Laminar Organization of the Entorhinal Cortex in Macaque Monkeys Based on Cell-Type-Specific Markers and Connectivity

The entorhinal cortex (EC) is a major gateway between the hippocampus and telencephalic structures, and plays a critical role in memory and navigation. Through the use of various molecular markers and genetic tools, neuron types constituting EC are well studied in rodents, and their layer-dependent distributions, connections, and functions have also been characterized. In primates, however, such cell-type-specific understandings are lagging. To bridge the gap between rodents and primates, here we provide the first cell-type-based global map of EC in macaque monkeys. The laminar organization of the monkey EC was systematically examined and compared with that of the rodent EC by using immunohistochemistry for molecular markers which have been well characterized in the rodent EC: reelin, calbindin, and Purkinje cell protein 4 (PCP4). We further employed retrograde neuron labeling from the nucleus accumbens and amygdala to identify the EC output layer. This cell-type-based approach enabled us to apply the latest laminar definition of rodent EC to monkeys. Based on the similarity of the laminar organization, the monkey EC can be divided into two subdivisions: rostral and caudal EC. These subdivisions likely correspond to the lateral and medial EC in rodents, respectively. In addition, we found an overall absence of a clear laminar arrangement of layer V neurons in the rostral EC, unlike rodents. The cell-type-based architectural map provided in this study will accelerate the application of genetic tools in monkeys for better understanding of the role of EC in memory and navigation.

Laminar Computing by Cerebral Cortex

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.

Probabilistic skeletons endow brain-like neural networks with innate computing capabilities

Genetically encoded structure endows neural networks of the brain with innate computational capabilities that enable odor classification and basic motor control right after birth. It is also conjectured that the stereotypical laminar organization of neocortical microcircuits provides basic computing capabilities on which subsequent learning can build. However, it has remained unknown how nature achieves this. Insight from artificial neural networks does not help to solve this problem, since their computational capabilities result from learning. We show that genetically encoded control over connection probabilities between different types of neurons suffices for programming substantial computing capabilities into neural networks. This insight also provides a method for enhancing computing and learning capabilities of artificial neural networks and neuromorphic hardware through clever initialization.

Homologous laminar organization of the mouse and human subiculum

The subiculum is the major output component of the hippocampal formation and one of the major brain structures most affected by Alzheimer’s disease. Our previous work revealed a hidden laminar architecture within the mouse subiculum. However, the rotation of the hippocampal longitudinal axis across species makes it unclear how the laminar organization is represented in human subiculum. Using in situ hybridization data from the Allen Human Brain Atlas, we demonstrate that the human subiculum also contains complementary laminar gene expression patterns similar to the mouse. In addition, we provide evidence that the molecular domain boundaries in human subiculum correspond to microstructural differences observed in high resolution MRI and fiber density imaging. Finally, we show both similarities and differences in the gene expression profile of subiculum pyramidal cells within homologous lamina. Overall, we present a new 3D model of the anatomical organization of human subiculum and its evolution from the mouse.

Rabies anterograde monosynaptic tracing reveals organization of spinal sensory circuits

Somatosensory neurons detect vital information about the environment and internal status of the body, such as temperature, touch, itch and proprioception. The circuit mechanisms controlling the coding of somatosensory information and the generation of appropriate behavioral responses are not clear yet. In order to address this issue, it is important to define the precise connectivity patterns between primary sensory afferents dedicated to the detection of different stimuli and recipient neurons in the central nervous system. In this study we used a rabies tracing approach for mapping spinal circuits receiving sensory input from distinct, genetically defined, modalities. We analyzed the anatomical organization of spinal circuits involved in coding of thermal and mechanical stimuli and showed that somatosensory information from distinct modalities is relayed to partially overlapping ensembles of interneurons displaying stereotyped laminar organization, thus highlighting the importance of positional features and population coding for the processing and integration of somatosensory information.

Potential factors influencing replay across CA1 during sharp-wave ripples

Sharp-wave ripples are complex neurophysiological events recorded along the trisynaptic hippocampal circuit (i.e. from CA3 to CA1 and the subiculum) during slow-wave sleep and awake states. They arise locally but scale brain-wide to the hippocampal target regions at cortical and subcortical structures. During these events, neuronal firing sequences are replayed retrospectively or prospectively and in the forward or reverse order as defined by experience. They could reflect either pre-configured firing sequences, learned sequences or an option space to inform subsequent decisions. How can different sequences arise during sharp-wave ripples? Emerging data suggest the hippocampal circuit is organized in different loops across the proximal (close to dentate gyrus) and distal (close to entorhinal cortex) axis. These data also disclose a so-far neglected laminar organization of the hippocampal output during sharp-wave events. Here, I discuss whether by incorporating cell-type-specific mechanisms converging on deep and superficial CA1 sublayers along the proximodistal axis, some novel factors influencing the organization of hippocampal sequences could be unveiled. This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.

Homologous laminar organization of the mouse and human subiculum

SummaryThe subiculum is the major output structure of the hippocampal formation and one of the brain regions most affected by Alzheimer’s disease. Our previous work revealed a hidden laminar architecture within the mouse subiculum. However, the rotation of the hippocampal longitudinal axis across species makes it unclear how the laminar organization is represented in human subiculum. Using in situ hybridization data from the Allen Human Brain Atlas, we demonstrate that the human subiculum also contains complementary laminar gene expression patterns similar to the mouse. In addition, we provide evidence that the molecular domain boundaries in human subiculum correspond to microstructural differences observed in high resolution MRI and fiber density imaging. Finally, we show both similarities and differences in the gene expression profile of subiculum pyramidal cells within homologous lamina. Overall, we present a new 3D model of the anatomical organization of human subiculum and its evolution from the mouse.