Combining Probabilistic Population Codes

Inference by Reparameterization in Neural Population Codes

Behavioral experiments on humans and animals suggest that the brain performs probabilistic inference to interpret its environment. Here we present a new generalpurpose, biologically-plausible neural implementation of approximate inference. The neural network represents uncertainty using Probabilistic Population Codes (PPCs), which are distributed neural representations that naturally encode pro...

MODELING EARLY VISION: PROBABILISTIC COMPUTATION USING SPIKING NEURONS, POPULATION CODES, AND CUDA by DANIEL

Probabilistic Assessment of Earthquake Damage and Loss for the City of Tehran, Iran

Tehran is one of the densely populated metropolises located in earthquake-prone regions. Tehran, the population of which surpasses 8 million people, is the most populated area in Iran. There are historical evidences confirming that catastrophic earthquakes have destroyed the city in past years. In the present paper, our study covers all parts of Tehran because there is the potential of signific...

Spiking networks for Bayesian inference and choice.

Systems neuroscience traditionally conceptualizes a population of spiking neurons as merely encoding the value of a stimulus. Yet, psychophysics has revealed that people take into account stimulus uncertainty when performing sensory or motor computations and do so in a nearly Bayes-optimal way. This suggests that neural populations do not encode just a single value but an entire probability dis...

Curriculum Model of Research Ethics for Graduate Students of Humanities in Iranian Higher Education Centers

Background: Considering the importance of observing research ethics in the research process and the need for its teaching in curricula, the present study was conducted to design a research ethics curriculum model for graduate students of humanities in higher educative centers in Iran. Method: This research was conducted in terms of applied purpose and in the framework of a qualitative approach...