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Neuroscience Talks in Cambridge

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A superlist combining individual seminars and series from other lists on talks.cam. These Neuroscience-themed seminars will be advertised throughout the relevant interest group in Cambridge.
URL: http://talks.cam.ac.uk/show/index/6028
Updated: 14 min 43 sec ago

Wed 13 Mar 11:30: Neural Sociometrics: Precision assessment of parent-child brain-behaviour interaction dynamics

Fri, 08/03/2024 - 16:58
Neural Sociometrics: Precision assessment of parent-child brain-behaviour interaction dynamics

During early life, healthy neurodevelopment depends on warm, responsive and closely-coordinated social interactions between infants and caregivers. These rich multidimensional experiences act through multiple sensory and motor pathways to orchestrate healthy maturation of the neonatal brain, mind and body. Conversely, adverse early life experiences (including abuse or neglect) seed vulnerabilities for poor cognition and emotional instability throughout the lifespan. Despite the pivotal role played by caregiver interactions during early development, we still lack precision tools and models that can accurately and comprehensively capture the complex dynamics within the child’s “interactome”. Here, I will discuss neural sociometrics – real-time multi-sensor high-dimensional imaging of adult-infant dyadic social interactive behaviour and neurophysiology – as a deep phenotyping tool for early screening and precision intervention. Early risk identification and mitigation, paired with precision therapeutics, could fundamentally alter a child’s development trajectory toward lifelong mental wellbeing and productivity.

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Wed 06 Mar 15:00: Student Spotlight: Yan Xia, James Ackland, and Nikolay Petrov

Mon, 04/03/2024 - 13:38
Student Spotlight: Yan Xia, James Ackland, and Nikolay Petrov

This talk is open to the general public.

Meeting ID: 329 287 585 675

Passcode: yKwfhf

Yan Xia (Aalto University):

Title: Integrated or Segregated? User Behavior Change after Cross-Party Interactions on Reddit

Abstract: It is a widely shared concern that social media reinforces echo chambers of like-minded users and exacerbates political polarization. While fostering interactions across party lines is recognized as an important strategy to break echo chambers, there is a lack of empirical evidence on whether users will actually become more integrated or instead more segregated following such interactions on real social media platforms. We fill this gap by inspecting how users change their community participation after receiving a cross-party reply in the U.S. politics discussion on Reddit. More specifically, we investigate if their participation increases in communities of the opposing party, or in communities of their own party. We find that receiving a reply is significantly associated with increased user activity in both types of communities; when the reply is a cross-party one, the activity boost in cross-party communities is weaker. Nevertheless, compared with the case of receiving no reply, users are still significantly more likely to increase their participation in cross-party communities after receiving a cross-party reply. Our results therefore hint at a depolarization effect of cross-party interactions that better integrate users into discussions of the opposing side.

James Ackland (Cambridge):

Title: The Geographical Psychology of Ideological Misalignment

Abstract: Political psychologists have debated whether ideology is constructed from the top-down, by national-level parties and elites forming packages of beliefs to “sell” to voters (Downs, 1957); or from the bottom-up, by voters themselves aligning policy preferences with more fundamental social and psychological needs (Duckitt & Sibley, 2010). In this work, I assume that both processes coexist, and show how their interaction can explain some of the phenomena that characterise our modern politics. Of particular interest are places where bottom-up preferences are not matched by the top-down political offering. In Western Europe, this often means places where social conservatism exists alongside left-leaning economic preferences, in contrast to the pairing of social conservatism with a free-market ideology at the national level. In such places, I hypothesise that populist politics will be more successful, as measured by voting behaviour and political attitudes.

Nikolay Petrov (Cambridge):

Title: Limited ability of LLMs to simulate human psychological behaviours: an in-depth psychometric analysis

Abstract: The humanlike responses of Large Language Models (LLMs) have prompted social scientists to investigate whether LLMs can be used to simulate human participants in experiments, opinion polls and surveys. Of central interest in this line of research has been mapping out the psychological profile of LLMs by prompting them to respond to standardized questionnaires. The conflicting findings of this research are unsurprising given that going from LLMs’ text responses on surveys to mapping out underlying, or latent, traits is no easy task. To address this, we use psychometrics, the science of psychological measurement. In this study, we prompt OpenAI’s flagship models, GPT -3.5 and GPT -4, by asking them to assume different personas and respond to a range of standardized measures of personality constructs. We used two kinds of persona descriptions: either generic (5 random person descriptions) or specific (mostly demographics of actual humans from a large-scale human dataset). We found that using generic persona descriptions, more powerful models, such as GPT -4, show promising abilities to respond coherently, and similar to human norms, but both models failed miserably in assuming specific personas, described using demographic variables. We conclude that, currently, when LLMs are prompted to simulate specific human(s), they cannot represent latent traits and thus their responses fail to generalize across tasks.

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Thu 14 Mar 16:00: Epigenetic priming of embryonic cell lineages in the mammalian epiblast

Mon, 04/03/2024 - 13:23
Epigenetic priming of embryonic cell lineages in the mammalian epiblast

Miguel Torres trained in Drosophila Genetics during his PhD (1991) with Dr. Lucas Sánchez (CIB-CSIC, Madrid) and later in Mouse Developmental Genetics during his Postdoc at the MPI with Dr Peter Gruss. He established an independent research group at the National Center for Biotechnology, CSIC , Madrid in 1996 and moved in 2007 to CNIC where he now coordinates the Cardiovascular Regeneration Program. His group has a strong focus on understanding organ development and regeneration. Dr Torres group characterized the role of homeobox genes and signaling pathways in establishing positional information along the limb proximo-distal axis during development and regeneration. A second topic of interest has been understanding the role of cell death in embryonic development. The group demonstrated the conservation of cell death pathways in metazoan evolution and demonstrated the relevance of cell death and cell competition in mammalian tissue homeostasis and regeneration. The group has also developed clonal analysis strategies and live imaging tools that allowed defining new lineage relationships and tissue dynamics in limb and cardiovascular development.

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Wed 24 Apr 15:00: Title to be confirmed

Fri, 01/03/2024 - 16:34
Title to be confirmed

Abstract not available

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Wed 29 May 15:00: Cambridge Overcoming Polarisation Initiative

Fri, 01/03/2024 - 16:33
Cambridge Overcoming Polarisation Initiative

Abstract not available

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Mon 04 Mar 16:15: Estradiol feedback on the reproductive neuroendocrine system

Fri, 01/03/2024 - 15:50
Estradiol feedback on the reproductive neuroendocrine system

Abstract not available

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Mon 22 Apr 12:30: Handling missingness in cognitive variables using multiple imputation

Thu, 29/02/2024 - 15:31
Handling missingness in cognitive variables using multiple imputation

Speaker: Peter Watson (MRC CBU , Cambridge)

Bio: Peter Watson has been providing statistical support in various ways to the research at the MRC CBU since 1994, and before that fulfilling a similar role at the MRC Age and Cognitive Performance Research Centre in Manchester. He has also been secretary, since 1996, of the Cambridge Statistics Discussion Group and chair and meetings organiser for the SPSS users group (ASSESS) since 2001.

Title: Handling missingness in cognitive variables using multiple imputation

Abstract: Missing data is a common feature of many clinical studies. In this talk I show how we handled this using multiple imputation in a health and wellbeing study and reported the results. In particular, multiple imputation is more robust when there are large amounts of missingness as it takes sampling variables into account.

Venue: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09

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Thu 07 Mar 14:00: “Atomic pathology of neurodegenerative diseases by cryo-EM of amyloid filaments” TIME CHANGE Please note this talk is from 2pm to 3pm

Thu, 29/02/2024 - 14:35
“Atomic pathology of neurodegenerative diseases by cryo-EM of amyloid filaments”

Abstract not available

TIME CHANGE Please note this talk is from 2pm to 3pm

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Wed 06 Mar 16:00: ***CANCELLED*** Twenty years of sex influences on the brain: Some perspective on where we were, where we are, and where we are going

Wed, 28/02/2024 - 11:19
***CANCELLED*** Twenty years of sex influences on the brain: Some perspective on where we were, where we are, and where we are going

Please note that this talk has been cancelled and we are looking to reschedule.

*

About 20 years ago my research into brain mechanisms of emotional memory drew me into an issue about which I previously had zero interest: Sex influences on brain function. As I started to recognize the issue’s enormous importance, I switched my laboratory focus towards exploring, rather than ignoring, the issue. I also began more general efforts to help neuroscience move past its biases (all of which I had shared) and recognize that ignoring the issue, while perhaps once defensible, is no longer, and what is more, that ignoring the issue must disproportionately harm women. Twenty years later the biases against the issue remain strong among many, yet the situation has also changed irreversibly for the better. As I like to put it, neuroscience has turned a corner that cannot be unturned. I will try to capture where neuroscience was on the issue (and how it got there), where it seems to be today, and why I believe the issue is here to stay.

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Thu 07 Mar 12:00: Title to be confirmed

Mon, 26/02/2024 - 10:40
Title to be confirmed

Abstract not available

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Mon 18 Mar 12:30: Studies with Single Subjects or Large Numbers of Volunteers - Why, & How?

Mon, 26/02/2024 - 10:35
Studies with Single Subjects or Large Numbers of Volunteers - Why, & How?

Speaker: Wietske van der Zwaag (Spinoza Centre for Neuroimaging, Amsterdam)

Bio: Wietske van der Zwaag received her PhD in Physics and Astronomy from the University of Nottingham in the United Kingdom, in 2006, working with one of the first European 7T scanners. She subsequently worked at the Centre d’Imagerie Biomédicale (CIBM) at the Ecole Polytechnique Fédérale de Lausanne (EPFL) from 2007 to 2015. Van der Zwaag joined the Spinoza Centre, in 2015, shortly after its opening. In 2019, she formed her own group there, working at the boundary between MR development and neurosciences. The group’s research is centred on best harnessing the strong points of 7T in neuroimaging with a special interest in functional MRI of finely organized brain structures, such as the human cerebellum.

Title: Studies with Single Subjects or Large Numbers of Volunteers – Why, & How?

Abstract: In the functional MRI field, datasets continue to grow. Interestingly, there are two different trends: There are currently multiple efforts towards collection of datasets with a huge number of participants, to capture the variance in a population, or to use the power of massive averaging to discover subtle brain function patterns. A second trend is towards exhaustive sampling of a single participant (or a few), arguing that measurements of one brain likely generalize to most other brains. Dense sampling allows experiments with either many conditions or extremely detailed images, exploring different types of variance. This talk will discuss both trends.

Venue: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09

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Thu 29 Feb 12:00: “Biomarkers for Alzheimer’s disease in clinical routine - a pretty Swedish perspective” The talk is in-person only and a recording is not available.

Mon, 26/02/2024 - 10:35
“Biomarkers for Alzheimer’s disease in clinical routine - a pretty Swedish perspective”

Abstract not available

The talk is in-person only and a recording is not available.

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Mon 15 Apr 12:30: fMRI vs. Electrophysiology in Humans

Mon, 26/02/2024 - 10:27
fMRI vs. Electrophysiology in Humans

Speaker: Prof. Patricia Figueiredo (Institute for Systems and Robotics, Lisbon)

Bio: Professor Patrícia Figueiredo is a biomedical engineer focusing on noninvasive imaging of human brain function. She leverages MRI and EEG to explore brain function in both healthy individuals and patients with neurological and psychiatric disorders. She obtained her DPhil degree in Neuroimaging from the University of Oxford in 2003 and currently is a Principal Investigator of the Evolutionary Systems and Biomedical Engineering Lab (LaSEEB) at the Institute for Systems and Robotics of the University of Lisbon. Figueiredo’s notable contributions have been recognized with several awards, including the Prize for Women in Science by L’Oréal Portugal.

Title: fMRI vs. Electrophysiology in Humans

Abstract: Because BOLD -fMRI probes neuronal activity indirectly and with a lag of a few seconds, based on neurovascular coupling mechanisms, several studies have attempted to clarify its neuronal correlates in humans by combining it with the simultaneous recording of the electroencephalogram (EEG). Like other electrophysiology techniques, EEG provides direct measures of neuronal activity with sub-millisecond temporal resolution, albeit poorer spatial resolution and coverage than BOLD -fMRI. In this talk, I will overview the main characteristics of electrophysiology relative to BOLD -fMRI as well as the evidence contributed by EEG -fMRI studies towards our understanding of the neuronal correlates of different types of BOLD -fMRI measurements.

Venue: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09

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Mon 03 Jun 12:30: Advances in fMRI Data Acquisition Techniques

Mon, 26/02/2024 - 10:23
Advances in fMRI Data Acquisition Techniques

Abstract not available

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Tue 27 Feb 15:00: Computational Neuroscience Journal Club

Sun, 25/02/2024 - 21:32
Computational Neuroscience Journal Club

Please join us for our Computational Neuroscience journal club on Tuesday 27th February at 3pm UK time in the CBL seminar room

The title is “Alternatives to Backpropagation”, presented by Youjing Yu and Guillaume Hennequin.

Summary:

Backpropagation is one of the most widely-used algorithms for training neural networks. However, despite its popularity, there are several arguments against the use of backpropagation, one of the most important being its biological implausibility. In this journal club meeting, we are going to take a look at some alternatives developed to backpropagation.

We start by digesting the Forward-Forward algorithm proposed by Geoffrey Hinton [1]. Instead of running one forward pass through the network followed by one backward pass as in backpropagation, the Forward-Forward algorithm utilises two forward passes, one with positive, real data and another with negative, fake data. Each layer in the network has its own objective function, which is to generate high “goodness” for positive data and low “goodness” for negative data. We will dive into the working principles of the algorithm, its effectiveness on small problems and the associated limitations.

Next, we will present another cool idea that has been independently re-discovered by several labs, and was perhaps most cleanly articulated in Meulemans et al., NeurIPS 2022. This idea phrases learning as a least-control problem: a feedback control loop is set up that continuously keeps the learning system (e.g. neural network) in a state of minimum loss, and learning becomes the problem of progressively doing away with controls. As it turns out, gradient information is available in the control signals themselves, such that learning becomes local. We will give a general introduction and history of this idea, and look into Meulemans et al. in some detail.

[1] Hinton, Geoffrey. “The forward-forward algorithm: Some preliminary investigations.” arXiv preprint arXiv:2212.13345 (2022). [2] Meulemans, Alexander, et al. “The least-control principle for local learning at equilibrium.” Advances in Neural Information Processing Systems 35 (2022): 33603-33617.

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Tue 27 Feb 15:00: Title to be confirmed

Sun, 25/02/2024 - 21:31
Title to be confirmed

Please join us for our Computational Neuroscience journal club on Tuesday 27th February at 3pm UK time in the CBL seminar room

The title is “Alternatives to Backpropagation”, presented by Youjing Yu and Guillaume Hennequin.

Summary:

Backpropagation is one of the most widely-used algorithms for training neural networks. However, despite its popularity, there are several arguments against the use of backpropagation, one of the most important being its biological implausibility. In this journal club meeting, we are going to take a look at some alternatives developed to backpropagation.

We start by digesting the Forward-Forward algorithm proposed by Geoffrey Hinton [1]. Instead of running one forward pass through the network followed by one backward pass as in backpropagation, the Forward-Forward algorithm utilises two forward passes, one with positive, real data and another with negative, fake data. Each layer in the network has its own objective function, which is to generate high “goodness” for positive data and low “goodness” for negative data. We will dive into the working principles of the algorithm, its effectiveness on small problems and the associated limitations.

Next, we will present another cool idea that has been independently re-discovered by several labs, and was perhaps most cleanly articulated in Meulemans et al., NeurIPS 2022. This idea phrases learning as a least-control problem: a feedback control loop is set up that continuously keeps the learning system (e.g. neural network) in a state of minimum loss, and learning becomes the problem of progressively doing away with controls. As it turns out, gradient information is available in the control signals themselves, such that learning becomes local. We will give a general introduction and history of this idea, and look into Meulemans et al. in some detail.

[1] Hinton, Geoffrey. “The forward-forward algorithm: Some preliminary investigations.” arXiv preprint arXiv:2212.13345 (2022). [2] Meulemans, Alexander, et al. “The least-control principle for local learning at equilibrium.” Advances in Neural Information Processing Systems 35 (2022): 33603-33617.

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Thu 22 Feb 15:30: Exploring microcircuit properties for memory, from rodents to the human brain

Wed, 21/02/2024 - 14:28
Exploring microcircuit properties for memory, from rodents to the human brain

Human brain function arises from a continuous activity flowing through specific cells, guided by intricate synaptic arrangements. Therefore, determining the architecture and properties of functioning microcircuits is crucial for understanding the complexities of brain function. However, our current microcircuit knowledge is limited, and for the human brain – almost non-existent. I will present our recent findings using a combination of multicellular patch-clamp-based circuit analysis and super-resolution imaging to elucidate the microcircuit architecture of the hippocampus, a critical brain region for memory. Studying the rodent brain at the individual cell level reveals distinct cell populations with unique properties and interconnectivity, which significantly enhance the computational capabilities. Furthermore, I will discuss how we apply these techniques to the human brain, exploring the black box of our own wiring, which reveals new insights into the circuit basis of memory storage.

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Fri 17 May 16:30: Language, Mind and Brain The host for this talk is Jeff Dalley

Wed, 21/02/2024 - 11:02
Language, Mind and Brain

Abstract not available

The host for this talk is Jeff Dalley

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Wed 21 Feb 14:00: Computational Neuroscience Journal Club

Tue, 20/02/2024 - 02:29
Computational Neuroscience Journal Club

Please join us for our Computational Neuroscience journal club on Wednesday 21st February at 2pm UK time in the CBL seminar roo

The title is “Meta Reinforcement Learning”, presented by Luke Johnston and Theoklitos Amvrosiadis.

Summary:

Following on from last week’s journal club on distributional reinforcement learning, this week we examine another widely discussed topic within RL - that of meta reinforcement learning. Meta RL has long been of interest to neuroscientists for the extent to which it better reflects the macroscopic behaviour of animals, where the ability to generalise learning experiences across contexts (ie ‘learning to learn’) forms a vital part of higher-order cognition. However unlike traditional single task learning – where, for example, the mechanisms of classical conditioning are well characterised – the neural basis of meta-learning remains a source of debate.

We begin by taking a look back at the seminal 2018 paper from Botvinick et al. [1], which proposes meta learning to occur within a ‘prefrontal network’ centred largely in the PFC . Specifically, the authors postulate a two-part meta RL system that includes initial dopamine based learning by way of the classical cortico–basal ganglia–thalamo–cortical loop to shape the recurrent connectivity of the PFC network, followed by a second PFC -centred algorithm which is dynamically tailored to the task at hand.

In the second part of the journal club, we will look at a recent paper from the Komiyama lab [2], in which through 2-photon calcium imaging experiments in mice and computational models, the researchers argue that synaptic plasticity within orbitofrontal cortex (OFC) is necessary for learning across sessions, but not for within-session learning in already trained subjects.

[1] Wang, J. X., Kurth-Nelson, Z., Kumaran, D., Tirumala, D., Soyer, H., Leibo, J. Z., ...Botvinick, M. (2018). Prefrontal cortex as a meta-reinforcement learning system. Nat. Neurosci., 21, 860–868. doi: 10.1038/s41593-018-0147-8 [2] Hattori, R., Hedrick, N.G., Jain, A. et al. Meta-reinforcement learning via orbitofrontal cortex. Nat Neurosci 26, 2182–2191 (2023). https://doi.org/10.1038/s41593-023-01485-3 (

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Wed 24 Apr 15:00: Cambridge Overcoming Polarisation Initiative

Mon, 19/02/2024 - 14:55
Cambridge Overcoming Polarisation Initiative

Abstract not available

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Cambridge Memory Meeting 2015

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