diff --git a/applications/idp-arc/frontend/src/assets/ASST_graphic.jpeg b/applications/idp-arc/frontend/src/assets/ASST_graphic.jpeg new file mode 100644 index 0000000..e9c420a Binary files /dev/null and b/applications/idp-arc/frontend/src/assets/ASST_graphic.jpeg differ diff --git a/applications/idp-arc/frontend/src/assets/BanditFigure_UCLstyleBohan.png b/applications/idp-arc/frontend/src/assets/BanditFigure_UCLstyleBohan.png new file mode 100644 index 0000000..91f5064 Binary files /dev/null and b/applications/idp-arc/frontend/src/assets/BanditFigure_UCLstyleBohan.png differ diff --git a/applications/idp-arc/frontend/src/assets/four_choice_graphic.jpeg b/applications/idp-arc/frontend/src/assets/four_choice_graphic.jpeg new file mode 100644 index 0000000..d3f2cfa Binary files /dev/null and b/applications/idp-arc/frontend/src/assets/four_choice_graphic.jpeg differ diff --git a/applications/idp-arc/frontend/src/components/PageLayout.tsx b/applications/idp-arc/frontend/src/components/PageLayout.tsx index 37489cb..bec254b 100644 --- a/applications/idp-arc/frontend/src/components/PageLayout.tsx +++ b/applications/idp-arc/frontend/src/components/PageLayout.tsx @@ -201,7 +201,7 @@ export default function PageLayout({ pt: image ? '185px' : '193px', gap: 4, }, - pageBannerTitle: { maxWidth: { xs: '100%', lg: '40%' } }, + pageBannerTitle: { maxWidth: { xs: '100%', lg: '75%' } }, content: { position: 'relative', zIndex: 1 }, footer: { // marginTop: 58, @@ -450,8 +450,6 @@ export default function PageLayout({ {( [ { key: 'legal', label: t('footer.links.legal') }, - { key: 'docs', label: t('footer.links.docs') }, - { key: 'about', label: t('footer.links.about') }, { key: 'contact', label: t('footer.links.contact') }, ] as const ).map(({ key, label }) => ( diff --git a/applications/idp-arc/frontend/src/data/protocols.json b/applications/idp-arc/frontend/src/data/protocols.json index c9262d0..afb65de 100644 --- a/applications/idp-arc/frontend/src/data/protocols.json +++ b/applications/idp-arc/frontend/src/data/protocols.json @@ -1,56 +1,38 @@ [ { - "name": "Two arm bandit task", - "desc": "Test the flexibility using MED", + "name": "Four-choice reversal digging task", "scriptUrl": "https://gist.githubusercontent.com/D-GopalKrishna/fa759c74fce007dc3cc0808382e8aa79/raw/gistfile1.txt", - "scriptName": "two-arm-bandit-analysis.py", - "description": "The two-armed bandit task is a classic paradigm in behavioral neuroscience used to study decision-making under uncertainty. In this task, participants are presented with two options, each associated with a different probability of reward. By repeatedly choosing between the two options, participants learn to exploit the option with the higher reward probability while also exploring the other option to ensure that they are not missing out on a potentially better source of reward. This task has been used to investigate the neural mechanisms underlying reinforcement learning, exploration-exploitation trade-offs, and the role of different brain regions in decision-making.", - "imageUrl": "/protocol1.png", - "videoUrl": "https://static.vecteezy.com/system/resources/previews/013/566/514/mp4/futuristic-3d-hologram-brain-made-of-glowing-connections-concept-of-artificial-intelligence-computer-intelligent-learning-links-circuits-and-network-data-unfocused-luminous-particles-spinning-video.mp4" + "scriptName": "four-choice-reversal-analysis.py", + "description": "In the four choice reversal digging task mice must identify the single rewarded option and update their choice when a previously unrewarded option becomes rewarded. The reversal phase in this task is sensitive to orbitofrontal and dorsomedial prefrontal cortex function and the 2-day version used here provides a metric of recall on the 2nd day of testing before reversal.", + "imageUrls": ["assets/four_choice_graphic.jpeg"], + "videoUrl": "https://storage.googleapis.com/maabcd/tutorial.mp4", + "references": [ + "Johnson, C., & Wilbrecht, L. (2011). Juvenile mice show greater flexibility in multiple choice reversal learning than adults. Developmental cognitive neuroscience, 1(4), 540-551.", + "Thomas, A. W., Caporale, N., Wu, C., & Wilbrecht, L. (2016). Early maternal separation impacts cognitive flexibility at the age of first independence in mice. Developmental cognitive neuroscience, 18, 49-56.", + "Lu, J., Tjia, M., Mullen, B., Cao, B., Lukasiewicz, K., Shah-Morales, S., ... & Zuo, Y. (2021). An analog of psychedelics restores functional neural circuits disrupted by unpredictable stress. Molecular Psychiatry, 26(11), 6237-6252.", + "Delevich, K., Hoshal, B., Zhou, L.Z., Zhang, Y., Vedula, S., Lin, W.C., Chase, J., Collins, A.G. and Wilbrecht, L., 2022. Activation, but not inhibition, of the indirect pathway disrupts choice rejection in a freely moving, multiple-choice foraging task. Cell Reports, 40(4). DOI: 10.1016/j.celrep.2022.111129", + "Lin, W.C., Liu, C., Kosillo, P., Tai, L.H., Galarce, E., Bateup, H.S., Lammel, S. and Wilbrecht, L., 2022. Transient food insecurity during the juvenile-adolescent period affects adult weight, cognitive flexibility, and dopamine neurobiology. Current Biology, 32(17), pp.3690-3703. 10.1016/j.cub.2022.06.089", + "Cording, K.R., Tu, E.M., Wang, H., Agopyan-Miu, A.H. and Bateup, H.S., 2025. Cntnap2 loss drives striatal neuron hyperexcitability and behavioral inflexibility. elife, 13, p.RP100162. https://doi.org/10.7554/eLife.100162.3" + ] }, { "name": "ASST digging task", - "desc": "Attentional set-shifting task", "scriptUrl": "https://gist.githubusercontent.com/D-GopalKrishna/fa759c74fce007dc3cc0808382e8aa79/raw/gistfile1.txt", "scriptName": "asst-digging-analysis.py", "description": "The attentional set-shifting task (ASST) is a rodent analogue of the Cambridge Neuropsychological Test Automated Battery (CANTAB) IED task. It assesses the ability to shift attention between perceptual dimensions of compound stimuli. The task requires animals to learn sequential discriminations, measuring the cost of shifting attention from one perceptual dimension to another.", - "imageUrl": "/protocol1.png", - "videoUrl": "https://static.vecteezy.com/system/resources/previews/013/566/514/mp4/futuristic-3d-hologram-brain-made-of-glowing-connections-concept-of-artificial-intelligence-computer-intelligent-learning-links-circuits-and-network-data-unfocused-luminous-particles-spinning-video.mp4" - }, - { - "name": "Four-choice reversal digging task", - "desc": "Reversal learning assessment", - "scriptUrl": "https://gist.githubusercontent.com/D-GopalKrishna/fa759c74fce007dc3cc0808382e8aa79/raw/gistfile1.txt", - "scriptName": "four-choice-reversal-analysis.py", - "description": "The four-choice reversal digging task expands on the two-armed paradigm by introducing four distinct odor-digging options. Animals must identify the rewarded option and adapt when contingencies reverse. This task is particularly sensitive to orbitofrontal cortex dysfunction and provides multiple reversal learning indices.", - "imageUrl": "/protocol1.png", - "videoUrl": "https://static.vecteezy.com/system/resources/previews/013/566/514/mp4/futuristic-3d-hologram-brain-made-of-glowing-connections-concept-of-artificial-intelligence-computer-intelligent-learning-links-circuits-and-network-data-unfocused-luminous-particles-spinning-video.mp4" + "imageUrls": ["assets/ASST_graphic.jpeg"], + "videoUrl": "", + "references": [ + "Ma, S., Wang, K. H., & Zuo, Y. (2026). Targeting insulo-frontal pathway to reduce stress-evoked cognitive rigidity. Nature Communications." + ] }, { - "name": "Open field task", - "desc": "Locomotion and anxiety assessment", - "scriptUrl": "https://gist.githubusercontent.com/D-GopalKrishna/fa759c74fce007dc3cc0808382e8aa79/raw/gistfile1.txt", - "scriptName": "open-field-analysis.py", - "description": "The open field task is a widely used behavioral assay for measuring locomotion, anxiety-like behavior, and exploratory activity in rodents. Animals are placed in a novel arena and their movement patterns, time spent in the center versus periphery, and rearing behavior are recorded and analyzed.", - "imageUrl": "/protocol1.png", - "videoUrl": "https://static.vecteezy.com/system/resources/previews/013/566/514/mp4/futuristic-3d-hologram-brain-made-of-glowing-connections-concept-of-artificial-intelligence-computer-intelligent-learning-links-circuits-and-network-data-unfocused-luminous-particles-spinning-video.mp4" - }, - { - "name": "Elevated plus maze", - "desc": "Anxiety and risk-taking behavior", - "scriptUrl": "https://gist.githubusercontent.com/D-GopalKrishna/fa759c74fce007dc3cc0808382e8aa79/raw/gistfile1.txt", - "scriptName": "elevated-plus-maze-analysis.py", - "description": "The elevated plus maze (EPM) is a standard test for anxiety-like behavior in rodents. The maze consists of two open and two enclosed arms elevated above the floor. Anxious animals spend more time in the enclosed arms, while exploratory animals venture into the open arms. This task is sensitive to anxiolytic and anxiogenic compounds.", - "imageUrl": "/protocol1.png", - "videoUrl": "https://static.vecteezy.com/system/resources/previews/013/566/514/mp4/futuristic-3d-hologram-brain-made-of-glowing-connections-concept-of-artificial-intelligence-computer-intelligent-learning-links-circuits-and-network-data-unfocused-luminous-particles-spinning-video.mp4" - }, - { - "name": "Foraging task", - "desc": "Patch-leaving and optimal foraging", + "name": "Two arm bandit task", "scriptUrl": "https://gist.githubusercontent.com/D-GopalKrishna/fa759c74fce007dc3cc0808382e8aa79/raw/gistfile1.txt", - "scriptName": "foraging-analysis.py", - "description": "The foraging task models naturalistic patch-leaving decisions based on optimal foraging theory. Animals must decide when to leave a depleting food patch and travel to a new one, balancing exploitation of current resources against exploration of potentially richer alternatives. This task probes cost\u2013benefit decision-making circuits.", - "imageUrl": "/protocol1.png", - "videoUrl": "https://static.vecteezy.com/system/resources/previews/013/566/514/mp4/futuristic-3d-hologram-brain-made-of-glowing-connections-concept-of-artificial-intelligence-computer-intelligent-learning-links-circuits-and-network-data-unfocused-luminous-particles-spinning-video.mp4" + "scriptName": "two-arm-bandit-analysis.py", + "description": "The two-armed bandit task is a classic paradigm in behavioral neuroscience used to study decision-making under uncertainty. In this task, participants are presented with two options, each associated with a different probability of reward. By repeatedly choosing between the two options, participants learn to exploit the option with the higher reward probability while also exploring the other option to ensure that they are not missing out on a potentially better source of reward. This task has been used to investigate the neural mechanisms underlying reinforcement learning, exploration-exploitation trade-offs, and the role of different brain regions in decision-making.", + "imageUrls": ["assets/BanditFigure_UCLstyleBohan.png"], + "videoUrl": "", + "references": [] } ] diff --git a/applications/idp-arc/frontend/src/locales/en/about.json b/applications/idp-arc/frontend/src/locales/en/about.json index 8213179..23b879d 100644 --- a/applications/idp-arc/frontend/src/locales/en/about.json +++ b/applications/idp-arc/frontend/src/locales/en/about.json @@ -12,7 +12,7 @@ ], "overview": { "title": "Overview", - "body1": "The Adversity & Resilience Consortium Platform (ARC) develops a statistical framework for analyzing how early-life adversity shapes behavioral phenotypes. Behavioral outcomes arise from the interaction of multiple cognitive and motivational processes and are therefore inherently multidimensional. However, behavioral data are often analyzed using methods that treat individual measures independently, which limits the ability to detect coordinated patterns of behavioral change.", + "body1": "The Modeling Adolescent Adversity Brain and Cognitive Development Platform (MAABCD) develops a statistical framework for analyzing how early-life adversity shapes behavioral phenotypes. Behavioral outcomes arise from the interaction of multiple cognitive and motivational processes and are therefore inherently multidimensional. However, behavioral data are often analyzed using methods that treat individual measures independently, which limits the ability to detect coordinated patterns of behavioral change.", "body2": "The project addresses this challenge by modeling behavior as a multivariate phenotype embedded within a latent behavioral space. By applying dimensionality-reduction methods to high-dimensional behavioral datasets, the framework allows structured patterns of behavioral variation to be identified and compared across experimental groups." }, "objectives": { diff --git a/applications/idp-arc/frontend/src/locales/en/landingPage.json b/applications/idp-arc/frontend/src/locales/en/landingPage.json index 9dc6582..ee7b936 100644 --- a/applications/idp-arc/frontend/src/locales/en/landingPage.json +++ b/applications/idp-arc/frontend/src/locales/en/landingPage.json @@ -1,24 +1,24 @@ { "banner": { - "title": "Adversity & Resilience Consortium Platform", + "title": "Modeling Adolescent Adversity Brain and Cognitive Development Platform (MAABCD)", "ctaProtocols": "Protocols", "ctaDataUpload": "Data upload" }, "features": [ { - "title": "Download standard protocol & code", - "desc": "Download the standardized protocol and analysis code required to perform experiments according to ARC standards. These protocols considered not only likelihood of success, but also ethological relevance, and ease of access to both low and high budget research labs.", + "title": "Download protocols and templates", + "desc": "Download the standardized protocol and analysis code required to perform experiments according to MAABCD standards. These protocols considered not only likelihood of success, but also ethological relevance, and ease of access to both low and high budget research labs.", "cta": "Protocols", "ctaPath": "/protocols" }, { - "title": "Upload data", - "desc": "Share your experimental results with the research community. Sign in to upload datasets to the platform.", + "title": "Upload data in EMBER-DANDI", + "desc": "Share your experimental results with the research community. Sign in to upload dandisets to the Ember-Dandi platform.", "cta": "Data upload", "ctaPath": "/workspaces" }, { - "title": "Visualization and analysis tools", + "title": "Use your data in Open Source Brain", "desc": "Explore and analyze community data and your uploaded data with our integration with Open Source Brain (OSB). OSB lets you use interactive visualizations and powerful analysis tools with Jupyterlab, NetPyNE and NWB Explorer.", "cta": "Go to Open Source Brain", "ctaPath": "https://www.opensourcebrain.org/" @@ -28,22 +28,19 @@ "sectionTitle": "Protocols", "downloadZip": "Download .zip", "items": [ - { "name": "Two arm bandit task", "desc": "Test the flexibility using MED" }, - { "name": "ASST digging task", "desc": "Guidelines for recording and analyzing neural ensemble activity using multi-electrode arrays" }, - { "name": "Four-choice reversal digging task", "desc": "Techniques for measuring the electrical currents of neurons with high temporal resolution" }, - { "name": "Open field task", "desc": "Methods for controlling neuronal activity using light-sensitive proteins." }, - { "name": "Elevated plus maze", "desc": "Methods for controlling neuronal activity using light-sensitive proteins." }, - { "name": "Foraging task", "desc": "Methods for controlling neuronal activity using light-sensitive proteins." } + { "name": "Four-Choice Reversal Digging Task", "desc": "Measures odor discrimination and reversal learning." }, + { "name": "Attentional Set Shifting Task (ASST)", "desc": "Measures attentional set formation and shifting, and cognitive flexibility." }, + { "name": "Two-Armed Bandit Task (2ABT)", "desc": "Measures reward-guided choice and flexibility." } ] }, "about": { - "sectionTitle": "About ARC Platform", - "body1": "The Adversity Project develops a statistical framework for studying how early-life adversity shapes behavioral phenotypes. Rather than analyzing behavioral measures individually, the framework models behavior as a multivariate system embedded in a latent behavioral space. By applying dimensionality-reduction methods to high-dimensional behavioral datasets, structured patterns of behavioral variation can be identified and compared across experimental groups.", - "body2": "Within this framework, treatment effects are represented as systematic displacements in behavioral space, allowing adversity-related changes to be quantified and compared across experiments. This approach provides a principled way to characterize resilience as a continuous behavioral dimension and establishes a foundation for standardized behavioral analysis across laboratories and datasets.", + "sectionTitle": "About MAABCD Platform", + "body1": "Welcome to our site. MAABCD stands for Model Adolescent Adversity Brain and Cognitive Development. Many researchers are working hard to learn more and more about how experience of adversity can alter brain and behavioral development. One challenge of this work comes from the fact that it is hard to compare data between studies. This prevents us from learning which experiences have common or separable effects. Null results may also not often reach publication and can be lost to the community. To gain a more complete picture of the impacts of adversity, we sought to build a tool that could help our research community harmonize data collection across sites so that we can begin to compare the effects of different treatments on behavioral outcomes. We were inspired by the goals of the human ABCD projects to study adolescent development and the success of the International Brain lab, which harmonized a behavioral data collection from mice across 7 global sites.", + "body2": "In the long term we are interested in understanding a) if there are different dimensions of adversity which have separable effects on brain and behavior and b) if there are sensitive periods for exposure. We hope to disseminate these protocols so many labs can similarly harmonize their data collection enabling comparisons of a wide variety of treatments on the same behavioral outcome metrics. Our project is supported by the BBQS R34.", "learnMore": "Learn more" }, "nav": { - "logoTitle": "ARC Platform", + "logoTitle": "MAABCD Platform", "protocols": "Protocols", "about": "About", "myWorkspaces": "My workspaces", @@ -56,7 +53,7 @@ "cancel": "Cancel" }, "footer": { - "copyright": "Copyright © 2026 ARC Platform by IDP", + "copyright": "Copyright © 2026 MAABCD Platform by MetaCell", "links": { "legal": "Legal", "docs": "Docs", diff --git a/applications/idp-arc/frontend/src/pages/ProtocolsPage.tsx b/applications/idp-arc/frontend/src/pages/ProtocolsPage.tsx index 5489b15..902084c 100644 --- a/applications/idp-arc/frontend/src/pages/ProtocolsPage.tsx +++ b/applications/idp-arc/frontend/src/pages/ProtocolsPage.tsx @@ -1,29 +1,25 @@ import ArrowForwardIcon from '@mui/icons-material/ArrowForward' -import PauseRoundedIcon from '@mui/icons-material/PauseRounded' -import PlayArrowRoundedIcon from '@mui/icons-material/PlayArrowRounded' import { Box, Button, Container, - IconButton, List, ListItem, ListItemText, Stack, Typography, } from '@mui/material' -import { useCallback, useRef, useState } from 'react' +import { useState } from 'react' import PageLayout from '../components/PageLayout' import protocols from '../data/protocols.json' -const ArrowIcon = () => +// imageUrls entries starting with "assets/" point into src/assets and must go through Vite +// to get a hashed build URL; anything else is served as-is from public/. +const assetUrls = import.meta.glob('../assets/*.{png,jpg,jpeg,svg,webp}', { eager: true, query: '?url', import: 'default' }) as Record +const resolveImageUrl = (url: string) => (url.startsWith('assets/') ? assetUrls[`../${url}`] ?? url : url) +const ArrowIcon = () => -const references = [ - 'Allen, M. et al. (2021). "Bandit task performance as a measure of reversal learning." Journal of Experimental Psychology, 150(2), 234–249.', - 'Chen, L. & Bhatt, D. (2020). "Behavioral flexibility and working memory in rodents." Neuroscience & Biobehavioral Reviews, 112, 567–582.', - 'Smith, J. et al. (2019). "Multi-arm bandit tasks for measuring cognitive flexibility." Nature Neuroscience, 22(8), 1234–1245.', -] // Shared card styles consistent with the rest of the design system const protocolCardSx = { @@ -39,20 +35,6 @@ const protocolCardSx = { export default function ProtocolsPage() { const [activeProtocol, setActiveProtocol] = useState(0) const active = protocols[activeProtocol] - const videoRef = useRef(null) - const [isPlaying, setIsPlaying] = useState(true) - - const togglePlay = useCallback(() => { - const video = videoRef.current - if (!video) return - if (video.paused) { - video.play() - setIsPlaying(true) - } else { - video.pause() - setIsPlaying(false) - } - }, []) return ( @@ -151,78 +133,50 @@ export default function ProtocolsPage() { {active.name} - - - - - - {active.description} - - - - Protocol video - - - - - {isPlaying - ? - : } - - + {active.imageUrls.map((url) => ( + + - + ))} - - References - - {references.map((ref, i) => ( - - {ref} - - ))} + {active.description && ( + + {active.description} + + )} + + {active.videoUrl && ( + + Protocol video + + {/* Tutorials are long and narrated: native controls for sound, seeking and fullscreen; + preload="metadata" avoids pulling the whole file on page load. key resets playback + when switching protocol. */} + + - + )} + + {active.references.length > 0 && ( + + References + + {active.references.map((ref, i) => ( + + {ref} + + ))} + + + )}