Melbourne School of Psychological Sciences - Research Publications
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ItemGlobal semantic similarity effects in recognition memory: Insights from BEAGLE representations and the diffusion decision model(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2020-04-01)Recognition memory models posit that false alarm rates increase as the global similarity between the probe cue and the contents of memory is increased. Global similarity predictions have been commonly tested using category length designs where it has been found that false alarm rates increase as the number of studied items from a common category is increased. In this work, we explored global similarity predictions within unstructured lists of words using representations from the BEAGLE model (Jones & Mewhort, 2007). BEAGLE differs from traditional semantic space models in that it contains two types of representations: item vectors, which encode unordered co-occurrence, and order vectors, in which words are similar to the extent to which they are share neighboring words in the same relative positions. Global similarity among item and order vectors was regressed onto drift rates in the diffusion decision model (DDM: Ratcliff, 1978), which unifies both response times and accuracy. We implemented this model in a hierarchical Bayesian framework across seven datasets with lists composed of unrelated words. Results indicated clear deficits due to global similarity among item vectors, but only a minimal impact of global similarity among the order vectors. We also found evidence for a linear relationship between global similarity and drift rate and did not find any evidence that global similarity differentially affected performance in speed vs. accuracy emphasis conditions. In addition, we found that global semantic similarity could only partially account for the word frequency effect, suggesting that other factors besides semantic similarity may be responsible.
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ItemConstructing Word Meaning without Latent Representations using Spreading Activation(Cognitive Science Society, 2022-01-01)Models of word meaning, like the Topics model (Griffiths et al., 2007) and word2vec (Mikolov et al., 2013), condense word-by-context co-occurrence statistics to induce representations that organize words along semantically relevant dimensions (e.g., synonymy, antonymy, hyponymy etc.). However, their reliance on latent representations leaves them vulnerable to interference and makes them slow learners. We show how it is possible to construct the meaning of words online during retrieval to avoid these limitations. We implement our spreading activation account of word meaning in an associative net, a one-layer highly recurrent network of associations, called a Dynamic-Eigen-Net, that we developed to address the limitations of earlier variants of associative nets when scaling up to deal with unstructured input domains such as natural language text. After fixing the corpus across models, we show that spreading activation using a Dynamic-Eigen-Net outperforms the Topics model and word2vec in several cases when predicting human free associations and word similarity ratings. We argue in favour of the Dynamic-Eigen-Net as a fast learner that is not subject to catastrophic interference, and present it as an example of delegating the induction of latent relationships to process assumptions instead of assumptions about representation.
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ItemBeyond Pattern Completion with Short-Term Plasticity(Cognitive Science Society, 2020-01-01)In a Linear Associative Net (LAN), all input settles to a single pattern, therefore Anderson, Silverstein, Ritz, and Jones (1977) introduced saturation to force the system to reach other steady-states in the Brain-State-in-a-Box (BSB). Unfortunately, the BSB is limited in its ability to generalize because its responses are restricted to previously stored patterns. We present simulations showing how a Dynamic-Eigen-Net (DEN), a LAN with Short-Term Plasticity (STP), overcomes the single-response limitation. Critically, a DEN also accommodates novel patterns by aligning them with encoded structure. We train a two-slot DEN on a text corpus, and provide an account of lexical decision and judgement-of-grammaticality (JOG) tasks showing how grammatical bi-grams yield stronger responses relative to ungrammatical bi-grams. Finally, we present a simulation showing how a DEN is sensitive to syntactic violations introduced in novel bi-grams. We propose DENs as associative nets with greater promise for generalization than the classic alternatives.
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ItemEarly life stress alters pituitary growth during adolescence-A longitudinal study(PERGAMON-ELSEVIER SCIENCE LTD, 2015-03-01)The pituitary gland is integral in mediating the stress-response via its role in hypothalamic-pituitary-adrenal (HPA) axis function. Pituitary gland volume (PGV) is altered in stress-related psychopathology, and one study to date has shown stress to be associated with age-related PGV change during adolescence. The current study investigated the effects of a number of different types of early life (i.e., childhood and adolescent) stress (including childhood maltreatment, stressful life events, and maternal affective behavior) on PGV development from mid- to late adolescence using a longitudinal design. The influence of PGV development on depressive and anxiety symptoms was also investigated. Ninety one (49 male) adolescents took part in mother-child dyadic interaction tasks when they were approximately 12 years old, reported on childhood maltreatment and stressful life events when they were approximately 15 years old, and underwent two waves of structural magnetic resonance imaging (MRI) scans, when they were approximately 16 and 19 years old. Results revealed that childhood maltreatment predicted accelerated PGV development in females, and maternal dysphoric behavior predicted accelerated PGV development in the whole sample. PGV development was not associated with depressive or anxiety symptoms. These results suggest an effect of early life stress on altered HPA axis function across mid- to late adolescence. Further research is required to assess functional implications and whether these changes might be associated with risk for subsequent psychopathology.
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ItemCerebrospinal fluid neurofilament light and cerebral atrophy in younger-onset dementia and primary psychiatric disorders(WILEY, 2022-10-31)BACKGROUND AND AIMS: Neurodegeneration underpins the pathological processes of younger-onset dementia (YOD) and has been implicated in primary psychiatric disorders (PSYs). Cerebrospinal fluid (CSF) neurofilament light (NfL) has been used to investigate neurodegeneration severity through correlation with structural brain changes in various conditions, but has seldom been evaluated in YOD and PSYs. METHODS: This retrospective study included patients with YOD or PSYs with magnetic resonance imaging (MRI) of the brain and CSF NfL analysis. Findings from brain MRI were analysed using automated volumetry (volBrain) to measure white matter (WM), grey matter (GM) and whole brain (WB) volumes expressed as percentages of total intracranial volume. Correlations between NfL and brain volume measurements were computed whilst adjusting for age. RESULTS: Seventy patients (47 with YOD and 23 with PSY) were identified. YOD types included Alzheimer disease and behavioural variant frontotemporal dementia. PSY included schizophrenia and major depressive disorder. MRI brain sequences were either fast spoiler gradient-echo (FSPGR) or magnetization-prepared rapid acquisition gradient-echo (MPRAGE). In the total cohort, higher NfL was associated with reduced WB in the FSPGR and MPRAGE sequences (r = -0.402 [95% confidence interval (CI), -0.593 to -0.147], P = 0.008 and r = -0.625 [95% CI, -0.828 to -0.395], P < 0.001, respectively). Higher NfL was related to reduced GM in FSPGR (r = 0.385 [95% CI, -0.649 to -0.014], P = 0.017) and reduced WM in MPRAGE (r = -0.650 [95% CI, -0.777 to -0.307], P < 0.001). Similar relationships were seen in YOD, but not in PSY. CONCLUSION: Higher CSF NfL is related to brain atrophy in YOD, further supporting its use as a nonspecific marker of neurodegeneration severity.
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ItemTiming of referral to evaluate for epilepsy surgery: Expert Consensus Recommendations from the Surgical Therapies Commission of the International League Against Epilepsy(WILEY, 2022-10)Epilepsy surgery is the treatment of choice for patients with drug-resistant seizures. A timely evaluation for surgical candidacy can be life-saving for patients who are identified as appropriate surgical candidates, and may also enhance the care of nonsurgical candidates through improvement in diagnosis, optimization of therapy, and treatment of comorbidities. Yet, referral for surgical evaluations is often delayed while palliative options are pursued, with significant adverse consequences due to increased morbidity and mortality associated with intractable epilepsy. The Surgical Therapies Commission of the International League Against Epilepsy (ILAE) sought to address these clinical gaps and clarify when to initiate a surgical evaluation. We conducted a Delphi consensus process with 61 epileptologists, epilepsy neurosurgeons, neurologists, neuropsychiatrists, and neuropsychologists with a median of 22 years in practice, from 28 countries in all six ILAE world regions. After three rounds of Delphi surveys, evaluating 51 unique scenarios, we reached the following Expert Consensus Recommendations: (1) Referral for a surgical evaluation should be offered to every patient with drug-resistant epilepsy (up to 70 years of age), as soon as drug resistance is ascertained, regardless of epilepsy duration, sex, socioeconomic status, seizure type, epilepsy type (including epileptic encephalopathies), localization, and comorbidities (including severe psychiatric comorbidity like psychogenic nonepileptic seizures [PNES] or substance abuse) if patients are cooperative with management; (2) A surgical referral should be considered for older patients with drug-resistant epilepsy who have no surgical contraindication, and for patients (adults and children) who are seizure-free on 1-2 antiseizure medications (ASMs) but have a brain lesion in noneloquent cortex; and (3) referral for surgery should not be offered to patients with active substance abuse who are noncooperative with management. We present the Delphi consensus results leading up to these Expert Consensus Recommendations and discuss the data supporting our conclusions. High level evidence will be required to permit creation of clinical practice guidelines.
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ItemEvidence is king: A defence of evidence-based recommendations(WILEY, 2022-06-01)
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ItemThoroughly thought through? Experimenting with Registered Reports(WILEY, 2021-12-01)
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ItemPsychometric deficits in autoimmune encephalitis: A retrospective study from the Australian Autoimmune Encephalitis Consortium(WILEY, 2022-05-20)BACKGROUND AND PURPOSE: Despite the rapid increase in research examining outcomes in autoimmune encephalitis (AE) patients, there are few cohort studies examining cognitive outcomes in this population. The current study aimed to characterise psychometric outcomes in this population, and explore variables that may predict psychometric outcomes. METHODS: This retrospective observational study collected psychometric data from 59 patients across six secondary and tertiary referral centres in metropolitan hospitals in Victoria, Australia between January 2008 and July 2019. Frequency and pattern analysis were employed to define and characterize psychometric outcomes. Univariable logistic regression was performed to examine predictors of intact and pathological psychometric outcomes. RESULTS: Deficits in psychometric markers of executive dysfunction were the most common finding in this cohort, followed by deficits on tasks sensitive to memory. A total of 54.2% of patients were classified as having psychometric impairments across at least two cognitive domains. Twenty-nine patterns were observed, suggesting outcomes in AE are complex. None of the demographic data, clinical features or auxiliary examination variables were predictors of psychometric outcome. CONCLUSIONS: Cognitive outcomes in AE are complex. Further detailed and standardized cognitive testing, in combination with magnetic resonance imaging volumetrics and serum/cerebrospinal fluid biomarkers, is required to provide rigorous assessments of disease outcomes.