Laminar analysis of excitatory local circuits in vibrissal motor and sensory cortical areas

Rodents move their whiskers to locate and identify objects. Cortical areas involved in vibrissal somatosensation and sensorimotor integration include the vibrissal area of the primary motor cortex (vM1), primary somatosensory cortex (vS1; barrel cortex), and secondary somatosensory cortex (S2). We mapped local excitatory pathways in each area across all cortical layers using glutamate uncaging and laser scanning photostimulation. We analyzed these maps to derive laminar connectivity matrices describing the average strengths of pathways between individual neurons in different layers and between entire cortical layers. In vM1, the strongest projection was L2/3→L5. In vS1, strong projections were L2/3→L5 and L4→L3. L6 input and output were weak in both areas. In S2, L2/3→L5 exceeded the strength of the ascending L4→L3 projection, and local input to L6 was prominent. The most conserved pathways were L2/3→L5, and the most variable were L4→L2/3 and pathways involving L6. Local excitatory circuits in different cortical areas are organized around a prominent descending pathway from L2/3→L5, suggesting that sensory cortices are elaborations on a basic motor cortex-like plan.     

Distribution of neuropeptide Y immunoreactivity in human visual cortex and underlying white matter

Immunocytochemical techniques have been used to study neuropeptide Y (NPY) distribution in the human visual cortex (Brodman's areas 17, 18 and 19) NYP cell bodies belong mostly to inhibitory (multipolar and bitufted) but also to excitatory (bipolar and some pyramidal) neuronal types. Their distribution is similar in the three cortical areas studied: 20 to 40% of the NPY perikarya are located in the cortical gray matter, mostly in the deep layers, while the remaining 60 to 80% are located in the underlying white matter. Immunoreactive NPY processes form a rich network of intersecting fibers throughout the entire visual cortex. A superficial plexus (layers I and II) and a deep plexus (deep layer V and layer VI) of NPY fibers are present in areas 17, 18 and 19. In area 17, an additional well developed plexus is present in layers IVb and IVc. These plexuses receive branches from long parallel fibers arising from deep cortical layers or underlying white matter and terminating in superficial layers. Local or extrinsic NPY terminals wind around vessels in the cortex as well as in the white matter, and either penetrate them or form clusters of club endings on their walls. Our results suggest a role for NPY in human visual circuitry and in cortical blood flow regulation.     

Rhythm generation through period concatenation in rat somatosensory cortex

Rhythmic voltage oscillations resulting from the summed activity of neuronal populations occur in many nervous systems. Contemporary observations suggest that coexistent oscillations interact and, in time, may switch in dominance. We recently reported an example of these interactions recorded from in vitro preparations of rat somatosensory cortex. We found that following an initial interval of coexistent gamma ( approximately 25 ms period) and beta2 ( approximately 40 ms period) rhythms in the superficial and deep cortical layers, respectively, a transition to a synchronous beta1 ( approximately 65 ms period) rhythm in all cortical layers occurred. We proposed that the switch to beta1 activity resulted from the novel mechanism of period concatenation of the faster rhythms: gamma period (25 ms)+beta2 period (40 ms) = beta1 period (65 ms). In this article, we investigate in greater detail the fundamental mechanisms of the beta1 rhythm. To do so we describe additional in vitro experiments that constrain a biologically realistic, yet simplified, computational model of the activity. We use the model to suggest that the dynamic building blocks (or motifs) of the gamma and beta2 rhythms combine to produce a beta1 oscillation that exhibits cross-frequency interactions. Through the combined approach of in vitro experiments and mathematical modeling we isolate the specific components that promote or destroy each rhythm. We propose that mechanisms vital to establishing the beta1 oscillation include strengthened connections between a population of deep layer intrinsically bursting cells and a transition from antidromic to orthodromic spike generation in these cells. We conclude that neural activity in the superficial and deep cortical layers may temporally combine to generate a slower oscillation.     

Dopamine and norepinephrine innervated cells in the rat prefrontal cortex: Pharmacological differentiation using microiontophoretic techniques

Biochemical and fluorescence histochemical evidence suggest dopaminergic and noradrenergic projections to the prefrontal cortex which primarily innervate the deep layers (V & VI) and superficial layers respectively. Using microiontophoretic techniques, we determined the sensitivity of cells in the rat prefrontal cortex to the inhibitory effects of dopamine (DA) and norepinephrine (NE). A clear correspondence was found between the response of a cell to DA and NE and the layer in which that cell resided. Thus cells in layers II and III were more sensitive to NE than DA, whereas the opposite was true for layers V and VI. Applied microiontophoretically, desmethylimipramine, a selective NE uptake blocker, potentiated the inhibitory effects of NE in layers II and III but not in layers V and VI. Benztropine, a DA uptake blocker, potentiated the inhibitory effects of DA only on DA sensitive cells in layers V and VI. Trifluoperazine, a DA receptor blocker, selectively blocked DA inhibition of cell activity in the deep layers. Similar experiments performed in the hippocampus and accumbens nucleus yielded results identical to those obtained for cortical layers II and III (primary NE innervation) and V and VI (primary DA innervation, respectively).These findings suggest that using microiontophoretic techniques one can pharmacologically differentiate between DA and NE innervated cells in the rat prefrontal cortex.     

Effects of the thalamus on the development of cerebral cortical efferents in vitro

The cerebral cortex is a multilayered tissue, with each layer differing in its cellular composition and connections. Axons from deep layer neurons project subcortically, many to the thalamus, whereas superficial layer neurons target other cortical areas. The mechanisms that regulate the development of this pattern of connections are not fully understood. Our experiments examined the potential of the thalamus to attract and/or select neurites from appropriate cortical layers. First, we cocultured murine cortical slices in close proximity to thalamic explants in collagen gels. The amount of neurite outgrowth from deep layer cells was enhanced by, but not attracted to, the thalamic explants. Second, we cocultured cortical slices in contact with thalamic or cortical explants to test for laminar specificity of connections. Specificity was apparent after culture for about a week, in that deep cortical layers contained the highest proportions of corticothalamic cells and superficial cortical layers contained the highest proportions of corticocortical cells. After shorter culture of only a few days, however, specificity was not apparent and there were larger numbers of corticothalamic projections from the superficial layers than after a week. To study how the early nonspecific pattern of corticothalamic connections was transformed into the more specific pattern, we labeled corticothalamic cells early, after 2 days, but let the cultures survive for 8 days. On day 8, the nonspecific pattern of early-labeled cells was still seen. We conclude that although the thalamus does not block the initial entry of inappropriate axons from the superficial layers, many of these axons are subsequently lost. This suggests that contact-mediated interactions between cortical axons and the thalamus allow cortical efferents from appropriate layers to be distinguished from those arising in inappropriate layers. This may contribute to the development of layer-specific cortical connections in vivo.     

Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring

Understanding the structure and dynamics of cortical connectivity is vital to understanding cortical function. Experimental data strongly suggest that local recurrent connectivity in the cortex is significantly non-random, exhibiting, for example, above-chance bidirectionality and an overrepresentation of certain triangular motifs. Additional evidence suggests a significant distance dependency to connectivity over a local scale of a few hundred microns, and particular patterns of synaptic turnover dynamics, including a heavy-tailed distribution of synaptic efficacies, a power law distribution of synaptic lifetimes, and a tendency for stronger synapses to be more stable over time. Understanding how many of these non-random features simultaneously arise would provide valuable insights into the development and function of the cortex. While previous work has modeled some of the individual features of local cortical wiring, there is no model that begins to comprehensively account for all of them. We present a spiking network model of a rodent Layer 5 cortical slice which, via the interactions of a few simple biologically motivated intrinsic, synaptic, and structural plasticity mechanisms, qualitatively reproduces these non-random effects when combined with simple topological constraints. Our model suggests that mechanisms of self-organization arising from a small number of plasticity rules provide a parsimonious explanation for numerous experimentally observed non-random features of recurrent cortical wiring. Interestingly, similar mechanisms have been shown to endow recurrent networks with powerful learning abilities, suggesting that these mechanism are central to understanding both structure and function of cortical synaptic wiring.     

Spatiotemporal receptive fields: a dynamical model derived from cortical architectonics

We assume that the mammalian neocortex is built up out of some six layers which differ in their morphology and their external connections. Intrinsic connectivity is largely excitatory, leading to a considerable amount of positive feedback. The majority of cortical neurons can be divided into two main classes: the pyramidal cells, which are said to be excitatory, and local cells (most notably the non-spiny stellate cells), which are said to be inhibitory. The form of the dendritic and axonal arborizations of both groups is discussed in detail. This results in a simplified model of the cortex as a stack of six layers with mutual connections determined by the principles of fibre anatomy. This stack can be treated as a multi-input-multi-output system by means of the linear systems theory of homogeneous layers. The detailed equations for the simulation are derived in the Appendix. The results of the simulations show that the temporal and spatial behaviour of an excitation distribution cannot be treated separately. Further, they indicate specific processing in the different layers and some independence from details of wiring. Finally, the simulation results are applied to the theory of visual receptive fields. This yields some insight into the mechanisms possibly underlying hypercomplexity, putative nonlinearities, lateral inhibition, oscillating cell responses, and velocity-dependent tuning curves.     

Interdigitated paralemniscal and lemniscal pathways in the mouse barrel cortex

Primary sensory cortical areas receive information through multiple thalamic channels. In the rodent whisker system, lemniscal and paralemniscal thalamocortical projections, from the ventral posteromedial nucleus (VPM) and posterior medial nucleus (POm) respectively, carry distinct types of sensory information to cortex. Little is known about how these separate streams of activity are parsed and integrated within the neocortical microcircuit. We used quantitative laser scanning photostimulation to probe the organization of functional thalamocortical and ascending intracortical projections in the mouse barrel cortex. To map the thalamocortical projections, we recorded from neocortical excitatory neurons while stimulating VPM or POm. Neurons in layers (L)4, L5, and L6A received dense input from thalamus (L4, L5B, and L6A from VPM; and L5A from POm), whereas L2/3 neurons rarely received thalamic input. We further mapped the lemniscal and paralemniscal circuits from L4 and L5A to L2/3. Lemniscal L4 neurons targeted L3 within a column. Paralemniscal L5A neurons targeted a superficial band (thickness, 60 μm) of neurons immediately below L1, defining a functionally distinct L2 in the mouse barrel cortex. L2 neurons received input from lemniscal L3 cells and paralemniscal L5A cells spread over multiple columns. Our data indicate that lemniscal and paralemniscal information is segregated into interdigitated cortical layers.     

Columnar Connectivity and Laminar Processing in Cat Primary Auditory Cortex

Background

Radial intra- and interlaminar connections form a basic microcircuit in primary auditory cortex (AI) that extracts acoustic information and distributes it to cortical and subcortical networks. Though the structure of this microcircuit is known, we do not know how the functional connectivity between layers relates to laminar processing.

Methodology/Principal Findings

We studied the relationships between functional connectivity and receptive field properties in this columnar microcircuit by simultaneously recording from single neurons in cat AI in response to broadband dynamic moving ripple stimuli. We used spectrotemporal receptive fields (STRFs) to estimate the relationship between receptive field parameters and the functional connectivity between pairs of neurons. Interlaminar connectivity obtained through cross-covariance analysis reflected a consistent pattern of information flow from thalamic input layers to cortical output layers. Connection strength and STRF similarity were greatest for intralaminar neuron pairs and in supragranular layers and weaker for interlaminar projections. Interlaminar connection strength co-varied with several STRF parameters: feature selectivity, phase locking to the stimulus envelope, best temporal modulation frequency, and best spectral modulation frequency. Connectivity properties and receptive field relationships differed for vertical and horizontal connections.

Conclusions/Significance

Thus, the mode of local processing in supragranular layers differs from that in infragranular layers. Therefore, specific connectivity patterns in the auditory cortex shape the flow of information and constrain how spectrotemporal processing transformations progress in the canonical columnar auditory microcircuit.     

Multiple roles of ephrins during the formation of thalamocortical projections: maps and more

The functional architecture of the cerebral cortex is based on intrinsic connections that precisely link neurons from distinct cortical laminae as well as layer-specific afferent and efferent projections. Experimental strategies using in vitro assays originally developed by Friedrich Bonhoeffer have suggested that positional cues confined to individual layers regulate the assembly of local cortical circuits and the formation of thalamocortical projections. One of these wiring molecules is ephrinA5, a ligand for Eph receptor tyrosine kinases. EphrinA5 and Eph receptors exhibit highly dynamic expression patterns in distinct regions of the cortex and thalamus during early and late stages of thalamocortical and cortical circuit formation. In vitro assays suggest that ephrinA5 is a multifunctional wiring molecule for different populations of cortical and thalamic axons. Additionally, the expression patterns of ephrinA5 during cortical development are consistent with this molecule regulating, in alternative ways, specific components of thalamic and cortical connectivity. To test this directly, the organization of thalamocortical projections was examined in mice lacking ephrinA5 gene expression. The anatomical studies in ephrinA5 knockout animals revealed a miswiring of limbic thalamic projections and changes in neocortical circuits that were predicted from the expression pattern and the in vitro analysis of ephrinA5 function.     

APOE polymorphism and clinical duration determine regional neuropathology in Swedish APP(670, 671) mutation carriers: implications for late-onset Alzheimer's disease

Neurofibrillary changes throughout the brain were investigated for three relatives who carried the Swedish APP_670,671 mutation which causes overproduction of Aβ40 and Aβ42. They differed in terms of APOE genotype, age at the onset of dementia, and disease duration (P1: ɛ2/3, age 57, 11 years; P2: ɛ2/3, age 61, 5 years; P3: ɛ4/4, age 44, 12 years). For each subject, paraffin-embedded sections from diverse anatomically and cytoarchitectonically well-preserved regions were stained using the modified Bielschowsky method. Neurofibrillary tangles (NFT) and neuritic plaques (NP) were counted, and the area occupied by plaque estimated (%NP). In addition, sections from the medial frontal gyrus were stained with monoclonal antibodies to APOE. The regional patterns of neurofibrillary changes were consistent with those for late-onset AD. Longer disease duration was associated with further accumulations in earlier-affected areas, with superficial cortical layers consistently containing higher %NP than deep layers. APOE ɛ4/4 was associated with deeper limbic and frontal NFT, with an excess of NP (especially in the outer parietal cortex) which stained heavily for APOE - as well as with very early onset. APP_670,671 mutation carriers demonstrate regional brain neurofibrillary changes characteristic of late-onset Alzheimer's disease with evidence for more Aβ deposition for ɛ4/4 than ɛ2/3. This raises the possibility that early Braak Stage I-II lesions might also follow this pattern of promotion.     

Prior expectations evoke stimulus-specific activity in the deep layers of the primary visual cortex

The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.

The way we perceive the world is strongly influenced by our expectations, but the neural circuitry through which the brain achieves this remains unknown. A study using ultra-high field fMRI reveals that prior expectations evoke stimulus-specific signals in the deep layers of the primary visual cortex.     

Learning-induced plasticity in the barrel cortex is disrupted by inhibition of layer 4 somatostatin-containing interneurons

Gaba-ergic neurons are a diverse cell class with extensive influence over cortical processing, but their role in experience-dependent plasticity is not completely understood. Here we addressed the role of cortical somatostatin- (SOM-INs) and vasoactive intestinal polypeptide- (VIP-INs) containing interneurons in a Pavlovian conditioning where stimulation of the vibrissae is used as a conditioned stimulus and tail shock as unconditioned one. This procedure induces a plastic change observed as an enlargement of the cortical functional representation of vibrissae activated during conditioning. Using layer-targeted, cell-selective DREADD transductions, we examined the involvement of SOM-INs and VIP-INs activity in learning-related plastic changes. Under optical recordings, we injected DREADD-expressing vectors into layer IV (L4) barrels or layer II/III (L2/3) areas corresponding to the activated vibrissae. The activity of the interneurons was modulated during all conditioning sessions, and functional 2-deoxyglucose (2DG) maps were obtained 24 h after the last session.In mice with L4 but not L2/3 SOM-INs suppressed during conditioning, the plastic change of whisker representation was absent. The behavioral effect of conditioning was disturbed. Both L4 SOM-INs excitation and L2/3 VIP-INs inhibition during conditioning did not affect the plasticity or the conditioned response.We found the activity of L4 SOM-INs is indispensable in the formation of learning-induced plastic change. We propose that L4 SOM-INs may provide disinhibition by blocking L4 parvalbumin interneurons, allowing a flow of information into upper cortical layers during learning.     

Specificity of cortical synaptic connectivity: Emphasis on perspectives gained from quantitative electron microscopy

This report traces the historical development of concepts regarding the specificity of synaptic connectivity in the cerebral cortex as viewed primarily from the perspective of electron microscopy. The occurrence of stereotypical patterns of connection (e.g., contrasting synaptic patterns on the surfaces of spiny vs. non-spiny neurons, the general consistency with which axonal pathways impinge on and originate within specific cortical areas and layers, triadic synaptic relationships) implies that cortical connectivity is highly structured. The high degree of order characterizing many aspects of cortical organization is mirrored by an equally ordered arrangement of synaptic connections between specific types of neurons. This observation is based on quantitative electron microscopic studies of synapses between identified neurons and from the results of correlative anatomical/electrophysiological investigations. The recognition of recurring synaptic patterns and responses between specific neurons has generated increased support for the notion of specificity of synaptic connections at the expense of randomness, but the role of specificity in cortical function is an unresolved question. At the core of cortical processing lie myriad possibilities for computation provided by the wealth of synaptic connections involving each cortical neuron. Specificity, by limiting possibilities for connection, can impose an order on synaptic interactions even as processes of dynamic selection or synaptic remodeling ensure the constant formation and dissolution of cortical circuits. These operations make maximal use of the richness of cortical synaptic connections to produce a highly flexible system, irrespective of the degree of randomness or specificity that obtains for cortical wiring at any particular time.     

Activation of glutamate ionotropic connections of sensorimotor cortex neurons during conditioning

Changes in conditioned impulse reactions of neurons in sensorimotor cortex were studied during microiontophoretic application of glutamatergic and GABA ergic agonistic and antagonistic drugs. It was shown that ionotropic glutamate receptors (AMPA and NMDA) are activated by a conditioned stimulus. Not only large pyramidal neurons of deep cortical layers but surrounding short-axon inhibitory interneurons are involved in the reaction. It was shown that the activity of pyramidal neurons is under a constant inhibitory control from surrounding interneurons. This inhibition is involved in organization of excitatory cortical responses during conditioning.     

Dense inhibitory connectivity in neocortex

The connectivity diagram of neocortical circuits is still unknown, and there are conflicting data as to whether cortical neurons are wired specifically or not. To investigate the basic structure of cortical microcircuits, we use a two-photon photostimulation technique that enables the systematic mapping of synaptic connections with single-cell resolution. We map the inhibitory connectivity between upper layers somatostatin-positive GABAergic interneurons and pyramidal cells in mouse frontal cortex. Most, and sometimes all, inhibitory neurons are locally connected to every sampled pyramidal cell. This dense inhibitory connectivity is found at both young and mature developmental ages. Inhibitory innervation of neighboring pyramidal cells is similar, regardless of whether they are connected among themselves or not. We conclude that local inhibitory connectivity is promiscuous, does not form subnetworks, and can approach the theoretical limit of a completely connected synaptic matrix.     

Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model

Cortical rhythms have been thought to play crucial roles in our cognitive abilities. Rhythmic activity in the beta frequency band, around 20 Hz, has been reported in recent studies that focused on neural correlates of attention, indicating that top-down beta rhythms, generated in higher cognitive areas and delivered to earlier sensory areas, can support attentional gain modulation. To elucidate functional roles of beta rhythms and underlying mechanisms, we built a computational model of sensory cortical areas. Our simulation results show that top-down beta rhythms can activate ascending synaptic projections from L5 to L4 and L2/3, responsible for biased competition in superficial layers. In the simulation, slow-inhibitory interneurons are shown to resonate to the 20 Hz input and modulate the activity in superficial layers in an attention-related manner. The predicted critical roles of these cells in attentional gain provide a potential mechanism by which cholinergic drive can support selective attention.     

Suppression of HPV-16 late L1 5′-splice site SD3632 by binding of hnRNP D proteins and hnRNP A2/B1 to upstream AUAGUA RNA motifs

Human papillomavirus type 16 (HPV-16) 5′-splice site SD3632 is used exclusively to produce late L1 mRNAs. We identified a 34-nt splicing inhibitory element located immediately upstream of HPV-16 late 5′-splice site SD3632. Two AUAGUA motifs located in these 34 nt inhibited SD3632. Two nucleotide substitutions in each of the HPV-16 specific AUAGUA motifs alleviated splicing inhibition and induced late L1 mRNA production from episomal forms of the HPV-16 genome in primary human keratinocytes. The AUAGUA motifs bind specifically not only to the heterogeneous nuclear RNP (hnRNP) D family of RNA-binding proteins including hnRNP D/AUF, hnRNP DL and hnRNP AB but also to hnRNP A2/B1. Knock-down of these proteins induced HPV-16 late L1 mRNA expression, and overexpression of hnRNP A2/B1, hnRNP AB, hnRNP DL and the two hnRNP D isoforms hnRNP D37 and hnRNP D40 further suppressed L1 mRNA expression. This inhibition may allow HPV-16 to hide from the immune system and establish long-term persistent infections with enhanced risk at progressing to cancer. There is an inverse correlation between expression of hnRNP D proteins and hnRNP A2/B1 and HPV-16 L1 production in the cervical epithelium, as well as in cervical cancer, supporting the conclusion that hnRNP D proteins and A2/B1 inhibit HPV-16 L1 mRNA production.     

The wiring economy principle: connectivity determines anatomy in the human brain

Minimization of the wiring cost of white matter fibers in the human brain appears to be an organizational principle. We investigate this aspect in the human brain using whole brain connectivity networks extracted from high resolution diffusion MRI data of 14 normal volunteers. We specifically address the question of whether brain anatomy determines its connectivity or vice versa. Unlike previous studies we use weighted networks, where connections between cortical nodes are real-valued rather than binary off-on connections. In one set of analyses we found that the connectivity structure of the brain has near optimal wiring cost compared to random networks with the same number of edges, degree distribution and edge weight distribution. A specifically designed minimization routine could not find cheaper wiring without significantly degrading network performance. In another set of analyses we kept the observed brain network topology and connectivity but allowed nodes to freely move on a 3D manifold topologically identical to the brain. An efficient minimization routine was written to find the lowest wiring cost configuration. We found that beginning from any random configuration, the nodes invariably arrange themselves in a configuration with a striking resemblance to the brain. This confirms the widely held but poorly tested claim that wiring economy is a driving principle of the brain. Intriguingly, our results also suggest that the brain mainly optimizes for the most desirable network connectivity, and the observed brain anatomy is merely a result of this optimization.     

Laminar and Dorsoventral Molecular Organization of the Medial Entorhinal Cortex Revealed by Large-scale Anatomical Analysis of Gene Expression

Neural circuits in the medial entorhinal cortex (MEC) encode an animal’s position and orientation in space. Within the MEC spatial representations, including grid and directional firing fields, have a laminar and dorsoventral organization that corresponds to a similar topography of neuronal connectivity and cellular properties. Yet, in part due to the challenges of integrating anatomical data at the resolution of cortical layers and borders, we know little about the molecular components underlying this organization. To address this we develop a new computational pipeline for high-throughput analysis and comparison of in situ hybridization (ISH) images at laminar resolution. We apply this pipeline to ISH data for over 16,000 genes in the Allen Brain Atlas and validate our analysis with RNA sequencing of MEC tissue from adult mice. We find that differential gene expression delineates the borders of the MEC with neighboring brain structures and reveals its laminar and dorsoventral organization. We propose a new molecular basis for distinguishing the deep layers of the MEC and show that their similarity to corresponding layers of neocortex is greater than that of superficial layers. Our analysis identifies ion channel-, cell adhesion- and synapse-related genes as candidates for functional differentiation of MEC layers and for encoding of spatial information at different scales along the dorsoventral axis of the MEC. We also reveal laminar organization of genes related to disease pathology and suggest that a high metabolic demand predisposes layer II to neurodegenerative pathology. In principle, our computational pipeline can be applied to high-throughput analysis of many forms of neuroanatomical data. Our results support the hypothesis that differences in gene expression contribute to functional specialization of superficial layers of the MEC and dorsoventral organization of the scale of spatial representations.