ePoster · Neuroscience
Antoine Daigle, Antoine Legare, Michele Desjardins, Joel Boutin, Gabrielle Germain, Vincent Breton-Provencher · COSYNE 2025
Noradrenaline (NA) is a ubiquitous neuromodulator largely produced by locus coeruleus (LC) neurons that impacts multiple cognitive processes. Non-invasive methods are used to track LC-NA activity. For instance, pupillometry is shown to be linked to arousal state, LC-NA, and other neuromodulator activity. However, given that pupillometry is a relatively slow process, the extent by which LC-NA can be predicted by pupil is limited. Since movements are linked with increased LC activity, orofacial movements could potentially be used as an additional psychophysiological marker for arousal and LC-N
ePoster · Neuroscience
Pragya Pandey, Indrajeet Indrajeet, Supriya Ray · FENS Forum 2024
Our attention falters, which is commonly known as ‘attentional blink’ (AB), after spotting a target; as a result, the subsequent target often goes unnoticed. Attentional demand also affects the size of the pupillary aperture. In previous studies, differential pupillary dilation averaged across trials within a short critical epoch distinguished AB. In contrast, we examined the pupil dynamics on a trial-by-trial basis. Healthy young volunteers performed a task, wherein two visual targets embedded in a series of distractors were presented in a rapid succession. The participants were asked to iden
ePoster · Neuroscience
Loredana Stoica Ghita, Lukas Hillisch, Jonathan R. Whitlock · FENS Forum 2024
The mammalian brain continuously integrates sensory and proprioceptive information. This dynamic process enables adaptation to rapidly changing environments and is critical for perception and action selection. However, the exact underlying neuronal computations remain poorly understood, particularly in freely moving animals where behavioral and sensorial transitions are rapid. Relating neural activity to natural behavior has been technically challenging due to a lack of tools to quantify postural dynamics at ethologically relevant timescales. Furthermore, sensory systems have traditionally bee
ePoster · Neuroscience
Sofia Castro e Almeida, Letícia Wopfner, Alexander Wallerus, Aron Koszeghy, Arsenii Petryk, Maja Überegger, Johannes Passecker · FENS Forum 2024
Reinforcement Learning algorithms allow agents to learn the probabilistic structure of the environment. These structures, termed belief-states, predict future outcomes and guide choice policies to maximize rewards. The ability to utilize new evidence to update belief-states is vital for adaptive behaviors, a process often impaired in schizophrenia contributing to psychosis, cognitive deficits, and avolition.A critical challenge persists in determining the underlying neuronal mechanisms governing belief-state updating and its impact on learning and reasoning. To address this, we train wildtype-