You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
58 lines
2.1 KiB
58 lines
2.1 KiB
import scipy.stats |
|
import numpy as np |
|
|
|
from .population import Population |
|
from .. import cells |
|
|
|
|
|
class Bushy(Population): |
|
"""Population of bushy cells. |
|
|
|
Cells are distributed uniformly from 2kHz to 64kHz. |
|
|
|
Note that `cf` is the mean value used when selecting SGCs to connect; |
|
it is NOT the measured CF of the cell (although it should be close). |
|
""" |
|
|
|
type = "bushy" |
|
|
|
def __init__(self, species="mouse", **kwds): |
|
freqs = self._get_cf_array(species) |
|
fields = [ |
|
("cf", float), |
|
("input_sr", list), # distribution probability of SGC SR groups |
|
("sr", int), |
|
] |
|
super(Bushy, self).__init__(species, len(freqs), fields=fields, **kwds) |
|
self._cells["cf"] = freqs |
|
self._cells["input_sr"] = [np.tile([1.0, 1.0, 1.0], len(freqs))] |
|
|
|
def create_cell(self, cell_rec): |
|
""" Return a single new cell to be used in this population. The |
|
*cell_rec* argument is the row from self.cells that describes the cell |
|
to be created. |
|
""" |
|
return cells.Bushy.create(species=self.species, **self._cell_args) |
|
|
|
def connection_stats(self, pop, cell_rec): |
|
""" The population *pop* is being connected to the cell described in |
|
*cell_rec*. Return the number of presynaptic cells that should be |
|
connected and a dictionary of distributions used to select cells |
|
from *pop*. |
|
""" |
|
size, dist = Population.connection_stats(self, pop, cell_rec) |
|
|
|
from .. import populations |
|
|
|
if isinstance(pop, populations.SGC): |
|
# only select SGC inputs from a single SR group |
|
# (this relationship is hypothesized based on reconstructions of |
|
# endbulbs) |
|
sr_vals = pop.cells["sr"] |
|
u = np.random.choice(sr_vals) # assign input sr for this cell |
|
# print('u: ', u) |
|
# pick from one sr group for all inputs, with prob same as distribution in nerve |
|
dist["sr"] = (sr_vals == u).astype(float) |
|
self._cells["sr"] = u |
|
|
|
return size, dist
|
|
|