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Memory Decoding Journal Club: Functional connectomics reveals general wiring rule in mouse visual cortex
Functional connectomics reveals general wiring rule in mouse visual cortex
Memory Decoding Journal Club: "Connectomic traces of Hebbian plasticity in the entorhinalhippocampal system
Connectomic traces of Hebbian plasticity in the entorhinalhippocampal system
Memory Decoding Journal Club: Distinct synaptic plasticity rules operate across dendritic compartments in vivo during learning
Distinct synaptic plasticity rules operate across dendritic compartments in vivo during learning
Memory Decoding Journal Club: A combinatorial neural code for long-term motor memory
A combinatorial neural code for long-term motor memory
Memory Decoding Journal Club: Behavioral time scale synaptic plasticity underlies CA1 place fields
Behavioral time scale synaptic plasticity underlies CA1 place fields
Memory Decoding Journal Club: "Connectomic reconstruction of a cortical column" cortical column
Connectomic reconstruction of a cortical column
Memory Decoding Journal Club: "Binary and analog variation of synapses between cortical pyramidal neurons
Binary and analog variation of synapses between cortical pyramidal neurons
Memory Decoding Journal Club: Systems consolidation reorganizes hippocampal engram circuitry
Systems consolidation reorganizes hippocampal engram circuitry
Memory Decoding Journal Club: Neocortical synaptic engrams for remote contextual memories
Neocortical synaptic engrams for remote contextual memories
Memory Decoding Journal Club: "Structure and function of the hippocampal CA3 module
Structure and function of the hippocampal CA3 module
Memory Decoding Journal Club: "Synaptic architecture of a memory engram in the mouse hippocampus
Synaptic architecture of a memory engram in the mouse hippocampus
Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons
Join Us for the Memory Decoding Journal Club! A collaboration of the Carboncopies Foundation and BPF Aspirational Neuroscience. This time, we’re diving into a groundbreaking paper: "Motor learning selectively strengthens cortical and striatal synapses of motor engram neurons
Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala
Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala. This study by Marios Abatis et al. demonstrates how fear conditioning strengthens synaptic connections between engram cells in the lateral amygdala, revealed through optogenetic identification of neuronal ensembles and electrophysiological measurements. The work provides crucial insights into memory formation mechanisms at the synaptic level, with implications for understanding anxiety disorders and developing targeted interventions. Presented by Dr. Kenneth Hayworth, this journal club will explore the paper's methodology linking engram cell reactivation with synaptic plasticity measurements, and discuss implications for memory decoding research.
Memory Decoding Journal Club: Reconstructing a new hippocampal engram for systems reconsolidation and remote memory updating
Join us for the Memory Decoding Journal Club, a collaboration between the Carboncopies Foundation and BPF Aspirational Neuroscience. This month, we're diving into a groundbreaking paper: 'Reconstructing a new hippocampal engram for systems reconsolidation and remote memory updating' by Bo Lei, Bilin Kang, Yuejun Hao, Haoyu Yang, Zihan Zhong, Zihan Zhai, and Yi Zhong from Tsinghua University, Beijing Academy of Artificial Intelligence, IDG/McGovern Institute of Brain Research, and Peking Union Medical College. Dr. Randal Koene will guide us through an engaging discussion on these exciting findings and their implications for neuroscience and memory research.
Bayesian expectation in the perception of the timing of stimulus sequences
In the current virtual journal club Dr Di Luca will present findings from a series of psychophysical investigations where he measured sensitivity and bias in the perception of the timing of stimuli. He will present how improved detection with longer sequences and biases in reporting isochrony can be accounted for by optimal statistical predictions. Among his findings was also that the timing of stimuli that occasionally deviate from a regularly paced sequence is perceptually distorted to appear more regular. Such change depends on whether the context these sequences are presented is also regular. Dr Di Luca will present a Bayesian model for the combination of dynamically updated expectations, in the form of a priori probability, with incoming sensory information. These findings contribute to the understanding of how the brain processes temporal information to shape perceptual experiences.
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
Event-related frequency adjustment (ERFA): A methodology for investigating neural entrainment
Neural entrainment has become a phenomenon of exceptional interest to neuroscience, given its involvement in rhythm perception, production, and overt synchronized behavior. Yet, traditional methods fail to quantify neural entrainment due to a misalignment with its fundamental definition (e.g., see Novembre and Iannetti, 2018; Rajandran and Schupp, 2019). The definition of entrainment assumes that endogenous oscillatory brain activity undergoes dynamic frequency adjustments to synchronize with environmental rhythms (Lakatos et al., 2019). Following this definition, we recently developed a method sensitive to this process. Our aim was to isolate from the electroencephalographic (EEG) signal an oscillatory component that is attuned to the frequency of a rhythmic stimulation, hypothesizing that the oscillation would adaptively speed up and slow down to achieve stable synchronization over time. To induce and measure these adaptive changes in a controlled fashion, we developed the event-related frequency adjustment (ERFA) paradigm (Rosso et al., 2023). A total of twenty healthy participants took part in our study. They were instructed to tap their finger synchronously with an isochronous auditory metronome, which was unpredictably perturbed by phase-shifts and tempo-changes in both positive and negative directions across different experimental conditions. EEG was recorded during the task, and ERFA responses were quantified as changes in instantaneous frequency of the entrained component. Our results indicate that ERFAs track the stimulus dynamics in accordance with the perturbation type and direction, preferentially for a sensorimotor component. The clear and consistent patterns confirm that our method is sensitive to the process of frequency adjustment that defines neural entrainment. In this Virtual Journal Club, the discussion of our findings will be complemented by methodological insights beneficial to researchers in the fields of rhythm perception and production, as well as timing in general. We discuss the dos and don’ts of using instantaneous frequency to quantify oscillatory dynamics, the advantages of adopting a multivariate approach to source separation, the robustness against the confounder of responses evoked by periodic stimulation, and provide an overview of domains and concrete examples where the methodological framework can be applied.
NII Methods (journal club): NeuroQuery, comprehensive meta-analysis of human brain mapping
We will discuss a recent paper by Taylor et al. (2023): https://www.sciencedirect.com/science/article/pii/S1053811923002896. They discuss the merits of highlighting results instead of hiding them; that is, clearly marking which voxels and clusters pass a given significance threshold, but still highlighting sub-threshold results, with opacity proportional to the strength of the effect. They use this to illustrate how there in fact may be more agreement between researchers than previously thought, using the NARPS dataset as an example. By adopting a continuous, "highlighted" approach, it becomes clear that the majority of effects are in the same location and that the effect size is in the same direction, compared to an approach that only permits rejecting or not rejecting the null hypothesis. We will also talk about the implications of this approach for creating figures, detecting artifacts, and aiding reproducibility.
BrainLM Journal Club
Connor Lane will lead a journal club on the recent BrainLM preprint, a foundation model for fMRI trained using self-supervised masked autoencoder training. Preprint: https://www.biorxiv.org/content/10.1101/2023.09.12.557460v1 Tweeprint: https://twitter.com/david_van_dijk/status/1702336882301112631?t=Q2-U92-BpJUBh9C35iUbUA&s=19
NII Methods (journal club): NeuroQuery, comprehensive meta-analysis of human brain mapping
We will discuss this paper on Neuroquery, a relatively new web-based meta-analysis tool: https://elifesciences.org/articles/53385.pdf. This is different from Neurosynth in that it generates meta-analysis maps using predictive modeling from the string of text provided at the prompt, instead of performing inferential statistics to calculate the overlap of activation from different studies. This allows the user to generate predictive maps for more nuanced cognitive processes - especially for clinical populations which may be underrepresented in the literature compared to controls - and can be useful in generating predictions about where the activity will be for one's own study, and for creating ROIs.
Algonauts 2023 winning paper journal club (fMRI encoding models)
Algonauts 2023 was a challenge to create the best model that predicts fMRI brain activity given a seen image. Huze team dominated the competition and released a preprint detailing their process. This journal club meeting will involve open discussion of the paper with Q/A with Huze. Paper: https://arxiv.org/pdf/2308.01175.pdf Related paper also from Huze that we can discuss: https://arxiv.org/pdf/2307.14021.pdf
1.8 billion regressions to predict fMRI (journal club)
Public journal club where this week Mihir will present on the 1.8 billion regressions paper (https://www.biorxiv.org/content/10.1101/2022.03.28.485868v2), where the authors use hundreds of pretrained model embeddings to best predict fMRI activity.
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Untitled Seminar
Neuroccino is a weekly journal club discussing the hot topics in neuroscience
Myelination: another form of brain plasticity
Studies of neural circuit plasticity focus almost exclusively on functional and structural changes of neuronal synapses. In recent years, however, myelin plasticity has emerged as a potential modulator of neuronal networks. Myelination of previously unmyelinated axons and changes in the structure on already-myelinated axons can have large effects on the function of neuronal networks. Yet myelination has been mostly studied in relation to its functional and metabolic activity. Myelin modifications are increasingly being implicated as a mechanism for sensory-motor learning and unpublished data from our lab indicate that myelination also occurs during cognitive non-motor learning. It is, however, unclear how specific these myelin changes are and even less is known of the underlying mechanisms of learning-evoked myelin plasticity. In this journal club, Dr Giulia Bonetto will provide a general overview on myelin plasticity. Additionally, she will present new data addressing the role of myelin plasticity in cognitive non-motor learning.
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