Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

Using simplified peer review processes to fund research: A prospective study

Objective: To prospectively test two simplified peer review processes, estimate the agreement between the simplified and official processes, and compare the costs of peer review. Design, participants and setting: A prospective parallel study of Project Grant proposals submitted in 2013 to the National Health and Medical Research Council (NHMRC) of Australia. The official funding outcomes were compared with two simplified processes using proposals in Public Health and Basic Science. The two simplified processes were: panels of 7 reviewers who met face-to-face and reviewed only the nine-page research proposal and track record (simplified panel); and 2 reviewers who independently reviewed only the nine-page research proposal (journal panel). The official process used panels of 12 reviewers who met face-to-face and reviewed longer proposals of around 100 pages. We compared the funding outcomes of 72 proposals that were peer reviewed by the simplified and official processes. Main outcome measures: Agreement in funding outcomes; costs of peer review based on reviewers’ time and travel costs. Results: The agreement between the simplified and official panels (72%, 95% CI 61% to 82%), and the journal and official panels (74%, 62% to 83%), was just below the acceptable threshold of 75%. Using the simplified processes would save $A2.1–$A4.9 million per year in peer review costs. Conclusions: Using shorter applications and simpler peer review processes gave reasonable agreement with the more complex official process. Simplified processes save time and money that could be reallocated to actual research. Funding agencies should consider streamlining their application processes.

Dopaminergic neuromodulation of semantic processing: A 4-T fMRI study with levodopa

There is emerging evidence that alterations in dopaminergic transmission can influence semantic processing, yet the neural mechanisms involved are unknown. The influence of levodopa (L-DOPA) on semantic priming was investigated in healthy individuals (n=20) using event-related functional magnetic resonance imaging with a randomized, double-blind crossover design. Critical prime-target pairs consisted of a lexical ambiguity prime and 1) a target related to the dominant meaning of the prime (e.g., bank-money), 2) a target related to the subordinate meaning (e.g., fence-sword), or 3) an unrelated target (e.g., ball-desk). Behavioral data showed that both dominant and subordinate meanings were primed on placebo. In contrast, there was preserved priming of dominant meanings and no significant priming of subordinate meanings on L-DOPA, the latter associated with decreased anterior cingulate and dorsal prefrontal cortex activity. Dominant meaning activation on L-DOPA was associated with increased activity in the left rolandic operculum and left middle temporal gyrus. These findings suggest that L-DOPA enhances frequency-based semantic focus via prefrontal and temporal modulation of automatic semantic priming and through engagement of anterior cingulate mechanisms supporting attentional/controlled priming.

No specific role for the manual motor system in processing the meanings of words related to the hand

The present study explored whether semantic and motor systems are functionally interwoven via the use of a dual-task paradigm. According to embodied language accounts that propose an automatic and necessary involvement of the motor system in conceptual processing, concurrent processing of hand-related information should interfere more with hand movements than processing of unrelated body-part (i.e., foot, mouth) information. Across three experiments, 100 right-handed participants performed left- or right-hand tapping movements while repeatedly reading action words related to different body-parts, or different body-part names, in both aloud and silent conditions. Concurrent reading of single words related to specific body-parts, or the same words embedded in sentences differing in syntactic and phonological complexity (to manipulate context-relevant processing), and reading while viewing videos of the actions and body-parts described by the target words (to elicit visuomotor associations) all interfered with right-hand but not left-hand tapping rate. However, this motor interference was not affected differentially by hand-related stimuli. Thus, the results provide no support for proposals that body-part specific resources in cortical motor systems are shared between overt manual movements and meaning-related processing of words related to the hand.

Young drivers’ responses to anti-speeding advertisements: Comparison of self-report and objective measures of persuasive processing and outcomes

Objective Self-report measures are typically used to assess the effectiveness of road safety advertisements. However, psychophysiological measures of persuasive processing (i.e., skin conductance response [SCR]) and objective driving measures of persuasive outcomes (i.e., in-vehicle GPS devices) may provide further insights into the effectiveness of these advertisements. This study aimed to explore the persuasive processing and outcomes of two anti-speeding advertisements by incorporating both self-report and objective measures of speeding behaviour. In addition, this study aimed to compare the findings derived from these different measurement approaches. Methods Young drivers (N = 20, Mage = 21.01 years) viewed either a positive or negative emotion-based anti-speeding television advertisement. Whilst viewing the advertisement, SCR activity was measured to assess ad-evoked arousal responses. The RoadScout® GPS device was then installed into participants’ vehicles for one week to measure on-road speed-related driving behaviour. Self-report measures assessed persuasive processing (emotional and arousal responses) and actual driving behaviour. Results There was general correspondence between the self-report measures of arousal and the SCR and between the self-report measure of actual driving behaviour and the objective driving data (as assessed via the GPS devices). Conclusions This study provides insights into how psychophysiological and GPS devices could be used as objective measures in conjunction with self-report measures to further understand the persuasive processes and outcomes of emotion-based anti-speeding advertisements.

Early mathematical learning: Number processing skills and executive function at 5 and 8 years of age

This research investigated differences and associations in performance in number processing and executive function for children attending primary school in a large Australian metropolitan city. In a cross-sectional study, performance of 25 children in the first full-time year of school, (Prep; mean age = 5.5 years) and 21 children in Year 3 (mean age = 8.5 years) completed three number processing tasks and three executive function tasks. Year 3 children consistently outperformed the Prep year children on measures of accuracy and reaction time, on the tasks of number comparison, calculation, shifting, and inhibition but not on number line estimation. The components of executive function (shifting, inhibition, and working memory) showed different patterns of correlation to performance on number processing tasks across the early years of school. Findings could be used to enhance teachers’ understanding about the role of the cognitive processes employed by children in numeracy learning, and so inform teachers’ classroom practices.

Improving deep convultional neural networks with unsupervised feature learning

The latest generation of Deep Convolutional Neural Networks (DCNN) have dramatically advanced challenging computer vision tasks, especially in object detection and object classification, achieving state-of-the-art performance in several computer vision tasks including text recognition, sign recognition, face recognition and scene understanding. The depth of these supervised networks has enabled learning deeper and hierarchical representation of features. In parallel, unsupervised deep learning such as Convolutional Deep Belief Network (CDBN) has also achieved state-of-the-art in many computer vision tasks. However, there is very limited research on jointly exploiting the strength of these two approaches. In this paper, we investigate the learning capability of both methods. We compare the output of individual layers and show that many learnt filters and outputs of the corresponding level layer are almost similar for both approaches. Stacking the DCNN on top of unsupervised layers or replacing layers in the DCNN with the corresponding learnt layers in the CDBN can improve the recognition/classification accuracy and training computational expense. We demonstrate the validity of the proposal on ImageNet dataset.

Resilience: A new integrative approach to health and mental health research

We know from anecdote and research, science and art, that human resilience is a powerful, seemingly ubiquitous force. What is needed is a better understanding of the properties, variations, and applications of that concept to health and well-being. In this paper we put forth two definitions of resilience: Sustainability of purpose in the face of stress, and recovery from adversity. We review current thinking in the social sciences on the nature of biological, psychological and socio-community processes that may confer resilience. In doing so, we encourage greater attention to aspects of biopsychosocial resourcefulness as a dimension of influence on health and mental health distinct from measures of risk found in standard models of public health inquiry. Multi-level, longitudinal, and intervention methods are advocated for research and applications of the concept with conceptual guidelines for the examination of laboratory, diary, and community indicator data on manifestations of resilience across the life span.

On robust face recognition via sparse coding: The good, the bad and the ugly

In the field of face recognition, sparse representation (SR) has received considerable attention during the past few years, with a focus on holistic descriptors in closed-set identification applications. The underlying assumption in such SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such an assumption is easily violated in the face verification scenario, where the task is to determine if two faces (where one or both have not been seen before) belong to the same person. In this study, the authors propose an alternative approach to SR-based face verification, where SR encoding is performed on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which then form an overall face descriptor. Owing to the deliberate loss of spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment and various image deformations. Within the proposed framework, they evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN) and an implicit probabilistic technique based on Gaussian mixture models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, on both the traditional closed-set identification task and the more applicable face verification task. The experiments also show that l1-minimisation-based encoding has a considerably higher computational cost when compared with SANN-based and probabilistic encoding, but leads to higher recognition rates.

Supervising practice: Perspectives on the supervision of creative practice higher degrees by research

PhD supervision is a particularly complex form of pedagogical practice, and nowhere is its complexity more apparent than in new and emergent fields, such as creative practice Higher Degrees by Research (HDRs) where supervisors face the challenges of a unique, uncharted area of research training. While there is an increasing body of literature on postgraduate supervision, and another emerging body of research into what creative practice/practice-led/practice-based research is, so far little attention has been paid to matters associated with research education leadership and pedagogical aspects of supervision in creative practice disciplines.For this reason, this special issue brings together a range of perspectives on the supervision of creative practice PhDs in visual and performing arts, media production, creative writing, and design.

Application of image processing techniques for frog call classification

Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

The modern day bystander: Online and face-to-face bystander actions of adolescents in traditional bullying and cyberbullying

This study investigated whether bystanders of traditional bullying and cyberbullying used face-to-face methods, online methods or both methods when reporting, discouraging and providing support to the victims of traditional bullying and cyberbullying. A questionnaire was completed by 348 high school students (Years 7 – 12) from seven independent schools in Australia. Overall, students predominantly utilized face-to-face methods when reporting to others for both types of bullying. Older students were more likely to use online methods to discourage the traditional bully (i.e., asking the bully to stop). Males and older students were more likely to use online methods to support victims of traditional bullying. Females were more likely to use face-to-face methods to support victims of cyberbullying. Implications for practice and future research are discussed.

Functional activation during the Rapid Visual Information Processing task in a middle aged cohort: An fMRI study

The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.