Functional development of large-scale sensorimotor cortical networks in the brain

MRI morphometry of the anterior and posterior cerebellar vermis and its relationship to sensorimotor and cognitive functions in children

INTRODUCTION

The human cerebellum emerges as a posterior brain structure integrating neural networks for sensorimotor, cognitive, and emotional processing across the lifespan. Developmental studies of the cerebellar anatomy and function are scant. We examine age-dependent MRI morphometry of the anterior cerebellar vermis, lobules I-V and posterior neocortical lobules VI-VII and their relationship to sensorimotor and cognitive functions.

METHODS

Typically developing children (TDC; n=38; age 9-15) and healthy adults (HAC; n=31; 18-40) participated in high-resolution MRI. Rigorous anatomically informed morphometry of the vermis lobules I-V and VI-VII and total brain volume (TBV) employed manual segmentation computer-assisted FreeSurfer Image Analysis Program [http://surfer.nmr.mgh.harvard.edu]. The neuropsychological scores (WASI-II) were normalized and related to volumes of anterior, posterior vermis, and TBV.

RESULTS

TBVs were age independent. Volumes of I-V and VI-VII were significantly reduced in TDC. The ratio of VI-VII to I-V (∼60%) was stable across age-groups; I-V correlated with visual-spatial-motor skills; VI-VII with verbal, visual-abstract and FSIQ.

CONCLUSIONS

In TDC neither anterior I-V nor posterior VI-VII vermis attained adult volumes. The "inverted U" developmental trajectory of gray matter peaking in adolescence does not explain this finding. The hypothesis of protracted development of oligodendrocyte/myelination is suggested as a contributor to TDC's lower cerebellar vermis volumes.

Reproducible network changes occur in a mouse model of temporal lobe epilepsy but do not correlate with disease severity

Studying the development of brain network disruptions in epilepsy is challenged by the paucity of data before epilepsy onset. Here, we used the unilateral, kainate mouse model of hippocampal epilepsy to investigate brain network changes before and after epilepsy onset and their stability across time. Using 32 epicranial electrodes distributed over the mouse hemispheres, we analyzed EEG epochs free from epileptic activity in 15 animals before and 28 days after hippocampal injection (group 1) and in 20 animals on two consecutive days (d28 and d29, group 2). Statistical dependencies between electrodes were characterized with the debiased-weighted phase lag index. We analyzed: a) graph metric changes from baseline to chronic stage (d28) in group 1; b) their reliability across d28 and d29, in group 2; c) their correlation with epileptic activity (EA: seizure, spike and fast-ripple rates), averaged over d28 and d29, in group 2. During the chronic stage, intra-hemispheric connections of the non-injected hemisphere strengthened, yielding an asymmetrical network in low (4-8 Hz) and high theta (8-12 Hz) bands. The contralateral hemisphere also became more integrated and segregated within the high theta band. Both network topology and EEG markers of EA were stable over consecutive days but not correlated with each other. Altogether, we show reproducible large-scale network modifications after the development of focal epilepsy. These modifications are mostly specific to the non-injected hemisphere. The absence of correlation with epileptic activity does not allow to specifically ascribe these network changes to mechanisms supporting EA or rather compensatory inhibition but supports the notion that epilepsy extends beyond the sole repetition of EA and impacts network that might not be involved in EA generation.

Functional MRI reveals brain-wide actions of thalamically-initiated oscillatory activities on associative memory consolidation

As a key oscillatory activity in the brain, thalamic spindle activities are long believed to support memory consolidation. However, their propagation characteristics and causal actions at systems level remain unclear. Using functional MRI (fMRI) and electrophysiology recordings in male rats, we found that optogenetically-evoked somatosensory thalamic spindle-like activities targeted numerous sensorimotor (cortex, thalamus, brainstem and basal ganglia) and non-sensorimotor limbic regions (cortex, amygdala, and hippocampus) in a stimulation frequency- and length-dependent manner. Thalamic stimulation at slow spindle frequency (8 Hz) and long spindle length (3 s) evoked the most robust brain-wide cross-modal activities. Behaviorally, evoking these global cross-modal activities during memory consolidation improved visual-somatosensory associative memory performance. More importantly, parallel visual fMRI experiments uncovered response potentiation in brain-wide sensorimotor and limbic integrative regions, especially superior colliculus, periaqueductal gray, and insular, retrosplenial and frontal cortices. Our study directly reveals that thalamic spindle activities propagate in a spatiotemporally specific manner and that they consolidate associative memory by strengthening multi-target memory representation.

A physical neural mass model framework for the analysis of oscillatory generators from laminar electrophysiological recordings

Cortical function emerges from the interactions of multi-scale networks that may be studied at a high level using neural mass models (NMM) that represent the mean activity of large numbers of neurons. Here, we provide first a new framework called laminar NMM, or LaNMM for short, where we combine conduction physics with NMMs to simulate electrophysiological measurements. Then, we employ this framework to infer the location of oscillatory generators from laminar-resolved data collected from the prefrontal cortex in the macaque monkey. We define a minimal model capable of generating coupled slow and fast oscillations, and we optimize LaNMM-specific parameters to fit multi-contact recordings. We rank the candidate models using an optimization function that evaluates the match between the functional connectivity (FC) of the model and data, where FC is defined by the covariance between bipolar voltage measurements at different cortical depths. The family of best solutions reproduces the FC of the observed electrophysiology by selecting locations of pyramidal cells and their synapses that result in the generation of fast activity at superficial layers and slow activity across most depths, in line with recent literature proposals. In closing, we discuss how this hybrid modeling framework can be more generally used to infer cortical circuitry.

Weakly Correlated Local Cortical State Switches under Anesthesia Lead to Strongly Correlated Global States

During recovery from anesthesia, brain activity switches abruptly between a small set of discrete states. Surprisingly, this switching also occurs under constant doses of anesthesia, even in the absence of stimuli. These metastable states and the transitions between them are thought to form a "scaffold" that ultimately guides the brain back to wakefulness. The processes that constrain cortical activity patterns to these states and govern how states are coordinated between different cortical regions are unknown. If state transitions were driven by subcortical modulation, different cortical sites should exhibit near-synchronous state transitions. Conversely, spatiotemporal heterogeneity would suggest that state transitions are coordinated through corticocortical interactions. To differentiate between these hypotheses, we quantified synchrony of brain states in male rats exposed to a fixed isoflurane concentration. States were defined from spectra of local field potentials recorded across layers of visual and motor cortices. A transition synchrony measure shows that most state transitions are highly localized. Furthermore, while most pairs of cortical sites exhibit statistically significant coupling of both states and state transition times, coupling strength is typically weak. States and state transitions in the thalamic input layer (L4) are particularly decoupled from those in supragranular and infragranular layers. This suggests that state transitions are not imposed on the cortex by broadly projecting modulatory systems. Although each pairwise interaction is typically weak, we show that the multitude of such weak interactions is sufficient to confine global activity to a small number of discrete states.SIGNIFICANCE STATEMENT The brain consistently recovers to wakefulness after anesthesia, but this process is poorly understood. Previous work revealed that, during recovery from anesthesia, corticothalamic activity falls into one of several discrete patterns. The neuronal mechanisms constraining the cortex to just a few discrete states remain unknown. Global states could be coordinated by fluctuations in subcortical nuclei that project broadly to the cortex. Alternatively, these states may emerge from interactions within the cortex itself. Here, we provide evidence for the latter possibility by demonstrating that most pairs of cortical sites exhibit weak coupling. We thereby lay groundwork for future investigations of the specific cellular and network mechanisms of corticocortical activity state coupling.

Alteration in Functional Magnetic Resonance Imaging Signal Complexity Across Multiple Time Scales in Patients With Migraine Without Aura

Background

Migraine is a primary neurological disorder associated with complex brain activity. Recently, mounting evidence has suggested that migraine is underpinned by aberrant dynamic brain activity characterized by linear and non-linear changes across a variety of time scales. However, the abnormal dynamic brain activity at different time scales is still unknown in patients with migraine without aura (MWoA). This study aimed to assess the altered patterns of brain activity dynamics over different time scales and the potential pathophysiological mechanisms of alterations in patients with MWoA.

Methods

Multiscale entropy in 50 patients and 20 healthy controls (HCs) was calculated to investigate the patterns and altered brain complexity (BC) across five different time scales. Spearman rank correlation analysis between BC in regions showing significant intergroup differences and clinical scores (i.e., frequency of migraine attacks, duration, headache impact test) was conducted in patients with MWoA.

Results

The spatial distribution of BC varied across different time scales. At time scale1, BC was higher in the posterior default mode network (DMN) across participants. Compared with HCs, patients with MWoA had higher BC in the DMN and sensorimotor network. At time scale2, BC was mainly higher in the anterior DMN across participants. Patients with MWoA had higher BC in the sensorimotor network. At time scale3, BC was mainly higher in the frontoparietal network across participants. Patients with MWoA had increased BC in the parietal gyrus. At time scale4, BC is mainly higher in the sensorimotor network. Patients with MWoA had higher BC in the postcentral gyrus. At time scale5, BC was mainly higher in the DMN. Patients with MWoA had lower BC in the posterior DMN. In particular, BC values in the precuneus and paracentral lobule significantly correlated with clinical symptoms.

Conclusion

Migraine is associated with alterations in dynamic brain activity in the sensorimotor network and DMN over multiple time scales. Time-varying BC within these regions could be linked to instability in pain transmission and modulation. Our findings provide new evidence for the hypothesis of abnormal dynamic brain activity in migraine.

Structure supports function: Informing directed and dynamic functional connectivity with anatomical priors

The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural connectivity (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estimating dynamic and directed FC using structural connectivity information as priors. We tested the filter in rat epicranial recordings and human event-related EEG data, using SC priors from a meta-analysis of tracer studies and diffusion tensor imaging metrics, respectively. We show that, particularly under conditions of low signal-to-noise ratio, SC priors can help to refine estimates of directed FC, promoting sparse functional networks that combine information from structure and function. In addition, the proposed filter provides intrinsic protection against SC-related false negatives, as well as robustness against false positives, representing a valuable new tool for multimodal imaging in the context of dynamic and directed FC analysis.

Temporal controls over inter-areal cortical projection neuron fate diversity

Interconnectivity between neocortical areas is critical for sensory integration and sensorimotor transformations^1-6. These functions are mediated by heterogeneous inter-areal cortical projection neurons (ICPN), which send axon branches across cortical areas as well as to subcortical targets^7-9. Although ICPN are anatomically diverse^10-14, they are molecularly homogeneous¹⁵, and how the diversity of their anatomical and functional features emerge during development remains largely unknown. Here we address this question by linking the connectome and transcriptome in developing single ICPN of the mouse neocortex using a combination of multiplexed analysis of projections by sequencing^16,17 (MAPseq, to identify single-neuron axonal projections) and single-cell RNA sequencing (to identify corresponding gene expression). Focusing on neurons of the primary somatosensory cortex (S1), we reveal a protracted unfolding of the molecular and functional differentiation of motor cortex-projecting ([Formula: see text]) ICPN compared with secondary somatosensory cortex-projecting ([Formula: see text]) ICPN. We identify SOX11 as a temporally differentially expressed transcription factor in [Formula: see text] versus [Formula: see text] ICPN. Postnatal manipulation of SOX11 expression in S1 impaired sensorimotor connectivity and disrupted selective exploratory behaviours in mice. Together, our results reveal that within a single cortical area, different subtypes of ICPN have distinct postnatal paces of molecular differentiation, which are subsequently reflected in distinct circuit connectivities and functions. Dynamic differences in the expression levels of a largely generic set of genes, rather than fundamental differences in the identity of developmental genetic programs, may thus account for the emergence of intra-type diversity in cortical neurons.

Neural activity temporal pattern dictates long-range propagation targets

Brain possesses a complex spatiotemporal architecture for efficient information processing and computing. However, it remains unknown how neural signal propagates to its intended targets brain-wide. Using optogenetics and functional MRI, we arbitrarily initiated various discrete neural activity pulse trains with different temporal patterns and revealed their distinct long-range propagation targets within the well-defined, topographically organized somatosensory thalamo-cortical circuit. We further observed that such neural activity propagation over long range could modulate brain-wide sensory functions. Electrophysiological analysis indicated that distinct propagation pathways arose from system level neural adaptation and facilitation in response to the neural activity temporal characteristics. Together, our findings provide fundamental insights into the long-range information transfer and processing. They directly support that temporal coding underpins the whole brain functional architecture in presence of the vast and relatively static anatomical architecture.

Electrical Source Imaging in Freely Moving Rats: Evaluation of a 12-Electrode Cortical Electroencephalography System

This work presents and evaluates a 12-electrode intracranial electroencephalography system developed at the National Institute of Mental Health (Klecany, Czech Republic) in terms of an electrical source imaging (ESI) technique in rats. The electrode system was originally designed for translational research purposes. This study demonstrates that it is also possible to use this well-established system for ESI, and estimates its precision, accuracy, and limitations. Furthermore, this paper sets a methodological basis for future implants. Source localization quality is evaluated using three approaches based on surrogate data, physical phantom measurements, and in vivo experiments. The forward model for source localization is obtained from the FieldTrip-SimBio pipeline using the finite-element method. Rat brain tissue extracted from a magnetic resonance imaging template is approximated by a single-compartment homogeneous tetrahedral head model. Four inverse solvers were tested: standardized low-resolution brain electromagnetic tomography, exact low-resolution brain electromagnetic tomography (eLORETA), linear constrained minimum variance (LCMV), and dynamic imaging of coherent sources. Based on surrogate data, this paper evaluates the accuracy and precision of all solvers within the brain volume using error distance and reliability maps. The mean error distance over the whole brain was found to be the lowest in the eLORETA solution through signal to noise ratios (SNRs) (0.2 mm for 25 dB SNR). The LCMV outperformed eLORETA under higher SNR conditions, and exhibiting higher spatial precision. Both of these inverse solvers provided accurate results in a phantom experiment (1.6 mm mean error distance across shallow and 2.6 mm across subcortical testing dipoles). Utilizing the developed technique in freely moving rats, an auditory steady-state response experiment provided results in line with previously reported findings. The obtained results support the idea of utilizing a 12-electrode system for ESI and using it as a solid basis for the development of future ESI dedicated implants.

Modeling time-varying brain networks with a self-tuning optimized Kalman filter

Brain networks are complex dynamical systems in which directed interactions between different areas evolve at the sub-second scale of sensory, cognitive and motor processes. Due to the highly non-stationary nature of neural signals and their unknown noise components, however, modeling dynamic brain networks has remained one of the major challenges in contemporary neuroscience. Here, we present a new algorithm based on an innovative formulation of the Kalman filter that is optimized for tracking rapidly evolving patterns of directed functional connectivity under unknown noise conditions. The Self-Tuning Optimized Kalman filter (STOK) is a novel adaptive filter that embeds a self-tuning memory decay and a recursive regularization to guarantee high network tracking accuracy, temporal precision and robustness to noise. To validate the proposed algorithm, we performed an extensive comparison against the classical Kalman filter, in both realistic surrogate networks and real electroencephalography (EEG) data. In both simulations and real data, we show that the STOK filter estimates time-frequency patterns of directed connectivity with significantly superior performance. The advantages of the STOK filter were even clearer in real EEG data, where the algorithm recovered latent structures of dynamic connectivity from epicranial EEG recordings in rats and human visual evoked potentials, in excellent agreement with known physiology. These results establish the STOK filter as a powerful tool for modeling dynamic network structures in biological systems, with the potential to yield new insights into the rapid evolution of network states from which brain functions emerge.

During normal behavior, brains transition between functional network states several times per second. This allows humans to quickly read a sentence, and a frog to catch a fly. Understanding these fast network dynamics is fundamental to understanding how brains work, but up to now it has proven very difficult to model fast brain dynamics for various methodological reasons. To overcome these difficulties, we designed a new Kalman filter (STOK) by innovating on previous solutions from control theory and state-space modelling. We show that STOK accurately models fast network changes in simulations and real neural data, making it an essential new tool for modelling fast brain networks in the time and frequency domain.

The Emergence of Hierarchical Somatosensory Processing in Late Prematurity

The somatosensory system has a hierarchical organization. Information processing increases in complexity from the contralateral primary sensory cortex to bilateral association cortices and this is represented by a sequence of somatosensory-evoked potentials recorded with scalp electroencephalographies. The mammalian somatosensory system matures over the early postnatal period in a rostro-caudal progression, but little is known about the development of hierarchical information processing in the human infant brain. To investigate the normal human development of the somatosensory hierarchy, we recorded potentials evoked by mechanical stimulation of hands and feet in 34 infants between 34 and 42 weeks corrected gestational age, with median postnatal age of 3 days. We show that the shortest latency potential was evoked for both hands and feet at all ages with a contralateral somatotopic source in the primary somatosensory cortex (SI). However, the longer latency responses, localized in SI and beyond, matured with age. They gradually emerged for the foot and, although always present for the hand, showed a shift from purely contralateral to bilateral hemispheric activation. These results demonstrate the rostro-caudal development of human somatosensory hierarchy and suggest that the development of its higher tiers is complete only just before the time of normal birth.

Altered cortical processing of somatosensory input in pre-term infants who had high-grade germinal matrix-intraventricular haemorrhage

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Infants who had GM-IVH recruit different cortical sources following foot stimulation.

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Results indicate restructuring of somatosensory processing during the weeks after GM-IVH.

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GM-IVH is more detrimental for lower than upper limb somatosensory processing.

High-grade (large) germinal matrix-intraventricular haemorrhage (GM-IVH) is one of the most common causes of somatomotor neurodisability in pre-term infants. GM-IVH presents during the first postnatal week and can impinge on somatosensory circuits resulting in aberrant somatosensory cortical events straight after injury. Subsequently, somatosensory circuits undergo significant plastic changes, sometimes allowing the reinstatement of a somatosensory cortical response. However, it is not known whether this restructuring results in a full recovery of somatosensory functions. To investigate this, we compared somatosensory responses to mechanical stimulation measured with 18-channels EEG between infants who had high-grade GM-IVH (with ventricular dilatation and/or intraparenchymal lesion; n = 7 studies from 6 infants; mean corrected gestational age = 33 weeks; mean postnatal age = 56 days) and age-matched controls (n = 9 studies from 8 infants; mean corrected gestational age = 32 weeks; mean postnatal age = 36 days). We showed that infants who had high-grade GM-IVH did not recruit the same cortical source configuration following stimulation of the foot, but their response to stimulation of the hand resembled that of controls. These results show that somatosensory cortical circuits are reinstated in infants who had GM-IVH, during the several weeks after injury, but remain different from those of infants without brain injury. An important next step will be to investigate whether these evidences of neural reorganisation predict neurodevelopmental outcome.

Fast Electrophysiological Mapping of Rat Cortical Motor Representation on a Time Scale of Minutes during Skin Stimulation

The topographic map of motor cortical representation, called the motor map, is not invariant, but can be altered by motor learning, neurological injury, and functional recovery from injury. Although much attention has been paid to short-term changes of the motor map, robust measures have not been established. The existing mapping methods are time-consuming, and the obtained maps are confounded by time preference. The purpose of this study was to examine the dynamics of the motor map on a timescale of minutes during transient somatosensory input by a fast motor mapping technique. We applied 32-channel micro-electrocorticographic electrode arrays to the rat sensorimotor cortex for cortical stimulation, and the topographic profile of motor thresholds in forelimb muscle was identified by fast motor mapping. Sequential motor maps were obtained every few minutes before, during, and just after skin stimulation to the dorsal forearm using a wool buff. During skin stimulation, the motor map expanded and the center of gravity of the map was shifted caudally. The expansion of the map persisted for at least a few minutes after the end of skin stimulation. Although the motor threshold of the hotspot was not changed, the area in which it was decreased appeared caudally to the hotspot, which may be in the somatosensory cortex. The present study demonstrated rapid enlargement of the forelimb motor map in the order of a few minutes induced by skin stimulation. This helps to understand the spatial dynamism of motor cortical representation that is modulated rapidly by somatosensory input.

Validating Non-invasive EEG Source Imaging Using Optimal Electrode Configurations on a Representative Rat Head Model

The curtain of technical limitations impeding rat multichannel non-invasive electroencephalography (EEG) has risen. Given the importance of this preclinical model, development and validation of EEG source imaging (ESI) is essential. We investigate the validity of well-known human ESI methodologies in rats which individual tissue geometries have been approximated by those extracted from an MRI template, leading also to imprecision in electrode localizations. With the half and fifth sensitivity volumes we determine both the theoretical minimum electrode separation for non-redundant scalp EEG measurements and the electrode sensitivity resolution, which vary over the scalp because of the head geometry. According to our results, electrodes should be at least ~3 to 3.5 mm apart for an optimal configuration. The sensitivity resolution is generally worse for electrodes at the boundaries of the scalp measured region, though, by analogy with human montages, concentrates the sensitivity enough to localize sources. Cramér-Rao lower bounds of source localization errors indicate it is theoretically possible to achieve ESI accuracy at the level of anatomical structures, such as the stimulus-specific somatosensory areas, using the template. More validation for this approximation is provided through the comparison between the template and the individual lead field matrices, for several rats. Finally, using well-accepted inverse methods, we demonstrate that somatosensory ESI is not only expected but also allows exploring unknown phenomena related to global sensory integration. Inheriting the advantages and pitfalls of human ESI, rat ESI will boost the understanding of brain pathophysiological mechanisms and the evaluation of ESI methodologies, new pharmacological treatments and ESI-based biomarkers.

Electrophysiological Brain Connectivity: Theory and Implementation

We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography (EEG), magnetoencephalography (MEG), electrocorticography (ECoG), stereoelectroencephalography (SEEG). Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.

Temporal refinement of sensory-evoked activity across layers in developing mouse barrel cortex

Rhythmic whisking behavior in rodents fully develops during a critical period about 2 weeks after birth, in parallel with the maturation of other sensory modalities and the onset of exploratory locomotion. How whisker-related sensory processing develops during this period in the primary somatosensory cortex (S1) remains poorly understood. Here, we characterized neuronal activity evoked by single- or dual-whisker stimulation patterns in developing S1, before, during and after the occurrence of active whisking. Employing multi-electrode recordings in all layers of barrel cortex in urethane-anesthetized mice, we find layer-specific changes in multi-unit activity for principal and neighboring barrel columns. While whisker stimulation evoked similar early responses (0-50 ms post-stimulus) across development, the late response (50-150 ms post-stimulus) decreased in all layers with age. Furthermore, peak onset times and the duration of the late response decreased in all layers across age groups. Responses to paired-pulse stimulation showed increases in spiking precision and in paired-pulse ratios in all cortical layers during development. Sequential activation of two neighboring whiskers with varying stimulus intervals evoked distinct response profiles in the activated barrel columns, depending on the direction and temporal separation of the stimuli. In conclusion, our findings indicate that the temporal sharpening of sensory-evoked activity coincides with the onset of active whisking.

Developmental trajectory of movement-related cortical oscillations during active sleep in a cross-sectional cohort of pre-term and full-term human infants

In neonatal animal models, isolated limb movements during active sleep provide input to immature somatomotor cortex necessary for its development and are somatotopically encoded by alpha-beta oscillations as late as the equivalent of human full-term. Limb movements elicit similar neural patterns in very pre-term human infants (average 30 corrected gestational weeks), suggesting an analogous role in humans, but it is unknown until when they subserve this function. In a cohort of 19 neonates (31-42 corrected gestational weeks) we showed that isolated hand movements during active sleep continue to induce these same somatotopically distributed oscillations well into the perinatal period, but that these oscillations decline towards full-term and fully disappear at 41 corrected gestational weeks (equivalent to the end of gestation). We also showed that these highly localised alpha-beta oscillations are associated with an increase in delta oscillations which extends to the frontal area and does not decline with age. These results suggest that isolated limb movements during active sleep could have an important role in experience-dependent somatomotor development up until normal birth in humans.

Assessing the performance of Granger-Geweke causality: Benchmark dataset and simulation framework

Nonparametric methods based on spectral factorization offer well validated tools for estimating spectral measures of causality, called Granger–Geweke Causality (GGC). In Pagnotta et al. (2018) [1] we benchmarked nonparametric GGC methods using EEG data recorded during unilateral whisker stimulations in ten rats; here, we include detailed information about the benchmark dataset. In addition, we provide codes for estimating nonparametric GGC and a simulation framework to evaluate the effects on GGC analyses of potential problems, such as the common reference problem, signal-to-noise ratio (SNR) differences between channels, and the presence of additive noise. We focus on nonparametric methods here, but these issues also affect parametric methods, which can be tested in our framework as well. Our examples allow showing that time reversal testing for GGC (tr-GGC) mitigates the detrimental effects due to SNR imbalance and presence of mixed additive noise, and illustrate that, when using a common reference, tr-GGC unambiguously detects the causal influence׳s dominant spectral component, irrespective of the characteristics of the common reference signal. Finally, one of our simulations provides an example that nonparametric methods can overcome a pitfall associated with the implementation of conditional GGC in traditional parametric methods.

Layer-Specific Refinement of Sensory Coding in Developing Mouse Barrel Cortex

Rodent rhythmic whisking behavior matures during a critical period around 2 weeks after birth. The functional adaptations of neocortical circuitry during this developmental period remain poorly understood. Here, we characterized stimulus-evoked neuronal activity across all layers of mouse barrel cortex before, during, and after the onset of whisking behavior. Employing multi-electrode recordings and 2-photon calcium imaging in anesthetized mice, we tested responses to rostro-caudal whisker deflections, axial "tapping" stimuli, and their combination from postnatal day 10 (P10) to P28. Within this period, whisker-evoked activity of neurons displayed a general decrease in layer 2/3 (L2/3) and L4, but increased in L5 and L6. Distinct alterations in neuronal response adaptation during the 2-s period of stimulation at ~5 Hz accompanied these changes. Moreover, single-unit analysis revealed that response selectivity in favor of either lateral deflection or axial tapping emerges in deeper layers within the critical period around P14. For superficial layers we confirmed this finding using calcium imaging of L2/3 neurons, which also exhibited emergence of response selectivity as well as progressive sparsification and decorrelation of evoked responses around P14. Our results demonstrate layer-specific development of sensory responsiveness and response selectivity in mouse somatosensory cortex coinciding with the onset of exploratory behavior.

Time-varying MVAR algorithms for directed connectivity analysis: Critical comparison in simulations and benchmark EEG data

Human brain function depends on directed interactions between multiple areas that evolve in the subsecond range. Time-varying multivariate autoregressive (tvMVAR) modeling has been proposed as a way to help quantify directed functional connectivity strengths with high temporal resolution. While several tvMVAR approaches are currently available, there is a lack of unbiased systematic comparative analyses of their performance and of their sensitivity to parameter choices. Here, we critically compare four recursive tvMVAR algorithms and assess their performance while systematically varying adaptation coefficients, model order, and signal sampling rate. We also compared two ways of exploiting repeated observations: single-trial modeling followed by averaging, and multi-trial modeling where one tvMVAR model is fitted across all trials. Results from numerical simulations and from benchmark EEG recordings showed that: i) across a broad range of model orders all algorithms correctly reproduced patterns of interactions; ii) signal downsampling degraded connectivity estimation accuracy for most algorithms, although in some cases downsampling was shown to reduce variability in the estimates by lowering the number of parameters in the model; iii) single-trial modeling followed by averaging showed optimal performance with larger adaptation coefficients than previously suggested, and showed slower adaptation speeds than multi-trial modeling. Overall, our findings identify strengths and weaknesses of existing tvMVAR approaches and provide practical recommendations for their application to modeling dynamic directed interactions from electrophysiological signals.

Development of the whisker-to-barrel cortex system

This review provides an overview on the development of the rodent whisker-to-barrel cortex system from late embryonic stage to the end of the first postnatal month. During this period the system shows a remarkable transition from a mostly genetic-molecular driven generation of crude connectivity, providing the template for activity-dependent structural and functional maturation and plasticity, to the manifestation of a complex behavioral repertoire including social interactions. Spontaneous and sensory-evoked activity is present in neonatal barrel cortex and control the generation of the cortical architecture. Half a century after its first description by Woolsey and van der Loos the whisker-to-barrel cortex system with its unique and clear topographic organization still offers the exceptional opportunity to study sensory processing and complex behavior.

Electrophysiological Evidence for the Development of a Self-Sustained Large-Scale Epileptic Network in the Kainate Mouse Model of Temporal Lobe Epilepsy

Most research on focal epilepsy focuses on mechanisms of seizure generation in the primary epileptic focus (EF). However, neurological deficits that are not directly linked to seizure activity and that may persist after focus removal are frequent. The recruitment of remote brain regions of an epileptic network (EN) is recognized as a possible cause, but a profound lack of experimental evidence exists concerning their recruitment and the type of pathological activities they exhibit. We studied the development of epileptic activities at the large-scale in male mice of the kainate model of unilateral temporal lobe epilepsy using high-density surface EEG and multiple-site intracortical recordings. We show that, along with focal spikes and fast ripples that remain localized to the injected hippocampus (i.e., the EF), a subpopulation of spikes that propagate across the brain progressively emerges even before the expression of seizures. The spatiotemporal propagation of these generalized spikes (GSs) is highly stable within and across animals, defining a large-scale EN comprising both hippocampal regions and frontal cortices. Interestingly, GSs are often concomitant with muscular twitches. In addition, while fast ripples are, as expected, highly frequent in the EF, they also emerge in remote cortical regions and in particular in frontal regions where GSs propagate. Finally, we demonstrate that these remote interictal activities are dependent on the focus in the early phase of the disease but continue to be expressed after focus silencing at later stages. Our results provide evidence that neuronal networks outside the initial focus are progressively altered during epileptogenesis.SIGNIFICANCE STATEMENT It has long been held that the epileptic focus is responsible for triggering seizures and driving interictal activities. However, focal epilepsies are associated with heterogeneous symptoms, calling into question the concept of a strictly focal disease. Using the mouse model of hippocampal sclerosis, this work demonstrates that focal epilepsy leads to the development of pathological activities specific to the epileptic condition, notably fast ripples, that appear outside of the primary epileptic focus. Whereas these activities are dependent on the focus early in the disease, focus silencing fails to control them in the chronic stage. Thus, dynamical changes specific to the epileptic condition are built up outside of the epileptic focus along with disease progression, which provides supporting evidence for network alterations in focal epilepsy.

Systematic population spike delays across cortical layers within and between primary sensory areas

The coordinated propagation of activity across cortical layers enables simultaneous local computation and inter-areal interactions. A pattern of upward propagation from deeper to more superficial layers, which has been repeatedly demonstrated in spontaneous activity, would allow these functions to occur in parallel. But it remains unclear whether upward propagation also occurs for stimulus evoked activity, and how it relates to activity in other cortical areas. Here we used a new method to analyze relative delays between spikes obtained from simultaneous laminar recordings in primary sensory cortex (S1) of both hemispheres. The results identified systematic spike delays across cortical layers that showed a general upward propagation of activity in evoked and spontaneous activity. Systematic spike delays were also observed between hemispheres. After spikes in one S1 the delays in the other S1 were shortest at infragranular layers and increased in the upward direction. Model comparisons furthermore showed that upward propagation was better explained as a step-wise progression over cortical layers than as a traveling wave. The results are in line with the notion that upward propagation functionally integrates activity into local processing at superficial layers, while efficiently allowing for simultaneous inter-areal interactions.

Rapid Postnatal Expansion of Neural Networks Occurs in an Environment of Altered Neurovascular and Neurometabolic Coupling

In the adult brain, increases in neural activity lead to increases in local blood flow. However, many prior measurements of functional hemodynamics in the neonatal brain, including functional magnetic resonance imaging (fMRI) in human infants, have noted altered and even inverted hemodynamic responses to stimuli. Here, we demonstrate that localized neural activity in early postnatal mice does not evoke blood flow increases as in the adult brain, and elucidate the neural and metabolic correlates of these altered functional hemodynamics as a function of developmental age. Using wide-field GCaMP imaging, the development of neural responses to somatosensory stimulus is visualized over the entire bilaterally exposed cortex. Neural responses are observed to progress from tightly localized, unilateral maps to bilateral responses as interhemispheric connectivity becomes established. Simultaneous hemodynamic imaging confirms that spatiotemporally coupled functional hyperemia is not present during these early stages of postnatal brain development, and develops gradually as cortical connectivity is established. Exploring the consequences of this lack of functional hyperemia, measurements of oxidative metabolism via flavoprotein fluorescence suggest that neural activity depletes local oxygen to below baseline levels at early developmental stages. Analysis of hemoglobin oxygenation dynamics at the same age confirms oxygen depletion for both stimulus-evoked and resting-state neural activity. This state of unmet metabolic demand during neural network development poses new questions about the mechanisms of neurovascular development and its role in both normal and abnormal brain development. These results also provide important insights for the interpretation of fMRI studies of the developing brain.

SIGNIFICANCE STATEMENT

This work demonstrates that the postnatal development of neuronal connectivity is accompanied by development of the mechanisms that regulate local blood flow in response to neural activity. Novel in vivo imaging reveals that, in the developing mouse brain, strong and localized GCaMP neural responses to stimulus fail to evoke local blood flow increases, leading to a state in which oxygen levels become locally depleted. These results demonstrate that the development of cortical connectivity occurs in an environment of altered energy availability that itself may play a role in shaping normal brain development. These findings have important implications for understanding the pathophysiology of abnormal developmental trajectories, and for the interpretation of functional magnetic resonance imaging data acquired in the developing brain.

Development and Experimental Validation of a Dry Non-Invasive Multi-Channel Mouse Scalp EEG Sensor through Visual Evoked Potential Recordings

In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An experimental framework targeting the laboratory animals has the potential to lead to successful translational research when it closely resembles the environment of real applications. To serve scalp electroencephalography (EEG) research environments for the laboratory mice, the dry non-invasive scalp EEG sensor with sixteen electrodes is proposed to measure brainwaves over the entire brain area without any surgical procedures. We validated the proposed sensor system with visual evoked potential (VEP) experiments elicited by flash stimulations. The VEP responses obtained from experiments are compared with the existing literature, and analyzed in temporal and spatial perspectives. We further interpret the experimental results using time-frequency distribution (TFD) and distance measurements. The developed sensor guarantees stable operations for in vivo experiments in a non-invasive manner without surgical procedures, therefore exhibiting a high potential to strengthen longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms.

Statistically significant time-varying neural connectivity estimation using generalized partial directed coherence

This paper illustrates the effectiveness of generalized partial directed coherence (gPDC) in characterizing time-varying neural connectivity by properly extrapolating its single trial asymptotic statistical results to a multi trial setting. Time-varying estimation is performed with a sliding-window procedure based on the proposal in [1], whereby a time-frequency map of the connectivity between channels is built. The technique is validated on a non-linear toy model generating simulated EEG and then applied to a publicly available real EEG dataset for benchmarking purposes.

Rapid Postnatal Expansion of Neural Networks Occurs in an Environment of Altered Neurovascular and Neurometabolic Coupling

In the adult brain, increases in neural activity lead to increases in local blood flow. However, many prior measurements of functional hemodynamics in the neonatal brain, including functional magnetic resonance imaging (fMRI) in human infants, have noted altered and even inverted hemodynamic responses to stimuli. Here, we demonstrate that localized neural activity in early postnatal mice does not evoke blood flow increases as in the adult brain, and elucidate the neural and metabolic correlates of these altered functional hemodynamics as a function of developmental age. Using wide-field GCaMP imaging, the development of neural responses to somatosensory stimulus is visualized over the entire bilaterally exposed cortex. Neural responses are observed to progress from tightly localized, unilateral maps to bilateral responses as interhemispheric connectivity becomes established. Simultaneous hemodynamic imaging confirms that spatiotemporally coupled functional hyperemia is not present during these early stages of postnatal brain development, and develops gradually as cortical connectivity is established. Exploring the consequences of this lack of functional hyperemia, measurements of oxidative metabolism via flavoprotein fluorescence suggest that neural activity depletes local oxygen to below baseline levels at early developmental stages. Analysis of hemoglobin oxygenation dynamics at the same age confirms oxygen depletion for both stimulus-evoked and resting-state neural activity. This state of unmet metabolic demand during neural network development poses new questions about the mechanisms of neurovascular development and its role in both normal and abnormal brain development. These results also provide important insights for the interpretation of fMRI studies of the developing brain.

SIGNIFICANCE STATEMENT

This work demonstrates that the postnatal development of neuronal connectivity is accompanied by development of the mechanisms that regulate local blood flow in response to neural activity. Novel in vivo imaging reveals that, in the developing mouse brain, strong and localized GCaMP neural responses to stimulus fail to evoke local blood flow increases, leading to a state in which oxygen levels become locally depleted. These results demonstrate that the development of cortical connectivity occurs in an environment of altered energy availability that itself may play a role in shaping normal brain development. These findings have important implications for understanding the pathophysiology of abnormal developmental trajectories, and for the interpretation of functional magnetic resonance imaging data acquired in the developing brain.

Expression of Npas4 mRNA in Telencephalic Areas of Adult and Postnatal Mouse Brain

The transcription factor neuronal PAS domain-containing protein 4 (Npas4) is an inducible immediate early gene which regulates the formation of inhibitory synapses, and could have a significant regulatory role during cortical circuit formation. However, little is known about basal Npas4 mRNA expression during postnatal development. Here, postnatal and adult mouse brain sections were processed for isotopic in situ hybridization using an Npas4 specific cRNA antisense probe. In adults, Npas4 mRNA was found in the telencephalon with very restricted or no expression in diencephalon or mesencephalon. In most telencephalic areas, including the anterior olfactory nucleus (AON), piriform cortex, neocortex, hippocampus, dorsal caudate putamen (CPu), septum and basolateral amygdala nucleus (BLA), basal Npas4 expression was detected in scattered cells which exhibited strong hybridization signal. In embryonic and neonatal brain sections, Npas4 mRNA expression signals were very low. Starting at postnatal day 5 (P5), transcripts for Npas4 were detected in the AON, CPu and piriform cortex. At P8, additional Npas4 hybridization was found in CA1 and CA3 pyramidal layer, and in primary motor cortex. By P13, robust mRNA expression was located in layers IV and VI of all sensory cortices, frontal cortex and cingulate cortex. After onset of expression, postnatal spatial mRNA distribution was similar to that in adults, with the exception of the CPu, where Npas4 transcripts became gradually restricted to the most dorsal part. In conclusion, the spatial distribution of Npas4 mRNA is mostly restricted to telencephalic areas, and the temporal expression increases with developmental age during postnatal development, which seem to correlate with the onset of activity-driven excitatory transmission.

Brain Source Imaging in Preclinical Rat Models of Focal Epilepsy using High-Resolution EEG Recordings

Electroencephalogram (EEG) has been traditionally used to determine which brain regions are the most likely candidates for resection in patients with focal epilepsy. This methodology relies on the assumption that seizures originate from the same regions of the brain from which interictal epileptiform discharges (IEDs) emerge. Preclinical models are very useful to find correlates between IED locations and the actual regions underlying seizure initiation in focal epilepsy. Rats have been commonly used in preclinical studies of epilepsy; hence, there exist a large variety of models for focal epilepsy in this particular species. However, it is challenging to record multichannel EEG and to perform brain source imaging in such a small animal. To overcome this issue, we combine a patented-technology to obtain 32-channel EEG recordings from rodents and an MRI probabilistic atlas for brain anatomical structures in Wistar rats to perform brain source imaging. In this video, we introduce the procedures to acquire multichannel EEG from Wistar rats with focal cortical dysplasia, and describe the steps both to define the volume conductor model from the MRI atlas and to uniquely determine the IEDs. Finally, we validate the whole methodology by obtaining brain source images of IEDs and compare them with those obtained at different time frames during the seizure onset.

Causal inference in neuronal time-series using adaptive decomposition

BACKGROUND

The assessment of directed functional connectivity from neuronal data is increasingly common in neuroscience by applying measures based in the Granger causality (GC) framework. Although initially these consisted in simple analyses based on directionality strengths, current methods aim to discriminate causal effects both in time and frequency domain.

NEW METHOD

We study the effect of adaptive data analysis on the GC framework by combining empirical mode decomposition (EMD) and causal analysis of neuronal signals. EMD decomposes data into simple amplitude and phase modulated oscillatory modes, the intrinsic mode functions (IMFs), from which it is possible to compute their instantaneous frequencies (IFs). Hence, we propose a method where causality is estimated between IMFs with comparable IFs, in a static or time-varying procedure, and then attributed to the frequencies corresponding to the IF of the driving IMF for improved frequency localization.

RESULTS

We apply a thorough simulation framework involving all possible combinations of EMD algorithms with causality metrics and realistically simulated datasets. Results show that synchrosqueezing wavelet transform and noise-assisted multivariate EMD, paired with generalized partial directed coherence or with Geweke's GC, provide the highest sensitivity and specificity results.

COMPARISON WITH EXISTING METHODS

Compared to standard causal analysis, the output of selected representative instances of this methodology result in the fulfillment of performance criteria in a well-known benchmark with real animal epicranial recordings and improved frequency resolution for simulated neural data.

CONCLUSIONS

This study presents empirical evidence that adaptive data analysis is a fruitful addition to the existing causal framework.

Neurovascular coupling and decoupling in the cortex during voluntary locomotion

Hemodynamic signals are widely used to infer neural activity in the brain. We tested the hypothesis that hemodynamic signals faithfully report neural activity during voluntary behaviors by measuring cerebral blood volume (CBV) and neural activity in the somatosensory cortex and frontal cortex of head-fixed mice during locomotion. Locomotion induced a large and robust increase in firing rate and gamma-band (40-100 Hz) power in the local field potential in the limb representations in somatosensory cortex, and was accompanied by increases in CBV, demonstrating that hemodynamic signals are coupled with neural activity in this region. However, in the frontal cortex, CBV did not change during locomotion, but firing rate and gamma-band power both increased, indicating a decoupling of neural activity from the hemodynamic signal. These results show that hemodynamic signals are not faithful indicators of the mean neural activity in the frontal cortex during locomotion; thus, the results from fMRI and other hemodynamic imaging methodologies for studying neural processes must be interpreted with caution.

Mapping epileptic activity: sources or networks for the clinicians?

Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity.

Development of an implantable flexible probe for simultaneous near-infrared spectroscopy and electrocorticography

A combination of near-infrared spectroscopy (NIRS) and electrocorticography (ECoG) provides beneficial information on cortical activity from different aspects. Integration of such multimodal measurement capability into a single apparatus and the direct measurement of cortical activity during chronic subdural implantation may be a powerful means for clinical diagnosis and neuroscience. However, an optical fiber-based NIRS probe cannot be miniaturized for implantation into the brain, and the light-scattering effect of ECoG electrodes in NIRS measurements is unknown. We describe here the development of a flexible probe, small enough for chronic subdural implantation, for simultaneous NIRS and ECoG. Two light-emitting diodes of different wavelengths and two photodiodes were mounted on a polyimide-based flexible substrate, and ECoG electrodes were formed with a design minimizing artifacts in NIRS recording. The fabricated probe measured ECoGs at sufficient spatial resolution and submicromolar changes in hemoglobin concentrations in in vivo experiments with acute implantation into a rat. Comparison of measured changes in hemoglobin concentrations for different source-detector distances reveals the reliability of the measured values and the practicality of the simulation model. The proposed intracranial multimodality probe may provide beneficial evidence for pre- and intrasurgical assessment of neurosurgery and reveal the interaction of electrophysiology and hemodynamics at high spatial resolution without artifacts due to scalp blood flow.

Dynamic connectivity among cortical layers in local and large-scale sensory processing

Cortical processing of sensory stimuli typically recruits multiple areas, but how each area dynamically incorporates activity from other areas is not well understood. We investigated interactions between cortical columns of bilateral primary sensory regions (S1s) in rats by recording local field potentials and multi-unit activity simultaneously in both S1s with electrodes positioned at each cortical layer. Using dynamic connectivity analysis based on Granger-causal modeling, we found that, shortly after whisker stimulation (< 10 ms), contralateral S1 (cS1) already relays activity to granular and infragranular layers of S1 in the other hemisphere, after which cS1 shows a pattern of within-column interactions that directs activity upwards toward superficial layers. This pattern of predominant upward driving was also observed in S1 ipsilateral to stimulation, but at longer latencies. In addition, we found that interactions between the two S1s most strongly target granular and infragranular layers. Taken together, the results suggest a possible mechanism for how cortical columns integrate local and large-scale neocortical computation by relaying information from deeper layers to local processing in superficial layers.

Whole-scalp EEG mapping of somatosensory evoked potentials in macaque monkeys

High-density scalp EEG recordings are widely used to study whole-brain neuronal networks in humans non-invasively. Here, we validate EEG mapping of somatosensory evoked potentials (SSEPs) in macaque monkeys (Macaca fascicularis) for the long-term investigation of large-scale neuronal networks and their reorganisation after lesions requiring a craniotomy. SSEPs were acquired from 33 scalp electrodes in five adult anaesthetized animals after electrical median or tibial nerve stimulation. SSEP scalp potential maps were identified by cluster analysis and identified in individual recordings. A distributed, linear inverse solution was used to estimate the intracortical sources of the scalp potentials. SSEPs were characterised by a sequence of components with unique scalp topographies. Source analysis confirmed that median nerve SSEP component maps were in accordance with the somatotopic organisation of the sensorimotor cortex. Most importantly, SSEP recordings were stable both intra- and interindividually. We aim to apply this method to the study of recovery and reorganisation of large-scale neuronal networks following a focal cortical lesion requiring a craniotomy. As a prerequisite, the present study demonstrated that a 300-mm² unilateral craniotomy over the sensorimotor cortex necessary to induce a cortical lesion, followed by bone flap repositioning, suture and gap plugging with calcium phosphate cement, did not induce major distortions of the SSEPs. In conclusion, SSEPs can be successfully and reproducibly recorded from high-density EEG caps in macaque monkeys before and after a craniotomy, opening new possibilities for the long-term follow-up of the cortical reorganisation of large-scale networks in macaque monkeys after a cortical lesion.

The physiological plausibility of time-varying Granger-causal modeling: normalization and weighting by spectral power

Time-varying connectivity methods are increasingly used to study directed interactions between brain regions from electrophysiological signals. These methods often show good results in simulated data but it is unclear to what extent connectivity results obtained from real data are physiologically plausible. Here we introduce a benchmark approach using multichannel somatosensory evoked potentials (SEPs) measured across rat cortex, where the structural and functional connectivity is relatively simple and well-understood. Rat SEPs to whisker stimulation are exclusively initiated by contralateral primary sensory cortex (S1), at known latencies, and with activity spread from S1 to specific cortical regions. This allows for a comparison of time-varying connectivity measures according to fixed criteria. We thus evaluated the performance of time-varying Partial Directed Coherence (PDC) and the Directed Transfer Function (DTF), comparing row- and column-wise normalization and the effect of weighting by the power spectral density (PSD). The benchmark approach revealed clear differences between methods in terms of physiological plausibility, effect size and temporal resolution. The results provide a validation of time-varying directed connectivity methods in an animal model and suggest a driving role for ipsilateral S1 in the later part of the SEP. The benchmark SEP dataset is made freely available.

Preterm birth affects the developmental synergy between cortical folding and cortical connectivity observed on multimodal MRI

The survival rates of infants born prematurely have improved as a result of advances in neonatal care, although there remains an increased risk of subsequent disability. Accurate measurement of the shape and appearance of the very preterm brain at term-equivalent age may guide the development of predictive biomarkers of neurological outcome. We demonstrate in 92 preterm infants (born at an average gestational age of 27.0±2.7weeks) scanned at term equivalent age (scanned at 40.4±1.74weeks) that the cortical sulcation ratio varies spatially over the cortical surface at term equivalent age and correlates significantly with gestational age at birth (r=0.49,p<0.0001). In the underlying white matter, fractional anisotropy of local white matter regions correlated significantly with gestational age at birth at term equivalent age (for the genu of the corpus callosum r=0.26,p=0.02 and for the splenium r=0.52,p<0.001) and in addition the fractional anisotropy in these local regions varies according to location. Finally, we demonstrate that connectivity measurements from tractography correlate significantly and specifically with the sulcation ratio of the overlying cortical surface at term equivalent age in a subgroup of 20 infants (r={0.67,0.61,0.86}, p={0.004,0.01,0.00002}) for tract systems emanating from the left and right corticospinal tracts and the corpus callosum respectively). Combined, these results suggest a close relationship between the cortical surface phenotype and underlying white matter structure assessed by diffusion weighted MRI. The spatial surface pattern may allow inference on the connectivity and developmental trajectory of the underlying white matter complementary to diffusion imaging and this result may guide the development of biomarkers of functional outcome.

Voltage-sensitive dye imaging reveals dynamic spatiotemporal properties of cortical activity after spontaneous muscle twitches in the newborn rat

Spontaneous activity in the developing brain contributes to its maturation, but how this activity is coordinated between distinct cortical regions and whether it might reflect developing sensory circuits is not well understood. Here, we address this question by imaging the spread and synchronization of cortical activity using voltage-sensitive dyes (VSDs) in the developing rat in vivo. In postnatal day 4-6 rats (n = 10), we collected spontaneous changes in VSD signal that reflect underlying membrane potential changes over a large craniotomy (50 mm2) that encompassed both the sensory and motor cortices of both hemispheres. Bursts of depolarization that occurred approximately once every 12 s were preceded by spontaneous twitches of the hindlimbs and/or tail. The close association with peripheral movements suggests that these bursts may represent a slow component of spindle bursts, a prominent form of activity in the developing somatosensory cortex. Twitch-associated cortical activity was synchronized between subregions of somatosensory cortex, which reflected the synchronized twitching of the limbs and tail. This activity also spread asymmetrically, toward the midline of the brain. We found that the spatial and temporal structure of such spontaneous cortical bursts closely matched that of sensory-evoked activity elicited via direct stimulation of the periphery. These data suggest that spontaneous cortical activity provides a recurring template of functional cortical circuits within the developing cortex and could contribute to the maturation of integrative connections between sensory and motor cortices.

Distinct developmental principles underlie the formation of ipsilateral and contralateral whisker-related axonal patterns of layer 2/3 neurons in the barrel cortex

Axonal organizations with specific patterns underlie the functioning of local intracortical circuitry, but their precise anatomy and development still remain elusive. Here, we selectively visualized layer 2/3 neurons using in utero electroporation and examined their axonal organization in the barrel cortex contralateral to the electroporated side. We found that callosal axons run preferentially in septal regions of layer 4 and showed a whisker-related pattern in the contralateral barrel cortex in rats and mice. In addition, presynaptic marker proteins were found in this whisker-related axonal organization. Although the whisker-related patterns were observed in both the ipsilateral and contralateral barrel cortex, we found a difference in their developmental processes. While the formation of the whisker-related pattern in the ipsilateral cortex consisted of two distinct steps, that in the contralateral cortex did not have the 1st step, in which the axons were diffusely distributed without preference to septal or barrel regions. We also found that these more diffuse axons ran close to radial glial fibers. Together, our results uncovered a whisker-related axonal pattern of callosal axons and two independent developmental processes involved in the formation of the axonal trajectories of layer 2/3 neurons.