The hippocampus and related structures are thought to be capable of 1) representing cortical activity in a way that minimizes overlap of the representations assigned t ~ different cortical patterns (pattern separation); and 2) modifying synaptic connections so that these representations can later be reinstated from partial or noisy versions of the cortical activity pattern that was present at the time of storage (pattern completion). We point out that there is a trade-off between pattern separation and completion and propose that the unique anatomical and physiological properties of the hippocampus might serve to minimize this trade-off. We use analytical methods to determine quantitative estimates of both separation and completion for specified parameterized models of the hippocampus. These estimates are then used to evaluate the role of various properties and of the hippocampus, such as the activity levels seen in different hippocampal regions, synaptic potentiation and depression, the multi-layer connectivity of the system, and the relatively focused and strong mossy fiber projections. This analysis is focused on the feedforward pathways from the entorhinal cortex (EC) to the dentate gyrus (DG) and region CA3. Among our results are the following: 1) Hebbian synaptic modification (LTP) facilitates completion but reduces separation, unless the

We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, the network learned to recognize ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalization capa- bility. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.

Brain metabolic mapping techniques, such as positron emis-sion tomography (PET), can provide information about the functional interactions within entire neural systems. With the large quantity of data that can accumulate from a mapping study, a network analysis, which makes sense of the com-plex interactions among neural elements, is necessary. A network analysis was performed on data obtained from a PET study that examined both the changes in regional ce-rebral blood flow (rCBF) and interregional correlations among human cortical areas during performance of an object vision (face matching) and spatial vision (dot-location matching) task. Brain areas for the network were selected based on regions showing significant rCBF or interregional correla-tions between tasks. Anterior temporal and frontal lobe regions were added to the network using a principal com-

Objectives: The time series of single trial cortical evoked potentials typically have a random appearance, and their trial-to-trial variability is commonly explained by a model in which random ongoing background noise activity is linearly combined with a stereotyped evoked response. In this paper, we demonstrate that more realistic models, incorporating amplitude and latency variability of the evoked response itself, can explain statistical properties of cortical potentials that have often been attributed to stimulus-related changes in functional connectivity or other intrinsic neural parameters.

Patients with damage to left anteromedial temporal cortex often show a striking deficit: they fail to recognize animals and other living things. This failure of recognition presents an important challenge to theories of the neural representation of conceptual knowledge. Here we propose that this lesion--behaviour association arises because polymodal neurons in anteromedial temporal cortex integrate simple features into complex feature conjunctions, providing the neural infrastructure for differentiating among objects.

Different neuropsychological populations implicate diverse cortical regions in semantic memory: semantic dementia (SD) is characterized by atrophy of the anterior temporal lobes whilst poor comprehension in stroke aphasia is associated with prefrontal or temporal–parietal infarcts. This study employed a case-series design to compare SD and comprehension-impaired stroke aphasic patients directly on the same battery of semantic tests. Although the two groups obtained broadly equivalent scores, they showed qualitatively different semantic deficits. The SD group showed strong correlations between different semantic tasks—regardless of input/ output modality—and substantial consistency when a set of items was assessed several times. They were also highly sensitive to frequency/familiarity and made coordinate and superordinate semantic errors in picture naming. These findings support the notion that amodal semantic representations degrade in SD. The stroke aphasia group also showed multimodal deficits and consistency across different input modalities, but inconsistent performance on tasks requiring different types of semantic processing. They were insensitive to familiarity/frequency—instead, tests of semantic association were influenced by the ease with which relevant semantic relationships could be identified and distractors rejected. In addition, the aphasic patients made associative semantic errors in picture naming that SD patients did not make. The aphasic patients ’ picture naming performance improved considerably with phonemic cues suggesting that these patients retained knowledge

Recent research has indicated that anteromedial temporal cortex (including the perirhinal cortex) may function as the endpoint of a hierarchically organized visual object--processing network providing the basis for fine-grained discrimination among objects. The present study examines whether the same system is involved in processing conceptual information when concepts, and their properties, are denoted by words. A lesion--behavior correlational study was conducted in which cortical damage in 21 braindamaged patients was correlated with behavioral scores in a verbally presented property verification task. Results indicated that the neural correlates of conceptual processing depend on the dynamic interaction between the content of a conceptual representation and the specific demands of the task and that the role of anteromedial temporal cortex in this process is not limited to the visual input modality. The results are consistent with the claim that anteromedial temporal cortex provides the neural structure necessary for the emergence of fine-grained conceptual knowledge about objects, although the region is strongly weighted toward processing of visually based object features.