Alumni Talk Series: Ryszard Auksztulewicz (Oxford) and Christoph Korn (Hamburg)
Host: Felix Blankenburg
Ryszard Auksztulewicz was a member of doctoral cohort 2009–2012. He is now a postdoctoral researcher at the Oxford Centre for Human Brain Activity, University of Oxford, and at the Wellcome Trust Centre for Neuroimaging, University College London, UK. He will speak about “Sensory predictions are modulated by attention and task relevance: evidence from electrophysiology and modelling”.
Abstract: The brain is thought to generate internal predictions to optimise behaviour. However, it is unclear to what extent these predictions are modulated by other top-down factors such as attention and task demands. In this talk I will present results of three studies combining human electrophysiology and computational modelling to identify the neural mechanisms of sensory predictions and their interactions with current context.
First, using magnetoencephalography (MEG) and dynamic causal modelling (DCM), sensory predictions and temporal attention were orthogonally manipulated in an auditory mismatch paradigm, revealing interactive effects on evoked response amplitude. This interaction effect was modelled in a canonical microcircuit using DCM. While mismatch responses were explained by recursive interplay of sensory predictions and prediction errors, their attentional modulation was linked to increased early sensory gain.
Second, we analysed electrocorticographic data recorded from patients performing a task orthogonally manipulating “what” and “when” predictability of auditory targets. The two predictability types modulated evoked responses in different cortical regions and at dissociable latencies. DCM served to disambiguate between models of stimulus predictability in terms of top-down processing and gain modulation: “what” predictability increased auditory short-term plasticity, while “when” predictability increased putative synaptic gain in motor areas. This suggests that distinct predictions are mediated by qualitatively different neural mechanisms.
Finally, we independently manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. Relevance modulated the influence of predictability on task performance. To explain these effects, we estimated our participants’ subjective predictions using a Hierarchical Gaussian Filter (HGF). Model-based time-series of predictions and prediction errors were linked to dissociable induced activity measured with MEG. Predictions correlated with beta-band activity, while prediction errors were signalled by increased gamma and decreased alpha-band activity. Crucially, these oscillatory correlates were modulated by task relevance, suggesting that current goals influence prediction signalling.
Christoph Korn was a member of doctoral cohort 2009–2012. He is now a postdoctoral researcher with Jan Gläscher at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf. He will speak about “How do we solve multi-step decision-making problems? Optimal versus heuristic solutions”.
Abstract: Making a decision now influences which decisions we will face next. Ideally, our decisions should thus consider the current situation as well as all possible up-coming situations. However, this requires computing the values for a vast combination of probabilistic future situations. The complexities of such multi-step computations can easily exceed our cognitive capabilities, which is why we may often resort to myopic heuristics that only rely on the situation at hand. I will present a series of studies that combine mathematical modeling with functional neuroimaging to specify how human participants trade off using optimal versus heuristic solutions. Computing this trade-off recruits different parts of the medial prefrontal cortex. Furthermore, I will delineate how these notions of multi-step decisions can be extended to social scenarios, which pose the added challenge that we have to predict how our interaction partners react to our decisions.
All are welcome!
