Are Myxobacteria intelligent?

“…Myxobacteria are a complex group of bacteria that share a variety of unique phenotypic features such as large genome size [ 37 , 48 , 54 , 58 ], production of secondary metabolites [ 43 , 78 – 81 ], and their developmental phenotype [ 44 , 62 , 82 – 85 ]. Considering their genomic and physiological features, we identified the distribution of PAS and MCPsignal domains amongst them in search of any putative energy taxis mechanisms.…”

“…Thus, a single neuron is not only performing summation of its inputs, but it also predicts the expected future, which we propose is a crucial component of the brain's learning mechanism. Note that a single neuron has complexity similar to single-cell organisms, which have been shown to have 'intelligent' adaptive behaviours, including predicting the consequences of their actions so as to navigate towards food and away from danger [46][47][48] . This suggests that typical neuronal models used in machine learning may be too simplistic to account for the essential computational properties of biological neurons.…”

“…Thus, a single neuron is not only performing summation of its inputs, but it also predicts the expected future, which we propose is a crucial component of the brain’s learning mechanism. Note that a single neuron has complexity similar to single cell organisms, which were shown to have ‘intelligent’ adaptive behaviors, including predicting consequences of its action in order to navigate toward food and away from danger (Tero et al, 2010; Kaiser, 2013; Boisseau et al, 2016). This suggests that typical neuronal models used in machine learning may be too simplistic to account for the essential computational properties of biological neurons.…”

“…Myxobacteria are a complex group of bacteria that share a variety of unique phenotypic features such as large genome size [ 37 , 48 , 54 , 58 ], production of secondary metabolites [ 43 , 78 – 81 ], and their developmental phenotype [ 44 , 62 , 82 – 85 ]. Considering their genomic and physiological features, we identified the distribution of PAS and MCPsignal domains amongst them in search of any putative energy taxis mechanisms.…”

“…Thus, a single neuron is not only performing summation of its inputs, but it also predicts the expected future, which we propose is a crucial component of the brain's learning mechanism. Note that a single neuron has complexity similar to single-cell organisms, which have been shown to have 'intelligent' adaptive behaviours, including predicting the consequences of their actions so as to navigate towards food and away from danger [46][47][48] . This suggests that typical neuronal models used in machine learning may be too simplistic to account for the essential computational properties of biological neurons.…”

“…Thus, a single neuron is not only performing summation of its inputs, but it also predicts the expected future, which we propose is a crucial component of the brain’s learning mechanism. Note that a single neuron has complexity similar to single cell organisms, which were shown to have ‘intelligent’ adaptive behaviors, including predicting consequences of its action in order to navigate toward food and away from danger (Tero et al, 2010; Kaiser, 2013; Boisseau et al, 2016). This suggests that typical neuronal models used in machine learning may be too simplistic to account for the essential computational properties of biological neurons.…”

“…Myxobacteria are a complex group of bacteria that share a variety of unique phenotypic features such as large genome size [ 37 , 48 , 54 , 58 ], production of secondary metabolites [ 43 , 78 – 81 ], and their developmental phenotype [ 44 , 62 , 82 – 85 ]. Considering their genomic and physiological features, we identified the distribution of PAS and MCPsignal domains amongst them in search of any putative energy taxis mechanisms.…”

“…Thus, a single neuron is not only performing summation of its inputs, but it also predicts the expected future, which we propose is a crucial component of the brain's learning mechanism. Note that a single neuron has complexity similar to single-cell organisms, which have been shown to have 'intelligent' adaptive behaviours, including predicting the consequences of their actions so as to navigate towards food and away from danger [46][47][48] . This suggests that typical neuronal models used in machine learning may be too simplistic to account for the essential computational properties of biological neurons.…”

“…Thus, a single neuron is not only performing summation of its inputs, but it also predicts the expected future, which we propose is a crucial component of the brain’s learning mechanism. Note that a single neuron has complexity similar to single cell organisms, which were shown to have ‘intelligent’ adaptive behaviors, including predicting consequences of its action in order to navigate toward food and away from danger (Tero et al, 2010; Kaiser, 2013; Boisseau et al, 2016). This suggests that typical neuronal models used in machine learning may be too simplistic to account for the essential computational properties of biological neurons.…”