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Guffanti, A, Simchovitz A, Soreq H.  2014.  Emerging bioinformatics approaches for analysis of NGS-derived coding and non-coding RNAs in neurodegenerative diseases.. Frontiers in cellular neuroscience. 8:89. Abstract
Neurodegenerative diseases in general and specifically late-onset Alzheimer's disease (LOAD) involve a genetically complex and largely obscure ensemble of causative and risk factors accompanied by complex feedback responses. The advent of "high-throughput" transcriptome investigation technologies such as microarray and deep sequencing is increasingly being combined with sophisticated statistical and bioinformatics analysis methods complemented by knowledge-based approaches such as Bayesian Networks or network and graph analyses. Together, such "integrative" studies are beginning to identify co-regulated gene networks linked with biological pathways and potentially modulating disease predisposition, outcome, and progression. Specifically, bioinformatics analyses of integrated microarray and genotyping data in cases and controls reveal changes in gene expression of both protein-coding and small and long regulatory RNAs; highlight relevant quantitative transcriptional differences between LOAD and non-demented control brains and demonstrate reconfiguration of functionally meaningful molecular interaction structures in LOAD. These may be measured as changes in connectivity in "hub nodes" of relevant gene networks (Zhang etal., 2013). We illustrate here the open analytical questions in the transcriptome investigation of neurodegenerative disease studies, proposing "ad hoc" strategies for the evaluation of differential gene expression and hints for a simple analysis of the non-coding RNA (ncRNA) part of such datasets. We then survey the emerging role of long ncRNAs (lncRNAs) in the healthy and diseased brain transcriptome and describe the main current methods for computational modeling of gene networks. We propose accessible modular and pathway-oriented methods and guidelines for bioinformatics investigations of whole transcriptome next generation sequencing datasets. We finally present methods and databases for functional interpretations of lncRNAs and propose a simple heuristic approach to visualize and represent physical and functional interactions of the coding and non-coding components of the transcriptome. Integrating in a functional and integrated vision coding and ncRNA analyses is of utmost importance for current and future analyses of neurodegenerative transcriptomes.
Rotem, N, Sestieri E, Hounsgaard J, Yarom Y.  2014.  Excitatory and inhibitory synaptic mechanisms at the first stage of integration in the electroreception system of the shark.. Frontiers in cellular neuroscience. 8:72. Abstract
High impulse rate in afferent nerves is a common feature in many sensory systems that serve to accommodate a wide dynamic range. However, the first stage of integration should be endowed with specific properties that enable efficient handling of the incoming information. In elasmobranches, the afferent nerve originating from the ampullae of Lorenzini targets specific neurons located at the Dorsal Octavolateral Nucleus (DON), the first stage of integration in the electroreception system. Using intracellular recordings in an isolated brainstem preparation from the shark we analyze the properties of this afferent pathway. We found that stimulating the afferent nerve activates a mixture of excitatory and inhibitory synapses mediated by AMPA-like and GABAA receptors, respectively. The excitatory synapses that are extremely efficient in activating the postsynaptic neurons display unusual voltage dependence, enabling them to operate as a current source. The inhibitory input is powerful enough to completely eliminate the excitatory action of the afferent nerve but is ineffective regarding other excitatory inputs. These observations can be explained by the location and efficiency of the synapses. We conclude that the afferent nerve provides powerful and reliable excitatory input as well as a feed-forward inhibitory input, which is partially presynaptic in origin. These results question the cellular location within the DON where cancelation of expected incoming signals occurs.
de Hoz, L, Nelken I.  2014.  Frequency tuning in the behaving mouse: different bandwidths for discrimination and generalization.. PloS one. 9(3):e91676. Abstract
When faced with sensory stimuli, an organism may be required to detect very small differences in a physical parameter (discrimination), while in other situations it may have to generalize over many possible values of the same physical parameter. This decision may be based both on learned information and on sensory aspects of perception. In the present study we describe frequency processing in the behaving mouse using both discrimination and generalization as two key aspects of behaviour. We used a novel naturalistic behavioural apparatus designed for mice, the Audiobox, and paradigm contingencies that were identical for both auditory discrimination and generalization, the latter measured using latent inhibition. Mice learned to discriminate between frequencies that were an octave apart in a single trial. They showed significant discrimination between tone frequencies that were as close as 4-7%, and had d' of about 1 for ΔF of around 10%. In contrast, pre-exposure frequencies that were half an octave or less below the conditioned tone elicited latent inhibition, showing a generalization bandwidth of at least half an octave. Thus, in the same apparatus and using the same general memory paradigm, mice showed generalization gradients that were considerably wider than their discrimination threshold, indicating that environmental requirements and previous experience can determine whether the same two frequencies will be considered same or different. Remarkably, generalization gradients paralleled the typical bandwidths established in the auditory periphery and midbrain, suggesting that frequencies may be considered similar when falling within the same critical band.
Shrem, T, Deouell LY.  2014.  Frequency-dependent auditory space representation in the human planum temporale.. Frontiers in human neuroscience. 8:524. Abstract
Functional magnetic resonance imaging (fMRI) findings suggest that a part of the planum temporale (PT) is involved in representing spatial properties of acoustic information. Here, we tested whether this representation of space is frequency-dependent or generalizes across spectral content, as required from high order sensory representations. Using sounds with two different spectral content and two spatial locations in individually tailored virtual acoustic environment, we compared three conditions in a sparse-fMRI experiment: Single Location, in which two sounds were both presented from one location; Fixed Mapping, in which there was one-to-one mapping between two sounds and two locations; and Mixed Mapping, in which the two sounds were equally likely to appear at either one of the two locations. We surmised that only neurons tuned to both location and frequency should be differentially adapted by the Mixed and Fixed mappings. Replicating our previous findings, we found adaptation to spatial location in the PT. Importantly, activation was higher for Mixed Mapping than for Fixed Mapping blocks, even though the two sounds and the two locations appeared equally in both conditions. These results show that spatially tuned neurons in the human PT are not invariant to the spectral content of sounds.
Greenberg, DS, Soreq H.  2014.  MicroRNA therapeutics in neurological disease.. Current pharmaceutical design. 20(38):6022-7. Abstract
Developing microRNA therapeutics for neurological diseases is both a promising opportunity and an extremely challenging topic for several reasons. The promise stems from the very small size of microRNAs, which makes them amenable for manipulation via short synthetic oligonucleotides or engineered viruses. Also, the fact that each microRNA may regulate numerous target transcripts of the same pathway predicts that such manipulations may affect an entire pathway rather than a single gene and gives reason to hope that low dose therapeutic targeting of the top microRNA in such a hierarchic pyramid would suffice to induce a focused change in the entire pyramid. However, these same features, which make microRNAs such promising targets for therapeutic manipulations also present great challenges. Thus the plethora of functional targets for each microRNA in specific cell types is yet far from being elucidated, which implies that the targets to be affected may not be those planned to be manipulated (a risk of 'off-target' effects). Also, the hierarchic order of microRNA regulation is yet unknown, which predicts a risk of complex, multi-leveled consequences following the manipulation of a single microRNA; and the delivery of oligonucleotide therapeutics into the brain is a challenge due to the blood-brain barrier. In this chapter, we briefly outline the current state of knowledge regarding microRNA regulation in different neuropathologies and sketch the emerging principles for the development of microRNA therapeutics for these diseases.We address issues such as modes of delivery and consideration of the inherited and acquired variability between individuals in the susceptibility to such treatments. We further refer in a somewhat more in-depth manner to the issue of manipulating microRNA functioning in the parasympathetic system and the pathway of cholinergic signaling. Beyond the brain and within it, cholinergic signaling controls inflammatory reactions, and microRNA changes would likely affect this function as well. Furthermore, microRNA regulation of cholinergic signaling involves the elements of complexity and hierarchy noted above, and is relevant to numerous neuropathologies and neurodegenerative syndromes. Research and translational efforts that lead to the development of microRNA therapeutics merit thorough discussion.
Kalcheim, C, Storey KG.  2014.  Neural-mesodermal progenitor interactions in pattern formation: an introduction to the collection.. F1000Research. 3:275. Abstract
Mesodermal and spinal cord progenitors originate from common founder cells from which they segregate during development. Moreover, neural and mesodermal tissues closely interact during embryogenesis to ensure timely patterning and differentiation of both head and trunk structures. For instance, the fate and morphogenesis of neural progenitors is dependent on signals produced by mesodermal cells and vice-versa. While some of the cellular and molecular signals that mediate these interactions have been described, much more remains to be uncovered. The scope of this collection will cover these interactions between neural (CNS or PNS) and mesodermal progenitors in patterning body plans and specific body systems in vertebrate embryos. This includes, but is not limited to, interactions influencing the formation of body axes, neural tube formation, neural crest migration, gut development, muscle patterning and myogenesis.
Nadorp, B, Soreq H.  2014.  Predicted overlapping microRNA regulators of acetylcholine packaging and degradation in neuroinflammation-related disorders.. Frontiers in molecular neuroscience. 7:9. Abstract
MicroRNAs (miRNAs) can notably control many targets each and regulate entire cellular pathways, but whether miRNAs can regulate complete neurotransmission processes is largely unknown. Here, we report that miRNAs with complementary sequence motifs to the key genes involved in acetylcholine (ACh) synthesis and/or packaging show massive overlap with those regulating ACh degradation. To address this topic, we first searched for miRNAs that could target the 3'-untranslated regions of the choline acetyltransferase (ChAT) gene that controls ACh synthesis; the vesicular ACh transporter (VAChT), encoded from an intron in the ChAT gene and the ACh hydrolyzing genes acetyl- and/or butyrylcholinesterase (AChE, BChE). Intriguingly, we found that many of the miRNAs targeting these genes are primate-specific, and that changes in their levels associate with inflammation, anxiety, brain damage, cardiac, neurodegenerative, or pain-related syndromes. To validate the in vivo relevance of this dual interaction, we selected the evolutionarily conserved miR-186, which targets both the stress-inducible soluble "readthrough" variant AChE-R and the major peripheral cholinesterase BChE. We exposed mice to predator scent stress and searched for potential associations between consequent changes in their miR-186, AChE-R, and BChE levels. Both intestinal miR-186 as well as BChE and AChE-R activities were conspicuously elevated 1 week post-exposure, highlighting the previously unknown involvement of miR-186 and BChE in psychological stress responses. Overlapping miRNA regulation emerges from our findings as a recently evolved surveillance mechanism over cholinergic neurotransmission in health and disease; and the corresponding miRNA details and disease relevance may serve as a useful resource for studying the molecular mechanisms underlying this surveillance.
Medan, G, Kronman A, Joskowicz L.  2014.  Reduced-dose patient to baseline CT rigid registration in 3D Radon space.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 17(Pt 1):291-8. Abstract
We present a new method for rigid registration of CT scans in Radon space. The inputs are the two 3D Radon transforms of the CT scans, one densely sampled and the other sparsely sampled. The output s the rigid transformation that best matches them. The algorithm starts by finding the best matching between each direction vector in the sparse transform and the corresponding direction vector in the dense transform. It then solves the system of linear equations derived from the direction vector pairs. Our method can be used to register two CT scans and to register a baseline scan to the patient with reduced-dose scanning without compromising registration accuracy. Our preliminary simulation results on the Shepp-Logan head phantom dataset and a pair of clinical head CT scans indicates that our 3D Radon space rigid registration method performs significantly better than image-based registration for very few scan angles and comparably for densely-sampled scans.
Applebaum, M, Ben-Yair R, Kalcheim C.  2014.  Segregation of striated and smooth muscle lineages by a Notch-dependent regulatory network.. BMC biology. 12:53. Abstract
Lineage segregation from multipotent epithelia is a central theme in development and in adult stem cell plasticity. Previously, we demonstrated that striated and smooth muscle cells share a common progenitor within their epithelium of origin, the lateral domain of the somite-derived dermomyotome. However, what controls the segregation of these muscle subtypes remains unknown. We use this in vivo bifurcation of fates as an experimental model to uncover the underlying mechanisms of lineage diversification from bipotent progenitors.
Weiss, AH, Biron T, Lieder I, Granot RY, Ahissar M.  2014.  Spatial vision is superior in musicians when memory plays a role.. Journal of vision. 14(9) Abstracti1534-7362-14-9-18.pdf
Musicians' perceptual advantage in the acoustic domain is well established. Recent studies show that musicians' verbal working memory is also superior. Additionally, some studies report that musicians' visuospatial skills are enhanced although others failed to find this enhancement. We now examined whether musicians' spatial vision is superior, and if so, whether this superiority reflects refined visual skills or a general superiority of working memory. We examined spatial frequency discrimination among musicians and nonmusician university students using two presentation conditions: simultaneous (spatial forced choice) and sequential (temporal forced choice). Musicians' performance was similar to that of nonmusicians in the simultaneous condition. However, their performance in the sequential condition was superior, suggesting an advantage only when stimuli need to be retained, i.e., working memory. Moreover, the two groups showed a different pattern of correlations: Musicians' visual thresholds were correlated, and neither was correlated with their verbal memory. By contrast, among nonmusicians, the visual thresholds were not correlated, but sequential thresholds were correlated with verbal memory scores, suggesting that a general working memory component limits their performance in this condition. We propose that musicians' superiority in spatial frequency discrimination reflects an advantage in a domain-general aspect of working memory rather than a general enhancement in spatial-visual skills.
Goll, Y, Bekenstein U, Barbash S, Greenberg DS, Zangen R, Shoham S, Soreq H.  2014.  Sustained Alzheimer's amyloid pathology in myeloid differentiation protein-88-deficient APPswe/PS1 mice.. Neuro-degenerative diseases. 13(2-3):58-60. Abstract
Most Alzheimer's disease (AD) cases arise sporadically and may involve innate immune activation of microglial expressed Toll-like receptors regulated through the myeloid differentiation protein 88 (MyD88) pathway.
Ofri, R, Itay L, Loewenstein Y, Ahissar M.  2014.  Contradictory Behavioral Biases Result from the Influence of Past Stimuli on Perception. PLoS Computational Biology . 10(12):e1003948. Abstract
Biases such as the preference of a particular response for no obvious reason, are an integral part of psychophysics. Such biases have been reported in the common two-alternative forced choice (2AFC) experiments, where participants are instructed to compare two consecutively presented stimuli. However, the principles underlying these biases are largely unknown and previous studies have typically used ad-hoc explanations to account for them. Here we consider human performance in the 2AFC tone frequency discrimination task, utilizing two standard protocols. In both protocols, each trial contains a reference stimulus. In one (Reference-Lower protocol), the frequency of the reference stimulus is always lower than that of the comparison stimulus, whereas in the other (Reference protocol), the frequency of the reference stimulus is either lower or higher than that of the comparison stimulus. We find substantial interval biases. Namely, participants perform better when the reference is in a specific interval. Surprisingly, the biases in the two experiments are opposite: performance is better when the reference is in the first interval in the Reference protocol, but is better when the reference is second in the Reference-Lower protocol. This inconsistency refutes previous accounts of the interval bias, and is resolved when experiments statistics is considered. Viewing perception as incorporation of sensory input with prior knowledge accumulated during the experiment accounts for the seemingly contradictory biases both qualitatively and quantitatively. The success of this account implies that even simple discriminations reflect a combination of sensory limitations, memory limitations, and the ability to utilize stimuli statistics.
David, A, Castrioto Anna, Renana E, Zvi I, Bergman H.  2014.  In quest of the oscillator(s) in tremor: are we getting closer? Brain. 137(Pt 12):3102-3103.
Nelken, I, Bizley J, Shamma SA, Wang X.  2014.  Auditory cortical processing in real-world listening: the auditory system going real.. The Journal of Neuroscience. Abstract
The auditory sense of humans transforms intrinsically senseless pressure waveforms into spectacularly rich perceptual phenomena: the music of Bach or the Beatles, the poetry of Li Bai or Omar Khayyam, or more prosaically the sense of the world filled with objects emitting sounds that is so important for those of us lucky enough to have hearing. Whereas the early representations of sounds in the auditory system are based on their physical structure, higher auditory centers are thought to represent sounds in terms of their perceptual attributes. In this symposium, we will illustrate the current research into this process, using four case studies. We will illustrate how the spectral and temporal properties of sounds are used to bind together, segregate, categorize, and interpret sound patterns on their way to acquire meaning, with important lessons to other sensory systems as well.
Marc, D, Peter H, Shay M, de Fernando R N, Hagai B, Zvi I.  2014.  Higher neuronal discharge rate un the motor area of the subthalamic nucleus of Parkinsonian patients.. Journal of Neurophysiology. 112:1409-1420. Abstract
In Parkinson's disease, pathological synchronous oscillations divide the subthalamic nucleus (STN) of patients into a dorsolateral oscillatory region and ventromedial non-oscillatory region. This bipartite division reflects the motor vs. the non-motor (associative/limbic) subthalamic areas, respectively. However, significant topographic differences in the neuronal discharge rate between these two STN sub-regions in Parkinsonian patients is still controversial. In this study, 119 STN microelectrode trajectories (STN length > 2mm, mean = 5.32mm) with discernible oscillatory and non-oscillatory regions were carried on 60 patients undergoing deep brain stimulation surgery for Parkinson's disease. 2137 and 2152 multi-unit stable signals were recorded (recording duration > 10s, mean = 21.25s) within the oscillatory and non-oscillatory STN regions, respectively. Spike detection and sorting was applied offline on every multi-unit stable signal using an automatic method with systematic quantification of the isolation quality (range = 0 to 1) of the identified units. In all, 3094 and 3130 units were identified in the oscillatory and non-oscillatory regions, respectively. On average, the discharge rate of better-isolated neurons (isolation score > 0.70) was higher in the oscillatory region than the non-oscillatory region (44.55 ± 0.87 versus 39.97 ± 0.77 spikes/s, N = 665 and 761, respectively). The discharge rate of the STN neurons was positively correlated to the strength of their own and their surrounding 13-30Hz beta oscillatory activity. Therefore, in the Parkinsonian STN, beta oscillations and higher neuronal discharge rate are correlated and coexist in the motor area of the STN compared to its associative/limbic area.
Hay, E, Segev I.  2014.  Dendritic Excitability and Gain Control in Recurrent Cortical Microcircuits. Cerebral Cortex. doi:10.1093/cercor/bhu200 Abstract
Layer 5 thick tufted pyramidal cells (TTCs) in the neocortex are particularly electrically complex, owing to their highly excitable dendrites. The interplay between dendritic nonlinearities and recurrent cortical microcircuit activity in shaping network response is largely unknown. We simulated detailed conductance-based models of TTCs forming recurrent microcircuits that were interconnected as found experimentally; the network was embedded in a realistic background synaptic activity. TTCs microcircuits significantly amplified brief thalamocortical inputs; this cortical gain was mediated by back-propagation activated N-methyl-d-aspartate depolarizations and dendritic back-propagation-activated Ca2+ spike firing, ignited by the coincidence of thalamic-activated somatic spike and local dendritic synaptic inputs, originating from the cortical microcircuit. Surprisingly, dendritic nonlinearities in TTCs microcircuits linearly multiplied thalamic inputs-amplifying them while maintaining input selectivity. Our findings indicate that dendritic nonlinearities are pivotal in controlling the gain and the computational functions of TTCs microcircuits, which serve as a dominant output source for the neocortex.
Tal, N, Yonatan L.  2014.  Spatial Generalization in Operant Learning: Lessons from Professional Basketball. PLoS Computational Biology . 10(5):e1003623. Abstract
In operant learning, behaviors are reinforced or inhibited in response to the consequences of similar actions taken in the past. However, because in natural environments the “same” situation never recurs, it is essential for the learner to decide what “similar” is so that he can generalize from experience in one state of the world to future actions in different states of the world. The computational principles underlying this generalization are poorly understood, in particular because natural environments are typically too complex to study quantitatively. In this paper we study the principles underlying generalization in operant learning of professional basketball players. In particular, we utilize detailed information about the spatial organization of shot locations to study how players adapt their attacking strategy in real time according to recent events in the game. To quantify this learning, we study how a make \ miss from one location in the court affects the probabilities of shooting from different locations. We show that generalization is not a spatially-local process, nor is governed by the difficulty of the shot. Rather, to a first approximation, players use a simplified binary representation of the court into 2 pt and 3 pt zones. This result indicates that rather than using low-level features, generalization is determined by high-level cognitive processes that incorporate the abstract rules of the game.
Gianluigi, M, Hanan S, Yonatan L.  2014.  The Misbehavior of Reinforcement Learning. Proceedings of the IEEE. 102(4):528-541. Abstract pdf FURTHER THOUGHTS
Organisms modify their behavior in response to its consequences, a phenomenon referred to as operant learning. The computational principles and neural mechanisms underlying operant learning are a subject of extensive experimental and theoretical investigations. Theoretical approaches largely rely on concepts and algorithms from reinforcement learning. The dominant view is that organisms maintain a value function, that is, a set of estimates of the cumulative future rewards associated with the different behavioral options. These values are then used to select actions. Learning in this framework results from the update of these values depending on experience of the consequences of past actions. An alternative view questions the applicability of such a computational scheme to many real-life situations. Instead, it posits that organisms exploit the intrinsic variability in their action–selection mechanism(s) to modify their behavior, e.g., via stochastic gradient ascent, without the need of an explicit representation of values. In this review, we compare these two approaches in terms of their computational power and flexibility, their putative neural correlates, and, finally, in terms of their ability to account for behavior as observed in repeated-choice experiments. We discuss the successes and failures of these alternative approaches in explaining the observed patterns of choice behavior. We conclude by identifying some of the important challenges to a comprehensive theory of operant learning.
Shteingart, H, Loewenstein Y.  2014.  Reinforcement learning and human behavior. Current Opinion in Neurobiology. 25:93-98. AbstractPDF
The dominant computational approach to model operant learning and its underlying neural activity is model-free reinforcement learning (RL). However, there is accumulating behavioral and neuronal-related evidence that human (and animal) operant learning is far more multifaceted. Theoretical advances in RL, such as hierarchical and model-based RL extend the explanatory power of RL to account for some of these findings. Nevertheless, some other aspects of human behavior remain inexplicable even in the simplest tasks. Here we review developments and remaining challenges in relating RL models to human operant learning. In particular, we emphasize that learning a model of the world is an essential step before or in parallel to learning the policy in RL and discuss alternative models that directly learn a policy without an explicit world model in terms of state-action pairs.
Grodzinsky, Y, Nelken I.  2014.  The Neural Code That Makes Us Human. Science. 343(978)
Pehlevan, C, Sompolinsky H.  2014.  Selectivity and Sparseness in Randomly Connected Balanced Networks. PLOS ONE. 9(2) Abstract
Neurons in sensory cortex show stimulus selectivity and sparse population response, even in cases where no strong functionally specific structure in connectivity can be detected. This raises the question whether selectivity and sparseness can be generated and maintained in randomly connected networks. We consider a recurrent network of excitatory and inhibitory spiking neurons with random connectivity, driven by random projections from an input layer of stimulus selective neurons. In this architecture, the stimulus-to-stimulus and neuron-to-neuron modulation of total synaptic input is weak compared to the mean input. Surprisingly, we show that in the balanced state the network can still support high stimulus selectivity and sparse population response. In the balanced state, strong synapses amplify the variation in synaptic input and recurrent inhibition cancels the mean. Functional specificity in connectivity emerges due to the inhomogeneity caused by the generative statistical rule used to build the network. We further elucidate the mechanism behind and evaluate the effects of model parameters on population sparseness and stimulus selectivity. Network response to mixtures of stimuli is investigated. It is shown that a balanced state with unselective inhibition can be achieved with densely connected input to inhibitory population. Balanced networks exhibit the ‘‘paradoxical’’ effect: an increase in excitatory drive to inhibition leads to decreased inhibitory population firing rate. We compare and contrast selectivity and sparseness generated by the balanced network to randomly connected unbalanced networks. Finally, we discuss our results in light of experiments.
Gjorgjieva, J, Sompolinsky H, Markus M.  2014.  Benefits of pathway splitting in sensory coding. The Journal of Neuroscience. 0270-6474/14/3412127-18$15.00/0 Abstract
In many sensory systems, the neural signal splits into multiple parallel pathways. For example, in the mammalian retina, ∼20 types of retinal ganglion cells transmit information about the visual scene to the brain. The purpose of this profuse and early pathway splitting remains unknown. We examine a common instance of splitting into ON and OFF neurons excited by increments and decrements of light intensity in the visual scene, respectively. We test the hypothesis that pathway splitting enables more efficient encoding of sensory stimuli. Specifically, we compare a model system with an ON and an OFF neuron to one with two ON neurons. Surprisingly, the optimal ON-OFF system transmits the same information as the optimal ON-ON system, if one constrains the maximal firing rate of the neurons. However, the ON-OFF system uses fewer spikes on average to transmit this information. This superiority of the ON-OFF system is also observed when the two systems are optimized while constraining their mean firing rate. The efficiency gain for the ON-OFF split is comparable with that derived from decorrelation, a well known processing strategy of early sensory systems. The gain can be orders of magnitude larger when the ecologically important stimuli are rare but large events of either polarity. The ON-OFF system also provides a better code for extracting information by a linear downstream decoder. The results suggest that the evolution of ON-OFF diversification in sensory systems may be driven by the benefits of lowering average metabolic cost, especially in a world in which the relevant stimuli are sparse.
Burak, Y.  2014.  Spatial coding and attractor dynamics of grid cells in the entorhinal cortex. Current Opinion in Neurobiology. 25:169-175.burak_2014.pdf
Ben, E, Eilon V.  2014.  Spatial computation with gamma oscillations. Front Syst. Neuros. 8(165)
Roth, ZN, Zohary E.  2014.  Fingerprints of Learned Object Recognition Seen in the fMRI Activation Patterns of Lateral Occipital Complex. Cerebral Cortex. :bhu042.