Biology subjects

Moujaes, F.

Publications and source records attributed to Moujaes, F..

3 recordsLinked to original sources

bioRxiv2025

Ketamine Alters Tuning of Neural and Behavioral Spatial Working Memory Precision

Deficits in working memory (WM) are a hallmark of neuropsy-chiatric disorders such as schizophrenia, yet their neurobiological basis remains poorly understood. Glutamate N-methyl-D-aspartate receptors (NMDARs) are critical for spatial WM (sWM), with NMDAR antagonist ketamine known to attenuate task-evoked activation and reduce sWM accuracy. Cortical microcircuit models hypothesize that NMDAR antagonism impairs sWM by broadening neural spatial tuning, but this mechanism has not been directly tested in humans. Using a pharmacological fMRI approach, we showed how ketamine broadened neural spatial tuning, attenuated activation across visual, parietal, and frontal areas, and worsened sWM performance in healthy humans. Ketamine-induced changes in tuning were more consistent across individuals and brain regions than changes in overall activation and correlated with individual differences in sWM performance. These findings provide empirical evidence linking NMDAR antagonism to disruptions in cortical microcircuit dynamics, the resulting neural tuning alterations, and sWM impairments, advancing frameworks for therapeutic development.

neuroscience↗

bioRxiv2022

Ketamine induces multiple individually distinct whole-brain functional connectivity signatures

BackgroundKetamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamines molecular mechanisms connect to its neural and behavioral effects. MethodsWe conducted a double-blind placebo-controlled study in which 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hour). We quantified resting-state functional connectivity via data-driven global brain connectivity, related it to individual ketamine-induced symptom variation, and compared it to cortical gene expression targets. ResultsWe found that: i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; ii) ketamines data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, implicating the role of SST and PVALB interneurons in ketamines acute effects; and iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level. ConclusionsCollectively, these findings support the possibility for developing individually precise pharmacological biomarkers for treatment selection in psychiatry. FundingThis study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1-190420); Swiss Neuromatrix Foundation (Grant No. 2016-0111m Grant No. 2015 - 010); Swiss National Science Foundation under the frame-work of Neuron Cofund (Grant No. 01EW1908), Usona Institute (2015 - 2056).

neuroscience↗

bioRxiv2020

Mapping Brain-Behavior Space Relationships Along the Psychosis Spectrum

Difficulties in advancing effective patient-specific therapies for psychiatric disorders highlight a need to develop a stable neurobiologically-grounded mapping between neural and symptom variation. This gap is particularly acute for psychosis-spectrum disorders (PSD). Here, in a sample of 436 cross-diagnostic PSD patients, we derived and replicated a dimensionality-reduced symptom space across hallmark psychopathology symptoms and cognitive deficits. In turn, these symptom axes mapped onto distinct, reproducible brain maps. Critically, we found that multivariate brain-behavior mapping techniques (e.g. canonical correlation analysis) do not produce stable results. Instead, we show that a univariate brain-behavioral space (BBS) can resolve stable individualized prediction. Finally, we show a proof-of-principle framework for relating personalized BBS metrics with molecular targets via serotonin and glutamate receptor manipulations and gene expression maps. Collectively, these results highlight a stable and data-driven BBS mapping across PSD, which offers an actionable path that can be iteratively optimized for personalized clinical biomarker endpoints.

neuroscience↗