… These characteristics, as well as the general current state of the art and challenges for future
research in the field of neural networks will be analysed in this paper. The text is organized …

… the nature of neural computation. Consequently, for present purposes, we define
computationalism as the thesis that neural computation (… Our argument challenges not only …

… A key challenge for neural modeling is to explain how a continuous stream of multimodal
input from a rapidly changing environment can be processed by stereotypical recurrent circuits …

… of large-scale neural recordings comes the challenge of inferring the computations they perform
… that begin to address this challenge, garnering insights from both biological and artificial …

… -first anniversary edition of Neural Computing & Applications, … of neural networks and
associated adaptive computing … is both huge and brings with it a number of challenges. …

… strengths and weaknesses of neural models. We illustrate the … that current-generation
feedforward neural networks are largely … that the fundamental challenges in neural modeling are …

… As we will see, it helps to work with visual stimuli that somehow reflect the actual challenges
the visual system faces in its natural environment. In a search for general computational …

… , a software/hardware computing platform incorporating a peripheral component interconnect
(PCI) based FPGA accelerator board to perform pipelined neural computations has been …

… “Microelectrode Arrays: Architecture, Challenges and Engineering Solutions” of … challenges
and material solutions, in developing highly efficient micro/nano electrodes as well as neural …

… arise from the coordinated dynamics of distributed, recurrently connected neural … of a neural
circuit presents considerable challenges. Here we show that some of these challenges can …