 Good afternoon everyone. Just before starting, I want to apologize for those who wrote me an element. I'm a bit slow, but I promise you I will really try to answer to the question you asked me by an element. So just be patient, that's it. So I basically wanted to start from what, from where we were yesterday, we were at this color property. So we were saying that the standard deviation of so the variability of your capacity of estimating the duration of T. It's basically this, it's a constant that it's the product of a constant and the duration, the base duration, the duration that you are basically discriminating. So this means that basically the just noticeable difference and also this minimum difference between two stimuli that enables you to discriminate between them. It's basically varies proportionally. So with with with the interval that you are attend. Okay, so it means that the your temporal system is sensitive to relative differences between the physical duration of two stimuli and not absolute difference. Okay. This is particularly, I think important and we yesterday we have the chance of saying that this is not a property that is exclusive for the temporal system but also it's a it's a general feature that the the the sensory system and it's due to a limitation intrinsic limitations, limitation of the sensory system that become basically sensitive to relative differences between physical properties of the stimuli. And we said that this is pretty common across species because we appreciate that in human subjects and also in monkeys and this is another example it's not just common across species so common across tasks. So, for example, this is a study here what you see. Okay, sorry, it's a study that uses two times old is an old psychophysical study by Richard library. Who basically tested the invariance of the of the scalar property of time and different tasks in this in one case the subjects were really discriminating sounds of different durations as with a perceptual task. In another case subjects were asked to reproduce a single interval as we said yesterday in this case they were just pressing holding and releasing. So there was first a sound, and then the subject have to reproduce the sound. And here what you see in plotted in this graph it's really the on the y axis the variance and on the x axis is the square duration so so the interval that the subject have to reproduce or to perceive. They have to discriminate where in this distinct ranges to 300 400 almost 500 and 550. Okay. And so what they really plot is just this variance with the square of the duration which is what is described by this equation right so and basically they claim that the variance. This is also another assumption they make is that the variance when you perform a certain task, a central temporal tasks some of these variants some of this variability in your performance is due to really to see the variability of your clock of your temporal mechanism and some other variability can be due to non specific to non temporal feature non temporal aspects of the task not that leads to the to also this very. Basically assume that if you regress variance over the square. If you do a linear regression between variance and square duration, the slope should be an index of this. Variability so of our time dependent source of variability and the intercept of this current so should basically be indicative of just to be linked to a non time non specific time component and basically what this plots is saying that. It's no matter whether you're using a perception tasks which are basically the performance with the with the black dots, or if you do a production task, basically the slope those two slopes are very close. So this is taken as really demonstration that the scholar property holds even across tasks so when basically the cognitive requirement of the task as likely different not. Not to show immediately something that is slightly different so in the same paper, so this is the same plot, but for the production task, rather than the subject rather than being that rather than producing single interval, so they hear a sound beep, and they have to press and release. They basically have to come they have to tap they have continued to have to synchronize their movement of the fingers with an external rhythm. And the written stays there for a while and after a certain amount of time it disappears the external input and the subject has to keep going with this finger tapping in absence of this external feedback. And as you can see now this the two slopes are quite different right so so if so I mean what I mean is in this task you still need time because you have to really precisely tap and you tap should have a very high temporal precision. In some case, it's very is synchronized to to an external trace, or you have to internally generate generate this very structured written, and if the task slightly changes. You lose this scar property because you see the slopes of the two lines are different. So this is already a demonstration of the, the fact that the Weber law holds but not often so not always so there are cases where. So this so not. I'm not saying that the Weber law doesn't hold I'm saying that it's not always the same across different conditions. So your performance your temporary performance depends on the task that you are performing and on the requirement the specific requirement. The task as okay so the so somehow the differences across the different duration is still there. No because your your body and so increases with the with the square of the interval so the this proportionality of your performance is still there, but it's not exactly. It doesn't have the same rate as in the other task. So that's the change in the intercept. Is anything to do with the fact that you have to do some calculation in the second task. Well, you don't have so the interest that could be you know the changing the intercept according to them could be due to the fact that you are doing something slightly different. So the clock so it's it's a requirement that the fact that you are moving your finger in different ways, right something that doesn't have it's a motor, but it doesn't have anything to do with time, according to them. So here in the second plot and the plot of the show later here you have not just the intercept change you have a change in slope. So there is a window on your screen. Maybe you want to remove so it's a warning. There is a warning. There is a warning. It disappeared because now I'm not in presentation mode. Nevertheless, I have to change what to share. Okay, stop sharing I share something different because I change the have to change the PowerPoint. Tell me whether or not. So you see dedicated versus intrinsic right. Yes, yes, we see the warning again. Yes, we see the warning that say there aren't any warning for this presentation. Okay, because I don't have any warning. So now let's really move into the models now and one of the several ways. Okay. First of all, I have to warn you that all the models that concerns time are very often are not very good models accordingly because they are often don't make very clear festival predictions about this model so you want to test them empirically and some of them are a bit vague not you can you have data and you can fit with this model and that model so I hope you won't get to disappoint by this models. Anyway, so one way of sort of make big categories out of those different models is to distinguish between models that are dedicated versus intrinsic models. So models, this, this big sort of distinction concerns the fact that some of those model, assume that you have mechanisms in the brain that are really specialized they are dedicated to distributions. So there is a modularity in and for time in the brain. And to this, this category belong to the internal clock model, and multiple oscillators model. On the other, on the other category so that when, when we talk about distributed time models are all models that assume that really this modularity doesn't exist in the brain so there is no dedicated mechanism or dedicated brain area that computes time, but time is really intrinsically computed in the brain and at the most extreme version of this most extreme version of these models, any brain region can in principle, it's in principle able to compute time. And they've been so the models that belong to these categories are multiple timers energy reader and stay dependent network models. So, but I will start with the internal clock model that this is a very old model and it comes from my information theory so it's a model that really doesn't want to have a biological possibility really. And it doesn't have a biological possibility. It's a model that assumed that there is a clock in the brain. And this clock is a sort of a pacemaker is an oscillator. And the oscillator oscillates at certain frequency and a base frequency. And there is this ticks that are, they are produced by this pacemaker are accumulated are counted somehow by a structure that it's called an accumulator that its function is really accumulating the sticks of the clock. This clock stage. So this sorry this accumulator. It's very important because the clock. It's sort of It's always right. There is nobody beating the clock. The clock keeps always the same frequency. And your perception of time is function of the number of ticks that are accumulated into this accumulator. Okay, so the more than the greater the number of ticks in the accumulator, the longer is your perception of time. And this modes the switch mode. This is a switch that is supposed to be basically a mechanism that gates so that allows the ticks to be entered into the accumulator right and this is this mode switch can be modified by the level of by the level of attention so if you pay attention to time the sort of this gate opens, let's say okay this switch opens, whereas if you don't it closes so what also is it's so whatever. So there is this basically clock stage, then there is a memory stage this model assumes that once this information is stored is stored in a working memory, then you have a reference memory. So the current information let's say the incoming sensor information storing this working memory. Then what you do you compare this working memory, the information that is storing the working memory with the reference memory, and then there is a decision stage where you compare the working versus the reference you make a decision so you decide. So, as soon as you see this you immediately get that this model it's very tuned to a certain task, which is basically this two interval forces choice task right is a task where that it's a model that assume that you have something incoming that you have a reference that you somehow stored in the past by experience via learning, and then you do this comparison and you make a decision, but for example it's not a model that can be applied when you do reproduction for example this is something that it's already disturbing about this model that it's super tuned to a specific task and it cannot be easily generalizable to other other type of tasks. Anyway, so what is important about this model is that the model assume that any perceived temporal interval, it's the result of this sum of the base maker bits into the accumulator so the model, so the clock is universal. No matter, for example, no matter the length of the interval that you are, that you, you are perceiving that you are producing, so no matter whether it's just half, so it's 50 milliseconds or if three seconds. So according to this model you use exactly this clock, no matter whether what is the sensory modality from which you, you get the signal right so no matter whether you are estimating the duration of a sound or that of a visual image and no matter also of the task that you are doing so, you see it clearly that it's tuned to this task. Anyway, the model assume that even if you have to eat the bowl, when you play tennis you use exactly this clock. And yeah, also important is that any source of variability shouldn't affect the clock, but the switch and the accumulator so the clock always it's always as I said correct always keeps on the same frequency. The universality somehow of this color property is always taken as a proof that the internal clock that the mechanism that tells time is universal. Okay, so this is always taken as a is one of the argument that the supporters of the internal clock model brings. But, but as I show also now here this is also very, very old paper one of the first psycho physical papers that tries to see whether time perception follows Weber's law or specific or a special case of it is this paper and of the 1975 where it shows that basically that this is the standard deviation in milliseconds and this at the time that the subject has to discriminate. And basically it shows that the beggars law it's, it's, it's, it holds for a range that goes from 200 milliseconds up to more or less two seconds but above two seconds doesn't hold anymore, you know the steepness of this curve rises up immediately also another case where the, the, the, the, the steepness changes so that the law is not so universal. Also, another, another empirical evidence that is a bit of against this universality of the scholar property comes from this interesting study where basically the, the, the, the, the subjects were asked to perform several tasks. Using also some of them were more perceptual some others were more motor, like, and this is a multiple top interval. So this is similar to what I said before. The subject has to synchronize with an external metronome. So you see here the tips. So there is a synchronization phase where you synchronize with the metronome and that it is a continuation where you just keep going without the external metronome. And here you basically you have the, so you do this. So you do this task with different interval with different base intervals. So you tap where so that see here the duration is not in the top I hope you get by using the distance between tops. Okay, sometimes this difference is 300 milliseconds. Sometimes it's 450 or 550 or 850. Okay. In the single interval top, you do more or less so that the motor requirement are similar to that, but rather than having a very continuous stream of movements. Here you have single tops. So you have, you have, you have to be and then you have to reproduce by tapping. You have to sort of produce the interval by giving an onset and onset with your movement. Okay, so these are belongs to motor category of tasks. This is with multiple interval, which is a single interval. And this is a more those tasks are more perceptual in one case. You have, you listen at a sort of a written. Again, you have a base interval to attend, and then you have a comparison where the intervals is shorter or longer, like in this case, and you have to decide which. So whether this second was longer or shorter than the first. Okay, this was longer. This was shorter. So you have always to compare two ratings, let's say. Okay. So here you have more or less the same perceptual task, but rather than having a rather than comparing to things that happen sequentially. Here you have to basically categorize. So what you hear is just a single rhythm. And then you have to categorize the written has belong to the short or to the long category. Okay, so there are, you know, speaking you can, there are two main categories action perception single interval or multiple intervals. Okay. And here what they do they just plot the some of the variants so the variability of the performance in the of the subjects. This is a group of subject. And as a function of the square of the interval and again they look at the steepness of those curves and intercepting as you see those curves are totally according to the task. And this is different. This is SS PMT cut this is basically are the those different multiple top. This is categorization. This is discrimination. This is single top interval so are those different conditions basically and the interval where given either in the auditory modality or individual modality. There are these tops where either beps or flashes. Okay, and you see that basically here there is a lot of although there is still this proportionality so the performance changes function of the of the basic interval you are handling the steepness of this course is different. So again this is a another example of how it's this universality it's not so universal in the end so that if the clock is the same if the mechanism is the same you shouldn't seal this variability across the task and across the sensory modalities. Now I want to move into another proof of the universality of the clock. So another empirical data that seems yes. I think there are a couple of questions in the chat. Sorry, I didn't, I don't see the chat. So it's my fault. So, so, but the Charlie asks whether you could explain again the intersection in the graph on the left so I think this was a couple of slides ago. And this. Yeah, so it was even the other presentation but yes, it should be the intercept in this in these graphs. Exactly what the interest the intercepting these graphs should reflect the variability that it's not due to the clock. So if you interpret this data, as if you have an internal clock. So this, this variance, so that the intercept should reflect so this difference in the intercept should just reflect the variance that is not due to the clock, but to components of the task and different motor requirements. Is this that you asked them. I think this is a question so whereas the slow should reflect variability that is due to the clock to the motor to the to the temporal come to the genuine temporal components of the task. Okay, so there is another question that maybe has to do with what you mean by modern so the question is how do you simulate this model. How do you simulate so if there is there are some simulations. I mean does this model correspond to mathematical model with equations. Yes, you can find yeah I can give you the references yes. Yeah, yeah, yeah, there are some, some for mathematical formalization of these models. Yeah, I can provide I didn't put here but I didn't really put it here but there are I can I can give you one of these tradesman I can put in the, I because in the references that I gave to my course they're not those. The references are not so specific but if you ask for it, I can just add it. Okay. Okay. Okay, so. Excuse me, another question I have here in the diagram of auditory and visual diagram. We see different slopes. So, can we conclude that our sensation of time through our eyes or try ears are different. Yeah. Yeah, I mean, this is one possibility right so that. So this is one possibility so it might be possible that this differences are different due to the fact that you are the information through which so the channel to which the information comes in is different to different sensitivity of the system. So of course, a possibility, but another possibility could be that since the channel is different, you use. So, the channel to which you receive this information does something on the perception so it's linked somehow to the perception of time so that. This model it's I found it always a bit bizarre and a bit tautological as well so it's not very. So, because it assume as if so it's assumed the existence of a man with a clock inside the brain, right, but it doesn't forget that you receive information through a system that has certain properties and the sensory system that is that has to really his job is to to encode so to extract features from the sensory stimulus and the send any sensory stimulus has a permanence in time right as a temporal dimension, and so this clock really. This model doesn't take into account to the fact that in this this sensory system passes the information to the clock and why passing the information to the clock. It needs to do something on this information. And you see what I mean so they only assume this high level structure that which is very abstract know and then you cannot even grasp what is this clock. So where is in the brain a clock. So we have multiple so the brain for example it's they assume that it is it's an oscillator right we have tons of oscillators in the brain. So oscillatory activity so the brain the neurons sometimes have this synchrony activity know. There are different rhythms and all the different frequency of which they synchronize but no one has ever shown that there is a particular synchrony that it's linked to time perception. So to get to go back to your question it is possible that all these differences have due to the channel but the question is does the channel transfer this information in a very neutral way, or does it do something on the signal itself, when the signal comes. I don't know if I was. Professor to follow up on that question. So from this experiment it seems that perception of time becomes nuanced based on instrumentation. And in this case, whether the ears or the eyes. It is evident that the perception of auditory and visual are somehow different. Yeah, what happens then when you, how, how is that reconciled. For example, what if the stimulus is audio visual. Exactly. But that's why we need that this is an important point because we don't know so we are able to. We have first of all now you need to reverse that of things and also you are able. So you are able to tell time different sensory modalities now. So it means that if I have an audio visual stimulus and I'm still able to be accurate in time those stimuli means that there is also some structure. That has to deal with time. Okay. But so what I'm saying is not that everything is just the upstream, sorry. So I'm not saying that everything is just due to the sensory system, and it's characterized by the channel to which you experience information. I'm saying that the two things are equal valid that you still have a high level structure that integrates time and serves the integration of temporal information, but you also you cannot deny the fact that sensory channel does something on the does a job in extracting this temporal information. And that's my criticism to the internal clock, apart from the fact that the beings so vague in terms of where is it in the brain. But you know as I said it comes from information theory that doesn't have that wasn't made with the purpose of being biological. Okay, but still, I think we have to go beyond this idea of a single mechanism is we, we really I think need to think in a more complex so things are more complex than this model would assume. Exactly. Thank you. Thank you very much. So and one, you know to go back to this question and to go to move forward to the to the lecture. So another basically prove that somehow there are high level areas that deal with time. It's the fact that, for example, if you, if I ask, okay, if I if I ask subjects. So I met so far I just stop. I just told you about psychophysics not so only measuring behavior and recording accuracy. Okay, but if I imagine that if I do, if I put some if I record the brain signal, while the subject is performing all these different tasks. So I'm asking someone to judge the duration of a sound or other the duration of a visual image and in some people do finger tapping other do reproduction other do just discrimination. So if you look at this, at this, if I record, for example, if I use fmi and I record in humans activation I see which brain areas are active, while the subjects is engaging in one of those tasks. Common areas across these tasks in this sensory modalities. Okay, so I see that there are common regions, and we will see where which region are those I just first move forward and then go backwards and this is a an example of of an experiment of that sort. Okay. No, probably I'm sorry just that the question you made me think that maybe I can just move into this one. Okay, this is related to what I just said. So this is a meta analysis. Okay, of fmi data now then we go slightly backwards. When I have to explain to you what we measure with MRI and how with the logical so in doing the MRI experiment. So, but this is what they just said. So these are areas you recall of code. This is as a template is a brain. Okay, this is a different is like a different section so different slices of the brain. So as you cut it in in the axial plane. This is on top. This is top of the head. This is bottom. Okay, this is a bell. So if you move. So here from top to bottom, you see that there are areas that seem to be active. When you do a motor task, perceptual task and this is a conjunction. So this is the conjunction of the tasks. So these are areas that are common across tasks. So this is a great level of overlap between those regions in this meta analysis. And this is basically, I think this refers to sub second timing. Okay, and these are data that refers to super second timing. So this is what I just said so they just do a method they collect a lot of fMRI studies, and they try to see the common areas the commonalities the differences for people that use different tasks and different duration ranges. So, I think that he here you can be happy and say okay there are lots of commonalities so these areas are some of them are promoter area. So, this is a promoter cortex is an area that we will see later on. It's very important for time in is an area. See, yeah. Yeah, what is jd is equal to 50 or 40. What is this jd value denotes the diagram itself there is jd is equal to 50 and jd is equal to 40. What is this is jd. Sorry, I didn't get the question. In the diagram, it is showing that there is equal to 50. So this is a slide number slice number or something. Ah, yes, the numbers. Yes, sure. No, the numbers is the, the, basically, the, the basically, you have a 3d volume right the brain. So you have coordinates. And the xz and y plane. So this is the coordinates in the z plane you are a 50 in in the actual plane as you again, if you see myself in the window, you just go from up from bottom to top. And in the z you are this coordinate at 50. Okay, it's in, yeah, it's coordinates in the, in the Cartesian plane basically xyz. Okay, this is the reference space that we use. This is a common brain. Okay, so basically you take activations from lots of people and you put in in a common space. It's a template brain. It's not the brain of specific subjects and all. Yeah, so you see the lower you go the more negative become the Z. Yeah, so you have commonalities. You have lots of okay promoter areas. So what is also interesting to notice is that most of these regions are regions that are involved with motor tasks so I was talking about this promoter area. This is an area that normally is active when you plan to make a movement before you moving your finger. And this area becomes active just slightly before you really execute the movement. So it's a is an area that is supposed to be important when you plan motor motor movements. Okay, so you see that it's also involved in time. And this is also an area that is important for motion, but it's when you, it's moved when you move you make an eye movements. So also promoter other area that is are seem to be involved in motor. It's all other areas that seem to be involved in time. It's this, the ones that belong to motor sir. So to the base. So these are subcortical areas. So these are deep in the. So this is cortex. Okay, this is deep. It's not anymore cortex. It's just deep in the brain. And also this is, it's called treatment. So it's a series of nuclei that are involved that are connected to the frontal cortex. And they're also important for a motion execution movement execution. And as well as a very important for motor coordination. So it also has activity that it's correlated with temporal tasks. So this comes, this is true for below seconds above seconds. These activity are always very similar. But for example, you see also activity in higher brain areas like prefrontal regions. So these are region regions that are important for high cognitive functions like planning strategies, right. It's an area that are sort of supervised areas of something that happens in lower regions. And more or less, you see a lot of commonalities and the areas, the two areas that seem to be constantly there, no matter the task, no matter the range are exactly this supplementary motor area and this inferior frontal gyros. So these are seem to be very highly common. Now, what does it mean, all these. So this in the first place, these are correlational methods. Okay, so what you measure with FMRI that was this information I wanted to provide what you measure, you measure the level of blood oxygenation. So it's an indirect measure of brain activity, you know, and you measure so basically how much oxygen, a given area needs, okay, and because this oxygen supply, it's correlated with neural activity because the more active, the more the more spikes are, you know, different in a certain area, the more oxygen you need, the more, you know, there is a metabolic need when a certain region is active. Okay, so what you do in MRI, and that's why does this, I just now go a little bit backwards, just because it's important for you to have also going the opposite way. Okay, just for you to have an idea of the tools that we have at hand, and the precision of these tools also. So, so you see, this is really you measure this amodynamic response so you measure the level of oxygenation, of oxygenation in blood. And here, for example, is a schematic difference between an area that is active, so it needs a lot of, you have a lot of, so the red spots are hemoglobin so it's basically where it's transports hemoglobin oxygen, so the more active, the more oxygen you need, you have also an increase in blood flow, you have an increase in and also, yeah, in the blood flow. So here you see the difference between a rest condition, so where you don't have any, so cognitive you have nothing to do, and here you are active. Okay, so you, it's an amodynamic response function. So, it's an indirect measure of neural activity and here there are some studies, for example in monkeys. The Nicologutitis is one of the researchers that first tried to see what to explore with electrophysiology and with fMRI, really he was trying to understand what you really measure with fMRI, so what are, so the hemodynamic response function correlates with what? With local field potential, with reflex or post-synaptic potential, reflex action potentials, so and here are really, so it shows that what you measure so that the changes in hemodynamic response function correlates best with the local field potential, so with reflex more post-synaptic activity, so you don't really, you're not measuring action potentials, you're measuring the consequence of action potentials, okay, so post-synaptic activity. And most importantly here, so what your spatial resolution is a box cell, so it's a 3D pixel, okay, so these are what you get are matrices of numbers that reflects the variations of the signal in the brain, and the spatial resolution of your images is a good vary, of course it depends on also on the field, on the type of sequence you are using, so it depends on the tool, but for example in a box cell that is 55 millimeter squares basically, the number of neurons are millions of neurons, so underneath this box cell. So what you are measuring here is an hemodynamic response that correlates with post-synaptic activity, so that is a consequence of neural activity, and it reflects the activity of a population, okay, so it's population of neurons, so the precision is. Local field potential is a single neural activity, right? No. No, local field potential, it reflects post-synaptic activity of populations of neurons, okay. Okay, either it is pure. The consequence, MUA, so the multi-unit activity is action potentials. Post-synaptic is what you record in the cell that receives the action potential. Yes. Okay, that's the post-synaptic activity. It's the cell that receives the input, the action potential. Yeah. And so it means that your special resolution is really, so what you record is really the population, so and also what you have to bear in mind that these are what you record when you see fMRI data, you record stuff that are, so okay, you're recording activity of a population, and this is activity that correlates with a given task, okay, so it means that it's not, you cannot make inferences about causality, right? It doesn't mean that you need those neurons or those populations activity for the task. It means that when you have a certain task, you observe that kind of activity. But most importantly, I think this is important for you to understand that we don't do, so there is a level of precision also in our investigation, in the sense that I think as you grasp the task that we give to the subjects that have different requirements, right? In one case you ask some, so you ask to tap, in another case you ask to discriminate, so from the cognitive point of view there are tons of different variables that can explain the different results, okay? So imagine that you want to compare, okay, that you want to compare the activity associated with the finger tapping with the activity that is associated with the discrimination task. So if I put a subject in the scanner and I measure differences of that sort, I would be a very bad scientist because any differences between those two tasks can be due to the tons of differences that you are, that the subject, the tons of differences in the two tasks, right? So normally the way you, the way we do things is that if I want to measure, if I want to understand what is the correlates of a temporal task, I really want to be precise and ask a subject to perform a certain task like to discriminate duration and I measure activity while the subject is measuring duration, then I want to ask my subjects to perform another task where is doing, from the cognitive point of view is doing something very similar. But rather than measuring duration is measuring some other feature of the task, so I want to compare activations of two tasks that are very similar from lots of components of the task except the component I'm interested in, I'm interested in, which is time. And this is a beautiful example of what I mean, it's an old paper, 2004, and I'll show you what this person did, so he asked, you see, he asked, this is a, so your subject will ask either to measure the duration of those blobs. So for how long the blob was on the screen for, or whether it was, so whether the two, so you have to still compare two things here, right, but in one case you have to decide which one was longer. In another case you decide which one was more personal. So you vary the color, the you of the of the stimuli. Okay, so you still have to compare, so as you can, as I hope you, as you can surely appreciate the cognitive requirement of the two tasks are very similar. What it changes is just the future, the feature of the stimulus that you have to attend, the color versus time, and what also they manipulate, they manipulate the level of attention. So they give, okay, this is a schematic view of what they ask. So there is a queue at the beginning, which tells you which feature to attend, either time or color. Okay. So, and here also this is a graded queue. It means that you have to pay more attention to time and less to color. Here, you know, 100% time, zero color, and so on and so forth. So you have a graded manipulation of attention to those different, to those different features. And you have, you go from one extreme to another extreme. Okay, and so you measure brain activity while the subject is doing this. And so the, the, what why it's nice because then what you do you subtract. So you subtract activation you see, if I am paying attention exclusively to color, but not to time, what is left in my brain activity. It's the same you can do with color. So when you attend to color, but not to time, what's left in my brain activity. In this case, you are sure that what what's left refers to the only difference between the task, which is either color or time. And what she sees is that you see, this is a reaction times. So you see that the reaction times over the attentional condition in the x axis not total time total color and these are the intermediate conditions so you see that there is a, there is a modulation in the reaction times. So that the more attention, the, the, the, the more attention the more use you should be the less error, you, you, you, you exactly the less error you perform and the faster you are. Okay, and the activity and so then what they measure that they see. So this is what I'm showing here are all the areas and these are the, so then these numbers are the coordinate system, the XYZ coordinates of this template of all the different areas that they see. Basically this is the area active, while the subject is performing time but not color. So you see it's a wide network that goes from areas from areas in the mid-temporal region, superior temporal, parietal, so you go from back to from temporal and back of the brain to the front of the brain. Okay, and here instead you see activity in an area, in areas that were that are active when you do color but not time. So here you see this occipital area and what is this before activity, this is called before, it's an area that's called before, and what is nice is that you see how also the activity in these areas modulated by attention so the more attention you pay, the greater is the activity in this region. And it's the same, sorry, basically it's the same for time, for time. So in the activity of the supplementary motor area, so this area here, which I showed you before, as one of the areas that most consistently is there when you do this meta-analysis about temporal task, but also this activity is modulated with attention. Okay, so, but this is beautiful, it's nice, you are sort of confident from the methodological point of view that you are really pinpointing an areas that are there because of your manipulation and not because of something specific that it's linked to the differences in the task, but I think there is the risk of missing something and the missing something is this contribution of sensory regions, right? Because you are extracting information from a visual stimulus and you are contrasting activity, so you are subtracting activity, so in the two tasks that you are, the two tasks that this experiment uses are visual. So you are missing all the contribution of the visual cortices, but for that you can run more tuned experiment. But just because I'm almost out of the time, the key message, sorry, in this is that, sure, you have areas, level areas that seem to be engaged with temporal computation. So there must be something I level, there must be an eye level clock, but it's not always, it's not only and exclusively this internal clock, and we'll see later next week. There are a couple of questions in the chat, I don't know if you want to finish then. Yeah, no, I'm done. So I think I will end the video. So one question in the chat, it goes back to the two different models. So, no, sorry. What happens when a person is performing several activities at the same time? So being multitasking, which areas are activated? I think you addressed this to some extent. Maybe you want to say something more. No, when you do multitasking, so if you do multitasking, I would expect that common areas are active. I would see the same network if it depends on what is common and what is different across the task you are performing, right? So if there are similarities in the tension load that is the task requires or the motor component that the task requires, I expect to see similar activity. Okay, but a question. So another question is what happens to the perception of time when you do multiple things. And this has been, so when you do multiple things, so if you are engaged in multiple activity, your perception of time, it's worse, and you have biases. You tend to perceive time shorter than it actually is. And this has been done in a proper experiment. It's another question on going back to the distinction between the two models. I think you discussed some of these dedicated model, no, but this asks, do these experiments give shed any light on the discussion between these dedicated? Well, yeah, so on the internet, so this, this expert, so observation, so all the observation, the pinpoint to areas that are common across tasks, across sensory modalities that I like these commonalities, they seem to sort of suggest that, especially, okay, maybe the, the last example, the last experiment I show it's, it's, I can answer by referring to this experiment. So if I subtract time versus color, and I see that only in time, only in the time task I see activity in supplementary motor area, I can say that maybe there is a sort of specialization of this area for time, because this area, it's not active for color. So somehow it looks like that the, the supplementary motor area as a specific function for the temporal task that doesn't have for the color task. So in some, to some extent, it is, it is modular, it has a specialization. I think here the question is not being modular or not, is not zero one, it's not binary. It's, I think it's the degree of modularity that it's questionable. But it might be not so absolute. So you might be, there is an area that it's specialized to time and other things, but not 100% to time. Okay. Other questions? So next, okay, no. Go ahead. Next week I will present some data that tells about so that emphasize more the role of sensory regions. Okay, so we go into the other extreme in seeing what's going on with these sensory regions. Yeah. Okay, so then, I think this is a good time to stop. Thank you again. Thank you. Thanks to all you guys and be patient. I will reply to your chat in the element. And I will post this extra references actually to the tradesman model, for example, for more mathematical formalization. Okay, so with this, we wish you all a very nice weekend and see you on Monday. Have a nice weekend.