| Neural computation (Churchland and Sejnowski, 2016) |
Transformation of sensory input to behavioral output. |
Computer-like transformation of sensory input to behavioral output. |
| Neural representation, code, or information (Baker et al., 2022; Brette, 2019; Nizami, 2019) |
Patterns of neuronal activity that correlate with, or change in response to, sensory input. |
Internal representations or encodings of information about the external world. |
| Neural networks (Bowers et al., 2022) |
Artificial neural networks (machine-learning models). |
Biological neural networks. |
| Necessity and sufficiency (Yoshihara and Yoshihara, 2018) |
The induction or suppression of behavior through stimulation or inhibition of neural substrate. |
Logical equivalence between behavior and neural substrate. |
| Functional connectivity (Reid et al., 2019) |
Correlated neural activity. |
Neural connectivity that causes function. |
| Complexity (Merker et al., 2022) |
Patterns of neural structure that are neither ordered nor disordered. |
Patterns of neural structure that are fundamentally important. |
| Motifs |
Repeating patterns of brain-network connectivity. |
Motifs of neural computation. |
| Efficiency |
Communication between pairs of brain nodes via algorithmic sequences of connections. |
Efficiency of neural communication. |
| Modularity |
Propensity of brain networks to be divided into clusters. |
Propensity of brain networks to be robust or evolvable. |
| Flexibility |
Propensity for brain nodes to dynamically switch their cluster affiliations. |
Propensity for cognitive flexibility. |
| The brain is a network, like many other natural and synthetic systems. |
The brain consists of connected elements, like many other natural and synthetic systems. |
The brain shares functional network principles with many natural and synthetic systems. |
| Brain disorders are disconnection syndromes. |
Brain disorders are correlated with brain-network abnormalities. |
Brain disorders are caused by brain-network abnormalities. |
