Mutations in LOXHD1 gene can cause auditory neuropathy spectrum disorder.

Objectives: The aim of this paper was to study the auditory phenotype of three related children with sensorineural hearing loss (2 sisters and their cousin) following genetic analysis revealing mutations in LOXHD1. Methods: Genetic testing was conducted on three related children. They were assessed with a standard clinical test battery including distortion otoacoustic emissions, auditory brainstem responses and audiometry. Results: We identified heterozygous variants in LOXHD1 in a family of Irish/German and Italian/Irish ancestry with autosomal recessive auditory neuropathy spectrum disorder (ANSD). Mutations in LOXHD1 (MIM #613072) have been linked to an autosomal recessive nonsyndromic hearing loss (DFNB77), mapped to the locus 18q12-q21. All three subjects had evidence of some, albeit few, functioning cochlear hair cells as revealed by the presence of a cochlear microphonic and/or partial otoacoustic emissions early in life. Conclusion: To our knowledge, this is the first association between LOXHD1 mutations and ANSD in two patients who have been successfully managed with cochlear implants.

New semantic learning in patients with large medial temporal lobe lesions.

Two patients with large lesions of the medial temporal lobe were given four tests of semantic knowledge that could only have been acquired after the onset of their amnesia. In contrast to previous studies of postmorbid semantic learning, correct answers could be based on a simple, nonspecific sense of familiarity about single words, faces, or objects. According to recent computational models (for example, Norman and O'Reilly (2003) Psychol Rev 110:611-646), this characteristic should be optimal for detecting the kind of semantic learning that might be supported directly by the neocortex. Both patients exhibited some capacity for new learning, albeit at a level substantially below control performances. Notably, the correct answers appeared to reflect declarative memory. It was not the case that the correct answers simply popped out in some automatic way in the absence of any additional knowledge about the items. Rather, the few correct choices made by the patients tended to be accompanied by additional information about the chosen items, and the available knowledge appeared to be similar qualitatively to the kind of factual knowledge that healthy individuals gradually acquire over the years. The results are consistent with the idea that neocortical structures outside the medial temporal lobe are able to support some semantic learning, albeit to a very limited extent. Alternatively, the small amount of learning detected in the present study could depend on tissue within the posterior medial temporal lobe that remains intact in both patients.

Banishing the homunculus: making working memory work.

The prefrontal cortex has long been thought to subserve both working memory and "executive" function, but the mechanistic basis of their integrated function has remained poorly understood, often amounting to a homunculus. This paper reviews the progress in our laboratory and others pursuing a long-term research agenda to deconstruct this homunculus by elucidating the precise computational and neural mechanisms underlying these phenomena. We outline six key functional demands underlying working memory, and then describe the current state of our computational model of the prefrontal cortex and associated systems in the basal ganglia (BG). The model, called PBWM (prefrontal cortex, basal ganglia working memory model), relies on actively maintained representations in the prefrontal cortex, which are dynamically updated/gated by the basal ganglia. It is capable of developing human-like performance largely on its own by taking advantage of powerful reinforcement learning mechanisms, based on the midbrain dopaminergic system and its activation via the basal ganglia and amygdala. These learning mechanisms enable the model to learn to control both itself and other brain areas in a strategic, task-appropriate manner. The model can learn challenging working memory tasks, and has been corroborated by several important empirical studies.

Under what conditions is recognition spared relative to recall after selective hippocampal damage in humans?

The claim that recognition memory is spared relative to recall after focal hippocampal damage has been disputed in the literature. We examined this claim by investigating object and object-location recall and recognition memory in a patient, YR, who has adult-onset selective hippocampal damage. Our aim was to identify the conditions under which recognition was spared relative to recall in this patient. She showed unimpaired forced-choice object recognition but clearly impaired recall, even when her control subjects found the object recognition task to be numerically harder than the object recall task. However, on two other recognition tests, YR's performance was not relatively spared. First, she was clearly impaired at an equivalently difficult yes/no object recognition task, but only when targets and foils were very similar. Second, YR was clearly impaired at forced-choice recognition of object-location associations. This impairment was also unrelated to difficulty because this task was no more difficult than the forced-choice object recognition task for control subjects. The clear impairment of yes/no, but not of forced-choice, object recognition after focal hippocampal damage, when targets and foils are very similar, is predicted by the neural network-based Complementary Learning Systems model of recognition. This model postulates that recognition is mediated by hippocampally dependent recollection and cortically dependent familiarity; thus hippocampal damage should not impair item familiarity. The model postulates that familiarity is ineffective when very similar targets and foils are shown one at a time and subjects have to identify which items are old (yes/no recognition). In contrast, familiarity is effective in discriminating which of similar targets and foils, seen together, is old (forced-choice recognition). Independent evidence from the remember/know procedure also indicates that YR's familiarity is normal. The Complementary Learning Systems model can also accommodate the clear impairment of forced-choice object-location recognition memory if it incorporates the view that the most complete convergence of spatial and object information, represented in different cortical regions, occurs in the hippocampus.

Generalization in interactive networks: the benefits of inhibitory competition and Hebbian learning.

Computational models in cognitive neuroscience should ideally use biological properties and powerful computational principles to produce behavior consistent with psychological findings. Error-driven backpropagation is computationally powerful and has proven useful for modeling a range of psychological data but is not biologically plausible. Several approaches to implementing backpropagation in a biologically plausible fashion converge on the idea of using bidirectional activation propagation in interactive networks to convey error signals. This article demonstrates two main points about these error-driven interactive networks: (1) they generalize poorly due to attractor dynamics that interfere with the network's ability to produce novel combinatorial representations systematically in response to novel inputs, and (2) this generalization problem can be remedied by adding two widely used mechanistic principles, inhibitory competition and Hebbian learning, that can be independently motivated for a variety of biological, psychological, and computational reasons. Simulations using the Leabra algorithm, which combines the generalized recirculation (GeneRec), biologically plausible, error-driven learning algorithm with inhibitory competition and Hebbian learning, show that these mechanisms can result in good generalization in interactive networks. These results support the general conclusion that cognitive neuroscience models that incorporate the core mechanistic principles of interactivity, inhibitory competition, and error-driven and Hebbian learning satisfy a wider range of biological, psychological, and computational constraints than models employing a subset of these principles.

Conjunctive representations in learning and memory: principles of cortical and hippocampal function.

The authors present a theoretical framework for understanding the roles of the hippocampus and neocortex in learning and memory. This framework incorporates a theme found in many theories of hippocampal function: that the hippocampus is responsible for developing conjunctive representations binding together stimulus elements into a unitary representation that can later be recalled from partial input cues. This idea is contradicted by the fact that hippocampally lesioned rats can learn nonlinear discrimination problems that require conjunctive representations. The authors' framework accommodates this finding by establishing a principled division of labor, where the cortex is responsible for slow learning that integrates over multiple experiences to extract generalities whereas the hippocampus performs rapid learning of the arbitrary contents of individual experiences. This framework suggests that tasks involving rapid, incidental conjunctive learning are better tests of hippocampal function. The authors implement this framework in a computational neural network model and show that it can account for a wide range of data in animal learning.

Creating a stable tympanic membrane perforation using mitomycin C.

OBJECTIVE: To determine the ability of topically applied mitomycin C to create a stable tympanic membrane perforation. STUDY DESIGN AND SETTING: Twenty-four rats underwent subtotal removal of the tympanic membranes bilaterally. Forty ears received 0.2 mg/ml of mitomycin C. The remaining 8 received phosphate-buffered saline solution (control). Photographs taken every 3 to 5 days for 44 days were digitally scanned and computer analyzed to calculate the percentage of residual perforation. Application of solutions, photography, and data analysis were performed in a blinded fashion. RESULTS: The mitomycin C treated ears had delayed closure time and healing rate (from day 0 to 25) compared to the control group. All controls healed by day 14. By day 44, 92.5% of the mitomycin C treated ears healed. CONCLUSION: Mitomycin C prolongs the closure and healing rate of myringotomies in rat tympanic membranes. SIGNIFICANCE: Myringotomy with concurrent mitomycin C application may be useful for creating an animal model for chronic tympanic membrane perforation and should be tested in human beings as a method to maintain myringotomy patency for long-term ventilation.

Visual representation in the wild: how rhesus monkeys parse objects.

Visual object representation was studied in free-ranging rhesus monkeys. To facilitate comparison with humans, and to provide a new tool for neurophysiologists, we used a looking time procedure originally developed for studies of human infants. Monkeys' looking times were measured to displays with one or two distinct objects, separated or together, stationary or moving. Results indicate that rhesus monkeys used featural information to parse the displays into distinct objects, and they found events in which distinct objects moved together more novel or unnatural than events in which distinct objects moved separately. These findings show both commonalities and contrasts with those obtained from human infants. We discuss their implications for the development and neural mechanisms of higher-level vision.

Conjunctive representations, the hippocampus, and contextual fear conditioning.

The context in which events occur can be represented as both (1) a set of independent features, the feature representation view, and (2) a set of features bound into a unitary representation, the conjunction representation view. It is assumed that extrahippocampal (e.g., neocortical) areas provide a basis for feature representations, but the hippocampal formation makes an essential contribution to the automatic storage of conjunctive representations. We develop this dual-representation view and explore its implications for hippocampal contributions to contextual fear conditioning processes. To this end, we discuss how our framework can resolve some of the conflicts in the recent literature relating the hippocampus to contextual fear conditioning. We also present new data supporting the role of a key mechanism afforded by conjunctive representations--pattern completion (the ability of a subset of a memory pattern to activate the complete memory)--in contextual fear conditioning. As is implied by this mechanism, we report that fear can be conditioned to the memory representation of a context that is not actually present at the time of shock. Moreover, this result is predicted by our computational model of cortical and hippocampal function. We suggest that pattern completion demonstrated in animals and by our model provides a mechanistic bridge to human declarative memory.

Interactions between frontal cortex and basal ganglia in working memory: a computational model.

The frontal cortex and the basal ganglia interact via a relatively well understood and elaborate system of interconnections. In the context of motor function, these interconnections can be understood as disinhibiting, or "releasing the brakes," on frontal motor action plans: The basal ganglia detect appropriate contexts for performing motor actions and enable the frontal cortex to execute such actions at the appropriate time. We build on this idea in the domain of working memory through the use of computational neural network models of this circuit. In our model, the frontal cortex exhibits robust active maintenance, whereas the basal ganglia contribute a selective, dynamic gating function that enables frontal memory representations to be rapidly updated in a task-relevant manner. We apply the model to a novel version of the continuous performance task that requires subroutine-like selective working memory updating and compare and contrast our model with other existing models and theories of frontal-cortex-basal-ganglia interactions.

Computational principles of learning in the neocortex and hippocampus.

We present an overview of our computational approach towards understanding the different contributions of the neocortex and hippocampus in learning and memory. The approach is based on a set of principles derived from converging biological, psychological, and computational constraints. The most central principles are that the neocortex employs a slow learning rate and overlapping distributed representations to extract the general statistical structure of the environment, while the hippocampus learns rapidly, using separated representations to encode the details of specific events while suffering minimal interference. Additional principles concern the nature of learning (error-driven and Hebbian), and recall of information via pattern completion. We summarize the results of applying these principles to a wide range of phenomena in conditioning, habituation, contextual learning, recognition memory, recall, and retrograde amnesia, and we point to directions of current development.

Effectiveness of the particle repositioning maneuver in subtypes of benign paroxysmal positional vertigo.

OBJECTIVES: To assess the efficacy of the particle repositioning maneuver (PRM) in patients presenting with idiopathic benign paroxysmal positional vertigo (BPPV) compared with those with evidence of additional peripheral vestibulopathies. METHODS: Retrospective administration of the Dizziness Handicap Inventory (DHI) to 41 patients with primary BPPV and 31 patients with secondary BPPV to subjectively evaluate their symptoms before and after the PRM. RESULTS: Both groups indicated a marked improvement in symptoms after the PRM. Only two patients reported an increase in their symptoms after the PRM and both had secondary BPPV. CONCLUSIONS: The PRM was found to be highly effective in all forms of BPPV, but careful history and judicious testing may identify patients requiring additional intervention to relieve their symptoms.

Graded effects in hierarchical figure-ground organization: reply to Peterson (1999).

An important issue in vision research concerns the order of visual processing. S. P. Vecera and R. C. O'Reilly (1998) presented an interactive, hierarchical model that placed figure-ground segregation prior to object recognition. M. A. Peterson (1999) critiqued this model, arguing that because it used ambiguous stimulus displays, figure-ground processing did not precede object processing. In the current article, the authors respond to Peterson's (1999) interpretation of ambiguity in the model and her interpretation of what it means for figure-ground processing to come before object recognition. The authors argue that complete stimulus ambiguity is not critical to the model and that figure-ground precedes object recognition architecturally in the model. The arguments are supported with additional simulation results and an experiment, demonstrating that top-down inputs can influence figure-ground organization in displays that contain stimulus cues.

Contextual fear conditioning, conjunctive representations, pattern completion, and the hippocampus.

Impaired contextual fear conditioning produced by damage to the hippocampus has been attributed to the loss of a conjunctive representation of the features of the context. There is, however, no direct evidence that conjunctive representations contribute to contextual fear conditioning. These experiments addressed this issue and found support for the conjunctive representation view. Two results made this point: (a) Preexposure to the conditioning context, but not to its separable features, facilitated contextual fear conditioning, and (b) generalization of fear conditioning to similar contexts was enhanced by preexposure to the context used to test for generalization. These results are interpreted as pattern completion to the preexposed context during the conditioning episode. They support the view that a conjunctive representation of context plays an important role in contextual fear conditioning and that the impairments produced by damage to the hippocampus result from the loss of this conjunctive contribution.

Figure-ground organization and object recognition processes: an interactive account.

Traditional bottom-up models of visual processing assume that figure-ground organization precedes object recognition. This assumption seems logically necessary: How can object recognition occur before a region is labeled as figure? However, some behavioral studies find that familiar regions are more likely to be labeled figure than less familiar regions, a problematic finding for bottom-up models. An interactive account is proposed in which figure-ground processes receive top-down input from object representations in a hierarchical system. A graded, interactive computational model is presented that accounts for behavioral results in which familiarity effects are found. The interactive model offers an alternative conception of visual processing to bottom-up models.

Six principles for biologically based computational models of cortical cognition.

This review describes and motivates six principles for computational cognitive neuroscience models: biological realism, distributed representations, inhibitory competition, bidirectional activation propagation, error-driven task learning, and Hebbian model learning. Although these principles are supported by a number of cognitive, computational and biological motivations, the prototypical neural-network model (a feedforward back-propagation network) incorporates only two of them, and no widely used model incorporates all of them. It is argued here that these principles should be integrated into a coherent overall framework, and some potential synergies and conflicts in doing so are discussed.