Academic literature on the topic 'Cortical layers'

During development of the thalamocortical projection, afferent fibers from the thalamus reach the cortex at a time when their target cells have just been generated but have not yet migrated to their final position. Thalamic axons begin to invade the cortex only shortly before their target layer 4 is formed. The mechanisms responsible for the innervation and termination of thalamic fibers in the cortex are not known. Here we show that the growth of thalamic axons in vitro is influenced by the age of cortical explants. Cortical explants of early embryonic stages were not invaded by thalamic explants, whereas thalamic fibers entered explants from postnatal cortices and terminated properly in their target layer 4 in vitro. Outgrowth assays on cortical cell membranes prepared at different developmental stages revealed that the growth of thalamic axons is selectively influenced by growth- promoting molecules that are up-regulated during development. Moreover, experiments with postnatal cortical membranes isolated from distinct layers revealed that the growth of thalamic axons is selectively reduced on membranes prepared from layer 4. These results provide evidence that membrane-bound molecules in the cortex are involved in both the regulation of thalamic innervation into the cortical layers and their termination in the correct target layer.

Neurotrophin-3 and its receptor TrkC are expressed during the development of the mammalian cerebral cortex. To examine whether neurotrophin-3 might play a role in the elaboration of layer-specific cortical circuits, slices of layer 6 and layers 2/3 neurons were cultured in the presence of exogenously applied neurotrophin-3. Results indicate that neurotrophin-3 promotes axonal branching of layer 6 axons, which target neurotrophin-3-expressing layers in vivo, and that it inhibits branching of layers 2/3 axons, which avoid neurotrophin-3-expressing layers. Such opposing effects of neurotrophin-3 on axonal branching were also observed with embryonic cortical neurons, indicating that the response to neurotrophin-3 is specified at early developmental stages, prior to cell migration. In addition to its effects on fiber branching, axonal guidance assays also indicate that neurotrophin-3 is an attractive signal for layer 6 axons and a repellent guidance cue for layers 2/3 axons. Experiments with specific antibodies to neutralize neurotrophin-3 in cortical membranes revealed that endogenous levels of neurotrophin-3 are sufficient to regulate branching and targeting of cortical axons. These opposing effects of neurotrophin-3 on specific populations of axons demonstrate that it could serve as one of the signals for the elaboration of local cortical circuits.

SUMMARYThe cuticle of adult forms of Strongyloides venezuelensis was studied by routine transmission electron microscopy, conventional freeze-fracture and also using quick-freeze and deep-etch techniques. In routine thin sections the cuticle of S. venezuelensis comprises 7 layers: epicuticle, outer cortical, inner corticcal, external medial, internal medial, fibrous and basal. Observation of replicas of specimens fractured across the thickness of the body wall, revealed at the epicuticle an ordered array of particles accompanying the cuticular annulations. At the level of the cortical and medial layers we observed few scattered particles embedded in an amorphous matrix without a particular arrangement. The fibrous layer was represented by several parallel lines of ordered particles of similar size. In tangentially fractured specimens, the epicuticle cleaves readily exposing 2 faces, one exhibiting intramembranous particles without any particular arrangement, immersed in a smooth matrix (P face), and the other showing depressions and very few particles (E face). In replicas of fractures submitted to etching, we observed at the level of the cortical, medial fibrous and basal layers an interconnecting fibrous and globous structure which was organized in a different direction at the fibrous layer. The association of freeze-fracture to deep-etch technique revealed the internal structural organization of the cuticle layers showing details that were not seen before using conventional freeze–fracture technique.

1. Spontaneous and stimulus-induced activity were recorded from corresponding somatotopic representations in the ventroposterolateral nucleus (VPL) of the thalamus and primary somatosensory (SI) cortex of intact, halothane-anesthetized cats. Thalamic and cortical neurons with overlapping receptive fields on the hairy skin of the forelimb were excited by a series of interleaved air jets aimed at multiple skin sites. 2. The laminar locations of 68% (240 of 355) of the neurons recorded in SI cortex were histologically reconstructed and responses of these 240 SI neurons were analyzed with respect to responses recorded from 118 thalamic neurons. Maximum responsiveness during the initial onset (1st 100 ms) of air jet stimulation was similar for neurons distributed throughout all layers of SI cortex (2-4 spikes per stimulus) and did not differ significantly from VPL responses. During the subsequent plateau phase of the stimulus, VPL neurons discharged at a mean rate of 19.0 spikes/ s and neurons in cortical layers II, IIIa, IIIb, and IV discharged at similar rates. Mean responsiveness during the plateau phase of the stimulus was significantly reduced among neurons in cortical layers V and VI and only averaged 7.1 and 3.9 spikes/s, respectively. 3. Responses recorded simultaneously from pairs of thalamic and cortical neurons were analyzed with cross-correlation analysis to determine differences in the incidence and strength of neuronal interactions as a function of cortical layer. Among 421 thalamocortical neuron pairs displaying stimulus-induced responses, 68 neuron pairs exhibited significant interactions during air jet stimulation. A laminar analysis revealed that 28% (45 of 163) of the neurons in the middle cortical layers displayed significant interactions with thalamic neurons, whereas only 14% (13 of 92) of superficial layer neurons and 6% (10 of 166) of deep layer neurons were synchronized with thalamic activity during air jet stimulation. When thalamocortical efficacy for different layers of cortex was plotted as a cumulative frequency distribution, the strongest interactions in the middle cortical layers were twice as strong as interactions involving the superficial or deep cortical layers. 4. More than 70% of stimulus-induced interactions involved thalamic discharges followed by subsequent cortical discharges and the majority of these interactions involved interspike intervals of < or = 3 ms. Nearly 75% (27 of 37) of interactions in the thalamocortical direction that involved cortical neurons in layers IIIb and IV transpired within a 3-ms interspike interval. For interactions with superficial or deep cortical layers, the proportion of thalamocortical interactions transpiring within 3 ms was only 58% (7 of 12) and 33% (2 of 6), respectively. 5. Cross-correlation analysis of spontaneous activity indicated that 124 pairs of thalamic and cortical neurons displayed synchronous activity in the absence of sensory stimulation. A laminar analysis indicated that similar proportions of cortical neurons in each layer were synchronized with thalamic activity in the absence of cutaneous stimulation. Thus 27% (44 of 163) of middle layer neurons, 30% (28 of 92) of superficial layer neurons, and 31% (51 of 166) of deep layer neurons displayed spontaneous interactions with thalamic neurons. The temporal pattern of spontaneous activity was examined with autocorrelation analysis to determine whether neuronal oscillations were essential for coordinating thalamic and cortical activity in the absence of peripheral stimulation. Only 18.5% (23 of 124) of spontaneous interactions between thalamic and cortical neurons were associated with periodic activity, which suggests that thalamocortical synchronization occurs before the constituent neurons begin to oscillate. 6. The influence of sensory stimulation on spontaneous interactions was examined in 31 pairs of thalamic and cortical neurons that exhibited interactions during prestimulus and stimulus in

The initiation site for triggering epileptiform activity was investigated via optical imaging using voltage-sensitive dyes in the neocortical slice perfused with artificial cerebral spinal fluid containing nominally zero magnesium. The neocortical slices (400-μm thick) were harvested from Sprague-Dawley rats (P21–28). Optical imaging was made by using a high speed photodiode array. Spontaneous epileptiform activity emerged 20–40 min after the preparation was perfused with zero-magnesium solution. There was a good correspondence between electrical and optical signals ( n = 46), although the details of the two recordings were somewhat different. The initiation sites were measured optically in 11 preparations. Among them, four were found to be located in superficial layers, two were found in middle layers, and five were found in deep layers. Repeated recordings revealed that these initiation sites were relatively stable; shifting of the initiation site was not observed. Therefore spontaneous epileptiform activity could be initiated in various cortical layers, from layer I to layer VI. The activation started from a small area <0.04 mm3 and spread smoothly from the initiation site to adjacent cortical areas, suggesting that the initiation site is very confined to one of the cortical layers. The initiation sites were distributed randomly in various cortical areas, and no higher probability was found in a special cortical region. Electrical stimulation delivered via a glass microelectrode filled with 2 M NaCl (2–5 MΩ) could reliably trigger epileptiform activity that had the same characteristics as the spontaneous activity. The cortical neurons activated directly by the stimulation were around the electrode’s tip and estimated to be within a 50-μm area, suggesting that only a few neurons were needed to form an initiation site. Because the timing for stimulation was arbitrary and the evoked events were initiated independent of discharges of neurons in any other layers, it is likely that the initiation site for epileptiform activity in various cortical layers is independent of the control of layer V pyramidal neurons. Together these finding suggest that the epileptiform focus is confined and can be formed in several (probably all) neocortical layers and in many cortical areas. The initiating neurons may be of different types because neuronal types in various cortical layers are different.

To clarify mechanisms through which activation of the nucleus basalis of Meynert (NBM) increases cerebral cortical blood flow, we examined whether cortical parenchymal arteries dilate during NBM stimulation in anesthetized mice. We used two-photon microscopy to measure the diameter of single penetrating arteries at different depths (~800 μm, layers I to V) of the frontal cortex, and examined changes in the diameter during focal electrical stimulation of the NBM (0.5 ms at 30 to 50 μA and 50 Hz) and hypercapnia (3% CO2 inhalation). Stimulation of the NBM caused diameter of penetrating arteries to increase by 9% to 13% of the prestimulus diameter throughout the different layers of the cortex, except at the cortical surface and upper part of layer V, where the diameter of penetrating arteries increased only slightly during NBM stimulation. Hypercapnia caused obvious dilation of the penetrating arteries in all cortical layers, including the surface arteries. The diameters began to increase within 1 second after the onset of NBM stimulation in the upper cortical layers, and later in lower layers. Our results indicate that activation of the NBM dilates cortical penetrating arteries in a layer-specific manner in magnitude and latency, presumably related to the density of cholinergic nerve terminals from the NBM.

During general anesthesia, global brain activity and behavioral state are profoundly altered. Yet it remains mostly unknown how anesthetics alter sensory processing across cortical layers and modulate functional cortico-cortical connectivity. To address this gap in knowledge of the micro- and mesoscale effects of anesthetics on sensory processing in the cortical microcircuit, we recorded multiunit activity and local field potential in awake and anesthetized ferrets ( Mustela putoris furo) during sensory stimulation. To understand how anesthetics alter sensory processing in a primary sensory area and the representation of sensory input in higher-order association areas, we studied the local sensory responses and long-range functional connectivity of primary visual cortex (V1) and prefrontal cortex (PFC). Isoflurane combined with xylazine provided general anesthesia for all anesthetized recordings. We found that anesthetics altered the duration of sensory-evoked responses, disrupted the response dynamics across cortical layers, suppressed both multimodal interactions in V1 and sensory responses in PFC, and reduced functional cortico-cortical connectivity between V1 and PFC. Together, the present findings demonstrate altered sensory responses and impaired functional network connectivity during anesthesia at the level of multiunit activity and local field potential across cortical layers.

The neocortex covers 90% of the human cerebral cortex [41] and is responsible for higher cognitive function and socio-cognitive skills in all mammals. It is known to be structured in layers and in some species or cortical areas, in columns. A balanced network model was built, which incorporated these structural organizations and in particular, the layers, minicolumns and hypercolumns. The dynamics of eight different network models were studied, based on combinations of structural organizations that they have. The eigenvalue spectra of their matrices was calculated showing that layered networks have eigenvalues outside their bulk distribution in contrast to networks with columns and no layers. It was demonstrated, through simulations, that networks with layers are unstable and have a lower threshold to synchronization, thus, making them more susceptible to switch to synchronous and regular activity regimes [10]. Moreover, introduction of minicolumns to these networks was observed to partially counterbalance synchrony and regularity, in the network and neuron activity, respectively. Layered networks, principally the ones without minicolumns, also have higher degree correlations and a reduced size of potential pre- and post- connections, which induces correlations in the neuronal activity and oscillations.

Visual attention improves sensory processing, as well as perceptual readout and behavior. Over the last decades, many proposals have been put forth to explain how attention affects visual neural processing. These include the modulation of neural firing rates and synchrony, neural tuning properties, and rhythmic, subthreshold activity. Despite the wealth of knowledge provided by previous studies, the way attention shapes interactions between cortical layers within and between visual sensory areas is only just emerging. To investigate this, we studied neural signals from macaque V1 and V4 visual areas, while monkeys performed a covert, feature-based spatial attention task. The data were simultaneously recorded from laminar electrodes disposed normal to cortical surface in both areas (16 contacts, 150 μm inter-contact spacing). Stimuli presentation was based on the overlap of the receptive fields (RFs) of V1 and V4. Channel depths alignment was referenced to laminar layer IV, based on spatial current source density and temporal latency analyses. Our analyses mainly focused on the study of Local Field Potential (LFP) signals, for which we applied local (bipolar) re-referencing offline. We investigated the effects of attention on LFP spectral power and laminar interactions between LFP signals at different depths, both at the local level within V1 and V4, and at the inter-areal level across V1 and V4. Inspired by current progress from literature, we were interested in the characterization of frequency-specific laminar interactions, which we investigated both in terms of rhythmic synchronization by computing spectral coherence, and in terms of directed causal influence, by computing Granger causalities (GCs). The spectral power of LFPs in different frequency bands showed relatively small differences along cortical depths both in V1 and in V4. However, we found attentional effects on LFP spectral power consistent with previous literature. For V1 LFPs, attention to stimuli in RF location mainly resulted in a shift of the low-gamma (∼30-50 Hz) spectral power peak towards (∼3-4 Hz) higher frequencies and increases in power for frequency bands above low-gamma peak frequencies, as well as decreases in power below these frequencies. For V4 LFPs, attention towards stimuli in RF locations caused a decrease in power for frequencies < 20 Hz and a broad band increase for frequencies > 20 Hz. Attention affected spectral coherence within V1 and within V4 layers in similar way as the spectral power modulation described above. Spectral coherence between V1 and V4 channel pairs was increased by attention mainly in the beta band (∼ 15-30 Hz) and the low-gamma range (∼ 30-50 Hz). Attention affected GC interactions in a layer and frequency dependent manner in complex ways, not always compliant with predictions made by the canonical models of laminar feed-forward and feed-back interactions. Within V1, attention increased feed-forward efficacy across almost all low-frequency bands (∼ 2-50 Hz). Within V4, attention mostly increased GCs in the low and high gamma frequency in a 'downwards' direction within the column, i.e. from supragranular to granular and to infragranular layers. Increases were also evident in an ‘upwards’ direction from granular to supragranular layers. For inter-areal GCs, the dominant changes were an increase in the gamma frequency range from V1 granular and infragranular layers to V4 supragranular and granular layers, as well as an increase from V4 supragranular layers to all V1 layers.

The subplate layer of the cerebral cortex is comprised of a heterogeneous population of cells and contains some of the earliest-generated neurons. Subplate plays a fundamental role in cortical development. In the embryonic brain, subplate cells contribute to the guidance and areal targeting of corticofugal and thalamic axons. At later stages, these cells are involved in the maturation and plasticity of the cortical circuitry and the establishment of functional modules. In my thesis, I aimed to further characterize the embryonic murine subplate by establishing a gene expression profile of this population at embryonic day 15.5 (E15.5) using laser capture microdissection combined with microarrays. I found over 250 transcripts with presumed higher expression in the subplate at E15.5. Using quantitative RT-PCR, in situ hybridization and immunohistochemistry, I have confirmed specific expression in the E15.5 subplate for 13 selected genes which have not been previously associated with this compartment. In the reeler mutant, the expression pattern of a majority of these genes was shifted in accordance with the altered position of subplate cells. These genes belong to several functional groups and likely contribute to the maturation and electrophysiological properties of subplate cells and to axonal growth and guidance. The roles of two selected genes - cadherin 10 (Cdh10) and Unc5 homologue c (Unc5c) - were explored in more detail. Preliminary results suggest an involvement of Cdh10 in subplate layer organization while Unc5c could mediate the waiting period of subplate corticothalamic axons in the internal capsule. Finally, I compared the expression of a selection of subplate-specific genes (subplate markers) between mouse and rat and found some surprising species differences. Confirmed subplate markers were used to monitor subplate injury in a rat model of preterm hypoxiaischemia and it appeared that deep cortical layers including subplate showed an increased vulnerability over upper layers. Further characterization of subplate-specific genes will allow us to broaden our understanding of molecular mechanisms underlying subplate properties and functions in normal and pathological development.

Le principe de codage efficace suggère que le traitement des informations dans le système visuel primaire est optimisé et adapté aux statistiques de l’environnement. Une étude intracellulaire menée dans le cortex visuel primaire (V1) du chat anesthésié et paralysé a démontré que la reproductibilité des réponses neuronales est optimisée lorsque des statistiques naturelles sont présentées. En utilisant les mêmes stimuli artificiels et naturels, nous avons enregistré, à l’aide d’électrodes laminaires denses, l’activité neuronale (activité unitaire, multi-unitaire et potentiel de champ local) dans le cortex visuel primaire du chat. Dans un 1er temps, nous avons étudié la reproductibilité de l’activité neuronale et sa dépendance laminaire. Nos résultats démontrent que les images naturelles induisent toujours la réponse la plus reproductible, suggérant une optimisation de V1 dans le traitement des statistiques naturelles. De plus, nous avons montré que les couches 4 et 5/6 présentent des réponses plus reproductibles que la couche 2/3. Cela suggère qu’un « filtrage fonctionnel » des informations pertinentes se produit entre ces différents compartiments laminaires. Dans un 2nd temps nous avons étudié la corrélation de la réponse ou de la variabilité de la réponse de neurones situés dans une même couche ou dans des couches différentes. Les niveaux de corrélation sont les plus élevées lorsque les images naturelles sont présentées. De plus, les corrélations sont plus fortes au sein d’une même couche qu’entre deux couches. Cela suggère qu’un regroupement fonctionnel des neurones se produit afin d’optimiser l’encodage de l’information visuelle
The principle of efficient coding suggests that processing in the early visual system should be optimized and adapted to the environmental statistics. An intracellular study of the primary visual cortex (V1) in the anesthetized and paralyzed cat showed that the reliability of the neural response is optimized for natural statistics. Using the same natural and artificial stimuli, we recorded the neuronal population activity (single unit, multi-unit and local field potentials) in cat’s V1 with high-density linear silicon probes. We first investigated the reliability and of the mesoscopic signal with the intracellular signal and explored its laminar dependency. Our results showed that natural images evoke, at all scales, the most reliable response, suggesting that V1 is better suited to efficiently encode natural statistics. In addition, granular and infragranular layers displayed higher reliability levels than the supragranular one. This argues for a functional filtering of the pertinent information between these layers. We also explored which statistics of the natural images produce this reliable response. Finally, we specifically addressed the role of the correlations between neurons (within and between layers) by measuring the amount of shared variability and signal of the neuronal population in response to our stimulus set. We observed that natural images always evoked higher correlations. We did not observe a strong decorrelation at the single cell level but instead at the scale of groups of neurons, with those that are close together being more correlated and farther apart less correlated, arguing for a functional clustering of the neurons into coherent “neural mass”

Mitochondrial metabolism of reactive oxygen species (ROS) is tightly regulated during brain development. Imbalance has been correlated to neuropsychiatric disorders. Nevertheless, the contribution of ROS accumulation to aberrant cortical circuit organization and function remains unknown. Individuals with 22q11 deletion syndrome (22q11DS) are highly susceptible to psychiatric disorders; therefore, 22q11DS has been suggested as a model for studying the neurodevelopmental origins of these disorders. Six genes –Mrpl40, Tango2, Prodh, Zdhhc8, Txnrd2 and Scl25a1– located in the 22q11DS commonly deleted region encode proteins that localize to mitochondria. This project aimed to characterize the effects of altered mitochondrial function, due to diminished dosage of these genes, on cortical projection neuron development, using the LgDel mouse model of 22q11DS. I found growth deficits in LgDel neurons that are due to increased mitochondrial ROS and are Txnrd2-dependent. Antioxidant treatment, by n-acetyl cysteine (NAC), rescues neuronal morphogenesis in LgDel and Txnrd2-depleted neurons in vitro and in vivo. Electroporation of Txnrd2 restores ROS levels and normal dendritic and axonal growth. Txnrd2-dependent redox regulation underlies a key aspect of cortical circuit differentiation in a mouse model of 22q11DS. These studies define the effects of mitochondrial accumulation of ROS on neuronal integrity, and establish the role of altered pyramidal neuron differentiation in the formation of circuits in 22q11DS. These data provide novel insight into the role of redox imbalance in aberrant development of cortical circuits.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, February 2017.
Cataloged from PDF version of thesis. "September 2016."
Includes bibliographical references.
Neocortex learns predictive models of sensory input, allowing mammals to anticipate future events. A fundamental component of this process is the comparison between expected and actual sensory input, and the layered architecture of neocortex is presumably central to this computation. In this thesis, I examine the role of laminar differences, and specifically the role of layer 6 (L6) in the encoding and perception of stimuli that deviate from previous patterns. In awake mice, layer 4 neurons encode current stimulus deviations with a predominantly monotonic, faithful encoding, while neurons in layer 2/3 encode history dependent change signals with heterogeneous receptive fields. Corticothalamic (CT) cells in Layer 6 respond sparsely, but faithfully encode stimulus identity. Weak optogenetic drive of L6 CT cells disrupted this encoding in layer 6 without affecting overall firing rates. This manipulation also caused layer 2/3 to represent only current stimuli. In a head-fixed stimulus detection task, small stimulus deviations typically make stimuli more detectable, and the L6 manipulation removed this effect, without affecting detection of non-changing stimuli. Analogously, in free sensory decision making behavior, the manipulation selectively impaired perception of deviant stimuli, without affecting basic performance. In contrast, stronger L6 drive reduced sensory gain and impaired tactile sensitivity. These results show an explicit laminar encoding of stimulus changes, and that L6 can play a role in the perception of sensory changes by modulating responses depending on previous, or expected input. This finding provides a new perspective on how the layered cortical architecture can implement computations on hierarchical models of the world.
by Jakob Voigts.
Ph. D.

This chapter describes how the activity of neurons produces electrical potentials that can be recorded at the levels of single cells, small groups of neurons, and larger neuronal networks. It outlines how the movement of ions across neuronal membranes produces action potentials and synaptic potentials. It considers how the spatial arrangement of specific ion channels on the neuronal surface can produce potentials that can be recorded from the extracellular space. Finally, it outlines how the layered cellular structure of the neocortex can result in summation of signals from many neurons to be large enough to record through the scalp as evoked potentials or the electroencephalogram.

Higher cognitive disorders involve insults to the neural circuits of the newly evolved association cortices. Although these cortices comprise the majority of the human cortex, little is understood about their molecular modulation. Research on the primate dorsolateral prefrontal cortex (dlPFC) indicates that the newly evolved layer III circuits underlying mental representation are regulated at the molecular level in a manner that is fundamentally different from classic synapses. These mechanisms must be respected to create effective treatments for human disorders, where a major goal is to optimize the network connectivity needed for persistent and precise neural representations. Understanding the needs of dlPFC circuits has led to the successful translation of guanfacine (Intuniv) for treating cognitive disorders, supporting this research strategy.

This chapter provides a crude overview of current knowledge in neuroscience about the human nervous system and its functionality. The distinction between the peripheral and central nervous systems is introduced. Next, brain anatomy is introduced, as well as nerve cells and the information processing principles that unfold in biological neural networks. Moreover, brain modules are covered, including their interconnected communication. With modularizations and wiring systematicities in mind, functional and structural systematicities are surveyed, including neural homunculi, cortical columnar structures, and the six-layered structure of the cerebral cortex. Finally, different available brain imaging techniques are contrasted. In conclusion, evidence is surveyed that suggests that the brain can be viewed as a highly modularized predictive processing system, which maintains internal activity and produces internal structures for the purpose of maintaining bodily needs in approximate homeostasis.

Bones are multifunctional passive organs of movement that supports soft tissue and directly attached muscles. They also protect internal organs and are a reserve of calcium, phosphorus and magnesium. Each bone is covered with periosteum, and the adjacent bone surfaces are covered by articular cartilage. Histologically, the bone is an organ composed of many different tissues. The main component is bone tissue (cortical and spongy) composed of a set of bone cells and intercellular substance (mineral and organic), it also contains fat, hematopoietic (bone marrow) and cartilaginous tissue. Bones are a tissue that even in adult life retains the ability to change shape and structure depending on changes in their mechanical and hormonal environment, as well as self-renewal and repair capabilities. This process is called bone turnover. The basic processes of bone turnover are: • bone modeling (incessantly changes in bone shape during individual growth) following resorption and tissue formation at various locations (e.g. bone marrow formation) to increase mass and skeletal morphology. This process occurs in the bones of growing individuals and stops after reaching puberty • bone remodeling (processes involve in maintaining bone tissue by resorbing and replacing old bone tissue with new tissue in the same place, e.g. repairing micro fractures). It is a process involving the removal and internal remodeling of existing bone and is responsible for maintaining tissue mass and architecture of mature bones. Bone turnover is regulated by two types of transformation: • osteoclastogenesis, i.e. formation of cells responsible for bone resorption • osteoblastogenesis, i.e. formation of cells responsible for bone formation (bone matrix synthesis and mineralization) Bone maturity can be defined as the completion of basic structural development and mineralization leading to maximum mass and optimal mechanical strength. The highest rate of increase in pig bone mass is observed in the first twelve weeks after birth. This period of growth is considered crucial for optimizing the growth of the skeleton of pigs, because the degree of bone mineralization in later life stages (adulthood) depends largely on the amount of bone minerals accumulated in the early stages of their growth. The development of the technique allows to determine the condition of the skeletal system (or individual bones) in living animals by methods used in human medicine, or after their slaughter. For in vivo determination of bone properties, Abstract 10 double energy X-ray absorptiometry or computed tomography scanning techniques are used. Both methods allow the quantification of mineral content and bone mineral density. The most important property from a practical point of view is the bone’s bending strength, which is directly determined by the maximum bending force. The most important factors affecting bone strength are: • age (growth period), • gender and the associated hormonal balance, • genotype and modification of genes responsible for bone growth • chemical composition of the body (protein and fat content, and the proportion between these components), • physical activity and related bone load, • nutritional factors: – protein intake influencing synthesis of organic matrix of bone, – content of minerals in the feed (CA, P, Zn, Ca/P, Mg, Mn, Na, Cl, K, Cu ratio) influencing synthesis of the inorganic matrix of bone, – mineral/protein ratio in the diet (Ca/protein, P/protein, Zn/protein) – feed energy concentration, – energy source (content of saturated fatty acids - SFA, content of polyun saturated fatty acids - PUFA, in particular ALA, EPA, DPA, DHA), – feed additives, in particular: enzymes (e.g. phytase releasing of minerals bounded in phytin complexes), probiotics and prebiotics (e.g. inulin improving the function of the digestive tract by increasing absorption of nutrients), – vitamin content that regulate metabolism and biochemical changes occurring in bone tissue (e.g. vitamin D3, B6, C and K). This study was based on the results of research experiments from available literature, and studies on growing pigs carried out at the Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences. The tests were performed in total on 300 pigs of Duroc, Pietrain, Puławska breeds, line 990 and hybrids (Great White × Duroc, Great White × Landrace), PIC pigs, slaughtered at different body weight during the growth period from 15 to 130 kg. Bones for biomechanical tests were collected after slaughter from each pig. Their length, mass and volume were determined. Based on these measurements, the specific weight (density, g/cm3) was calculated. Then each bone was cut in the middle of the shaft and the outer and inner diameters were measured both horizontally and vertically. Based on these measurements, the following indicators were calculated: • cortical thickness, • cortical surface, • cortical index. Abstract 11 Bone strength was tested by a three-point bending test. The obtained data enabled the determination of: • bending force (the magnitude of the maximum force at which disintegration and disruption of bone structure occurs), • strength (the amount of maximum force needed to break/crack of bone), • stiffness (quotient of the force acting on the bone and the amount of displacement occurring under the influence of this force). Investigation of changes in physical and biomechanical features of bones during growth was performed on pigs of the synthetic 990 line growing from 15 to 130 kg body weight. The animals were slaughtered successively at a body weight of 15, 30, 40, 50, 70, 90, 110 and 130 kg. After slaughter, the following bones were separated from the right half-carcass: humerus, 3rd and 4th metatarsal bone, femur, tibia and fibula as well as 3rd and 4th metatarsal bone. The features of bones were determined using methods described in the methodology. Describing bone growth with the Gompertz equation, it was found that the earliest slowdown of bone growth curve was observed for metacarpal and metatarsal bones. This means that these bones matured the most quickly. The established data also indicate that the rib is the slowest maturing bone. The femur, humerus, tibia and fibula were between the values of these features for the metatarsal, metacarpal and rib bones. The rate of increase in bone mass and length differed significantly between the examined bones, but in all cases it was lower (coefficient b <1) than the growth rate of the whole body of the animal. The fastest growth rate was estimated for the rib mass (coefficient b = 0.93). Among the long bones, the humerus (coefficient b = 0.81) was characterized by the fastest rate of weight gain, however femur the smallest (coefficient b = 0.71). The lowest rate of bone mass increase was observed in the foot bones, with the metacarpal bones having a slightly higher value of coefficient b than the metatarsal bones (0.67 vs 0.62). The third bone had a lower growth rate than the fourth bone, regardless of whether they were metatarsal or metacarpal. The value of the bending force increased as the animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. The rate of change in the value of this indicator increased at a similar rate as the body weight changes of the animals in the case of the fibula and the fourth metacarpal bone (b value = 0.98), and more slowly in the case of the metatarsal bone, the third metacarpal bone, and the tibia bone (values of the b ratio 0.81–0.85), and the slowest femur, humerus and rib (value of b = 0.60–0.66). Bone stiffness increased as animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. Abstract 12 The rate of change in the value of this indicator changed at a faster rate than the increase in weight of pigs in the case of metacarpal and metatarsal bones (coefficient b = 1.01–1.22), slightly slower in the case of fibula (coefficient b = 0.92), definitely slower in the case of the tibia (b = 0.73), ribs (b = 0.66), femur (b = 0.59) and humerus (b = 0.50). Bone strength increased as animals grew. Regardless of the growth point tested, bone strength was as follows femur > tibia > humerus > 4 metacarpal> 3 metacarpal> 3 metatarsal > 4 metatarsal > rib> fibula. The rate of increase in strength of all examined bones was greater than the rate of weight gain of pigs (value of the coefficient b = 2.04–3.26). As the animals grew, the bone density increased. However, the growth rate of this indicator for the majority of bones was slower than the rate of weight gain (the value of the coefficient b ranged from 0.37 – humerus to 0.84 – fibula). The exception was the rib, whose density increased at a similar pace increasing the body weight of animals (value of the coefficient b = 0.97). The study on the influence of the breed and the feeding intensity on bone characteristics (physical and biomechanical) was performed on pigs of the breeds Duroc, Pietrain, and synthetic 990 during a growth period of 15 to 70 kg body weight. Animals were fed ad libitum or dosed system. After slaughter at a body weight of 70 kg, three bones were taken from the right half-carcass: femur, three metatarsal, and three metacarpal and subjected to the determinations described in the methodology. The weight of bones of animals fed aa libitum was significantly lower than in pigs fed restrictively All bones of Duroc breed were significantly heavier and longer than Pietrain and 990 pig bones. The average values of bending force for the examined bones took the following order: III metatarsal bone (63.5 kg) <III metacarpal bone (77.9 kg) <femur (271.5 kg). The feeding system and breed of pigs had no significant effect on the value of this indicator. The average values of the bones strength took the following order: III metatarsal bone (92.6 kg) <III metacarpal (107.2 kg) <femur (353.1 kg). Feeding intensity and breed of animals had no significant effect on the value of this feature of the bones tested. The average bone density took the following order: femur (1.23 g/cm3) <III metatarsal bone (1.26 g/cm3) <III metacarpal bone (1.34 g / cm3). The density of bones of animals fed aa libitum was higher (P<0.01) than in animals fed with a dosing system. The density of examined bones within the breeds took the following order: Pietrain race> line 990> Duroc race. The differences between the “extreme” breeds were: 7.2% (III metatarsal bone), 8.3% (III metacarpal bone), 8.4% (femur). Abstract 13 The average bone stiffness took the following order: III metatarsal bone (35.1 kg/mm) <III metacarpus (41.5 kg/mm) <femur (60.5 kg/mm). This indicator did not differ between the groups of pigs fed at different intensity, except for the metacarpal bone, which was more stiffer in pigs fed aa libitum (P<0.05). The femur of animals fed ad libitum showed a tendency (P<0.09) to be more stiffer and a force of 4.5 kg required for its displacement by 1 mm. Breed differences in stiffness were found for the femur (P <0.05) and III metacarpal bone (P <0.05). For femur, the highest value of this indicator was found in Pietrain pigs (64.5 kg/mm), lower in pigs of 990 line (61.6 kg/mm) and the lowest in Duroc pigs (55.3 kg/mm). In turn, the 3rd metacarpal bone of Duroc and Pietrain pigs had similar stiffness (39.0 and 40.0 kg/mm respectively) and was smaller than that of line 990 pigs (45.4 kg/mm). The thickness of the cortical bone layer took the following order: III metatarsal bone (2.25 mm) <III metacarpal bone (2.41 mm) <femur (5.12 mm). The feeding system did not affect this indicator. Breed differences (P <0.05) for this trait were found only for the femur bone: Duroc (5.42 mm)> line 990 (5.13 mm)> Pietrain (4.81 mm). The cross sectional area of the examined bones was arranged in the following order: III metatarsal bone (84 mm2) <III metacarpal bone (90 mm2) <femur (286 mm2). The feeding system had no effect on the value of this bone trait, with the exception of the femur, which in animals fed the dosing system was 4.7% higher (P<0.05) than in pigs fed ad libitum. Breed differences (P<0.01) in the coross sectional area were found only in femur and III metatarsal bone. The value of this indicator was the highest in Duroc pigs, lower in 990 animals and the lowest in Pietrain pigs. The cortical index of individual bones was in the following order: III metatarsal bone (31.86) <III metacarpal bone (33.86) <femur (44.75). However, its value did not significantly depend on the intensity of feeding or the breed of pigs.

Over the past two decades, the barrel cortex has emerged as a major model system for the analysis of the structure, function, and experience-dependent plasticity of neocortical circuits. Driven by the availability of transgenic animals expressing fluorescent proteins and protein effectors in specific cell types, circuit studies of the barrel cortex are now mostly performed in mice. The cortical layers, cell types, and the intralaminar connectivity are similar in mice and rats. This chapter combines information gained from experiments in both species, but all quantitative data pertain to the mouse barrel cortex. We summarize current knowledge about the inputs, outputs and local circuits of the barrel cortex. Special emphasis is placed on the structure and function of layer 4, which may currently be the best understood cortical circuit. Circuit principles derived from layer 4 likely apply to cortical circuits in general.

The cerebral cortex computes the highest forms of biological intelligence in all sensory and cognitive modalities. Neocortical cells are organized into circuits that form six cortical layers in all cortical areas that carry out perception and cognition. Variations in cell properties within these layers and their connections have been used to classify the cerebral cortex into more than fifty divisions, or areas, to which distinct functions have been attributed. Why the cortex has a laminar organization for the control of behavior has, however, remained a mystery until recently. Also mysterious has been how variations on this ubiquitous laminar cortical design can give rise to so many different types of intelligent behavior. This chapter explains how Laminar Computing contributes to biological intelligence, and how layered circuits of neocortical cells support all the various kinds of higher-order biological intelligence, including vision, language, and cognition, using variations of the same canonical laminar circuit. This canonical circuit can be used in general-purpose VLSI chips that can be specialized to carry out different kinds of biological intelligence, and seamlessly joined together to control autonomous adaptive algorithms and mobile robots. These circuits show how preattentive automatic bottom-up processing and attentive task-selective top-down processing are joined together in the deeper cortical layers to form a decision interface. Here, bottom-up and top-down constraints cooperate and compete to generate the best decisions, by combining properties of fast feedforward and feedback processing, analog and digital computing, and preattentive and attentive learning, including laminar ART properties such as analog coherence.

Fractures of the mandible are a common form of traumatic injury. These fractures may be repaired using miniplates secured to cortical bone with screws. In the present research, the authors measure the pull-out strengths of cortical screws using a standard test paradigm and develop a finite element model to analyze forces acting on these screws. Pull-out strengths are measured in a tri-laminate synthetic material that mimics the cortical layers and cancellous bone of the mandible. A finite-element (FE) model is developed to analyze the mechanics of deformation of the model bone during the pullout process. Issues that are important for the proper modeling of both normal and fractured mandibles are also considered.