Biology subjects

Fouragnan, E.

Publications and source records attributed to Fouragnan, E..

3 recordsLinked to original sources

bioRxiv2018

Manipulation of deep brain activity in primates using transcranial focused ultrasound stimulation

The causal role of an area within a neural network can be determined by interfering with its activity and measuring the impact. Many current reversible manipulation techniques have limitations preventing their focal application particularly in deep areas of the primate brain. Here we demonstrate a transcranial focused ultrasound stimulation (TUS) protocol that manipulates activity even in deep brain areas: a subcortical brain structure, the amygdala (experiment 1), and a deep cortical region, anterior cingulate cortex (ACC, experiment 2), in macaques. TUS neuromodulatory effects were measured by examining relationships between activity in each area and the rest of the brain using functional magnetic resonance imaging (fMRI). In control conditions without sonication, activity in a given area is related to activity in interconnected regions but such relationships are reduced after sonication. Dissociable and focal effects on neural activity could not be explained by auditory artefacts.

neuroscience↗

bioRxiv2017

Dorsomedial prefrontal cortex activity during reinforcement learning discriminates response to Cognitive Behavioural Therapy in depression.

BACKGROUNDCognitive behavioural therapy (CBT) is an effective evidence based treatment for depression. At present there is no reliable predictor of CBT in depression. Although the key to successful CBT in depression lies in altering maladaptive information processing, no previous imaging study has probed predictors of CBT response using pre-treatment neural encoding of information processing. METHODS: Using functional magnetic resonance imaging we scanned 37 unmedicated depressed subjects before and after completing computerised CBT (cCBT). We model the trial-by-trial appraisal of feedback information during a probabilistic learning task by means of a dynamic learning rate. To discriminate response to cCBT we capitalise on the pre-treatment blood oxygen level dependent (BOLD) activity encoding the dynamic learning rate as a function of feedback congruence and valence. Additionally, we probe between-group differences in the learning style encoded in the models parameters.\n\nRESULTSWe show BOLD activity in the dorsomedial prefrontal cortex (dmPFC) to be encoding the dynamic learning rate. Crucially, responders exhibit greater BOLD activity in the dmPFC during incongruent negative trials but lower BOLD activity during congruent negative trials than non-responders. Additionally, on between-group comparisons of models parameter estimates we show responders take relatively greater account of previous feedback history and make comparatively smaller adjustments to the learning rate as a result of outcome surprisingness.\n\nCONCLUSIONSOur findings provide novel and important insights into the cognitive mechanisms underpinning response to cCBT and lend support to the feasibility and validity of neurocomputational approaches to treatment prediction research in psychiatry.

neuroscience↗

bioRxiv2016

Spatiotemporal characterization of the neural correlates of outcome valence and surprise during reward learning in humans

Reward learning depends on accurate reward associations with potential choices. Two separate outcome dimensions, namely the valence (positive or negative) and surprise (the absolute degree of deviation from expectations) of an outcome are thought to subserve adaptive decision-making and learning, however their neural correlates and relative contribution to learning remain debated. Here, we coupled single-trial analyses of electroencephalography with simultaneously acquired fMRI, while participants performed a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of outcome valence and surprise in the human brain. Electrophysiological variability in outcome valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Variability in outcome surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations we also found a linear superposition of the two outcome dimensions in a smaller network encompassing visuo-mnemonic and reward areas. This spatiotemporal overlap was uniquely exposed by our EEG-informed fMRI approach. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.

neuroscience↗