The neural subjective frame: from bodily signals to perceptual consciousness

The report ‘I saw the stimulus’ operationally defines visual consciousness, but where does the ‘I’ come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness.     

Understanding the temporal codes of intra-cellular signals

The health of organisms and cells depends on appropriate responses to diverse internal and external cues, stimuli, or challenges, such as changes in hormone or cytokine levels, or exposure to a pathogen. Cellular responses must be tailored to the identity and intensity of the stimulus and therefore intra-cellular signals must carry information about both. However, signaling mediators often form intricate networks that react to multiple stimuli yet manage to produce stimulus-specific responses. The multi-functionality ('functional pleiotropism') of signaling nodes suggests that biological networks have evolved ways of passing physiologically relevant stimulus information through shared channels. Increasing evidence supports the notion that this is achieved in part through temporal regulation of signaling mediators' activities. The present challenge is to identify the features of temporal activity profile that represent information about a given stimulus and understand how cells read the temporal codes to control their responses.     

Otx2 is required to respond to signals from anterior neural ridge for forebrain specification

Previous analysis employing chimeric and transgenic rescue experiments has suggested that Otx2 is required in the neuroectoderm for development of the forebrain region. In order to elucidate the precise role of Otx2 in forebrain development, we attempted to generate an allelic series of Otx2 mutations by Flp- and Cre-mediated recombination for the production of conditional knock-out mice. Unexpectedly, the neo-cassette insertion created a hypomorphic Otx2 allele; consequently, the phenotype of compound mutant embryos carrying both a hypomorphic and a null allele (Otx2(frt-neo/-)) was analyzed. Otx2(frt-neo/-) mutant mice died at birth, displaying rostral head malformations. Molecular marker analysis demonstrated that Otx2(frt-neo/-) mutant embryos appeared to undergo anterior-posterior axis generation and induction of anterior neuroectoderm normally; however, these mutants subsequently failed to correctly specify the forebrain region. As the rostral margin of the neural plate, termed the anterior neural ridge (ANR), plays crucial roles with respect to neural plate specification, we examined expression of molecular markers for the ANR and the neural plate; moreover, neural plate explant studies were performed. Analyses revealed that telencephalic gene expression did not occur in mutant embryos due to defects of the neural plate; however, the mutant ANR bore normal induction activity on gene expression. These results further suggest that Otx2 dosage may be crucial in the neural plate with respect to response to inductive signals primarily from the ANR for forebrain specification.     

Explicit neural signals reflecting reward uncertainty

The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, depending on whether the probability distributions of outcomes are known or unknown. Behavioural neurophysiological studies on dopamine neurons revealed a risk signal, which covaried with the standard deviation or variance of the magnitude of juice rewards and occurred separately from reward value coding. Human imaging studies identified similarly distinct risk signals for monetary rewards in the striatum and orbitofrontal cortex (OFC), thus fulfilling a requirement for the mean variance approach of economic decision theory. The orbitofrontal risk signal covaried with individual risk attitudes, possibly explaining individual differences in risk perception and risky decision making. Ambiguous gambles with incomplete probabilistic information induced stronger brain signals than risky gambles in OFC and amygdala, suggesting that the brain's reward system signals the partial lack of information. The brain can use the uncertainty signals to assess the uncertainty of rewards, influence learning, modulate the value of uncertain rewards and make appropriate behavioural choices between only partly known options.     

Towards energy-efficient parallel analysis of neural signals

Recent advances of experimental methods and neuroscience research have made neural signals constantly massive and analysis of these signals highly compute-intensive. This study explore the possibility proposes a massively parallel approach for analysis of neural signals using General-purpose computing on the graphics processing unit (GPGPU). We demonstrate the uses and correctness of the proposed approach via a case of analyzing EEG with focal epilepsy. An experimental examination has been carried out to investigate (1) the GPGPU-aided approach’s performance and (2) energy costs of the GPGPU-aided application versus the original CPU-only systems. Experimental results indicate that the proposed approach excels in both aspects.     

Metabolic rate estimates for a eutrophic lake from diel dissolved oxygen signals

Estimates of net primary production, community respiration (R'), and gross primary production (P_g) are developed and presented for the productive layers of eutrophic Onondaga Lake, NY, U.S.A., for time scales ranging from diel to several months, based on 4 months of robotic diel profiles of dissolved oxygen (DO) and temperature. Metabolic rate calculations are made through application of a DO mass balance framework that also accommodates inputs and losses of DO mediated by exchange across the air–water interface and across the lower boundary of the productive layers. It is demonstrated that the dynamics of the flux across the air–water interface are important to the metabolic rate estimates, while vertical mixing-based losses to the underlying layers can be ignored. Study average estimates of R' (1.49 g O₂ m^–3 d^–1) and P_g (1.60 g O₂ m^–3 d^–1) obtained by this non-isolated community approach are consistent with levels reported in the literature for similar chlorophyll a concentrations, based on isolated community (bottle experiment) protocols to measure these metabolic rates. The non-isolated community approach is shown to have limited utility for quantifying day-to-day changes in these rates in this lake, apparently because of horizontal exchange with waters of different DO concentrations. However, this approach may support reliable estimates of metabolic rates at intermediate time scales; e.g., several days to a week. The DO mass balance framework is demonstrated to be valuable in resolving the relative roles of various physical and biological processes in regulating the DO pool of the productive layers.     

Ensemble place codes in hippocampus: CA1, CA3, and dentate gyrus place cells have multiple place fields in large environments

Previously we reported that the hippocampus place code must be an ensemble code because place cells in the CA1 region of hippocampus have multiple place fields in a more natural, larger-than-standard enclosure with stairs that permitted movements in 3-D. Here, we further investigated the nature of hippocampal place codes by characterizing the spatial firing properties of place cells in the CA1, CA3, and dentate gyrus (DG) hippocampal subdivisions as rats foraged in a standard 76-cm cylinder as well as a larger-than-standard box (1.8 m×1.4 m) that did not have stairs or any internal structure to permit movements in 3-D. The rats were trained to forage continuously for 1 hour using computer-controlled food delivery. We confirmed that most place cells have single place fields in the standard cylinder and that the positional firing pattern remapped between the cylinder and the large enclosure. Importantly, place cells in the CA1, CA3 and DG areas all characteristically had multiple place fields that were irregularly spaced, as we had reported previously for CA1. We conclude that multiple place fields are a fundamental characteristic of hippocampal place cells that simplifies to a single field in sufficiently small spaces. An ensemble place code is compatible with these observations, which contradict any dedicated coding scheme.     

A proposed mechanism for multiplication of neural signals

The probability of the joint occurrence of two statistically independent events is the product of the probabilities of the individual events. This fact is used to show that a neuron which detects coincident arrivals of spikes from two input neurons can function as a multiplier, i.e. its average output spike frequency is proportional to the product of the average input spike frequencies. The theoretical analysis is checked in two ways: (a) Computer simulations confirm the derived expressions for the output frequency and show that increasing the jitter in the input spike trains improves the operation of the multiplier by making the output spike train more regular (b) Experimentally recorded spike trains are used to demonstrate that the type and amount of jitter present in real spike trains is adequate for satisfactory operation of the proposed scheme for multiplication. The operating characteristics of the proposed multiplier make it an attractive candidate for the multiplicative mechanism that is involved in the optomotor response of insects.     

Drosophila perlecan modulates FGF and hedgehog signals to activate neural stem cell division

Mutations in the Drosophila trol gene cause cell cycle arrest of neuroblasts in the larval brain. Here, we show that trol encodes the Drosophila homolog of Perlecan and regulates neuroblast division by modulating both FGF and Hh signaling. Addition of human FGF-2 to trol mutant brains in culture rescues the trol proliferation phenotype, while addition of a MAPK inhibitor causes cell cycle arrest of the regulated neuroblasts in wildtype brains. Like FGF, Hh activates stem cell division in the larval brain in a Trol-dependent fashion. Coimmunoprecipitation studies are consistent with interactions between Trol and Hh and between mammalian Perlecan and Shh that are not competed with heparin sulfate. Finally, analyses of mutations in trol, hh, and ttv suggest that Trol affects Hh movement. These results indicate that Trol can mediate signaling through both of the FGF and Hedgehog pathways to control the onset of stem cell proliferation in the developing nervous system.     

Converting the guanine phosphoribosyltransferase from Giardia lamblia to a hypoxanthine-guanine phosphoribosyltransferase

Guanine phosphoribosyltransferase from Giardia lamblia, a key enzyme in the purine salvage pathway, is a potential target for anti-giardiasis chemotherapy. Recent structural determination of GPRTase (Shi, W., Munagala, N. R., Wang, C. C., Li, C. M., Tyler, P. C., Furneaux, R. H., Grubmeyer, C., Schramm, V. L., and Almo, S. C. (2000) Biochemistry 39, 6781-6790) showed distinctive features, which could be responsible for its singular guanine specificity. Through characterizing specifically designed site-specific mutants of GPRTase, we identified essential moieties in the active site for substrate binding. Mutating the unusual Tyr-127 of GPRTase to the highly conserved Ile results in 6-fold lower K(m) for guanine. A L186F mutation in GPRTase increased the affinity toward guanine by 3. 3-fold, whereas the corresponding human HGPRTase mutant L192F showed a 33-fold increase in K(m) for guanine. A double mutant (Y127I/K152R) of GPRTase retained the improved binding of guanine and also enabled the enzyme to utilize hypoxanthine as a substrate with a K(m) of 54 +/- 15.5 microm. A triple mutant (Y127I/K152R/L186F) resulted in further increased binding affinity with both guanine and hypoxanthine with the latter showing a lowered K(m) of 29.8 +/- 4.1 microm. Dissociation constants measured by fluorescence quenching showed 6-fold tighter binding of GMP with the triple mutant compared with wild type. Thus, by increasing the binding affinity of 6-oxopurine, we were able to convert the GPRTase to a HGPRTase.     

Bitter taste stimuli induce differential neural codes in mouse brain

A growing literature suggests taste stimuli commonly classified as bitter induce heterogeneous neural and perceptual responses. Here, the central processing of bitter stimuli was studied in mice with genetically controlled bitter taste profiles. Using these mice removed genetic heterogeneity as a factor influencing gustatory neural codes for bitter stimuli. Electrophysiological activity (spikes) was recorded from single neurons in the nucleus tractus solitarius during oral delivery of taste solutions (26 total), including concentration series of the bitter tastants quinine, denatonium benzoate, cycloheximide, and sucrose octaacetate (SOA), presented to the whole mouth for 5 s. Seventy-nine neurons were sampled; in many cases multiple cells (2 to 5) were recorded from a mouse. Results showed bitter stimuli induced variable gustatory activity. For example, although some neurons responded robustly to quinine and cycloheximide, others displayed concentration-dependent activity (p<0.05) to quinine but not cycloheximide. Differential activity to bitter stimuli was observed across multiple neurons recorded from one animal in several mice. Across all cells, quinine and denatonium induced correlated spatial responses that differed (p<0.05) from those to cycloheximide and SOA. Modeling spatiotemporal neural ensemble activity revealed responses to quinine/denatonium and cycloheximide/SOA diverged during only an early, at least 1 s wide period of the taste response. Our findings highlight how temporal features of sensory processing contribute differences among bitter taste codes and build on data suggesting heterogeneity among bitter stimuli, data that challenge a strict monoguesia model for the bitter quality.     

Effects of the synaptic transmission's dynamics on possible neural codes

To examine the effects of paired pulse facilitation, long-term synaptic modifications as well as spike frequency adaptation on neural signal transmission, a simple model was applied. This way various input-output properties of the model units were described. Particularly, the transmission of the mean and S.D. of the simulated synaptic currents were studied. The results indicate that the transfer of the mean value of the membrane currents cannot be described in terms of synaptic weights. So firing rate can hardly be an efficient neural code, especially for adaptive channels of the central nervous system (CNS). On the contrary, the transfer of S.D. of synaptic currents behaves in accordance with the synaptic weights. So it is supported that S.D. of the synaptic currents is a biological relevant subclass of the variation codes [see Perkel, H., Bullock, T.H., 1968. Neurol coding. Neurosci. Res. Program Bull. 6, 221-344]. It is discussed how this code can be established and how it works.     

Neuronal specification in the spinal cord: inductive signals and transcriptional codes

Neural circuits are assembled with remarkable precision during embryonic development, and the selectivity inherent in their formation helps to define the behavioural repertoire of the mature organism. In the vertebrate central nervous system, this developmental program begins with the differentiation of distinct classes of neurons from progenitor cells located at defined positions within the neural tube. The mechanisms that specify the identity of neural cells have been examined in many regions of the nervous system and reveal a high degree of conservation in the specification of cell fate by key signalling molecules.