From decision to action: Detailed modelling of frog tadpoles reveals neuronal mechanisms of decision-making and reproduces unpredictable swimming movements in response to sensory signals
Fig 3
a. Visualisation of the adjacency matrix (connectome), where red are excitatory and blue are inhibitory connections. Rows and columns correspond to pre- and post-synaptic neurons, respectively. There are 12 types of neuronal populations in the CNS model and they are separated by solid grey lines. Dashed lines separate the matrix into symmetrical sub-blocks. Within each sub-block vertical and horizontal dotted lines separate the left body side (top rows and left columns) from the right body side (bottom rows and right columns). In each sub-block neurons are ordered according to increasing rostro-caudal position. The matrix describes 128,958 pair-wise connections in one CNS model (in 100 models, the mean of total connection number: 128,845.8; s. d. is 1,715.4). b-c. Examples of connection probabilities distributions (histograms) and zoomed extraction (lower panels) of excitatory (red) and inhibitory (blue) connections for tSt->tIN and MHR->dIN, respectively. (b) Probabilities pk, (k = 1,..,m) for tSt->tIN connections are in the range [0.06, 0.66]. Note: this sub-matrix has been extracted from the adjacency matrix A(i,j) and transposed: here columns and rows correspond to pre- and post-synaptic neurons, respectively. The number of connections m = 691 and the mean and standard deviation: s = 17.6 (the mean of non-zero probabilities
(s.d. is 0.08)—about half of possible connections. (c) For MHR->dIN connections the probabilities are in the range [0.001, 0.21]. The number of connections m = 338, the mean and standard deviation:
s = 16.9, the mean of non-zero probabilities
= 0.1 (s.d. is 0.07)–sparse connections.