Spontaneous emergence of fast attractor dynamics in a model of developing primary visual cortex.

Recent evidence suggests that neurons in primary sensory cortex arrange into competitive groups, representing stimuli by their joint activity rather than as independent feature analysers. A possible explanation for these results is that sensory cortex implements attractor dynamics, although this proposal remains controversial. Here we report that fast attractor dynamics emerge naturally in a computational model of a patch of primary visual cortex endowed with realistic plasticity (at both feedforward and lateral synapses) and mutual inhibition. When exposed to natural images (but not random pixels), the model spontaneously arranges into competitive groups of reciprocally connected, similarly tuned neurons, while developing realistic, orientation-selective receptive fields. Importantly, the same groups are observed in both stimulus-evoked and spontaneous (stimulus-absent) activity. The resulting network is inhibition-stabilized and exhibits fast, non-persistent attractor dynamics. Our results suggest that realistic plasticity, mutual inhibition and natural stimuli are jointly necessary and sufficient to generate attractor dynamics in primary sensory cortex.

Imagery May Arise from Associations Formed through Sensory Experience: A Network of Spiking Neurons Controlling a Robot Learns Visual Sequences in Order to Perform a Mental Rotation Task.

Mental imagery occurs "when a representation of the type created during the initial phases of perception is present but the stimulus is not actually being perceived." How does the capability to perform mental imagery arise? Extending the idea that imagery arises from learned associations, we propose that mental rotation, a specific form of imagery, could arise through the mechanism of sequence learning-that is, by learning to regenerate the sequence of mental images perceived while passively observing a rotating object. To demonstrate the feasibility of this proposal, we constructed a simulated nervous system and embedded it within a behaving humanoid robot. By observing a rotating object, the system learns the sequence of neural activity patterns generated by the visual system in response to the object. After learning, it can internally regenerate a similar sequence of neural activations upon briefly viewing the static object. This system learns to perform a mental rotation task in which the subject must determine whether two objects are identical despite differences in orientation. As with human subjects, the time taken to respond is proportional to the angular difference between the two stimuli. Moreover, as reported in humans, the system fills in intermediate angles during the task, and this putative mental rotation activates the same pathways that are activated when the system views physical rotation. This work supports the proposal that mental rotation arises through sequence learning and the idea that mental imagery aids perception through learned associations, and suggests testable predictions for biological experiments.

Reentry: a key mechanism for integration of brain function.

Reentry in nervous systems is the ongoing bidirectional exchange of signals along reciprocal axonal fibers linking two or more brain areas. The hypothesis that reentrant signaling serves as a general mechanism to couple the functioning of multiple areas of the cerebral cortex and thalamus was first proposed in 1977 and 1978 (Edelman, 1978). A review of the amount and diversity of supporting experimental evidence accumulated since then suggests that reentry is among the most important integrative mechanisms in vertebrate brains (Edelman, 1993). Moreover, these data prompt testable hypotheses regarding mechanisms that favor the development and evolution of reentrant neural architectures.

Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device.

Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

Versatile networks of simulated spiking neurons displaying winner-take-all behavior.

We describe simulations of large-scale networks of excitatory and inhibitory spiking neurons that can generate dynamically stable winner-take-all (WTA) behavior. The network connectivity is a variant of center-surround architecture that we call center-annular-surround (CAS). In this architecture each neuron is excited by nearby neighbors and inhibited by more distant neighbors in an annular-surround region. The neural units of these networks simulate conductance-based spiking neurons that interact via mechanisms susceptible to both short-term synaptic plasticity and STDP. We show that such CAS networks display robust WTA behavior unlike the center-surround networks and other control architectures that we have studied. We find that a large-scale network of spiking neurons with separate populations of excitatory and inhibitory neurons can give rise to smooth maps of sensory input. In addition, we show that a humanoid brain-based-device (BBD) under the control of a spiking WTA neural network can learn to reach to target positions in its visual field, thus demonstrating the acquisition of sensorimotor coordination.

Physical evidence supporting a ribosomal shunting mechanism of translation initiation for BACE1 mRNA.

In Alzheimer disease, elevated levels of the BACE1 enzyme are correlated with increased production of amyloid peptides and disease pathology. The increase in BACE1 levels is post-transcriptional and may involve altered translation efficiency. Earlier studies have indicated that translation of BACE1 mRNA is cap-dependent. As ribosomal subunits move from the cap-structure to the initiation codon, they fail to recognize several AUG codons in the 5' leader. In this study, we looked for physical evidence of the mechanism underlying ribosomal scanning or shunting along the BACE1 5' leader by investigating structural stability in the 5' leaders of endogenous mRNAs in vivo. To perform this analysis, we probed RNAs using lead(II) acetate, a cell-permeable chemical that induces cleavage of unpaired nucleotides having conformational flexibility. The data revealed that the ≈440-nt 5' leader was generally resistant to cleavage except for a region upstream of the initiation codon. Cleavage continued into the coding region, consistent with destabilization of secondary structures by translating ribosomes. Evidence that a large segment of the BACE1 5' leader was not cleaved indicates that this region is structurally stable and suggests that it is not scanned. The data support a mechanism of translation initiation in which ribosomal subunits bypass (shunt) part of the BACE1 5' leader to reach the initiation codon. We suggest that a nucleotide bias in the 5' leader may predispose the initiation codon to be more accessible than other AUG codons in the 5' leader, leading to an increase in its relative utilization.

Biology of consciousness.

The Dynamic Core and Global Workspace hypotheses were independently put forward to provide mechanistic and biologically plausible accounts of how brains generate conscious mental content. The Dynamic Core proposes that reentrant neural activity in the thalamocortical system gives rise to conscious experience. Global Workspace reconciles the limited capacity of momentary conscious content with the vast repertoire of long-term memory. In this paper we show the close relationship between the two hypotheses. This relationship allows for a strictly biological account of phenomenal experience and subjectivity that is consistent with mounting experimental evidence. We examine the constraints on causal analyses of consciousness and suggest that there is now sufficient evidence to consider the design and construction of a conscious artifact.

Developmentally regulated expression of the cold-inducible RNA-binding motif protein 3 in euthermic rat brain.

mRNA-binding proteins are critical regulators of protein synthesis during neural development. We demonstrated previously that the cold-inducible mRNA-binding protein 3 (RBM3) is present within euthermic neurons and that it enhances translation. Other studies have attributed anti-apoptotic and proliferative functions to RBM3. Here we characterize the developmental expression of RBM3 in rat brain. RBM3 is expressed widely during early brain development, peaking in the first to second postnatal weeks. This is followed by a decline in most brain regions and a shift from a nuclear to a more somatodendritic distribution by approximately P13. The highest levels of RBM3 in adult brain were observed in the cerebellum, olfactory bulb, proliferating cell fields and other regions reported to have high translation rates. RBM3 was expressed in glutamatergic and GABAergic cells, subtypes of which exhibited strong dendritic labeling for RBM3 mRNA and protein. Expression of RBM3 was also high in newly formed and migrating neurons marked by Ki67, nestin, and doublecortin, such as those in the subventricular zone and rostral migratory stream. These results indicate that expression of RBM3, a cold stress-responsive mRNA-binding protein, is dynamically regulated in the developing brain and suggest that it contributes to translation-dependent processes underlying proliferation, differentiation, and plasticity.

Caffeine stimulates cytochrome oxidase expression and activity in the striatum in a sexually dimorphic manner.

Epidemiological studies indicate that caffeine consumption reduces the risk of Parkinson's disease (PD) in men, and antagonists of the adenosine 2A receptor ameliorate the motor symptoms of PD. These findings motivated us to identify proteins whose expression is regulated by caffeine in a sexually dimorphic manner. Using mass spectroscopy, we found that Cox7c, a nuclear-encoded subunit of the mitochondrial enzyme cytochrome oxidase, is up-regulated in the striatum of male but not female mice after receiving a single dose of caffeine. The expression of two other Cox subunits, Cox1 and Cox4, was also stimulated by caffeine in a male-specific fashion. This up-regulation of Cox subunits by caffeine was accompanied by an increase in Cox enzyme activity in the male striatum. Caffeine-induced stimulation of Cox expression and activity were reproduced using the adenosine 2A receptor (A2AR)-specific antagonist 5-amino-7-(2-phenylethyl)-2-(2-furyl)-pyrazolo[4,3-epsilon]-1,2,4-triazolo[1,5-c]pyrimidine (SCH58261), and coadministration of the A2AR-specific agonist 2-[p-(2-carboxyethyl)phenethylamino]-5'-N-ethylcarboxamidoadenosine (CGS21680) counteracted the elevation of Cox expression and activity by caffeine. Caffeine also increased Cox activity in PC-12 cells. In contrast, small interfering RNA (siRNA) knockdown of Cox7c expression in PC-12 cells blunted Cox activity, and this was counteracted by caffeine treatment. Caffeine was also found to increase Cox7c mRNA expression in the striatum and in PC-12 cells. This occurred at the level of transcription and was mediated by a segment of the Cox7c promoter. Overall, these findings indicate that cytochrome oxidase is a metabolic target of caffeine and that stimulation of Cox activity by caffeine via blockade of A2AR signaling may be an important mechanism underlying the therapeutic benefits of caffeine in PD.

Embodied models of delayed neural responses: spatiotemporal categorization and predictive motor control in brain based devices.

In order to respond appropriately to environmental stimuli, organisms must integrate over time spatiotemporal signals that reflect object motion and self-movement. One possible mechanism to achieve this spatiotemporal transformation is to delay or lag neural responses. This paper reviews our recent modeling work testing the sufficiency of delayed responses in the nervous system in two different behavioral tasks: (1) Categorizing spatiotemporal tactile cues with thalamic "lag" cells and downstream coincidence detectors, and (2) Predictive motor control was achieved by the cerebellum through a delayed eligibility trace rule at cerebellar synapses. Since the timing of these neural signals must closely match real-world dynamics, we tested these ideas using the brain based device (BBD) approach in which a simulated nervous system is embodied in a robotic device. In both tasks, biologically inspired neural simulations with delayed neural responses were critical for successful behavior by the device.

Large-scale model of mammalian thalamocortical systems.

The understanding of the structural and dynamic complexity of mammalian brains is greatly facilitated by computer simulations. We present here a detailed large-scale thalamocortical model based on experimental measures in several mammalian species. The model spans three anatomical scales. (i) It is based on global (white-matter) thalamocortical anatomy obtained by means of diffusion tensor imaging (DTI) of a human brain. (ii) It includes multiple thalamic nuclei and six-layered cortical microcircuitry based on in vitro labeling and three-dimensional reconstruction of single neurons of cat visual cortex. (iii) It has 22 basic types of neurons with appropriate laminar distribution of their branching dendritic trees. The model simulates one million multicompartmental spiking neurons calibrated to reproduce known types of responses recorded in vitro in rats. It has almost half a billion synapses with appropriate receptor kinetics, short-term plasticity, and long-term dendritic spike-timing-dependent synaptic plasticity (dendritic STDP). The model exhibits behavioral regimes of normal brain activity that were not explicitly built-in but emerged spontaneously as the result of interactions among anatomical and dynamic processes. We describe spontaneous activity, sensitivity to changes in individual neurons, emergence of waves and rhythms, and functional connectivity on different scales.

Learning in and from brain-based devices.

Biologically based mobile devices have been constructed that differ from robots based on artificial intelligence. These brain-based devices (BBDs) contain simulated brains that autonomously categorize signals from the environment without a priori instruction. Two such BBDs, Darwin VII and Darwin X, are described here. Darwin VII recognizes objects and links categories to behavior through instrumental conditioning. Darwin X puts together the "what,""when," and "where" from cues in the environment into an episodic memory that allows it to find a desired target. Although these BBDs are designed to provide insights into how the brain works, their principles may find uses in building hybrid machines. These machines would combine the learning ability of BBDs with explicitly programmed control systems.

The ribosome filter redux.

The ribosome filter hypothesis postulates that ribosomes are not simply translation machines but also function as regulatory elements that differentially affect or filter the translation of particular mRNAs. On the basis of new information, we take the opportunity here to review the ribosome filter hypothesis, suggest specific mechanisms of action, and discuss recent examples from the literature that support it.

Distinguishing causal interactions in neural populations.

We describe a theoretical network analysis that can distinguish statistically causal interactions in population neural activity leading to a specific output. We introduce the concept of a causal core to refer to the set of neuronal interactions that are causally significant for the output, as assessed by Granger causality. Because our approach requires extensive knowledge of neuronal connectivity and dynamics, an illustrative example is provided by analysis of Darwin X, a brain-based device that allows precise recording of the activity of neuronal units during behavior. In Darwin X, a simulated neuronal model of the hippocampus and surrounding cortical areas supports learning of a spatial navigation task in a real environment. Analysis of Darwin X reveals that large repertoires of neuronal interactions contain comparatively small causal cores and that these causal cores become smaller during learning, a finding that may reflect the selection of specific causal pathways from diverse neuronal repertoires.

BDNF induces widespread changes in synaptic protein content and up-regulates components of the translation machinery: an analysis using high-throughput proteomics.

The brain-derived neurotrophic factor (BDNF) plays an important role in neuronal development, and in the formation and plasticity of synaptic connections. These effects of BDNF are at least partially due to the ability of the neurotrophin to increase protein synthesis both globally and locally. However, only a few proteins have been shown to be up-regulated at the synapse by BDNF. Using multidimensional protein identification technology (MudPIT) and relative quantification by spectra counting, we found that several hundred proteins are up-regulated in a synaptoneurosome preparation derived from cultured cortical neurons that were treated with BDNF. These proteins fall into diverse functional categories, including those involved in synaptic vesicle formation and movement, maintenance or remodeling of synaptic structure, mRNA processing, transcription, and translation. A number of translation factors, ribosomal proteins, and tRNA synthetases were rapidly up-regulated by BDNF. This up-regulation of translation components was sensitive to protein synthesis inhibitors and dependent on the activation of the mammalian target of rapamycin (mTOR), a regulator of cap-dependent mRNA translation. The presence of a subset of these proteins and their mRNAs in neuronal processes was corroborated by immunocytochemistry and in situ hybridization, and their up-regulation was confirmed by Western blotting. The data demonstrate that BDNF increases the synthesis of a wide variety of synaptic proteins and suggest that the neurotrophin may enhance the translational capacity of synapses.

Retrospective and prospective responses arising in a modeled hippocampus during maze navigation by a brain-based device.

Recent recordings of place field activity in rodent hippocampus have revealed correlates of current, recent past, and imminent future events in spatial memory tasks. To analyze these properties, we used a brain-based device, Darwin XI, that incorporated a detailed model of medial temporal structures shaped by experience-dependent synaptic activity. Darwin XI was tested on a plus maze in which it approached a goal arm from different start arms. In the task, a journey corresponded to the route from a particular starting point to a particular goal. During maze navigation, the device developed place-dependent responses in its simulated hippocampus. Journey-dependent place fields, whose activity differed in different journeys through the same maze arm, were found in the recordings of simulated CA1 neuronal units. We also found an approximately equal number of journey-independent place fields. The journey-dependent responses were either retrospective, where activity was present in the goal arm, or prospective, where activity was present in the start arm. Detailed analysis of network dynamics of the neural simulation during behavior revealed that many different neural pathways could stimulate any single CA1 unit. That analysis also revealed that place activity was driven more by hippocampal and entorhinal cortical influences than by sensory cortical input. Moreover, journey-dependent activity was driven more strongly by hippocampal influence than journey-independent activity.

Ribosomal tethering and clustering as mechanisms for translation initiation.

Eukaryotic mRNAs often recruit ribosomal subunits some distance upstream of the initiation codon; however, the mechanisms by which they reach the initiation codon remain to be fully elucidated. Although scanning is a widely accepted model, evidence for alternative mechanisms has accumulated. We previously suggested that this process may involve tethering of ribosomal complexes to the mRNA, in which the intervening mRNA is bypassed, or clustering, in which the initiation codon is reached by dynamic binding and release of ribosomal subunits at internal sites. The present studies tested the feasibility of these ideas by using model mRNAs and revealed that translation efficiency varied with the distance between the site of ribosomal recruitment and the initiation codon. The present studies also showed that translation could initiate efficiently at AUG codons located upstream of an internal site. These observations are consistent with ribosomal tethering at the cap structure and clustering at internal sites.

Theories and measures of consciousness: an extended framework.

A recent theoretical emphasis on complex interactions within neural systems underlying consciousness has been accompanied by proposals for the quantitative characterization of these interactions. In this article, we distinguish key aspects of consciousness that are amenable to quantitative measurement from those that are not. We carry out a formal analysis of the strengths and limitations of three quantitative measures of dynamical complexity in the neural systems underlying consciousness: neural complexity, information integration, and causal density. We find that no single measure fully captures the multidimensional complexity of these systems, and all of these measures have practical limitations. Our analysis suggests guidelines for the specification of alternative measures which, in combination, may improve the quantitative characterization of conscious neural systems. Given that some aspects of consciousness are likely to resist quantification altogether, we conclude that a satisfactory theory is likely to be one that combines both qualitative and quantitative elements.

Ribosomal shunting mediated by a translational enhancer element that base pairs to 18S rRNA.

In eukaryotes, 40S ribosomal subunits move from their recruitment site on the mRNA to the initiation codon by an as yet poorly understood process. One postulated mechanism involves ribosomal shunting, in which ribosomal subunits completely bypass regions of the 5' leader. For some mRNAs, shunting has been shown to require various mRNA elements, some of which are thought to base pair to 18S rRNA; however, the role of base pairing has not yet been tested directly. In earlier studies, we demonstrated that a short mRNA element in the 5' leader of the Gtx homeodomain mRNA functioned as a ribosomal recruitment site by base pairing to the 18S rRNA. Using a model system to assess translation in transfected cells, we now show that this intermolecular interaction also facilitates ribosomal shunting across two types of obstacles: an upstream AUG codon in excellent context or a stable hairpin structure. Highly efficient shunting occurred when multiple Gtx elements were present upstream of the obstacles, and a single Gtx element was present downstream. Shunting was less efficient, however, when the multiple Gtx elements were present only upstream of the obstacles. In addition, control experiments with mRNAs lacking the upstream elements showed that these results could not be attributed to recruitment by the single downstream element. Experiments in yeast in which the mRNA elements and 18S rRNA sequences were both mutated indicated that shunting required an intact complementary match. The data obtained by this model system provide direct evidence that ribosomal shunting can be mediated by mRNA-rRNA base pairing, a finding that may have general implications for mechanisms of ribosome movement.

Single-trial discrimination of truthful from deceptive responses during a game of financial risk using alpha-band MEG signals.

We studied whether magnetoencephalography (MEG) could detect deceptive responses on a single-subject, trial-by-trial basis. To elicit spontaneous, ecologically valid deception, we developed a paradigm in which subjects in a simulated customs setting were presented with a series of pictures of items which might be in their baggage, and for each item, they decided whether to "declare" (tell the truth) or "smuggle" (lie). Telling the truth involved a small but certain monetary penalty, whereas lying involved both greater monetary risk and greater potential reward. Most subjects showed decreased signal power in the 8-12 Hz (alpha) range during deceptive responses as compared to truthful responses. In a cross-validation analysis, we were able to use alpha power to classify truthful and deceptive responses on a trial-by-trial basis, with significantly greater predictive accuracy than that achieved using simultaneously recorded skin conductance signals. Average predictive accuracy for spontaneous deception was greater than 78%, and for some subjects, predictive accuracy exceeded 90%. Our results raise the possibility that alpha power modulation during deception may reflect risk management and/or cognitive control.