Seminar: Dr Naoya Takahashi

Dendritic mechanisms for somatosensory perception

Monday 10 June, 4pm at the Small Lecture Theatre, DPAG Sherrington Building, Oxford

 

The Cortex Club is excited to host Dr Naoya Takahashi from the Humbold University Berlin, who will be talking to us about his work on the role of cortical and subcortical pathways in perception. Please join us on June 10th, at the Small Lecture Theatre in the Sherrington Building of the Department of Physiology, Anatomy and Genetics, Parks Road, Oxford.

Dr Naoya Takahashi is happy to meet students and staff individually. If you would like to arrange a meeting please contact Tai-Ying Lee at tai-ying.lee [at] dpag.ox.ac.uk.

Please also join us at the pub after the talk, to which everybody is welcome. Register at https://forms.gle/UmRftpmXEE414vrm8

 

Abstract

The result of cortical processing is routed to different downstream targets via distinct pathways – broadly, cortico-cortical and cortico-subcortical. It is as yet unclear what roles these pathways play in perception, and what cellular and circuit mechanisms regulate their gating. I recently showed that activation of the apical dendrites of layer 5 (L5) pyramidal neurons correlates to the threshold for perception (Takahashi et al., 2016). Two distinct classes of L5 neurons target either other cortical areas or subcortical areas. I took advantage of two transgenic mouse lines to determine the relative contribution of these L5 subclasses to the perceptual process. I found that the activation of apical dendrites in neurons of the somatosensory cortex that project to subcortical regions almost exclusively determined the detection of whisker deflections in mice. Moreover, dendritic activation was strongly modulated by behavioral context. These results suggest that dendritic activation drives context-dependent interactions between cortex and subcortical regions that are crucial for perception. During the seminar, I will further discuss my long-term goal to develop a mechanistic understanding of how internal brain states, such as attention and expectation, modulate sensory processing to control perceptual behaviors.

Seminar: A/ Professor Denise Cai

Linking Memories Across Time

Friday 7 June, 4pm at the Sherrington Library, DPAG Sherrington Building, Oxford

 

The Cortex Club is delighted to host Assistant Professor Denise Cai from the Mount Sinai, New York,  who will be talking to us about her work on hippocampal networks link memories. Please join us on June 7th, at the Sherrington Library, located in the Sherrington Building of the Department of Physiology, Anatomy and Genetics, Parks Road, Oxford.

 

A/ Prof. Denise Cai has kindly agreed to meet students and staff individually. If you would like to arrange a meeting please contact Tai-Ying Lee at tai-ying.lee [at] dpag.ox.ac.uk.

Please also join us at the pub after the talk, to which everybody is welcome. Register at https://forms.gle/dx8aScGdEjHo25rb7

 

Abstract

The compilation of memories, collected and aggregated across a lifetime defines our human experience. My lab is interested in dissecting how memories are stored, updated, integrated and retrieved across a lifetime. Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. Using in vivo calcium imaging (with open-source Miniscopes in freely behaving mice), TetTag transgenic system, chemogenetics, electrophysiology and novel behavioral designs, we tested how hippocampal networks temporally link memories. Multiple convergent findings suggest that contextual memories encoded close in time are linked by directing storage into overlapping hippocampal ensembles, such that the recall of one memory can trigger the recall of another temporally-related memory. Alteration of this process (e.g. during aging, PTSD, etc) affect the temporal structure of memories, thus impairing efficient recall of related information.

Seminar: A/ Prof Demba Ba

Population Codes, Behavior, and Hierarchical Sparse Coding: an Unsupervised Learning Approach and its Connections to Artificial Neural Networks

Friday 31 May, 4pm at the Sherrington Library, DPAG Sherrington Building, Oxford

 

 

The Cortex Club is delighted to host A/ Professor Demba Ba from the Harvard University, who will be talking to us about his work on developing computational tools to identify neuronal populations during behaviour and deep sparse coding models to identify principles underlying hierarchical sensory processing in the brain. Please join us on May 31st, at the Sherrington Library, located in the Sherrington Building of the Department of Physiology, Anatomy and Genetics, Parks Road, Oxford.

A/ Professor Demba Ba has kindly agreed to meet students and staff individually. If you would like to arrange a meeting please contact Tai-Ying Lee at tai-ying.lee [at] dpag.ox.ac.uk.

 

Please also join us at the pub after the talk, to which everybody is welcome. Registration would be appreciated at: https://forms.gle/tuB9kEqwV5mapPKy8

 

Abstract

Two important problems in neuroscience are to understand 1) how populations of neurons encode stimuli and how this encoding is related to behavior and 2) how the brain represents sensory signals hierarchically. I have developed theoretical and computational unsupervised learning tools to answer these questions. In the first part of my talk, I will describe a statistical framework to identify sub-groups of neurons within a larger population that have similar response profiles. The framework clusters multiple rasters that exhibit nonlinear dynamics into an a-priori-unknown number of functional sub-groups that each comprises rasters with similar dynamics. I will show an application to clustering neuronal responses from the prefrontal cortex of mice in an experiment designed to characterize the neural underpinnings of the observational learning of fear. The method is able to identify “empathy” clusters of neurons, namely groups of neurons that allow an observer mouse to understand when a demonstrator demonstrator is in distress. In the second part of my talk, I will describe a deep generalization of the famous sparse coding model of Olhausen and Field. I will show a strong parallel between this deep sparse coding model and deep neural networks with ReLu nonlinearities, namely that a deep neural network architecture with ReLu nonlinearities arises from a finite sequence of cascaded sparse coding models, the outputs of which, except for the last element in the cascade, are sparse and unobservable. The benefits of the deep sparse coding model are two-fold. First, it gives answers based on theory to the question “what is the complexity of learning a deep ReLu auto-encoder?”. Second, it makes experimentally-testable predictions as to the principles that may underlie hierarchical sensory processing in the brain.

Seminar: Prof Loren Frank

Understanding the brain’s model of the external world

Wednesday 22 May, 11am at the Large Lecture Theatre, Le Gros Clarke Building, Oxford

 

The Cortex Club is delighted to co-host, together with the Neurotheory Seminar Series, Prof Loren Frank from UCSF,  who will be talking to us about his work on how neuronal networks create a predictive model of the external world. Please join us on May 22nd, at the Large Lecture Theatre located in the Le Gros Clark Building of the Department of Physiology, Anatomy and Genetics, Parks Road, Oxford.

 

Prof. Loren Frank has kindly agreed to meet students and staff individually. If you would like to arrange a meeting please contact Tai-Ying Lee at tai-ying.lee [at] dpag.ox.ac.uk.

 

 

Abstract

The ability to create an accurate, predictive model of the world is one of the most remarkable attributes of the brain.  Our goal is to understand how activity and plasticity in neural circuits underlie both the ability to create this model and to use it to make decisions. In this talk I will focus on neural activity patterns that have the potential to play a central role in model-based decision-making.  This work began with the realization that the ability to generate and evaluate representations of hypothetical experience, whether of a counterfactual past or of a possible future, has profound adaptive value. How and when the brain might express these representations has not been clear, and I will describe work from my laboratory that has identified and characterized these representations as a surprisingly common motif in hippocampal spiking activity. We have also found that changes in firing rates in medial prefrontal cortex can be seen immediately before and during the expression of these hippocampal representations, consistent with the possibility that this activity marks the time of engagement and evaluation of mental simulations.

Q&A: Prof Katrin Amunts

Next generation brain maps – concepts, challenges, collaboration

Friday 17 May, 14.00pm at the Sherrington Library, Sherrington Building, Oxford

 

The Cortex Club is delighted to host a Q&A session with Prof Katrin Amunts from the Institute of Neuroscience and Medicine, Forschungszentrum Julich, Germany, who will be giving the DPAG Head of Department Seminar in the Large Lecture Theatre at 13.00. Please join us after the lecture for the Q&A session on May 17th at the Sherrington Library located in the Sherrington Building, Department of Physiology, Anatomy and Genetics, Oxford.

Please register for the Q&A session at: https://forms.gle/oVofw8CJn9YKosdF7
Free sandwich lunch provided!

 

 

Abstract

The human brain is a highly complex system, with different levels of spatial organisation. E.g., on a macroscopic level, the brain shows a highly variable folding pattern, while nerve cells on a microscopical level are arranged in layers and columns in a regionally specific way. Cytoarchitecture is a concept that itself encompasses different aspects of brain organization – the different cell types have distinct morphology, molecular, genetic and connectional fingerprints. Axons form complex networks at the level of microcircuits or large cognitive system. To capture the cellular and axonal architecture and to study the role of a specific brain region to function or behaviour requires to analyse the brain in 3D with microscopical resolution. Deep-learning offers new tools to 3D reconstruct images of histological
sections at the microscopical scale, and convolutional neuronal networks support to automatize brain mapping. Considering the size of the brain with its nearly 86 billion nerve cells, HPC-based workflows play an increasing
role for developing high-resolution brain models, to tame brain complexity. To develop such tools is key in the Human Brain Project. It is building a European research infrastructure for brain research, to collaborate towards a better understanding of the human brain.