Functional parcellation of the neonatal cortical surface

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

Functional parcellation of the neonatal brain

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that adult- and older infant-derived parcels are a poor fit with neonatal data, emphasizing the need for neonatal-specific parcels. We next derive a set of 283 cortical surface parcels from a sample of n=261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies.

The organization and development of cortical interneuron presynaptic circuits are area specific

Parvalbumin and somatostatin inhibitory interneurons gate information flow in discrete cortical areas that compute sensory and cognitive functions. Despite the considerable differences between areas, individual interneuron subtypes are genetically invariant and are thought to form canonical circuits regardless of which area they are embedded in. Here, we investigate whether this is achieved through selective and systematic variations in their afferent connectivity during development. To this end, we examined the development of their inputs within distinct cortical areas. We find that interneuron afferents show little evidence of being globally stereotyped. Rather, each subtype displays characteristic regional connectivity and distinct developmental dynamics by which this connectivity is achieved. Moreover, afferents dynamically regulated during development are disrupted by early sensory deprivation and in a model of fragile X syndrome. These data provide a comprehensive map of interneuron afferents across cortical areas and reveal the logic by which these circuits are established during development.

Where We Mentalize: Main Cortical Areas Involved in Mentalization

When discussing “mentalization,” we refer to a very special ability that only humans and few species of great apes possess: the ability to think about themselves and to represent in their mind their own mental state, attitudes, and beliefs and those of others. In this review, a summary of the main cortical areas involved in mentalization is presented. A thorough literature search using PubMed MEDLINE database was performed. The search terms “cognition,” “metacognition,” “mentalization,” “direct electrical stimulation,” “theory of mind,” and their synonyms were combined with “prefrontal cortex,” “temporo-parietal junction,” “parietal cortex,” “inferior frontal gyrus,” “cingulate gyrus,” and the names of other cortical areas to extract relevant published papers. Non-English publications were excluded. Data were extracted and analyzed in a qualitative manner. It is the authors' belief that knowledge of the neural substrate of metacognition is essential not only for the “neuroscientist” but also for the “practical neuroscientist” (i.e., the neurosurgeon), in order to better understand the pathophysiology of mentalizing dysfunctions in brain pathologies, especially those in which integrity of cortical areas or white matter connectivity is compromised. Furthermore, in the context of neuro-oncological surgery, understanding the anatomical structures involved in the theory of mind can help the neurosurgeon obtain a wider and safer resection. Though beyond of the scope of this paper, an important but unresolved issue concerns the long-range white matter connections that unify these cortical areas and that may be themselves involved in neural information processing.

Local neuronal relational structures underlying the contents of human conscious experience

While most theories of consciousness posit some kind of dependence on global network activities, I consider here an alternative, localist perspective-in which localized cortical regions each underlie the emergence of a unique category of conscious experience. Under this perspective, the large-scale activation often found in the cortex is a consequence of the complexity of typical conscious experiences rather than an obligatory condition for the emergence of conscious awareness-which can flexibly shift, depending on the richness of its contents, from local to more global activation patterns. This perspective fits a massive body of human imaging, recordings, lesions and stimulation data but opens a fundamental problem: how can the information, defining each content, be derived locally in each cortical region. Here, I will discuss a solution echoing pioneering structuralist ideas in which the content of a conscious experience is defined by its relationship to all other contents within an experiential category. In neuronal terms, this relationship structure between contents is embodied by the local geometry of similarity distances between cortical activation patterns generated during each conscious experience, likely mediated via networks of local neuronal connections. Thus, in order for any conscious experience to appear in an individual's mind, two central conditions must be met. First, a specific configural pattern ("bar-code") of neuronal activity must appear within a local relational geometry, i.e. a cortical area. Second, the individual neurons underlying the activated pattern must be bound into a unified functional ensemble through a burst of recurrent neuronal firing: local "ignitions".

Self-organization of cortical areas in the development and evolution of neocortex

While the mechanisms generating the topographic organization of primary sensory areas in the neocortex are well studied, what generates secondary cortical areas is virtually unknown. Using physical parameters representing primary and secondary visual areas as they vary from monkey to mouse, we derived a network growth model to explore if characteristic features of secondary areas could be produced from correlated activity patterns arising from V1 alone. We found that V1 seeded variable numbers of secondary areas based on activity-driven wiring and wiring-density limits within the cortical surface. These secondary areas exhibited the typical mirror-reversal of map topography on cortical area boundaries and progressive reduction of the area and spatial resolution of each new map on the caudorostral axis. Activity-based map formation may be the basic mechanism that establishes the matrix of topographically organized cortical areas available for later computational specialization.

Dorsal White Matter Integrity and Name Retrieval in Midlife

Abstract:

Background: Recent findings on retrieval of proper names in cognitively healthy middle-aged persons indicate that Tip-Of-The-Tongue (TOT) states occurring during proper name retrieval implicate inferior frontal (BA 44) and parietal (BA 40) cortical areas. Such findings give rise to the possibility that anatomical connectivity via dorsal white matter may be associated with difficulties in name retrieval in midlife.

Objectives & Method:

Using Diffusion Tensor Imaging, we examined in vivo microstructural properties of white matter in 72 cognitively healthy Middle-Aged (MA) and 59 Young Adults (YA), comparing their naming abilities as well as testing, for possible associations between dorsal white matter integrity and naming abilities in the MA group.

Results:

The MA group was better in retrieving correct names (U = 1525.5, p = .006), but they also retrieved more incorrect names than YA believing they had retrieved the correct ones (U = 1265.5, p < .001). Furthermore, despite being more familiar with the tested names than YA (U = 930, p < .001), MA experienced significantly more TOTs relative to YA (U = 1498.5, p = .004). Tract-based spatial statistics showed significant group differences in values of fractional anisotropy (FA), mean diffusivity, axial diffusivity, radial diffusivity, and mode of anisotropy in a range of white matter tracts. In the MA group, FA values in the right Superior Longitudinal Fasciculus (SLF) were positively correlated with “don’t know” scores (rs = .287, p = .014).

Conclusion:

The association of SLF integrity and name retrieval ability in midlife indicates a need to revisit the models of name retrieval that posit no role for dorsal white matter in proper name retrieval.

Imbalance between Emotionally Negative and Positive Life Events Retrieval and the Associated Asymmetry of Brain Activity

Sustained focusing on a negative assessment of life events can create negative background and changes in the emotional feedback to new information. In this regard, it is important to assess the balance between self-assessment of emotional memories and their reflection in brain activity. The study was aimed at exploring the brain activity using electroencephalographic (EEG) analysis in six frequency ranges from delta to beta2 during the retrieval of positive or negative emotional memory compared with the resting state. According to ANOVA results, the most informative for differentiation of emotions were the alpha2 and beta2 rhythms with greater synchronization effect for positive than for negative emotions. The memory retrieval, regardless of the valence of emotions, was accompanied by alpha1 desynchronization at the posterior cortex. Self-assessment of the memory intensity was not significantly different due to emotion valences. However, the scores of positive emotions were related positively with beta2 oscillations at the left anterior temporal site, whereas for negative emotions, at the right one. Thus, the emotional autobiographical memory is reflected by activation processes in the visual cortex and areas associated with multimodal information processing, whereas differentiation of the valence of emotions is presented by the high-frequency oscillations at the temporal cortex areas.

Analysis Pipeline for Extracting Features of Cortical Slow Oscillations

Cortical slow oscillations (≲1 Hz) are an emergent property of the cortical network that integrate connectivity and physiological features. This rhythm, highly revealing of the characteristics of the underlying dynamics, is a hallmark of low complexity brain states like sleep, and represents a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal properties of this emergent activity. We improved and enriched a robust analysis procedure that has already been successfully applied to both in vitro and in vivo data acquisitions. We tested the new tools of the methodology by analyzing the electrocorticography (ECoG) traces recorded from a custom 32-channel multi-electrode array in wild-type isoflurane-anesthetized mice. The enhanced analysis pipeline, named SWAP (Slow Wave Analysis Pipeline), detects Up and Down states, enables the characterization of the spatial dependency of their statistical properties, and supports the comparison of different subjects. The SWAP is implemented in a data-independent way, allowing its application to other data sets (acquired from different subjects, or with different recording tools), as well as to the outcome of numerical simulations. By using the SWAP, we report statistically significant differences in the observed slow oscillations (SO) across cortical areas and cortical sites. Computing cortical maps by interpolating the features of SO acquired at the electrode positions, we give evidence of gradients at the global scale along an oblique axis directed from fronto-lateral toward occipito-medial regions, further highlighting some heterogeneity within cortical areas. The results obtained using the SWAP will be essential for producing data-driven brain simulations. A spatial characterization of slow oscillations will also trigger a discussion on the role of, and the interplay between, the different regions in the cortex, improving our understanding of the mechanisms of generation and propagation of delta rhythms and, more generally, of cortical properties.

Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo

Complementing long-standing traditions centered on histology, fMRI approaches are rapidly maturing in delineating brain areal organization at the macroscale. The non-human primate (NHP) provides the opportunity to overcome critical barriers in translational research. Here, we establish the data requirements for achieving reproducible and internally valid parcellations in individuals. We demonstrate that functional boundaries serve as a functional fingerprint of the individual animals and can be achieved under anesthesia or awake conditions (rest, naturalistic viewing), though differences between awake and anesthetized states precluded the detection of individual differences across states. Comparison of awake and anesthetized states suggested a more nuanced picture of changes in connectivity for higher-order association areas, as well as visual and motor cortex. These results establish feasibility and data requirements for the generation of reproducible individual-specific parcellations in NHPs, provide insights into the impact of scan state, and motivate efforts toward harmonizing protocols.

Computational architecture of a visual model for biological motions segregation

This paper outlines a neural model inspired by the dorsal stream of the visual system for motion recognition. Two areas are considered: the primary visual area (V1) and the middle temporal area (MT). In model area, V1 neurons are organized to detect eight local motion directions. MT is modelled using classical receptive field (CRF), where the cells respond to wide-field motion. The biological motion can be identified through spatial motion dynamics for the limbs and body. In this article, we propose spatio-temporal sampling detectors, where a set of circular masks over motion scenario are utilized to detect the motion dynamics. Two alternative mechanisms, Max-pooling and Sum-pooling, are used to extracting spatio-temporal descriptors from motion energy occupied by the circular masks. To improve the classification results, centroid kinematics is added to the feature vectors, where this feature contributes substantially to characterizing the motion pattern of an action. We evaluate our model by using two challenging datasets: the Weizmann biological action dataset and the KTH biological motion dataset. Our results reflect the potential of spatio-temporal sampling detectors in describing the biological motion of body and limbs using only short video frames (snippets). In addition, the centroid kinematic feature improves the recognition rate and refines the action classification.

Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans

The cerebral cortex in mammals contains a mosaic of cortical areas that differ in function, architecture, connectivity, and/or topographic organization. A combination of local connectivity (within-area microcircuitry) and long-distance (between-area) connectivity enables each area to perform a unique set of computations. Some areas also have characteristic within-area mesoscale organization, reflecting specialized representations of distinct types of information. Cortical areas interact with one another to form functional networks that mediate behavior, and each area may be a part of multiple, partially overlapping networks. Given their importance to the understanding of brain organization, mapping cortical areas across species is a major objective of systems neuroscience and has been a century-long challenge. Here, we review recent progress in multi-modal mapping of mouse and nonhuman primate cortex, mainly using invasive experimental methods. These studies also provide a neuroanatomical foundation for mapping human cerebral cortex using noninvasive neuroimaging, including a new map of human cortical areas that we generated using a semiautomated analysis of high-quality, multimodal neuroimaging data. We contrast our semiautomated approach to human multimodal cortical mapping with various extant fully automated human brain parcellations that are based on only a single imaging modality and offer suggestions on how to best advance the noninvasive brain parcellation field. We discuss the limitations as well as the strengths of current noninvasive methods of mapping brain function, architecture, connectivity, and topography and of current approaches to mapping the brain's functional networks.

Intrinsic functional architecture of the macaque dorsal and ventral lateral frontal cortex

Investigations of the cellular and connectional organization of the lateral frontal cortex (LFC) of the macaque monkey provide indispensable knowledge for generating hypotheses about the human LFC. However, despite numerous investigations, there are still debates on the organization of this brain region. In vivo neuroimaging techniques such as resting-state functional magnetic resonance imaging (fMRI) can be used to define the functional circuitry of brain areas, producing results largely consistent with gold-standard invasive tract-tracing techniques and offering the opportunity for cross-species comparisons within the same modality. Our results using resting-state fMRI from macaque monkeys to uncover the intrinsic functional architecture of the LFC corroborate previous findings and inform current debates. Specifically, within the dorsal LFC, we show that 1) the region along the midline and anterior to the superior arcuate sulcus is divided in two areas separated by the posterior supraprincipal dimple, 2) the cytoarchitectonically defined area 6DC/F2 contains two connectional divisions, and 3) a distinct area occupies the cortex around the spur of the arcuate sulcus, updating what was previously proposed to be the border between dorsal and ventral motor/premotor areas. Within the ventral LFC, the derived parcellation clearly suggests the presence of distinct areas: 1) an area with a somatomotor/orofacial connectional signature (putative area 44), 2) an area with an oculomotor connectional signature (putative frontal eye fields), and 3) premotor areas possibly hosting laryngeal and arm representations. Our results illustrate in detail the intrinsic functional architecture of the macaque LFC, thus providing valuable evidence for debates on its organization.NEW & NOTEWORTHY Resting-state functional MRI is used as a complementary method to invasive techniques to inform current debates on the organization of the macaque lateral frontal cortex. Given that the macaque cortex serves as a model for the human cortex, our results help generate more fine-tuned hypothesis for the organization of the human lateral frontal cortex.

Generation and Evaluation of a Cortical Area Parcellation from Resting-State Correlations

The cortical surface is organized into a large number of cortical areas; however, these areas have not been comprehensively mapped in the human. Abrupt transitions in resting-state functional connectivity (RSFC) patterns can noninvasively identify locations of putative borders between cortical areas (RSFC-boundary mapping; Cohen et al. 2008). Here we describe a technique for using RSFC-boundary maps to define parcels that represent putative cortical areas. These parcels had highly homogenous RSFC patterns, indicating that they contained one unique RSFC signal; furthermore, the parcels were much more homogenous than a null model matched for parcel size when tested in two separate datasets. Several alternative parcellation schemes were tested this way, and no other parcellation was as homogenous as or had as large a difference compared with its null model. The boundary map-derived parcellation contained parcels that overlapped with architectonic mapping of areas 17, 2, 3, and 4. These parcels had a network structure similar to the known network structure of the brain, and their connectivity patterns were reliable across individual subjects. These observations suggest that RSFC-boundary map-derived parcels provide information about the location and extent of human cortical areas. A parcellation generated using this method is available at http://www.nil.wustl.edu/labs/petersen/Resources.html.

Cortico-cortical communication dynamics

In principle, cortico-cortical communication dynamics is simple: neurons in one cortical area communicate by sending action potentials that release glutamate and excite their target neurons in other cortical areas. In practice, knowledge about cortico-cortical communication dynamics is minute. One reason is that no current technique can capture the fast spatio-temporal cortico-cortical evolution of action potential transmission and membrane conductances with sufficient spatial resolution. A combination of optogenetics and monosynaptic tracing with virus can reveal the spatio-temporal cortico-cortical dynamics of specific neurons and their targets, but does not reveal how the dynamics evolves under natural conditions. Spontaneous ongoing action potentials also spread across cortical areas and are difficult to separate from structured evoked and intrinsic brain activity such as thinking. At a certain state of evolution, the dynamics may engage larger populations of neurons to drive the brain to decisions, percepts and behaviors. For example, successfully evolving dynamics to sensory transients can appear at the mesoscopic scale revealing how the transient is perceived. As a consequence of these methodological and conceptual difficulties, studies in this field comprise a wide range of computational models, large-scale measurements (e.g., by MEG, EEG), and a combination of invasive measurements in animal experiments. Further obstacles and challenges of studying cortico-cortical communication dynamics are outlined in this critical review.

Systematic, balancing gradients in neuron density and number across the primate isocortex

The cellular and areal organization of the cerebral cortex impacts how it processes and integrates information. How that organization emerges and how best to characterize it has been debated for over a century. Here we demonstrate and describe in the isocortices of seven primate species a pronounced anterior-to-posterior gradient in the density of neurons and in the number of neurons under a unit area of the cortical surface. Our findings assert that the cellular architecture of the primate isocortex is neither arranged uniformly nor into discrete patches with an arbitrary spatial arrangement. Rather, it exhibits striking systematic variation. We conjecture that these gradients, which establish the basic landscape that richer areal and cellular structure is built upon, result from developmental patterns of cortical neurogenesis which are conserved across species. Moreover, we propose a functional consequence: that the gradient in neurons per unit of cortical area fosters the integration and dimensional reduction of information along its ascent through sensory areas and toward frontal cortex.

Microstructural Parcellation of the Human Cerebral Cortex - From Brodmann's Post-Mortem Map to in vivo Mapping with High-Field Magnetic Resonance Imaging

The year 2009 marked the 100th anniversary of the publication of the famous brain map of Korbinian Brodmann. Although a “classic” guide to microanatomical parcellation of the cerebral cortex, it is – from today's state-of-the-art neuroimaging perspective – problematic to use Brodmann's map as a structural guide to functional units in the cortex. In this article we discuss some of the reasons, especially the problematic compatibility of the “post-mortem world” of microstructural brain maps with the “in vivo world” of neuroimaging. We conclude with some prospects for the future of in vivo structural brain mapping: a new approach which has the enormous potential to make direct correlations between microstructure and function in living human brains: “in vivo Brodmann mapping” with high-field magnetic resonance imaging.

Architectonic subdivisions of neocortex in the gray squirrel (Sciurus carolinensis)

Squirrels are highly visual mammals with an expanded cortical visual system and a number of well-differentiated architectonic fields. To describe and delimit cortical fields, subdivisions of cortex were reconstructed from serial brain sections cut in the coronal, sagittal, or horizontal planes. Architectonic characteristics of cortical areas were visualized after brain sections were processed with immunohistochemical and histochemical procedures for revealing parvalbumin, calbindin, neurofilament protein, vesicle glutamate transporter 2, limbic-associated membrane protein, synaptic zinc, cytochrome oxidase, myelin or Nissl substance. In general, these different procedures revealed similar boundaries between areas, suggesting that functionally relevant borders were being detected. The results allowed a more precise demarcation of previously identified areas as well as the identification of areas that had not been previously described. Primary sensory cortical areas were characterized by sparse zinc staining of layer 4, as thalamocortical terminations lack zinc, as well as by layer 4 terminations rich in parvalbumin and vesicle glutamate transporter 2. Primary areas also expressed higher levels of cytochrome oxidase and myelin. Primary motor cortex was associated with large SMI-32 labeled pyramidal cells in layers 3 and 5. Our proposed organization of cortex in gray squirrels includes both similarities and differences to the proposed of cortex in other rodents such as mice and rats. The presence of a number of well-differentiated cortical areas in squirrels may serve as a guide to the identification of homologous fields in other rodents, as well as a useful guide in further studies of cortical organization and function.

Differential expression of COUP-TFI, CHL1, and two novel genes in developing neocortex identified by differential display PCR

Genes that control the specification and differentiation of the functionally specialized areas of the mammalian neocortex are likely expressed across the developing neocortex in graded or restricted patterns. To search for such genes we have performed a PCR-based differential display screen using RNAs from rostral neocortex, which included the primary motor area, and caudal neocortex, which included the primary visual area, of embryonic day 16 rats. We identified 82 differentially expressed gene fragments. Secondary screening by in situ hybridization confirmed that five fragments, representing four genes, are differentially expressed across developing rat neocortex. Two of the genes, chick ovalbumin upstream transcription factor I (COUP-TFI) and close homolog of L1 (CHL1), have been cloned previously, but their differential expression in cortex has not been reported. Sequences from the other two fragments suggest that they represent novel genes. The expression patterns include graded, restricted, and discontinuous expression with abrupt borders that might correlate with those of areas. The differential expression patterns of all four genes are established before the arrival of thalamocortical afferents, suggesting that they are independent of thalamic influence, and could direct or reflect arealization. In addition, COUP-TFI and CHL1 exhibit dynamic expression patterns that undergo substantial changes after thalamocortical afferents invade the cortical plate, suggesting that thalamic axons may influence their later expression. Postnatally, COUP-TFI is most prominently expressed in layer 4, in both rats and mice, and CHL1 is expressed in layer 5. COUP-TFI expression in cortex, and in ventral telencephalon and dorsal thalamus, suggests several possible causes for the loss of layer 4 neurons and the reduced thalamocortical projection reported in COUP-TFI knock-out mice.

Membrane-associated molecules guide limbic and nonlimbic thalamocortical projections

Membrane-associated signals expressed in restricted domains of the developing cerebral cortex may mediate axon target recognition during the establishment of thalamocortical projections, which form in a highly precise manner during development. To test this hypothesis, we first analyzed the outgrowth of thalamic explants from limbic and nonlimbic nuclei on membrane substrates prepared from limbic cortex and neocortex. The results show that different thalamic fiber populations are able to discriminate between membrane substrates prepared from target and nontarget cortical regions. A candidate molecule that could mediate selective choice in the thalamocortical system is the limbic system-associated membrane protein (LAMP), which is an early marker of cortical and subcortical limbic regions (Pimenta et al.,1995) that can promote outgrowth of limbic axons. Limbic thalamic and cortical axons showed preferences for recombinant LAMP (rLAMP) in a stripe assay. Incubation of cortical membranes with an antibody against LAMP prevented the ability of limbic thalamic fibers to distinguish between membranes from limbic cortex and neocortex. Strikingly, nonlimbic thalamic fibers also responded to LAMP, but in contrast to limbic thalamic fibers, rLAMP inhibited branch formation and acted as a repulsive axonal guidance signal for nonlimbic thalamic axons. The present studies indicate that LAMP fulfills a role as a selective guidance cue in the developing thalamocortical system.