3. The advantages and disadvantages of teaching English to young children. Today there is a worldwide trend that parents want their offspring to be able to speak English. And they hold the notion that the earlier kids start learning the foreign language, the more impressive results they will receive. This post talks about the advantages and disadvantages of teaching English to very young students. 4. The advantages of teaching English to young children. On the one hand, small children benefit substantially from learning a foreign language. They consider English classes to be fun and interactive. It is next to impossible for a teacher not to use games and songs in the classroom. Singing super simple songs, young students learn sounds, words, and even phrases. Such songs are usually catchy and they are accompanied by a funny video. As for games, which can be frequently used in the classroom, they all obviously need to have an educational purpose. They must be simple and fun as well. It is quite an effective way to learn and review vocabulary through games. For example, a variation of hopscotch helped me a lot when I was teaching kids in a kindergarten in China. As a consequence, children learn and do not realize that they are learning. Furthermore, I believe that such an early commencement of learning English develop both receptive and productive skills. Let us examine the former skills, which are listening and reading. Kids acquire listening skills at a very young age and it helps them throughout their lives. They are likely to understand English words and phrases in different songs and natural speech. In addition, they may learn letters and spelling in a kindergarten, and it will definitely help them at school when they start to read. Coming back to productive skills, I want to mention that young children eventually get used to a foreign language, and they can pronounce words and use some phrases themselves. What is more important, they understand the meaning as a teacher must have used pictures or objects to show the meaning of the word rather than translating them. If they keep acquiring vocabulary in such a way, they will avoid translation from L1 afterward and become more fluent. The disadvantages of teaching English to young children. On the other hand, there are downsides in such a burdensome trend. First of all, English classes in a kindergarten are not always cheap as principals endeavour to hire TEFL-certified native teachers who command a high salary. Therefore, not everyone can afford to teach their child English so early. Moreover, it is obvious that such young students lack motivation and it can be difficult for them to understand, why they need to repeat some weird sounds that is why they are prone to misbehavior. If a teacher gets distracted by such poorly motivated students, a lesson is unlikely to be successful. A teacher needs to engage reluctant kids in the games and relax the atmosphere in the classroom. To add, some children can be shy and not willing to participate in any activities. It can be an issue, especially if there are a lot of students in the class, as kids copy each other. We should bear in mind that not everyone is an apt student as a new language is not their cup of tea. Instead of learning a new skill, they are forced to do something they do not appreciate, and it can lead to psychological problems that are not easy to overcome. To motivate such children there should be some incentives like points or stickers so a student can understand, why he does some particular task. The carrot and stick approach should be implemented, with more carrots preferable. What do you think? In conclusion, I can gather that despite a number of disadvantages, such as lack of motivation and problems with behaviour among very young students. There are considerable advantages in teaching English as a foreign language in a kindergarten because students easily acquire receptive and productive skills.


Thank you, Sean, and the other organizers for the invitation and to the excellent INCF staff who's made this such a wonderful conference. And I'm especially happy to be talking in this mini symposium because I think it's almost certainly the first symposium that brings together the Allen Institute that's been in the business of large-scale neuroscience and neuroinformatics projects for the past decade and is just at the beginning of its second decade expansion into into new fields that I'll be telling you about. But it's wonderful to be along here with the human brain project from the EU and the United States nascent brain initiative. So I'll be telling you about work that's just beginning at the Allen Institute, a project called Project Minescope, exploring mammalian neoportex in a high throughput manner. And I think it's useful to go back to the beginning and the present at the Allen Institute. Again, it's 10 years old. It's having a 10 year, 10th anniversary celebration this month or next month, September. And it's really important to emphasize the great contributions and accomplishments of the Allen Institute over the past decade starting with the mouse brain atlas. This is the portal. I suppose I don't have a, there's the pointer. This is the Allen Institute's portal BrainMap.org. And the first product, thank you, the first product in BrainMap.org is the mouse brain atlas which is a map of the gene expression in the mouse that was completed over the first four or five years of the Institute's existence which has been extended greatly in the ensuing five or six years to have a gene expression atlas developing mouse brain of non-human primates of the human brain and atlases of development. And all of these have really been great advances in neuroscience that have been of great use to the neuroscience community but also really signal achievements in neuroinformatics in large databases that are online that are easily queryable by the public and the neuroscience community. Most recently is the connection atlas, an atlas of the connections between different brain areas in the mouse that I'll be telling you about briefly. But my primary task today is to tell you about the Minescope project which is a large component of what the Institute is doing currently and will be doing over the next decade but it's only one component. And the Minescope program is a program to examine the mouse visual system with a concentration on the cortex and associated thalamic nuclei and really going from photons in from visual stimuli through behavior. And I think I'll read the mission statement. We seek to understand the computations that lead from photons to behavior by observing and modeling the transformations of signals in the corticothalamic visual system. We want to catalog and characterize the cellular building blocks of the cerebral cortex, their dynamics, and cell type specific structural and functional connectomes. We want to know what the animal sees, how it thinks, and how it decides. So there's a real emphasis on explaining in vivo physiology all the way through behavior. And as I'll tell you it has three components. Neural coding, that's the group that I'm meeting, cell types led by Hong Kui Zhang who's been at the Institute for around six years, and modeling analysis and theory led by Christof Koker, a chief scientific officer, and Mike Harleys who's been at the Institute almost from the beginning. So the Minescope team really is a it's a team. Starting all the way at the top with Alan Jones our CEO, Christof Koker, chief scientific officer. I've told you about the three of us leading the three equal-thirds of Minescope. But in addition, Qin Dang who leads technology, John Phillips who is not listed, who leads structured science and large-scale projects, and a large number of PhD level scientists starting with investigators, junior group leaders including people in all three divisions of Minescope. And within a year we're going to have 52 or more PhDs working in this project. That'll be within roughly two years of its inception. And all of this was made possible by really an unprecedented gift from Paul and Jodie Allen who have made a significant pledge for the first four years of this project after a decade of support of the Allen Institute. And really that's the inception of what promises to be a 10-year project. So the goal of Minescope is to understand coding and what do we mean by that? How did the 1 to 2 million nerve cells in the mouse visual cortex, not in primary visual cortex, but at all in the visual cortical areas represent and transform visual information? Starting with describing the building blocks, the cellular components, the cell types, and their projections. Counting, just enumerating the components with quantitative neuroanatomy. Recording, this is in the neural coding component. Observing the spiking activity of neurons of each of these cell types. Interfering using optogenetic tools, using light to modulate the firing of neurons to see how this affects the firing, the physiology of the circuit, and all the way through behavior. And then finally, and very importantly, bringing it all together with modeling, predicting and modeling these neural networks in a quantitative manner. And theory, this movie was supposed to play earlier. This is a movie showing the physiology, and I'll explain it later. I'll stop that now. And understanding, really, it's not just merely a data generation exercise. It's really a group endeavor trying to achieve understanding and theoretical understanding of the mouse visual system. And really, more generally, mouse cortical circuits, both single circuits, primary visual cortex, and the network of networks of the multiple different visual cortical areas. And what's unique, I think, in the organization of this is that it's injected into the highly successful organization of the Allen Institute. And it's really modeled after biotech as a matrix organization, that there are projects that draw from the resources at the institute. So the project is Project Mindscope, which again has three components, neural coding or experimental neural coding, cell types, and modeling analysis in theory. And these groups are decent, quite big, with primarily PhD and just a few technicians, but most of the experimental help and computational help comes from central resources that are organized separately and shared through the institute. So there's a very important program management component, Structured Science, which is the group that has already brought all of these wonderful projects to fruition over the past decade. Technology, which is the information technology, computational engine that runs all of the analysis, all the way through the web products, and of course, engineering, allowing the experiments to be performed. And we decided very early, sort of the ground rules of this endeavor were that it obviously should be in the mouse with all of the wonderful genetic tools that are available in mouse and the great strengths in mouse neuroscience at the institute, and that it would be cortical centric, that it would really attack the problem of cortical computation and that it would relate to behavior. And quite early, we settled on the mouse visual system, which really is a wonderful system that, although the mouse has low visual acuity, it has actually a quite wonderfully developed visual system. And it's very similar to the visual system of other mammals, but writ small, with large but more tractable numbers than other species. 45,000 retinal ganglion cells, which are the output of the retina. 18,000 LGN neurons at the LGN at the lateral geniculate nucleus of the thalamus, the primary relay station for information from the ganglion cells to primary visual cortex or V1. And as opposed to primates with probably hundreds of millions of cells in primary visual cortex, or many millions of cells in primary visual cortex, the mouse primary visual cortex has only 75,000 or 100,000 neurons in layer 4, that is, in layer 4, and 360,000 neurons overall. The reason I concentrate on layer 4 in this slide is that our first one or two-year milestone project to show that the whole system is working is an in-depth analysis of the primary input layer of cortex layer 4. I'm only barely going to touch on that. So really for the purposes of this talk, I'll be discussing primary visual cortex and then the network of higher visual areas, which there are 14 million cortical neurons in the mouse, and one or two million of those are related to the visual system. And it's really a wonderful part of mouse neurobiology that over the past decade, led by Burkhalter at Washington University, a detailed map of the mouse visual cortical system, where there are 10, maybe 12 distinct areas that process visual information, all of which are arranged in a hierarchical manner, much like the hierarchical visual system that one sees in the primate. Again, writ small, and the details are different, but it really provides a wonderful model system of a network of networks that allows us to study cortical communication. So the dominant metaphor that Christoph Koken and I and the rest of us at the Institute like to use is that of astronomical observatories. And Christoph and I wrote a piece in commentary in Nature, I guess, two years ago, where it was entitled Observatories of the Mind. And using the metaphor of astronomical observatories, just looking at this next generation telescope, a ground-based telescope with 30-meter primary mirror consisting of many hexagonal mirrors. This is a very large-scale project that will bring astronomy to the next generation 10 times higher resolution than Hubble. It's a very long-term project. It's ballpark similarly expensive as all three of the endeavors that we'll be talking about today. And we want to do something similar. We want to create observatories of the mind that have a number of attributes so that one would usually expect with big science. Standardizable, reproducible, of course, accurate. We'll be putting data online. The first three sort of standard reason that's the way science should be, but I think neuroscience, everyone included. We do small-scale studies, and it's often very difficult for labs to reproduce the work sometimes of themselves, but certainly of other laboratories. And it's wonderful to have a framework and an institution where that kind of reproducible science is what they do. And along with that, it is scalable that in individual laboratories, one can always do a small number of experiments leading to a paper. But that doesn't mean that those techniques can be scalable, which means teaching the experimental techniques to a significant number of people so it can be run the same experiment day in and day out. And I'll show a recent example of that from the Allen Institute. And that's the connectivity atlas. So the connectivity atlas is a project that's led by Han Kui-Zang, who also leads the mouse cell types component of the Minds Code project. And it's being performed by the structured science team at the Allen Institute. And this atlas is, again, a single experiment that has been performed by numerous laboratories by using viruses to trace the projections, the connections from one area to the next. And either using a virus to infect all local cells where it's injected and see where those cells project, or to infect only certain cells that are driven by Cree, that express Cree. And an enzyme that allows another transgene to be expressed. And these Cree lines can be many different things, but the goal of this part of neuroscience is to have lines that are as close as possible to a well-defined neuronal cell type, such as pyramidal cells in layer 5 that project the superior calliculus, for instance. And the later stage of this connection atlas is using cell-type specific Cree driver lines. So a virus is injected into mice of a specific age, all standardizable. It's put into a machine that does serial sections through the brain every 100 microns. And the brain itself is imaged with two-photon microscopy. And this is a machine that allows an entire mouse brain to be reconstructed at this resolution in less than 24 hours, using almost a terabyte of data from each mouse. And the important thing is that with standardized injections, very standardized brain placement and registration techniques, all neuroinformatic techniques, currently it has more than 1.2 petabytes of anatomical data online that is viewable with a standalone viewer 3D brain explorer, or it can be looked at through the web portal, as I showed you. And this is a four-year project that's coming to completion and the next generation is just beginning now. And it's online already, one of the initially scary, but as one joins the Institute, but really wonderful thing is that for all of these projects, the data don't go online after the paper is published. The data go online as soon, not as they're taken, but as soon as they're validated and go through quality control, registration, et cetera, they go straight online.  So here's an example of a number of injection sites in the dark, the bright colors of the injection sites and then it's hard to see here, but you know, go to brainmap.org, I implore you, it's really a wonderful thing to wander through the data and you can look at all the projections from the various areas, but there are these wonderful informatics tools that allow you to visualize the injections and the projection sites in three dimensions within the Allen brain, mouse brain coordinate system. And from these data, you know, it's standardizable, reproducible, scalable, but it's very important, it's complete in some sense. Of course, you can't ever be totally complete, but there's a very rich and well thought out targeting strategy so that at the end of the day, there is a connectivity matrix from hundreds of distinct brain areas, from hundreds of areas to hundreds of areas and really this object is unprecedented, I think in neuroscience, a really detailed connection atlas throughout the mouse brain with quantitative data and the amplitude, the strength of those connections measured in the fluorescence of the terminal fields scans, I forget but it is, but certainly three or four, maybe five orders of magnitude. And it can be examined by theoretical neuroscientists to look at the structure of such networks, model dynamics on such networks, but it really also can be used by classical neuroanatomists or people with specific questions. For instance, people interested in thalamic to cortical interconnections. So that's the precursor of one part of the cell types program. The rest of the cell types program includes many components and I can just list them here. I really won't have time to go through all of them, characterizing the cell types in V1, imaging and reconstructing morphology of single neurons in V1, map the connections using both anterograde and transnaptic tracing, electrophysiological profiling, which I won't be able to tell you about and transcriptomic profiling, which again I won't be able to tell you about but here's some transcriptomic data. I'm going to concentrate in the next 10, 15 minutes on the neural coding program just to give a deep dive into one program that, you know, the program that I'm most familiar with, you know, with the program that I'm leaving and I'll just give an overview of the motivation of the program and two types of data that we will be collecting. But really I want to step back and motivate studying the visual system in any species and just for people who haven't seen sort of the basic properties or more importantly listen to the basic properties of visual portable neurons, I think it's always best to go back to the source and it's very fitting the Swedish source here in Stockholm, David Hubel and Torsten Wiesel, their work starting in the late 50s. And but for the purposes of neural coding, we really want to understand two things, you know, what individual neurons do, you know, what is the computation and the much more difficult question, how do they do it, you know, what physical structure is used to perform these computations. But starting with, you know, what do they do, the neurons do many things but among the things they do is respond to visual stimuli and the quintessential new feature in visual portable responses compared to most of the retinal and phylamic afferents is orientation selectivity. So I just want to show this wonderful movie taken in the 70s by Hubel and Wiesel. And can everyone hear that? So what you're hearing are the action potentials of a single neuron in the visual cortex. And you can hear that it fires action potentials to a visual stimulus that is in quote the right place and now they're drawing a box which is the receptive field, the area in visual space that if the stimulus is there spikes maybe a vote. Can I be turned up? Electrophysiology is always hard. Now I've gone back to the beginning of the movie. Again, we're going to the beginning of the movie. This is where the, I think this was working. There we go. Just in time. So a stimulus in the right place evokes spikes but it's a very selective receptive field that many spikes are evoked if the stimulus is of the right orientation. But here comes the critical experiments. Few spikes and now no spikes at all. And now we have spikes again. So that's only one of the many computations that a cortical network might perform. And you know, that's the view in the 60s but now there's a much more sophisticated, much richer view of receptive fields. But the story stays the same. One is the story is that given the responses of neurons and also the behavioral modulation of those responses how can we explain those responses? And now we have more advanced tools such as calcium imaging. This is a movie from years ago from work that we did at Harvard where we're looking at 100 neurons in the cat visual cortex and the neurons are the bright spots and when they're activated they get yet brighter. And you can see that when the stimulus moves down to the left half of the neurons fire action potentials and up into the right the other half. So this is showing a map of direction cell activity in the visual cortex. And the goal of the neural coding program is to, through a series of physiological and anatomical observatories study the relationship between structure, connectivity, cell types and function in the mouse visual system. And going back to the last sentence in the mission statement of Minescope we want to see, to understand how the animal sees, how it thinks and how it decides all the way through behavior and decision making. And again this is through a number of observatories. And I like going through this series of images of the mouse at successively finer scales to show how different observatories might look at the visual system at different scales. We start off with the entire mouse, obviously an intact mouse that's actually awake and behaving or reacting to visual stimuli and we look at its brain or we listen in with electrodes I won't be telling you about. We look at the brain through a small portal in the brain, a glass window that allows us to look directly at the cerebral cortex and there's the cerebral cortex from a map by Burkhalter's group again. And here are all the areas in the cerebral cortex of the mouse flattened out into two dimensions. But the nice thing, there are many nice things about the mouse brain one of the very nice things for imagers such as myself is that it doesn't have cell cyan gyri, it's listencephalic or flat. So one can look directly at a broad expanse of the visual system and I like using again the metaphor of astronomy if we build observatories where do we point them we can do both a wide field survey and there are all sorts of synoptic surveys of the night sky the Sloan Digital Sky Survey and others but there are also the narrow field observatories the Hubble Deep Field and I think Ultra Deep Field very long exposures from the Hubble Space Telescope looking back near the beginning of the universe more than 10 billion light rears away and showing again a narrow field of early galaxies. So what's the metaphor there? The physiological imaging of multiple cortical areas is wide field imaging where we have a quite large window roughly a fifth of the mouse cerebral cortex which encompasses multiple areas most of which are visually driven and what we do is we do this type of calcium imaging which is a good measure of the spiking activity of neurons and we look this is before virus injection the virus holds a genetically encoded calcium indicator after a targeted virus injection we can look at two in this case of the multiple visual cortical areas and then in order to look at single neuron resolution we zoom in to fields of view that are 100 microns to half a millimeter or maybe a millimeter in scale and when we zoom in we see a field of view that looked like the movie I showed you earlier where this field of view has in this case 100 neurons that we can study the firing of those neurons with calcium indicators and find out for instance which of these cells respond to vertical stimuli which respond to horizontal stimuli which of them are modulated behavior which of them are not in this case the color code encodes the responses to the different visual stimuli of different orientations so the green neurons are color green because they respond to vertical orientations the red neurons are colored red because they respond to horizontal orientations and the blue and the yellow are the two obliques and that gives us a microscopic view of what individual neurons do but we can zoom in yet further to do a very fine scale anatomy at the EM at the ultra structural level and look at again serial section electron microscopy section after section with section thickness on the order of 40 nanometers looking at XY resolution of 4 nanometers and we're at that resolution we can see every axon dendrite and synapse and then we have the extraordinarily hard job that you heard about this morning of segmenting the data but that's again a problem for the audience that neural computation, neuroinformatics one of the grand challenges is analyzing these large data sets and that's what I'll be telling you about in the next number of slides and just stepping back way back to the issue of the structure of cortical networks of course there are two types excitatory inhibitory cells for me probably the most important fact by the excitatory network is that it's sparsely interconnected with neighboring neurons of the same cell type right next to each other the probability of connection is at most 10 maybe 20% connected and that poses the important question which neurons are connected to which and how does that relate to the computation being performed by those neurons so there are dominant models that the excitatory network is sparse and random and there are models that are actually yet again becoming dominant these things go back and forth are there cell assemblies are there within any cortical networks are there sub-assemblies of cells that are preferentially interconnected and those might be cells that do the same thing or more simply and more generally neurons that fire synchronously and any heavy network neurons that fire synchronously tend to be more connected but it's a remarkable and tumbling fact of current neuroscience is that although we believe in these plasticity rules we really don't know what is the end result of these plasticity rules how is the cortical network wired up how does that relate to co-activity and how it relates to function those are all just they remain just as much of a black box as they were in the 60s with a few notable exceptions but close so the general question of the functional conectomics part of the neural coding program is what do individual neurons do that's functional imaging and how are they wired up with respect to what they do and for instance to the vertically oriented cells connected the vertically oriented cells to the cells that signal fast velocities versus slow velocities are those interconnected and neurons that do vastly different very different things not interconnected and that's again not one question about neuronal function and it's not one question about connectivity it's are the feed forward connections from the thalamus rule-based from layer 4 to layer 2, 3 are those rule-based the recurrent connections in layer 2, 3 and the feedback connections are all of these what are they rule-based and if so what are the rules and in order to do this we have been doing large-scale electron microscopy correlated to physiology so remember I showed at the very beginning a zoom in to a red and a green cell and asked the question how are they preferentially interconnected this is the actual EM data from those red and green cells we knew what they did in vivo but in fact it's data from a very large array of cells it was a project led by Davy Bach and Wei Chang Li in my lab at Harvard and it's being continued by Nuno de Costa and others at the Allen Institute and also by Wei Li at Harvard correlating function with fine-scale connectivity with electron microscopy but in order to do that you need a lot of electron microscopy here's the cortical surface of this EM image the bright things or cell bodies that you can see pretty well the very brightest things are blood vessels and in the volume that we looked at you can almost think of it as a cortical slice it has 1500 cells on the order of 10 million synapses and its spatial extent was 400 microns 130 microns by 350 microns each picture was pushing 10 giga pixels there were 1100 of these pictures and when I say picture these are all montages the actual number of pictures from the EM system that we built it was 3 or 4 million individual pictures that were all stitched together in three dimensions by a group at the Pittsburgh supercomputing center that were put together or more terabytes of data we needed high-throughput imaging and a lot of post-processing so if there's any neuroinformatic problem this is one it's tera-scale and in the new the new project that the data of the way we connected at Harvard the raw data were well more than 100 terabytes so it's 0.1 peta-scale individual imaging data set then the question is what do you do with it and first of all you zoom into it so you can see the individual components here's a 3D view of the two cells that I showed at the beginning but that doesn't show you very much other than the nuclei and the apical dendrites but if you zoom in and zoom in again I love big screens this is maybe 3 meters so at this scale the entire data set is three football fields by three football fields of data just in 2D times a thousand so it's just an infinite data set but the point of it being so big is that you have to have a very large extent to encompass cortical neurons but you also need the nanometer scale resolution to see what you really care about which is first the cell body and then the hardest thing are the little axons these little axons, the cutting cross-section are tubes cutting cross-section that you trace through multiple images and there they can be as small as 70 nanometers so those are seven little axons that need to be traced by computer programs or currently through beleaguered undergraduates they seem to enjoy it by human tracers and the goal is to trace axons until you see a synapse jump that synapse go back to the cell body and then you have a connection from a cell body through an axon, through a spine through a dendrite to another cell body segmented all by hand in the first study that we published a couple years ago very importantly these data are online in the open connecthomeproject.org Randall Burns told you about this two days ago and it's a really wonderful public resource for this type of data of course the Allen Institute when we get into this business we'll host the data ourselves as well but currently it's not computer programs doing the tracing but an enormous amount of work that here we have some number of cells that we characterize physiologically and then with an enormous amount of tracing these are the postsynaptic targets of those cells I won't tell you anything about the science of this project but I'll tell you about the goal of the project in general the second generation and future generations is again is to ask pose this question how does connectivity relate to function? five minutes and the most important question that people always ask is why do these unitary experiments want to be different every time but the goal is not to find the details of one brain circuit but to find the rules by rule I would say how does connectivity relate to function and motifs can be independent of function are there highly interconnected sub networks that would be a motif and like any part of science looking for the regularities rather than the specificities the second so that's functional conectomics the next part really the final part is functional projectome where a projectome is not a point to point neuron to neuron connectivity but an area to area connectivity and again there are two aspects of our endeavor one is to look at cortical computation within a single cortical network and we're using primarily primary visual cortex and the second is to look at the network of networks multiple cortical areas and this science comes from a couple of studies from my lab at Harvard but studies from other groups as well here we have primary visual cortex and five of the nine or now eleven different higher cortical areas and the first question one can pose of these areas is what do they do differently V1 if we understand the receptive fields and how those neurons relate to behavior what do the higher visual cortical areas do or more simply what are the receptive field properties characteristics of these neurons in different visual areas and a couple years ago our group and Ed Calloway's group published surveys of response properties in different cortical areas and there are a lot of details in those studies but an oversimplification is that primary visual cortex responds to a broad range of different stimuli in particular responds to a broad range of stimulus velocities over a factor of more than a thousand different velocities and the higher visual areas some of them respond to a broad range and some of them are very specialized to high or low velocities and also finer or course structures so that's what these early studies did a more recent study that came out this year from Lindsay Glickfeld is how does primary visual cortex distribute the information to higher visual areas what are the rules of projections between different cortical areas and the hypotheses again it's a whole string of hypotheses but these hypotheses have the form do functionally distinct populations of V1 neurons project to different cortical areas and they can be functionally distinct populations that respond to different velocities or they can be different cell types and that's where the whole mindset project where we can look both at function and cell types in different areas there are a large number of questions about cortical networks that we can examine with this type of technique and the question is do they match the functions of higher cortical areas the technique is very similar to the connection atlas or projection atlas that the Allen Institute is already performing make an injection in V1 a virus that makes neurons express a fluorescent protein in this case it's a fluorescent calcium indicator so here we have you can see in the different cortical areas weaker fluorescence than the cell bodies give but significant fluorescence of the projection from V1 to different cortical areas and if you zoom in I showed you this movie earlier this is one of these things Lindsay first started doing these experiments and you can just look at this the kind of experiment that at least made us smile the early experiments a decade ago when we could see visual cortical single neurons flash when they responded to different stimuli now we can see single axons and even individual butons this is sped up but look right here right above where the pointer is pointing there are two butons and sometimes they fire together sometimes they fire at different times there are clearly two butons from different neurons firing away and we can look so these are neurons in primary visual cortex in a higher area and we can study the receptive field properties of these neurons so we can I could go through the details but obviously there's no time we can look at the speed tuning of these butons and I told you in V1 different neurons have a broad range of speed tuning some respond only to very slow stimuli and some only to very fast there are two cortical areas AL and PM where if you look at the cell bodies the cell bodies respond to either fast stimuli or slow stimuli and it would stand to reason but it's actually it doesn't have to be true that the projections from V1 to these higher areas match those areas that the V1 neurons that project to AL have speed tuning so that some of them respond to 400 degrees per second or even 800 degrees per second but and very few to 1 degree per second however in PM neurons that respond to 1 degree per second or 6 degree per second are much more V1 neurons are much more likely to project than neurons that respond very quickly and there's a V2 like area and the projection from V1 is very general so again for this one projection we know that neurons V1 have diverse properties and they project to distinct areas but that's an anecdote and neuroscience is full of anecdotes our first physiological pipeline in the neural coding program is the functional projectome and this will be similar to the connection atlas but with physiology and it's a very large matrix of experiments that each one of these squares is a distinct injection and the injection will be in one of 11 areas or thalamic targets projection cell types it'll be in one of several cell types a layer 5 cell type a layer 2-3 cell types each of which will have distinct projection patterns so that's the anatomy experiment and then the physiology experiment is again multi-dimensional we'll look in N different target areas you know from V1 to 10-11 different target areas we'll have different stimulus types velocity tuning noise stimuli to map receptive fields natural scenes etc and of animals in different behaviors running doing a cognitive task and sleeping there's a lot of neuroscience in there that we hope will be used by people in a reverse array of fields and again it's neuroinformatics and really our goal is to get people interested in physiology and anatomy and their interrelations munching and doing science under a very large data set now the goal I'm almost done I told you about the mouse cell types program very briefly I told you in great detail about the neural coding program and two large scale projects in that the functional connectome, the functional projectome and then very briefly apologies Christoph and Mike I'll tell you about the modeling and theory component but again it's an equal component and really it brings the synthesis together there are component models, system models and theory the component models are generalized linear and nonlinear single neuron models adapting synaptic models sort of different types of single neuron models system models spans a very broad and very important range ranging from biophysically realistic models of the type that in particular the human brain project is working on quite a bit more reduced models, generalized integrated fire models of v1 and what Christoph and the team call IC a generalized integrated fire point model of the entire visual system from retina to thalamus to multiple cortical areas and finally it wouldn't be leading to understanding unless there were theories, so theories of dynamics of Bayesian coding and reconstruction and hierarchical models such as Hmax of cortical computation and the near term goals of the modeling this is the next slide the near term goals of modeling and theory again are concentrating on primary visual cortex and in fact even layer 4 a model of the optics of the mouse eye the morphology and just the numbers of cell types in v1 and their interconnections spiking models for the thalamus and the cortical targets spiking models of an entire cortical column and how it relates to both receptive fields and population statistics and dynamics and finally large scale models of the network of networks from the connectivity atlas I guess and also this is not modeling but analysis and there is a wonderful computational anatomy team led by Hanh Chuan Peng and I told you about that so in the last slide really I'll talk about the general project of Minescope and its challenges what we have are plans for a very large scale project by the end of the decade there will be 250 people working on the Minescope project in an institute that will be twice that size an easy to state goal is to build these observatories of doing large scale experiments and that's something that has experimental challenges, informatics challenges but I think the more important part of this large project is the tight integration of anatomy, physiology, modeling and theory and the real goal is to have groups to achieve synergy so our watch word, our journal it's called synergy where the entire group ranging from mathematical physicists to intracellular physiologists to molecular biologists get together and discuss the problem of coding and computation in the visual cortex and really the goal, the related goal of making all of these scientists who have distinct interests but have signed on to work on one common project, I think that's really the hallmark of this project at the Allen Institute it's one institute, one project one goal with a large number of people targeted on the same thing and it's really as Kristoff and we all say it's as much a scientific project as an experiment with the sociology of neuroscience and really this is the important part of the team that this is the team a year ago before I think any of the mind scope people have arrived and you can see how large it is there, it's over 100, now it's well over 200 and we'll be growing to 500 by the end of the decade and it's really just an extraordinary time in neuroscience when these large scale projects are happening at single institutes and nationwide or continent-wide here in Europe and it's remarkable to me and really remarkable to the institute that the generosity of two people, Paul and Jody Allen allow us to do this comparable scale project in neuroscience thanks Yeah maybe I can start yeah, so first I think it's a wonderful talk and a wonderful project and it's sort of like the interesting thing is that the institute which is most open to data sharing in practice is actually privately owned it should be the other way in some sense or privately driven, privately funded it's scary for individual groups to do it but if it's the price of doing business it's the privilege of doing business is to have the data curated and put online so I think many people here in this room would like to use some of this data that comes out, so what's the time scale for getting out morphologies of the neurons or maybe like multi-compartmental models of the neurons how do you see, when can you expect to have them online? No, frankly the original plan was to not have any of the mind scope pipelines ramping up until 2015 we've been somewhat over eager and we'll be starting the functional projectome and a morphology and biophysics pipeline and also the next generation connectivity pipeline next year, I we're planning and this isn't a promise even though it's public I guess on YouTube that by the beginning of 2015 the first data sets for mind scope will be going online Hi, I'm Michael Bota from University of Southern California can we go back for just a moment to the Ponectom slide where you show that great matrix I have a question, let's say with two parts and it's better to have the matrix You wanted the matrix of the mouse connectivity atlas? Okay Okay, so these data where from crane injections or classical tracers? They're AAV injections AAV so overwhelmingly enter a great connections and what do you think what are you going to do with retrograde or labeling? That is one component of what we called next-gen connectivity so stay tuned Great And again, this is Hank Weissang's project The second part, let's say the second part of the question you mentioned that you have quantitative data in this matrix did you actually count the terminals? No It's overall fluorescence waiting for more informatics but that's what it currently is Intensity, optical intensities, something like this Optical intensities Optical intensities So how are you dissociating between a fiber of passage and a terminal? When you say when you have overlap of these two in a workshop? No, it's a concern This is the detailed analysis but it's not that's why the data are online The beauty of the Allen Institute is that it works with a timeline Is it the final word on this project? No, but is it the definitive first word? Absolutely You had to produce something by a time It's more than that So is it the most quantitative analysis of the point-to-point connectivity? No but I think and they think it's not my work signal intensity is something like this It's closely related Would you be interested in some other people to help you annotating and polluting manually this data? Absolutely These data are extremely valuable They are unique The data are all online There are means for getting the entire data set It's a header byte so you'd have to pick and choose but it is online and the institute will be continuing to work on it but of course the community would be a great feature There would be ways that the community didn't do further analysis Thank you very much


Bar and even if he just puts his hand on the map right here, and I'm in my crab ride I can always scoop it okay, but I want a more match like situation to where he's trying to make me panic And I have to adjust okay, and scoop obviously I don't hang out here very long now He's talking about it. We come here this guy comes to his knees And I have a bar and a half. Yeah, I'm just gonna float and just stack it straight up right here They just stack it straight up drop my hip in the armpit all that type of stuff now One thing I want you to think about if you lose the bar Don't worry about it. You lose the bar. Don't freak out Okay, if I lose the bar I'm just gonna adjust my half and I'm gonna make this guy pin himself Raise your hand if you've ever like purposefully pinned yourself in a match Hope nobody raised their hand Like you were you were close to being pinned and you just went okay, it's time And just waiting for the referee to slap the map somebody in here's done that for real Okay All right, do you remember who it was against you don't I would remember the guy I was wrestling if I made myself If I pinned myself, this is why I'm saying that I'm gonna put this kind of position to where he either goes to sleep Or he pins himself and it's gonna be a hundred percent legal. All right focus focus I got my half and I got my bar Okay, got my half and got my bar and he's kind of making me feel uncomfortable again high-end side kicks Low-end side pushes off the map. So I start to punch trying to get into his back right here And I'm straddling trying to run and I didn't start to go in and I'll lose the bar Okay, don't worry about it. You lose the bar right here if I lose the bar All I'm gonna do is still drop to my outside hip right here. Okay to this position Okay, he's gonna be on this here.  Okay That feels horrible, right? I'm taking my chest and putting it through his chest. I'm bringing my elbows to my ribs Okay, so if I lose the bar and he's on his hip I just go elbow deep with my half so get on your right hip If I lose the bar I got my half right here and I had this bar and I lose it I just drop to this position. He's gonna be fighting into me, right? He's gonna be fighting into me right here I'm elbow deep. I'm gonna swim elbow to the mat. See how this foot steps up I'm gonna walk his body over my arm. See how my arm is under his waist Then when I get here elbows to my ribs chest through his chest, and I'm just taking them down slow Slow slow. Okay. It'll be a very very very tight pin All right


will be advising against gatherings of persons of 500 people or greater from Monday. No fans, but no lack of intrigue at Back West this evening. What I'm here to do today is to announce and to inform you that FFA has taken a very difficult and tough decision to postpone the final rounds of the Hyundai A-League. But in the end, the obstacles proved too much. I think it was the only option that it was to postpone the season. Post-bucked against coronavirus. And that's what must have gone to see. For the A-League, we'll resume in two weeks after the official announcement of the fixture yesterday. Yeah, we're back to finish what we started. For me, it's as simple as that. Any side outside the top six as it stands right now can jump in. I think there might be a surprise from outside the top six that being Western Sydney Wanderers. I've got a feeling they might sneak in. We're causing damage and make that final six and hopefully make that grand final. One off game, we can put ourselves off against anyone.


Today, I want to tell you about Cards Against Anxiety, which is a really cool resource that I wrote recently. It is not specifically aimed at children, although lots of the ideas in here would be great if you're working with children and young people. It was commissioned for use with adults, and you can buy it in places like the Works and also on Amazon.  So, I'll give you an example of some of the cards. So, in the box, you've got your book and you've got this little set of cards here. Now, lots of you watch my channel and you love the anxiety hacks, and these are basically just a whole series of anxiety hacks. So, you've got things here like this one. Is that going to focus? This one is about square breathing. So, you have square breathing written on one side of the card. And then in the back, you've got some instruction that you can carry around with you. This then matches up with the book. So, you'll see on here it says it's got a page reference number. So, we're going to look at page 14. More explanation about what's on this card. So, the idea being that you can learn about the idea in full in the book and maybe practice it. And if it's an idea that you think would work with you, then you would carry this card around with you as a prompt to do this at a time of anxiety. So, you might put it in your wallet, in your phone, you might keep it by your bed. Wherever you might need those kind of prompts. There are 25 of these different cards and they've all got a different prompt on them. And each prompt has got step-by-step or simple instructions on the back about how to use it. And each of them is explained in full in the book. So, there's 25 of them and then in addition to that, there's a whole bunch of other ideas in the book, which were kind of things that you couldn't do like instantly in the moment. So, the cards are all things that you could do anytime, right now. I'm feeling anxious this might help. And then the book has things which are maybe slightly bigger. So, for example, here's a page where we talk about like mood journaling and using that to help kind of chart how you're feeling. So, I like it. I'm really proud of it as a resource. It wasn't my idea. It was commissioned by Korto Publishing, who make loads of really beautiful resources and it's been picked up by the works. So, you can get it really cheaply as well as being able to get it on Amazon. Oddly, the Amazon version is slightly prettier. So, it's got the foil and the box is slightly different. But what's inside is largely the same. So, yeah, the works one's great, unless you really particularly want this slightly prettier packaging. But yeah, so that's that really. I'm pleased with it. I hope you like it. I'd really be interested to hear your feedback and I know that the publishers of this resource are thinking about, you know, adding other ones to the series and it'd be interesting to know your thoughts on that as well. But yeah, give it a go. Let me know what you think. And if you use it yourself or for like children and young people or adults, in fact, that you're supporting, I'd love to hear their feedback on it as well, because, you know, always learning, always learning. OK, enjoy. Bye.


I have a feeling we'll have more people coming in as they wrap up lunch. So this panel is about data and how data can help build your brand and a lot of times you really don't really think of those two things together. Branding usually is something from the marketing department and from the art department and the people that help make pretty pictures. But really there's a lot that can be gleaned from data to help you make the right decisions about your brand. If you don't pay attention to the data you could make a decision that's going to cost you money. You may choose to brand your product in a way that maybe isn't what people are currently gravitating to or buying. So it really is something that you want to pay attention to. This panel is sponsored by Acerna. You may know them by their former name MJ Freeway. They recently went public this year. Had a really successful IPO. I'm going to be moderating this panel. Joining me is Jeannette Horton from MJ Freeway slash Acerna. I have the hardest time getting used to calling it Acerna. And Gordon Wade. Well, and of course I'm Jay Free. I'm sure you guys already know who they are. Seed to sale tracking. They work with dispensaries. They work with producers. So everyone really knows them very well. And then joining us is Gordon Wade from a company called Solo Sciences. And what his company does, and I'm sure he can give you a better description, but what his company does is basically assure the consumer that the product that they're buying is actually the product that they're buying. And I think it's really especially more important today than ever because again I think one of our earlier panels talked about the vaping issue that we've heard of with all the people getting sick and having so many problems. And a lot of what I've read is that it's been traced to products that weren't what people thought they were buying. And I know that I've heard there's a lot of counterfeit action going on in the market as well in cannabis. And so it's really more critical now than ever that consumers know that the package that they're buying is actually the package that they're buying. So without further ado, I think we'll start it off with really with you, Jeanette, as far as explaining to our audience what I was doing very awkwardly about the critical role of data for brands because you're on the front line. So you can tell them why it's so important. I mean, what you're doing with your data to help brands. Yeah. I'll start with what we're doing with our data to help brands and I'll just give you a sense of what kind of data we're talking about. So as a seed to sale tracking company, we collect data across the supply chain from seed to sale. And listening to the last panel and thinking about the conversational brands that we've had, I thought I'd narrow in on the kind of data we collect at retail. We also collect data at cultivation and we collect data from manufacturing that can give you a lot of interesting information about cost and margins and vendor performance and the right formulas to put into your machines and get that all dialed in. But we're going to focus on retail because I think that makes the most sense for the brands and for the dialogue that we've got today and have heard this morning. At retail, we collect data in two buckets. We collect or I like to think of it in kind of two categories. We collect product data and we collect consumer data. And that's unique for us as a seed to sell software. A Kurner Mj platform, the name of our brand, does collect a lot of consumer data, which is critical for brands to make good decisions about the kind of products they're going to bring to market, about how they're going to adjust their products to meet consumer need, to meet where the hockey puck is going, not where it is today. So product data that we collect, we collect brand information, we collect information about milligrams, we collect information about flavors, if it's chocolates or you know particular like get down to what chocolates are selling more than other chocolates, what flavors do better than other flavors. We collect that at the individual product level but also at the category level. We collect on consumers age, zip code, gender, we can track a consumer uniquely so we know how often they return, we know what they buy, when they buy it, how much they buy. You can tell you how profitable a certain consumer segment is over another segment. So there's a lot you can learn in that data. You get velocity and turns with product data. So what moves the fastest? What's got the best gross margin? There's so much to learn in that retail data and so much we concretely know versus are guessing at when we use the retail data. We've got about 10 years worth. It gives us a lot of history and we've got great coverage across the U.S. to really understand what's happening with consumers and what they're buying. And I would love to kick it to Gordon to actually answer the second part of your question, Deborah, which is how do brands use data? Just giving Gordon's background really working with brands outside of cannabis and helping them use data because I think that's where we're going. We don't use it enough in cannabis to make good data-driven decisions and Gordon can talk about kind of what's best practice outside of cannabis. My name is Gordon Wade. I am a consumer products expert. I created along with two other guys the principal process is used by every major retailer and every major manufacturer on a global basis. The process is called category management and my role was to assemble the data that was needed each step of the process to provide the metrics that people could utilize to build plans between manufacturers and retailers for any given category for any given retailer. And in the process I've accumulated a lot of knowledge about data. The entrepreneur who's the founder of Solar Sciences, Alex Shaw, who's here in the audience, and I worked together 25 years ago when we worked on this particular category management discipline I just mentioned, and Alex asked me to come back and help him in Solar Sciences in creating the sense of trust and the sense of credibility that you need about your brand. People, we've used the word brand a lot and nobody's at this point in time talked about what is a brand. A brand is basically a promise. It's a promise that you as a shopper, as a doctor, as a consumer is going to get the experience that you want, the experience physically, the experience emotionally that you want. This particular industry has, as we've discussed this morning, has suffered from counterfeiting. It's suffered from people not measuring up to that promise. And what Solar Sciences is determined to do is to take the kind of data that Jeanette was talking about, that MJ Freeway slash Akirna captures, and augment that with other data such that you will be able aspirationally to accumulate the data that is used in CPG. And without going into a long baffle gab about what that is, it's basically who buys the product, what are they buying, that is to say flavors, level of impact, level of power, where are they buying it, when are they buying it, why are they buying it, how are we influencing all those things that Jeanette was talking about. That creates a taxonomy for a product and the more that you have, the more you can use to build your brand. Data is to brand building what air is to the human body. You cannot build a brand without data.  What Solar Sciences does in its collaboration with Akirna, and I would urge you to Google an article that was in the Salt Lake City Tribune about the collaboration between Akirna and Solar Sciences in medical marijuana in Utah. Because that really represents the future. You know what MJ Freeway slash Akirna does, which Jeanette just recited. What we at Solar Sciences do is we put on the package an icon, what we call a quasar, which has a code on it. The shopper or the consumer or the doctor or the retailer has an app, which they download on their cell phone. And using this app, the app has a single code on it by surfing over so that the app is pointed at the quasar. It will confirm that the product is what it says to be, it was manufactured, by who manufactured it under the conditions in which manufactured. In other words, it creates a sense of confidence and trust, which is really what a brand promise is about. We'll talk more about that as we go on. Do you have a specific case study of how data has been used to grow a brand? Sure. I'm going to use consumer product category. Most of you are familiar with it. It will be something, the little K cups that go into a curing machine and makes coffee. If you go into a store, or if you went into a store a number of years ago, what you would have seen is six or seven brands with multiple flavors with and without caffeine at various prices, with various what I might call brand heritage. Maxwell House had one, you're good friends in mind at Folgers and Proctor had one, and there were many other brands. What happened was that the more sophisticated brand builders began to capture the data so that they could understand much the same way that a young woman talked about here where she was talking about the amount of product that was bought, that the heavy users, so to speak. With that data, they were able to understand the level of loyalty to brands, to flavors, to other attributes. An attribute is something like a flavor, could be a brand, could be an ingredient or lack thereof, could be a particular level of power with the amount of caffeine in the product, etc. So what the brand builders were able to do was to ascertain who was loyal to what and why. They were able to ascertain who was exclusively loyal to a specific attribute, for example, and with that, they were able to go to the retailer and say, why are you carrying seven flavors of vanilla coffee, a K cup? You don't need seven flavors at the same price point. You only need one because the consumer will switch between this brand and this brand, that flavor and that flavor, but they will be loyal to XYZ. So if you have this particular attribute on the shelf, that's all you need that represents that particular attribute. So what happened was the retailers began to realize they didn't have to have hundreds of dollars invested in non-moving inventory with this particular characteristic or attribute that they could narrow their assortment, so to speak, and thereby reduce their inventory, increase their product turn. There's various mathematical, I'm your basic math nerd, so there's calculations you can do on velocity. One of the principal ones called Gemroy gross margin return on inventory investment.  So anyway, this Gemroy capability, Gemroy metric can be utilized to help the retailer turn his inventory and become much more profitable. So one way to build your brand is to know who is buying it, who the heavy users are buying, what's the attribute the heavy user is buying, and utilize that, leverage that to modify your own brand assortment and much importantly also, or as importantly, convey that information to the retailer so that the retailer can winnow their assortment to generate more profitability. That's what category management is, that's why Alex Shaw asked me to come back because we want to apply this to your business while we give the shopper the confidence that they are getting the product that they want with the level of functionality they desire, etc. If you don't mind me interjecting, I came from Coca-Cola, I can vouch for what Gordon is saying, I hadn't met him till recently, but those are the practices that we use, that's the science that we looked at when we analyzed data and we analyzed what we had on the shelf and how quickly it was turning and how profitable that was, and it really boils down to data comes back to the data, whatever math you apply to it, you have to start with your base of data, and I like to think of it as either a laser or a crystal ball, so in Gordon's examples you've got a crystal ball that tells you can look into the future and tells you what's happening, but then you've also got a laser that pinpoints what's not working and where do you have the most opportunity and you can in your head get guesses or have gut feelings or you've scaled to a place where you just don't have a line of sight into everything and so you've got the data that gives you the future predictions as well as the laser focus on what's happening now that you could fix or improve. I think sometimes what happens in the cannabis industry is so many companies begin as startups with people that have an idea and they just take it and run with it, maybe without doing some of that homework and doing a little bit of research first, I know someone that I knew had created this smoking accessory and had spent a ton of money on an industrial designer and because she just particularly liked this way of consuming cannabis and I remember when she was, I was having this conversation, I'm a journalist and I was getting pitched this story and I remember thinking in my head the whole time that this pitch is coming to me about this wonderful smoking accessory and how it was quite expensive, they had gotten this very fancy industrial designer and the whole time I'm thinking yeah but nobody really consumes cannabis that way, I know it's not just me but I'm sitting here thinking that's a crazy idea and it never went anywhere and I know she lost a ton of money and I can't help but think had she stopped and invested her time and money more in is this a really good market to go in versus spending all that time and money on that industrial designer, she would not have wasted so much of her investment dollars into a product that basically failed because she really didn't take the time and I wonder if that's maybe one of the issues that we have in the cannabis industry is companies are so many of them are bootstrapped that they feel like they don't have the money to pay for this type of thing but it could become a very expensive mistake to not invest that money right? Oh I'm sorry this industry is a big problem with fragmentation, I mean it doesn't, there'll be no charge for this consulting insight but this industry has to consolidate, you just can't continue at this selling county by county, I heard the one lady talk about selling a specific county late flash there are 3,200 counties in the United States that a lot of people out there you got to reach, it takes money and takes time. I wanted to go back to the issue of brand equity just briefly, there's a book written by a gentleman named Kevin Lane Keller, you can Google it and he talks about the issue of brand equity models, how do you build equity with a brand, what are the characteristics and what's a mathematical or characteristic model that you should use, there are many of these probably 10 to 15 models that exist and there are two or three that have been used for years, one of the most important ones is something called the brand asset evaluator that was developed by Young and Rubicom, the advertising agency named Young and Rubicom a million years ago all of these models in one way or another say the same thing, that brand equity is really built by uniqueness or distinctiveness that if you can create a distinctive product you win and there's even been a study done by Spencer Stewart which is an economic consulting outfit which compared the value of a brand in the marketplace to its brand equity as measured by the brand equity model and basically proved that the economic value added which is the Stern Stewart metric was directly tied to this whole sense of uniqueness, so uniqueness is what you're striving for as one of the several people up here in the previous panel mentioned how unique they were and how they tried to be unique and that's certainly the objective. And I would add to that uniqueness with a market, so Deborah gave the story of a woman's vape device that was obviously very unique, it's how she liked to smoke but it didn't align with any segment in the market and when we were listening to the past panel and they were talking about uniqueness I thought about that challenge especially with chocolates. DeFonce was up here and they were early to the market and that's lucky for them, it's a highly saturated market chocolate edibles and so how do you create something unique and for me the answer is if you're really interested in getting into chocolate edibles or gummy edibles or another category that's highly saturated find the growing market segment that's small but growing or find the small market segment that's still large enough to be profitable and again that's where data is and you see an example senior women is a fast growing and they're highly capitalized they've got a lot of income to spend market and I don't see a lot of products marketed to them so if you were interested in bringing a category of edible another subcategory of edible to the market and you're trying to find yourself to be unique perhaps that's a market maybe that's not your market maybe there's another fast growing market but that's something else you can do with data is figure out how do I make a unique product that still matches to a market and if you can find a market that's yet underserved data is that laser that shows you where to go oh I feel that there's some kernel of a kernel of nugget of information they're sorry thanks Deborah um so you know what I digress I have to take a moment here because um I had asked um Jessica Billingsley who's the CEO of a kernel I said you know you what's up with the name what I don't understand this and she had explained to me that kernel is a software term and Kern is a software term and so that's where a kernel came from I didn't know that I'm not a software geek I had no idea she is uh which is why she runs a software company but I just thought that was super interesting that little bit of information but to get back to this what you just kind of talked about something about a growing segment from from what you've been seeing what consumer segment is growing so senior women is growing seniors in general are growing but but senior women are growing what we see another growing segment that's interesting that grows right at the shift of the medical to the rec market as women so women increase in size in terms of the versus men when you shift to the rec market so if you're where we are California and the market is really still making that transition you've got an opportunity to pick up new entrants new consumers that are women we track new new entrants to the market it's been about nine percent a month this year and new is new to the legal cannabis market we track those entrants so the market is growing with new consumers and our data can tell you who that is where you live because it might be different in Oregon versus California um let me build on that with the kind of data that you can develop and that um solar sciences could enhance one of the things you could do is ask new buyers directly because if you have the if you use the solar science um icon of solar science technology uh you you can have a two-way conversation with the individuals and you could ask the individuals a number of questions about the trigger that caused them that finally tipped the scale to for them to come into the marketplace uh was it a conversation with x was it some experience was it uh some uh issue that they were having in their life what is the trigger that that caused the people how did they feel before and after uh enduring the the purchase experience those kinds of things uh can can help you position your brand and build your brand in consumer products for example for many products that are bought by uh women who who uh work exclusively in the home they're home makers one of the principal things that they're concerned about is assuring themselves that they're being a good mother so the question that's often asked is how do you feel about yourself when you serve this product well those kinds of experiences and those kinds of answers you can only get when you have your data uh augmented by solar sciences can do and that any skilled researcher can do if you have the data if you don't have the data you can't make this up uh the i'm not a big fan of the teacher's union but they have a great bumper sticker and the bumper sticker is if you think information and knowledge is expensive try ignorance there's nothing more expensive than ignorance okay and because you'll you'll lose as we say in kentucky your hat and your ass okay you this is not a good experience you know it's interesting because um when we get to the big traditional cpg companies you know they've got teams that protect their product um they can make sure that there's nobody selling fake frosted flakes or anything of that nature you know this has been um an issue that has come to my attention not long ago about counterfeiting and protecting your brand you know what's the best way to protect your brand now that we're starting to have um not only counterfeiting on the black market because i somebody told me that 80 of the black market is counterfeited products where they're actually uh taking um a cannabis brand and copying the labels and and copying that the product and and selling it as if it was that product you know what what can people do if they've got a brand and they're a small operation to protect it i'm going to give you a self serving answer that is uh uh put the solo image on your package because that's a way of saying to your shoppers we care about your buying what you think you're buying and this will assure that you are getting what you think you're getting so it's a self-serving answer but that's that's the best way you can are the dispensaries getting behind that because i feel like when you go into a dispensary there's no real you know support for them making sure that what i mean you assume that if you go in a harborside or amendment or whatever that the product that they've got on the shelf is the right thing um but do we know that yeah so this is really new technology in this partnership with um a kerna and and solo sciences and i think in terms of answering your direct question do the dispensaries want to do that are they doing that i think a good number of them want to do it um we've seen this across hemp and cannabis uh where people are really concerned as retailers to communicate to their um their audience that their products are authentic that their products are safe the products are coming from where they're coming from and so the um quasar the solo code that goes on the product that is a new new really new technology that in partnership that we're offering communicates to consumers more than what's on the testing label so if i buy some cannabis i've got a testing label that tells me what the state says it has to tell me or tells me what the um retailer has has paid for so the state requires some things that requires you know your mulegrams and it requires a few other things and then other brands decide i want to tell you more i want to get tested for terpenes and tell you about terpenes i want to tell you about some other things on this product and the beauty of this this quasar code is you can um those testing labels are limited in size limited in what you can put on it not very attractive so this code can be branded to to you know match your packaging to be the luxury experience you want it to be and then the consumer can scan it with the app and learn as many things as you'd like to tell them about the chain of custody of that product where it was grown when it was grown when new chins were used to grown it grow it who harvested it when it was processed into oil what solvents were used whether there were any cutting agents added to the solvents all the things you might want to know and you might want to communicate to your consumers to assure them as we get more and more of either the counterfeiting or concerns about i really want a transparency on on what i'm smoking what i'm consuming and i want you to give all that information to me how do you do that on a small package how would you do that on a joint package you can do that with this with the solo code and mj freeway mj platform integration i know with a lot of the vaping lately we've seen some of the bigger companies come out with a press move you know where they've issued a a press release saying you can be sure that what we've got in our vape cartridges there's no you kind of mentioned the word filler there's no added chemicals it's this that and the other and i felt that was really smart of them to get out front and ahead of it because i feel like you know we were seeing this on the six o'clock news and that's not a good thing because i can't imagine what that was going to do to sales of thc vapes where i know you know they're coming from some of these products are coming from organic farms and and i thought their message is going to get lost because people are just going to lump vape into you know all one big category um you know we kind of touched a little bit on the category of uh women of a certain age being in a more emerging consumer group um what really is the what are the products that are emerging i know for a while there was all microdose was the big thing you know is is there a new you know product trend that we're seeing vapes yeah so um we find older consumers are vaping a lot um so vapes we had actually took a look at the data with the recent news in vaping and have seen just a bit um no decline in vape sales um in the cannabis legal market so they've been growing steadily and really fast and there's been no no impact in sales with the recent news you know and i also kind of wonder if a lot of the vape troubles we were seeing were from kids that that suck on a jewel like every five minutes and then that's what's really hurting their lungs but then they kind of lumped the whole thc vape into the category and we don't know and differentiate it and that's part of the issue with you know a lot of these have been purchased on the illegal market there's no seed to sell tracking there's no compliance there's no way of knowing what's in those products and whether they're full of pesticides and that we don't know so purchased from a legal market and the what's special about cannabis that's surprising is the amount of transparency and accountability we're bringing to a consumer product good that's more than any other industry you don't know what's happening with your tomatoes or your lotion or any other products you're consuming down to the level that we know with cannabis i you know it's funny that you bring that up because i know um now once you kind of get in your head that you're thinking about these uh cannabis products that you're buying and down drilling down to the farm it's coming from and such uh you can go in the grocery store and buy all kinds of foods that we have no idea where it's coming from and when we had that whole equal i thing with the lettuce it took them weeks to figure out where that came from and then when you get into um pig farms most of the farmers won't even let you onto their farm they won't let the regulators onto the farm to to figure out what's going on so if you had that kind of data you keep that from happening or you if there is a problem you determine it really quickly but that also protects the brand because back to that point if you've got the data to support that behind your brand your brand has once again what Gordon was pointing to trust and i thought that that was a really amazing point that you made at the beginning was you know what is a brand which is seems like a basic question but it was being able to trust in that product and the think of the experience uh when you have one of these quasars on the package and you have your own cell phone so this is a level of trust and confidence because you've got your cell phone in your hand you've got the app on your phone you're not depending upon something printed on the package that may not be accurate uh that may not even be the package it was made once you see the um uh quasar and and you see it with the cell phone that you're holding in your own hand uh it has a level of reinforcement for trust and confidence that is hard to get from almost any other experience i'm curious have people um started down one road with a product and then started that you know of that then once they saw the data pivoted and went a different direction because i feel like maybe that that often happens that you fall in love with an idea um kind of the sample the the example i gave earlier you fall in love with an idea because it came from you so of course it has to be amazing um and and then sometimes i feel like maybe um company leaders even though they see the data they just don't want to believe it because it was telling them that their idea maybe wasn't the greatest idea um i feel like you know it may be hard sometimes for company leaders to get that data and and then actually follow it i mean it's important to get it in the beginning to get your data you we've all said that to collect that in the very beginning so you don't make those costly mistakes because building an operation a cannabis operation around an idea is really expensive proposition so if your idea wasn't the right idea the product wasn't the right product that's that's not going to work usually what most the time most the time people have the product right what we see people making tweaks around is pricing we see them making tweaks around formulations um we see them innovating and moving to a new a new way of producing their product so live resin um is the most popular kind of name for concentrates right now so if you're buying a concentrate and you're thinking about types of concentrates it's hard to kind of call what do you call live resin but if you're thinking about um what's popular with consumers among concentrates if that's in the name that's very popular so that gives you a data to say make tweaks to a product we see more tweaking to say you know what i'm gonna i'm producing a great concentrate from a great strain but i really want to be able to call it live resin so i'm gonna change the way i produce this product in order to produce that type of concentrate because it's gotten very popular can the data give you that i mean can the data drill you down into those types of words like live resin it can it can and so we we produced a guide around concentrates recently for seven ten live resin's the most popular uh type of concentrate people are buying but sauce whatever you think of its sauce because i you know you label it sauce and it might look one way it might look another way but it's growing people are very excited to buy what is sauce so it's a particular it's different so sauce is a saucier concentrate it's a little bit more liquidy and often it'll have diamonds or crystals in it mixed in with the sauce and this is crystals this has become very popular so are you still but do you would and forgive me if being ignorant i'm a personal fan when i'm not six months pregnant so so are you do you put the sauce in a in a dab yeah you can adapt you dab it like you would dab anything else any other concentrated it's just a slightly different kind of consistency essentially okay um and maybe there's other things probably concentrate you know people out there extraction artists who want to strangle me um but yeah and and that i could see where that could be kind of uh where again this data is giving you that brand information because when you get into that concentrate area and you got wax and crumble and shatter who how do you make yourself unique right in that world right and so i would tell you sauce people are in love with sauce right now so there there you go that's that's the way to to get something any i would also feel like you know what we've seen in cpg as well traditional cpg is is flavorings and and you know how those trend go in and out flavorings and packaging so in cpg for sure like established cpg think of coca-cola or um kinds people have started innovating with packaging how do you bring innovative packaging to the market something probably everyone has seen or the new if you could a Chick-fil-A they have those packets of catch up where you like open it this way you kind of pull it down and dip or you squeeze it's still just catch up but the packaging innovation turns out to be unique and interesting and that's really helpful and so we we capture packaging to understand what packages of joints sell better as a three pack a six pack a two pack um and then how do you innovate with packaging how do you change your milligram um your your up your milligrams or lower your milligrams and conveying a whole chocolate bar or small chocolate bar and there's so many things you can dial in to understand this is the right package size or the growing package size for this segment that same experience that jenette was talking about exists across numerous product categories the the issue of packaging uh and utilizing the right size uh take uh tied pods for example that is a function of the fact that women were not using women who did the mocha laundry were not using the proper amount of product and therefore they were getting a sub optimal result and and not uh significantly not making proctor and gamble enough money because the consumer wasn't using enough so this was a scene by proctor is that everybody wins we'll we'll put them in a pod and give them the precise amount of product uh it's in technical terms it's builder and surfactant there's two driving functions within a detergent we'll give them that and we'll we'll force them to use this they'll get a better result they'll be happier etc etc unfortunately children thought they were big candy and began to eat them which is not desirable and that gets to an issue of safety with uh with cannabis uh one of the things that we heard one of the ladies in the previous panel talk about negative experience at different levels of potency and um this is going to cause a problem i mean this is a litigious society in which we live in i'm sure that people are going to start suing everybody for everything and and one of the things one of the ways that you can help to avoid that is by using a system similar to uh what akirna uh is is using and the with the capabilities uh and the assurance that can be provided by something like the solo science uh situation because you can say well we we told you this this this was what we told you it was what we said it was and you know you have some responsibility for x y z so it's it's going to happen and it kind of reminds me of i had um interviewed a gentleman that ran a company that does these uh cartoon figurines and they come in a square box and whenever you go to comic con the biggest line on the floor is the people that are in line to get these limited edition figurines in these square boxes and he had told me when he took over the company um they were floundering they weren't doing very well and one of the things that he implemented was he changed the packaging of these figurines because so many of the people that bought them were collectors and he said and they often didn't open the box of the toy is very much like you know 40 year virgin and um and and so he designed the boxes so that you could see the number of what the figurine was in the box and the number was on the top the number was on the side and the he had it in specific spots so you could stack the boxes and still see him you could stack them another way and still see him and so the collectors were thrilled that they finally had what they had been looking for which and it was such a minor thing blew the sales out because he made this simple change because he knew again that the data had told him that this was what people wanted and they weren't getting it from that company um looking ahead you know um what's this going to look like you know as I mean you you mentioned that we're really just kind of getting started on using data with cannabis where are we going well we we we know what the future looks like I mean our objective is to create the the symphony of data and of metrics that exist in uh cpg today and we can do that we we know what that looks like what we have to do is begin to capture the data and and then create the metrics but we have the platonic idea of the of our aspiration we know what that is it's not new it's been around for 20 25 years I want to go back briefly because I talk briefly about health effects one of the positive things that's going to happen especially in Utah as people are given uh cannabis for medical reasons because they will have the solo app and the Akirna data we'll be able to create A and B panels test panels for cancer patients and know what level of of potency did what under what circumstances and put it into this in evolving set of data that's coming utilizing predictive analytics to understand things like the progress of breast cancer and whether how cannabis would interact with that etc etc so the this data has not only a recreational capability or function but a dramatic scientific function if you know A that is correct stuff and B you can assure that the individual the patient or the test participant actually used the product that he or she was supposed to use do we have any questions I think we'd love to see if anybody has any questions for our panels yep we have some questions some people are shy about asking questions because they think that it makes them stupid I'm a reasonably smart person and I ask a lot of questions because I don't know much of anything so feel free to ask questions I certainly won't consider evidence of stupidity I consider evidence of intelligence and if you don't want to talk about it here please come and see Jeanette and me we'll be roaming around here and please come and see us and ask anything you want to well we're here to help we want to advance the cause and and the best way we can do that to share the information experience we have far away when it comes to predictive or prescriptive data it's one thing to have the data in your stakeholders hand it's another for them to be able to extract the insight that it provides how do you go about educating your stakeholders to become more data literate so we have I'll answer that for MJ platform you're right it's one thing to collect data it's a whole nother thing to analyze the data and get insights out of the data that help you make good decisions those are miles apart from each other so we provide in platform a visualization tool that is a lot of calculations for you it gives you gross margin it gives you sales it gives you you know all the data you want about consumers tells you gender and age etc etc are all calculated for you so you don't have to go slice and then you can slice and dice it you can slice it by product you can slice that by category and get your analysis there and really easy visual representations it's not going to give you everything but you can build your own dashboards and tools and then you know at least have a one-time consultation with us to build it or anyone else and then have this data refreshed every 15 minutes for you to come back to and answer those key questions and I would also tell you start somewhere start with a couple of questions you want to answer and then build from there it can get overwhelming because there is so much data collected start with a couple of questions and go from there but we do provide visualizations that make it a lot easier to answer take data and turn it into insights the issue is what are the questions we people always worry about the answers but the answers you can only get the right answer if you ask the right question so it helps if you ask yourself what is the problem I am trying to solve what is the question I'm trying to answer or what question if answered would put jingles into my genes those are the that's where you start then we developed a concept called analytical pathways which is if the if the question you're trying to solve is this here are the here's the order of operations in math geek terms here's the order of operations you need to do to get you that answer we many years ago put these issues up in algorithms on the computers of information resources and nielson who are the two principal providers of pos data and other kinds of data in the consumer package industry so when a person asks a question they we already had the pathway to the answer in fact nielson called that product nielson answers another question so what are may personally I haven't come across any system that integrates fully with metric but what are things that a lot of the software systems relations with the regulatory systems what are you guys doing to it because I know there's a lot of information that the regulatory systems will not give and a lot of that information could be very helpful to the industry and I really definitely see that that would be a benefit to the software program so I'm trying to figure out like how are you guys relating with the the governments in the various different states in these regulatory systems so we're actually plug for us fully integrated into metric in nine states but I can't say that I don't think that's true for California yet that being said though what the state systems collect is much less data than what's usually collected by the seed to sell software so as the seed to sell software is going to be a better source for for data because there's going to be usually more data and richer data but I say I say usually and it might not be usually with our software it's much much richer we collect a lot of data it makes us someone asked me about what's the difference between your software and other software's earlier it makes us a little we're not as simple to use because we're asking you to enter more data but that data is so much more valuable to you you can answer so many more questions and you can with what's what's only required to be collected by metric is not going to answer your questions so that's your point you're pointing out you got to move over to a seed to sell software and then assess if you're really about the data assess which one of these systems collects the most data I can use that's the real value metric's going to make you track some stuff or wherever you are whatever state you're in that data is great great for them it tells them about taxes and it helps them come out when they inspect you you need a lot different data about cost of goods about your consumers that you're going to get out of a proper seed to sell software so circling back to brand uniqueness for a second you were saying that it's very important for the brand to be unique and to be authentic but you're also talking about pivoting a little bit and identifying a market share that hey you may need to go over here how do you square those things with your client if there's a conflict well I think it has to be squared you know you look at where the opportunity is and you say this works for us and for our brand or this doesn't that's what that's where the magic is we I would never tell you to not be authentic you've got to figure out this this growing segment makes sense for us as well we can do this well what else there there are less expensive research techniques you can use I mean I would be shocked if people hadn't been using something like a focus group where you can bring in users or non-users as a case may be of various products and simply ask them and ask them you know why they're doing x and why they're doing y you can even create products and throw them out on the on the table and ask the people what about this product here's what this product does how would you visualize that some people use quantitative scoring techniques after they have a focus group where they'll show people a particular product idea with various attributes and then score it and doesn't take much money to collect a bunch of folks and you don't need a whole a whole lot of people or respondents to get some idea it helps you more on what on getting rid of the bad ideas than finding the really super ideas but I've seen people literally find super ideas in focus groups one of them I can remember very specifically was in infant diapers but that's another story so there are there are simple less expensive research techniques that you can use all right well one more question I see someone back there when you're selling like do the same principles apply when you're selling raw materials to the manufacturer I would think so because I would think that there's you know whether there's trend is towards organic or certain strains I mean building an authentic brand is going to apply even I think to raw materials and there's what one material is it and I could tell you what data you could collect or use I mean it really depends but I bet there's some data we could give you that would be useful for you as well like biomass biomass and how okay yeah absolutely I mean what you're going to want to know it this is how where I would you're telling me you're selling biomass you're going to want to know my guess would be what what's it going to be used for what are the growing trends and the finished goods that your product would go into and that would help you figure out what's the right raw material to sell and pricing yeah yes and pricing so thank you Deborah because you want to be priced where it's attractive for them based on what their in retail prices and again there are cheap ways to evaluate pricing we can talk about them later are we almost done here I just want to thank you on behalf of solo sciences for tolerating us at least me and both Jeanette and I'll be here and be more than willing to answer any questions that you might feel more comfortable in asking in a one-on-one situation thank you very much yes thank you we actually have a fact sheet in your folder that you got with some other data tidbits like the nine percent new consumer entrance and that senior women are growing so if you're interested take a look at that all right we'll be queuing up our next panel bigger is not always better you know we've got we've had about 200 of yes