A simple Hidden Markov Model for midbrain dopaminergic neurons

Poster presentation: Introduction Dopaminergic neurons in the midbrain show a variety of firing patterns, ranging from very regular firing pacemaker cells to bursty and irregular neurons. The effects of different experimental conditions (like pharmacological treatment or genetical manipulations) on these neuronal discharge patterns may be subtle. Applying a stochastic model is a quantitative approach to reveal these changes. ..

A model for the joint evaluation of burstiness and regularity in oscillatory spike trains

Poster presentation: Introduction The ability of neurons to emit different firing patterns is considered relevant for neuronal information processing. In dopaminergic neurons, prominent patterns include highly regular pacemakers with separate spikes and stereotyped intervals, processes with repetitive bursts and partial regularity, and irregular spike trains with nonstationary properties. In order to model and quantify these processes and the variability of their patterns with respect to pharmacological and cellular properties, we aim to describe the two dimensions of burstiness and regularity in a single model framework. Methods We present a stochastic spike train model in which the degree of burstiness and the regularity of the oscillation are described independently and with two simple parameters. In this model, a background oscillation with independent and normally distributed intervals gives rise to Poissonian spike packets with a Gaussian firing intensity. The variability of inter-burst intervals and the average number of spikes in each burst indicate regularity and burstiness, respectively. These parameters can be estimated by fitting the model to the autocorrelograms. This allows to assign every spike train a position in the two-dimensional space described by regularity and burstiness and thus, to investigate the dependence of the firing patterns on different experimental conditions. Finally, burst detection in single spike trains is possible within the model because the parameter estimates determine the appropriate bandwidth that should be used for burst identification. Results and Discussion We applied the model to a sample data set obtained from dopaminergic substantia nigra and ventral tegmental area neurons recorded extracellularly in vivo and studied differences between the firing activity of dopaminergic neurons in wildtype and K-ATP channel knock-out mice. The model is able to represent a variety of discharge patterns and to describe changes induced pharmacologically. It provides a simple and objective classification scheme for the observed spike trains into pacemaker, irregular and bursty processes. In addition to the simple classification, changes in the parameters can be studied quantitatively, also including the properties related to bursting behavior. Interestingly, the proposed algorithm for burst detection may be applicable also to spike trains with nonstationary firing rates if the remaining parameters are unaffected. Thus, the proposed model and its burst detection algorithm can be useful for the description and investigation of neuronal firing patterns and their variability with cellular and experimental conditions

Finding fundamental operations in language acquisition: Formal features as triggers

The recent history of linguistic theory exhibits a sharp shift to greater abstraction. The shift to abstraction creates a new range of promising and challenging acquisition predictions. We take one goal of all linguistics to be operations permissible within Universal Grammar (UG) may ultimately be, we can expect them to be pointedly visible in the acquisition process. A prediction follows: 1) Abstract Principles predict UG-unique grammars in acquisition. What weight do the words "abstract " and "unique " carry here? "Abstract " means we should find cases where the child executes an operation which is not representable with typical PS nodes (NP,VP, DP, AGRP). "Unique " means we should find cases permitted by UG, but which do not occur in the language being learned or possibly not in any known adult grammar. This follows if the set of grammars generated by UG is substantially larger than the 3000 known human grammars, which is surely true. The child must generate a gramma

Observations of the Gallery Habits of \u3ci\u3eTrypodendron Retusum\u3c/i\u3e (Coleoptera: Scolytidae) Infesting Aspen in Central Michigan

A monogamous pair of adult Trypodendron retusum construct a gallery system consisting of an entrance tunnel and from two to five lateral tunnels into the sapwood of aspen. Inoculation of the mutualistic fungus Ambrosiella ferruginea by the female beetle, was followed by oviposition in shallow egg cradles. Two instars were observed as the larvae enlarged their cradles. The number of cradles per gallery system was correlated to the length of the gallery system. Progeny adults with a sex ratio of approximately 1:1 emerged from late June to early August to overwinter in the litter

Gallery Characteristics and Life History of the Ambrosia Beetle Trypodendron betulae (Coleoptera: Curculionidae: Scolytinae) in Birch

Trypodendron betulae Swaine distributed attack entrance holes uniformly over the surface of standing stressed sub-canopy birch trees. Male and female pairs constructed galleries consisting of an entrance tunnel about 20 mm in length and then primary and secondary lateral tunnels averaging between 16 and 23 mm in length into the sapwood. Egg niches were constructed in the lateral tunnels after the symbiotic fungus was established in the galleries. Larvae enlarged the niches into cradles. Pupae and eventually teneral adults developed in the cradles. The sex ratio of resulting progeny adults was approximately one to one, and they emerged from galleries in September to overwinter in the litter