Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing

A multivariate comparison of electroencephalogram and functional magnetic resonance imaging to electrocorticogram using visual object representations in humans

Today, most neurocognitive studies in humans employ the non-invasive neuroimaging techniques functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG). However, how the data provided by fMRI and EEG relate exactly to the underlying neural activity remains incompletely understood. Here, we aimed to understand the relation between EEG and fMRI data at the level of neural population codes using multivariate pattern analysis. In particular, we assessed whether this relation is affected when we change stimuli or introduce identity-preserving variations to them. For this, we recorded EEG and fMRI data separately from 21 healthy participants while participants viewed everyday objects in different viewing conditions, and then related the data to electrocorticogram (ECoG) data recorded for the same stimulus set from epileptic patients. The comparison of EEG and ECoG data showed that object category signals emerge swiftly in the visual system and can be detected by both EEG and ECoG at similar temporal delays after stimulus onset. The correlation between EEG and ECoG was reduced when object representations tolerant to changes in scale and orientation were considered. The comparison of fMRI and ECoG overall revealed a tighter relationship in occipital than in temporal regions, related to differences in fMRI signal-to-noise ratio. Together, our results reveal a complex relationship between fMRI, EEG, and ECoG signals at the level of population codes that critically depends on the time point after stimulus onset, the region investigated, and the visual contents used

A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans

Converging reports indicate that face images are processed through specialized neural networks in the brain –i.e. face patches in monkeys and the fusiform face area (FFA) in humans. These studies were designed to find out how faces are processed in visual system compared to other objects. Yet, the underlying mechanism of face processing is not completely revealed. Here, we show that a hierarchical computational model, inspired by electrophysiological evidence on face processing in primates, is able to generate representational properties similar to those observed in monkey face patches (posterior, middle and anterior patches). Since the most important goal of sensory neuroscience is linking the neural responses with behavioral outputs, we test whether the proposed model, which is designed to account for neural responses in monkey face patches, is also able to predict well-documented behavioral face phenomena observed in humans. We show that the proposed model satisfies several cognitive face effects such as: composite face effect and the idea of canonical face views. Our model provides insights about the underlying computations that transfer visual information from posterior to anterior face patches

Health economic analysis of the integrated cognitive assessment tool to aid dementia diagnosis in the United Kingdom

ObjectivesThe aim of this study was to develop a comprehensive economic evaluation of the integrated cognitive assessment (ICA) tool compared with standard cognitive tests when used for dementia screening in primary care and for initial patient triage in memory clinics.MethodsICA was compared with standard of care comprising a mixture of cognitive assessment tools over a lifetime horizon and employing the UK health and social care perspective. The model combined a decision tree to capture the initial outcomes of the cognitive testing with a Markov structure that estimated long-term outcomes of people with dementia. Quality of life outcomes were quantified using quality-adjusted life years (QALYs), and the economic benefits were assessed using net monetary benefit (NMB). Both costs and QALYs were discounted at 3.5% per annum and cost-effectiveness was assessed using a threshold of £20,000 per QALY gained.ResultsICA dominated standard cognitive assessment tools in both the primary care and memory clinic settings. Introduction of the ICA tool was estimated to result in a lifetime cost saving of approximately £123 and £226 per person in primary care and memory clinics, respectively. QALY gains associated with early diagnosis were modest (0.0016 in primary care and 0.0027 in memory clinic). The net monetary benefit (NMB) of ICA introduction was estimated at £154 in primary care and £281 in the memory clinic settings.ConclusionIntroduction of ICA as a tool to screen primary care patients for dementia and perform initial triage in memory clinics could be cost saving to the UK public health and social care payer

Evaluation of self-esteem in children with attention-deficit/hyperactivity disorder based on event-related potential

Background: Self-esteem, the value we place on ourselves, has been associated with effects on health, and life satisfaction. Many studies reported that children with attention-deficit/hyperactivity disorder (ADHD) suffer from low self-esteem has been associated with negative life outcomes. The present study investigated neural correlation of self-esteem in this group compared with typically developing children using the event-related potentials (ERP). Materials and Methods: A total number of 10 children with ADHD were compared with 10 typically developing children matched with their age, gender and IQs. We employed the event-related potential (ERP) technique to explore neural manifestations of implicit self-esteem using the Go/Nogo association task (GNAT). Participants generated a response (Go) or withheld a response (Nogo) to self-words and good or bad attributed. Result: ERP results showed delayed N200 response in frontal areas in bad condition in normal children compared to ADHD children (p <0.05), indicating positive self-esteem. Conclusion: The present study provides neural evidence for probably low self-esteem in ADHD children

Health economic analysis of the integrated cognitive assessment tool to aid dementia diagnosis in the United Kingdom.

ObjectivesThe aim of this study was to develop a comprehensive economic evaluation of the integrated cognitive assessment (ICA) tool compared with standard cognitive tests when used for dementia screening in primary care and for initial patient triage in memory clinics.MethodsICA was compared with standard of care comprising a mixture of cognitive assessment tools over a lifetime horizon and employing the UK health and social care perspective. The model combined a decision tree to capture the initial outcomes of the cognitive testing with a Markov structure that estimated long-term outcomes of people with dementia. Quality of life outcomes were quantified using quality-adjusted life years (QALYs), and the economic benefits were assessed using net monetary benefit (NMB). Both costs and QALYs were discounted at 3.5% per annum and cost-effectiveness was assessed using a threshold of £20,000 per QALY gained.ResultsICA dominated standard cognitive assessment tools in both the primary care and memory clinic settings. Introduction of the ICA tool was estimated to result in a lifetime cost saving of approximately £123 and £226 per person in primary care and memory clinics, respectively. QALY gains associated with early diagnosis were modest (0.0016 in primary care and 0.0027 in memory clinic). The net monetary benefit (NMB) of ICA introduction was estimated at £154 in primary care and £281 in the memory clinic settings.ConclusionIntroduction of ICA as a tool to screen primary care patients for dementia and perform initial triage in memory clinics could be cost saving to the UK public health and social care payer

A general-purpose mechanism of visual feature association in visual word identification and beyond

As writing systems are a relatively novel invention (slightly over 5 kya),1 they could not have influenced the evolution of our species. Instead, reading might recycle evolutionary older mechanisms that originally supported other tasks2,3 and preceded the emergence of written language. Accordingly, it has been shown that baboons and pigeons can be trained to distinguish words from nonwords based on orthographic regularities in letter co-occurrence.4,5 This suggests that part of what is usually considered reading-specific processing could be performed by domain-general visual mechanisms. Here, we tested this hypothesis in humans: if the reading system relies on domain-general visual mechanisms, some of the effects that are often found with orthographic material should also be observable with non-orthographic visual stimuli. We performed three experiments using the same exact design but with visual stimuli that progressively departed from orthographic material. Subjects were passively familiarized with a set of composite visual items and tested in an oddball paradigm for their ability to detect novel stimuli. Participants showed robust sensitivity to the co-occurrence of features (\u201cbigram\u201d coding) with strings of letter-like symbols but also with made-up 3D objects and sinusoidal gratings. This suggests that the processing mechanisms involved in the visual recognition of novel words also support the recognition of other novel visual objects. These mechanisms would allow the visual system to capture statistical regularities in the visual environment.6\u20139 We hope that this work will inspire models of reading that, although addressing its unique aspects, place it within the broader context of vision. Vidal et al. show that an effect usually studied in the context of reading\u2014sensitivity to bigram frequencies\u2014is also found when participants are presented with images of objects and circular sinusoidal gratings. This suggests that some mechanisms implied in the processing of novel words are in fact of general purpose

How biological attention mechanisms improve task performance in a large-scale visual system model

How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives