The functional neuroanatomy of the evolving parent-infant relationship

Infant survival and the development of secure and cooperative relationships are central to the future of the species. In humans, this relies heavily on the evolving early parent–infant social and affective relationship. While much is known about the behavioural and psychological components of this relationship, relatively little is known about the underlying functional neuroanatomy. Affective and social neuroscience has helped to describe the main adult brain networks involved, but has so far engaged very little with developmental findings. In this review, we seek to highlight future avenues for research by providing a coherent framework for describing the parent–infant relationship over the first 18 months. We provide an outline of the evolving nature of the relationship, starting with basic orienting and recognition processes, and culminating in the infant's attainment of higher socio-emotional and cognitive capacities. Key social and affective interactions, such as communication, cooperative play and the establishment of specific attachments propel the development of the parent–infant relationship. We summarise our current knowledge of the developing infant brain in terms of structure and function, and how these relate to the emergent abilities necessary for the formation of a secure and cooperative relationship with parents or other caregivers. Important roles have been found for brain regions including the orbitofrontal, cingulate, and insular cortices in parent–infant interactions, but it has become clear that much more information is needed about the developmental time course and connectivity of these regions.

Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

Anhedonia and reward-circuit connectivity distinguish nonresponders from responders to dorsomedial prefrontal rTMS in major depression

Background Depression is a heterogeneous mental illness. Neurostimulation treatments, by targeting specific nodes within the brain’s emotion-regulation network, may be useful both as therapies and as probes for identifying clinically relevant depression subtypes. Methods Here, we applied 20 sessions of magnetic resonance imaging-guided repetitive transcranial magnetic stimulation (rTMS) to the dorsomedial prefrontal cortex in 47 unipolar or bipolar patients with a medication-resistant major depressive episode. Results Treatment response was strongly bimodal, with individual patients showing either minimal or marked improvement. Compared with responders, nonresponders showed markedly higher baseline anhedonia symptomatology (including pessimism, loss of pleasure, and loss of interest in previously enjoyed activities) on item-by-item examination of Beck Depression Inventory-II and Quick Inventory of Depressive Symptomatology ratings. Congruently, on baseline functional magnetic resonance imaging, nonresponders showed significantly lower connectivity through a classical reward pathway comprising ventral tegmental area, striatum, and a region in ventromedial prefrontal cortex. Responders and nonresponders also showed opposite patterns of hemispheric lateralization in the connectivity of dorsomedial and dorsolateral regions to this same ventromedial region. Conclusions The results suggest distinct depression subtypes, one with preserved hedonic function and responsive to dorsomedial rTMS and another with disrupted hedonic function, abnormally lateralized connectivity through ventromedial prefrontal cortex, and unresponsive to dorsomedial rTMS. Future research directly comparing the effects of rTMS at different targets, guided by neuroimaging and clinical presentation, may clarify whether hedonia/reward circuit integrity is a reliable marker for optimizing rTMS target selection.

A gradual depth-dependent change of connectivity features of supragranular pyramidal cells in rat barrel cortex

Recent experimental evidence suggests a finer genetic, structural and functional subdivision of the layers which form a cortical column. The classical layer II/III (LII/III) of rodent neocortex integrates ascending sensory information with contextual cortical information for behavioral read-out. We systematically investigated to which extent regular-spiking supragranular pyramidal neurons, located at different depths within the cortex, show different input-output connectivity patterns. Combining glutamate-uncaging with whole-cell recordings and biocytin filling, we revealed a novel cellular organization of LII/III: (i) “Lower LII/III” pyramidal cells receive a very strong excitatory input from lemniscal LIV and much fewer inputs from paralemniscal LVa. They project to all layers of the home column, including a feedback projection to LIV whereas transcolumnar projections are relatively sparse. (ii) “Upper LII/III” pyramidal cells also receive their strongest input from LIV, but in addition, a very strong and dense excitatory input from LVa. They project extensively to LII/III as well as LVa and Vb of their home and neighboring columns, (iii) “Middle LII/III” pyramidal cell show an intermediate connectivity phenotype that stands in many ways in-between the features described for lower versus upper LII/III. “Lower LII/III” intracolumnarly segregates and transcolumnarly integrates lemniscal information whereas “upper LII/III” seems to integrate lemniscal with paralemniscal information. This suggests a finegrained functional subdivision of the supragranular compartment containing multiple circuits without any obvious cytoarchitectonic, other structural or functional correlate of a laminar border in rodent barrel cortex.

Landscape connectivity: a key to effective habitat restoration in lowland agricultural landscapes

Landscape scale habitat restoration has the potential to reconnect habitats in fragmented landscapes. This study investigates landscape connectivity as a key to effective habitat restoration in lowland agricultural landscapes and applies these findings to transferable management recommendations. The study area is the Stonehenge World Heritage Site, UK, where landscape scale chalk grassland restoration has been implemented. Here, the ecological benefits of landscape restoration and the species, habitat and landscape characteristics that facilitate or impede the enhancement of biodiversity and landscape connectivity were investigated. Lepidoptera were used as indictors of restoration success and results showed restoration grasslands approaching the ecological conditions of the target chalk grassland habitat and increasing in biodiversity values within a decade. Restoration success is apparent for four species with a broad range of grass larval host plants (e.g. Melanargia galathea, Maniola jurtina) or with intermediate mobility (Polyommatus icarus). However, two species with specialist larval host plants and low mobility (Lysandra bellargus), are restricted to chalk grassland fragments. Studies of restoration grassland of different ages show that recent grassland restoration (1 or 2 years old) may reduce the functional isolation of chalk grassland fragments. A management experiment showed that mowing increases boundary following behaviour in two species of grassland Lepidoptera; Maniola jurtina and Zygaena filipendulae. Analysis of the landscape scale implications of the grassland restoration illustrates an increase in grassland habitat network size and in landscape connectivity, which is likely to benefit the majority of grassland associated Lepidoptera. Landscape and habitat variables can be managed to increase the success of restoration projects including the spatial targeting of receptor sites, vegetation structure and selection of seed source and management recommendations are provided that are transferrable to other species-rich grassland landscape scale restoration projects. Overall results show restoration success for some habitats and species within a decade. However, additional management is required to assist the re-colonisation of specialist species. Despite this, habitat restoration at the landscape scale can be an effective, long term approach to enhance butterfly biodiversity and landscape connectivity.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

Synaptic connectivity in micropatterned networks of neuronal cells

The presented thesis describes the formation of functional neuronal networks on an underlying micropattern. Small circuits of interconnected neurons defined by the geometry of the patterned substrate could be observed and were utilised as a model system of reduced complexity for the behaviour of neuronal network formation and activity. The first set of experiments was conducted to investigate aspects of the substrate preparation. Micropatterned substrates were created by microcontact printing of physiological proteins onto polystyrene culture dishes. The substrates displayed a high contrast between the repellant background and the cell attracting pattern, such that neurons seeded onto these surfaces aligned with the stamped structure. Both the patterning process and the cell culture were optimised, yielding highly compliant low-density networks of living neuronal cells. In the second step, cellular physiology of the cells grown on these substrates was investigated by patch-clamp measurements and compared to cells cultivated under control conditions. It could be shown that the growth on a patterned substrate did not result in an impairment of cellular integrity nor that it had an impact on synapse formation or synaptic efficacy. Due to the extremely low-density cell culture that was applied, cellular connectivity through chemical synapses could be observed at the single cell level. Having established that single cells were not negatively affected by the growth on patterned substrates, aspects of network formation were investigated. The formation of physical contact between two cells was analysed through microinjection studies and related to the rate at which functional synaptic contacts formed between two neighbouring cells. Surprisingly, the rate of synapse formation between physically contacting cells was shown to be unaltered in spite of the drastic reduction of potential interaction partners on the micropattern. Additional features of network formation were investigated and found consistent with results reported by other groups: A different rate of synapse formation by excitatory and inhibitory neurons could be reproduced as well as a different rate of frequency-dependent depression at excitatory and inhibitory synapses. Furthermore, regarding simple feedback loops, a significant enrichment of reciprocal connectivity between mixed pairs of excitatory and inhibitory neurons relative to uniform pairs could be demonstrated. This phenomenon has also been described by others in unpatterned cultures [Muller, 1997] and may therefore be a feature underlying neuronal network formation in general. Based on these findings, it can be assumed that inherent features of neuronal behaviour and cellular recognition mechanisms were found in the cultured networks and appear to be undisturbed by patterned growth. At the same time, it was possible to reduce the complexity of the forming networks dramatically in a cell culture on a patterned surface. Thus, features of network architecture and synaptic connectivity could be investigated on the single cell level under highly defined conditions.

Brain connectivity at different time-scales measured with EEG

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

BRAIN ACTIVATION AND CONNECTIVITY IN NON-DISABLED MULTIPLE SCLEROSIS PATIENTS

Multiple sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. There is no cure for MS and current therapies have limited efficacy. While the majority of individuals with MS develop significant clinical disability, a subset experiences a disease course with minimal impairment even in the presence of significant apparent tissue damage on magnetic resonance imaging (MRI). The current studies combined functional MRI and diffusion tensor imaging (DTI) to elucidate brain mechanisms associated with lack of clinical disability in patients with MS. Recent evidence has implicated cortical reorganization as a mechanism to limit the clinical manifestation of the disease. Functional MRI was used to test the hypothesis that non-disabled MS patients (Expanded Disability Status Scale ≤ 1.5) show increased recruitment of cognitive control regions (dorsolateral prefrontal and anterior cingulate cortex) while performing sensory, motor and cognitive tasks. Compared to matched healthy controls, patients increased activation of cognitive control brain regions when performing non-dominant hand movements and the 2-back working memory task. Using dynamic causal modeling, we tested whether increased cognitive control recruitment is associated with alterations in connectivity in the working memory functional network. Patients exhibited similar network connectivity to that of control subjects when performing working memory tasks. We subsequently investigated the integrity of major white matter tracts to assess structural connectivity and its relation to activation and functional integration of the cognitive control system. Patients showed substantial alterations in callosal, inferior and posterior white matter tracts and less pronounced involvement of the corticospinal tracts and superior longitudinal fasciculi (SLF). Decreased structural integrity within the right SLF in patients was associated with decreased performance, and decreased activation and connectivity of the cognitive control system when performing working memory tasks. These studies suggest that patient with MS without clinical disability increase cognitive control system recruitment across functional domains and rely on preserved functional and structural connectivity of brain regions associated with this network. Moreover, the current studies show the usefulness of combining brain activation data from functional MRI and structural connectivity data from DTI to improve our understanding of brain adaptation mechanisms to neurological disease.

Functional wiring of hypocretin and LC-NE neurons: implications for arousal.

To survive in a rapidly changing environment, animals must sense their external world and internal physiological state and properly regulate levels of arousal. Levels of arousal that are abnormally high may result in inefficient use of internal energy stores and unfocused attention to salient environmental stimuli. Alternatively, levels of arousal that are abnormally low may result in the inability to properly seek food, water, sexual partners, and other factors necessary for life. In the brain, neurons that express hypocretin neuropeptides may be uniquely posed to sense the external and internal state of the animal and tune arousal state according to behavioral needs. In recent years, we have applied temporally precise optogenetic techniques to study the role of these neurons and their downstream connections in regulating arousal. In particular, we have found that noradrenergic neurons in the brainstem locus coeruleus (LC) are particularly important for mediating the effects of hypocretin neurons on arousal. Here, we discuss our recent results and consider the implications of the anatomical connectivity of these neurons in regulating the arousal state of an organism across various states of sleep and wakefulness.

Studying functional brain networks with concurrent transcranical alternating current stimulation and EEG

Recently transcranial electric stimulation (tES) has been widely used as a mean to modulate brain activity. The modulatory effects of tES have been studied with the excitability of primary motor cortex. However, tES effects are not limited to the site of stimulation but extended to other brain areas, suggesting a need for the study of functional brain networks. Transcranial alternating current stimulation (tACS) applies sinusoidal current at a specified frequency, presumably modulating brain activity in a frequency-specific manner. At a behavioural level, tACS has been confirmed to modulate behaviour, but its neurophysiological effects are still elusive. In addition, neural oscillations are considered to reflect rhythmic changes in transmission efficacy across brain networks, suggesting that tACS would provide a mean to modulate brain networks. To study neurophysiological effects of tACS, we have been developing a methodological framework by combining transcranial magnetic stimulation (TMS), EEG and tACS. We have developed the optimized concurrent tACS-EEG recording protocol and powerful artefact removal method that allow us to study neurophysiological effects of tACS. We also established the concurrent tACS-TMS-EEG recording to study brain network connectivity while introducing extrinsic oscillatory activity by tACS. We show that tACS modulate brain activity in a phase-dependent manner. Our methodological advancement will open an opportunity to study causal role of oscillatory brain activity in neural transmissions in cortical brain networks.

Confocal analysis of synaptic connectivity of the rod pathway in the rabbit retina

The retina is a specialized neuronal structure that transforms the optical image into electrical signals which are transmitted to the brain via the optic nerve. As part of the strategy to cover a stimulus range as broad as 10 log units, from dim starlight to bright sunlight, retinal circuits are broadly divided into rod and cone pathways, responsible for dark and light-adapted vision, respectively. ^ In this dissertation, confocal microscopy and immunocytochemical methods were combined to study the synaptic connectivity of the rod pathway from the level of individual synapses to whole populations of neurons. The study was focused on synaptic interactions at the rod bipolar terminal. The purpose is to understand the synaptic structure of the dyad synapse made by rod bipolar terminals, including the synaptic components and connections, and their physiological functions in the rod pathway. In addition, some additional components and connections of the rod pathway were also studied in these experiments. The major results can be summarized as following: At the dyad synapse of rod bipolar terminals, three postsynaptic components—processes of All amacrine cells and the varicosities of S1 or S2 amacrine cells express different glutamate receptor subunits, which may underlie the functional diversity of these postsynaptic neurons. A reciprocal feedback system is formed by rod bipolar terminals and S1/S2 amacrine cells. Analysis showed these two wide-field GABA amacrine cells have stereotyped synaptic connections with the appropriate morphology and distribution to perform specific functions. In addition, S1 and S2 cells have different coupling patterns and, in general, there is no coupling between the two types. Besides the classic rod pathway though rod bipolar cells and All amacrine cells, the finding of direct connections between certain types of OFF cone bipolar cells and rods indicates the presence of an alternative rod pathway in the rabbit retina. ^ In summary, this dissertation presents a detailed view of the connection and receptors at rod bipolar terminals. Based on the morphology, distribution and coupling, different functional roles were identified for S1 and S2 amacrine cells. Finally, an alternative to the classic rod pathway was found in the rabbit retina. ^

Remote Effects of Hippocampal Sclerosis on Effective Connectivity during Working Memory Encoding: A Case of Connectional Diaschisis?

Accumulating evidence suggests a role for the medial temporal lobe (MTL) in working memory (WM). However, little is known concerning its functional interactions with other cortical regions in the distributed neural network subserving WM. To reveal these, we availed of subjects with MTL damage and characterized changes in effective connectivity while subjects engaged in WM task. Specifically, we compared dynamic causal models, extracted from magnetoencephalographic recordings during verbal WM encoding, in temporal lobe epilepsy patients (with left hippocampal sclerosis) and controls. Bayesian model comparison indicated that the best model (across subjects) evidenced bilateral, forward, and backward connections, coupling inferior temporal cortex (ITC), inferior frontal cortex (IFC), and MTL. MTL damage weakened backward connections from left MTL to left ITC, a decrease accompanied by strengthening of (bidirectional) connections between IFC and MTL in the contralesional hemisphere. These findings provide novel evidence concerning functional interactions between nodes of this fundamental cognitive network and sheds light on how these interactions are modified as a result of focal damage to MTL. The findings highlight that a reduced (top-down) influence of the MTL on ipsilateral language regions is accompanied by enhanced reciprocal coupling in the undamaged hemisphere providing a first demonstration of “connectional diaschisis.”

HERMES: A user-friendly connectivity analysis software

The analysis of the interdependence between time series has become an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, and the introduction of concepts such as Generalized (GS) and Phase synchronization (PS). This increase in the number of approaches to tackle the existence of the so-called functional (FC) and effective connectivity (EC) (Friston 1994) between two, (or among many) neural networks, along with their mathematical complexity, makes it desirable to arrange them into a unified toolbox, thereby allowing neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them.