Deciphering the brain's codes

The two sensory systems discussed use similar algorithms for the synthesis of the neuronal selectivity for the stimulus that releases a particular behavior, although the neural circuits, the brain sites involved, and even the species are different. This stimulus selectivity emerges gradually in a neural network organized according to parallel and hierarchical design principles. The parallel channels contain lower order stations with special circuits for the creation of neuronal selectivities for different features of the stimulus. Convergence of the parallel pathways brings these selectivities together at a higher order station for the eventual synthesis of the selectivity for the whole stimulus pattern. The neurons that are selective for the stimulus are at the top of the hierarchy, and they form the interface between the sensory and motor systems or between sensory systems of different modalities. The similarities of these two systems at the level of algorithms suggest the existence of rules of signal processing that transcend different sensory systems and species of animals

Auditory Spatial Acuity Approximates the Resolving Power of Space-Specific Neurons

The relationship between neuronal acuity and behavioral performance was assessed in the barn owl (Tyto alba), a nocturnal raptor renowned for its ability to localize sounds and for the topographic representation of auditory space found in the midbrain. We measured discrimination of sound-source separation using a newly developed procedure involving the habituation and recovery of the pupillary dilation response. The smallest discriminable change of source location was found to be about two times finer in azimuth than in elevation. Recordings from neurons in its midbrain space map revealed that their spatial tuning, like the spatial discrimination behavior, was also better in azimuth than in elevation by a factor of about two. Because the PDR behavioral assay is mediated by the same circuitry whether discrimination is assessed in azimuth or in elevation, this difference in vertical and horizontal acuity is likely to reflect a true difference in sensory resolution, without additional confounding effects of differences in motor performance in the two dimensions. Our results, therefore, are consistent with the hypothesis that the acuity of the midbrain space map determines auditory spatial discrimination

Multiplicative Auditory Spatial Receptive Fields Created by a Hierarchy of Population Codes

A multiplicative combination of tuning to interaural time difference (ITD) and interaural level difference (ILD) contributes to the generation of spatially selective auditory neurons in the owl's midbrain. Previous analyses of multiplicative responses in the owl have not taken into consideration the frequency-dependence of ITD and ILD cues that occur under natural listening conditions. Here, we present a model for the responses of ITD- and ILD-sensitive neurons in the barn owl's inferior colliculus which satisfies constraints raised by experimental data on frequency convergence, multiplicative interaction of ITD and ILD, and response properties of afferent neurons. We propose that multiplication between ITD- and ILD-dependent signals occurs only within frequency channels and that frequency integration occurs using a linear-threshold mechanism. The model reproduces the experimentally observed nonlinear responses to ITD and ILD in the inferior colliculus, with greater accuracy than previous models. We show that linear-threshold frequency integration allows the system to represent multiple sound sources with natural sound localization cues, whereas multiplicative frequency integration does not. Nonlinear responses in the owl's inferior colliculus can thus be generated using a combination of cellular and network mechanisms, showing that multiple elements of previous theories can be combined in a single system

A Functional Role for Neural Columns: Resolving F2 Transition Variability in Stop Place Categorization

Documented examples from neuroethology have revealed species-specific neural encoding mechanisms capable of mapping highly variable, but lawful, visual and auditory inputs within neural columns. By virtue of the entire column being the functional unit of both representation and processing, signal variation is collectively ‘absorbed’, and hence normalized, to help form natural categories possessing an underlying physically-based commonality. Stimulus-specific ‘tolerance ranges’ define the limits of signal variation, effectively shaping the functionality of the columnar-based processing. A conceptualization for an analogous human model utilizing this evolutionarily conserved neural encoding strategy for signal variability absorption is described for the non-invariance issue in stop place perception

Hotspots of dendritic spine turnover facilitate clustered spine addition and learning and memory.

Modeling studies suggest that clustered structural plasticity of dendritic spines is an efficient mechanism of information storage in cortical circuits. However, why new clustered spines occur in specific locations and how their formation relates to learning and memory (L&M) remain unclear. Using in vivo two-photon microscopy, we track spine dynamics in retrosplenial cortex before, during, and after two forms of episodic-like learning and find that spine turnover before learning predicts future L&M performance, as well as the localization and rates of spine clustering. Consistent with the idea that these measures are causally related, a genetic manipulation that enhances spine turnover also enhances both L&M and spine clustering. Biophysically inspired modeling suggests turnover increases clustering, network sparsity, and memory capacity. These results support a hotspot model where spine turnover is the driver for localization of clustered spine formation, which serves to modulate network function, thus influencing storage capacity and L&M

The tectum/superior colliculus as the vertebrate solution for spatial sensory integration and action

The superior colliculus, or tectum in the case of non-mammalian vertebrates, is a part of the brain that registers events in the surrounding space, often through vision and hearing, but also through electrosensation, infrared detection, and other sensory modalities in diverse vertebrate lineages. This information is used to form maps of the surrounding space and the positions of different salient stimuli in relation to the individual. The sensory maps are arranged in layers with visual input in the uppermost layer, other senses in deeper positions, and a spatially aligned motor map in the deepest layer. Here, we will review the organization and intrinsic function of the tectum/superior colliculus and the information that is processed within tectal circuits. We will also discuss tectal/superior colliculus outputs that are conveyed directly to downstream motor circuits or via the thalamus to cortical areas to control various aspects of behavior. The tectum/superior colliculus is evolutionarily conserved among all vertebrates, but tailored to the sensory specialties of each lineage, and its roles have shifted with the emergence of the cerebral cortex in mammals. We will illustrate both the conserved and divergent properties of the tectum/superior colliculus through vertebrate evolution by comparing tectal processing in lampreys belonging to the oldest group of extant vertebrates, larval zebrafish, rodents, and other vertebrates including primates

Sensorimotor maps can be dynamically calibrated using an adaptive-filter model of the cerebellum

Substantial experimental evidence suggests the cerebellum is involved in calibrating sensorimotor maps. Consistent with this involvement is the well-known, but little understood, massive cerebellar projection to maps in the superior colliculus. Map calibration would be a significant new role for the cerebellum given the ubiquity of map representations in the brain, but how it could perform such a task is unclear. Here we investigated a dynamic method for map calibration, based on electrophysiological recordings from the superior colliculus, that used a standard adaptive-filter cerebellar model. The method proved effective for complex distortions of both unimodal and bimodal maps, and also for predictive map-based tracking of moving targets. These results provide the first computational evidence for a novel role for the cerebellum in dynamic sensorimotor map calibration, of potential importance for coordinate alignment during ongoing motor control, and for map calibration in future biomimetic systems. This computational evidence also provides testable experimental predictions concerning the role of the connections between cerebellum and superior colliculus in previously observed dynamic coordinate transformations

Adaptive map alignment in the superior colliculus of the barn owl: a neuromorphic implementation

Adaptation is one of the basic phenomena of biology, while adaptability is an important feature for neural network. Young barn owl can well adapt its visual and auditory integration to the environmental change, such as prism wearing. At first, a mathematical model is introduced by the related study in biological experiment. The model well explained the mechanism of the sensory map realignment through axongenesis and synaptogenesis. Simulation results of this model are consistent with the biological data. Thereafter, to test the model’s application in hardware, the model is implemented into a robot. Visual and auditory signals are acquired by the sensors of the robot and transferred back to PC through bluetooth. Results of the robot experiment are presented, which shows the SC model allowing the robot to adjust visual and auditory integration to counteract the effects of a prism. Finally, based on the model, a silicon Superior Colliculus is designed in VLSI circuit and fabricated. Performance of the fabricated chip has shown the synaptogenesis and axogenesis can be emulated in VLSI circuit. The circuit of neural model provides a new method to update signals and reconfigure the switch network (the chip has an automatic reconfigurable network which is used to correct the disparity between signals). The chip is also the first Superior Colliculus VLSI circuit to emulate the sensory map realignment