We also revealed the spectrotemporal patterns of excitatory and inhibitory synaptic tonal receptive fields (TRFs) in DS neurons, because they might be the major determinants underlying the responses to FM sweeps (Andoni et al., 2007, Atencio et al., 2007,

deCharms et al., 1998, Felsheim and Ostwald, 1996, Schnupp et al., 2001 and Ye et al., 2010). Our data indicate that the topography of direction selectivity observed in the primary auditory cortex can be traced as early as to the IC. For neurons in the IC, direction selectivity is constructed by the temporal interplay between excitatory and inhibitory synaptic inputs that are not direction selective, instead of the coincidental excitatory inputs in response Selumetinib mw to the preferred direction or coincident inhibitory inputs evoked by the null direction. Such temporal imbalance of excitation and inhibition and DS topography

can be attributed to the find more spectral disparity of DS neurons’ synaptic receptive fields, in which much broader inhibitory input receptive fields with extended frequency domains were observed. These findings also imply that synaptic input circuitry can be the underlying substrates of neurons’ functional properties and organizational topography. To investigate the spatial distribution and the response properties of neurons in the subcortical auditory nuclei, we carried out multiunit extracellular recordings to determine where the salient responses to pure tone pips and the direction of FM sweeps could be located. Pure tone pips with various frequency-intensity combinations were used to map the frequency-intensity tonal receptive field for spike responses (spike TRF) at each recording site. The characteristic frequency (CF) was then determined

as the frequency to which the neurons were most sensitive. Spike responses to FM sweeps at various speeds were examined at different intensities. A direction selectivity index (DSI) was calculated for the responses to the pairs of opposing directional sweeps with the same speed and intensity. A DSI with a positive value indicates upward direction selectivity, whereas a DSI with a negative value indicates downward direction selectivity (see Experimental Procedures). We focused on the core afferent pathway connecting the auditory nerve and the primary auditory else cortex, so only the recording sites in the CN, the central nucleus of the inferior colliculus (CNIC), and the ventral nucleus of medial geniculate body (MGBv) were considered in this study (Winer and Schreiner, 2005). In total, 91 sampling sites from the CN (46 from the dorsal cochlear nucleus, DCN; 23 from posteroventral cochlear nucleus, PVCN; and 22 from the anteroventral cochlear nucleus, AVCN), 115 sampling sites from the CNIC, and 82 sampling sites from the MGBv were included (Figure 1A; also see Experimental Procedures).

In this study, we used in vivo whole-cell

voltage-clamp recordings to show that intracortical excitatory inputs play an important role in shaping odor-evoked synaptic excitation in the piriform cortex. We took advantage of the distinct properties of synaptic circuits in the olfactory cortex and selectively silenced intracortical synapses via GABAB receptor activation. We found that strongly driven odor-evoked excitatory synaptic responses largely selleck products reflect the contribution of intracortical ASSN inputs. Furthermore, the relative contribution of direct sensory LOT input and intracortical input to odor-evoked excitation varies with the tuning properties of individual pyramidal cells. Specifically, broadly tuned cells receive stronger intracortical excitation, whereas cells that respond selectively to odors receive mainly afferent sensory input. LOT afferent fibers target the distal portion of pyramidal cell apical dendrites in layer 1a, whereas associational synapses contact more proximal apical dendrites in layer 1b, as well as basal dendrites of pyramidal cells in layers 2/3 (Neville and Haberly, 2004). How valid are our somatic recordings of EPSC charge Quisinostat solubility dmso for determining the relative impact of LOT and ASSN inputs to pyramidal cell excitability? LOT-mediated EPSCs might be more heavily attenuated than proximal ASSN

EPSCs at our somatic recording location due to dendritic filtering. However, the dendrites of piriform cortex pyramidal cells are relatively electrotonically compact, with only a 50% maximal Resminostat somatic

current loss for synaptic inputs arriving at the most distal dendritic regions (Bathellier et al., 2009). In addition, piriform pyramidal cell dendrites are only weakly active, and spike output has been shown to reflect the nearly linear summation of synaptic inputs at the soma of these cells (Bathellier et al., 2009). Together, these findings suggest that our somatic charge measurements are a good indicator of the excitation that triggers spike output of piriform pyramidal cells. Recent studies have shown how the convergence and integration of M/T cell inputs from different glomeruli onto piriform cortical neurons can shape odor representations in the piriform cortex (Apicella et al., 2010, Davison and Ehlers, 2011 and Miyamichi et al., 2011). However, in addition to olfactory bulb afferent input patterns, excitatory intracortical input has also been suggested to shape response properties of piriform cortical neurons. Indeed, experiments in APC slices revealed extensive long-range recurrent connections and suggest that individual pyramidal cells receive far larger numbers of recurrent inputs than afferent inputs (Franks et al., 2011 [this issue of Neuron]).

Ces critères ont une certaine pertinence : pour certains auteurs [66] and [67], la réduction des risques est une option thérapeutique envisageable et laisser les patients choisir leurs objectifs thérapeutiques augmente les chances selleck inhibitor de succès [68]. Différentes échelles d’évaluation étaient utilisées (OCDS, DrInC, Craving Severity Scale [CSS], European Addiction Severity Index [EuropASI]), ne permettant pas les comparaisons entre les

études. Dans les marqueurs d’évaluation biologique, le recours au CDT n’était pas systématique. Certains essais utilisaient un design particulier, par exemple, un essai ouvert comparant le topiramate à la naltrexone a inclus indifféremment des patients sevrés ou non [24], un autre essai ouvert comparant le topiramate au disulfirame [25] exigeait l’implication des familles dans la prise en charge. Dans la dépendance tabagique, il n’existe qu’un essai monocentrique randomisé

contrôlé versus placebo de faible puissance [26]. Les autres résultats sont issus de l’analyse de sous-groupe au sein d’essais concernant l’alcoolodépendance [27] and [28]. Dans la dépendance à la cocaïne, un essai [29] ne retient que des sujets avec un score de sevrage (Cocaine Selective Severity Assessment) inférieur à vingt-deux et ne rapporte pas de résultats significatifs mais un rapport de cote (Odds Ratio) de consommer de la cocaïne. Un autre essai [12] retrouve une proportion d’abstinents plus importante dans le groupe topiramate et sels d’amphétamines mais la significativité de ce résultat n’est pas rapportée. screening assay Un troisième essai a retrouvé un résultat significatif sur un critère de jugement composite (consommation rapportée, test urinaire et taux de concordance estimé entre les deux) mais les résultats restent non significatifs concernant la proportion de semaines sans test urinaire positif [13]. Dans le gambling, il n’existe qu’un essai monocentrique randomisé contrôlé versus placebo de faible puissance [36]. Actuellement, la prescription du topiramate dans les troubles addictifs est une indication non reconnue dans la plupart des pays francophones,

notamment en France, en Belgique et au Canada. Le patient doit en être informé et le recueil de son consentement 3-mercaptopyruvate sulfurtransferase est nécessaire. La balance bénéfice/risque doit être évaluée, et la prescription doit pouvoir être scientifiquement justifiée. Le risque de survenue de glaucome lors de la prescription de topiramate et les complications potentiellement graves de cette pathologie ophtalmologique (cécité notamment) incitent à la prudence. Enfin, les effets indésirables du topiramate sont indépendants des substances consommées et il peut être introduit chez des patients qui ne sont pas encore abstinents, quelle que soit l’addiction. Il n’y a pas eu d’interactions décrites avec l’alcool ou les drogues consommés par les patients inclus dans les études.

,

1998; Shepherd et al., 2004; Yokoi et al., 1995). However, the direct measurement of granule cell activity in vivo has been limited to a few studies performed in anesthetized animals (Cang and Isaacson, 2003; Tan et al., 2010), hampering our understanding of the operation of olfactory bulb inhibitory interneurons in the awake state. Attempts to estimate the effect of anesthesia on granule cell activity with extracellular recording of field potentials (Nicoll, 1972; Stewart and Scott, 1976; Tsuno et al., 2008) have reached inconsistent conclusions, reflecting the difficulty of interpreting these indirect measurements. Here we report, to our knowledge, the first direct in vivo measurements of granule cell activity in awake animals. Granule cells respond to odors rapidly, and their tuning properties are similar to those of mitral cells. Strikingly, anesthesia caused a substantial attenuation Akt phosphorylation of both spontaneous and odor-evoked granule cell activity, which is in stark contrast to the enhancement of odor-evoked activity of mitral cells in the anesthetized state.

The reduction of granule cell activity in the anesthetized state is consistent with previous intracellular recordings under anesthesia, which reported a low probability of odor-evoked action potentials in granule cells (Cang and Isaacson, 2003) and indicates that granule cell recordings under anesthesia Ku-0059436 solubility dmso have underestimated their actions in the awake state. We think it is unlikely that the anesthetics

are directly changing the intrinsic excitability of granule cells, since the two chemically distinct anesthetics (ketamine and urethane) had the same effect on granule cell activity. Rather, the effect of the anesthetics is likely to reflect modulation of brain state. For example, granule cells are a major target of centrifugal input TCL originating from the olfactory cortex (de Olmos et al., 1978; Haberly and Price, 1978), which could be sensitive to the state of the animal (Murakami et al., 2005). Taken together, our results suggest that wakefulness greatly enhances the impact of inhibitory circuits on olfactory bulb odor representations. We envision that the sparsening and richer temporal dynamics of mitral cell odor representations we observed in the awake state may be a result of shaping by active inhibitory circuits. It will be interesting to determine whether wakefulness also enhances the activity of interneurons in other brain regions. We showed that repeated brief odor experience leads to a modification of mitral cell activity that accumulates across days and persists for over a month. Hence, experience-dependent plasticity in the olfactory bulb is not just a transient adaptation to continuous odor stimuli, but rather a process that integrates months of odor experience.

, 2013], though this is lower than a large meta-analysis of twin data [Nan et al., 2012]). In Figure 3, we show results under the assumption that MD has a similar genetic architecture to weight (red dotted line) or to height (black continuous line) (Yang et al., 2010b). We estimated the number of samples needed for an MD GWAS to have 80% power to detect at least one locus, for different disease prevalences. If MD has a genetic architecture similar to weight (red dotted line), then, for a disease prevalence of 10% (typical

of most surveys of MD), a sample size of more than 50,000 cases will be needed to detect at least one genome-wide significant hit. About 10,000 cases are needed if MD has a genetic architecture similar to height. Figure 3 also shows that disease prevalence has a big impact on power. For example, while power to detect a variant that EPZ-6438 in vitro explains 0.08% of the variance on liability to MD will be 4%, in a sample size of 10,000 cases and 10,000 this website controls, power in schizophrenia (prevalence 1%) is

approximately 50% for the same sample size. The effect of disease prevalence (shown on the vertical axis) is not linearly related to sample size. In order to find genes with a smaller sample size, we need to collect a sample that has a lower prevalence. That could be achieved in one of two ways. If MD is truly a quantitative phenotype, then the extremes of the distribution will represent a

Tryptophan synthase less prevalent form of disease. We could take disease that is so severe that it has a prevalence of 0.5% or lower, so that fewer than 20,000 cases would provide 80% power to detect at least one locus. The problem is finding the appropriate severity scale. Alternatively, we could identify rare subtypes of depression that are less prevalent and we hope represent a more homogenous condition than MD broadly defined. Ideally, such subtypes would have a different genetic architecture, veering more toward that of height than of weight, so that much smaller samples are needed. Do such heritable subtypes of MD exist? We address this question below. We start however with a review of the genetics literature to determine whether there might be rare but relatively large-effect loci that GWASs have been unable to detect. The data we have summarized so far are compatible with the hypothesis that the genetic basis of MD arises from the joint effect of very many loci of small effect, with odds ratios of much less than 1.2. However, it is also compatible with the existence of larger effect loci, under two alternative (but not incompatible) hypotheses; first, some of the heritability of MD is explained by rare relatively large-effect loci; second, larger effect sizes would be observed if more homogeneous heritable phenotypic groupings could be identified.

, 2004, Dhillon et al., 2006 and van de Wall et al., 2008) and possibly serotonin neurons in the raphe (Yadav et al., 2009). An important question is which, if any, of these neurons are GABAergic as determined by Cre activity in Vgat-ires-Cre mice and consequently contribute to the obesity phenotype of Vgat-ires-Cre, Leprlox/lox mice. As previously

mentioned, SF1 neurons are glutamatergic (Figure 1 and Tong et al., 2007). In support of this, no GABAergic neurons were found in the VMH (Figure 1). To determine if POMC neurons are GABAergic or glutamatergic and to confirm that AgRP neurons are GABAergic (Cowley et al., 2001 and Tong et al., 2008), we used immunodetectable hrGFP expressed from POMC-hrGFP (Parton et al., 2007) and NPY-hrGFP (van MK-8776 chemical structure den Pol et al., 2009) BAC transgenes to identify POMC and AgRP neurons and colocalized this with Cre activity (tdTomato, as described below). BIBW2992 supplier Note that NPY and AgRP are coexpressed in the arcuate nucleus (van den Pol et al., 2009). GABAergic (VGAT+) and glutamatergic (VGLUT2+) neurons were identified by immunodetectable tdTomato in Vgat-ires-Cre, lox-tdTomato mice and Vglut2-ires-Cre, lox-tdTomato mice, respectively (lox-tdTomato, Ai9;

Madisen et al., 2010). Of note, essentially no POMC neurons (<1%) were VGAT+ ( Figure 3A) and ∼10% of POMC neurons were VGLUT2+ ( Figure 3B). AgRP neurons, as expected, were GABAergic ( Figure 3C). It is important to note, however, that AgRP neurons represent only a subset of all GABAergic neurons in the arcuate ( Figure 3C). Also of note, POMC neurons, which are not GABAergic, are situated in a dense background of GABAergic neurons ( Figure 3A). Finally, serotonin neurons in the raphe PDK4 (as identified by immunohistochemistry for TpH), do not express Cre activity in Vgat-ires-Cre mice ( Figure S3). Thus, AgRP neurons, but not POMC or SF1 neurons, are GABAergic and therefore are the only previously established first-order neurons that contribute directly to the obesity seen

in Vgat-ires-Cre, Leprlox/lox mice. However, as previously discussed, the contribution of LEPRs on AgRP neurons to regulation of energy balance is small ( van de Wall et al., 2008). Thus, the majority of leptin’s antiobesity must be mediated by previously uncharacterized first-order leptin-responsive GABAergic neurons. Given the above, a key question becomes the location of leptin-responsive GABAergic neurons. To address this, we colocalized LEPR activity, as assessed by leptin-inducible STAT3 phosphorylation, with Cre activity in Vgat-ires-Cre and Vglut2-ires-Cre, lox-GFP reporter mice, with or without neuron-specific deletion of LEPRs. Note that leptin-inducible P-STAT3 is a robust means of detecting LEPR activity ( Münzberg et al., 2004). Leptin was injected (4 mg/kg body weight i.p.) into mice that were fasted overnight and 1 hr later brains were removed and assessed for P-STAT3 and GFP expression.

, 1998 and Cohen et al., 2012) and unidentified VTA neurons ( Kiyatkin and Rebec, 1998). Since VTA neurons are thought to encode properties of rewards and predictive cues, we next determined the consequences of VTA GABA activation at key time points in a cue-reward conditioning task. ChR2-eYFP was selectively expressed in VTA GABAergic neurons, and implantable optical fibers (Sparta et al., 2011) were secured unilaterally into brain tissue above the VTA (Figure S1 available online). Following recovery from surgery, mice were trained in daily cue-reward conditioning sessions consisting of 40 trials (60–120 s intertrial interval) where a 5 s tone/light

stimulus predicted the delivery of 20 μl of a 10% sucrose solution. Following ∼25 training sessions, Alisertib mice displayed consistent Neratinib nmr anticipatory licking during cue presentation as well as reward consummatory licking after the reward delivery (Figure 2A). During subsequent conditioning sessions, VTA GABA neurons were optically excited during either the 5 s cue presentation period or the first 5 s following reward delivery. Activation of VTA GABA neurons during the 5 s cue period did not alter either anticipatory

or reward consummatory licking (Figures 2B, 2D, and 2F) compared to behavioral sessions, where laser pulses were delivered through the fiber optic cable but light was not permitted to enter the brain. Interestingly, VTA GABA activation during the 5 s period following reward Megestrol Acetate delivery significantly decreased reward consummatory licking, which then rebounded in the 5 s after termination of VTA GABA activation (Figures 2C, 2E, and 2G). The ability of VTA GABA activation to

disrupt reward consumption became even more pronounced when these neurons were optogenetically stimulated for 10 s (Figure S2). Furthermore, 5 s GABA activation during the cue presentation did not alter the total number of licks over the entire behavioral session (Figure 2F), whereas activation following reward delivery significantly decreased the total number of licks (Figure 2G). In addition, when the 5 s optogenetic stimulation of VTA GABA neurons was applied every 30 s in an open field arena, we observed a reduction in movement velocity time locked to optical activation but no change in rotational locomotor behavior (Figure S2). Taken together, these data demonstrate that activation of VTA GABA neurons following sucrose delivery disrupts reward consumption. Next, we examined whether activation of VTA GABA neurons, or their projections to the NAc, could alter reward consumption in a task where mice were allowed free access to sucrose. ChR2-eYFP and optical fibers (Figure S1) were targeted to VTA GABA neurons as described above.

The difference among the Or47b, the Or46a, and the Or22a neurons in rich and Rab6 mutants may reflect this difference. Here, we report the identification of mutations in rich, a gene that is evolutionarily

conserved from worms to human. rich is required for synaptic specificity in Drosophila eyes and olfactory receptor neurons and acts together with Rab6. Our data define a role for Rich and Rab6 in regulating axon targeting in the eye by regulating CadN trafficking in a subset of neurons to control target specificity. Rab6 has been implicated in multiple membrane trafficking pathway and numerous “downstream” effectors have been identified (Valente et al., 2010). However, the “upstream” regulators have not yet been identified in higher eukaryotes. The Ric1p forms Selleck PLX4032 a complex with Rgp1p in yeast and promotes GTP exchange for the yeast Rab6 homolog Ypt6 (Siniossoglou et al., 2000). Surprisingly, although Rab6 family proteins Cell Cycle inhibitor are highly conserved (similarity between

Rab6 and Ypt6 is 84%), the Ric1p and Rgp1p only exhibit limited similarity with the fly and vertebrate homologs (Figure 3B). In addition, fly Rich contains several WD40 domains not found in the yeast protein, yet both the RIC1 and WD40 domains bind to Rab6. Importantly, rich and Rab6 show obvious genetic interactions and similarities in phenotypes in flies. However, we were not able to detect GTP exchange activity of Rich, nor were we able to find an interaction between Rich and the Drosophila Rgp1p like protein. Therefore, it is likely that Rich is using other interactors to regulate Rab6 activity. Moreover, we found that Rich/Rab6 regulates CadN trafficking in a cell type specific manner, yet both Rab6 and Rich are broadly expressed in brains. Hence, the other Rich interactors might be key to modulate Rab6 activity differentially in various cell types. In the medulla, several Ketanserin cell surface proteins have been identified that regulate R7 or R8 targeting in a cell-type-specific manner. For example, CadN (Lee et al., 2001), as well as DLAR (Clandinin et al., 2001) and PTP69D

(Newsome et al., 2000), mainly regulate R7 but not R8 synaptic specificity. On the other hand, Jeb (Bazigou et al., 2007), together with Flamingo (fmi) (Senti et al., 2003) and Golden goal (gogo) (Tomasi et al., 2008) direct R8 but not R7 targeting. The expression patterns of these cell surface molecules are broad, whereas their cell type specific functions are quite defined. It is therefore likely that these proteins depend on a regulated set of trafficking rules to achieve synaptic specificity. However, so far, only Sec15 has been shown to affect synaptic specificity, and in sec15 mutants, the synaptic specificity of both R7 and R8 are affected ( Mehta et al., 2005). Here, we established a role for two proteins that have not yet been implicated in trafficking of important cell surface proteins in the CNS like CadN.

Note, however, that we were able to assess the requirement for homophilic binding in da neurons from the knockin alleles by using iMARCM, as reported in the previous section, because expression from the endogenous locus does not rely on GAL4. Unfortunately, iMARCM does not facilitate expression of two chimeric

isoforms encoded at the endogenous locus in the same cell. Thus, to test for cell-autonomous rescue of self-avoidance by complementary isoforms, we used MARCM analysis in MB neurons. cDNAs that encode Dscam1 isoforms, both wild-type and chimeras, selleck chemicals were placed under the control of the upstream activating sequence (UAS) enhancer and were inserted into a defined genomic position through phiC31 site-specific recombination (Groth et al., 2004). Different isoforms were expressed at similar levels as assessed by western blots of extracts that were prepared from embryos in which UAS expression was driven by a panneuronal GAL4 transgene (data not shown). Consistent with iMARCM experiments (Figures 2 and S5), expression of two copies of any of the four chimeras

only provided weak self-avoidance activity in Dscam1null MB neurons ( Figure 3A). Expression of either pair of complementary isoforms (i.e., a single copy of each UAS transgene inserted into the same site on two homologous chromosomes), however, rescued the branch segregation defect to a similar extent to the wild-type transgenes ( Figure 3A). Mephenoxalone Thus, Dscam1 acts in a cell-autonomous fashion through direct binding of A-1210477 order complementary protein domains on sister neurites of the same cell ( Figure 3B). These data establish that binding between matching isoforms is essential for Dscam1

function in vivo. If Dscam1 isoform-specific recognition does, indeed, play an instructive role in self-recognition, then expressing two different, yet complementary, isoforms on neurites of different cells should also elicit a repulsive response between them. To test this, we expressed chimeric isoforms alone or in combination with a complementary isoform in da neurons and explored the dendritic arbor patterns elaborated by class III (v’pda) neurons relative to the dendrites of class I (vpda) neurons (Figure 4). In wild-type animals, the class I dendritic arbor pattern is established first (Soba et al., 2007). Subsequently, the class III neurons elaborate dendrites, which overlap with the dendrites of class I neurons (Hughes et al., 2007, Matthews et al., 2007 and Soba et al., 2007) (Figures 4A and 4E). Expression of a wild-type Dscam1 isoform in both cells induced repulsion and, as a result, there were few overlaps between their dendrites (Hughes et al., 2007, Matthews et al., 2007 and Soba et al., 2007) (Figures 4B and 4E). Only weak ectopic repulsion was seen in response to expression of each Dscam1 chimera (Figures 4C and 4E).

The I/V relationship now showed two distinct components: a LVA find more Ca2+ current that peaked at around −50mV, and a HVA current that peaked at around −10mV (Figure 4B, black curve). ITCa currents were half-activated at −51.0 ± 0.3mV (Figure 4E), were half-inactivated at −72.8 ± 0.4mV, and had a conductance of 20.1 ± 2.9 nS (at −54mV; n = 7; ECa = +50mV). The activation kinetics of ITCa upon stepping to −54mV were fast (time to peak: 5.7 ± 0.7 ms; n = 7;

Figure 4F). Inactivation was also fast, decaying with a single exponential (11.5 ± 1.4 ms; n = 7; at −54mV; Figure 4F). Application of the ITCa antagonist mibefradil (2μM, Figures 4C, 4D, and 4G) blocked 79% of the transient calcium current (measured on stepping to −54mV; n = 3; p ≤ 0.005; Figure 4G). These data confirm that SPN neurons have large voltage-gated calcium currents, and the voltage-dependent inactivation of ITCa (gray shaded area in Figures 4B and 4D) suggests that IPSPs would promote recovery from inactivation. So what is the more important role for the IPSP: activation of IH or deinactivation of ITCa? The combined results from our in vivo and in vitro recording INK 128 supplier demonstrate that sound activation of

IPSPs hyperpolarizes the membrane potential, activates IH, and removes ITCa inactivation. Under current-clamp recording conditions, application of an IH antagonist (ZD7288, 20 μM) slowed the membrane time constant and removed the voltage “sag” (Figures 5A and 5B, red trace). This block of IH slowed the time to half-decay from 1.03 ± 0.1 ms to 7.53 ± 1.3 ms (n = 14; p ≤ 0.001; Figure 5D). Blockade of ITCa by mibefradil or NNC 55-0396 did not further influence the timing of the offset response (Figures 5A and 5B) but it reduced the number of offset APs from 3.5 ± 1.3 (control; n = 65) to 1.0 ± 0.4 (mibefradil;

n = 6; p = 0.009) or 0.8 ± 0.3 (NNC 55-0396; n = 5; p = 0.008; Figures 5A, 5B, and 5D). However, even the blockade of both IH and ITCa did not further change the membrane time constant or time Resminostat to half-decay (Figure 5C; n = 11; p = 0.69), consistent with the idea that IH is the dominant current for driving short-latency offset firing. The subthreshold depolarization that remained after blocking IH and ITCa was TTX sensitive (Figure 5B, green trace). As a further test of our hypothesis we developed a computational model of SPN neuron firing, in which we could test the ionic basis of offset firing and separate the relative importance and contributions of IH and ITCa. The basic Hodgkin-Huxley model could match the control firing pattern, AP waveform, and activation of offset APs in response to hyperpolarizing current injection (Figure 5E).