateful to Josef Kittler (University College London), Chitoshi Takayama (University of the Ryukyus), and Masato Hirata (Kyushu University) for kindly providing the GFP-tagged GABAAR constructs, antibodies against GABAAR subunits, and plasmids for GABARAP, respectively. We also thank Yosuke Tanaka, Ying Tong, and Yayoi Selleckchem SB203580 Kikkawa for assistance in generating the knockout mouse; Yoshimitsu Kanai, Shinsuke Niwa, and Kazuhiko Mitsumori for technical assistance; and H. Sato, H. Fukuda, N. Onouchi, T. Akamatsu, T. Aizawa, and these all other members of the Hirokawa laboratory

for assistance. This work was supported by a Grant-in-Aid for specially promoted research to N.H. from the Ministry of Education, Culture, Sports, Science and Technology of Japan, and by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Korean Ministry of Education, Science and Technology (2012-007530, to D.-H.S.). “
“Interpreting and acting upon incoming sensory information in contextually appropriate ways is crucial for the survival of an animal. Revealing how sensory representations in the brain are affected by factors such as brain state and the animal’s history is an important step toward understanding how the brain processes sensory information. Here we address this issue by exploring how the intial stages of olfactory information processing are modulated by wakefulness and experience. Odors are detected by odorant receptors on olfactory sensory neurons (OSNs), each of which expresses one of ∼1,000 odorant receptors (Buck and Axel, 1991). The axons of OSNs expressing the same receptor converge onto one to two glomeruli in the olfactory bulb (Mombaerts et al., 1996), where different odors activate distinct sets of glomeruli (Belluscio and Katz, 2001; Bozza et al., 2004; Igarashi and Mori, 2005; Johnson et al.

Inaccurate saccades within the deadline had no time out. However, monkeys had difficulty discriminating lack of reward from an inaccurate saccade and lack of reward from slow responding. Hence, the display was removed on 25%–50% of missed-deadline trials. Monkeys quickly learned that reinforcement was only available prior to this time. All patterns of results and conclusions were unchanged by these trials. Monkeys respected the response deadlines (proportion of missed deadlines: Q Accurate: 0.18, Fast: 0.16; S Accurate: 0.19, Fast: 0.13). Some sessions included only the Fast and BAY 73-4506 manufacturer Accurate conditions; for that

reason, variability should be expected to be higher in the Neutral condition. We recorded neurons in FEF, located on the anterior bank of the arcuate sulcus, using tungsten microelectrodes (2–4 MΩ, FHC) referenced to a guide tube in contact with the dura. Location was verified by evoking eye movements though low-threshold (<50 μA) microstimulation. The number of electrodes lowered on a given session ranged from one to eight. Single-unit waveforms were isolated online, sampled at 40 kHz, and resorted offline (Offline Sorter; Plexon). All surgical and experimental procedures were in accordance with the National Institutes of Health Guide for the

Care and Use of Laboratory Animals and approved by the Vanderbilt Institutional Animal Care and Use Committee. Stem Cell Compound Library cell line Neurons are categorized into three major types: visual, visuomovement, Thiamine-diphosphate kinase and movement. Though classification

operates along a continuum, many observations demonstrate that these populations are functionally distinct (Cohen et al., 2009; Ray et al., 2009; Gregoriou et al., 2012). Visual neurons increase discharge rates significantly immediately after array presentation but have no saccade-related modulation. Movement neurons increase discharge rate significantly before saccade initiation but have no visual response. Visuomovement neurons exhibit both periods of modulation. To classify neurons, we used activity from a memory-guided saccade task. To test for visual responses, we used t tests to compare the average activity in the interval 75–100 ms after target presentation to the activity in the 100 ms interval preceding target presentation. To test for presaccadic activity, we used t tests to compare the average activity in the 100 ms interval before saccade initiation to the activity in the interval 500–400 ms before saccade initiation. To determine when neurons responded differently to two SAT conditions or when the target as compared to distractors appeared in the RF, we computed ms-by-ms Wilcoxon rank-sum tests, evaluating the null hypothesis that target-in-RF activity was significantly different from distractor-in-RF activity. Target selection time (TST) was the first of ten successive time points significant at the p < 0.01 level. Population TST was computed using jackknifing.

Most visual areas also showed face selectivity under anesthesia, including prefrontal areas. The difference in stimulus size between awake and anesthetized animals did not lead to any differences between awake and anesthetized animals, most likely because faces were contrasted 17-AAG against other categories and because many of the reported areas are size invariant. The areas that showed no consistent activation under anesthesia were the amygdala and the hippocampus. Both awake animals showed bilateral activation in the amygdala, in agreement with earlier studies (Hadj-Bouziane et al., 2008 and Hoffman et al., 2007). Only one animal showed activation

in the amygdala under anesthesia. However, face-selective responses may not have reached significance in the anesthetized monkeys, because faces were contrasted against fruit and the amygdala also showed significant

responses to fruit in awake monkeys (p < 0.05). The amygdala has a high μ-opioid receptor density (Mansour et al., 1988) and it is also possible that binding of remifentanil may have reduced its neural responses. There are two caveats concerning the results from anesthetized monkeys. One is that the results may depend on the type of anesthesia and results may not generalize to other anesthesia regimens because different anesthetics AZD2281 mw affect cognitive processing differently. The other concerns the interpretation of the BOLD signal. It has been shown in V1 that the BOLD signal better represents the input to an area and its local processing than its output and that functional activation can occur in the absence of of spiking (Goense and Logothetis, 2008 and Logothetis et al., 2001). The conservative interpretation of preserved BOLD signal in a brain area would be that this means the activated area receives synaptic input. What types of further neural processes take place, whether

these differ between awake and anesthetized animals, and how they relate to single- or multiunit electrophysiological data (neural output) remains subject to further investigation. Conversely, a lack of BOLD signal could signify a lack of input from an earlier area. The issue of interpretation of the BOLD signal is independent of anesthesia, however, and is also relevant for awake subjects. The importance of the MTL in learning and memory function is well established. Area TE, the perirhinal (Brodmann areas 35 and 36) and parahippocampal cortices, the entorhinal cortex, and the hippocampus have all been shown to be involved in learning and memory (Osada et al., 2008 and Squire et al., 2004) with different structures mediating different (and possibly overlapping) functions, i.e., forming associations between objects, forming associations between objects and locations, or forming memories of scenes or locations. Although face selectivity is usually not explicitly tested, neural and BOLD responses to faces were shown in the human MTL in the context of memory and familiarity (Eichenbaum et al., 2007, Gonsalves et al.

, 2000; see also Voss et al., 2006). Anatomically, prediction of recovery from coma relies on the comprehensive assessment of all structures involved in arousal and awareness functions, namely, the ascending reticular activating system located in the postero-superior part of the brainstem and structures encompassing thalamus, basal forebrain, and fronto-parietal association cortices (Tshibanda et al., 2009). Lesion or inhibition of part of this system suffices to cause immediate coma (e.g., Parvizi and Damasio, 2003). Studies on traumatic coma patients

with conventional MRI showed that lesions of the pons, midbrain, and basal ganglia were predictive of poor outcome especially when they were bilateral (Tshibanda et al., 2009). In relation with the GNW model, it is noteworthy that prediction of nonrecovery after 1 year could be calculated with up to 86% sensitivity and 97% specificity when selleck inhibitor taking into account both diffusion tensor and spectroscopic measures of Dasatinib price cortical white matter integrity (Tshibanda et al., 2009). The objective neural measures of conscious processing demonstrated earlier in this review should be applicable to the difficult clinical problem of detecting consciousness in noncommunicating patients. Using fMRI, a few patients initially classified as vegetative by clinical signs showed essentially normal

activations of distributed long-distance cortical networks during speech processing and mental imagery tasks (Owen et al.,

2006 and Monti et al., 2010), and one patient proved able to voluntarily control them to provide yes/no answers to simple personal questions, clearly indicating some degree of preserved conscious processing (Monti et al., 2010). In an effort to isolate a more theoretically validated scalp signature of conscious sensory processing, Bekinschtein et al. (2009a) recorded ERPs to local versus global violations of an auditory regularity. When hearing a deviant tone after a sequence of repeated standard tones (sequence XXXXY), a local mismatch response was elicited nonconsciously even in coma and vegetative-state patients, as previously demonstrated (e.g., Fischer et al., 2004). However, when Isotretinoin this sequence XXXXY was repeatedly presented, such that the final tone change could be expected, the presentation of a deviant monotonic sequence (XXXXX) engendered a P3b wave in normal subjects that was absent in coma patients and in most vegetative-state patients but could still be observed in minimally conscious and locked-in patients. This paradigm, founded upon previous identification of the P3b component as a signature of conscious processing, is now undergoing validation as a means of identifying residual conscious processing in patients (Faugeras et al., 2011). The present review was deliberately limited to conscious access. Several authors argue, however, for additional, higher-order concepts of consciousness.

While the double mutation of R3 and D112 to serine (D112S-R3S) produced the largest disruption that we observed of ion selectivity, the charge swap (D112R-R3D) retained proton selectivity. Together, VX-770 price these observations suggest that D112 and R3 interact electrostatically to contribute to the selectivity filter of the channel, and that mutation of R3 alone or in combination with D112S

induces a voltage sensor that leaks cations other than protons (Figure 8B). The number of mutations required to create a pore in a VSD provides information on the length and shape of the pore’s most constricted site. The “omega pore” through the VSD of the Shaker K+ channel requires a single mutation of the first arginine R1 to a small side chain (Tombola et al., 2005), leading to its opening when S4 is in the “down state” at hyperpolarized potentials. However, it appears that Shaker actually requires a double gap (substitution of two arginines) and that the outermost position (three residues before Shaker’s R1) is naturally “missing” (i.e., is an alanine), while an omega pore can also be made in Shaker at other voltages by mutations at neighboring Androgen Receptor Antagonist pairs of arginines (Gamal El-Din et al., 2010). A double gap is also needed to create an omega pore through the

VSD in domain II of Nav1.2a, (Sokolov et al., 2005). However, in domain II of Nav1.4 channels, mutation of a single arginine (R2 or R3) is sufficient to make an omega current (Struyk et al., 2008, Sokolov et al., 2008 and Sokolov et al., 2010). We find that a single gap is sufficient for hHv1 to conduct Gu+, indicating that the pore of hHv1 is relatively short. As we observe here with hHv1, the Shaker omega pore is more permeable to Gu+ than to metal cations (Tombola et al., 2005). Moreover, Gu+ and protons have been found to be highly permeable through the VSD of domain II of Nav1.4 Na+ channel when Adenylyl cyclase a single arginine gap is made by substitution with glycine or histidine (Sokolov et al., 2010). Thus, the hHv1 VSD pore pathway shares with its counterparts from K+ and Na+ channels

a preference for the free ion that resembles the arginine side chain. A remarkable feature that appears to distinguish the omega pore of hHv1 from that of other channels is that arginine is uniquely able to select against Gu+, whereas other bulky or charged residues do not. Recent molecular dynamics simulations based on homology models built upon voltage-gated K+ channel crystal structures showed that water can occupy the core of the VSD of hHv1, but not of VSDs of tetrameric channels, suggesting that hHv1 may have evolved a specialized watery proton transfer pathway (Ramsey et al., 2010). Our findings are compatible with such a transfer pathway and with details of the homology model on which the simulations were based on, namely the close proximity of D112 to R3 in the activated state.

In a similar fashion, we found CHIR-99021 purchase that the magnitude and duration of the suppression of LTP by methoxamine (5 μM) depends on the duration of the agonist exposure (two-way ANOVA: F(1,24) = 25.2, p < 0.0001) (Figure 6G) and it was reversed within 2 hr (CTR: 150.1% ± 4.1%, n = 4; MTX: 142.4% ± 4.2%, n = 11; p = 0.20) (Figure 6G). Altogether, these results indicate that the selective adrenergic suppression of LTP and LTD is not restricted to synapses in

visual cortical layer II/III. The neuromodulation of LTP and LTD is an attractive mechanism to subordinate the magnitude and polarity of plasticity to behavioral demands. To examine whether neuromodulation of plasticity is operational in vivo we exploited the fact that α1 adrenergic agonists bring synapses into an “LTD-only” state, whereas β agonists produce an “LTP-only” state (see Figure 2). We reasoned that systemic application of α1 or β agonists in conjunction with visual stimulation to drive activity in V1 should respectively depress or potentiate active synapses in the visual cortex. Thus, anesthetized rats were first injected with α1 or β agonists or vehicle (intraperitoneally [i.p.], 15 mg/kg) and subjected to 1 hr of strong monocular visual stimulation to drive activity in V1 (see Experimental Procedures) (Girman et al., 1999).

Then, the changes in synaptic strength were evaluated ex vivo by quantifying miniature EPSCs (mEPSCs) recorded from layer 2/3 pyramidal neurons located in the monocular segment of V1, either contralateral or ipsilateral to the stimulated eye (see Figures 7A and 7B). The effects of the pretreatment with α1 agonist methoxamine and monocular EPZ-6438 concentration stimulation are shown in Figure 7C. On average, mEPSCs recorded in the contralateral (stimulated)

V1 were smaller in amplitude than the mEPSCs recorded in the ipsilateral (nonstimulated) cortex (Contra: 9.13 ± 0.07 pA, n = 22 cells; Ipsi: 11.37 ± 0.06 pA, n = 25 cells, seven rats; p < 0.0001) (Figure 7C). The distribution of mEPSC amplitude distributions were significantly different (Wilcoxon test: p < 0.0001) in a multiplicative manner, that is, the distribution of all contralateral mEPSCs is similar to the distribution of all ipsilateral mEPSCs scaled down by a factor of 0.8032 (Wilcoxon test: p = 0.9151). These results are consistent with a scenario in which the stimulation much activated most of the synapses and that methoxamine promoted the induction of LTD in these active synapses. Changes in the opposite direction were observed after pretreatment with the β agonist isoproterenol. The mEPSCs were larger in the contralateral, stimulated, V1 (Contra = 12.49 ± 0.10 pA, n = 15 cells; Ipsi = 10.55 ± 0.09 pA, n = 16 cells, six rats; p < 0.0001) (Figure 7D), and these differences were consistently observed across individuals (paired test: p = 0.007) (Figure 7D). On the other hand, the differences in the mEPSC amplitude distributions were significant (Wilcoxon test: p = 0.

, 1999). Considering the association between cannabis use and psychiatric disorders (e.g. Degenhardt et al., 2012, Lev-Ran et al., 2013 and Zammit et al., 2002), there are

reasons to believe that cannabis use would be associated with DP. In this study, we will therefor make use of a cohort study spanning over nearly 40 years to investigate (1) if there is an association between cannabis use in adolescence and future DP and (2) if possible associations persist after adjustment for a number of potential covariates. The study cohort, comprising 49,321 Swedish men has been described in detail elsewhere (Andréasson et al., 1987). In short, our study is a register follow-up to the cohort study including all Swedish men born in 1949–1951 selleck chemicals llc who were conscripted to compulsory military service in 1969–1970 (aged 18–20 years). The cohort covers approximately 97.7% of the Swedish male population at that time. Those not participating were exempted due to severe handicaps or congenital disorders. At time for conscription all men answered two questionnaires, one focused on alcohol consumption, tobacco

and illicit drug use, and the other was based on questions on family and social click here background, school performance, psychological factors, behavior and adjustment and self-rated health. In addition to this, they went through physical and psychological tests and a physician diagnosed physical and mental disorders according to the Swedish

version of the International Classification of Disease (ICD) 8th revision (ICD-8). Those with a psychiatric disorder were also examined by a psychiatrist. The study exposure is self-reported cannabis use at time for conscription. Questions were asked whether subjects had ever used drugs (including cannabis), which drugs had ever been used, first drug used, drug most commonly used, frequency of use and questions regarding use of specific drugs from a list with alternatives. The question about frequency of use had also fixed response alternatives; never, 1–2 times, 3–10 times (those two categories were collapsed into one; 1–10 times), 11–50 times and >50 times, that were used in our analyses. The study outcome is first time of being granted DP between 20 and 59 years of age. Data on DP was collected from the National Social Insurance Agency for the years 1971 to 1989 and from Longitudinal Register of Education and Labor Market Statistics from 1990 to 2008. DP was categorized into three groups, i.e., overall (aged 20–59), early DP (aged 20–39) and late DP (aged 40–59). A majority of all disability pensions occur during the second part of working life, i.e. after the age of 40. Based on previous studies on DP, we accounted for the following covariates: Social background including childhood socioeconomic position (SEP), i.e.

Summary data are reported as mean ± SD, and all statistical tests were Student’s t test unless noted otherwise. After recordings, slices were fixed overnight in 4% paraformaldehyde solution in PBS, at 4°C. To confirm the injection site,

samples were imaged with a confocal or a tiling wide-field imaging microscope (LSM 510 or Axio Imager Z2, Zeiss). To identify the recorded cells, biocytin was reacted to Selleckchem CX-5461 streptavidin conjugated with Alexa 594 (Invitrogen) in 0.1% PBS-Tx overnight and samples were imaged with a Zeiss LSM 510 and 710 confocal microscope. The fluorescence intensity of confocal images was analyzed by image processing in ImageJ. Two to five weeks postinjection rats were anesthetized with ketamine (100 mg/kg)/xylazine (10 mg/kg). A head-fixing plate was glued on the skull a small craniotomy was performed over the right bulb, ipsilateral to the injected AON, and the dura was removed. Extracellular signals from MCs were recorded with sharp tungsten electrodes (1–10 MΩ; FHC). Breathing

signals were monitored with a piezoelectric stress sensor (Kent Scientific) that was wrapped around the learn more mouse thorax. MCs were identified based on depth, respiration related firing pattern, and by monitoring the activity levels in more superficial layers. ChR2 was activated with a blue laser (450 nm, ∼60 mW/mm2 on the brain surface). Stimuli consisted of a pair of 40 ms pulses of light delivered 50 ms apart. Light intensity for in vivo experiments was greater than that used for in vitro experiments to ensure adequate penetration of the light through tissue. In both sets of experiments, light intensity and duration was kept within limits that typically do not cause heating effects in tissue (Cardin et al., 2010; Han, 2012).

second Odors were delivered from a custom-built olfactometer containing the following odors: methyl tiglate, ethyl valerate, isopropyl tiglate, ethyl butyrate, hexanal, heptanal, and isoamyl acetate. All odors were dissolved in diethyl-phthalate to a concentration of 10%. Odors were delivered by a stream of clean air (0.6 l/m) that was passed through vials containing the diluted odors. The airflow at the nose port was constant to ensure that that the responses obtained are not caused by a sudden change in air flow near the nose. Odors were delivered for 5 s every 45 s. Signals were amplified and filtered: 300 Hz to 5 kHz (A-M systems). Both breathing and MC activity signals were acquired at 20 kHz sampling and digitized with 16 bit precision (National Instruments). Data were analyzed using MATLAB (MathWorks). Spikes were sorted manually based on their projections in the principal component space and a refractory period was used for validation. Only single unit data are presented here. For analysis of the breathing signals, we defined peak inhalation as phase zero.

For example, an important prediction of the HR-EMD model is that the time constant of the delay line shapes the temporal tuning of fly motion detection and thus the shape of the optomotor response curve (Figures 1B and 3C; Reichardt, 1961). However, we found that silencing some lamina neurons (L1, L2, and L4) specifically decreased the tendency of flies to follow very fast motion stimuli, while silencing L3 had the opposite effect,

increasing fly responses to fast motion stimuli (Figure 7C). Consistent with our behavioral and simulation results, L3 neurons in larger flies have a higher input resistance than L1 or L2 (Hardie and Weckström, 1990), which could result in attenuation of high-frequency signals in L3 (although this attenuation PS-341 clinical trial may also occur in neurons downstream of L3). The simulation results of Figures 7F and 7G strongly suggest that processing by individual cell types (and subsequent downstream pathways) contribute to the aggregate tuning of motion vision. Specifically, the temporal frequency optimum of the elaborated HR-EMD (Figure 7F) is no longer determined strictly by the time constant of the delay line but is affected by the time constants of the input pathways as well (and would be further influenced by the dynamics of feedback pathways if included in the model). This

simulation illustrates one example of a potentially general principal of the fly lamina: anatomically related www.selleckchem.com/products/torin-1.html cell types carry out similar functions but with distinct temporal properties. The two classes of reverse-optomotor phenotypes (Figure 6) suggest that L2 those and L4, C2 and C3, and Lawf1 and Lawf2 may in each case represent two “arms” of a balanced network. The duplication of function with temporal specializations that we propose need not be independent (as in our model of Figure 7F) from the recently described bifurcation into pathways specialized for the detection of luminance increments and decrements (Joesch et al., 2013). Overall the diverse range of phenotypes related to motion responses at different speeds (Figures 6 and 7) suggests that

many lamina cell types contribute to shaping the temporal tuning of early visual processing. By structuring the inputs to downstream motion circuits, lamina neurons appear to play an important role in shaping the tuning of visual behaviors, such as the optomotor response, that have previously been compactly described by the HR-EMD model. These observations provide one possible explanation for the apparent mismatch between the minimal complexity of motion detection models and the elaborate diversity of lamina and medulla neuron classes. Our data also do not support the hypothesis that specific lamina neurons serve as dedicated pathways for encoding global stimulus features, such as patterns of optic flow.

DS had to report smoking daily, an average of 5–30 cigarettes per day (CPD), while ITS just had to report smoking 4–27 days per month. The study sample is described in greater detail in Shiffman et al. (2012c). DS (n = 218) were 37.2% African American (AA), 43.6% female, and averaged 40.7 (SD = 11.3) years of age. ITS (n = 252) were 31.0% AA, 50.4% female, and averaged 36.0 (SD = 12.3)

years of age. DS reported having smoked on average 25.2 (SD = 10.9) years, averaged 15.0 (SD = 5.9) CPD, and had an average Fagerstrom Test for Nicotine LGK-974 datasheet Dependence (FTND; Heatherton et al., 1991) score of 5.1 (SD = 1.9). ITS smoked for an average of 18.0 (SD = 12.1) years, averaged 4.5 (SD = 2.9) CPD on days in which they smoked, and had a mean FTND score of 1.4 (SD = 1.6), with nearly half of ITS (44.4%) having FTND scores of 0. Among ITS, CITS (n = 152) averaged 38.2 (SD = 12.4) years of age and NITS’ (n = 80) mean age was 33.3 (SD = 11.6) years. [Classification data were missing for 20 ITS, who thus do not participate in these analyses.] CITS were 37.5% AA and 56.6% female. Among NITS, 21.3% were AA and 41.3% were female. CITS reported having smoked, on average, for 20.2 (SD = 12.1) years, an average of 5.1 (SD = 3.1) CPD on smoking days, and had an average FTND score of 1.7 (SD = 1.8). NITS reported smoking an average of 13.4 (SD = 10.7) years,

3.3 (SD = 1.8) CPD on smoking Megestrol Acetate days, and scored a mean of 0.9 (SD = 1.2) Fludarabine cost on the FTND. Only participants (n = 471) who had non-missing

scores for all 13 WISDM scores were included: 41 participants dropped from the study before completing the WISDM and 3 skipped multiple items. One additional participant who responded “7” to all WISDM items, yielding a highly implausible profile with no variation (SD = 0), and undefined standardized scale scores, was dropped. Finally, a subset of participants completed WISDM assessments for which 2 items (one contributing to the Taste-Sensory scale; one contributing to the Weight Control scale) were systematically missing. For these individuals, scores for the Taste-Sensory (n = 115) and Weight Control (n = 117) scales were imputed using highly predictive multivariate regression (R2s = .98) from other subscale items. Subjects completed the 68-item WISDM, which was scored to yield 13 subscales. Piper et al. (2004) reported high reliability for all subscales, and a consistent factor structure in daily and non-daily smokers, suggesting it is suitable for use in ITS. Subjects were interviewed about their smoking history, to determine whether they had ever smoked daily for 6 months or more (CITS) or not (NITS); see Shiffman et al. (2012c) for a more complete description. Profile scatter was indexed by the within-profile standard deviation across the 13 scales of the WISDM.