Phase transitions in the spinless Falicov-Kimball model with correlated hopping

The canonical Monte-Carlo is used to study the phase transitions from the low-temperature ordered phase to the high-temperature disordered phase in the two-dimensional Falicov-Kimball model with correlated hopping. As the low-temperature ordered phase we consider the chessboard phase, the axial striped phase and the segregated phase. It is shown that all three phases persist also at finite temperatures (up to the critical temperature $\tau_c$) and that the phase transition at the critical point is of the first order for the chessboard and axial striped phase and of the second order for the segregated phase. In addition, it is found that the critical temperature is reduced with the increasing amplitude of correlated hopping $t'$ in the chessboard phase and it is strongly enhanced by $t'$ in the axial striped and segregated phase.Comment: 17 pages, 6 figure

Neural responses to natural sounds in the auditory midbrain: A model comparison

Abstract-The inferior colliculus (IC) is the main converging station in the auditory midbrain and important for processing of complex sounds. However, the functional mapping of natural complex sounds to its neural representation is not yet very well understood, and good modeling approaches would be useful. To evaluate prediction models, we use recordings from groups of neurons in the Ie of guinea pigs which were acoustically presented a set of 11 conspecific vocalizations. The different vocalizations display various envelope types and spectral contents. Using cross-correlation, we compare the predicted and recorded temporal neural responses for two approaches. The first model is a modification of the biophysically detailed Meddis model, and the second one is a filtering approach around the neuron's preferred frequency. Surprisingly, we find that for responses to natural sounds from groups of neurons, the filtering approach yields better predictions than the biophysically detailed model. Thus, the collective, integrated response can be well described by a frequency-band selective representation

Neural and response correlations to complex natural sounds in the auditory midbrain

How natural communication sounds are spatially represented across the inferior colliculus, the main center of convergence for auditory information in the midbrain, is not known. The neural representation of the acoustic stimuli results from the interplay of locally differing input and the organization of spectral and temporal neural preferences that change gradually across the nucleus. This raises the question of how similar the neural representation of the communication sounds is across these gradients of neural preferences, and whether it also changes gradually. Analyzed neural recordings were multi-unit cluster spike trains from guinea pigs presented with a spectrotemporally rich set of eleven species-specific communication sounds. Using cross-correlation, we analyzed the response similarity of spiking activity across a broad frequency range for neurons of similar and different frequency tuning. Furthermore, we separated the contribution of the stimulus to the correlations to investigate whether similarity is only attributable to the stimulus, or, whether interactions exist between the multi-unit clusters that lead to neural correlations and whether these follow the same representation as the response correlations. We found that similarity of responses is dependent on the neurons' spatial distance for similarly and differently frequency-tuned neurons, and that similarity decreases gradually with spatial distance. Significant neural correlations exist, and contribute to the total response similarity. Our findings suggest that for multi-unit clusters in the mammalian inferior colliculus, the gradual response similarity with spatial distance to natural complex sounds is shaped by neural interactions and the gradual organization of neural preferences