Conversation
Up to standards ✅🟢 Issues
|
| Metric | Results |
|---|---|
| Complexity | 0 |
| Duplication | 0 |
TIP This summary will be updated as you push new changes. Give us feedback
ramcdougal
changed the title
|
|
✔️ e0ef758 -> artifacts URL |
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## master #3739 +/- ##
==========================================
- Coverage 68.31% 68.28% -0.04%
==========================================
Files 689 689
Lines 111034 111034
==========================================
- Hits 75855 75819 -36
- Misses 35179 35215 +36 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
|
|
✔️ e0ef758 -> Azure artifacts URL |
| . . . and the right lower corner of the CellBuilder shows us that the default function is a Boltzmann function. | ||
|
|
||
| Our model isn't smart enough for a Boltzmann function. We just want a plain, dumb, linear ramp. | ||
| Our model doesn't require a Boltzmann function. We just want a plain, simple, linear ramp. |
There was a problem hiding this comment.
In this case, suppose that our model requires that the parameter vary linearly over the chosen spatial domain.
| The synchronization mechanism requires that all of the cells fire spontaneously at similar frequencies. It is obvious that if all cells are started at the same time, they will still be roughly synchronous after one cycle (since they have similar intrinsic cycle periods). After two cycles, they will have drifted further apart. After many cycles, differences in period will be magnified, leading to no temporal relationship of firing. | ||
|
|
||
| The key observation utilized here is that firing is fairly synchronized one cycle after onset. The trick is to reset the cells after each cycle so that they start together again. They then fire with temporal differences equal to the differences in their intrinsic periods. This resetting can be provided by an inhibitory input which pushes state variable *m* down far from threshold (hyperpolarized, as it were). This could be accomplished through an external pacemaker that reset all the cells, thereby imposing an external frequency onto the network. The interesting observation in this network is that pacemaking can also be imposed from within, though an intrinsic connectivity that enslaves all members to the will of the masses. | ||
| The key observation utilized here is that firing is fairly synchronized one cycle after onset. The trick is to reset the cells after each cycle so that they start together again. They then fire with temporal differences equal to the differences in their intrinsic periods. This resetting can be provided by an inhibitory input which pushes state variable *m* down far from threshold (hyperpolarized, as it were). This could be accomplished through an external pacemaker that reset all the cells, thereby imposing an external frequency onto the network. The interesting observation in this network is that pacemaking can also be imposed from within, through an intrinsic connectivity that synchronizes all members via collective dynamics. |
There was a problem hiding this comment.
I believe that one can attain quite a bit more conceptual clarity about why inhibitory networks of neurons with limited differences in intrinsic firing rate can approximately synchronize than vaguely appealing to will of the masses or collective dynamics. It really helps to look at a plot of the M trajactories of a selection of cells that includes the slowest and fastest. Two features are critical. 1) Suppose given inhibitory event occurs at time t_e before the cell would othewise fire. And the time the cell actually will fire due to this event is t_e + t_d ( the inhibitory event increases the interval to firing). It is the case for this integrate and fire cell that t_d is larger when t_e is smaller. The closer one is to threshold, the greater is the delay effect for a given inhibitory event. The shape of M() is convex with time so subracting an amount from M() has more delay effect the closer one is to firing. 2) substantial delay between cell firing and delivery of those (inhibitory) events to target cells is essential. Basically, all cells have to fire before the fastest cell reaches threshold again. Here is a plot of M derived from neurondemo for the fastest, slowest, and medium interval cell of the 10 cell inhibitory synchronization demo
(all parameters are default except delay set to 7 (ms)).
2 participants
No description provided.