Sessions

Sessions and Chairs

What prefrontal computations support social cognition?

Pat Lockwood

Rather than trying to identify what brain mechanisms are uniquely ‘social’, increasingly, social neuroscience is asking what fundamental computational building blocks support social cognition and how are they implemented in the brain? Only by focusing on the mechanisms of high-level social cognition we can begin to implement a process account of our extensive capacity to engage in complex social reasoning. However, complex social processes will also heavily draw from a more general purpose computational machinery with many important mechanisms in the PFC. Thus, we need more extensive exchange between people working on the neural mechanisms of non-social cognitive processes and their social counterparts to identify and test the already established computational mechanisms that could support social cognition and what still needs to be addressed. Only then we can build theories about the differences in ‘social’ computation in terms of mechanisms and use of information sources.

In this theme we will have set of speakers that work on neural mechanisms underlying social behaviours on different levels of description in scale, complexity and species. We will hopefully link these descriptions to more general computational mechanism important for supporting social cognition. We will then discuss what we need going forward to define thus far unsolved questions about the implementation of different types of social cognition computationally.

Confirmed speakers: Luke Chang, Xiaosi Gu, Olga Dal Monte, Marco Wittmann

 

Self-organized behaviours, control and ecological problems

Nils Kolling

PFC is particularly important for complex and novel behaviours that require behavioural flexibility and control. In fact, PFC often becomes increasingly irrelevant with repetition even when the decision problem is initially complex. We have learned a lot about how PFC enables animals and humans to be flexible when choosing between specific options e.g. reversing preferences during learning or complementing model-free with more model-based value estimates based on planning. We know however, comparatively little on how the PFC enables us to solve more unstrained decision problems or make decisions about how to organize our behaviour efficiently across space and time in more ecological contexts. However, by taking an ecological perspective it is possible to make specific predictions about what kind of competing circuits might exists to optimize more self-organized behaviour within the context of a set of evolutionarily relevant types of decision.

In this theme we will have a set of speakers tackling the problem of self-organized behaviours and the navigation of complex environments from different perspectives. This will hopefully lead to a larger discussion about what an ecological perspective can contribute to understanding the role of PFC in generating more self-organized behaviours which require the concurrent evaluation of the when, what, where, how hard and for how long for.

Confirmed speakers: Ben Hayden, Alla Karpova, Jeremy Seamans, Nathaniel Daw

 

Neural networks maintaining, processing and integrating information

Laurence Hunt  

One important characteristic of PFC is its functional flexibility. Depending on the task an agent is faced with, PFC can support many different kinds of working memory, evidence integration, decision making, task switching and monitoring. However, while the working memory and decision making fields are seen as quite separate the maintenance and integration processes involved look remarkably similar, suggesting there might be a lot of potential to learn from each other. For example, recent suggestions of activity silent working memory representations make novel predictions about the potential circuit level implementation of flexible representations as well as integration and decision making.

In this theme we want to bring together different people working on circuit level explanation of flexible integration, representation and computation within the PFC to discuss possible PFC specific circuit rules and mechanisms supporting the retention and integration of many sources of information for the purpose of adaptive responding.

Confirmed speakers: Emily Finn, Robert Gunagyu Yang, Chris Summerfield

 

Emotion and PFC

Jacqueline Scholl

PFC is relevant for many psychiatric disorders. A better understanding  of PFC can therefore really benefit psychiatry. However, very little exchange between psychiatric and other PFC research exists. As a result we know less than we should about how our theories might link to clinical profiles. Importantly, a better connection between the clinical, both psychiatry and neuropsychology, and other PFC research does not only increase its relevance to society but can also inform new ideas about core functions of PFC regions by observation of the behavioural consequences of their change.

The aim of this session is therefore to highlight the links between individual differences in psychiatric symptoms and lesion induced changes in  PFC with other general theories of PFC functions. Hopefully this will lead into discussions of how these theories could be adapted to either account for clinical findings or what new experiments need to be designed to measure core concepts linking to both clinical profiles and PFC function.

Confirmed speakers: Angela Roberts, Emma Robinson, Micah Allen, Eran Eldar

 

Pharmacology, computation and PFC

Mark Walton

This session will look at the computational role of different neurotransmitters in PFC. It will bring together work in humans, rodents and macaques. We will be particularly focused on serotonin, dopamine and noradrenaline and try to understand how they could act as more global signals in PFC and in computational models (i.e. have a meta-role).

Confirmed speakers: Vikaas Sohal, Hanneke den Ouden, Catherine Winstanley, Paul Anastasiades

 

Neural oscillations and temporal dynamics of PFC computations

Elsa Fouragnan

PFC circuit properties can be detected macroscopically by measuring its aggregate activity, oscillations and long range interactions and microscopically via direct recordings. These dynamics in general and oscillations in particular are constrained by the physiological and anatomical properties of the PFC. However, while we know a lot about oscillations in primary motor and sensory cortices and some subcortical brain regions such as the hippocampus, our knowledge of larger oscillatory patterns and other temporal dynamics in PFC is still very much lacking.

In this session we want to bring together some of the few people who have worked on temporal rhythms and patterns in PFC. We hope it will help us further integrate this feature of neural activity into our models of PFC computation.

Confirmed speakers: Suliann Ben Hamed, Erin Rich, Charlie Wilson, Raphel Polania

 

Representation, structure and Memory

Jill O’Reilly

For a long time humans have asked themselves the question of how knowledge is organized. With the addition of new computational theories and ways to probe brain mechanisms we now have a new perspective to this age old question. Specifically, we want to bring together ideas on statistical inference, world structure learning and the representation of knowledge and reward from the perspective of artificial intelligence, systems neuroscience and cognitive modelling to understand how the PFC supports learning, inference and planning. We also want to discuss the broader implication of our increasing understanding of how cognitive content is represented to other disciplines such as decision making.

Confirmed speakers: Helen Barron, Nico Schuck, Kim Stachenfeld, Caswell Barry

 

Anatomy and comparative work

Jerome Sallet

PFC is principally investigated in 5 different species (mouse, rat, marmoset, macaque and human). Yet, our ability to integrate across each one of those models at will is still lacking. However, as pointed out by Passingham and colleagues (Passingham et al. 2002), understanding anatomical features should guide our interpretation of functional data. Thus, a better understanding of the neuroanatomical similarities but also specificities (associated for instance with ecological/physical constraints: whiskers to explore the world vs hands) will also lead to a better integration. This is particularly true for PFC, because it has many interspecies differences. Beyond interspecies mapping a more functionally oriented comparative neuroscience can also tell us about the link between different ecological niches and behaviours and brain function, informing future theories of the function of different subdivisions of PFC. Of course, good neuroanatomy is equally important to inform us about the neurobiological substrates of PFC circuits, as knowing about circuit organization constraints its computational and functional roles.  It can also help us understand changes associated with learning.

Confirmed speakers: Rogier Mars, Jill McGaughy, Stefan Everling, Susan Haber