Current Opinion In Neurobiology Research Articles

Has multiple trace theory been refuted?

Multiple trace theory (Nadel & Moscovitch, Current Opinion in Neurobiology, 1997, 7, 217-227) has proven to be one of the most novel and influential recent memory theories, and played an essential role in shifting perspective on systems-level memory consolidation. Here, we briefly review its impact and testable predictions and focus our discussion primarily on nonhuman animal experiments. Perhaps, the most often supported claim is that episodic memory tasks should exhibit comparable severity of retrograde amnesia (RA) for recent and remote memories after extensive damage to the hippocampus (HPC). By contrast, there appears to be little or no experimental support for other core predictions, such as temporally limited RA after extensive HPC damage in semantic memory tasks, temporally limited RA for episodic memories after partial HPC damage, or the existence of storage of multiple HPC traces with repeated reactivations. Despite these shortcomings, it continues to be a highly cited HPC memory theory.

A computationally implemented mechanistic account of post-stroke aphasia recovery

A computationally implemented mechanistic account of post-stroke aphasia recovery

A Functional Connectivity Analysis Toolbox for Multiple Spike Trains Data: �ToolConnect�

A Functional Connectivity Analysis Toolbox for Multiple Spike Trains Data: �ToolConnect�

Measuring self-disgust in patients with Parkinson's disease: An emotion induction paradigm using the Skin Conductance Response (GSR)

Measuring self-disgust in patients with Parkinson's disease: An emotion induction paradigm using the Skin Conductance Response (GSR)

Music-based rehabilitation in cochlear implant users: Insights from brain-plasticity research

Music-based rehabilitation in cochlear implant users: Insights from brain-plasticity research

Dissociating contributions of ACC and vmPFC in reward prediction, outcome, and choice

Acting in an uncertain environment requires estimating the probability and the value of potential outcomes. These computations are typically ascribed to various parts of the medial prefrontal cortex (mPFC), but the functional architecture of this region remains debated. The anterior cingulate cortex (ACC) encodes reward prediction and outcome (i.e. win vs lose, Silvetti, Seurinck, & Verguts, 2013. Cortex, 49(6), 1627–35. doi:10.1016/j.cortex.2012.05.008). An outcome-related value signal has also been reported in the ventromedial Prefrontal Cortex (vmPFC, Rangel & Hare, 2010. Current Opinion in Neurobiology, 20(2), 262–70. doi:10.1016/j.conb.2010.03.001). Whether a functional dissociation can be traced in these regions with respect to reward prediction and outcome has been suggested but not rigorously tested. Hence an fMRI study was designed to systematically examine the contribution of ACC and vmPFC to reward prediction and outcome. A striking dissociation was identified, with ACC coding for positive prediction errors and vmPFC responding to outcome, irrespective of probability. Moreover, ACC has been assigned a crucial role in the selection of intentional actions (decision-making) and computing the value associated to these actions (action-based value). Conversely, vmPFC seems to implement stimulus-based value processing (Rudebeck et al., 2008. Journal of Neuroscience, 28(51), 13775–85. doi:10.1523/JNEUROSCI.3541-08.2008; Rushworth, Behrens, Rudebeck, & Walton, 2007. Trends in Cognitive Sciences, 11(4), 168–76. doi:10.1016/j.tics.2007.01.004). Therefore, a decision-making factor (choice vs. no choice condition) was also implemented in the present paradigm to distinguish stimulus-based versus action-based value coding in the mPFC during both decision and outcome phase. We found that vmPFC was more activated during the outcome phase in the no-choice than in the choice condition, potentially confirming the role of this area in stimulus-based (more than action-based) value processing.

How We Learn to Make Decisions: Rapid Propagation of Reinforcement Learning Prediction Errors in Humans

Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. E., Pierce, L. J., Holroyd, C. B., & Tanaka, J. W. Learning to become an expert: Reinforcement learning and the acquisition of perceptual expertise. Journal of Cognitive Neuroscience, 21, 1833-1840, 2009; Bayer, H. M., & Glimcher, P. W. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141, 2005; O'Doherty, J. P. Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology, 14, 769-776, 2004; Holroyd, C. B., & Coles, M. G. H. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709, 2002]. Here, we used the brain ERP technique to demonstrate that not only do rewards elicit a neural response akin to a prediction error but also that this signal rapidly diminished and propagated to the time of choice presentation with learning. Specifically, in a simple, learnable gambling task, we show that novel rewards elicited a feedback error-related negativity that rapidly decreased in amplitude with learning. Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward prediction errors and the changes in amplitude of these prediction errors at the time of choice presentation and reward delivery. Our results provide further support that the computations that underlie human learning and decision-making follow reinforcement learning principles.

Morphological changes associated with the genesis and development of an excitatory glutemergic synapse: An integrated framework model

Morphological changes associated with the genesis and development of an excitatory glutemergic synapse: An integrated framework model

Growth and development of the postsynaptic active region of an excitatory glutemergic synapse: An integrated model

Growth and development of the postsynaptic active region of an excitatory glutemergic synapse: An integrated model

Colavita dominance effect revisited: the effect of semantic congruity

To investigate the effect of semantic congruity on audiovisual target responses, participants detected a semantic concept that was embedded in a series of rapidly presented stimuli. The target concept appeared as a picture, an environmental sound, or both; and in bimodal trials, the audiovisual events were either consistent or inconsistent in their representation of a semantic concept. The results showed faster detection latencies to bimodal than to unimodal targets and a higher rate of missed targets when visual distractors were presented together with auditory targets, in comparison to auditory targets presented alone. The findings of Experiment 2 showed a cross-modal asymmetry, such that visual distractors were found to interfere with the accuracy of auditory target detection, but auditory distractors had no effect on either the speed or the accuracy of visual target detection. The biased-competition theory of attention (Desimone & Duncan Annual Review of Neuroscience 18: 1995; Duncan, Humphreys, & Ward Current Opinion in Neurobiology 7: 255-261 1997) was used to explain the findings because, when the saliency of the visual stimuli was reduced by the addition of a noise filter in Experiment 4, visual interference on auditory target detection was diminished. Additionally, the results showed faster and more accurate target detection when semantic concepts were represented in a visual rather than an auditory format.

Mojo 2.0: Connectome Annotation Tool

Mojo 2.0: Connectome Annotation Tool

Human like trajectories for humanoid robots

Human like trajectories for humanoid robots

Understanding the mathematics of hearing using electronic circuits

The human cochlea is a fascinating transduction organ that illustrates the ingenious way in which engineering problems are solved in nature. A healthy cochlea has a dynamic range in the order of~120\,dB; that is, the difference between the roar of the engines of a Boeing~747 and the faintest whisper. We discuss the recent assertion that the cochlea is governed by the dynamics of a Hopf bifurcation. In our cochlea model we discretise the basilar membrane into resonant sections with logarithmically decreasing characteristic frequencies. We show that the observed active behaviour of the cochlea can be modelled as a change in the quality factor of the individual resonant sections in a discretised model, and that this has dynamics which embody the Hopf bifurcation. References S. Camalet, T. Duke, F. Julicher, and J. Prost, Auditory Sensitivity Provided by Self-Tuned Critical Oscillations of Hair Cells. Proceedings of the National Academy of Sciences of the United States of America 97, 2000, pp. 3183--3188. V. M. Eguiluz, M. Ospeck, Y. Choe, A. J. Hudspeth, and M. O. Magnasco, Essential Nonlinearities in Hearing. Physical Review Letters 84, 2000, 5232--5235. E. Fragniere, Analogue VLSI Emulation of the Cochlea, Doctoral Thesis, Departement d'electricite, EPFL, Lausanne, 1998. http://library.epfl.ch/en/theses/?nr=1796 T. J. Hamilton, C. Jin, A. van Schaik, and J. Tapson, An Active 2-D Silicon Cochlea. Biomedical Circuits and Systems, IEEE Transactions on 2, 2008, 30--43. T. J. Hamilton, J. Tapson, C. Jin, and A. van Schaik, Analogue VLSI implementations of two dimensional, nonlinear, active cochlea models, Biomedical Circuits and Systems Conference, 2008. IEEE, 2008, pp. 153--156. A. Kern, J.-J. van der Vyver, and R. Stoop, Towards a biomorphic silicon Hopf cochlea, Proceedings of the 10th IEEE conference on nonlinear dynamics of electronic systems, 2, 2002. A. Kern, and R. Stoop, Essential Role of Couplings between Hearing Nonlinearities, Physical Review Letters 91 (12) 2003, 128101. M. O. Magnasco, A Wave Traveling over a Hopf Instability Shapes the Cochlear Tuning Curve, Physical Review Letters 90 (5) 2003, 058101. C. J. Plack, The Sense of Hearing, Lawrence Erlbaum Associates, Inc., New Jersey, 2005. M. A. Ruggero, Responses to sound of the basilar membrane of the mammalian cochlea. Current Opinion in Neurobiology 2, 1992, 449--456. S. H. Strogatz, Nonlinear Dynamics and Chaos, Westview Press, Cambridge, 1994. J. Tapson, T. J. Hamilton, C. Jin, and A. van Schaik, Self-Tuned Regenerative Amplification and the Hopf Bifurcation, IEEE International Symposium on Circuits and Systems (ISCAS), Seattle, USA, 2008. A. van Schaik, and E. Fragniere, Pseudo-voltage domain implementation of a 2-dimensional silicon cochlea, International Symposium on Circuits and Systems (ISCAS), Sydney, Australia, 2001, pp. 185--188 vol. 2 doi:10.1109/ISCAS.2001921277

Human Motor Behavior

Human Motor Behavior

Topographical, Autobiographical and Semantic Memory in a Patient with Bilateral Mesial Temporal and Retrosplenial Infarction

According to Consolidation Theory (Squire, 1992, Psychological Review, 99, 195; Squire & Alvarez, 1995, Current Opinion in Neurobiology, 5, 169), the mesial temporal lobes have a time-limited role in the maintenance, storage and retrieval of retrograde declarative memories, such that they are not necessary for recalling remote memories. In contrast, proponents of the Multiple Trace Theory (Fuji, Moscovitch, & Nadel, 2000, Handbook of neuropsychology, 2nd ed., p 223, Amsterdam, New York: Elsevier; Nadel & Moscovitch, 1999, Current Opinion in Neurobiology, 7, 217) posit that the mesial temporal lobe (MTL) is necessary for remembering detailed autobiographical and topographical material from all time periods. A third theory of hippocampal function, the Cognitive Map Theory (O'Keefe & Nadel, 1978, The hippocampus as a cognitive map. Oxford: Clarendon), states that the hippocampus is involved in the processing of allocentric spatial representations. The precise role of the MTL in remote memory has been difficult to elucidate, as the majority of studies present cases with widespread brain damage that often occurred many years prior to testing. We investigated retrograde autobiographical, semantic and topographical memories in a subject (SG) who had recently sustained infarctions confined to the MTL and retrosplenial region bilaterally. Inconsistent with the predictions of Cognitive Map Theory, memory for spatial maps that were learned in the past was preserved. Additional testing indicated that SG suffered from a landmark agnosia, which affected remotely and recently acquired information equally. SG was also poor at imagining which direction he would have to turn his body to move from one landmark to another. In accordance with Consolidation Theory, SG performed similarly to control subjects for remote time periods on various measures of retrograde autobiographical memory and demonstrated intact knowledge regarding famous faces and vocabulary terms that were acquired in the past. In contrast, memory for remote public events was impaired. The current findings indicate that the mesial temporal and/or retrosplenial regions have little role to play in memory for remotely acquired spatial maps, autobiographical memories, famous faces or vocabulary terms. However, the findings for landmark naming, directional calculations between landmarks and knowledge of public events suggest that the MTL and/or retrosplenial cortices remain important for accessing these types of memories indefinitely.

The rhythm aftereffect: Support for time sensitive neurons with broad overlapping tuning curves

Ivry [Ivry, R. B. (1996). The representation of temporal information in perception and motor control. Current Opinion in Neurobiology, 6, 851–857.] proposed that explicit coding of brief time intervals is accomplished by neurons that are tuned to a preferred temporal interval and have broad overlapping tuning curves. This proposal is analogous to the orientation selective cells in visual area V1. To test this proposal, we used a temporal analog to the visual tilt aftereffect. After adapting to a fast auditory rhythm, a moderately fast test rhythm (400 ms between beats) seemed slow and vice versa. If the speed of the adapting rhythm was made too disparate from speed of the test rhythm the effect was diminished. The effect occurred whether the adapting and test stimuli were presented to the same or different ears, but did not occur when an auditory adapting rhythm was followed by a visual test rhythm. Results support the proposition that explicit time information is coded by neural units tuned to specific temporal intervals with broad overlapping tuning curves. In addition, it appears that there is a single timing mechanism for each incoming sensory mode, but distinct timers for different modes.

New Thinking on Neurodevelopment

The notion that some substances in the environment can damage the nervous system has an ancient history. The neurotoxicity of lead was recognized more than 2,000 years ago by the Greek physician Dioscerides, who wrote, “Lead makes the mind give way.” In the intervening millennia many other substances have been added to the list of known or suspected neurotoxicants. Despite this accumulation of knowledge, there is still much that isn’t understood about how neurotoxicants affect the developing brain, especially the effects of low-dose exposures. Today researchers are taking a hard look at low-dose exposures in utero and during childhood to unravel some of the mysteries of impaired neurodevelopment. About 17% of school-age children in the United States suffer from a disability that affects their behavior, memory, or ability to learn, according to a study published in the March 1994 issue of Pediatrics by a team from the Centers for Disease Control and Prevention (CDC). The list of maladies includes attention deficit/hyperactivity disorder (ADHD), autistic spectrum disorders, epilepsy, Tourette syndrome, and less specific conditions such as mental retardation and cerebral palsy. All are believed to be the outcome of some abnormal process that unfolded as the brain was developing in utero or in the young child. These disorders have an enormous impact on families and society. According to the 1996 book Learning Disabilities: Lifelong Issues, children with these disorders have higher rates of mental illness and suicide, and are more likely to engage in substance abuse and to commit crimes as adults. The overall economic cost of neurodevelopmental disorders in the United States is estimated to be $81.5–167 billion per year, according to a report published in the December 2001 issue of EHP Supplements. Potentially even more disturbing is that a number of epidemiologic studies suggest that the incidence of certain disorders is on the rise. In the United States, the diagnosis of autistic spectrum disorders increased from 4–5 per 10,000 children in the 1980s to 30–60 per 10,000 children in the 1990s, according to a report in the August 2003 Journal of Autism and Developmental Disorders. Similarly, notes a report in the February 2002 issue of CNS Drugs, the diagnosis of ADHD grew 250% between 1990 and 1998. The number of children in special education programs classified with learning disabilities increased 191% between 1977 and 1994, according to an article in Advances in Learning and Behavioral Disabilities, Volume 12, published in 1998. So what is going on? The short answer is that no one really knows. There’s not even consensus on what the soaring rates actually mean. Heightened public awareness could account for the surge in the numbers, or it may be that physicians are getting better at diagnosing the conditions. Some autism researchers believe the rise in that condition’s prevalence simply reflects changes in diagnostic criteria over the last 25 years. On the other hand, some scientists believe that the rates of neurodevelopmental disease are truly increasing, and that the growing burden of chemicals in the environment may play a role. With that in mind, investigators are considering the effects of gene–environment interactions. A child with a mild genetic tendency toward a neurodevelopmental disorder might develop without clinically measurable abnormalities in the absence of environmental “hits.” However, children in industrialized nations develop and grow up in a veritable sea of xenobiotic chemicals, says Isaac Pessah, director of the University of California, Davis, Center for Children’s Environmental Health and Disease Prevention. “Fortunately,” he says, “most of us have a host of defense mechanisms that protect us from adverse outcomes. However, genetic polymorphisms, complex epistasis, and cytogenetic abnormalities could weaken these defenses and amplify chemical damage, initiating a freefall into a clinical syndrome.” Pessah cites the example of autism. He says susceptibility for autism is likely conferred by several defective genes, no one of which can account for all the core symptoms of social disinterest, repetitive and overly focused behaviors, and problems in communication. Could multiple genetic liabilities and exposure to a chemically complex environment act in concert to increase the incidence and severity of the condition? Despite the uncertainties, many scientists believe it would be wise to err on the side of caution when it comes to a research agenda. As Martha Herbert, a pediatric neurologist at Harvard Medical School, puts it, “Even though we may have neither consensus nor certainty about an autism epidemic, there are enough studies coming in with higher numbers that we should take it seriously. Environmental hypotheses ought to be central to research now. The physiological systems that have been harmed by environmental factors may also point to treatment targets, and this might be a great way to help the children.”

Face processing in humans is compatible with a simple shape–based model of vision

Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence, a general class of recognition models has emerged, which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity. However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ 'featurally' are much easier to distinguish when inverted than those that differ 'configurally'; a finding that is difficult to reconcile with the physiological models. Here, we show that after controlling for subjects' expectations, there is no difference between 'featurally' and 'configurally' transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in the cortex.

Visual impairment in infancy: impact on neurodevelopmental and neurobiological processes

Visual impairment in infancy: impact on neurodevelopmental and neurobiological processes

Cognitive neuroscience

A selection of World Wide Web sites relevant to papers published in this issue of Current Opinion in Neurobiology.