72 research outputs found
Intrusive memories to traumatic footage: The neural basis of their encoding and involuntary recall
No full textBackgroundA hallmark symptom after psychological trauma is the presence of intrusive memories. It is unclear why only some moments of trauma become intrusive, and how these memories involuntarily return to mind. Understanding the neural mechanisms involved in the encoding and involuntary recall of intrusive memories may elucidate these questions.MethodParticipants (n = 35) underwent functional magnetic resonance imaging (fMRI) while being exposed to traumatic film footage. After film viewing, participants indicated within the scanner, while undergoing fMRI, if they experienced an intrusive memory of the film. Further intrusive memories in daily life were recorded for 7 days. After 7 days, participants completed a recognition memory test. Intrusive memory encoding was captured by comparing activity at the time of viewing ‘Intrusive scenes’ (scenes recalled involuntarily), ‘Control scenes’ (scenes never recalled involuntarily) and ‘Potential scenes’ (scenes recalled involuntarily by others but not that individual). Signal change associated with intrusive memory involuntary recall was modelled using finite impulse response basis functions.ResultsWe found a widespread pattern of increased activation for Intrusive v. both Potential and Control scenes at encoding. The left inferior frontal gyrus and middle temporal gyrus showed increased activity in Intrusive scenes compared with Potential scenes, but not in Intrusive scenes compared with Control scenes. This pattern of activation persisted when taking recognition memory performance into account. Intrusive memory involuntary recall was characterized by activity in frontal regions, notably the left inferior frontal gyrus.ConclusionsThe left inferior frontal gyrus may be implicated in both the encoding and involuntary recall of intrusive memories.<br/
MVPA to enhance the study of rare cognitive events: an investigation of experimental PTSD
No full textMany cognitive processes are challenging to study due to their scarce occurrence. Here we demonstrate how pattern recognition and brain imaging can enhance the study of such processes by providing fast, sensitive, and non-intrusive detection of these events. This can enable efficient experimental and clinical intervention. We focus on the study of traumatic events producing flashbacks associated with post-traumatic stress disorder (PTSD), using an experimental analogue of trauma (a traumatic film). These events are rare and challenging to reliably elicit in experimental settings. We show that a classifier can be built to predict, based upon brain response, which stimuli are likely to induce these rare flashbacks at the point of exposure. An ability to predict these stimuli makes possible the trialing of context-specific preventative clinical interventions. We present results from two independent datasets, outlining key analytic challenges. © 2014 IEEE
First steps in using machine learning on fMRI data to predict intrusive memories of traumatic film footage
No full textAfter psychological trauma, why do some only some parts of the traumatic event return as intrusive memories while others do not? Intrusive memories are key to cognitive behavioural treatment for post-traumatic stress disorder, and an aetiological understanding is warranted. We present here analyses using multivariate pattern analysis (MVPA) and a machine learning classifier to investigate whether peri-traumatic brain activation was able to predict later intrusive memories (i.e. before they had happened). To provide a methodological basis for understanding the context of the current results, we first show how functional magnetic resonance imaging (fMRI) during an experimental analogue of trauma (a trauma film) via a prospective event-related design was able to capture an individual's later intrusive memories. Results showed widespread increases in brain activation at encoding when viewing a scene in the scanner that would later return as an intrusive memory in the real world. These fMRI results were replicated in a second study. While traditional mass univariate regression analysis highlighted an association between brain processing and symptomatology, this is not the same as prediction. Using MVPA and a machine learning classifier, it was possible to predict later intrusive memories across participants with 68% accuracy, and within a participant with 97% accuracy; i.e. the classifier could identify out of multiple scenes those that would later return as an intrusive memory. We also report here brain networks key in intrusive memory prediction. MVPA opens the possibility of decoding brain activity to reconstruct idiosyncratic cognitive events with relevance to understanding and predicting mental health symptoms
Representational Dynamics Simulator
No full textThis app is hosted at Heroku, and is based on the work in Higgins et al. (2022).
Please cite as: Van Es, M.W.J., Higgins, C., Quinn, A.J., Vidaurre, D., Gould Van Praag, C.D., Fabus, M.S., Woolrich, M.W. (2022). Representational Dynamics Simulator. Zenodo. doi: 10.5281/zenodo.6579997.
In this simulator we illustrate the relationship between the frequency content of a (neural) signal and the subsequent decoding accuracy metrics when we use instantaneous signal decoding.
We simulate two conditions across two channels, each of which are made up out of a maximum two frequency components. The frequencies and the amplitudes in each condition and channel can be changed using the sliders. Example 1/2 can be toggled to see the examples corresponding to figure 2 in Higgins et al (2022). We can see that when we use instantaneous signal decoding, the information content oscillates with twice the original frequency.
App created by Mats W.J. van Es, 2022, Copyright University of Oxford.
Author contributions (CRediT):
Conceptualization: Mats W.J. van Es, Cameron Higgins
Data curation: Mats W.J. van Es
Formal analysis: Mats W.J. van Es
Funding acquisition: Diego Vidaurre, Mark W. Woolrich
Investigation: Mats W.J. van Es, Cameron Higgins
Methodology: Mats W.J. van Es, Cameron Higgins
Project administration: Mats W.J. van Es
Resources: Mats W.J. van Es, Cassandra D. Gould Van Praag, Marco S. Fabus
Software: Mats W.J. van Es, Cassandra D. Gould Van Praag, Marco S. Fabus
Supervision: Mark W. Woolrich
Validation: Mats W.J. van Es, Cameron Higgins, Andrew J. Quinn, Mark W. Woolrich
Visualization: Mats W.J. van Es
Writing - original draft: Mats W.J. van Es
Writing - review & editing: Mats W.J. van Es, Cameron Higgins, Andrew J. Quinn, Diego Vidaurre, Mark W. Woolrich
This research was funded by the Wellcome Trust (106183/Z/14/Z, 215573/Z/19/Z), the New Therapeutics in Alzheimer's Diseases (NTAD) study supported by UK MRC and the Dementia Platform UK (RG94383/RG89702) and the EU-project euSNN (MSCA-ITN H2020-860563), and supported by the NIHR Oxford Health Biomedical Research Centre, and the . The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z). DV is supported by a Novo Nordisk Emerging Investigator Award (NNF19OC-0054895) and by the European Research Council (ERC-StG-2019-850404)
Angeli neri: il mondo tenebroso di Cornell Woolrich nel cinema di François Truffaut
No full textIn his 1971 preface to the short-story collection Night webs, Truffaut talks of the clouds of ignorance surrounding American authors such as Woolrich, and it would appear that at the start of the 21st century nothing had changed, with the introduction to his novel Rendezvous in Black pointing out that: “Revered by mystery fans, students of film noir, and lovers of hard-boiled crime fiction and detective novels, Cornell Woolrich remains almost unknown to the general reading public” (Dooling 2004: vii). There are of course well-known advantages to a director deliberately picking a lesser known, or second-rate writer, to base a film on: it means that the viewer will not have the burning temptation to continually compare book and film and that critics will not merely “assess a picture on the basis of its literary quality rather than its cinematic quality” (Truffaut 1983: 69). While taking for granted that Truffaut is the sole author of his films, making use of literary works which are then freely refashioned so as to create films which bear his hallmark, the aim of this brief paper is to investigate some of the characteristics of Woolrich’s vast output in order to attempt to understand how much of this writer’s macabre pen can be traced in these two films by Truffaut. In doing so, I will refer not only to the novels The Bride Wore Black and Waltz into Darkness, but also to other works, in particular the novel Rendezvous in Black, a revisitation of the Bride wore black published in 1948.
Dooling, Richard. 2004 [1948]. Introduction. In Cornell Woolrich, Rendezvous in Black, New York: The Modern Library.
Truffaut, François . 1983. Hitchcock, Revised Edition, New York: Schuster
White matter tracts in first-episode psychosis: a DTI tractography study of the uncinate fasciculus.
No full textA model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the symptoms and cognitive abnormalities of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail, and we present here a study of patients with first-episode psychosis using this technique. We studied the uncinate fasciculus (UF), the largest white matter tract that connects the frontal and temporal lobes, two brain regions significantly implicated in schizophrenia. Nineteen patients with first-episode schizophrenia and 23 controls were studied using a probabilistic tractography algorithm (PICo). Fractional anisotropy (FA) and probability of connection were obtained for every voxel in the tract, and the group means and distributions of these variables were compared. The spread of the FA distribution in the upper tail, as measured by the squared coefficient of variance (SCV), was reduced in the left UF in the patient group, indicating that the number of voxels with high FA values was reduced in the core of the tract and suggesting the presence of changes in fibre alignment and tract coherence in the patient group. The SCV of FA was lower in females across both groups and there was no correlation between the SCV of FA and clinical ratings
Measuring functional connectivity in MEG: a multivariate approach insensitive to linear source leakage.
No full textA number of recent studies have begun to show the promise of magnetoencephalography (MEG) as a means to non-invasively measure functional connectivity within distributed networks in the human brain. However, a number of problems with the methodology still remain--the biggest of these being how to deal with the non-independence of voxels in source space, often termed signal leakage. In this paper we demonstrate a method by which non-zero lag cortico-cortical interactions between the power envelopes of neural oscillatory processes can be reliably identified within a multivariate statistical framework. The method is spatially unbiased, moderately conservative in false positive rate and removes linear signal leakage between seed and target voxels. We demonstrate this methodology in simulation and in real MEG data. The multivariate method offers a powerful means to capture the high dimensionality and rich information content of MEG signals in a single imaging statistic. Given a significant interaction between two areas, we go on to show how classical statistical tests can be used to quantify the importance of the data features driving the interaction
Author response
No full textMost perceptual decisions require comparisons between current input and an internal template. Classic studies propose that templates are encoded in sustained activity of sensory neurons. However, stimulus encoding is itself dynamic, tracing a complex trajectory through activity space. Which part of this trajectory is pre-activated to reflect the template? Here we recorded magneto- and electroencephalography during a visual target-detection task, and used pattern analyses to decode template, stimulus, and decision-variable representation. Our findings ran counter to the dominant model of sustained pre-activation. Instead, template information emerged transiently around stimulus onset and quickly subsided. Cross-generalization between stimulus and template coding, indicating a shared neural representation, occurred only briefly. Our results are compatible with the proposal that template representation relies on a matched filter, transforming input into task-appropriate output. This proposal was consistent with a signed difference response at the perceptual decision stage, which can be explained by a simple neural model
- …
