Neural circuit models for computations in early visual cortex

Some cortical circuit models study the mechanisms of the transforms from visual inputs to neural responses. They model neural properties such as feature tunings, pattern sensitivities, and how they depend on intracortical connections and contextual inputs. Other cortical circuit models are more concerned with computational goals of the transform from visual inputs to neural responses, or the roles of the neural responses in the visual behavior. The appropriate complexity of a cortical circuit model depends on the question asked. Modeling neural circuits of many interacting hypercolumns is a necessary challenge, which is providing insights to cortical computations, such as visual saliency computation, and linking physiology with global visual cognitive behavior such as bottom-up attentional selection.     

Neural and behavioral mechanisms of olfactory perception

Recent in vivo and in vitro studies have challenged existing models of olfactory processing in the vertebrate olfactory bulb and insect antennal lobe. Whereas lateral connectivity between olfactory glomeruli was previously thought to form a dense, topographically organized inhibitory surround, new evidence suggests that lateral connections may be sparse, nontopographic, and partly excitatory. Other recent studies highlight the role of active sensing (sniffing) in shaping odor-evoked neural activity and perception.     

Neural mechanisms of feature binding

正An object is usually composed of different features (e.g.,color, orientation, and motion), which are processed by segregated visual pathways and represented by functionally specialized brain areas. However, we perceive an object as a coherent whole, rather than its isolated features. How we integrate those isolated features and achieve a precise perception of objects is a fundamental challenge for the visual     

Neural network organization for courtship-song feature detection in Drosophila

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Neural mechanisms for color perception in the primary visual cortex

New neurophysiological results show the existence of multiple transformations of color signals in the primary visual cortex (V1) in macaque monkey. These different color mechanisms may contribute separately to the perception of color boundaries and colored regions. Many cells in V1 respond to color and to black-white (luminance) patterns. These neurons are spatially selective and could provide signals about boundaries between differently colored regions. Other V1 neurons that prefer color over luminance respond without much spatial selectivity to colored stimuli, and could be the neural basis for the response to local color modulation within a region. How these different types of color cells combine inputs from cone photoreceptors is what gives them their different spatial selectivities for color.     

Neural circuit mechanisms linking courtship and reward in Drosophila males

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Neural mechanisms of tactile motion integration in somatosensory cortex

How are local motion signals integrated to form a global motion percept? We investigate the neural mechanisms of tactile motion integration by presenting tactile gratings and plaids to the fingertips of monkeys, using the tactile analogue of a visual monitor and recording the responses evoked in somatosensory cortical neurons. The perceived directions of the gratings and plaids are measured in parallel psychophysical experiments. We identify a population of somatosensory neurons that exhibit integration properties comparable to those induced by analogous visual stimuli in area MT and find that these neural responses account for the perceived direction of the stimuli across all stimulus conditions tested. The preferred direction of the neurons and the perceived direction of the stimuli can be predicted from the weighted average of the directions of the individual stimulus features, highlighting that the somatosensory system implements a vector average mechanism to compute tactile motion direction that bears striking similarities to its visual counterpart.     

Sensitivity of basic oscillatory mechanisms for pattern generation and detection

 Intrinsic oscillators are the basic building blocks of central pattern generators, which model the neural circuits underlying pattern generation. Coupled intrinsic oscillators have been shown to synchronize their oscillatory frequencies and to maintain a characteristic pattern of phase relationships. Recently, oscillatory neurons have also been identified in sensory systems that are involved in decoding phase information. It has been hypothesized that the neural oscillators are part of neural circuits that implement phase-locked loops (PLLs), which are well-known electrical circuits for temporal decoding. Thus, there is evidence that intrinsic neural oscillators participate in both temporal pattern generation and temporal pattern decoding. The present paper investigates the dynamics underlying forced oscillators and forced PLLs, using a single framework, and compares both their stability and sensitivity characteristics. In particular, a method for assessing whether an oscillatory neuron is forced directly or indirectly, as part of a PLL, is developed and applied to published data. Received: 17 July 2000 / Accepted in revised form: 14 March 2001     

Somatosensory cortical mechanisms of feature detection in tactile and kinesthetic discrimination

Neurons in somatosensory cortex of primates process sensory information from the hand by integrating information from large populations of receptors to extract specific features. Tactile neurons in areas 1 and 2 are shown to select features such as contact area, edge orientation, motion across the skin, or direction of movement. Features coded by kinesthetic neurons in areas 3a and 2 relate to joint movement, the joint angle around which the movement occurs, or coordinated postures of the hand and arm. An even higher order cortical cell integrates tactile and kinesthetic information; these "haptic neurons" respond optimally to contact of objects actively grasped in the hand. These global features are coded at the expense of loss of information concerning fine-grained spatial detail.     

Neural networks with constrained inputs as models for pattern formation in primate visual cortex

We present a neural network model for the formation of ocular dominance stripes on primate visual cortex and examine the generic phase behavior and dynamics of the model. The dynamical equation of ocular dominance development can be identified with a class of Langevin equations with a nonconserved order parameter. We first set up and examine an Ising model with long-range interactions in an external field, which is equivalent to the model described by the Langevin equation. We use both mean-field theory and Monte-Carlo simulations to study the equilibrium phase diagram of this equivalent Ising model. The phase diagram comprises three phases: a striped phase, a hexagonal bubble phase, and a uniform paramagnetic phase. We then examine the dynamics of the striped phase by solving the Langevin equation both numerically and by singular perturbation theory. Finally, we compare the results of the model with physiological data. The typical striped structure of the ocular dominance columns corresponds to the zero-field configurations of the model. Monocular deprivation can be simulated by allowing the system to evolve in the absence of an external field at early times and then continuing the simulation in the presence of an external field. The physical and physiological applications of our model are discussed in the conclusion.     

Neural mechanisms in the anterior olfactory nucleus of the rabbit and their possible relevance to localization of an olfactory source

Extracellular recordings were obtained from 40 Anterior OlfactoryNucleus (A.O.N.) units in response to birhinal olfactory stimulations.The units located in the A.O.N. pars dorsalis responded differentlyaccording to the time interval between the onsets of right andleft puffs during birhinal olfactory stimulation. On the contrary,the greater part of the units located in the A.O.N. pars ventraliswas not sensitive to time intervals variations. These data indicatethe ability of some A.O.N. cells to encode temporal characteristicsof an olfactory stimulation.     

Activity-dependent plasticity in an olfactory circuit

Olfactory sensory neurons (OSNs) form synapses with local interneurons and second-order projection neurons to form stereotyped olfactory glomeruli. This primary olfactory circuit is hard-wired through the action of genetic cues. We asked whether individual glomeruli have the capacity for stimulus-evoked plasticity by focusing on the carbon dioxide (CO2) circuit in Drosophila. Specialized OSNs detect this gas and relay the information to a dedicated circuit in the brain. Prolonged exposure to CO2 induced a reversible volume increase in the CO2-specific glomerulus. OSNs showed neither altered morphology nor function after chronic exposure, but one class of inhibitory local interneurons showed significantly increased responses to CO2. Two-photon imaging of the axon terminals of a single PN innervating the CO2 glomerulus showed significantly decreased functional output following CO2 exposure. Behavioral responses to CO2 were also reduced after such exposure. We suggest that activity-dependent functional plasticity may be a general feature of the Drosophila olfactory system.     

Neural circuit mechanisms of hierarchical sequence learning tested on large-scale recording data

The brain performs various cognitive functions by learning the spatiotemporal salient features of the environment. This learning requires unsupervised segmentation of hierarchically organized spike sequences, but the underlying neural mechanism is only poorly understood. Here, we show that a recurrent gated network of neurons with dendrites can efficiently solve difficult segmentation tasks. In this model, multiplicative recurrent connections learn a context-dependent gating of dendro-somatic information transfers to minimize error in the prediction of somatic responses by the dendrites. Consequently, these connections filter the redundant input features represented by the dendrites but unnecessary in the given context. The model was tested on both synthetic and real neural data. In particular, the model was successful for segmenting multiple cell assemblies repeating in large-scale calcium imaging data containing thousands of cortical neurons. Our results suggest that recurrent gating of dendro-somatic signal transfers is crucial for cortical learning of context-dependent segmentation tasks.     

Strong single-fiber sensory inputs to olfactory cortex: implications for olfactory coding

Olfactory information is first encoded in a combinatorial fashion by olfactory bulb glomeruli, which individually represent distinct chemical features of odors. This information is then transmitted to piriform (olfactory) cortex, via axons of olfactory bulb mitral and tufted (M/T) cells, where it is presumed to form the odor percept. However, mechanisms governing the integration of sensory information in mammalian olfactory cortex are unclear. Here we show that single M/T cells can make powerful connections with cortical pyramidal cells, and coincident input from few M/T cells is sufficient to elicit spike output. These findings suggest that odor coding is broad and distributed in olfactory cortex.     

State-dependent sensory gating in olfactory cortex

Sensory systems show behavioral state-dependent gating of information flow that largely depends on the thalamus. Here we examined whether the state-dependent gating occurs in the central olfactory pathway that lacks a thalamic relay. In urethane-anesthetized rats, neocortical EEG showed a periodical alternation between two states: a slow-wave state (SWS) characterized by large and slow waves and a fast-wave state (FWS) characterized by faster waves. Single-unit recordings from olfactory cortex neurons showed robust spike responses to adequate odorants during FWS, whereas they showed only weak responses during SWS. The state-dependent change in odorant-evoked responses was observed in a majority of olfactory cortex neurons, but in only a small percentage of olfactory bulb neurons. These findings demonstrate a powerful state-dependent gating of odor information in the olfactory cortex that works in synchrony with the gating of other sensory systems. They suggest a state-dependent switchover of signal processing modes in the olfactory cortex.     

Interhemispheric olfactory circuit and the memory beyond

In mammals, olfactory sensory neurons project their axons exclusively to the ipsilateral olfactory bulb. It remains unclear how odor information interacts between the two hemispheres of the brain. In this issue of Neuron, Yan et al. describe the precise interbulbar connection through the anterior olfactory nucleus pars externa (AONpE), which links contralateral isotypic olfactory columns.     

Analysis of the Lynch-Granger model for olfactory cortex

The behavior of the Lynch-Granger model for layer-II piriform cortex is reviewed, and a simple neural model with similar properties is introduced. This model allows us to understand the observed functionality of the Lynch-Granger model intuitively, and suggests which of the many biological facts introduced into the original model are relevant to this particular behavior.     

Bursting activity in visual neurons of the cat cortex during pattern detection

The time course of neuronal response to presentation of a static flashing slit at different angles and both light spots and light strips moving in different directions was investigated in the Clare-Bishop area of the cat cortex. It was found that orientational and directional tuning patterns were mainly determined by the bursting constituent of the response and could be measured according to the number of spikes per burst or the actual number of bursts. A closed-loop model for pattern detection is introduced to shed light on bursting activity.V. Kapsuko State University, Vil'nius. Translated from Neirofiziologiya, Vol. 19, No. 3, pp. 335–343, May–June, 1987.