reading
Latest
Reading Scenes
Trends in NeuroAI - Brain-like topography in transformers (Topoformer)
Dr. Nicholas Blauch will present on his work "Topoformer: Brain-like topographic organization in transformer language models through spatial querying and reweighting". Dr. Blauch is a postdoctoral fellow in the Harvard Vision Lab advised by Talia Konkle and George Alvarez. Paper link: https://openreview.net/pdf?id=3pLMzgoZSA Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri | https://groups.google.com/g/medarc-fmri).
Epileptic micronetworks and their clinical relevance
A core aspect of clinical epileptology revolves around relating epileptic field potentials to underlying neural sources (e.g. an “epileptogenic focus”). Yet still, how neural population activity relates to epileptic field potentials and ultimately clinical phenomenology, remains far from being understood. After a brief overview on this topic, this seminar will focus on unpublished work, with an emphasis on seizure-related focal spreading depression. The presented results will include hippocampal and neocortical chronic in vivo two-photon population imaging and local field potential recordings of epileptic micronetworks in mice, in the context of viral encephalitis or optogenetic stimulation. The findings are corroborated by invasive depth electrode recordings (macroelectrodes and BF microwires) in epilepsy patients during pre-surgical evaluation. The presented work carries general implications for clinical epileptology, and basic epilepsy research.
Dyslexia, Rhythm, Language and the Developing Brain
Recent insights from auditory neuroscience provide a new perspective on how the brain encodes speech. Using these recent insights, I will provide an overview of key factors underpinning individual differences in children’s development of language and phonology, providing a context for exploring atypical reading development (dyslexia). Children with dyslexia are relatively insensitive to acoustic cues related to speech rhythm patterns. This lack of rhythmic sensitivity is related to the atypical neural encoding of rhythm patterns in speech by the brain. I will describe our recent data from infants as well as children, demonstrating developmental continuity in the key neural variables.
Trends in NeuroAI - Unified Scalable Neural Decoding (POYO)
Lead author Mehdi Azabou will present on his work "POYO-1: A Unified, Scalable Framework for Neural Population Decoding" (https://poyo-brain.github.io/). Mehdi is an ML PhD student at Georgia Tech advised by Dr. Eva Dyer. Paper link: https://arxiv.org/abs/2310.16046 Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri | https://groups.google.com/g/medarc-fmri).
Trends in NeuroAI - Meta's MEG-to-image reconstruction
Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: Brain-optimized inference improves reconstructions of fMRI brain activity Abstract: The release of large datasets and developments in AI have led to dramatic improvements in decoding methods that reconstruct seen images from human brain activity. We evaluate the prospect of further improving recent decoding methods by optimizing for consistency between reconstructions and brain activity during inference. We sample seed reconstructions from a base decoding method, then iteratively refine these reconstructions using a brain-optimized encoding model that maps images to brain activity. At each iteration, we sample a small library of images from an image distribution (a diffusion model) conditioned on a seed reconstruction from the previous iteration. We select those that best approximate the measured brain activity when passed through our encoding model, and use these images for structural guidance during the generation of the small library in the next iteration. We reduce the stochasticity of the image distribution at each iteration, and stop when a criterion on the "width" of the image distribution is met. We show that when this process is applied to recent decoding methods, it outperforms the base decoding method as measured by human raters, a variety of image feature metrics, and alignment to brain activity. These results demonstrate that reconstruction quality can be significantly improved by explicitly aligning decoding distributions to brain activity distributions, even when the seed reconstruction is output from a state-of-the-art decoding algorithm. Interestingly, the rate of refinement varies systematically across visual cortex, with earlier visual areas generally converging more slowly and preferring narrower image distributions, relative to higher-level brain areas. Brain-optimized inference thus offers a succinct and novel method for improving reconstructions and exploring the diversity of representations across visual brain areas. Speaker: Reese Kneeland is a Ph.D. student at the University of Minnesota working in the Naselaris lab. Paper link: https://arxiv.org/abs/2312.07705
Trends in NeuroAI - Meta's MEG-to-image reconstruction
Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). This will be an informal journal club presentation, we do not have an author of the paper joining us. Title: Brain decoding: toward real-time reconstruction of visual perception Abstract: In the past five years, the use of generative and foundational AI systems has greatly improved the decoding of brain activity. Visual perception, in particular, can now be decoded from functional Magnetic Resonance Imaging (fMRI) with remarkable fidelity. This neuroimaging technique, however, suffers from a limited temporal resolution (≈0.5 Hz) and thus fundamentally constrains its real-time usage. Here, we propose an alternative approach based on magnetoencephalography (MEG), a neuroimaging device capable of measuring brain activity with high temporal resolution (≈5,000 Hz). For this, we develop an MEG decoding model trained with both contrastive and regression objectives and consisting of three modules: i) pretrained embeddings obtained from the image, ii) an MEG module trained end-to-end and iii) a pretrained image generator. Our results are threefold: Firstly, our MEG decoder shows a 7X improvement of image-retrieval over classic linear decoders. Second, late brain responses to images are best decoded with DINOv2, a recent foundational image model. Third, image retrievals and generations both suggest that MEG signals primarily contain high-level visual features, whereas the same approach applied to 7T fMRI also recovers low-level features. Overall, these results provide an important step towards the decoding - in real time - of the visual processes continuously unfolding within the human brain. Speaker: Dr. Paul Scotti (Stability AI, MedARC) Paper link: https://arxiv.org/abs/2310.19812
Trends in NeuroAI - SwiFT: Swin 4D fMRI Transformer
Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: SwiFT: Swin 4D fMRI Transformer Abstract: Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans. To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner. SwiFT achieves this by implementing a 4D window multi-head self-attention mechanism and absolute positional embeddings. We evaluate SwiFT using multiple large-scale resting-state fMRI datasets, including the Human Connectome Project (HCP), Adolescent Brain Cognitive Development (ABCD), and UK Biobank (UKB) datasets, to predict sex, age, and cognitive intelligence. Our experimental outcomes reveal that SwiFT consistently outperforms recent state-of-the-art models. Furthermore, by leveraging its end-to-end learning capability, we show that contrastive loss-based self-supervised pre-training of SwiFT can enhance performance on downstream tasks. Additionally, we employ an explainable AI method to identify the brain regions associated with sex classification. To our knowledge, SwiFT is the first Swin Transformer architecture to process dimensional spatiotemporal brain functional data in an end-to-end fashion. Our work holds substantial potential in facilitating scalable learning of functional brain imaging in neuroscience research by reducing the hurdles associated with applying Transformer models to high-dimensional fMRI. Speaker: Junbeom Kwon is a research associate working in Prof. Jiook Cha’s lab at Seoul National University. Paper link: https://arxiv.org/abs/2307.05916
Dyslexias in words and numbers
Research Data Management in neuroimaging
This set of short webinars will provide neuroscience researchers working in a neuroimaging setting with practical tips on strengthening credibility at different stages of the research project. Each webinar will be hosted by Cassandra Gould Van Praag from the Wellcome Centre for Integrative Neuroimaging.
Bridging clinical and cognitive neuroscience together to investigate semantics, above and beyond language
We will explore how neuropsychology can be leveraged to directly test cognitive neuroscience theories using the case of frontotemporal dementias affecting the language network. Specifically, we will focus on pathological, neuroimaging, and cognitive data from primary progressive aphasia. We will see how they can help us investigate the reading network, semantic knowledge organisation, and grammatical categories processing. Time permitting, the end of the talk will cover the temporal dynamics of semantic dimensions recovery and the role played by the task.
Real-world scene perception and search from foveal to peripheral vision
A high-resolution central fovea is a prominent design feature of human vision. But how important is the fovea for information processing and gaze guidance in everyday visual-cognitive tasks? Following on from classic findings for sentence reading, I will present key results from a series of eye-tracking experiments in which observers had to search for a target object within static or dynamic images of real-world scenes. Gaze-contingent scotomas were used to selectively deny information processing in the fovea, parafovea, or periphery. Overall, the results suggest that foveal vision is less important and peripheral vision is more important for scene perception and search than previously thought. The importance of foveal vision was found to depend on the specific requirements of the task. Moreover, the data support a central-peripheral dichotomy in which peripheral vision selects and central vision recognizes.
Learning-to-read and dyslexia: a cross-language computational perspective
How do children learn to read in different countries? How do deficits in various components of the reading network affect learning outcomes? What are the consequences of such deficits in different languages? In this talk, I will present a full-blown developmentally plausible computational model of reading acquisition that has been implemented in English, French, Italian and German. The model can simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. I will use the model to show how cross-language differences affect the learning-to-read process in different languages and to investigate to what extent similar deficits will produce similar or different manifestations of dyslexia in different languages.
The role of astroglia-neuron interactions in generation and spread of seizures
Astroglia-neuron interactions are involved in multiple processes, regulating development, excitability and connectivity of neural circuits. Accumulating number of evidences highlight a direct connection between aberrant astroglial genetics and physiology in various forms of epilepsies. Using zebrafish seizure models, we showed that neurons and astroglia follow different spatiotemporal dynamics during transitions from pre-ictal to ictal activity. We observed that during pre-ictal period neurons exhibit local synchrony and low level of activity, whereas astroglia exhibit global synchrony and high-level of calcium signals that are anti correlated with neural activity. Instead, generalized seizures are marked by a massive release of astroglial glutamate release as well as a drastic increase of astroglia and neuronal activity and synchrony across the entire brain. Knocking out astroglial glutamate transporters leads to recurrent spontaneous generalized seizures accompanied with massive astroglial glutamate release. We are currently using a combination of genetic and pharmacological approaches to perturb astroglial glutamate signalling and astroglial gap junctions to further investigate their role in generation and spreading of epileptic seizures across the brain.
Dynamic structural neuroplasticity in the bilingual brain
Research on the effects of bilingualism on the structure of the brain has so far yielded variable patterns. Although it cannot be disputed that learning and using additional languages restructures the brain, the reported effects vary considerably, including both increases and reductions in grey matter volume and white matter diffusivity. This presentation reviews the available evidence and compares it to patterns from other domains of skill acquisition, culminating in the Dynamic Restructuring Model, a theory which synthesises the available evidence from the perspective of experience-based neuroplasticity. New corroborating evidence is also presented from healthy young and older bilinguals, and the presentation concludes with the implications of these effects for the ageing brain.
Separable pupillary signatures of perception and action during perceptual multistability
The pupil provides a rich, non-invasive measure of the neural bases of perception and cognition, and has been of particular value in uncovering the role of arousal-linked neuromodulation, which alters cortical processing as well as pupil size. But pupil size is subject to a multitude of influences, which complicates unique interpretation. We measured pupils of observers experiencing perceptual multistability -- an ever-changing subjective percept in the face of unchanging but inconclusive sensory input. In separate conditions the endogenously generated perceptual changes were either task-relevant or not, allowing a separation between perception-related and task-related pupil signals. Perceptual changes were marked by a complex pupil response that could be decomposed into two components: a dilation tied to task execution and plausibly indicative of an arousal-linked noradrenaline surge, and an overlapping constriction tied to the perceptual transient and plausibly a marker of altered visual cortical representation. Constriction, but not dilation, amplitude systematically depended on the time interval between perceptual changes, possibly providing an overt index of neural adaptation. These results show that the pupil provides a simultaneous reading on interacting but dissociable neural processes during perceptual multistability, and suggest that arousal-linked neuromodulation shapes action but not perception in these circumstances. This presentation covers work that was published in e-life
Towards a More Authentic Vision of the (multi)Coding Potential of RNA
Ten of thousands of open reading frames (ORFs) are hidden within transcripts. They have eluded annotations because they are either small or within unsuspected locations. These are named alternative ORFs (altORFs) or small ORFs and have recently been highlighted by innovative proteogenomic approaches, such as our OpenProt resource, revealing their existence and implications in biological functions. Due to the absence of altORFs from annotations, pathogenic mutations within these are being ignored. I will discuss our latest progress on the re-analysis of large-scale proteomics datasets to improve our knowledge of proteomic diversity, and the functional characterization of a second protein coded by the FUS gene. Finally, I will explain the need to map the coding potential of the transcriptome using artificial intelligence rather than with conventional annotations that do not capture the full translational activity of ribosomes.
“Mind reading” with brain scanners: Facts versus science fiction
Every thought is associated with a unique pattern of brain activity. Thus, in principle, it should be possible to use these activity patterns as "brain fingerprints" for different thoughts and to read out what a person is thinking based on their brain activity alone. Indeed, using machine learning considerable progress has been made in such "brainreading" in recent years. It is now possible to decode which image a person is viewing, which film sequence they are watching, which emotional state they are in or which intentions they hold in mind. This talk will provide an overview of the current state of the art in brain reading. It will also highlight the main challenges and limitations of this research field. For example, mathematical models are needed to cope with the high dimensionality of potential mental states. Furthermore, the ethical concerns raised by (often premature) commercial applications of brain reading will also be discussed.
Migraine: a disorder of excitatory-inhibitory balance in multiple brain networks? Insights from genetic mouse models of the disease
Migraine is much more than an episodic headache. It is a complex brain disorder, characterized by a global dysfunction in multisensory information processing and integration. In a third of patients, the headache is preceded by transient sensory disturbances (aura), whose neurophysiological correlate is cortical spreading depression (CSD). The molecular, cellular and circuit mechanisms of the primary brain dysfunctions that underlie migraine onset, susceptibility to CSD and altered sensory processing remain largely unknown and are major open issues in the neurobiology of migraine. Genetic mouse models of a rare monogenic form of migraine with aura provide a unique experimental system to tackle these key unanswered questions. I will describe the functional alterations we have uncovered in the cerebral cortex of genetic mouse models and discuss the insights into the cellular and circuit mechanisms of migraine obtained from these findings.
Migraine Headache: the revolution and its evolution
This seminar will focus on the extraordinary shift in migraine research during the last 4 decades with the discovery of the trigeminovascular system (TVS) and it’s major impact on pathophysiology and treatment. Compelling evidence supporting the importance of TVS, cortical spreading depression and parameningeal inflammation will be explored as will the implications of newly discovered microvascular channels within the meninges on an attack.
Communicating (Neuro)Science
In recent years, communicating one’s research to audiences outside of academia has grown in importance and time commitment for many researchers. Science Slams or University Open Days reliably draw large crowds, and the potential of social media to amplify any message has made it possible to reach interested recipients without the traditional press as a middleman. In this presentation, I will provide insights into science communication from my perspective as a neuroscience researcher, who enjoys spreading the word about how amazing insect brains are. We will have a look at the What?, Why? and How? of science communication. What do we generally mean by the term, and what forms can it take? Why should – or must – we engage in it? And how can we best achieve our aims with it? I will provide an overview of the current communication landscape, some food for (critical) thought, and many practical tips that help me when preparing to share my science with a wider audience.
Untitled Seminar
40 years of headache research
Lifelong devotion to headache research has led to many discoveries. First a series of studies of brain blood flow during attacks of migraine. The results showed changes compatible with cortical spreading depression in migraine without aura effectively negating the then prevailing vasospastic/ischemic theory. In migraine without aura no changes in brain blood flow. This difference was crucial for the separation of migraine with aura and migraine without aura in the first and subsequent editions of the international headache classification headed by me. Then a human migraine provocation model that has elucidated the molecular mechanisms of migraine. Successively we showed in series of papers the importance of nitric oxide, histamine, CGRP, PACAP and prostanoids. Therapeutic effectiveness of antagonizing these provokers by tonabersat, L-NMMA, CGRP receptor antagonists and monoclonal antibodies and of NSAIDs. Present and future attempts to put all these signaling mechanisms into a framework but it is not easy
Spreading dynamics and homeostatic regulation in neural networks
Reading out responses of large neural population with minimal information loss
Classic studies show that in many species – from leech and cricket to primate – responses of neural populations can be quite successfully read out using a measure neural population activity termed the population vector. However, despite its successes, detailed analyses have shown that the standard population vector discards substantial amounts of information contained in the responses of a neural population, and so is unlikely to accurately describe how signal communication between parts of the nervous system. I will describe recent theoretical results showing how to modify the population vector expression in order to read out neural responses without information loss, ideally. These results make it possible to quantify the contribution of weakly tuned neurons to perception. I will also discuss numerical methods that can be used to minimize information loss when reading out responses of large neural populations.
Surprising generalizations in the neural implementation of Hebrew and English word reading
Role of Tunneling Nanotubes (TNTs) in the spreading of amyloid proteins in neurodegenerative diseases
Blood is thicker than water
According to Hamilton’s inclusive fitness hypothesis, kinship is an organizing principle of social behavior. Behavioral evidence supporting this hypothesis includes the ability to recognize kin and the adjustment of behavior based on kin preference with respect to altruism, attachment and care for offspring in insect societies. Despite the fundamental importance of kinship behavior, the underlying neural mechanisms are poorly understood. We repeated behavioral experiments by Hepper on behavioral preference of rats for their kin. Consistent with Hepper’s work, we find a developmental time course for kinship behavior, where rats prefer sibling interactions at young ages and express non-sibling preferences at older ages. In probing the brain areas responsible for this behavior, we find that aspiration lesions of the lateral septum but not control lesions of cingulate cortices eliminate the behavioral preference in young animals for their siblings and in older rats for non-siblings. We then presented awake and anaesthetized rats with odors and calls of age- and status-matched kin (siblings and mothers) and non-kin (non-siblings and non-mothers) conspecifics, while performing in vivo juxta-cellular and whole-cell patch-clamp recordings in the lateral septum. We find multisensory (olfactory and auditory) neuronal responses, whereby neurons typically responded preferentially but not exclusively to individual social stimuli. Non-kin-odor responsive neurons were found dorsally, while kin-odor responsive neurons were located in ventrally in the lateral septum. To our knowledge such an ordered representation of response preferences according to kinship has not been previously observed and we refer this organization as nepotopy. Nepotopy could be instrumental in reading out kinship from preferential but not exclusive responses and in the generation of differential behavior according to kinship. Thus, our results are consistent with a role of the lateral septum in organizing mammalian kinship behavior.
When spontaneous waves meet angiogenesis: a case study from the neonatal retina
By continuously producing electrical signals, neurones are amongst the most energy-demanding cells in the organism. Resting ionic levels are restored via metabolic pumps that receive the necessary energy from oxygen supplied by blood vessels. Intense spontaneous neural activity is omnipresent in the developing CNS. It occurs during short, well-defined periods that coincide precisely with the timing of angiogenesis. Such coincidence cannot be random; there must be a universal mechanism triggering spontaneous activity concurrently with blood vessels invading neural territories for the first time. However, surprisingly little is known about the role of neural activity per se in guiding angiogenesis. Part of the reason is that it is challenging to study developing neurovascular networks in tri-dimensional space in the brain. We investigate these questions in the neonatal mouse retina, where blood vessels are much easier to visualise because they initially grow in a plane, while waves of spontaneous neural activity (spreading via cholinergic starburst amacrine cells) sweep across the retinal ganglion cell layer, in close juxtaposition with the growing vasculature. Blood vessels reach the periphery by postnatal day (P) 7-8, shortly before the cholinergic waves disappear (at P10). We discovered transient clusters of auto-fluorescent cells that form an annulus around the optic disc, gradually expanding to the periphery, which they reach at the same time as the growing blood vessels. Remarkably, these cells appear locked to the frontline of the growing vasculature. Moreover, by recording waves with a large-scale multielectrode array that enables us to visualise them at pan-retinal level, we found that their initiation points are not random; they follow a developmental centre-to-periphery pattern similar to the clusters and blood vessels. The density of growing blood vessels is higher in cluster areas than in-between clusters at matching eccentricity. The cluster cells appear to be phagocytosed by microglia. Blocking Pannexin1 (PANX1) hemichannels activity with probenecid completely blocks the spontaneous waves and results in the disappearance of the fluorescent cell clusters. We suggest that these transient cells are specialised, hyperactive neurones that form spontaneous activity hotspots, thereby triggering retinal waves through the release of ATP via PANX1 hemichannels. These activity hotspots attract new blood vessels to enhance local oxygen supply. Signalling through PANX1 attracts microglia that establish contact with these cells, eventually eliminating them once blood vessels have reached their vicinity. The auto-fluorescence that characterises the cell clusters may develop only once the process of microglial phagocytosis is initiated.
Sparks, flames, and inferno: epileptogenesis in the glioblastoma microenvironment
Glioblastoma cells trigger pharmacoresistant seizures that may promote tumor growth and diminish the quality of remaining life. To define the relationship between growth of glial tumors and their neuronal microenvironment, and to identify genomic biomarkers and mechanisms that may point to better prognosis and treatment of drug resistant epilepsy in brain cancer, we are analyzing a new generation of genetically defined CRISPR/in utero electroporation inborn glioblastoma (GBM) tumor models engineered in mice. The molecular pathophysiology of glioblastoma cells and surrounding neurons and untransformed astrocytes are compared at serial stages of tumor development. Initial studies reveal that epileptiform EEG spiking is a very early and reliable preclinical signature of GBM expansion in these mice, followed by rapidly progressive seizures and death within weeks. FACS-sorted transcriptomic analysis of cortical astrocytes reveals the expansion of a subgroup enriched in pro-synaptogenic genes that may drive hyperexcitability, a novel mechanism of epileptogenesis. Using a prototypical GBM IUE model, we systematically define and correlate the earliest appearance of cortical hyperexcitability with progressive cortical tumor cell invasion, including spontaneous episodes of spreading cortical depolarization, innate inflammation, and xCT upregulation in the peritumoral microenvironment. Blocking this glutamate exporter reduces seizure load. We show that the host genome contributes to seizure risk by generating tumors in a monogenic deletion strain (MapT/tau -/-) that raises cortical seizure threshold. We also show that the tumor variant profile determines epilepsy risk. Our genetic dissection approach sets the stage to broadly explore the developmental biology of personalized tumor/host interactions in mice engineered with novel human tumor mutations in specified glial cell lineages.
Analogy in Cognitive Architecture
Cognitive architectures are attempts to build larger-scale models of minds. This talk will explore how structure-mapping models of analogical matching, retrieval, and generalization are used in the Companion cognitive architecture. Examples will include modeling conceptual change, learning by reading, and analogical Q/A training.
Does spreading depression rewire cortical pain networks?
FENS Forum 2024
Fragmentation and multithreading of consciousness in the default-mode network
FENS Forum 2024
Investigating the impact of seizure-associated spreading depolarisation to postictal depression and loss of arousal in a novel model of temporal lobe epilepsy
FENS Forum 2024
Ketamine prevents the inverse haemodynamic response to spreading depolarization in ischaemic cortical tissue
FENS Forum 2024
Mechanisms of facilitation of cortical spreading depression in a genetic mouse model of migraine with a gain-of-function mutation in CaV2.1 channels
FENS Forum 2024
Tau spreading in Alzheimer’s disease models is facilitated by the amyloid-β precursor protein
FENS Forum 2024
Spreading depolarization disrupts neurovascular coupling after experimental acute ischemic stroke
FENS Forum 2024
reading coverage
38 items