Language and memory for object location

In three experiments, we investigated the influence of two types of language on memory for object location: demonstratives (this, that) and possessives (my, your). Participants first read instructions containing demonstratives/possessives to place objects at different locations, and then had to recall those object locations (following object removal). Experiments 1 and 2 tested contrasting predictions of two possible accounts of language on object location memory: the Expectation Model (Coventry, Griffiths, & Hamilton, 2014) and the congruence account (Bonfiglioli, Finocchiaro, Gesierich, Rositani, & Vescovi, 2009). In Experiment 3, the role of attention allocation as a possible mechanism was investigated. Results across all three experiments show striking effects of language on object location memory, with the pattern of data supporting the Expectation Model. In this model, the expected location cued by language and the actual location are concatenated leading to (mis)memory for object location, consistent with models of predictive coding (Bar, 2009; Friston, 2003)

Impaired Representation of Geometric Relationships in Humans with Damage to the Hippocampal Formation

The pivotal role of the hippocampus for spatial memory is well-established. However, while neurophysiological and imaging studies suggest a specialization of the hippocampus for viewpoint-independent or allocentric memory, results from human lesion studies have been less conclusive. It is currently unclear whether disproportionate impairment in allocentric memory tasks reflects impairment of cognitive functions that are not sufficiently supported by regions outside the medial temporal lobe or whether the deficits observed in some studies are due to experimental factors. Here, we have investigated whether hippocampal contributions to spatial memory depend on the spatial references that are available in a certain behavioral context. Patients with medial temporal lobe lesions affecting systematically the right hippocampal formation performed a series of three oculomotor tasks that required memory of a spatial cue either in retinal coordinates or relative to a single environmental reference across a delay of 5000 ms. Stimulus displays varied the availability of spatial references and contained no complex visuo-spatial associations. Patients showed a selective impairment in a condition that critically depended on memory of the geometric relationship between spatial cue and environmental reference. We infer that regions of the medial temporal lobe, most likely the hippocampal formation, contribute to behavior in conditions that exceed the potential of viewpoint-dependent or egocentric representations. Apparently, this already applies to short-term memory of simple geometric relationships and does not necessarily depend on task difficulty or integration of landmarks into more complex representations. Deficient memory of basic geometric relationships may represent a core deficit that contributes to impaired performance in allocentric spatial memory tasks

Language and perceptual categorisation

In a pioneering set of experiments, Rosch investigated the colour processing of a remote traditional culture. It was concluded that colours form universally natural and salient categories. However, our own cross-cultural research, backed up by neuropsychological data and interference studies, indicates that perceptual categories are derived from the words in the speaker's language. The new data support a rather strong version of the Whorfian view that perceptual categories are organized by the linguistic systems of our mind

Processing Ordinality and Quantity: The Case of Developmental Dyscalculia

In contrast to quantity processing, up to date, the nature of ordinality has received little attention from researchers despite the fact that both quantity and ordinality are embodied in numerical information. Here we ask if there are two separate core systems that lie at the foundations of numerical cognition: (1) the traditionally and well accepted numerical magnitude system but also (2) core system for representing ordinal information. We report two novel experiments of ordinal processing that explored the relation between ordinal and numerical information processing in typically developing adults and adults with developmental dyscalculia (DD). Participants made “ordered” or “non-ordered” judgments about 3 groups of dots (non-symbolic numerical stimuli; in Experiment 1) and 3 numbers (symbolic task: Experiment 2). In contrast to previous findings and arguments about quantity deficit in DD participants, when quantity and ordinality are dissociated (as in the current tasks), DD participants exhibited a normal ratio effect in the non-symbolic ordinal task. They did not show, however, the ordinality effect. Ordinality effect in DD appeared only when area and density were randomized, but only in the descending direction. In the symbolic task, the ordinality effect was modulated by ratio and direction in both groups. These findings suggest that there might be two separate cognitive representations of ordinal and quantity information and that linguistic knowledge may facilitate estimation of ordinal information

A New Architecture for Deriving Dynamic Brain-Machine Interfaces

Abstract. Great potential exists for future Brain Machine Interfaces (BMIs) to help paralyzed patients, and others with motor disabilities, regain (artificial) motor control and autonomy. This paper describes a novel approach towards the development of new design architectures and research test-beds for advanced BMIs. It addresses a critical design challenge in deriving the functional mapping between the subject’s movement intent and actuated behavior. Currently, adaptive signal processing techniques are used to correlate neuronal modulation with known movements generated by the subject. However, with patients who are paralyzed, access to the individual’s movement is unavailable. Inspired by motor control research, this paper considers a predictive framework for BMI using multiple adaptive models trained with supervised or reinforcement learning in a closed-loop architecture that requires real-time feedback. Here, movement trajectories can be inferred and incrementally updated using instantaneous knowledge of the movement target and the individual’s current neuronal activation. In this framework, BMIs require a computing infrastructure capable of selectively executing multiple models on the basis of signals received by and/or provided to the brain in real time. Middleware currently under investigation to provide this data-driven dynamic capability is discussed.