Announcement

Collapse
No announcement yet.

Controllability of structural brain networks

Collapse
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • CT Controllability of structural brain networks

    http://www.nature.com/ncomms/2015/15...comms9414.html

    Abstract
    Abstract• Introduction• Results• Discussion• Methods• Additional information• References• Acknowledgements• Author information• Supplementary information
    Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.
    Jo Bowyer
    Chartered Physiotherapist Registered Osteopath.
    "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

  • #2
    Human brain networks function in connectome-specific harmonic waves

    http://www.nature.com/ncomms/2016/16...omms10340.html

    Abstract
    Abstract• Introduction• Results• Discussion• Methods• Additional information• References• Acknowledgements• Author information• Supplementary information
    A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call ‘connectome harmonics’, oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory–inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation–inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.
    A characteristic feature of cortical dynamics in mammals is the emergence of behaviour-dependent oscillatory networks spanning five orders of magnitude in the frequency domain4. Recently, strong temporal correlation within widely distributed cortical regions has also been discovered in spontaneous slow (<0.1 Hz) fluctuations of the blood oxygen level-dependent signal measured with functional magnetic resonance imaging (fMRI). This discovery revealed that spontaneous activity, in the absence of any external stimuli or task condition, also exhibits highly structured correlation patterns throughout the brain. Remarkably, the topography of these correlation patterns, termed the resting state networks (RSNs)5, 6, closely resembles the functional networks of the human brain identified by various sensory, motor and cognitive paradigms6, 7 and have been found to relate to electroencephalography microstates, global brain states occurring in discrete epochs of about 100 ms (refs 8, 9).
    Our description of the universal harmonics implied by the graph Laplacian in terms of diffusion rests on the undirected nature of the structural connectome (represented by a symmetric adjacency matrix). However, we know that reciprocal forward and backward connections show strong asymmetries in the human brain, rendering the conceptual link between the (directed) effective connectivity and diffusion not always valid. Having said this, there is no reason why one cannot pursue modelling and simulation using the eigenmodes of directed effective connectivity matrices28.
    In summary, in this work we introduce a new connectome-specific representation of cortical activity patterns and dynamics, which extends the Fourier basis to the structural connectivity of the thalamo-cortical system. Remarkably, when expressed in this new analytic language, RSNs of the human brain overlap with the connectome harmonic patterns of certain frequencies. We demonstrate the self-organization of these connectome-specific harmonics patterns from the interplay of neural excitation and inhibition in coupled dynamical systems as described by neural field models. Interestingly, due to the emergence of these harmonic patterns in various natural phenomena, ranging from acoustic vibrations, electromagnetic interactions and electron wave functions to morphogenesis, it is tempting to suppose that human brain activity might also be governed by the same underlying principles as other natural phenomena.

    This is what lies beneath.

    It references the work of Laplace, Schrodinger, Alan Turing's work on biological pattern formation, the Wilson-Cowan equations and Karl Friston's nodes and modes.
    Last edited by Jo Bowyer; 27-01-2016, 10:11 PM.
    Jo Bowyer
    Chartered Physiotherapist Registered Osteopath.
    "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

    Comment


    • #3
      MATHEMATICALLY MODELLING HOW THE BRAIN MAKES COMPLEX DECISIONS

      http://neurosciencenews.com/decision...th-model-3578/

      “A goal-based decision is much more complicated from a neurological point of view, because there are so many more variables – it involves exploring a branching set of possible future situations,” said the paper’s first author Dr Johannes Friedrich of Columbia University, who conducted the work while a postdoctoral researcher in Cambridge’s Department of Engineering. “If you think about a detour on your daily commute, you need to make a separate decision each time you reach an intersection.”

      Habit-based decisions have been thoroughly studied by neuroscientists and are fairly well-understood in terms of how they work at a neural level. The mechanisms behind goal-based decisions however, remain elusive.
      Jo Bowyer
      Chartered Physiotherapist Registered Osteopath.
      "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

      Comment


      • #4
        A role of phase-resetting in coordinating large scale neural oscillations during attention and goal-directed behavior

        http://journal.frontiersin.org/artic...00018/abstract

        Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits, (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances, (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations, and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior.
        Keywords: oscillations, Phase reset, cross frequency coupling, coding, inter-areal coordination, theta, alpha, gamma




        Time-compressed preplay of anticipated events in human primary visual cortex

        https://www.nature.com/articles/ncomms15276

        Abstract
        Perception is guided by the anticipation of future events. It has been hypothesized that this process may be implemented by pattern completion in early visual cortex, in which a stimulus sequence is recreated after only a subset of the visual input is provided. Here we test this hypothesis using ultra-fast functional magnetic resonance imaging to measure BOLD activity at precisely defined receptive field locations in visual cortex (V1) of human volunteers. We find that after familiarizing subjects with a spatial sequence, flashing only the starting point of the sequence triggers an activity wave in V1 that resembles the full stimulus sequence. This preplay activity is temporally compressed compared to the actual stimulus sequence and remains present even when attention is diverted from the stimulus sequence. Preplay might therefore constitute an automatic prediction mechanism for temporal sequences in V1.
        Introduction
        The visual system is predictive in nature, anticipating relevant events to facilitate sensory processing and decision-making1. Prediction in perception has often been studied in static contexts, where a stimulus is expected because the base rate of occurrence is higher2 or because of statistical associations between stimuli3. These forms of prediction can be neurally implemented by pre-activating sensory representations of the expected events4,5,6.

        However, real-world predictions are typically dynamic: for example, we predict the trajectory of a ball moving towards us or whether a car will hit us if we cross the road. Implementing this kind of dynamic prediction is more complex, as it requires an anticipatory wave of visual responses that is both spatially and temporally precise. Recently, such waves of preplay activity have been observed in the visual cortical system of rats7 and monkeys8, but the existence, function and potential source of preplay waves in humans however remain unknown.

        Here we tested whether human primary visual cortex (V1) is engaged in dynamic prediction by preplaying anticipated visual events. We characterized neural activity in the primary visual cortex at both high spatial and temporal resolution, by combining ultra-fast functional magnetic resonance imaging (fMRI, using a volume acquisition time (TR) of 88 ms) and population receptive field (pRF) mapping9 to identify retinotopically specific responses with high temporal resolution.
        Update 31/05/2017
        Last edited by Jo Bowyer; 31-05-2017, 09:00 AM.
        Jo Bowyer
        Chartered Physiotherapist Registered Osteopath.
        "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

        Comment


        • #5
          Stimuli Reduce the Dimensionality of Cortical Activity

          http://journal.frontiersin.org/artic...016.00011/full

          The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.
          Understanding the dynamics of neural activity and how it is generated in cortical circuits is a fundamental question in Neuroscience.
          Jo Bowyer
          Chartered Physiotherapist Registered Osteopath.
          "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

          Comment


          • #6
            On the character of consciousness

            http://journal.frontiersin.org/artic...00027/abstract

            The human brain is a particularly demanding system to infer its nature from observations. Thus, there is on one hand plenty of room for theorizing and on the other hand a pressing need for a rigorous theory. We apply statistical mechanics of open systems to describe the brain as a hierarchical system in consuming free energy in least time. This holistic tenet accounts for cellular metabolism, neuronal signaling, cognitive processes all together or any other process by a formal equation of motion that extends down to the ultimate precision of one quantum of action. According to this general thermodynamic theory cognitive processes are no different by their operational and organizational principle from other natural processes. Cognition too will emerge and evolve along path-dependent and non-determinate trajectories by consuming free energy in least time to attain thermodynamic balance within the nervous system itself and with its surrounding systems. Specifically, consciousness can be ascribed to a natural process that integrates various neural networks for coherent consumption of free energy, i.e., for meaningful deeds. The whole hierarchy of integrated systems can be formally summed up to thermodynamic entropy. The holistic tenet provides insight to the character of consciousness also by acknowledging awareness in other systems at other levels of nature’s hierarchy.


            Who Am I: The Conscious and the Unconscious Self
            http://journal.frontiersin.org/artic...017.00126/full

            Who am I? What is the self and where does it come from? This may be one of the oldest problems in philosophy. Beyond traditional philosophy, only very recently approaches from neuroscience (in particular imaging studies) have tried to address these questions, too. So what are neural substrates of our self? An increasing body of evidence has demonstrated that a set of structures labeled as cortical midline structures are fundamental components to generate a conscious self. Moreover, recent theories on embodied cognition propose that this conscious self might be supplemented by additional structures, for example, in the somatosensory cortices, which enable our brain to create an “embodied mind”. While the self based on cortical midline structures may be related to a conscious self, we here propose that the embodied facet of the self may be linked to something we call unconscious self. In this article we describe problems of this model of a conscious and unconscious self and discuss possible solutions from a theoretical point of view.
            Who Am I?
            We know that even in prehistoric times humans tried to open the skulls of their sick conspecifics. Moreover, prehistoric men used human skulls, usually those of ancestors, for religious worship long after death. Thus, the head always seemed to be an object of interest for us. Perhaps the prehistoric men assumed that something inside our skull may be related to our feelings, thoughts and memories. But we had to wait until the French philosopher René Descartes, who was the first one who made the distinction between mind and body very explicit. His famous philosophical statement “Cogito ergo sum” can be translated as “I think, therefore I am”. Hence, he concludes that he can be certain that he exists because he thinks. For many researchers these thoughts mark the beginning of modern western philosophy. Descartes statement raised a lot of questions, in particular about the relationship between body and mind, which are still a matter of discussion today.

            This is in particular true since modern neuroscience started to unravel the mystery of the brain. New imaging tools such as fMRI enable us to look at our brain while it is working. These new approaches have opened the door to answer the questions Descartes posed about the relationship between mind and body in a way he never would have imagined.

            In this article we suggest the idea that the processing of self-referential stimuli in cortical midline structures may represent an important part of the conscious self, which may be supplemented by an unconscious part of the self that has been called an “embodied mind” (Varela et al., 1991), which relies on other brain structures.
            Update 05/04/2017
            Last edited by Jo Bowyer; 05-04-2017, 06:12 PM.
            Jo Bowyer
            Chartered Physiotherapist Registered Osteopath.
            "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

            Comment


            • #7
              Multisensory Tracking of Objects in Darkness: Capture of Positive Afterimages by the Tactile and Proprioceptive Senses

              http://journals.plos.org/plosone/art...l.pone.0150714

              Abstract

              This paper reports on three experiments investigating the contribution of different sensory modalities to the tracking of objects moved in total darkness. Participants sitting in the dark were exposed to a brief, bright flash which reliably induced a positive visual afterimage of the scene so illuminated. If the participants subsequently move their hand in the darkness, the visual afterimage of that hand fades or disappears; this is presumably due to conflict between the illusory visual afterimage (of the hand in its original location) and other information (e.g., proprioceptive) from a general mechanism for tracking body parts. This afterimage disappearance effect also occurs for held objects which are moved in the dark, and some have argued that this represents a case of body schema extension, i.e. the rapid incorporation of held external objects into the body schema. We demonstrate that the phenomenon is not limited to held objects and occurs in conditions where incorporation into the body schema is unlikely. Instead, we propose that the disappearance of afterimages of objects moved in darkness comes from a general mechanism for object tracking which integrates input from multiple sensory systems. This mechanism need not be limited to tracking body parts, and thus we need not invoke body schema extension to explain the afterimage disappearance. In this series of experiments, we test whether auditory feedback of object movement can induce afterimage disappearance, demonstrate that the disappearance effect scales with the magnitude of proprioceptive feedback, and show that tactile feedback alone is sufficient for the effect. Together, these data demonstrate that the visual percept of a positive afterimage is constructed not just from visual input of the scene when light reaches the eyes, but in conjunction with input from multiple other senses.
              Jo Bowyer
              Chartered Physiotherapist Registered Osteopath.
              "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

              Comment


              • #8
                Dynamic causal modelling of eye movements during pursuit: Confirming precision-encoding in V1 using MEG

                http://www.ncbi.nlm.nih.gov/pubmed/26921713

                Abstract
                This paper shows that it is possible to estimate the subjective precision (inverse variance) of Bayesian beliefs during oculomotor pursuit. Subjects viewed a sinusoidal target, with or without random fluctuations in its motion. Eye trajectories and magnetoencephalographic (MEG) data were recorded concurrently. The target was periodically occluded, such that its reappearance caused a visual evoked response field (ERF). Dynamic causal modelling (DCM) was used to fit models of eye trajectories and the ERFs. The DCM for pursuit was based on predictive coding and active inference, and predicts subjects' eye movements based on their (subjective) Bayesian beliefs about target (and eye) motion. The precisions of these hierarchical beliefs can be inferred from behavioural (pursuit) data. The DCM for MEG data used an established biophysical model of neuronal activity that includes parameters for the gain of superficial pyramidal cells, which is thought to encode precision at the neuronal level. Previous studies (using DCM of pursuit data) suggest that noisy target motion increases subjective precision at the sensory level: i.e., subjects attend more to the target's sensory attributes. We compared (noisy motion-induced) changes in the synaptic gain based on the modelling of MEG data to changes in subjective precision estimated using the pursuit data. We demonstrate that imprecise target motion increases the gain of superficial pyramidal cells in V1 (across subjects). Furthermore, increases in sensory precision - inferred by our behavioural DCM - correlate with the increase in gain in V1, across subjects. This is a step towards a fully integrated model of brain computations, cortical responses and behaviour that may provide a useful clinical tool in conditions like schizophrenia.
                Jo Bowyer
                Chartered Physiotherapist Registered Osteopath.
                "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                Comment


                • #9
                  Rapid Adaptation Induces Persistent Biases in Population Codes for Visual Motion

                  http://www.jneurosci.org/content/36/....abstract?etoc

                  Abstract

                  Each visual experience changes the neural response to subsequent stimuli. If the brain is unable to incorporate these encoding changes, the decoding, or perception, of subsequent stimuli is biased. Although the phenomenon of adaptation pervades the nervous system, its effects have been studied mainly in isolation, based on neuronal encoding changes induced by an isolated, prolonged stimulus. To understand how adaptation-induced biases arise and persist under continuous, naturalistic stimulation, we simultaneously recorded the responses of up to 61 neurons in the marmoset (Callithrix jacchus) middle temporal area to a sequence of directions that changed every 500 ms. We found that direction-specific adaptation following only 0.5 s of stimulation strongly affected encoding for up to 2 s by reducing both the gain and the spike count correlations between pairs of neurons with preferred directions close to the adapting direction. In addition, smaller changes in bandwidth and preferred direction were observed in some animals. Decoding individual trials of adaptation-affected activity in simultaneously recorded neurons predicted repulsive biases that are consistent with the direction aftereffect. Surprisingly, removing spike count correlations by trial shuffling did not impact decoding performance or bias. When adaptation had the largest effect on encoding, the decoder made the most errors. This suggests that neural and perceptual repulsion is not a mechanism to enhance perceptual performance but is instead a necessary consequence of optimizing neural encoding for the identification of a wide range of stimulus properties in diverse temporal contexts.

                  SIGNIFICANCE STATEMENT Although perception depends upon decoding the pattern of activity across a neuronal population, the encoding properties of individual neurons are unreliable: a single neuron's response to repetitions of the same stimulus is variable, and depends on both its spatial and temporal context. In this manuscript, we describe the complete cascade of adaptation-induced effects in sensory encoding and show how they predict population decoding errors consistent with perceptual biases. We measure the time course of adaptation-induced changes to the response properties of neurons in isolation, and to the correlation structure across pairs of simultaneously recorded neurons. These results provide novel insight into how and for how long adaptation affects the neural code, particularly during continuous, naturalistic vision.
                  Jo Bowyer
                  Chartered Physiotherapist Registered Osteopath.
                  "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                  Comment


                  • #10
                    The Medial Orbitofrontal Cortex Regulates Sensitivity to Outcome Value

                    http://www.jneurosci.org/content/36/....abstract?etoc

                    Abstract

                    An essential component of goal-directed decision-making is the ability to maintain flexible responding based on the value of a given reward, or “reinforcer.” The medial orbitofrontal cortex (mOFC), a subregion of the ventromedial prefrontal cortex, is uniquely positioned to regulate this process. We trained mice to nose poke for food reinforcers and then stimulated this region using CaMKII-driven Gs-coupled designer receptors exclusively activated by designer drugs (DREADDs). In other mice, we silenced the neuroplasticity-associated neurotrophin brain-derived neurotrophic factor (BDNF). Activation of Gs-DREADDs increased behavioral sensitivity to reinforcer devaluation, whereas Bdnf knockdown blocked sensitivity. These changes were accompanied by modifications in breakpoint ratios in a progressive ratio task, and they were recapitulated in Bdnf+/− mice. Replacement of BDNF selectively in the mOFC in Bdnf+/− mice rescued behavioral deficiencies, as well as phosphorylation of extracellular-signal regulated kinase 1/2 (ERK1/2). Thus, BDNF expression in the mOFC is both necessary and sufficient for the expression of typical effort allocation relative to an anticipated reinforcer. Additional experiments indicated that expression of the immediate-early gene c-fos was aberrantly elevated in the Bdnf+/− dorsal striatum, and BDNF replacement in the mOFC normalized expression. Also, systemic administration of an MAP kinase kinase inhibitor increased breakpoint ratios, whereas the addition of discrete cues bridging the response–outcome contingency rescued breakpoints in Bdnf+/− mice. We argue that BDNF–ERK1/2 in the mOFC is a key regulator of “online” goal-directed action selection.

                    SIGNIFICANCE STATEMENT Goal-directed response selection often involves predicting the consequences of one's actions and the value of potential payoffs. Lesions or chemogenetic inactivation of the medial orbitofrontal cortex (mOFC) in rats induces failures in retrieving outcome identity memories (Bradfield et al., 2015), suggesting that the healthy mOFC serves to access outcome value information when it is not immediately observable and thereby guide goal-directed decision-making. Our findings suggest that the mOFC also bidirectionally regulates effort allocation for a given reward and that expression of the neurotrophin BDNF in the mOFC is both necessary and sufficient for mice to sustain stable representations of reinforcer value.
                    cue dorsal striatum neurotrophin operant orbital progressive ratio
                    Jo Bowyer
                    Chartered Physiotherapist Registered Osteopath.
                    "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                    Comment


                    • #11
                      Dual-process theories and consciousness: the case for ‘Type Zero’ cognition

                      http://nc.oxfordjournals.org/content/2016/1/niw005

                      Abstract
                      A step towards a theory of consciousness would be to characterize the effect of consciousness on information processing. One set of results suggests that the effect of consciousness is to interfere with computations that are optimally performed non-consciously. Another set of results suggests that conscious, system 2 processing is the home of norm-compliant computation. This is contrasted with system 1 processing, thought to be typically unconscious, which operates with useful but error-prone heuristics. These results can be reconciled by separating out two different distinctions: between conscious and non-conscious representations, on the one hand, and between automatic and deliberate processes, on the other. This pair of distinctions is used to illuminate some existing experimental results and to resolve the puzzle about whether consciousness helps or hinders accurate information processing. This way of resolving the puzzle shows the importance of another category, which we label ‘type 0 cognition’, characterized by automatic computational processes operating on non-conscious representations.
                      consciousness unconscious processing theories and models function of consciousness dual processing

                      via Micah Allen's twitter feed
                      Jo Bowyer
                      Chartered Physiotherapist Registered Osteopath.
                      "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                      Comment


                      • #12
                        Opposing Effects of Neuronal Activity on Structural Plasticity

                        http://journal.frontiersin.org/artic...016.00075/full

                        Introduction
                        Information from the environment leads to the activation of neural subnetworks in the brain. The connectivity of these neural subnetworks, i.e., the existence and strength of synapses between neurons, influences the neuronal activation and, thereby, determines the way environmental information is processed. Accordingly, the long-term storage of information is related to activity-dependent (long-lasting) changes in connectivity (Hebb, 1949; Morris et al., 1986; Rioult-Pedotti et al., 1998; Leuner et al., 2003; Pastalkova et al., 2006; Whitlock et al., 2006; reviewed, e.g., in Martin et al., 2000; Chklovskii et al., 2004; Dudai, 2004; Hübener and Bonhoeffer, 2010). Basically two types of activity-dependent mechanisms yield such changes: synaptic or functional plasticity and structural plasticity. Structural or architectural plasticity determines the formation and removal of synapses. On the other hand, synaptic or functional plasticity changes the electrochemical transmission efficacy of synapses by altering, for instance, the receptor configuration of the postsynaptic site. Note, as we will show, this functional synaptic plasticity is associated with structural changes at existing synapses (size, postsynaptic density, etc.) and these changes are sometimes summarized as structural plasticity (Lamprecht and LeDoux, 2004). However, here we restrict structural plasticity to changes of the number of synapses (and of axonal/dendritic trees) and refer the long-term functional changes at existing synapses as synaptic plasticity.

                        The alterations of the transmission efficacy by synaptic plasticity depend on the level of neuronal activation. However, the mapping between activity level and triggered synaptic changes is not unique. In general, they are categorized into two classes: Hebbian and homeostatic synaptic plasticity. Hebbian synaptic plasticity yields an increase in synaptic efficacy given high neuronal activities (long-term potentiation; LTP; Bliss and Lomo, 1973; Lynch et al., 1983; Bliss and Collingridge, 1993; see Feldman, 2009 for a review), while low levels of activity induce a decrease (long-term depression; LTD; Lynch et al., 1977; Dudek and Bear, 1992; Mulkey and Malenka, 1992; see Collingridge et al., 2010 for a review). Thus, Hebbian synaptic plasticity basically maps the neuronal activation onto the synaptic efficacies or rather connectivity (high activity → stronger connections; low activity → weaker connections; Hebb, 1949; Bliss and Lomo, 1973; Dudek and Bear, 1992; Kirkwood et al., 1996). These changes in the connectivity, in turn, influence the neuronal activities. Along these lines, theoretical studies show (Rochester et al., 1956; Riedel and Schild, 1992; Gerstner and Kistler, 2002; Kolodziejski et al., 2010) that Hebbian synaptic plasticity alone induces a positive feedback loop leading to unrestricted synaptic (and thus neuronal) dynamics. On the other hand, homeostatic synaptic plasticity, as synaptic scaling (Turrigiano et al., 1998), act conversely to Hebbian synaptic plasticity. If neuronal activities are high, synaptic efficacies are decreased, while, if activities are low, efficacies are increased (high activity → weaker connections; low activity → stronger connections; Turrigiano et al., 1998; Hou et al., 2008, 2011; Ibata et al., 2008). Thereby, homeostatic synaptic plasticity alone induces a negative feedback loop and, thus, stabilizes the dynamics. As several theoretical results indicate (Tetzlaff et al., 2011; Zenke et al., 2013; Toyoizumi et al., 2014), the combination of both plasticity processes lead to desired, stable dynamics.

                        We will argue in this review that, analogous to functional synaptic plasticity, structural plasticity can also be categorized into two different classes of activity-dependency: (i) One class of structural changes maps features of the neuronal activity onto the connectivity, such that the connectivity is strengthened with high activity levels and vice versa. These changes will be referred to as Hebbian structural plasticity (Hebb, 1949; Helias et al., 2008). (ii) The other class of structural changes weakens (strengthens) the connectivity given high (low) neuronal activities and, thus, stabilizes the dynamics. This class is named homeostatic structural plasticity (Butz et al., 2009).

                        Note, this classification is phenomenological. Changes in connectivity (synaptic as well as structural) are not directly linked to neuronal activity. Neuronal activity initiates such changes by triggering secondary processes as molecular signaling cascades, which lead to the corresponding changes. For the here discussed plasticity processes, these underlying signaling cascades can have different degrees of similarity, which we will not consider in detail. The focus of this review is to systematize the qualitative links between the neuronal activity level and resulting connectivity changes.

                        Moreover, we focus on morphological changes of connections between excitatory neurons only. The dynamics of inhibitory synapses has been reviewed, for instance, by Vogels et al. (2013) for inhibitory synaptic plasticity and by Flores and Méndez (2014) for inhibitory structural plasticity. Further non-synaptic homeostatic mechanisms stabilizing neural network dynamics have been reviewed in Turrigiano and Nelson (2004), Marder and Goaillard (2006), or Yin and Yuan (2014).

                        In the following, as structural and synaptic plasticity are linked to each other, we first briefly outline the main findings for synaptic plasticity. Then, we review the morphological changes of synapses induced by synaptic plasticity and relate these changes to the dynamics of synapses and, thus, to structural plasticity. Following this, we summarize the experimental evidence of activity-dependent structural changes and categorize these, similar to synaptic plasticity, into the two classes of Hebbian and homeostatic structural plasticity. We also briefly review indications of Hebbian and homeostatic processes occurring during development. Finally, we sort theoretical investigations studying the dynamics of structural plasticity by this categorization and, based on their results, arrive at conclusions about the different functional roles of Hebbian and homeostatic structural plasticity.
                        Jo Bowyer
                        Chartered Physiotherapist Registered Osteopath.
                        "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                        Comment


                        • #13
                          Emergent spatial patterns of excitatory and inhibitory synaptic strengths drive somatotopic representational discontinuities and their plasticity

                          in a computational model of primary sensory cortical area 3b

                          http://journal.frontiersin.org/artic...00072/abstract

                          Mechanisms underlying the emergence and plasticity of representational discontinuities in the mammalian primary somatosensory cortical representation of the hand are investigated in a computational model. The model consists of an input lattice organized as a three-digit hand forward-connected to a lattice of cortical columns each of which contains a paired excitatory and inhibitory cell. Excitatory and inhibitory synaptic plasticity of feedforward and lateral connection weights is implemented as a simple covariance rule and competitive normalization. Receptive field properties are computed independently for excitatory and inhibitory cells and compared within and across columns. Within digit representational zones intracolumnar excitatory and inhibitory receptive field extents are concentric, single-digit, small, and unimodal. Exclusively in representational boundary-adjacent zones, intracolumnar excitatory and inhibitory receptive field properties diverge: excitatory cell receptive fields are single-digit, small, and unimodal; and the paired inhibitory cell receptive fields are bimodal, double-digit, and large. In simulated syndactyly (webbed fingers), boundary-adjacent intracolumnar receptive field properties reorganize to within-representation type; divergent properties are reacquired following syndactyly release. This study generates testable hypotheses for assessment of cortical laminar-dependent receptive field properties and plasticity within and between cortical representational zones. For computational studies, present results suggest that concurrent excitatory and inhibitory plasticity may underlie novel emergent properties.
                          Keywords: Somatosensory Cortex, Area 3b, Syndactyly, inhibitory synaptic plasticity, neural plasticity, somatotopy, cortical column, receptive field, emergent properties
                          Jo Bowyer
                          Chartered Physiotherapist Registered Osteopath.
                          "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                          Comment


                          • #14
                            Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates

                            http://journals.plos.org/plosbiology...l.pbio.1002512

                            Abstract

                            Mammals show a wide range of brain sizes, reflecting adaptation to diverse habitats. Comparing interareal cortical networks across brains of different sizes and mammalian orders provides robust information on evolutionarily preserved features and species-specific processing modalities. However, these networks are spatially embedded, directed, and weighted, making comparisons challenging. Using tract tracing data from macaque and mouse, we show the existence of a general organizational principle based on an exponential distance rule (EDR) and cortical geometry, enabling network comparisons within the same model framework. These comparisons reveal the existence of network invariants between mouse and macaque, exemplified in graph motif profiles and connection similarity indices, but also significant differences, such as fractionally smaller and much weaker long-distance connections in the macaque than in mouse. The latter lends credence to the prediction that long-distance cortico-cortical connections could be very weak in the much-expanded human cortex, implying an increased susceptibility to disconnection syndromes such as Alzheimer disease and schizophrenia. Finally, our data from tracer experiments involving only gray matter connections in the primary visual areas of both species show that an EDR holds at local scales as well (within 1.5 mm), supporting the hypothesis that it is a universally valid property across all scales and, possibly, across the mammalian class.
                            Jo Bowyer
                            Chartered Physiotherapist Registered Osteopath.
                            "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                            Comment


                            • #15
                              Different Stages, Different Signals: The Modulating Effect of Cognitive Conflict on Subsequent Processing

                              http://journals.plos.org/plosone/art...l.pone.0163263

                              Abstract

                              The present study used event-related potentials (ERPs) to investigate the function of signals induced by cognitive conflict during the detection stage and the resolution stage of perceptual processing. The study used a combination of the Stroop task and an affective priming task to examine the conflict priming effect when the stimulus onset asynchrony (SOA) was 200 ms or 800 ms. Behavioral results showed that the RTs were shorter for positive targets following congruent primes relative to incongruent primes, and for negative targets following incongruent primes relative to congruent primes when the SOA was 200 ms. ERP results showed that the N2 amplitudes (200–300 ms) for incongruent stimuli were significantly larger than for congruent stimuli in the Stroop task, which indicated a significant conflict effect. Moreover, the N400 amplitudes (500–700 ms) for positive targets after congruent primes were significantly lower than those after incongruent primes when the SOA was 200 ms, which showed a significant negative priming effect. While the SOA was 800 ms, behavioral results showed that the RTs were shorter for positive targets following incongruent primes relative to congruent primes. ERP results showed that the N2 amplitudes (200–300 ms) for incongruent stimuli were significantly larger than for congruent stimuli in the Stroop task, which indicated a significant conflict effect. The N400 amplitudes (1100–1300 ms) for the negative targets after congruent primes were significantly lower than those after incongruent primes when the SOA was 800 ms, which showed a significant positive priming effect. The results demonstrated that the functions of signals induced by cognitive conflict were reversed in two different cognitive processing stages.
                              Cognitive control refers to the human ability to adjust actions and goals in response to external and internal demands during ongoing information processing [1]. In everyday life, for example, if right-handed persons are required to write or eat with their left hand, they would find it difficult to do and they would have to pay more attention to complete the task. In the laboratory, cognitive control is mainly studied by using a conflict-response paradigm, as conflict is a primer for cognitive control processing [2]. Over the past few decades, studies on control did not just involve “cold” cognition, but involved emotional processing and affective adjustments [3, 4]. Evidences from brain imaging researches have shown that the anterior cingulate cortex (ACC) plays a major role in cognitive-control processing [2
                              Jo Bowyer
                              Chartered Physiotherapist Registered Osteopath.
                              "Out beyond ideas of wrongdoing and rightdoing,there is a field. I'll meet you there." Rumi

                              Comment

                              Working...
                              X