Overlapping Activation Patterns Research Articles

Spatiotemporal interactions between jaguars (Panthera onca) and their potential prey in Amazonian islands

AbstractAlthough large carnivores usually prefer large prey, in some situations, they may shift their predation patterns towards smaller but abundant prey. The jaguar (Panthera onca) is a large carnivore capable of changing its diet according to prey and habitat availability. Here, we assessed the temporal and spatiotemporal interactions between jaguars and their prey in the Maracá‐Jipioca Islands (Northeastern Amazon, Brazil) through camera traps. We assessed overlapping activity patterns and tested for spatiotemporal segregation/avoidance between jaguars and nine potential prey species. We used a time‐to‐encounter approach, which consists in calculating the minimum time between prey and jaguar's detections, and vice versa, for each record of preys' species at a specific camera trap station, which translates into aggregation or avoidance behaviors. We found that these insular jaguars are more active in daylight periods when most of their prey are active and in locations used by species that cannot become nocturnal to avoid predators due to morphology constraints. Four prey species (great egret, white‐tailed deer, muscovy duck, and black‐and‐white tegu) presented moderate activity overlapping with jaguars. Agoutis and white‐tailed deer seek to spatiotemporally segregate from jaguars, although jaguars did not show spatiotemporal aggregation with any of the evaluated prey. Understanding the spatiotemporal dynamics is essential to establish the islands' trophic network composition and structure. This is fundamental information to efficiently allocate efforts for reducing costs and maximizing benefits in managing this population aiming to protect and conserve it, and consequently, the related ecosystems.

Overlapping representations of observed actions and action-related features.

The lateral occipitotemporal cortex (LOTC) has been shown to capture the representational structure of a smaller range of actions. In the current study, we carried out an fMRI experiment in which we presented human participants with images depicting 100 different actions and used representational similarity analysis (RSA) to determine which brain regions capture the semantic action space established using judgments of action similarity. Moreover, to determine the contribution of a wide range of action-related features to the neural representation of the semantic action space we constructed an action feature model on the basis of ratings of 44 different features. We found that the semantic action space model and the action feature model are best captured by overlapping activation patterns in bilateral LOTC and ventral occipitotemporal cortex (VOTC). An RSA on eight dimensions resulting from principal component analysis carried out on the action feature model revealed partly overlapping representations within bilateral LOTC, VOTC, and the parietal lobe. Our results suggest spatially overlapping representations of the semantic action space of a wide range of actions and the corresponding action-related features. Together, our results add to our understanding of the kind of representations along the LOTC that support action understanding.

Integrative views of representations and processes in morphology: an introduction

AbstractOne of the most enduring conceptualisations of the language architecture rests on a modular subdivision of work between lexical representations of stored items on the one hand, and dynamic processes, modelled as procedural rules working on such items, on the other hand. In morphology, network-based approaches have suggested an alternative “integrative” view of word representations and processes, where lexical representations consist of partially overlapping activation patterns spreading over several processing units. From this integrative perspective, the resulting network is both a lexicon and a word processor. We argue that the network-based view provides a stimulating research framework for several complementary levels of language inquiry (including theoretical, computational and neuro-psychological approaches) to be fruitfully integrated into a novel, comprehensive understanding of morphology. We discuss some implications of this view and delineate prospects of progress in this area.

Computational imaging during video game playing shows dynamic synchronization of cortical and subcortical networks of emotions.

Emotions are multifaceted phenomena affecting mind, body, and behavior. Previous studies sought to link particular emotion categories (e.g., fear) or dimensions (e.g., valence) to specific brain substrates but generally found distributed and overlapping activation patterns across various emotions. In contrast, distributed patterns accord with multi-componential theories whereby emotions emerge from appraisal processes triggered by current events, combined with motivational, expressive, and physiological mechanisms orchestrating behavioral responses. According to this framework, components are recruited in parallel and dynamically synchronized during emotion episodes. Here, we use functional MRI (fMRI) to investigate brain-wide systems engaged by theoretically defined components and measure their synchronization during an interactive emotion-eliciting video game. We show that each emotion component recruits large-scale cortico-subcortical networks, and that moments of dynamic synchronization between components selectively engage basal ganglia, sensory-motor structures, and midline brain areas. These neural results support theoretical accounts grounding emotions onto embodied and action-oriented functions triggered by synchronized component processes.

Principles of Mutual Information Maximization and Energy Minimization Affect the Activation Patterns of Large Scale Networks in the Brain.

Successive patterns of activation and deactivation in local areas of the brain indicate the mechanisms of information processing in the brain. It is possible that this process can be optimized by principles, such as the maximization of mutual information and the minimization of energy consumption. In the present paper, I showed evidence for this argument by demonstrating the correlation among mutual information, the energy of the activation, and the activation patterns. Modeling the information processing based on the functional connectome datasets of the human brain, I simulated information transfer in this network structure. Evaluating the statistical quantities of the different network states, I clarified the correlation between them. First, I showed that mutual information and network energy have a close relationship, and that the values are maximized and minimized around a same network state. This implies that there is an optimal network state in the brain that is organized according to the principles regarding mutual information and energy. On the other hand, the evaluation of the network structure revealed that the characteristic network structure known as the criticality also emerges around this state. These results imply that the characteristic features of the functional network are also affected strongly by these principles. To assess the functional aspects of this state, I investigated the output activation patterns in response to random input stimuli. Measuring the redundancy of the responses in terms of the number of overlapping activation patterns, the results indicate that there is a negative correlation between mutual information and the redundancy in the patterns, suggesting that there is a trade-off between communication efficiency and robustness due to redundancy, and the principles of mutual information and network energy are important to network formation and its function in the human brain.

Temporal coexistence in a carnivore assemblage from central Mexico: temporal-domain dependence

Species coexistence at a given locality generally implies segregation along one of the three resource dimensions of the ecological niche: spatial, trophic or temporal. Temporal activity patterns of species are ecologically important as they expose how species exploit their environments. Using camera traps, we evaluated the temporal activity patterns and temporal overlap for a mammalian carnivore assemblage from Sierra Nanchititla Natural Park, central Mexico. We characterized and compared temporal activity patterns and temporal overlap between species pairs using circular statistics. Temporal overlap was analyzed using three temporal domains (full diel, diurnal, and nocturnal), and null models were used to contrast the empirical assemblage-wide temporal overlap in relation to randomly generated distributions. We found that pair-wise temporal overlap comparisons among species were quite heterogeneous and dependent on the temporal domain used for the analyses. Two major inferences can be derived from pair-wise analyses and the null model: (a) most of the carnivore assemblage show a nocturnal activity pattern in common and (b) most of the pair-wise comparisons indicate temporal segregation among species. The highest temporal overlap at the assemblage-wide level was found when only the nocturnal domain was evaluated and we found coincident temporal activities at the full domain level, independent of the temporal resolution used. Overall, our results suggest that carnivores with distinct trophic and habitat use like the margay (Leopardus wiedii) and gray fox (Urocyon cinereoargenteus) had temporal overlapping activity patterns to full diel and nocturnal domains, and species with similar trophic and habitat use always presented temporal segregation (gray fox and white-nosed coati, Nasua narica). Finally, species with predator-prey relationships (white-nosed coati and cougar, Puma concolor) showed segregation during the day but overlap at night. Our results indicate that species temporal activity patterns likely change in relation to different interspecific interactions such as predation and competition to allow species coexistence within this carnivore assemblage.

Reproducibility of importance extraction methods in neural network based fMRI classification

Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have proved useful in functional magnetic resonance imaging (fMRI) studies, there are concerns regarding extraction, reproducibility and visualization of brain regions that contribute most significantly to the classification. We addressed these issues using an fMRI classification scheme based on neural networks and compared a set of methods for extraction of category-related voxel importances in three simulated and two empirical datasets. The simulation data revealed that the proposed scheme successfully detects spatially distributed and overlapping activation patterns upon successful classification. Application of the proposed classification scheme to two previously published empirical fMRI datasets revealed robust importance maps that extensively overlap with univariate maps but also provide complementary information. Our results demonstrate increased statistical power of importance maps compared to univariate approaches for both detection of overlapping patterns and patterns with weak univariate information.

Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks

Pattern separation is a fundamental function of the brain. The divergent feedforward networks thought to underlie this computation are widespread, yet exhibit remarkably similar sparse synaptic connectivity. Marr-Albus theory postulates that such networks separate overlapping activity patterns by mapping them onto larger numbers of sparsely active neurons. But spatial correlations in synaptic input and those introduced by network connectivity are likely to compromise performance. To investigate the structural and functional determinants of pattern separation we built models of the cerebellar input layer with spatially correlated input patterns, and systematically varied their synaptic connectivity. Performance was quantified by the learning speed of a classifier trained on either the input or output patterns. Our results show that sparse synaptic connectivity is essential for separating spatially correlated input patterns over a wide range of network activity, and that expansion and correlations, rather than sparse activity, are the major determinants of pattern separation.

Dissociating maternal responses to sad and happy facial expressions of their own child: An fMRI study.

BackgroundMaternal sensitive behavior depends on recognizing one’s own child’s affective states. The present study investigated distinct and overlapping neural responses of mothers to sad and happy facial expressions of their own child (in comparison to facial expressions of an unfamiliar child).MethodsWe used functional MRI to measure dissociable and overlapping activation patterns in 27 healthy mothers in response to happy, neutral and sad facial expressions of their own school-aged child and a gender- and age-matched unfamiliar child. To investigate differential activation to sad compared to happy faces of one’s own child, we used interaction contrasts. During the scan, mothers had to indicate the affect of the presented face. After scanning, they were asked to rate the perceived emotional arousal and valence levels for each face using a 7-point Likert-scale (adapted SAM version).ResultsWhile viewing their own child’s sad faces, mothers showed activation in the amygdala and anterior cingulate cortex whereas happy facial expressions of the own child elicited activation in the hippocampus. Conjoint activation in response to one’s own child happy and sad expressions was found in the insula and the superior temporal gyrus.ConclusionsMaternal brain activations differed depending on the child’s affective state. Sad faces of the own child activated areas commonly associated with a threat detection network, whereas happy faces activated reward related brain areas. Overlapping activation was found in empathy related networks. These distinct neural activation patterns might facilitate sensitive maternal behavior.

Contextual and Perceptual Brain Processes Underlying Moral Cognition: A Quantitative Meta-Analysis of Moral Reasoning and Moral Emotions

Background and ObjectivesHuman morality has been investigated using a variety of tasks ranging from judgments of hypothetical dilemmas to viewing morally salient stimuli. These experiments have provided insight into neural correlates of moral judgments and emotions, yet these approaches reveal important differences in moral cognition. Moral reasoning tasks require active deliberation while moral emotion tasks involve the perception of stimuli with moral implications. We examined convergent and divergent brain activity associated with these experimental paradigms taking a quantitative meta-analytic approach.Data SourceA systematic search of the literature yielded 40 studies. Studies involving explicit decisions in a moral situation were categorized as active (n = 22); studies evoking moral emotions were categorized as passive (n = 18). We conducted a coordinate-based meta-analysis using the Activation Likelihood Estimation to determine reliable patterns of brain activity.Results & ConclusionsResults revealed a convergent pattern of reliable brain activity for both task categories in regions of the default network, consistent with the social and contextual information processes supported by this brain network. Active tasks revealed more reliable activity in the temporoparietal junction, angular gyrus and temporal pole. Active tasks demand deliberative reasoning and may disproportionately involve the retrieval of social knowledge from memory, mental state attribution, and construction of the context through associative processes. In contrast, passive tasks reliably engaged regions associated with visual and emotional information processing, including lingual gyrus and the amygdala. A laterality effect was observed in dorsomedial prefrontal cortex, with active tasks engaging the left, and passive tasks engaging the right. While overlapping activity patterns suggest a shared neural network for both tasks, differential activity suggests that processing of moral input is affected by task demands. The results provide novel insight into distinct features of moral cognition, including the generation of moral context through associative processes and the perceptual detection of moral salience.

Interactions between Auditory and Visual Semantic Stimulus Classes: Evidence for Common Processing Networks for Speech and Body Actions

Incongruencies between auditory and visual signals negatively affect human performance and cause selective activation in neuroimaging studies; therefore, they are increasingly used to probe audiovisual integration mechanisms. An open question is whether the increased BOLD response reflects computational demands in integrating mismatching low-level signals or reflects simultaneous unimodal conceptual representations of the competing signals. To address this question, we explore the effect of semantic congruency within and across three signal categories (speech, body actions, and unfamiliar patterns) for signals with matched low-level statistics. In a localizer experiment, unimodal (auditory and visual) and bimodal stimuli were used to identify ROIs. All three semantic categories cause overlapping activation patterns. We find no evidence for areas that show greater BOLD response to bimodal stimuli than predicted by the sum of the two unimodal responses. Conjunction analysis of the unimodal responses in each category identifies a network including posterior temporal, inferior frontal, and premotor areas. Semantic congruency effects are measured in the main experiment. We find that incongruent combinations of two meaningful stimuli (speech and body actions) but not combinations of meaningful with meaningless stimuli lead to increased BOLD response in the posterior STS (pSTS) bilaterally, the left SMA, the inferior frontal gyrus, the inferior parietal lobule, and the anterior insula. These interactions are not seen in premotor areas. Our findings are consistent with the hypothesis that pSTS and frontal areas form a recognition network that combines sensory categorical representations (in pSTS) with action hypothesis generation in inferior frontal gyrus/premotor areas. We argue that the same neural networks process speech and body actions.

Retention of identity versus expression of emotional faces differs in the recruitment of limbic areas

Faces are multidimensional stimuli that convey information for complex social and emotional functions. Separate neural systems have been implicated in the recognition of facial identity (mainly extrastriate visual cortex) and emotional expression (limbic areas and the superior temporal sulcus). Working-memory (WM) studies with faces have shown different but partly overlapping activation patterns in comparison to spatial WM in parietal and prefrontal areas. However, little is known about the neural representations of the different facial dimensions during WM. In the present study 22 subjects performed a face-identity or face-emotion WM task at different load levels during functional magnetic resonance imaging. We found a fronto-parietal-visual WM-network for both tasks during maintenance, including fusiform gyrus. Limbic areas in the amygdala and parahippocampal gyrus demonstrated a stronger activation for the identity than the emotion condition. One explanation for this finding is that the repetitive presentation of faces with different identities but the same emotional expression during the identity-task is responsible for the stronger increase in BOLD signal in the amygdala. These results raise the question how different emotional expressions are coded in WM. Our findings suggest that emotional expressions are re-coded in an abstract representation that is supported at the neural level by the canonical fronto-parietal WM network.

Plasticity of multisensory dorsal stream functions: Evidence from congenitally blind and sighted adults

The dorsal stream has been proposed to compute vision for space perception and for the control of action. However, perceiving space and guiding movements is not only based on vision but also on other sensory modalities such as proprioception and kinesthesia. Blind people who lost vision early in life provide an exceptional example to study the plasticity of dorsal stream functions. Using fMRI and psychophysical methods, action control and space perception was investigated in congenitally blind and sighted adults while performing active and passive hand movements without visual feedback. The functional imaging data showed largely overlapping activation patterns for kinesthetically guided hand movements in congenitally blind and sighted participants covering regions of the dorsal stream. In contrast to the sighted participants, congenitally blind participants additionally activated the extrastriate cortex and the auditory cortex. The psychophysical results revealed a significant correlation between proprioceptive spatial discrimination acuity of the blind and the age when they had attended an orientation and mobility training, i.e., an extensive non-visual spatial training. The earlier the blind acquired such a spatial training the more accurate and the more precise was their space perception in later life. Our findings suggest a multisensory network of movement control that develops on the basis of sensorimotor feedback rather than being under the exclusive control of vision. Thus, visual deprivation seems to result in both cross-modal and compensatory intra-modal plasticity. The present findings further imply that dorsal stream functions are shaped by non-visual spatial information during early development.

How moving objects become animated: The human mirror neuron system assimilates non-biological movement patterns

The so-called mirror neuron system (MNS) responds when humans observe actions performed by a member of their own species. This activity is understood as an internal motor representation of the observed movement pattern. By contrasting meaningless human hand movements with meaningless artificial movements of objects in space, we tested the claim that exclusively movements belonging to the human motor repertoire have direct access to the MNS. Eighteen participants observed video clips of moving hands and objects while the hemodynamic response was recorded with functional magnetic resonance imaging. Second-level analysis of the hemodynamic response revealed substantially overlapping activation patterns for both types of movements including relevant structures of the MNS (bilateral premotor and parietal areas, occipito-temporal junction, postcentral gyrus and the right superior temporal sulcus). This suggests that perceptual processing of moving hands and objects recruits similar and overlapping cortical networks. Direct comparison of the two movement types revealed stronger activations for hand movements mainly in structures of the MNS suggesting an “expertise effect”. Overall, our results provide evidence that observing movements not explicitly belonging to the human motor repertoire can activate the human MNS, most likely because an association with a biological movement is evoked.

Glomerular activation patterns and the perception of odor mixtures

Odor mixtures can produce several qualitatively different percepts; it is not known at which stage of processing these are determined. We asked if activity within the first stage of olfactory processing, the glomerular layer of the olfactory bulb, predicts odor mixture perception. We characterized how mice respond to components after training to five different mixture ratios of pentanal and hexanal, and found two types of responses: elemental perception and overshadowing. We then used intrinsic signal imaging to observe glomerular activity in response to the same mixtures and their components. As has been previously described, glomerular activity patterns produced by mixtures resemble the linear combination of responses to components. Mice trained to identify mixtures with more hexanal than pentanal recognized hexanal but not pentanal when the odorants were presented alone (overshadowing). Consistent with these behavioral responses, the imaged activity pattern in response to mixtures was similar to that produced to hexanal alone. Moreover, there was no significant effect of glomerular inhibition in the imaged response. In contrast, the glomerular activity patterns did not predict elemental perception: when trained to identify mixtures with more pentanal than hexanal, mice recognized both components equally well, even with highly overlapping activation patterns. This suggests that spatial activity patterns within the olfactory bulb are not always sufficient to specify component recognition in mixtures.

Active processing in visual and visuospatial working memory

Keywords Visual AE Visuospatial working memory AEfMRI AE Mental rotationBackgroundA distinction between visual and visuospatial workingmemory is discussed recently in the literature. Thepresent study aimed to investigate whether similarneuronal mechanisms underlie the manipulation andactive processing of visual and visuospatial stimuli withlow and high working memory demands.MethodsSimultaneous and successive mental rotation andidentity judgement of 2-D matrices and 3-D cubefigures were contrasted using functional MagneticResonance Imaging (fMRI).ResultsResults demonstrate that activation patterns duringmental rotation with low working memory demandsdiffer depending on stimulus type (2-D vs. 3-D).Comparison of simultaneous mental rotation ofmatrices and 3-D cubes resulted in activation of frontalas well as inferior and superior parietal cortices. Theopposite contrast (mental rotation of 3-D cubes vs. 2-Dmatrices) yielded only frontal cortex activation. Mentalrotation of 2-D matrices and 3-D cubes with increasedworking memory demands yielded nearly overlappingactivation patterns.ConclusionConverging and overlapping activation patterns for2-D and 3-D stimuli with increased working memorydemands suggest that visual and visuospatial workingmemory share the same neural mechanism under spe-cific conditions (see Suchan et al. 2006). Results arediscussed in terms of the distributed ‘continuum’model as suggested by Cornoldi and Vecchi (2000).References

Neural substrates of manipulation in visuospatial working memory

The present study aimed to investigate in humans whether similar neuronal mechanisms underlie the manipulation and active processing of visual and visuospatial stimuli. Simultaneous and successive mental rotation and identity judgment of 2-D matrices and 3-D cube figures were contrasted using functional magnetic resonance imaging (fMRI). Results demonstrate that activation patterns during mental rotation with low working memory demands differ depending on stimulus type (2-D vs. 3-D). Comparison of simultaneous mental rotation of matrices and 3-D cubes resulted in activation of frontal as well as inferior and superior parietal cortices. The opposite contrast (mental rotation of 3-D cubes vs. 2-D matrices) yielded only frontal cortex activation. The findings also yield evidence for converging, overlapping activation patterns for 2-D and 3-D stimuli if working memory demands are increased. Results are discussed within the framework of current working memory models.

Deep processing activates the medial temporal lobe in young but not in old adults

Age-related impairments in episodic memory have been related to a deficiency in semantic processing, based on the finding that elderly adults typically benefit less than young adults from deep, semantic as opposed to shallow, nonsemantic processing of study items. In the present study, we tested the hypothesis that elderly adults are not able to perform certain cognitive operations under deep processing conditions. We further hypothesised that this inability does not involve regions commonly associated with lexical/semantic retrieval processes, but rather involves a dysfunction of the medial temporal lobe (MTL) memory system. To this end, we used functional MRI on rather extensive groups of young and elderly adults to compare brain activity patterns obtained during a deep (living/nonliving) and a shallow (uppercase/lowercase) classification task. Common activity in relation to semantic classification was observed in regions that have been previously related to semantic retrieval, including mainly left-lateralised activity in the inferior prefrontal, middle temporal, and middle frontal/anterior cingulate gyrus. Although the young adults showed more activity in some of these areas, the finding of mainly overlapping activation patterns during semantic classification supports the idea that lexical/semantic retrieval processes are still intact in elderly adults. This received further support by the finding that both groups showed similar behavioural performances as well on the deep and shallow classification tasks. Importantly, though, the young revealed significantly more activity than the elderly adults in the left anterior hippocampus during deep relative to shallow classification. This finding is in line with the idea that age-related impairments in episodic encoding are, at least partly, due to an under-recruitment of the medial temporal lobe memory system.

Chemotopic, Combinatorial, and Noncombinatorial Odorant Representations in the Olfactory Bulb Revealed Using a Voltage-Sensitive Axon Tracer

Odor information is first represented in the brain by patterns of input activity across the glomeruli of the olfactory bulb (OB). To examine how odorants are represented at this stage of olfactory processing, we labeled anterogradely the axons of olfactory receptor neurons with the voltage-sensitive dye Di8-ANEPPQ in zebrafish. The activity induced by diverse natural odorants in afferent axons and across the array of glomeruli was then recorded optically. The results show that certain subregions of the OB are preferentially activated by defined chemical odorant classes. Within these subregions, "ordinary" odorants (amino acids, bile acids, and nucleotides) induce overlapping activity patterns involving multiple glomeruli, indicating that they are represented by combinatorial activity patterns. In contrast, two putative pheromone components (prostaglandin F2alpha and 17alpha, 20beta-dihydroxy-4-pregnene-3-one-20-sulfate) each induce a single focus of activity, at least one of which comes from a single, highly specific and sensitive glomerulus. These results indicate that the OB is organized into functional subregions processing classes of odorants. Furthermore, they suggest that individual odorants can be represented by "combinatorial" or "noncombinatorial" (focal) activity patterns and that the latter may serve to process odorants triggering distinct responses such as that of pheromones.