Neural convergence and divergence in the mammalian cerebral cortex: from experimental neuroanatomy to functional neuroimaging

Asymmetry in synaptic connectivity balances redundancy and reachability in the Caenorhabditis elegans connectome

The brain is overall bilaterally symmetrical, but also exhibits considerable asymmetry. While symmetry may endow neural networks with robustness and resilience, asymmetry may enable parallel information processing and functional specialization. How is this tradeoff between symmetrical and asymmetrical brain architecture balanced? To address this, we focused on the Caenorhabditis elegans connectome, comprising 99 classes of bilaterally symmetrical neuron pairs. We found symmetry in the number of synaptic partners between neuron class members, but pronounced asymmetry in the identity of these synapses. We applied graph theoretical metrics for evaluating Redundancy, the selective reinforcement of specific neural paths by multiple alternative synaptic connections, and Reachability, the extent and diversity of synaptic connectivity of each neuron class. We found Redundancy and Reachability to be stochastically tunable by the level of network asymmetry, driving the C. elegans connectome to favor Redundancy over Reachability. These results elucidate fundamental relations between lateralized neural connectivity and function.

The emergence of identity, agency and consciousness from the temporal dynamics of neural elaboration

Identity-differentiating self from external reality-and agency-being the author of one's acts-are generally considered intrinsic properties of awareness and looked at as mental constructs generated by consciousness. Here a different view is proposed. All physiological systems display complex time-dependent regulations to adapt or anticipate external changes. To interact with rapid changes, an animal needs a nervous system capable of modelling and predicting (not simply representing) it. Different algorithms must be employed to predict the momentary location of an object based on sensory information (received with a delay), or to design in advance and direct the trajectory of movement. Thus, the temporal dynamics of external events and action must be handled in differential ways, thereby generating the distinction between self and non-self ("identity") as an intrinsic computational construct in neuronal elaboration. Handling time is not what neurons are designed for. Neuronal circuits are based on parallel processing: each bit of information diverges on many neurons, each of which combines it with many other data. Spike firing reports the likelihood that the specific pattern the neuron is designed to respond to is present in the incoming data. This organization seems designed to process synchronous datasets. However, since neural networks can introduce delays in processing, time sequences can be transformed into simultaneous patterns and analysed as such. This way predictive algorithms can be implemented, and continually improved through neuronal plasticity. To successfully interact with the external reality, the nervous system must model and predict, but also differentially handle perceptual functions or motor activity, by putting in register information that becomes available at different time moments. Also, to learn through positive/negative reinforcement, modelling must establish a causal relation between motor control and its consequences: the contrast between phase lag in perception and phase lead (and control) in motor programming produces the emergence of identity (discerning self from surrounding) and agency (control on actions) as necessary computational constructs to model reality. This does not require any form of awareness. In a brain, capable of producing awareness, these constructs may evolve from mere computational requirements into mental (conscious) constructs.

Grounded Cognition Entails Linguistic Relativity: A Neglected Implication of a Major Semantic Theory

According to the popular Grounded Cognition Model (GCM), the sensory and motor features of concepts, including word meanings, are stored directly within neural systems for perception and action. More precisely, the core claim is that these concrete conceptual features reuse some of the same modality-specific representations that serve to categorize experiences involving the relevant kinds of objects and events. Research in semantic typology, however, has shown that word meanings vary significantly across the roughly 6500 languages in the world. I argue that this crosslinguistic semantic diversity has significant yet previously unrecognized theoretical consequences for the GCM. In particular, to accommodate the typological data, the GCM must assume that the concrete features of word meanings are not merely stored within sensory/motor brain systems, but are represented there in ways that are, to a nontrivial degree, language-specific. Moreover, it must assume that these conceptual representations are also activated during the nonlinguistic processing of the relevant kinds of objects and events (e.g., during visual perception and action planning); otherwise, they would not really be grounded, which is to say, embedded inside sensory/motor systems. Crucially, however, such activations would constitute what is traditionally called linguistic relativity-that is, the influence of language-specific semantic structures on other forms of cognition. The overarching aim of this paper is to elaborate this argument more fully and explore its repercussions. To that end, I discuss in greater detail the key aspects of the GCM, the evidence for crosslinguistic semantic diversity, pertinent work on linguistic relativity, the central claim that the GCM entails linguistic relativity, some initial supporting results, and some important limitations and future directions.

Cardiac vagal afferent neurotransmission in health and disease: review and knowledge gaps

The meticulous control of cardiac sympathetic and parasympathetic tone regulates all facets of cardiac function. This precise calibration of cardiac efferent innervation is dependent on sensory information that is relayed from the heart to the central nervous system. The vagus nerve, which contains vagal cardiac afferent fibers, carries sensory information to the brainstem. Vagal afferent signaling has been predominantly shown to increase parasympathetic efferent response and vagal tone. However, cardiac vagal afferent signaling appears to change after cardiac injury, though much remains unknown. Even though subsequent cardiac autonomic imbalance is characterized by sympathoexcitation and parasympathetic dysfunction, it remains unclear if, and to what extent, vagal afferent dysfunction is involved in the development of vagal withdrawal. This review aims to summarize the current understanding of cardiac vagal afferent signaling under in health and in the setting of cardiovascular disease, especially after myocardial infarction, and to highlight the knowledge gaps that remain to be addressed.

Imagination: The dawn of consciousness: Fighting some misconceptions in the discussion about consciousness

Several theories of consciousness (ToC) have been proposed, but it is hard to integrate them into a consensus theory. Each theory has its merits, in dealing with some aspects of the question, but the terminology is inconsistent, each ToC aims at answering a different question, and there is not even a reasonable agreement about what 'consciousness' is in the first place. Some common implicit assumptions, and the way some critical words - such as 'sensation', 'perception', 'neural correlate of consciousness' (NCC) - are thought to relate to consciousness, have introduced a series of misconceptions that make it difficult to pinpoint what consciousness consists in and how it arises in the brain. The purpose of this contribution is twofold: firstly, to discern the various steps that lead from the detection of a stimulus to a conscious experience, by redefining terms such as sensation and perception with an adequate operative meaning; secondly, to emphasize the inevitable contribution of emotions and the active role of imagination in this process. The diffuse view, for the layperson but among scientists as well, is that the brain produces an internal 'representation' of the external reality and of oneself. This tends to consign one to a Cartesian perspective, i.e., the idea that some entity must be there to witness and interpret such representation. This approach splits the conscious experience into brain activity, which generates a (possible) content of consciousness (still unconscious), and a vaguely defined entity or process that 'generates' consciousness and injects (or sheds the light of) consciousness onto the content of brain activity. This way, however, we learn nothing about how such consciousness would arise. We propose here that consciousness is the function that generates a subjectively relevant and emotionally coloured internal image of the experience one is living. In this process, endogenous, spontaneous activity (imaginative activity, consisting in recalling and reviving memories, prefiguring consequences, analysing conjectures) produces many vague and ambiguous hints, rich of symbolic links, which compete in giving rise to an implicit, emotionally characterized, and semantically pleiotropic, internal experience. Cognitive elaboration may extract from this a defined and univocal, complete and consistent, explicit experience, that can be verbally reported ('what it is like to...').

Angular gyrus: an anatomical case study for association cortex

The angular gyrus is associated with a spectrum of higher order cognitive functions. This mini-review undertakes a broad survey of putative neuroanatomical substrates, guided by the premise that area-specific specializations derive from a combination of extrinsic connections and intrinsic area properties. Three levels of spatial resolution are discussed: cellular, supracellular connectivity, and synaptic micro-scale, with examples necessarily drawn mainly from experimental work with nonhuman primates. A significant factor in the functional specialization of the human parietal cortex is the pronounced enlargement. In addition to "more" cells, synapses, and connections, however, the heterogeneity itself can be considered an important property. Multiple anatomical features support the idea of overlapping and temporally dynamic membership in several brain wide subnetworks, but how these features operate in the context of higher cognitive functions remains for continued investigations.

Novel Cognitive Functions Arise at the Convergence of Macroscale Gradients

Functions in higher-order brain regions are the source of extensive debate. Although past trends have been to describe the brain-especially posterior cortical areas-in terms of a set of functional modules, a new emerging paradigm focuses on the integration of proximal functions. In this review, we synthesize emerging evidence that a variety of novel functions in the higher-order brain regions are due to convergence: convergence of macroscale gradients brings feature-rich representations into close proximity, presenting an opportunity for novel functions to arise. Using the TPJ as an example, we demonstrate that convergence is enabled via three properties of the brain: (1) hierarchical organization, (2) abstraction, and (3) equidistance. As gradients travel from primary sensory cortices to higher-order brain regions, information becomes abstracted and hierarchical, and eventually, gradients meet at a point maximally and equally distant from their sensory origins. This convergence, which produces multifaceted combinations, such as mentalizing another person's thought or projecting into a future space, parallels evolutionary and developmental characteristics in such regions, resulting in new cognitive and affective faculties.

Leveraging hierarchy in multimodal generative models for effective cross-modality inference

This work addresses the problem of cross-modality inference (CMI), i.e., inferring missing data of unavailable perceptual modalities (e.g., sound) using data from available perceptual modalities (e.g., image). We overview single-modality variational autoencoder methods and discuss three problems of computational cross-modality inference, arising from recent developments in multimodal generative models. Inspired by neural mechanisms of human recognition, we contribute the Nexus model, a novel hierarchical generative model that can learn a multimodal representation of an arbitrary number of modalities in an unsupervised way. By exploiting hierarchical representation levels, Nexus is able to generate high-quality, coherent data of missing modalities given any subset of available modalities. To evaluate CMI in a natural scenario with a high number of modalities, we contribute the "Multimodal Handwritten Digit" (MHD) dataset, a novel benchmark dataset that combines image, motion, sound and label information from digit handwriting. We access the key role of hierarchy in enabling high-quality samples during cross-modality inference and discuss how a novel training scheme enables Nexus to learn a multimodal representation robust to missing modalities at test time. Our results show that Nexus outperforms current state-of-the-art multimodal generative models in regards to their cross-modality inference capabilities.

Transsynaptic mapping of Drosophila mushroom body output neurons

The mushroom body (MB) is a well-characterized associative memory structure within the Drosophila brain. Analyzing MB connectivity using multiple approaches is critical for understanding the functional implications of this structure. Using the genetic anterograde transsynaptic tracing tool, trans-Tango, we identified divergent projections across the brain and convergent downstream targets of the MB output neurons (MBONs). Our analysis revealed at least three separate targets that receive convergent input from MBONs: other MBONs, the fan-shaped body (FSB), and the lateral accessory lobe (LAL). We describe, both anatomically and functionally, a multilayer circuit in which inhibitory and excitatory MBONs converge on the same genetic subset of FSB and LAL neurons. This circuit architecture enables the brain to update and integrate information with previous experience before executing appropriate behavioral responses. Our use of trans-Tango provides a genetically accessible anatomical framework for investigating the functional relevance of components within these complex and interconnected circuits.

The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex

Transcranial magnetic stimulation (TMS) is a noninvasive method to modulate brain activity and behavior in humans. Still, stimulation effects substantially vary across studies and individuals, thereby restricting the large-scale application of TMS in research or clinical settings. We revealed that low-frequency stimulation had opposite impact on the functional connectivity of sensory and cognitive brain regions. Biophysical modeling then identified a neuronal mechanism underlying these region-specific effects. Stimulation of the frontal cortex decreased local inhibition and disrupted feedforward and feedback connections. Conversely, identical stimulation increased local inhibition and enhanced forward signaling in the occipital cortex. Last, we identified functional integration as a macroscale network parameter to predict the region-specific effect of stimulation in individual subjects. In summary, we revealed how TMS modulation critically depends on the connectivity profile of target regions and propose an imaging marker to improve sensitivity of noninvasive brain stimulation for research and clinical applications.

An insular view of the social decision-making network

Social animals must detect, evaluate and respond to the emotional states of other individuals in their group. A constellation of gestures, vocalizations, and chemosignals enable animals to convey affect and arousal to others in nuanced, multisensory ways. Observers integrate social information with environmental and internal factors to select behavioral responses to others via a process call social decision-making. The Social Decision Making Network (SDMN) is a system of brain structures and neurochemicals that are conserved across species (mammals, reptiles, amphibians, birds) that are the proximal mediators of most social behaviors. However, how sensory information reaches the SDMN to shape behavioral responses during a social encounter is not well known. Here we review the empirical data that demonstrate the necessity of sensory systems in detecting social stimuli, as well as the anatomical connectivity of sensory systems with each node of the SDMN. We conclude that the insular cortex is positioned to link integrated social sensory cues to this network to produce flexible and appropriate behavioral responses to socioemotional cues.

A Flexible Model of Working Memory

Working memory is fundamental to cognition, allowing one to hold information "in mind." A defining characteristic of working memory is its flexibility: we can hold anything in mind. However, typical models of working memory rely on finely tuned, content-specific attractors to persistently maintain neural activity and therefore do not allow for the flexibility observed in behavior. Here, we present a flexible model of working memory that maintains representations through random recurrent connections between two layers of neurons: a structured "sensory" layer and a randomly connected, unstructured layer. As the interactions are untuned with respect to the content being stored, the network maintains any arbitrary input. However, in our model, this flexibility comes at a cost: the random connections overlap, leading to interference between representations and limiting the memory capacity of the network. Additionally, our model captures several other key behavioral and neurophysiological characteristics of working memory.

A thalamocortical circuit for updating action-outcome associations

The ability to flexibly use knowledge is one cardinal feature of goal-directed behaviors. We recently showed that thalamocortical and corticothalamic pathways connecting the medial prefrontal cortex and the mediodorsal thalamus (MD) contribute to adaptive decision-making (Alcaraz et al., 2018). In this study, we examined the impact of disconnecting the MD from its other main cortical target, the orbitofrontal cortex (OFC) in a task assessing outcome devaluation after initial instrumental training and after reversal of action-outcome contingencies. Crossed MD and OFC lesions did not impair instrumental performance. Using the same approach, we found however that disconnecting the OFC from its other main thalamic afferent, the submedius nucleus, produced a specific impairment in adaptive responding following action-outcome reversal. Altogether, this suggests that multiple thalamocortical circuits may act synergistically to achieve behaviorally relevant functions.

The Cognitive Thalamus as a Gateway to Mental Representations

Historically, the thalamus has been viewed as little more than a relay, simply transferring information to key players of the cast, the cortex and hippocampus, without providing any unique functional contribution. In recent years, evidence from multiple laboratories researching different thalamic nuclei has contradicted this idea of the thalamus as a passive structure. Dated models of thalamic functions are being pushed aside, revealing a greater and far more complex contribution of the thalamus for cognition. In this Viewpoints article, we show how recent data support novel views of thalamic functions that emphasize integrative roles in cognition, ranging from learning and memory to flexible adaption. We propose that these apparently separate cognitive functions may indeed be supported by a more general role in shaping mental representations. Several features of thalamocortical circuits are consistent with this suggested role, and we highlight how divergent and convergent thalamocortical and corticothalamic pathways may complement each other to support these functions. Furthermore, the role of the thalamus for subcortical integration is highlighted as a key mechanism for maintaining and updating representations. Finally, we discuss future areas of research and stress the importance of incorporating new experimental findings into existing knowledge to continue developing thalamic models. The presence of thalamic pathology in a number of neurological conditions reinforces the need to better understand the role of this region in cognition.

Processing Narratives Concerning Protected Values: A Cross-Cultural Investigation of Neural Correlates

Narratives are an important component of culture and play a central role in transmitting social values. Little is known, however, about how the brain of a listener/reader processes narratives. A receiver's response to narration is influenced by the narrator's framing and appeal to values. Narratives that appeal to "protected values," including core personal, national, or religious values, may be particularly effective at influencing receivers. Protected values resist compromise and are tied with identity, affective value, moral decision-making, and other aspects of social cognition. Here, we investigated the neural mechanisms underlying reactions to protected values in narratives. During fMRI scanning, we presented 78 American, Chinese, and Iranian participants with real-life stories distilled from a corpus of over 20 million weblogs. Reading these stories engaged the posterior medial, medial prefrontal, and temporo-parietal cortices. When participants believed that the protagonist was appealing to a protected value, signal in these regions was increased compared with when no protected value was perceived, possibly reflecting the intensive and iterative search required to process this material. The effect strength also varied across groups, potentially reflecting cultural differences in the degree of concern for protected values.

Emergence of a hierarchical brain during infancy reflected by stepwise functional connectivity

The hierarchical nature of the brain's functional organization has long been recognized, but when and how this architecture emerges during development remains largely unknown. Here the development of the brain's hierarchical organization was characterized using a modified stepwise functional connectivity approach based on resting-state fMRI in a fully longitudinal sample of infants (N = 28, with scans after birth, and at 1 and 2 years) and adults. Results obtained by placing seeds in early sensory cortices revealed novel hierarchical patterns of adult brain organization ultimately converging in limbic, paralimbic, basal ganglia, and frontoparietal brain regions. These findings are remarkably consistent with predictive coding accounts of neural processing that place these regions at the top of predictive coding hierarchies. Infants gradually developed toward this architecture in a region- and step-dependent manner, and displayed many of the same regions as adults in top hierarchical positions, starting from 1 year of age. The findings further revealed patterns of inter-sensory connectivity likely reflecting the emergence and development of multisensory processing strategies during infancy, the strengths of which were correlated with early cognitive development scores. Hum Brain Mapp 38:2666-2682, 2017. © 2017 Wiley Periodicals, Inc.

Alzheimer's disease: The influence of age on clinical heterogeneity through the human brain connectome

INTRODUCTION

One major factor that influences the heterogeneity of Alzheimer's disease (AD) is age: younger AD patients more frequently exhibit atypical forms of AD. We propose that this age-related heterogeneity can be understood better by considering age-related differences in atrophy in the context of large-scale brain networks subserving cognitive functions that contribute to memory.

METHODS

We examined data from 75 patients with mild AD dementia from Alzheimer's Disease Neuroimaging Initiative. These individuals were chosen because they have cerebrospinal fluid amyloid and p-tau levels in the range suggesting the presence of AD neuropathology, and because they were either younger than age 65 years early-onset AD (EOAD) or age 80 years or older late-onset AD (LOAD).

RESULTS

In the EOAD group, the most prominent atrophy was present in the posterior cingulate cortex, whereas in the LOAD group, atrophy was most prominent in the medial temporal lobe. Structural covariance analysis showed that the magnitude of atrophy in these epicenters is strongly correlated with a distributed atrophy pattern similar to distinct intrinsic connectivity networks in the healthy brain. An examination of memory performance in EOAD dementia versus LOAD dementia demonstrated relatively more prominent impairment in encoding in the EOAD group than in the LOAD group, with similar performance in memory storage in LOAD and EOAD but greater impairment in semantic memory in LOAD than in EOAD.

DISCUSSION

The observations provide novel insights about age as a major factor contributing to the heterogeneity in the topography of AD-related cortical atrophy.

The Neural Correlates of Humor Creativity

Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur “improv” comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC), but increased activation in temporal association regions (TMP). Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search.

Convergent and invariant object representations for sight, sound, and touch

We continuously perceive objects in the world through multiple sensory channels. In this study, we investigated the convergence of information from different sensory streams within the cerebral cortex. We presented volunteers with three common objects via three different modalities-sight, sound, and touch-and used multivariate pattern analysis of functional magnetic resonance imaging data to map the cortical regions containing information about the identity of the objects. We could reliably predict which of the three stimuli a subject had seen, heard, or touched from the pattern of neural activity in the corresponding early sensory cortices. Intramodal classification was also successful in large portions of the cerebral cortex beyond the primary areas, with multiple regions showing convergence of information from two or all three modalities. Using crossmodal classification, we also searched for brain regions that would represent objects in a similar fashion across different modalities of presentation. We trained a classifier to distinguish objects presented in one modality and then tested it on the same objects presented in a different modality. We detected audiovisual invariance in the right temporo-occipital junction, audiotactile invariance in the left postcentral gyrus and parietal operculum, and visuotactile invariance in the right postcentral and supramarginal gyri. Our maps of multisensory convergence and crossmodal generalization reveal the underlying organization of the association cortices, and may be related to the neural basis for mental concepts.

A network convergence zone in the hippocampus

The hippocampal formation is a key structure for memory function in the brain. The functional anatomy of the brain suggests that the hippocampus may be a convergence zone, as it receives polysensory input from distributed association areas throughout the neocortex. However, recent quantitative graph-theoretic analyses of the static large-scale connectome have failed to demonstrate the centrality of the hippocampus; in the context of the whole brain, the hippocampus is not among the most connected or reachable nodes. Here we show that when communication dynamics are taken into account, the hippocampus is a key hub in the connectome. Using a novel computational model, we demonstrate that large-scale brain network topology is organized to funnel and concentrate information flow in the hippocampus, supporting the long-standing hypothesis that this region acts as a critical convergence zone. Our results indicate that the functional capacity of the hippocampus is shaped by its embedding in the large-scale connectome.

Cortical odor processing in health and disease

The olfactory system has a rich cortical representation, including a large archicortical component present in most vertebrates, and in mammals neocortical components including the entorhinal and orbitofrontal cortices. Together, these cortical components contribute to normal odor perception and memory. They help transform the physicochemical features of volatile molecules inhaled or exhaled through the nose into the perception of odor objects with rich associative and hedonic aspects. This chapter focuses on how olfactory cortical areas contribute to odor perception and begins to explore why odor perception is so sensitive to disease and pathology. Odor perception is disrupted by a wide range of disorders including Alzheimer's disease, Parkinson's disease, schizophrenia, depression, autism, and early life exposure to toxins. This olfactory deficit often occurs despite maintained functioning in other sensory systems. Does the unusual network of olfactory cortical structures contribute to this sensitivity?

Cortical high-density counterstream architectures

Small-world networks provide an appealing description of cortical architecture owing to their capacity for integration and segregation combined with an economy of connectivity. Previous reports of low-density interareal graphs and apparent small-world properties are challenged by data that reveal high-density cortical graphs in which economy of connections is achieved by weight heterogeneity and distance-weight correlations. These properties define a model that predicts many binary and weighted features of the cortical network including a core-periphery, a typical feature of self-organizing information processing systems. Feedback and feedforward pathways between areas exhibit a dual counterstream organization, and their integration into local circuits constrains cortical computation. Here, we propose a bow-tie representation of interareal architecture derived from the hierarchical laminar weights of pathways between the high-efficiency dense core and periphery.