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Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. One of the central questions in neuroscience is how neural activity is organized across different spatial and temporal scales. As larger populations oscillate and synchronize at lower frequencies and smaller ensembles are active at higher frequencies, a cross-frequency coupling would facilitate flexible coordination of neural activity simultaneously in time and space. Although various experiments have revealed amplitude-to-amplitude and phase-to-phase coupling, the most common and most celebrated result is that the phase of the lower frequency component modulates the amplitude of the higher frequency component. Over the recent 5 years the amount of experimental works finding such phase-amplitude coupling in LFP, ECoG, EEG and MEG has been tremendous (summarized in [1]). We suggest that although the mechanism of cross-frequency-coupling (CFC) is theoretically very tempting, the current analysis methods might overestimate any physiological CFC actually evident in the signals of LFP, ECoG, EEG and MEG. In particular, we point out three conceptual problems in assessing the components and their correlations of a time series. Although we focus on phase-amplitude coupling, most of our argument is relevant for any type of coupling. 1) The first conceptual problem is related to isolating physiological frequency components of the recorded signal. The key point is to notice that there are many different mathematical representations for a time series but the physical interpretation we make out of them is dependent on the choice of the components to be analyzed. In particular, when one isolates the components by Fourier-representation based filtering, it is the width of the filtering bands what defines what we consider as our components and how their power or group phase change in time. We will discuss clear cut examples where the interpretation of the existence of CFC depends on the width of the filtering process. 2) A second problem deals with the origin of spectral correlations as detected by current cross-frequency analysis. It is known that non-stationarities are associated with spectral correlations in the Fourier space. Therefore, there are two possibilities regarding the interpretation of any observed CFC. One scenario is that basic neuronal mechanisms indeed generate an interaction across different time scales (or frequencies) resulting in processes with non-stationary features. The other and problematic possibility is that unspecific non-stationarities can also be associated with spectral correlations which in turn will be detected by cross frequency measures even if physiologically there is no causal interaction between the frequencies. 3) We discuss on the role of non-linearities as generators of cross frequency interactions. As an example we performed a phase-amplitude coupling analysis of two nonlinearly related signals: atmospheric noise and the square of it (Figure 1) observing an enhancement of phase-amplitude coupling in the second signal while no pattern is observed in the first. Finally, we discuss some minimal conditions need to be tested to solve some of the ambiguities here noted. In summary, we simply want to point out that finding a significant cross frequency pattern does not always have to imply that there indeed is physiological cross frequency interaction in the brain.
Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. To truly appreciate the myriad of events which relate synaptic function and vesicle dynamics, simulations should be done in a spatially realistic environment. This holds true in particular in order to explain the rather astonishing motor patterns presented here which we observed within in vivo recordings which underlie peristaltic contractions at a well characterized synapse, the neuromuscular junction (NMJ) of the Drosophila larva. To this end, we have employed a reductionist approach and generated three dimensional models of single presynaptic boutons at the Drosophila larval NMJ. Vesicle dynamics are described by diffusion-like partial differential equations which are solved numerically on unstructured grids using the uG platform. In our model we varied parameters such as bouton-size, vesicle output probability (Po), stimulation frequency and number of synapses, to observe how altering these parameters effected bouton function. Hence we demonstrate that the morphologic and physiologic specialization maybe a convergent evolutionary adaptation to regulate the trade off between sustained, low output, and short term, high output, synaptic signals. There seems to be a biologically meaningful explanation for the co-existence of the two different bouton types as previously observed at the NMJ (characterized especially by the relation between size and Po),the assigning of two different tasks with respect to short- and long-time behaviour could allow for an optimized interplay of different synapse types. As a side product, we demonstrate how advanced methods from numerical mathematics could help in future to resolve also other difficult experimental neurobiological issues.
Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. Parallel multiunit recordings from V1 in anesthetized cat were collected during the presentation of random sequences of drifting sinusoidal gratings at 12 fixed orientations while gamma oscillations were present. In agreement with the seminal work [1], most units were orientation selective to varying degrees and synchronization was evident in spike train crosscorrelograms computed between units with similar preferred orientations, particularly during the presentation of optimal stimuli. Interestingly, a subset of units, which we refer to as synchronization hubs, were additionally found to synchronize with units having differing preferred orientations which was consistent with a previous study [2]. Moreover, oscillatory patterning in spike train autocorrelograms was also found to be strongest in units denoted as synchronization hubs, and synchronization hubs also tended to have narrower tuning curves relative to other units. We used simplified computational models of small networks of V1 neurons to demonstrate that neurons subject to a sufficiently strong level of inhibitory input can function as synchronization hubs. Neurons were endowed either with integrate-and-fire or conductance-based dynamics and each neuron received a combination of excitatory (AMPA) synaptic inputs that were Poisson-distributed and inhibitory (GABA) inputs that were coherent at a gamma-frequency range. If the strength of rhythmic inhibition was increased for a subset of neurons in the network, and excitation was increased simultaneously to maintain a fixed firing rate, then these neurons produced stronger oscillatory patterning in their discharge probabilities. The oscillations in turn synchronized these neurons with other neurons in the network. Importantly, the strength of synchronization increased with neurons of differing orientation preferences even though no direct synaptic coupling existed between the hubs and the other neurons. Enhanced levels of inhibition account for the emergence of synchronization hubs in the following way: Inhibitory inputs exhibiting a gamma rhythm determine a time window within which a cell is likely to discharge. Increased levels of inhibition narrow down this window further simultaneously leading to (i) even stronger oscillatory patterning of the neuron's activity and (ii) enhanced synchronization with other neurons. This enables synchronization even between cells with differing orientation preferences. Additionally, the same increased levels of inhibition may be responsible for the narrow tuning curves of hub neurons. In conclusion, synchronization hubs may be the cells that interact most strongly with the network of inhibitory interneurons during gamma oscillations in primary visual cortex.
Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. Background: Oscillatory activity in high-beta and gamma bands (20-80Hz) is known to play an important role in cortical processing being linked to cognitive processes and behavior. Beta/gamma oscillations are thought to emerge in local cortical circuits via two mechanisms: the interaction between excitatory principal cells and inhibitory interneurons – the pyramidal-interneuron gamma (PING) [1], and in networks of coupled inhibitory interneurons under tonic excitation – the interneuronal gamma (ING) [2]. Experimental evidence underlines the important role of inhibitory interneurons and especially of the fast spiking (FS) interneurons [3,4]. We show in simulation that an important property of FS neurons, namely the membrane resonance (frequency preference), represents an additional mechanism – the resonance induced gamma (RING), i.e. modulation of oscillatory discharge by resonance. RING promotes frequency stability and enables oscillations in purely excitatory networks. Methods: Local circuits were modeled with small world networks of 80% excitatory and 20% inhibitory neuron populations interconnected in small-world topology by realistic conductance-based synapses. Neuron populations were leaky integrate and fire (LIF) or Izhikevich resonator (RES) neurons. We also tested networks of purely inhibitory and purely excitatory RES neurons. Networks were stimulated with miniature postsynaptic potentials (MINIs) [5] and with low frequency sinusoidal (0.5 Hz) input that mimics the effect of gratings passing trough the visual field. The activity was calibrated to match recordings from cat visual cortex (firing rate, oscillatory activity). Results: Sinusoidal input modulates network oscillation frequency. This effect is most prominent in IF excitatory and IF inhibitory (IF-IF) networks and less prominent (about 4 times) in IF-RES or RES-IF networks where frequency remains relatively stable. The most stable frequency was observed in networks of pure resonators (RES-RES, None-RES, RES-None). Interestingly, purely excitatory RES networks (RES-None) were also able to exhibit oscillations through RING. By contrast purely excitatory or inhibitory IF networks (IF-None, None-IF) were not able to express oscillations under these conditions, matching experimental parameters. Conclusions: In both PING and ING, adding membrane resonance to principal cells or inhibitory interneurons stabilizes network oscillation frequency via the RING mechanism. Notably, in networks of purely excitatory networks, where ING and PING are not defined, oscillations can emerge via the RING mechanism if membrane resonance is expressed. Thus, RING appears as a potentially important mechanism for promoting stable network oscillations.
Background: In many species males face a higher predation risk than females because males display elaborate traits that evolved under sexual selection, which may attract not only females but also predators. Females are, therefore, predicted to avoid such conspicuous males under predation risk. The present study was designed to investigate predator-induced changes of female mating preferences in Atlantic mollies (Poecilia mexicana). Males of this species show a pronounced polymorphism in body size and coloration, and females prefer large, colorful males in the absence of predators. Results: In dichotomous choice tests predator-naïve (lab-reared) females altered their initial preference for larger males in the presence of the cichlid Cichlasoma salvini, a natural predator of P. mexicana, and preferred small males instead. This effect was considerably weaker when females were confronted visually with the non-piscivorous cichlid Vieja bifasciata or the introduced non-piscivorous Nile tilapia (Oreochromis niloticus). In contrast, predator experienced (wild-caught) females did not respond to the same extent to the presence of a predator, most likely due to a learned ability to evaluate their predators' motivation to prey. Conclusions: Our study highlights that (a) predatory fish can have a profound influence on the expression of mating preferences of their prey (thus potentially affecting the strength of sexual selection), and females may alter their mate choice behavior strategically to reduce their own exposure to predators. (b) Prey species can evolve visual predator recognition mechanisms and alter their mate choice only when a natural predator is present. (c) Finally, experiential effects can play an important role, and prey species may learn to evaluate the motivational state of their predators. Keywords: Sexual selection; female choice; non-independent mate choice; predator recognition; Poecilia mexicana
The molecular conformation of the title compound, C18H18N2O3S, is stabilized by an intramolecular N—H ... O hydrogen bond. The crystal packing shows centrosymmetric dimers connected by N—H ... S hydrogen bonds. The terminal ethoxy substituents are statistically disordered [occupancy ratio 0.527 (5):0.473 (5)].
The title compound, C20H22O4S2, was synthesized by the reaction of 1,4-dibromobutene with methyl thiosalicylate. The aliphatic segment of this ligand is in an all-trans conformation. The bridging chain, –S-(CH2)4-S–, is almost planar (r.m.s. deviation for all non-H atoms: 0.056 Å) and its mean plane forms dihedral angles of 16.60 (7) and 5.80 (2)° with the aromatic rings. In the crystal, the molecules are linked by weak C—H ... O interactions into chains with graph-set notation C(14) along [0 0 1]. The crystal studied was a racemic twin, the ratio of the twin components being 0.27 (9):0.73 (9).
The title compound, C14H11NO4, crystallizes with two molecules in the asymmetric unit. The major conformational difference between these two molecules is the dihedral angle between the aromatic rings, namely 36.99 (5) and 55.04 (5)°. The nitro groups are coplanar with the phenyl rings to which they are attached, the O—N—C—C torsion angles being -1.9 (3) and 1.0 (3)° in the two molecules.
The 3,5-methoxy groups in the title compound, C16H23NO4, are almost coplanar with the aromatic ring, whereas the 4-methoxy group is bent out of this plane. The three CH3—O—C—C torsion angles are -1.51 (18), 0.73 (19) and 75.33 (15)°. The cyclohexane ring adopts a chair conformation. In the crystal, molecules are connected by intermolecular N—H ... O hydrogen bonds into chains running along the b axis.