Competing neural responses for auditory and visual decisions

Why is it hard to divide attention between dissimilar activities, such as reading and listening to a conversation? We used functional magnetic resonance imaging (fMRI) to study interference between simple auditory and visual decisions, independently of motor competition. Overlapping activity for auditory and visual tasks performed in isolation was found in lateral prefrontal regions, middle temporal cortex and parietal cortex. When the visual stimulus occurred during the processing of the tone, its activation in prefrontal and middle temporal cortex was suppressed. Additionally, reduced activity was seen in modality-specific visual cortex. These results paralleled impaired awareness of the visual event. Even without competing motor responses, a simple auditory decision interferes with visual processing on different neural levels, including prefrontal cortex, middle temporal cortex and visual regions.     

Candidate neural locus for sex differences in reproductive decisions

Sexual selection and signal detection theories predict that females should be selective in their responses to mating signals in mate choice, while the response of males to signals in male competition should be less selective. The neural processes underlying this behavioural sex difference remain obscure. Differences in behavioural selectivity could result from differences in how sensitive sensory systems are to mating signals, distinct thresholds in motor areas regulating behaviour, or sex differences in selectivity at a gateway relaying sensory information to motor systems. We tested these hypotheses in frogs using the expression of egr-1 to quantify the neural responses of each sex to mating signals. We found that egr-1 expression in a midbrain auditory region was elevated in males in response to both conspecific and heterospecific calls, whereas in females, egr-1 induction occurred only in response to conspecific signals. This differential neural selectivity mirrored the sex differences in behavioural responsiveness to these stimuli. By contrast, egr-1 expression in lower brainstem auditory centres was not different in males and females. Our results support a model in which sex differences in behavioural selectivity arise from sex differences in the neural selectivity in midbrain areas relaying sensory information to the forebrain.     

A new neural framework for visuospatial processing

The division of cortical visual processing into distinct dorsal and ventral streams is a key framework that has guided visual neuroscience. The characterization of the ventral stream as a 'What' pathway is relatively uncontroversial, but the nature of dorsal stream processing is less clear. Originally proposed as mediating spatial perception ('Where'), more recent accounts suggest it primarily serves non-conscious visually guided action ('How'). Here, we identify three pathways emerging from the dorsal stream that consist of projections to the prefrontal and premotor cortices, and a major projection to the medial temporal lobe that courses both directly and indirectly through the posterior cingulate and retrosplenial cortices. These three pathways support both conscious and non-conscious visuospatial processing, including spatial working memory, visually guided action and navigation, respectively.     

A neural network for processing olfactory-like stimuli

Several critical issues associated with the processing of olfactory stimuli in animals (but focusing on insects) are discussed with a view to designing a neural network which can process olfactory stimuli. This leads to the construction of a neural network that can learn and identify the quality (direction cosines) of an input vector or extract information from a sequence of correlated input vectors, where the latter corresponds to sampling a time varying olfactory stimulus (or other generically similar pattern recognition problems). The network is constructed around a discrete time content-addressable memory (CAM) module which basically satisfies the Hopfield equations with the addition of a unit time delay feedback. This modification improves the convergence properties of the network and is used to control a switch which activates the learning or template formation process when the input is “unknown”. The network dynamics are embedded within a sniff cycle which includes a larger time delay (i.e. an integert _s <1) that is also used to control the template formation switch. In addition, this time delay is used to modify the input into the CAM module so that the more dominant of two mingling odors or an odor increasing against a background of odors is more readily identified. The performance of the network is evaluated using Monte Carlo simulations and numerical results are presented.     

Dissecting neural circuits for multisensory integration and crossmodal processing

We rely on rich and complex sensory information to perceive and understand our environment. Our multisensory experience of the world depends on the brain''s remarkable ability to combine signals across sensory systems. Behavioural, neurophysiological and neuroimaging experiments have established principles of multisensory integration and candidate neural mechanisms. Here we review how targeted manipulation of neural activity using invasive and non-invasive neuromodulation techniques have advanced our understanding of multisensory processing. Neuromodulation studies have provided detailed characterizations of brain networks causally involved in multisensory integration. Despite substantial progress, important questions regarding multisensory networks remain unanswered. Critically, experimental approaches will need to be combined with theory in order to understand how distributed activity across multisensory networks collectively supports perception.     

Reinforcement learning with internal expectation in the random neural networks for cascaded decisions

The reinforcement learning scheme proposed in Halici (J. Biosystems 40 (1997) 83) for the random neural network (RNN) (Neural Computation 1 (1989) 502) is based on reward and performs well for stationary environments. However, when the environment is not stationary it suffers from getting stuck to the previously learned action and extinction is not possible. To overcome the problem, the reinforcement scheme is extended in Halici (Eur. J. Oper. Res., 126(2000) 288) by introducing a new weight update rule (E-rule) which takes into consideration the internal expectation of reinforcement. Although the E-rule is proposed for the RNN, it can be used for training learning automata or other intelligent systems based on reinforcement learning. This paper looks into the behavior of the learning scheme with internal expectation for the environments where the reinforcement is obtained after a sequence of cascaded decisions. The simulation results have shown that the RNN learns well and extinction is possible even for the cases with several decision steps and with hundreds of possible decision paths.     

An inverse problem in neural processing

Any neural network aimed at the coding sensory events must contain computational properties which generally allow the organism to reconstruct the input signals with some degree of accuracy-else the association between stimulus and response would, at best, be uncertain. In this paper we investigate the problem of reconstructing external input signals to neural networks when the activity profiles of only some of its member cells are known. The evolution and activities of such cells are defined by an earlier formulation of one of us (Ouztöreli 1979) and, here, we restrict our application to local curcuits within the vertebrate retina. Solutions to this inverse coding problem are presented for specific network equations and examplified with 1, 3, and 5 neuron cases.This work was partially supported by the Natural Sciences and Engineering Research Council of Canada under Grant A-4345 to M.N.O. and grant A-4395 to T.M.C. through the University of Alberta     

Histochemical Methods for Dissociated Muscle Fibers

Skeletal or cardiac muscle fibers can be separated by brief (3-5 second) dissociation of formalin-fixed pieces with a Willems Polytron (Brinkmann Instrument Co.). Such separated fibers are useful for demonstration of abnormal accumulations of lipids, carbohydrates, proteins and minerals in metabolic diseases. Staining techniques for demonstration of various stored materials include: 1) toluidine blue at pH 2.8 for acid mucopolysaccharide in skeletal muscle fibers in Pompe's glycogenesis 2,2) one-step trichrome stain for nemaline myopathy and for abnormal mitochondria in X-linked infantile cardiomyopathy, 3) periodic acid-methenamine silver stain for glycolipid-containing lysosomes in I-cell disease (mucolipidosis 2), 4) Sudan black B stain for lipid in skeletal muscle fibers in Reye's syndrome, infantile lactic acidosis, Leigh's infantile subacute necrotizing encephalopathy and Jansky-Bielschowsky late infantile ceroid lipofuscinosis, 5) iron stain for iron in cardiac and skeletal muscle fibers in thalassemia with advanced hemosiderosis, and 6) autofluorescence for “ceroid” in skeletal muscle fibers in Jansky-Bielschowsky disease.     

The dorsal neural tube: A dynamic setting for cell fate decisions

The dorsal neural tube first generates neural crest cells that exit the neural primordium following an epithelial‐to‐mesenchymal conversion to become sympathetic ganglia, Schwann cells, dorsal root sensory ganglia, and melanocytes of the skin. Following the end of crest emigration, the dorsal midline of the neural tube becomes the roof plate, a signaling center for the organization of dorsal neuronal cell types. Recent lineage analysis performed before the onset of crest delamination revealed that the dorsal tube is a highly dynamic region sequentially traversed by fate‐restricted crest progenitors. Furthermore, prospective roof plate cells were shown to originate ventral to presumptive crest and to progressively relocate dorsalward to occupy their definitive midline position following crest delamination. These data raise important questions regarding the mechanisms of cell emigration in relation to fate acquisition, and suggest the possibility that spatial and/or temporal information in the dorsal neural tube determines initial segregation of neural crest cells into their derivatives. In addition, they emphasize the need to address what controls the end of neural crest production and consequent roof plate formation, a fundamental issue for understanding the separation between central and peripheral lineages during development of the nervous system. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 70: 796–812, 2010.     

Dissociated Learning in Animals

This brief paper gives a very clear demonstration of a phenomenon of considerable interest to American researchers on memory and the nature of the brain. In addition to demonstrating clearly the effect of dissociated learning, the authors point to many areas in which the principle of dissociated learning may be applied.     

A neural network reflecting decisions about human faces.

Anatomic structures have been linked to the mnemonic component of working memory, but the neural network underlying associated decision processes remains elusive. Here we present an event-related functional magnetic resonance imaging study that measured activity during the decision period of a delayed face recognition task. A double dissociation of activity between anterior cingulate cortex (ACC), and a network including left fusiform face area (FFA) and left dorsolateral prefrontal cortex (DLPFC), reflected whether a probe face matched the remembered face at the time of decision. Greater activity in the left FFA and left DLPFC correlated with probe faces that matched the remembered face; in contrast, activity in ACC was greater when the probe face did not match the remembered face. These results support a model where frontal regions act in concert with stimulus-specific temporal structures to make recognition decisions about visual stimuli.     

Cell-intrinsic and cell-extrinsic cues regulating lineage decisions in multipotent neural crest-derived progenitor cells

Multipotent stem cells must generate various differentiated cell types in correct number and sequence during neural development. In the peripheral nervous system (PNS), this involves the formation of postmigratory progenitor cell types which maintain multipotency and are able to give rise to neural and non-neural cells in response to instructive growth factors. We propose that fate restrictions in such progenitor cells are controlled by the combinatorial interaction of different extracellular signals, including community effects in response to both neurogenic and gliogenic factors. In addition, distinct progenitor cell types display intrinsic differences which modulate their response to the extracellular environment. Thus, a progenitor cell is apparently able to integrate multiple intrinsic and extrinsic cues and thereby to choose fates appropriate for its location. Fate analysis of genetically modified progenitor cells will help to identify the molecules involved. This approach appears promising given the identification of multipotent progenitor cells from the mouse PNS and the availability of genetics in the mouse system.     

Notch signaling regulates neural precursor allocation and binary neuronal fate decisions in zebrafish

Notch signaling plays a well-described role in regulating the formation of neurons from proliferative neural precursors in vertebrates but whether, as in flies, it also specifies sibling cells for different neuronal fates is not known. Ventral spinal cord precursors called pMN cells produce mostly motoneurons and oligodendrocytes, but recent lineage-marking experiments reveal that they also make astrocytes, ependymal cells and interneurons. Our own clonal analysis of pMN cells in zebrafish showed that some produce a primary motoneuron and KA' interneuron at their final division. We investigated the possibility that Notch signaling regulates a motoneuron-interneuron fate decision using a combination of mutant, transgenic and pharmacological manipulations of Notch activity. We show that continuous absence of Notch activity produces excess primary motoneurons and a deficit of KA' interneurons, whereas transient inactivation preceding neurogenesis results in an excess of both cell types. By contrast, activation of Notch signaling at the neural plate stage produces excess KA' interneurons and a deficit of primary motoneurons. Furthermore, individual pMN cells produce similar kinds of neurons at their final division in mib mutant embryos, which lack Notch signaling. These data provide evidence that, among some postmitotic daughters of pMN cells, Notch promotes KA' interneuron identity and inhibits primary motoneuron fate, raising the possibility that Notch signaling diversifies vertebrate neuron type by mediating similar binary fate decisions.     

Sensory processing by neural circuits in Caenorhabditis elegans

The anatomical and developmental constancy of Caenorhabditis elegans belies the complexity of its numerically small nervous system. Indeed, there is an increased appreciation of C. elegans as an organism to study systems level questions. Many recent studies focus on the circuits that control locomotion, egg-laying, and male mating behaviors and their modulation by multiple sensory stimuli.     

Sensorimotor integration in speech processing: computational basis and neural organization

Sensorimotor integration is an active domain of speech research and is characterized by two main ideas, that the auditory system is critically involved in speech production and that the motor system is critically involved in speech perception. Despite the complementarity of these ideas, there is little crosstalk between these literatures. We propose an integrative model of the speech-related "dorsal stream" in which sensorimotor interaction primarily supports speech production, in the form of a state feedback control architecture. A critical component of this control system is forward sensory prediction, which affords a natural mechanism for limited motor influence on perception, as recent perceptual research has suggested. Evidence shows that this influence is modulatory but not necessary for speech perception. The neuroanatomy of the proposed circuit is discussed as well as some probable clinical correlates including conduction aphasia, stuttering, and aspects of schizophrenia.     

The neural basis of first and second language processing

Fundamental breakthroughs in the neurosciences, combined with technical innovations for measuring brain activity, are shedding new light on the neural basis of second language (L2) processing, and on its relationship to native language processing (L1). The long-held assumption that L1 and L2 are necessarily represented in different brain regions in bilinguals has not been confirmed. On the contrary, the available evidence indicates that L1 and L2 are processed by the same neural devices. The neural differences in L1 and L2 representations are only related to the specific computational demands, which vary according to the age of acquisition, the degree of mastery and the level of exposure to each language. Finally, the acquisition of L2 could be considered as a dynamic process, requiring additional neural resources in specific circumstances.     

A comparative analysis of neural taste processing in animals

Understanding taste processing in the nervous system is a fundamental challenge of modern neuroscience. Recent research on the neural bases of taste coding in invertebrates and vertebrates allows discussion of whether labelled-line or across-fibre pattern encoding applies to taste perception. While the former posits that each gustatory receptor responds to one stimulus or a very limited range of stimuli and sends a direct 'line' to the central nervous system to communicate taste information, the latter postulates that each gustatory receptor responds to a wider range of stimuli so that the entire population of taste-responsive neurons participates in the taste code. Tastes are represented in the brain of the fruitfly and of the rat by spatial patterns of neural activity containing both distinct and overlapping regions, which are in accord with both labelled-line and across-fibre pattern processing of taste, respectively. In both animal models, taste representations seem to relate to the hedonic value of the tastant (e.g. palatable versus non-palatable). Thus, although the labelled-line hypothesis can account for peripheral taste processing, central processing remains either unknown or differs from a pure labelled-line coding. The essential task for a neuroscience of taste is, therefore, to determine the connectivity of taste-processing circuits in central nervous systems. Such connectivity may determine coding strategies that differ significantly from both the labelled-line and the across-fibre pattern models.