The Y cell visual pathway implements a demodulating nonlinearity

Neural encoding of sensory signals involves both linear and nonlinear processes. Determining which nonlinear operations are implemented by neural systems is crucial to understanding sensory processing. Here, we ask if demodulation, the process used to decode AM radio signals, describes how Y cells in the cat LGN nonlinearly encode the visual scene. In response to visual AM signals across?a wide range of carrier frequencies, Y cells were found to transmit a demodulated signal, with the firing rate of single-units fluctuating at the envelope frequency but not the carrier frequency. A comparison of temporal frequency tuning properties between LGN Y cells and neurons in two primary cortical areas suggests that Y cells initiate a distinct pathway that carries a demodulated representation of the visual scene to cortex. The nonlinear signal processing carried out by the Y cell pathway simplifies the neural representation of complex visual features and allows high spatiotemporal frequencies to drive cortical responses.     

Plasticity of central autonomic neural circuits in diabetes

Regulation of energy metabolism is controlled by the brain, in which key central neuronal circuits process a variety of information reflecting nutritional state. Special sensory and gastrointestinal afferent neural signals, along with blood-borne metabolic signals, impinge on parallel central autonomic circuits located in the brainstem and hypothalamus to signal changes in metabolic balance. Specifically, neural and humoral signals converge on the brainstem vagal system and similar signals concentrate in the hypothalamus, with significant overlap between both sensory and motor components of each system and extensive cross-talk between the systems. This ultimately results in production of coordinated regulatory autonomic and neuroendocrine cues to maintain energy homeostasis. Therapeutic metabolic adjustments can be accomplished by modulating viscerosensory input or autonomic motor output, including altering parasympathetic circuitry related to GI, pancreas, and liver regulation. These alterations can include pharmacological manipulation, but surgical modification of neural signaling should also be considered. In addition, central control of visceral function is often compromised by diabetes mellitus, indicating that circuit modification should be studied in the context of its effect on neurons in the diabetic state. Diabetes has traditionally been handled as a peripheral metabolic disease, but the central nervous system plays a crucial role in regulating glucose homeostasis. This review focuses on key autonomic brain areas associated with management of energy homeostasis and functional changes in these areas associated with the development of diabetes.     

A role for the cerebellum in the control of limb movement velocity

Accepting, rejecting or modifying the many different theories of the cerebellum's role in the control of movement requires an understanding of the signals encoded in the discharge of cerebellar neurons and how those signals are transformed by the cerebellar circuitry. Particularly challenging is understanding the sensory and motor signals carried by the two types of action potentials generated by cerebellar Purkinje cells, the simple spikes and complex spikes. Advances have been made in understanding this signal processing in the context of voluntary arm movements. Recent evidence suggests that mossy fiber afferents to the cerebellar cortex are a source of kinematic signals, providing information about movement direction and speed. In turn, the simple spike discharge of Purkinje cells integrates this mossy fiber information to generate a movement velocity signal. Complex spikes may signal errors in movement velocity. It is proposed that the cerebellum uses the signals carried by the simple and complex spike discharges to control movement velocity for both step and tracking arm movements.     

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons'' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.     

Context-dependent changes in functional circuitry in visual area MT

Animals can flexibly change their behavior in response to a particular sensory stimulus; the mapping between sensory and motor representations in the brain must therefore be flexible as well. Changes in the correlated firing of pairs of neurons may provide a metric of changes in functional circuitry during behavior. We studied dynamic changes in functional circuitry by analyzing the noise correlations of simultaneously recorded MT neurons in two behavioral contexts: one that promotes cooperative interactions between the two neurons and another that promotes competitive interactions. We found that identical visual stimuli give rise to differences in noise correlation in the two contexts, suggesting that MT neurons receive inputs of central origin whose strength changes with the task structure. The data are consistent with a mixed feature-based attentional strategy model in which the animal sometimes alternates attention between opposite directions of motion and sometimes attends to the two directions simultaneously.     

Variability of perceptual multistability: from brain state to individual trait

Few phenomena are as suitable as perceptual multistability to demonstrate that the brain constructively interprets sensory input. Several studies have outlined the neural circuitry involved in generating perceptual inference but only more recently has the individual variability of this inferential process been appreciated. Studies of the interaction of evoked and ongoing neural activity show that inference itself is not merely a stimulus-triggered process but is related to the context of the current brain state into which the processing of external stimulation is embedded. As brain states fluctuate, so does perception of a given sensory input. In multistability, perceptual fluctuation rates are consistent for a given individual but vary considerably between individuals. There has been some evidence for a genetic basis for these individual differences and recent morphometric studies of parietal lobe regions have identified neuroanatomical substrates for individual variability in spontaneous switching behaviour. Moreover, disrupting the function of these latter regions by transcranial magnetic stimulation yields systematic interference effects on switching behaviour, further arguing for a causal role of these regions in perceptual inference. Together, these studies have advanced our understanding of the biological mechanisms by which the brain constructs the contents of consciousness from sensory input.     

Visual information processing using bacteriorhodopsin-based complex LB films

Image extraction and visual information processing using bacteriorhodopsin (bR)-based bioelectronic devices is presented. Image extraction was achieved using a photoreceptor consisting of bR and spiropyran films. The undesired signals from the photoreceptor were automatically eliminated from the whole signal by spiropyran films acting as an optical noise filter that increases the target signal to an undesired signal ratio. For the information processing, the photoreceptor consisting of bR and lipid films deposited with different configurations was used and the target signals were processed to achieve the pattern recognition. The pattern recognition was based on not only the response variability of bacteriorhodopsin, induced by different film configurations, but also on the initial learning process. The input patterns were predicted by simple calculation with the known signals through the initial learning process.     

Optogenetic Stimulation of the Corticothalamic Pathway Affects Relay Cells and GABAergic Neurons Differently in the Mouse Visual Thalamus

The dorsal lateral geniculate nucleus (dLGN) serves as the primary conduit of retinal information to visual cortex. In addition to retinal input, dLGN receives a large feedback projection from layer VI of visual cortex. Such input modulates thalamic signal transmission in different ways that range from gain control to synchronizing network activity in a stimulus-specific manner. However, the mechanisms underlying such modulation have been difficult to study, in part because of the complex circuitry and diverse cell types this pathway innervates. To address this and overcome some of the technical limitations inherent in studying the corticothalamic (CT) pathway, we adopted a slice preparation in which we were able to stimulate CT terminal arbors in the visual thalamus of the mouse with blue light by using an adeno-associated virus to express the light-gated ion channel, ChIEF, in layer VI neurons. To examine the postsynaptic responses evoked by repetitive CT stimulation, we recorded from identified relay cells in dLGN, as well as GFP expressing GABAergic neurons in the thalamic reticular nucleus (TRN) and intrinsic interneurons of dLGN. Relay neurons exhibited large glutamatergic responses that continued to increase in amplitude with each successive stimulus pulse. While excitatory responses were apparent at postnatal day 10, the strong facilitation noted in adult was not observed until postnatal day 21. GABAergic neurons in TRN exhibited large initial excitatory responses that quickly plateaued during repetitive stimulation, indicating that the degree of facilitation was much larger for relay cells than for TRN neurons. The responses of intrinsic interneurons were smaller and took the form of a slow depolarization. These differences in the pattern of excitation for different thalamic cell types should help provide a framework for understanding how CT feedback alters the activity of visual thalamic circuitry during sensory processing as well as different behavioral or pathophysiological states.     

Analysis of neuronal networks in the visual system of the cat using statistical signals — Simple and complex cells

Superimposing additively a two-dimensional noise process to deterministic input signals (bars) the neurons of area 17 show a class-specific reaction for the task of signal extraction. Moving both parts of the signals simultaneously and varying the signal to noise ratio (S/N) the simple cells achieve the same performance as resulted from the psychophysical experiment. Type I complex cells extract moving deterministic signals (i.e. bars) from the stationary noise, whereas in the answers of Type II complex cells the statistical parts of the signals predominate. Considering the different cell types each as a series of a linear and a nonlinear system one obtains the cell specific space-time frequency and the amplitude characteristics.This work was supported by DFG Grant Ho 450/6 and Grant Se 251/9     

Visual threshold is set by linear and nonlinear mechanisms in the retina that mitigate noise: how neural circuits in the retina improve the signal-to-noise ratio of the single-photon response

In sensory biology, a major outstanding question is how sensory receptor cells minimize noise while maximizing signal to set the detection threshold. This optimization could be problematic because the origin of both the signals and the limiting noise in most sensory systems is believed to lie in stimulus transduction. Signal processing in receptor cells can improve the signal-to-noise ratio. However, neural circuits can further optimize the detection threshold by pooling signals from sensory receptor cells and processing them using a combination of linear and nonlinear filtering mechanisms. In the visual system, noise limiting light detection has been assumed to arise from stimulus transduction in rod photoreceptors. In this context, the evolutionary optimization of the signal-to-noise ratio in the retina has proven critical in allowing visual sensitivity to approach the limits set by the quantal nature of light. Here, we discuss how noise in the mammalian retina is mitigated to allow for highly sensitive night vision.     

Contributions of electric fish to the understanding of sensory processing by reafferent systems.

Sensory systems must solve the inverse problem of determining environmental events based on patterns of neural activity in the central nervous system that are affected by those environmental events. Different environmental events can give rise to indistinguishable patterns of neural activity, so that there will often, perhaps even always, be multiple solutions to a sensory inverse problem. Imaging strategies and brain organization confine these multiple solutions within a bounded set. Three different active strategies may be employed by animals to constrain the number of solutions to the sensory inverse problem: active generation of the energy (carrier) that stimulates receptors; reorientation of the point of view; and control of signal conditioning before transduction (pre-receptor mechanisms). This paper describes how these strategies are used in sensory-motor systems, using electric fish as a paradigmatic example. Carrier generation and receptor tuning to the carrier improve signal to noise ratio. Receptor tuning to different frequency bands of the carrier spectrum allows a sensory system to evaluate different kinds of carrier modulations and to extract the different features of objects in the environment. Pre-receptor mechanisms condition the signals, optimizing their detection at a foveal region where the sensory resolution is maximum. Active orientation of the sensory surface redirects the fovea to explore in detail the source of interesting signals. Sensory input generated by these active exploration mechanisms ('reafference') has two components: one, necessary, derived from the self-generated actions and another, contingent, consisting of the information obtained from the external world. Extracting environmental information ('exafference') requires that the self generated afference be subtracted from the sensory inflow. Such subtraction is often associated with the generation and storage of expectations about sensory inputs. It can be concluded that an animal's perceptual world and its ability to transform the world are inextricably linked. Understanding sensory systems must, therefore, always require understanding the organization of motor behavior.     

Processing of Multi-dimensional Sensorimotor Information in the Spinal and Cerebellar Neuronal Circuitry: A New Hypothesis

Why are sensory signals and motor command signals combined in the neurons of origin of the spinocerebellar pathways and why are the granule cells that receive this input thresholded with respect to their spike output? In this paper, we synthesize a number of findings into a new hypothesis for how the spinocerebellar systems and the cerebellar cortex can interact to support coordination of our multi-segmented limbs and bodies. A central idea is that recombination of the signals available to the spinocerebellar neurons can be used to approximate a wide array of functions including the spatial and temporal dependencies between limb segments, i.e. information that is necessary in order to achieve coordination. We find that random recombination of sensory and motor signals is not a good strategy since, surprisingly, the number of granule cells severely limits the number of recombinations that can be represented within the cerebellum. Instead, we propose that the spinal circuitry provides useful recombinations, which can be described as linear projections through aspects of the multi-dimensional sensorimotor input space. Granule cells, potentially with the aid of differentiated thresholding from Golgi cells, enhance the utility of these projections by allowing the Purkinje cell to establish piecewise-linear approximations of non-linear functions. Our hypothesis provides a novel view on the function of the spinal circuitry and cerebellar granule layer, illustrating how the coordinating functions of the cerebellum can be crucially supported by the recombinations performed by the neurons of the spinocerebellar systems.     

SK channel subtypes enable parallel optimized coding of behaviorally relevant stimulus attributes: A review

Ion channels play essential roles toward determining how neurons respond to sensory input to mediate perception and behavior. Small conductance calcium-activated potassium (SK) channels are found ubiquitously throughout the brain and have been extensively characterized both molecularly and physiologically in terms of structure and function. It is clear that SK channels are key determinants of neural excitability as they mediate important neuronal response properties such as spike frequency adaptation. However, the functional roles of the different known SK channel subtypes are not well understood. Here we review recent evidence from the electrosensory system of weakly electric fish suggesting that the function of different SK channel subtypes is to optimize the processing of independent but behaviorally relevant stimulus attributes. Indeed, natural sensory stimuli frequently consist of a fast time-varying waveform (i.e., the carrier) whose amplitude (i.e., the envelope) varies slowly and independently. We first review evidence showing how somatic SK2 channels mediate tuning and responses to carrier waveforms. We then review evidence showing how dendritic SK1 channels instead determine tuning and optimize responses to envelope waveforms based on their statistics as found in the organism's natural environment in an independent fashion. The high degree of functional homology between SK channels in electric fish and their mammalian orthologs, as well as the many important parallels between the electrosensory system and the mammalian visual, auditory, and vestibular systems, suggest that these functional roles are conserved across systems and species.     

Membrane Resonance and Stochastic Resonance Modulate Firing Patterns of Thalamocortical Neurons

We examined the interactions of subthreshold membrane resonance and stochastic resonance using whole-cell patch clamp recordings in thalamocortical neurons of rat brain slices, as well as with a Hodgkin-Huxley-type mathematical model of thalamocortical neurons. The neurons exhibited the subthreshold resonance when stimulated with small amplitude sine wave currents of varying frequency, and stochastic resonance when noise was added to sine wave inputs. Stochastic resonance was manifest as a maximum in signal-to-noise ratio of output response to subthreshold periodic input combined with noise. Stochastic resonance in conjunction with subthreshold resonance resulted in action potential patterns that showed frequency selectivity for periodic inputs. Stochastic resonance was maximal near subthreshold resonance frequency and a high noise level was required for detection of high frequency signals. We speculate that combined membrane and stochastic resonances have physiological utility in coupling synaptic activity to preferred firing frequency and in network synchronization under noise.     

Information processing in mammalian olfactory system

In recent years, considerable progress has been made in understanding how the olfactory system uses neural space to encode sensory information. In this review, we focus on recent studies aimed at understanding the organizational strategies used by the mammalian olfactory system to encode information. The odorant receptor gene family is discussed in the context of its genomic organization as well as the specificity of olfactory sensory neurons. These data have important consequences for the mechanisms of odorant receptor gene choice by a given sensory neuron. Division of the olfactory epithelium into zones that express different sets of odorant receptors is the first level of input organization. The topographical relationship between periphery and olfactory bulb represents a further level of processing of information and results in the formation of a highly organized spatial map of information in the olfactory bulb. There, local circuitry refines the sensory input through various lateral interactions. Finally, the factors that may drive the development of such a spatial map are discussed. The onset of expression and the establishment of the zonal organization of odorant receptor genes in the epithelium are not dependent upon the presence of the olfactory bulb, suggesting that the functional identity of olfactory sensory neurons is determined independently of target selection. © 1996 John Wiley & Sons, Inc.     

Integrating Top-Down and Bottom-Up Sensory Processing by Somato-Dendritic Interactions

The classical view of cortical information processing is that of a bottom-up process in a feedforward hierarchy. However, psychophysical, anatomical, and physiological evidence suggests that top-down effects play a crucial role in the processing of input stimuli. Not much is known about the neural mechanisms underlying these effects. Here we investigate a physiologically inspired model of two reciprocally connected cortical areas. Each area receives bottom-up as well as top-down information. This information is integrated by a mechanism that exploits recent findings on somato-dendritic interactions. (1) This results in a burst signal that is robust in the context of noise in bottom-up signals. (2) Investigating the influence of additional top-down information, priming-like effects on the processing of bottom-up input can be demonstrated. (3) In accordance with recent physiological findings, interareal coupling in low-frequency ranges is characteristically enhanced by top-down mechanisms. The proposed scheme combines a qualitative influence of top-down directed signals on the temporal dynamics of neuronal activity with a limited effect on the mean firing rate of the targeted neurons. As it gives an account of the system properties on the cellular level, it is possible to derive several experimentally testable predictions.     

Primary motor cortex reports efferent control of vibrissa motion on multiple timescales

Exploratory whisking in rat is an example of self-generated movement on multiple timescales, from slow variations in the envelope of whisking to the rapid sequence of muscle contractions during?a single whisk cycle. We find that, as a population, spike trains of single units in primary vibrissa motor cortex report the absolute angle of vibrissa position. This representation persists after sensory nerve transection, indicating an efferent source. About two-thirds of the units are modulated by slow variations in the envelope of whisking, while relatively few units report rapid changes in position within the whisk cycle. The combined results from this study and past measurements, which show that primary sensory cortex codes the whisking envelope as?a motor copy signal, imply that signals present in both sensory and motor cortices are necessary to compute angular coordinates based on vibrissa touch.     

Signal processing in a simple vertebrate photoreceptor system: the teleost pineal organ

The integrating circuitry and efferent pathways for neural signals evoked in the photosensory pineal organ by changes in ambient illumination have been investigated by a multidisciplinary approach. Intrapineal efferent neurons were identified by means of retrograde filling with horseradish peroxidase (HRP). In addition to several types of neurons, photoreceptor cells that emitted axons to the brain via the pineal tract were observed. The presence of several populations of local interneurons (putatively cholinergic, GABAergic and substance P-containing) and possible afferent (putatively noradrenergic and peptidergic) central innervations were established by means of immunocytochemistry. The anatomical substrate for processing of neural signals thus delineated, the responses of pineal sensory and neural elements to photic stimulation were investigated by means of intracellular recording. Successful recordings were followed by intracellular injection with HRP or Lucifer Yellow CH, for subsequent light or electron microscopical investigation. The recordings indicate the presence of at least two types of photoreceptor cells, that display morphological and physiological features of both retinal rods and cones. In addition, one type of (sign-conserving) interneuron was identified. The photosensory pineal organ thus possess an integrative neural circuitry that may be involved in the elaboration of neural signals to the brain, and/or in the local control of intrapineal functions, e.g. indoleamine synthesis.     

Neuronal precision and the limits for acoustic signal recognition in a small neuronal network

Recognition of acoustic signals may be impeded by two factors: extrinsic noise, which degrades sounds before they arrive at the receiver’s ears, and intrinsic neuronal noise, which reveals itself in the trial-to-trial variability of the responses to identical sounds. Here we analyzed how these two noise sources affect the recognition of acoustic signals from potential mates in grasshoppers. By progressively corrupting the envelope of a female song, we determined the critical degradation level at which males failed to recognize a courtship call in behavioral experiments. Using the same stimuli, we recorded intracellularly from auditory neurons at three different processing levels, and quantified the corresponding changes in spike train patterns by a spike train metric, which assigns a distance between spike trains. Unexpectedly, for most neurons, intrinsic variability accounted for the main part of the metric distance between spike trains, even at the strongest degradation levels. At consecutive levels of processing, intrinsic variability increased, while the sensitivity to external noise decreased. We followed two approaches to determine critical degradation levels from spike train dissimilarities, and compared the results with the limits of signal recognition measured in behaving animals.     

Origin and early evolution of neural circuits for the control of ciliary locomotion

Behaviour evolved before nervous systems. Various single-celled eukaryotes (protists) and the ciliated larvae of sponges devoid of neurons can display sophisticated behaviours, including phototaxis, gravitaxis or chemotaxis. In single-celled eukaryotes, sensory inputs directly influence the motor behaviour of the cell. In swimming sponge larvae, sensory cells influence the activity of cilia on the same cell, thereby steering the multicellular larva. In these organisms, the efficiency of sensory-to-motor transformation (defined as the ratio of sensory cells to total cell number) is low. With the advent of neurons, signal amplification and fast, long-range communication between sensory and motor cells became possible. This may have first occurred in a ciliated swimming stage of the first eumetazoans. The first axons may have had en passant synaptic contacts to several ciliated cells to improve the efficiency of sensory-to-motor transformation, thereby allowing a reduction in the number of sensory cells tuned for the same input. This could have allowed the diversification of sensory modalities and of the behavioural repertoire. I propose that the first nervous systems consisted of combined sensory-motor neurons, directly translating sensory input into motor output on locomotor ciliated cells and steering muscle cells. Neuronal circuitry with low levels of integration has been retained in cnidarians and in the ciliated larvae of some marine invertebrates. This parallel processing stage could have been the starting point for the evolution of more integrated circuits performing the first complex computations such as persistence or coincidence detection. The sensory-motor nervous systems of cnidarians and ciliated larvae of diverse phyla show that brains, like all biological structures, are not irreducibly complex.