prediction - Max Planck Neuroscience

Scientists identify workflow algorithm to predict psychosis

Helena.Decker — Fri, 29 Jan 2021 20:49:34 +0000

Cleverly combining artificial and human intelligence leads to improved prevention of psychosis in young patients

Scientists from the Max Planck Institute of Psychiatry, led by Nikolaos Koutsouleris, combined psychiatric assessments with machine-learning models that analyse clinical and biological data. The results of the study, published in JAMA Psychiatry, show that it is the combination of artificial and human intelligence that optimizes the prediction of mental illness. The algorithm improves the prevention of psychosis, especially in young patients at high risk or with emerging depression and enables therapists to intervene in a more targeted and well-timed manner.

Nikolaos Koutsouleris; Dominic B. Dwyer; Franziska Degenhardt et al. (2021). Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression. JAMA Psychiatry. Online now.
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Neurotelemetry Reveals Putative Predictive Activity in HVC during Call-Based Vocal Communications in Zebra Finches

Helena.Decker — Sat, 05 Sep 2020 18:50:14 +0000

Premotor predictions facilitate vocal interactions. Here, we study such mechanisms in the forebrain nucleus HVC (proper name), a cortex-like sensorimotor area of songbirds, otherwise known for being essential for singing in zebra finches. To study the role of the HVC in calling interactions between male and female mates, we used wireless telemetric systems for simultaneous measurement of neuronal activity of male zebra finches and vocalizations of males and females that freely interact with each other. In a non-social context, male HVC neurons displayed stereotypic premotor activity in relation to active calling and showed auditory-evoked activity to hearing of played-back female calls. In a social context, HVC neurons displayed auditory-evoked activity to hearing of female calls only if that neuron showed activity preceding the upcoming female calls. We hypothesize that this activity preceding the auditory-evoked activity in the male HVC represents a neural correlate of behavioral anticipation, predictive activity that helps to coordinate vocal communication between social partners.

SIGNIFICANCE STATEMENT: Most social-living vertebrates produce large numbers of calls per day, and the calls have prominent roles in social interactions. Here, we show neuronal mechanisms that are active during call-based vocal communication of zebra finches, a highly social songbird species. HVC, a forebrain nucleus known for its importance in control of learned vocalizations of songbirds, displays predictive activity that may enable the male to adjust his own calling pattern to produce very fast sequences of male female call exchanges.

Ma S, Ter Maat A, Gahr M. (2020). Neurotelemetry Reveals Putative Predictive Activity in HVC during Call-Based Vocal Communications in Zebra Finches. J Neurosci. 40(32):6219-6227.
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Proactive sensing of periodic and aperiodic auditory patterns

MPFI — Wed, 26 Sep 2018 14:58:29 +0000

The ability to predict when something will happen facilitates sensory processing and the ensuing computations. Building on the observation that neural activity entrains to periodic stimulation, leading neurophysiological models imply that temporal predictions rely on oscillatory entrainment. Although they provide a sufficient solution to predict periodic regularities, these models are challenged by a series of findings that question their suitability to account for temporal predictions based on aperiodic regularities. Aiming for a more comprehensive model of how the brain anticipates ‘when’ in auditory contexts, we emphasize the capacity of motor and higher -order top-down systems to prepare sensory processing in a proactive and temporally flexible manner. Focusing on speech processing, we illustrate how this framework leads to new hypotheses.

Rimmele, J. M., Morillon, B., Poeppel, D., & Arnal, L. H. (2018). Trends in Cognitive Sciences, Online Publication.
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(18)30192-X

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