Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Randall Britten]

Hi Hans

Our progress on this is that we have an interim format for representing
reset-rules/events, and are now prototyping the handling of this in
software.

Please see https://tracker.physiomeproject.org/show_bug.cgi?id=1543, where
we will post updates on progress.  (If you create a login for yourself on
our tracker, you can "CC" yourself to that tracker item, and get e-mails
regarding progress updates, or add comments and suggestions.)

Regards,
Randall

> -Original Message-
> From: cellml-discussion-boun...@cellml.org [mailto:cellml-discussion-
> boun...@cellml.org] On Behalf Of Dr. Hans Ekkehard Plesser
> Sent: Friday, 6 November 2009 10:15 p.m.
> To: CellML Discussion List
> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
models?
> (Alan Garny)
> 
> 
> Hi Poul,
> 
> I was just wondering how the work on CellML 1.2 is coming along,
especially
> with respect to
> events. I couldn't find anything about events on the "differences between
> 1.1 and 1.2" page
>
(http://www.cellml.org/specifications/proposed-differences-between-the-1-1-
> and-1-2-CellML-specifications).
> 
> Best regards,
> Hans
> 
> Poul Nielsen wrote:
> > Dear Hans
> >
> > Thank you for raising this. It s, in fact, one of the issues discussed
> > at the recent combined CellML SBGN-SBO BioPAX MIASE Workshop held this
> > April on Waiheke Island. There is a clear need to be able to specify
> > discontinuous processes and events, such as you have described.
> > However, both CellML and SBML use a declarative specification of
> > models, described with content MathML. Event handling fits more
> > naturally with imperative descriptions of models so there is currently
> > no clean way of describing events using content MathML. SBML, which
> > also uses content MathML as its underlying mathematical description
> > language, has addressed this problem by augmenting the language with
> > events and reset rules. After some discussion at the recent workshop,
> > the consensus was that the next iteration of CellML (1.2) would
> > include facilities for specifying events and applying reset rules in a
> > way that is consistent with SBML. There are several reasons for taking
> > this approach: it is a method that fits reasonably naturally with
> > modellers' notion of describing such models; the solution has been
> > tested by the SBML community; the construct will be straightforward to
> > handle when translating between SBML and CellML. We are currently
> > working on the CellML 1.2 specification and plan to have a draft
> > released shortly with the addition of events and reset rules to handle
> > problems such as you have described.
> >
> > Best wishes
> > Poul
> >
> > On 2009-06-05, at 00:50, Dr. Hans Ekkehard Plesser wrote:
> >
> >> Hi Alan!
> >>
> >> [Apologies for breaking the thread, I had subscribed to the list in
> >> digest form.]
> >>
> >> Thank you for your example. Unfortunately, fixed time-stepping
> >> schemes where events (threshold
> >> crossings and membrane potential resets) can occur only on a fixed
> >> time grid are one of the big
> >> no-nos in neuronal network modeling, since they can lead to strong
> >> synchronization artefacts.
> >> Indeed, quite a lot of research in recent years has focused on
> >> algorithms to determine the exact
> >> time of threshold crossings efficiencly. I'd be happy to send you
> >> reference if you are interested.
> >>
> >> Thus, if we wanted to use CellML to represent neuron models in a
> >> general form, we would need a
> >> possibility to represent instantaneous events in continuous time. I
> >> believe SBML events provide
> >> this, don't they?
> >>
> >> Best,
> >> Hans
> >>
> >>
> >>
> >>> --
> >>>
> >>> Message: 1
> >>> Date: Mon, 1 Jun 2009 12:17:54 +0100
> >>> From: "Alan Garny" 
> >>> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
> >>>   models?
> >>> To: "'CellML Discussion List'" 
> >>> Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
> >>> Content-Type: text/plain; charset="us-ascii"
> >>>
> >>> Hi Hans,
> >>>
> >>>> We are looking for a good way to describe and share neuron models,
> >>>> and
> >>>&

Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Dr. Hans Ekkehard Plesser]

Hi Poul,

I was just wondering how the work on CellML 1.2 is coming along, especially 
with respect to
events. I couldn't find anything about events on the "differences between 1.1 
and 1.2" page
(http://www.cellml.org/specifications/proposed-differences-between-the-1-1-and-1-2-CellML-specifications).

Best regards,
Hans

Poul Nielsen wrote:
> Dear Hans
> 
> Thank you for raising this. It s, in fact, one of the issues discussed  
> at the recent combined CellML SBGN-SBO BioPAX MIASE Workshop held this  
> April on Waiheke Island. There is a clear need to be able to specify  
> discontinuous processes and events, such as you have described.  
> However, both CellML and SBML use a declarative specification of  
> models, described with content MathML. Event handling fits more  
> naturally with imperative descriptions of models so there is currently  
> no clean way of describing events using content MathML. SBML, which  
> also uses content MathML as its underlying mathematical description  
> language, has addressed this problem by augmenting the language with  
> events and reset rules. After some discussion at the recent workshop,  
> the consensus was that the next iteration of CellML (1.2) would  
> include facilities for specifying events and applying reset rules in a  
> way that is consistent with SBML. There are several reasons for taking  
> this approach: it is a method that fits reasonably naturally with  
> modellers' notion of describing such models; the solution has been  
> tested by the SBML community; the construct will be straightforward to  
> handle when translating between SBML and CellML. We are currently  
> working on the CellML 1.2 specification and plan to have a draft  
> released shortly with the addition of events and reset rules to handle  
> problems such as you have described.
> 
> Best wishes
> Poul
> 
> On 2009-06-05, at 00:50, Dr. Hans Ekkehard Plesser wrote:
> 
>> Hi Alan!
>>
>> [Apologies for breaking the thread, I had subscribed to the list in  
>> digest form.]
>>
>> Thank you for your example. Unfortunately, fixed time-stepping  
>> schemes where events (threshold
>> crossings and membrane potential resets) can occur only on a fixed  
>> time grid are one of the big
>> no-nos in neuronal network modeling, since they can lead to strong  
>> synchronization artefacts.
>> Indeed, quite a lot of research in recent years has focused on  
>> algorithms to determine the exact
>> time of threshold crossings efficiencly. I'd be happy to send you  
>> reference if you are interested.
>>
>> Thus, if we wanted to use CellML to represent neuron models in a  
>> general form, we would need a
>> possibility to represent instantaneous events in continuous time. I  
>> believe SBML events provide
>> this, don't they?
>>
>> Best,
>> Hans
>>
>>
>>
>>> --
>>>
>>> Message: 1
>>> Date: Mon, 1 Jun 2009 12:17:54 +0100
>>> From: "Alan Garny" 
>>> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
>>> models?
>>> To: "'CellML Discussion List'" 
>>> Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
>>> Content-Type: text/plain; charset="us-ascii"
>>>
>>> Hi Hans,
>>>
 We are looking for a good way to describe and share neuron models,  
 and
 CellML appears a good
 candidate. The neuron models we are interested in consist mostly  
 of a
 single compartment,
 possibly of a small number of compartments.

 As far as I can see, CellML appears well suited to describe the so- 
 called
 subthreshold dynamics
 of model neurons. But I am wondering if CellML can also capture  
 (or be
 extended to capture) the
 threshold operation present in most simplified neuron models.  
 Briefly, the
 model dynamics are
 integrated according to a set of differential equations. When the  
 membrane
 potential of the
 neuron crosses a certain threshold, the neuron is said to "fire":  
 the
 membrane potential is
 reset to a certain value instantaneuously, and often clamped at  
 that value
 for a certain period
 of time afterwards (refractory period); also, an output signal is
>>> generated.
 In simple
 pseudocode, this would look like:

 while ( simulation time not up )

  process input
  update dynamics according to ODE

  if ( neuron is refractory )
V_m = V_reset
count down "refractoriness"

  if ( V_m > Threshold )
V_m = V_reset
emit output signal

  count up time
>>> I believe this could easily be done, as long as you are OK with the
>>> following:
>>> - this would require integrating the model using an integration  
>>> technique
>>> that relies on a fixed time step. In my experience, anything will  
>>> make your
>>> resetting of Vm difficult.
>>> - your output signal (Vm?) will always be generated.
>>>
>>> Attached is 

Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Dr. Hans Ekkehard Plesser]

Hi Poul!

Thanks for the information! I am looking forward to the 1.2 specifications! Do 
you have an
estimate when that would be ready for use?

Best,
Hans

Poul Nielsen wrote:
> Dear Hans
> 
> Thank you for raising this. It s, in fact, one of the issues discussed  
> at the recent combined CellML SBGN-SBO BioPAX MIASE Workshop held this  
> April on Waiheke Island. There is a clear need to be able to specify  
> discontinuous processes and events, such as you have described.  
> However, both CellML and SBML use a declarative specification of  
> models, described with content MathML. Event handling fits more  
> naturally with imperative descriptions of models so there is currently  
> no clean way of describing events using content MathML. SBML, which  
> also uses content MathML as its underlying mathematical description  
> language, has addressed this problem by augmenting the language with  
> events and reset rules. After some discussion at the recent workshop,  
> the consensus was that the next iteration of CellML (1.2) would  
> include facilities for specifying events and applying reset rules in a  
> way that is consistent with SBML. There are several reasons for taking  
> this approach: it is a method that fits reasonably naturally with  
> modellers' notion of describing such models; the solution has been  
> tested by the SBML community; the construct will be straightforward to  
> handle when translating between SBML and CellML. We are currently  
> working on the CellML 1.2 specification and plan to have a draft  
> released shortly with the addition of events and reset rules to handle  
> problems such as you have described.
> 
> Best wishes
> Poul
> 
> On 2009-06-05, at 00:50, Dr. Hans Ekkehard Plesser wrote:
> 
>> Hi Alan!
>>
>> [Apologies for breaking the thread, I had subscribed to the list in  
>> digest form.]
>>
>> Thank you for your example. Unfortunately, fixed time-stepping  
>> schemes where events (threshold
>> crossings and membrane potential resets) can occur only on a fixed  
>> time grid are one of the big
>> no-nos in neuronal network modeling, since they can lead to strong  
>> synchronization artefacts.
>> Indeed, quite a lot of research in recent years has focused on  
>> algorithms to determine the exact
>> time of threshold crossings efficiencly. I'd be happy to send you  
>> reference if you are interested.
>>
>> Thus, if we wanted to use CellML to represent neuron models in a  
>> general form, we would need a
>> possibility to represent instantaneous events in continuous time. I  
>> believe SBML events provide
>> this, don't they?
>>
>> Best,
>> Hans
>>
>>
>>
>>> --
>>>
>>> Message: 1
>>> Date: Mon, 1 Jun 2009 12:17:54 +0100
>>> From: "Alan Garny" 
>>> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
>>> models?
>>> To: "'CellML Discussion List'" 
>>> Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
>>> Content-Type: text/plain; charset="us-ascii"
>>>
>>> Hi Hans,
>>>
 We are looking for a good way to describe and share neuron models,  
 and
 CellML appears a good
 candidate. The neuron models we are interested in consist mostly  
 of a
 single compartment,
 possibly of a small number of compartments.

 As far as I can see, CellML appears well suited to describe the so- 
 called
 subthreshold dynamics
 of model neurons. But I am wondering if CellML can also capture  
 (or be
 extended to capture) the
 threshold operation present in most simplified neuron models.  
 Briefly, the
 model dynamics are
 integrated according to a set of differential equations. When the  
 membrane
 potential of the
 neuron crosses a certain threshold, the neuron is said to "fire":  
 the
 membrane potential is
 reset to a certain value instantaneuously, and often clamped at  
 that value
 for a certain period
 of time afterwards (refractory period); also, an output signal is
>>> generated.
 In simple
 pseudocode, this would look like:

 while ( simulation time not up )

  process input
  update dynamics according to ODE

  if ( neuron is refractory )
V_m = V_reset
count down "refractoriness"

  if ( V_m > Threshold )
V_m = V_reset
emit output signal

  count up time
>>> I believe this could easily be done, as long as you are OK with the
>>> following:
>>> - this would require integrating the model using an integration  
>>> technique
>>> that relies on a fixed time step. In my experience, anything will  
>>> make your
>>> resetting of Vm difficult.
>>> - your output signal (Vm?) will always be generated.
>>>
>>> Attached is a very simple CellML file (based on the van der Pol  
>>> model) that
>>> illustrates the kind of thing I think you are after. You want to  
>>> plot the x
>>> and y 

Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Peter Hunter]

Thanks Poul.
--
Sent using BlackBerry


- Original Message -
From: cellml-discussion-boun...@cellml.org 

To: CellML Discussion List 
Sent: Fri Jun 05 09:22:23 2009
Subject: Re: [cellml-discussion] Using CellML for simplified neuron models? 
(Alan Garny)

Dear Hans

Thank you for raising this. It s, in fact, one of the issues discussed
at the recent combined CellML SBGN-SBO BioPAX MIASE Workshop held this
April on Waiheke Island. There is a clear need to be able to specify
discontinuous processes and events, such as you have described.
However, both CellML and SBML use a declarative specification of
models, described with content MathML. Event handling fits more
naturally with imperative descriptions of models so there is currently
no clean way of describing events using content MathML. SBML, which
also uses content MathML as its underlying mathematical description
language, has addressed this problem by augmenting the language with
events and reset rules. After some discussion at the recent workshop,
the consensus was that the next iteration of CellML (1.2) would
include facilities for specifying events and applying reset rules in a
way that is consistent with SBML. There are several reasons for taking
this approach: it is a method that fits reasonably naturally with
modellers' notion of describing such models; the solution has been
tested by the SBML community; the construct will be straightforward to
handle when translating between SBML and CellML. We are currently
working on the CellML 1.2 specification and plan to have a draft
released shortly with the addition of events and reset rules to handle
problems such as you have described.

Best wishes
Poul

On 2009-06-05, at 00:50, Dr. Hans Ekkehard Plesser wrote:

>
> Hi Alan!
>
> [Apologies for breaking the thread, I had subscribed to the list in
> digest form.]
>
> Thank you for your example. Unfortunately, fixed time-stepping
> schemes where events (threshold
> crossings and membrane potential resets) can occur only on a fixed
> time grid are one of the big
> no-nos in neuronal network modeling, since they can lead to strong
> synchronization artefacts.
> Indeed, quite a lot of research in recent years has focused on
> algorithms to determine the exact
> time of threshold crossings efficiencly. I'd be happy to send you
> reference if you are interested.
>
> Thus, if we wanted to use CellML to represent neuron models in a
> general form, we would need a
> possibility to represent instantaneous events in continuous time. I
> believe SBML events provide
> this, don't they?
>
> Best,
> Hans
>
>
>
>> --
>>
>> Message: 1
>> Date: Mon, 1 Jun 2009 12:17:54 +0100
>> From: "Alan Garny" 
>> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
>>  models?
>> To: "'CellML Discussion List'" 
>> Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
>> Content-Type: text/plain; charset="us-ascii"
>>
>> Hi Hans,
>>
>>> We are looking for a good way to describe and share neuron models,
>>> and
>>> CellML appears a good
>>> candidate. The neuron models we are interested in consist mostly
>>> of a
>>> single compartment,
>>> possibly of a small number of compartments.
>>>
>>> As far as I can see, CellML appears well suited to describe the so-
>>> called
>>> subthreshold dynamics
>>> of model neurons. But I am wondering if CellML can also capture
>>> (or be
>>> extended to capture) the
>>> threshold operation present in most simplified neuron models.
>>> Briefly, the
>>> model dynamics are
>>> integrated according to a set of differential equations. When the
>>> membrane
>>> potential of the
>>> neuron crosses a certain threshold, the neuron is said to "fire":
>>> the
>>> membrane potential is
>>> reset to a certain value instantaneuously, and often clamped at
>>> that value
>>> for a certain period
>>> of time afterwards (refractory period); also, an output signal is
>> generated.
>>> In simple
>>> pseudocode, this would look like:
>>>
>>> while ( simulation time not up )
>>>
>>>  process input
>>>  update dynamics according to ODE
>>>
>>>  if ( neuron is refractory )
>>>V_m = V_reset
>>>count down "refractoriness"
>>>
>>>  if ( V_m > Threshold )
>>>V_m = V_reset
>>>emit output signal
>>>
>>

Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Poul Nielsen]

Dear Hans

Thank you for raising this. It s, in fact, one of the issues discussed  
at the recent combined CellML SBGN-SBO BioPAX MIASE Workshop held this  
April on Waiheke Island. There is a clear need to be able to specify  
discontinuous processes and events, such as you have described.  
However, both CellML and SBML use a declarative specification of  
models, described with content MathML. Event handling fits more  
naturally with imperative descriptions of models so there is currently  
no clean way of describing events using content MathML. SBML, which  
also uses content MathML as its underlying mathematical description  
language, has addressed this problem by augmenting the language with  
events and reset rules. After some discussion at the recent workshop,  
the consensus was that the next iteration of CellML (1.2) would  
include facilities for specifying events and applying reset rules in a  
way that is consistent with SBML. There are several reasons for taking  
this approach: it is a method that fits reasonably naturally with  
modellers' notion of describing such models; the solution has been  
tested by the SBML community; the construct will be straightforward to  
handle when translating between SBML and CellML. We are currently  
working on the CellML 1.2 specification and plan to have a draft  
released shortly with the addition of events and reset rules to handle  
problems such as you have described.


Best wishes
Poul

On 2009-06-05, at 00:50, Dr. Hans Ekkehard Plesser wrote:



Hi Alan!

[Apologies for breaking the thread, I had subscribed to the list in  
digest form.]


Thank you for your example. Unfortunately, fixed time-stepping  
schemes where events (threshold
crossings and membrane potential resets) can occur only on a fixed  
time grid are one of the big
no-nos in neuronal network modeling, since they can lead to strong  
synchronization artefacts.
Indeed, quite a lot of research in recent years has focused on  
algorithms to determine the exact
time of threshold crossings efficiencly. I'd be happy to send you  
reference if you are interested.


Thus, if we wanted to use CellML to represent neuron models in a  
general form, we would need a
possibility to represent instantaneous events in continuous time. I  
believe SBML events provide

this, don't they?

Best,
Hans




--

Message: 1
Date: Mon, 1 Jun 2009 12:17:54 +0100
From: "Alan Garny" 
Subject: Re: [cellml-discussion] Using CellML for simplified neuron
models?
To: "'CellML Discussion List'" 
Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
Content-Type: text/plain; charset="us-ascii"

Hi Hans,

We are looking for a good way to describe and share neuron models,  
and

CellML appears a good
candidate. The neuron models we are interested in consist mostly  
of a

single compartment,
possibly of a small number of compartments.

As far as I can see, CellML appears well suited to describe the so- 
called

subthreshold dynamics
of model neurons. But I am wondering if CellML can also capture  
(or be

extended to capture) the
threshold operation present in most simplified neuron models.  
Briefly, the

model dynamics are
integrated according to a set of differential equations. When the  
membrane

potential of the
neuron crosses a certain threshold, the neuron is said to "fire":  
the

membrane potential is
reset to a certain value instantaneuously, and often clamped at  
that value

for a certain period
of time afterwards (refractory period); also, an output signal is

generated.

In simple
pseudocode, this would look like:

while ( simulation time not up )

 process input
 update dynamics according to ODE

 if ( neuron is refractory )
   V_m = V_reset
   count down "refractoriness"

 if ( V_m > Threshold )
   V_m = V_reset
   emit output signal

 count up time


I believe this could easily be done, as long as you are OK with the
following:
- this would require integrating the model using an integration  
technique
that relies on a fixed time step. In my experience, anything will  
make your

resetting of Vm difficult.
- your output signal (Vm?) will always be generated.

Attached is a very simple CellML file (based on the van der Pol  
model) that
illustrates the kind of thing I think you are after. You want to  
plot the x

and y parameters (see attached screenshot).

Alan
-- next part --
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--

_

Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Alan Garny]

Hi Hans,

I can see your point now and agree that the solution I offered is not
suitable. In fact, I wasn't happy with the solution myself, but that was the
best I could come up with with CellML in mind. So, yes, this means that
events are not supported by CellML, unlike in SBML. 

Bottom line: you are out of luck with CellML while SBML is what you are
after, at least with regards to events.

Alan

> -Original Message-
> From: cellml-discussion-boun...@cellml.org [mailto:cellml-discussion-
> boun...@cellml.org] On Behalf Of Dr. Hans Ekkehard Plesser
> Sent: 04 June 2009 13:51
> To: cellml-discussion@cellml.org
> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
models?
> (Alan Garny)
> 
> 
> Hi Alan!
> 
> [Apologies for breaking the thread, I had subscribed to the list in digest
> form.]
> 
> Thank you for your example. Unfortunately, fixed time-stepping schemes
> where events (threshold
> crossings and membrane potential resets) can occur only on a fixed time
> grid are one of the big
> no-nos in neuronal network modeling, since they can lead to strong
> synchronization artefacts.
> Indeed, quite a lot of research in recent years has focused on algorithms
> to determine the exact
> time of threshold crossings efficiencly. I'd be happy to send you
reference
> if you are interested.
> 
> Thus, if we wanted to use CellML to represent neuron models in a general
> form, we would need a
> possibility to represent instantaneous events in continuous time. I
believe
> SBML events provide
> this, don't they?
> 
> Best,
> Hans
> 
> 
> 
> > --
> >
> > Message: 1
> > Date: Mon, 1 Jun 2009 12:17:54 +0100
> > From: "Alan Garny" 
> > Subject: Re: [cellml-discussion] Using CellML for simplified neuron
> > models?
> > To: "'CellML Discussion List'" 
> > Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
> > Content-Type: text/plain; charset="us-ascii"
> >
> > Hi Hans,
> >
> >> We are looking for a good way to describe and share neuron models, and
> >> CellML appears a good
> >> candidate. The neuron models we are interested in consist mostly of a
> >> single compartment,
> >> possibly of a small number of compartments.
> >>
> >> As far as I can see, CellML appears well suited to describe the so-
> called
> >> subthreshold dynamics
> >> of model neurons. But I am wondering if CellML can also capture (or be
> >> extended to capture) the
> >> threshold operation present in most simplified neuron models. Briefly,
> the
> >> model dynamics are
> >> integrated according to a set of differential equations. When the
> membrane
> >> potential of the
> >> neuron crosses a certain threshold, the neuron is said to "fire": the
> >> membrane potential is
> >> reset to a certain value instantaneuously, and often clamped at that
> value
> >> for a certain period
> >> of time afterwards (refractory period); also, an output signal is
> > generated.
> >> In simple
> >> pseudocode, this would look like:
> >>
> >> while ( simulation time not up )
> >>
> >>   process input
> >>   update dynamics according to ODE
> >>
> >>   if ( neuron is refractory )
> >> V_m = V_reset
> >> count down "refractoriness"
> >>
> >>   if ( V_m > Threshold )
> >> V_m = V_reset
> >> emit output signal
> >>
> >>   count up time
> >
> > I believe this could easily be done, as long as you are OK with the
> > following:
> >  - this would require integrating the model using an integration
> technique
> > that relies on a fixed time step. In my experience, anything will make
> your
> > resetting of Vm difficult.
> >  - your output signal (Vm?) will always be generated.
> >
> > Attached is a very simple CellML file (based on the van der Pol model)
> that
> > illustrates the kind of thing I think you are after. You want to plot
the
> x
> > and y parameters (see attached screenshot).
> >
> > Alan
> > -- next part --
> > A non-text attachment was scrubbed...
> > Name: Test.cellml
> > Type: application/octet-stream
> > Size: 4144 bytes
> > Desc: not available
> > URL: <http://www.cellml.org/pipermail/cellml-
> discussion/attachments/20090601/4c57e696/attachment.obj>
> > ---

Re: [cellml-discussion] Using CellML for simplified neuron models? (Alan Garny)

[Dr. Hans Ekkehard Plesser]

Hi Alan!

[Apologies for breaking the thread, I had subscribed to the list in digest 
form.]

Thank you for your example. Unfortunately, fixed time-stepping schemes where 
events (threshold
crossings and membrane potential resets) can occur only on a fixed time grid 
are one of the big
no-nos in neuronal network modeling, since they can lead to strong 
synchronization artefacts.
Indeed, quite a lot of research in recent years has focused on algorithms to 
determine the exact
time of threshold crossings efficiencly. I'd be happy to send you reference if 
you are interested.

Thus, if we wanted to use CellML to represent neuron models in a general form, 
we would need a
possibility to represent instantaneous events in continuous time. I believe 
SBML events provide
this, don't they?

Best,
Hans



> --
> 
> Message: 1
> Date: Mon, 1 Jun 2009 12:17:54 +0100
> From: "Alan Garny" 
> Subject: Re: [cellml-discussion] Using CellML for simplified neuron
>   models?
> To: "'CellML Discussion List'" 
> Message-ID: <001001c9e2aa$9beba840$d3c2f8...@garny@dpag.ox.ac.uk>
> Content-Type: text/plain; charset="us-ascii"
> 
> Hi Hans,
> 
>> We are looking for a good way to describe and share neuron models, and
>> CellML appears a good
>> candidate. The neuron models we are interested in consist mostly of a
>> single compartment,
>> possibly of a small number of compartments.
>>
>> As far as I can see, CellML appears well suited to describe the so-called
>> subthreshold dynamics
>> of model neurons. But I am wondering if CellML can also capture (or be
>> extended to capture) the
>> threshold operation present in most simplified neuron models. Briefly, the
>> model dynamics are
>> integrated according to a set of differential equations. When the membrane
>> potential of the
>> neuron crosses a certain threshold, the neuron is said to "fire": the
>> membrane potential is
>> reset to a certain value instantaneuously, and often clamped at that value
>> for a certain period
>> of time afterwards (refractory period); also, an output signal is
> generated.
>> In simple
>> pseudocode, this would look like:
>>
>> while ( simulation time not up )
>>
>>   process input
>>   update dynamics according to ODE
>>
>>   if ( neuron is refractory )
>> V_m = V_reset
>> count down "refractoriness"
>>
>>   if ( V_m > Threshold )
>> V_m = V_reset
>> emit output signal
>>
>>   count up time
> 
> I believe this could easily be done, as long as you are OK with the
> following:
>  - this would require integrating the model using an integration technique
> that relies on a fixed time step. In my experience, anything will make your
> resetting of Vm difficult.
>  - your output signal (Vm?) will always be generated.
> 
> Attached is a very simple CellML file (based on the van der Pol model) that
> illustrates the kind of thing I think you are after. You want to plot the x
> and y parameters (see attached screenshot).
> 
> Alan
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> 
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> End of cellml-discussion Digest, Vol 59, Issue 1
> 

-- 
Dr. Hans Ekkehard Plesser
Associate Professor

Dept. of Mathematical Sciences and Technology
Norwegian University of Life Sciences

Phone +47 6496 5467
Fax   +47 6496 5401
Email hans.ekkehard.ples...@umb.no
Home  http://arken.umb.no/~plesser
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