A specific and rapid neural signature for parental instinct

Darwin originally pointed out that there is something about infants which prompts adults to respond to and care for them, in order to increase individual fitness, i.e. reproductive success, via increased survivorship of one's own offspring. Lorenz proposed that it is the specific structure of the infant face that serves to elicit these parental responses, but the biological basis for this remains elusive. Here, we investigated whether adults show specific brain responses to unfamiliar infant faces compared to adult faces, where the infant and adult faces had been carefully matched across the two groups for emotional valence and arousal, as well as size and luminosity. The faces also matched closely in terms of attractiveness. Using magnetoencephalography (MEG) in adults, we found that highly specific brain activity occurred within a seventh of a second in response to unfamiliar infant faces but not to adult faces. This activity occurred in the medial orbitofrontal cortex (mOFC), an area implicated in reward behaviour, suggesting for the first time a neural basis for this vital evolutionary process. We found a peak in activity first in mOFC and then in the right fusiform face area (FFA). In mOFC the first significant peak (p<0.001) in differences in power between infant and adult faces was found at around 130 ms in the 10-15 Hz band. These early differences were not found in the FFA. In contrast, differences in power were found later, at around 165 ms, in a different band (20-25 Hz) in the right FFA, suggesting a feedback effect from mOFC. These findings provide evidence in humans of a potential brain basis for the "innate releasing mechanisms" described by Lorenz for affection and nurturing of young infants. This has potentially important clinical applications in relation to postnatal depression, and could provide opportunities for early identification of families at risk.

The effect of inversion on the encoding of normal and “thatcherized” faces

In the "Thatcher illusion" a face, in which the eyes and mouth are inverted relative to the rest of the face, looks grotesque when shown upright but not when inverted. In four experiments we investigated the contribution of local and global processing to this illusion in normal observers. We examined inversion effects (i.e., better performance for upright than for inverted faces) in a task requiring discrimination of whether faces were or were not "thatcherized". Observers made same/different judgements to isolated face parts (Experiments 1-2) and to whole faces (Experiments 3-4). Face pairs had the same or different identity, allowing for different processing strategies using feature-based or configural information, respectively. In Experiment 1, feature-based matching of same-person face parts yielded only a small inversion effect for normal face parts. However, when feature-based matching was prevented by using the face parts of different people on all trials (Experiment 2) an inversion effect occurred for normal but not for thatcherized parts. In Experiments 3 and 4, inversion effects occurred with normal but not with thatcherized whole faces, on both same- and different-person matching tasks. This suggests that a common configural strategy was used with whole (normal) faces. Face context facilitated attention to misoriented parts in same-person but not in different-person matching. The results indicate that (1) face inversion disrupts local configural processing, but not the processing of image features, and (2) thatcherization disrupts local configural processing in upright faces.

Nonlinearity compensation via spectral inversion and digital back-propagation:a practical approach

We report performance enhancements enabled by pre-dispersed spectral inversion equivalent to that of ideal back-propagation, with further x2 increase in reach from multi-channel compensation, with spectral inversion employed upto 400km (from mid-link) with <1dB penalties. © 2012 OSA.

Comparative quantitative study of ‘signature’ pathological lesions in the hippocampus and adjacent gyri of 12 neurodegenerative disorders

The hippocampus (HC) and adjacent gyri are implicated in dementia in several neurodegenerative disorders. To compare HC pathology among disorders, densities of ‘signature’ pathological lesions were measured at a standard location in eight brain regions of 12 disorders. Principal components analysis of the data suggested that the disorders could be divided into three groups: (1) Alzheimer’s disease (AD), Down’s syndrome (DS), sporadic Creutzfeldt–Jakob disease, and variant Creutzfeldt–Jakob disease in which either β-amyloid (Aβ) or prion protein deposits were distributed in all sectors of the HC and adjacent gyri, with high densities being recorded in the parahippocampal gyrus and subiculum; (2) Pick’s disease, sporadic frontotemporal lobar degeneration with TDP-43 immunoreactive inclusions, and neuronal intermediate filament inclusion disease in which relatively high densities of neuronal cytoplasmic inclusions were present in the dentate gyrus (DG) granule cells; and (3) Parkinson’s disease dementia, dementia with Lewy bodies, progressive supranuclear palsy, corticobasal degeneration, and multiple system atrophy in which densities of signature lesions were relatively low. Variation in density of signature lesions in DG granule cells and CA1 were the most important sources of neuropathological variation among disorders. Hence, HC and adjacent gyri are differentially affected in dementia reflecting either variation in vulnerability of hippocampal neurons to specific molecular pathologies or in the spread of pathological proteins to the HC. Information regarding the distribution of pathology could ultimately help to explain variations in different cognitive domains, such as memory, observed in various disorders.

The average mixing matrix signature

Laplacian-based descriptors, such as the Heat Kernel Signature and the Wave Kernel Signature, allow one to embed the vertices of a graph onto a vectorial space, and have been successfully used to find the optimal matching between a pair of input graphs. While the HKS uses a heat di↵usion process to probe the local structure of a graph, the WKS attempts to do the same through wave propagation. In this paper, we propose an alternative structural descriptor that is based on continuoustime quantum walks. More specifically, we characterise the structure of a graph using its average mixing matrix. The average mixing matrix is a doubly-stochastic matrix that encodes the time-averaged behaviour of a continuous-time quantum walk on the graph. We propose to use the rows of the average mixing matrix for increasing stopping times to develop a novel signature, the Average Mixing Matrix Signature (AMMS). We perform an extensive range of experiments and we show that the proposed signature is robust under structural perturbations of the original graphs and it outperforms both the HKS and WKS when used as a node descriptor in a graph matching task.