Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Low-dimensional models of single neurons: a review
We describe several representative models. We also describe systematic and heuristic methods of deriving reduced models from models of HH type.PMID:37060453 | DOI:10.1007/s00422-023-00960-1 (Source: Biological Cybernetics)
Source: Biological Cybernetics - April 15, 2023 Category: Science Authors: Ulises Chialva Vicente Gonz ález Boscá Horacio G Rotstein Source Type: research
Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models
Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Sp...
Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research
Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models
Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Sp...
Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research
Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models
Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Sp...
Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research
Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models
Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Sp...
Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research
Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models
Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Sp...
Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research
Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models
Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Sp...
Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research
Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition
Biol Cybern. 2023 Apr 1. doi: 10.1007/s00422-023-00956-x. Online ahead of print.ABSTRACTDeep neural networks have surpassed human performance in key visual challenges such as object recognition, but require a large amount of energy, computation, and memory. In contrast, spiking neural networks (SNNs) have the potential to improve both the efficiency and biological plausibility of object recognition systems. Here we present a SNN model that uses spike-latency coding and winner-take-all inhibition (WTA-I) to efficiently represent visual stimuli using multi-scale parallel processing. Mimicking neuronal response properties in ...
Source: Biological Cybernetics - April 2, 2023 Category: Science Authors: Melani Sanchez-Garcia Tushar Chauhan Benoit R Cottereau Michael Beyeler Source Type: research
