in humans and nonhuman primates. A major source of this limitation has been the contention that hippocampal processing is dedicated to spatial memory in rodents, in contrast to the global memory deficits observed following damage to the hippocampal region in humans and more recently in animals as well (Eichenbaum, 1997). Furthermore, several recent electrophysiological studies have revealed properties of hippocampal neuronal firing patterns that are inconsistent with the notion of a cognitive map and indicate a broader scope of information processing. This paper will focus on these 70211 Kuopio studies, reviewing some of the history and basic proper-Finland ties of place cells, and considering both early and recent findings that shed light on the content and organization

this article. Because there is no visible cue in the hidden-platform water maze task, it would not help the animal find the platform. 3. Route system. Routes stored in the hippocampus can be written out to the cortex, so that directions necessary to reach a goal are associated with local views. This is the system detailed in section 2.5 (see also section 4.3). This system requires training for each step the animal must take; it cannot learn to associate local views with directions to distant goals without hippocampal help (through route replay). The Role of the Hippocampus 97 If there were a way to show the animal the route to the goal, it might be possible to train the route system even without a hippocampus. Whishaw, Cassell, and Jarrard (1995) and Schallert, Day, Weisend, and Sutherland (1996) both showed ways to train the route system directly and found that animals could learn to solve the water maze even with hippocampal lesions. Whishaw et al. (1995) trained animals with fimbria/fornix lesions to find a visible platform and then removed the visible platform. These animals concentrated their search where the platform had been. Schallert et al. (1996) used animals with kainate-colchicine hippocampal lesions. The animals were first trained with a large platform that filled almost the entire maze. Once the animals could reach that platform reliably, it was shrunk trial by trial until it was the same size as a typical platform in a water maze task. Again, the animals could learn to solve the water maze without a hippocampus. 4.3 Where Is the Route System? Although the data are not yet conclusive, we suggest that the most likely candidate for anatomical instantiation of the route system is from posterior parietal to posterior cingulate cortex. There is a lot of evide...

Strong constraints on the neural mechanisms underlying the formation of place fields in the rodent hippocampus come from the systematic changes in spatial activity patterns that are consequent on systematic environmental manipulations. We describe an attractor network model of area CA3 in which local, recurrent, excitatory, and inhibitory interactions generate appropriate place cell representations from location- and directionspecific activity in the entorhinal cortex. In the model, familiarity with the environment, as reflected by activity in neuromodulatory systems, influences the efficacy and plasticity of the recurrent and feedforward inputs to CA3. In unfamiliar, novel, environments, mossy fiber inputs impose activity patterns on CA3, and the recurrent collaterals and the perforant path inputs are subject to graded Hebbian plasticity. The hippocampus is known to be involved in spatial learning and memory in rodents. Some of the most convincing evidence for this is the presence of place cells in areas CA3 and CA1 of the hippocampus (O’Keefe and Dostrovsky, 1971; O’Keefe, 1976) and of many other types of spatially selective cells in neighboring areas

Free recall and recognition are simulated in a network model of the hippocampal formation, incorporating simplified simulations of neurons, synaptic connections, and the effects of acetylcholine. Simulations focus on modeling the effects of the acetylcholine receptor blocker scopolamine on human memory. Systemic administration of scopolamine is modeled by blockade of the cellular effects of acetylcholine in the model, resulting in memory impairments replicating data from studies on human subjects. This blockade of cholinergic effects impairs the encoding of new input patterns (as measured by delayed free recall), but does not impair the delayed free recall of input patterns learned before the blockade. The impairment is selective to the free recall but not the recognition of items encoded under the influence of scopolamine. In the model, scopolamine blocks strengthening of recurrent connections in region CA3 to form attractor states for new items (encoding impaired) but allows recurrent excitation to drive the network into previously stored attractor states (retrieval spared). Neuron populations representing items (individual words) have weaker recurrent connections than neuron populations representing experimental context. When scopolamine further weakens the strength of recurrent connections it selectively prevents the subsequent reactivation of item attractor states by context input (impaired free recall) without impairing the subsequent reactivation of context attractor states by item input (spared recognition). This asymmetry in the strength of attractor states also allows simulation of the list-strength effect for free recall but not recognition. Simulation of a paired associate learning paradigm predicts that scopolamine should greatly enhance proactive interfere...

Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according to which sequence information is encoded through sustained patterns of activation within a recurrent neural network architecture. As demonstrated through a series of computer simulations, the model provides a parsimonious account for numerous benchmark characteristics of immediate serial recall, including data that have been considered to preclude the application of recurrent neural networks in this domain. Unlike most competing accounts, the model deals naturally with findings concerning the role of background knowledge in serial recall and makes contact with relevant neuroscientific data. Furthermore, the model gives rise to numerous testable predictions that differentiate it from competing theories. Taken together, the results presented indicate that recurrent neural networks may offer a useful framework for understanding short-term memory for serial order.

The medial temporal lobe (MTL) has been studied extensively at all levels of analysis, yet its function remains unclear. Theory regarding the cognitive function of the MTL has centered along 3 themes. Different authors have emphasized the role of the MTL in episodic recall, spatial navigation, or relational memory. Starting with the temporal context model (M.W. Howard and M. J. Kahana, 2002), a distributed memory model that has been applied to benchmark data from episodic recall tasks, the authors propose that the entorhinal cortex supports a gradually changing representation of temporal context and the hippocampus proper enables retrieval of these contextual states. Simulation studies show this hypothesis explains the firing of place cells in the entorhinal cortex and the behavioral effects of hippocampal lesion in relational memory tasks. These results constitute a first step towards a unified computational theory of MTL function that integrates neurophysiological, neuropsychological and cognitive findings.

markram.html We propose an alternative paradigm for processing time-varying visual inputs, in particular for tasks involving temporal and spatial integration, which is inspired by hypotheses about the computational role of cortical microcircuits. Instead of storing discrete frames of past visual inputs in a suitable datastructure and then applying a time-consuming algorithm to extract salient information about motion from these frames, we demonstrate through computer simulations that the following approach is in principle also feasible. Continuously timevarying visual inputs u (⋅) are directly injected into a sufficiently large and complex dynamical system (such as for example a cortical microcircuit). Simple readout devices can be trained to extract from the current state x(t) of such dynamical system at any time t in real-time salient information about the trajectory of recent inputs u ( s) for s < t. Since detailed knowledge about the precise structure of the dynamical system is not needed for that, it can in principle also be implemented with partially unknown or faulty analog hardware. In addition, this approach supports parallel real-time processing of time-varying visual inputs for diverse tasks, since different readouts can be trained to extract concurrently from the same dynamical system completely different information components.

The authors model the neural mechanisms underlying spatial cognition, integrating neuronal systems and behavioral data, and address the relationships between long-term memory, short-term memory, and imagery, and between egocentric and allocentric and visual and ideothetic representations. Long-term spatial memory is modeled as attractor dynamics within medial–temporal allocentric representations, and short-term memory is modeled as egocentric parietal representations driven by perception, retrieval, and imagery and modulated by directed attention. Both encoding and retrieval/imagery require translation between egocentric and allocentric representations, which are mediated by posterior parietal and retrosplenial areas and the use of head direction representations in Papez’s circuit. Thus, the hippocampus effectively indexes information by real or imagined location, whereas Papez’s circuit translates to imagery or from perception according to the direction of view. Modulation of this translation by motor efference allows spatial updating of representations, whereas prefrontal simulated motor efference allows mental exploration. The alternating temporal–parietal flows of information are organized by the theta rhythm. Simulations demonstrate the retrieval and updating of familiar spatial scenes, hemispatial neglect in memory, and the effects on hippocampal place cell firing of lesioned head direction representations and of conflicting visual and ideothetic inputs.

We readily acquire memories of events and situations in our daily lives. There is a broad consensus that the hippocampal system (HS) plays a critical role in the encoding and retrieval of such "episodic" memories. But how the HS subserves this mnemonic function is not fully understood. This article presents a computational model, SMRITI,that demonstrates how a transient pattern of activity representing an event can be transformed rapidly into a persistent and robust memory trace as a result of long-term potentiation within structures whose architecture and circuitry resemble those of the HS. Predictions and implications of the model are discussed. LONG ABSTRACT We readily remember events and situations in our daily lives and rapidly acquire memories of specific events by watching a telecast or reading a newspaper. There is a broad consensus that the hippocampal system (HS), consisting of the hippocampal formation and neighboring cortical areas, plays a critical role in the encoding and retrieval of such "episodic" memories. But how the HS subserves this mnemonic function is not fully understood. This article presents a computational model, SMRITI, that demonstrates how a cortically expressed transient pattern of activity representing an event can be transformed rapidly into a persistent and robust memory trace as a result of long-term potentiation within structures whose architecture and circuitry resemble those of the HS. Memory traces formed by the model respond to partial cues, and at the same time, reject similar but erroneous cues. During retrieval these memory traces, acting in concert with cortical circuits encoding semantic, causal, and procedural knowledge, can recreate activation-based representations of memorized events. The model explicates the representa...

One of the defining features of intelligent behaviour is the ordering of individual expressed actions into coherent, apparently rational patterns. Psychology has long assumed that hierarchical and sequential structures internal to the intelligent agent underlie this expression. Recently these assumptions have been challenged by claims that behaviour controlled by such structures is necessarily rigid, brittle, and incapable of reacting quickly and opportunistically to changes in the environment (Hendriks-Jansen 1996, Goldfield 1995, Brooks 1991a). This dissertation is intended to support the hypothesis that sequential and hierarchical structures are necessary to intelligent behaviour, and to refute the above claims of their impracticality. Three forms of supporting evidence are provided: • a demonstration in the form of experimental results in two domains that structured intelligence can lead to robust and reactive behaviour, • a review of recent research results and paradigmatic trends within artificial intelligence, and • a similar examination of related research in natural intelligence.