VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 27, through Friday, November 29. We will resume normal operations on Monday, December 2. Thank you for your patience.

Browsing by Author "Dolan, Raymond J."

Now showing 1 - 5 of 5
  • Thumbnail Image
    Alterations in Brain Connectivity Underlying Beta Oscillations in Parkinsonism
    Moran, Rosalyn J.; Mallet, Nicolas; Litvak, Vladimir; Dolan, Raymond J.; Magill, Peter J.; Friston, Karl J.; Brown, Peter (PLOS, 2011-08-11)
    Cortico-basal ganglia-thalamocortical circuits are severely disrupted by the dopamine depletion of Parkinson’s disease (PD), leading to pathologically exaggerated beta oscillations. Abnormal rhythms, found in several circuit nodes are correlated with movement impairments but their neural basis remains unclear. Here, we used dynamic causal modeling (DCM) and the 6-hydroxydopamine-lesioned rat model of PD to examine the effective connectivity underlying these spectral abnormalities. We acquired auto-spectral and cross-spectral measures of beta oscillations (10–35 Hz) from local field potential recordings made simultaneously in the frontal cortex, striatum, external globus pallidus (GPe) and subthalamic nucleus (STN), and used these data to optimise neurobiologically plausible models. Chronic dopamine depletion reorganised the cortico-basal ganglia-thalamocortical circuit, with increased effective connectivity in the pathway from cortex to STN and decreased connectivity from STN to GPe. Moreover, a contribution analysis of the Parkinsonian circuit distinguished between pathogenic and compensatory processes and revealed how effective connectivity along the indirect pathway acquired a strategic importance that underpins beta oscillations. In modeling excessive beta synchrony in PD, these findings provide a novel perspective on how altered connectivity in basal ganglia-thalamocortical circuits reflects a balance between pathogenesis and compensation, and predicts potential new therapeutic targets to overcome dysfunctional oscillations.
  • Thumbnail Image
    The chronometry of risk processing in the human cortex
    Symmonds, Mkael; Moran, Rosalyn J.; Wright, Nicholas D.; Bossaerts, Peter; Barnes, Gareth; Dolan, Raymond J. (Frontiers, 2013-08-20)
    The neuroscience of human decision-making has focused on localizing brain activity correlating with decision variables and choice, most commonly using functional MRI (fMRI). Poor temporal resolution means these studies are agnostic in relation to how decisions unfold in time. Consequently, here we address the temporal evolution of neural activity related to encoding of risk using magnetoencephalography (MEG), and show modulations of electromagnetic power in posterior parietal and dorsomedial prefrontal cortex (DMPFC) which scale with both variance and skewness in a lottery, detectable within 500 ms following stimulus presentation. Electromagnetic responses in somatosensory cortex following this risk encoding predict subsequent choices. Furthermore, within anterior insula we observed early and late effects of subject-specific risk preferences, suggestive of a role in both risk assessment and risk anticipation during choice. The observation that cortical activity tracks specific and independent components of risk from early time-points in a decision-making task supports the hypothesis that specialized brain circuitry underpins risk perception.
  • Thumbnail Image
    Dynamic Causal Models and Physiological Inference: A Validation Study Using Isoflurane Anaesthesia in Rodents
    Moran, Rosalyn J.; Jung, Fabienne; Kumagai, Tetsuya; Endepols, Heike; Graf, Rudolf; Dolan, Raymond J.; Friston, Karl J.; Stephan, Klaas Enno; Tittgemeyer, Marc (PLOS, 2011)
    Generative models of neuroimaging and electrophysiological data present new opportunities for accessing hidden or latent brain states. Dynamic causal modeling (DCM) uses Bayesian model inversion and selection to infer the synaptic mechanisms underlying empirically observed brain responses. DCM for electrophysiological data, in particular, aims to estimate the relative strength of synaptic transmission at different cell types and via specific neurotransmitters. Here, we report a DCM validation study concerning inference on excitatory and inhibitory synaptic transmission, using different doses of a volatile anaesthetic agent (isoflurane) to parametrically modify excitatory and inhibitory synaptic processing while recording local field potentials (LFPs) from primary auditory cortex (A1) and the posterior auditory field (PAF) in the auditory belt region in rodents. We test whether DCM can infer, from the LFP measurements, the expected drug-induced changes in synaptic transmission mediated via fast ionotropic receptors; i.e., excitatory (glutamatergic) AMPA and inhibitory GABAA receptors. Cross- and auto-spectra from the two regions were used to optimise three DCMs based on biologically plausible neural mass models and specific network architectures. Consistent with known extrinsic connectivity patterns in sensory hierarchies, we found that a model comprising forward connections from A1 to PAF and backward connections from PAF to A1 outperformed a model with forward connections from PAF to A1 and backward connections from A1 to PAF and a model with reciprocal lateral connections. The parameter estimates from the most plausible model indicated that the amplitude of fast glutamatergic excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs) behaved as predicted by previous neurophysiological studies. Specifically, with increasing levels of anaesthesia, glutamatergic EPSPs decreased linearly, whereas fast GABAergic IPSPs displayed a nonlinear (saturating) increase. The consistency of our model-based in vivo results with experimental in vitro results lends further validity to the capacity of DCM to infer on synaptic processes using macroscopic neurophysiological data.
  • Thumbnail Image
    Multi-Round Trust Game Quantifies Inter-Individual Differences in Social Exchange from Adolescence to Adulthood
    Hula, Andreas; Moutoussis, Michael; Will, Geert-Jan; Kokorikou, Danae; Reiter, Andrea M.; Ziegler, Gabriel; NSPN Consortium; Bullmore, Ed; Jones, Peter B.; Goodyer, Ian; Fonagy, Peter; Montague, P. Read; Dolan, Raymond J. (Ubiquity Press, 2021-10)
    Investing in strangers in a socio-economic exchange is risky, as we may be uncertain whether they will reciprocate. Nevertheless, the potential rewards for cooperating can be great. Here, we used a cross sectional sample (n = 784) to study how the challenges of cooperation versus defection are negotiated across an important period of the lifespan: from adolescence to young adulthood (ages 14 to 25). We quantified social behaviour using a multi round investor-trustee task, phenotyping individuals using a validated model whose parameters characterise patterns of real exchange and constitute latent social characteristics. We found highly significant differences in investment behaviour according to age, sex, socio-economic status and IQ. Consistent with the literature, we showed an overall trend towards higher trust from adolescence to young adulthood but, in a novel finding, we characterized key cognitive mechanisms explaining this, especially regarding socio-economic risk aversion. Males showed lower risk-aversion, associated with greater investments. We also found that inequality aversion was higher in females and, in a novel relation, that socio-economic deprivation was associated with more risk averse play.
  • Thumbnail Image
    Peak frequency in the theta and alpha bands correlates with human working memory capacity
    Moran, Rosalyn J.; Campo, Pablo; Maestu, Fernando; Reilly, Richard B.; Dolan, Raymond J.; Strangle, Bryan A. (Frontiers, 2010-11-11)
    Theta oscillations in the local field potential of neural ensembles are considered key mediators of human working memory. Theoretical accounts arising from animal hippocampal recordings propose that the phase of theta oscillations serves to instantiate sequential neuronal firing to form discrete representations of items held online. Human evidence of phase relationships in visual working memory has enhanced this theory, implicating long theta cycles in supporting greater memory capacity. Here we use human magnetoencephalographic recordings to examine a novel, alternative principle of theta functionality. The principle we hypothesize is derived from information theory and predicts that rather than long (low frequency) theta cycles, short (high frequency) theta cycles are best suited to support high information capacity. From oscillatory activity recorded during the maintenance period of a visual working memory task we show that a network of brain regions displays an increase in peak 4–12 Hz frequency with increasing memory load. Source localization techniques reveal that this network comprises bilateral prefrontal and right parietal cortices. Further, the peak of oscillation along this theta–alpha frequency axis is significantly higher in high capacity individuals compared to low capacity individuals. Importantly while we observe the adherence of cortical neuronal oscillations to our novel principle of theta functioning, we also observe the traditional inverse effect of low frequency theta maintaining high loads, where critically this was located in medial temporal regions suggesting parallel, dissociable hippocampal-centric, and prefrontal-centric theta mechanisms.