Venue: BBS
Organized by Andreas Frick and Théo Gauvrit
Speakers
Ian Duguid, University of Edinburgh (UK)
Brice Bathellier, Institut Pasteur (France)
Elizabeth Milne, The University of Sheffield (UK)
Elizabeth Milne
Resting State EEG biomarkers for autism: sparse findings from a large sample
Substantial research time has been dedicated to the search for an EEG-based biomarker for autism. However, despite intensive effort, no single biomarker nor common understanding about the way(s) in which neural dynamics may differ between autistic and neurotypical people has been identified.
In this talk, I will present the results of a large-scale secondary data analysis project where we compared eyes-open resting state EEG dynamics between autistic and neurotypical people in a sample of 776 participants (421 autistic, 355 neurotypical) and in a follow-up study where we analysed both eyes-open and eyes-closed resting state data in a sample of 300 participants (126 autistic and 355 neurotypical).
We took an extremely exploratory approach, extracting 726 variables from each participant reflecting absolute and relative power across six frequency bands; 1/f aperiodic activity; multiscale entropy, phase-amplitude coupling, and intersite phase coherence. After computing effect size and split-half reliability coefficients, we found very few variables that reliably differed between the autistic and neurotypical samples, although we noted that reliable group differences were more likely to be observed in data acquired during eyes-closed resting than eyes-open resting state. Group differences, where they occurred, were found primarily in variables that reflected relative power and hemispheric power asymmetry, particularly in the lower frequency bands (delta, alpha), and multi-scale entropy over frontal regions.
These data speak strongly to the heterogeneity and inter-individual variability of the autism profile and pose a substantial challenge to projects that aim to identify a single biomarker that reflects the diagnostic label of autism.
Brice Bathellier
A spatial code for temporal information is necessary for efficient sensory learning
The temporal structure of sensory inputs contains essential information for their interpretation. Sensory cortex represents these temporal cues through two codes: the temporal sequences of neuronal activity and the spatial patterns of neuronal firing rate. However, it is unknown which of these coexisting codes causally drives sensory decisions. To separate their contributions, we generated in the mouse auditory cortex optogenetically-driven activity patterns differing exclusively along their temporal or spatial dimensions. Mice could rapidly learn to behaviorally discriminate spatial but not temporal patterns. Moreover, large-scale neuronal recordings across the auditory system revealed that the auditory cortex is the first region in which spatial patterns efficiently represent temporal cues on the time scale of several hundred milliseconds. This feature is shared by the deep layers of neural networks categorizing time-varying sounds. Therefore, the emergence of a spatial code for temporal sensory cues is a necessary condition to efficiently associate temporally structured stimuli with decisions.
Ian Duguid
Corticospinal neurons in efficient response control
The ability to execute appropriate actions in response to salient environmental cues is termed response control. This requires brain-wide sensory-to-action transformations, involving sensory perception, motor planning, and ultimately movement execution, the latter being driven in part by a subset of motor cortical projection neurons with direct access to the spinal cord. These corticospinal neurons (CSNs) provide time-varying spinal cord input to orchestrate complex muscle synergies necessary for executing skilled movements and disrupting their output leads to loss of limb function, impaired reach precision, and hand discoordination. While CSN activation has been associated with movement execution and kinematic parameterization (e.g., force, velocity, and amplitude), in this talk I will discuss how CSN suppression, a ubiquitous feature of CSN dynamics across species, is topographically and temporally organised in motor cortex and how bidirectional CSN output contributes to the execution of task-appropriate actions.