The Perirhinal Cortex and Long-Term Familiarity Memory

A theory of hippocampal function: New developments

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

Perirhinal cortex automatically tracks multiple types of familiarity regardless of task-relevance

Perirhinal cortex (PrC) has long been implicated in familiarity assessment for objects and corresponding concepts. However, extant studies have focused mainly on changes in familiarity induced by recent exposure in laboratory settings. There is an increasing appreciation of other types of familiarity signals, in particular graded familiarity accumulated throughout one's lifetime. In prior work (Duke et al., 2017, Cortex, 89, 61-70), PrC has been shown to track lifetime familiarity ratings when participants make related judgements. A theoretically important characteristic of familiarity is its proposed automaticity. Support for automaticity comes from a documented impact of recent stimulus exposure on behavioral performance, and on PrC signals, under conditions in which this exposure is not task relevant. In the current fMRI study, we tested whether PrC also tracks lifetime familiarity of object concepts automatically, and whether this type of familiarity influences behavior even when it is not task relevant. During scanning, neurotypical participants (N = 30, age range 18-40, 7 males) provided animacy judgements about concrete object concepts presented at differing frequencies in an initial study phase. In a subsequent test phase, they made graded judgements of recent or lifetime familiarity. Behavioral performance showed sensitivity to lifetime familiarity even when it was not relevant for the task at hand. Across five sets of fMRI analyses, we found that PrC consistently tracked recent and lifetime familiarity of object concepts regardless of the task performed. Critically, while several other temporal-lobe regions also showed isolated familiarity effects, none of them tracked familiarity with the same consistency. These findings demonstrate that PrC automatically tracks multiple types of familiarity. They support models that assign a broad role in the representation of information about object concepts to this structure.

Extensive Cortical Connectivity of the Human Hippocampal Memory System: Beyond the "What" and "Where" Dual Stream Model

The human hippocampus is involved in forming new memories: damage impairs memory. The dual stream model suggests that object "what" representations from ventral stream temporal cortex project to the hippocampus via the perirhinal and then lateral entorhinal cortex, and spatial "where" representations from the dorsal parietal stream via the parahippocampal gyrus and then medial entorhinal cortex. The hippocampus can then associate these inputs to form episodic memories of what happened where. Diffusion tractography was used to reveal the direct connections of hippocampal system areas in humans. This provides evidence that the human hippocampus has extensive direct cortical connections, with connections that bypass the entorhinal cortex to connect with the perirhinal and parahippocampal cortex, with the temporal pole, with the posterior and retrosplenial cingulate cortex, and even with early sensory cortical areas. The connections are less hierarchical and segregated than in the dual stream model. This provides a foundation for a conceptualization for how the hippocampal memory system connects with the cerebral cortex and operates in humans. One implication is that prehippocampal cortical areas such as the parahippocampal TF and TH subregions and perirhinal cortices may implement specialized computations that can benefit from inputs from the dorsal and ventral streams.

Brain Networks Sensitive to Object Novelty, Value, and Their Combination

Novel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain responses to visual fractal patterns varying in either novelty or value dimensions and compared the results with the structure of functionally connected brain networks determined at rest. The results show that different brain networks possess unique combinations of novelty and value coding. One network identified in the ventral temporal cortex preferentially encoded object novelty, whereas another in the parietal cortex encoded the learned value. A third network, broadly composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, encoded both dimensions with similar activation dynamics. Our results support the emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.

Monkey Perirhinal Cortex is Critical for Visual Memory, but not for Visual Perception: Reexamination of the Behavioural Evidence from Monkeys

Overdependence on discrimination learning paradigms to assess the function of perirhinal cortex has complicated understanding of the cognitive role of this structure. Impairments in discrimination learning can result from at least two distinct causes: (a) failure to accurately apprehend and represent the relevant stimuli, or (b) failure to form and remember associations between stimulus representations and reward. Thus, the results of discrimination learning experiments do not readily differentiate deficits in perception from deficits in learning and memory. Here I describe studies that do dissociate learning and memory from perception and show that perirhinal cortex damage impairs learning and/or memory, but not perception. Reanalysis and reconsideration of other published data call into further question the hypothesis that the monkey perirhinal cortex plays a critical role in visual perception.

Perirhinal cortex tracks degree of recent as well as cumulative lifetime experience with object concepts

Evidence from numerous sources indicates that recognition of the prior occurrence of objects requires computations of perirhinal cortex (PrC) in the medial temporal lobe (MTL). Extant research has primarily probed recognition memory based on item exposure in a recent experimental study episode. Outside the laboratory, however, familiarity for objects typically accrues gradually with learning across many different episodic contexts, which can be distributed over a lifetime of experience. It is currently unknown whether PrC also tracks this cumulative lifetime experience with object concepts. To address this issue, we conducted a functional magnetic resonance imaging (fMRI) experiment in healthy individuals in which we compared judgments of the perceived lifetime familiarity with object concepts, a task that has previously been employed in many normative studies on concept knowledge, with frequency judgments for recent laboratory exposure in a study phase. Guided by neurophysiological data showing that neurons in primate PrC signal prior object exposure at multiple time scales, we predicted that PrC responses would track perceived prior experience in both types of judgments. Left PrC and a number of cortical regions that are often co-activated as part of the default-mode network showed an increase in Blood-Oxygen-Level Dependent (BOLD) response in relation to increases in the perceived cumulative lifetime familiarity of object concepts. These regions included the left hippocampus, left mid-lateral temporal cortex, as well as anterior and posterior cortical midline structures. Critically, left PrC was found to be the only region that showed this response in combination with the typically observed decrease in signal for perceived recent exposure in the experimental study phase. These findings provide, to our knowledge, the first evidence that ties signals in human PrC to variations in cumulative lifetime experience with object concepts. They offer a new link between the role of PrC in recognition memory and its broader role in conceptual processing.

Two separate, but interacting, neural systems for familiarity and novelty detection: a dual-route mechanism

It has long been assumed that familiarity- and novelty-related processes fall on a single continuum drawing on the same cognitive and neural mechanisms. The possibility that familiarity and novelty processing involve distinct neural networks was explored in a functional magnetic resonance imaging study (fMRI), in which familiarity and novelty judgments were made in contexts emphasizing either familiarity or novelty decisions. Parametrically modulated BOLD responses to familiarity and novelty strength were isolated in two separate, nonoverlapping brain networks. The novelty system involved brain regions along the ventral visual stream, the hippocampus, and the perirhinal and parahippocampal cortices. The familiarity system, on the other hand, involved the dorsomedial thalamic nucleus, and regions within the medial prefrontal cortex and the medial and lateral parietal cortex. Convergence of the two networks, treating familiarity and novelty as a single continuum was only found in a fronto-parietal network. Finally, the orbitomedial prefrontal cortex was found to be sensitive to reported strength/confidence, irrespective of stimulus' familiarity or novelty. This pattern of results suggests a dual-route mechanism supported by the existence of two distinct but interacting functional systems for familiarity and novelty. Overall, these findings challenge current assumptions regarding the neural systems that support the processing of novel and familiar information, and have important implications for research into the neural bases of recognition memory.

Limbic systems for emotion and for memory, but no single limbic system

The concept of a (single) limbic system is shown to be outmoded. Instead, anatomical, neurophysiological, functional neuroimaging, and neuropsychological evidence is described that anterior limbic and related structures including the orbitofrontal cortex and amygdala are involved in emotion, reward valuation, and reward-related decision-making (but not memory), with the value representations transmitted to the anterior cingulate cortex for action-outcome learning. In this 'emotion limbic system' a computational principle is that feedforward pattern association networks learn associations from visual, olfactory and auditory stimuli, to primary reinforcers such as taste, touch, and pain. In primates including humans this learning can be very rapid and rule-based, with the orbitofrontal cortex overshadowing the amygdala in this learning important for social and emotional behaviour. Complementary evidence is described showing that the hippocampus and limbic structures to which it is connected including the posterior cingulate cortex and the fornix-mammillary body-anterior thalamus-posterior cingulate circuit are involved in episodic or event memory, but not emotion. This 'hippocampal system' receives information from neocortical areas about spatial location, and objects, and can rapidly associate this information together by the different computational principle of autoassociation in the CA3 region of the hippocampus involving feedback. The system can later recall the whole of this information in the CA3 region from any component, a feedback process, and can recall the information back to neocortical areas, again a feedback (to neocortex) recall process. Emotion can enter this memory system from the orbitofrontal cortex etc., and be recalled back to the orbitofrontal cortex etc. during memory recall, but the emotional and hippocampal networks or 'limbic systems' operate by different computational principles, and operate independently of each other except insofar as an emotional state or reward value attribute may be part of an episodic memory.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Visual perception and memory systems: from cortex to medial temporal lobe

Visual perception and memory are the most important components of vision processing in the brain. It was thought that the perceptual aspect of a visual stimulus occurs in visual cortical areas and that this serves as the substrate for the formation of visual memory in a distinct part of the brain called the medial temporal lobe. However, current evidence indicates that there is no functional separation of areas. Entire visual cortical pathways and connecting medial temporal lobe are important for both perception and visual memory. Though some aspects of this view are debated, evidence from both sides will be explored here. In this review, we will discuss the anatomical and functional architecture of the entire system and the implications of these structures in visual perception and memory.

The organization and dissolution of semantic-conceptual knowledge: is the 'amodal hub' the only plausible model?

In recent years, the anatomical and functional bases of conceptual activity have attracted a growing interest. In particular, Patterson and Lambon-Ralph have proposed the existence, in the anterior parts of the temporal lobes, of a mechanism (the 'amodal semantic hub') supporting the interactive activation of semantic representations in all modalities and for all semantic categories. The aim of then present paper is to discuss this model, arguing against the notion of an 'amodal' semantic hub, because we maintain, in agreement with the Damasio's construct of 'higher-order convergence zone', that a continuum exists between perceptual information and conceptual representations, whereas the 'amodal' account views perceptual informations only as a channel through which abstract semantic knowledge can be activated. According to our model, semantic organization can be better explained by two orthogonal higher-order convergence systems, concerning, on one hand, the right vs. left hemisphere and, on the other hand, the ventral vs. dorsal processing pathways. This model posits that conceptual representations may be mainly based upon perceptual activities in the right hemisphere and upon verbal mediation in the left side of the brain. It also assumes that conceptual knowledge based on the convergence of highly processed visual information with other perceptual data (and mainly concerning living categories) may be bilaterally represented in the anterior parts of the temporal lobes, whereas knowledge based on the integration of visual data with action schemata (namely knowledge of actions, body parts and artefacts) may be more represented in the left fronto-temporo-parietal areas.

Synaptic plasticity from visual cortex to hippocampus: systems integration in spatial information processing

The adult cerebral cortex possesses the remarkable ability to change its neuronal connectivity through experience, a phenomenon termed "synaptic plasticity." Synaptic plasticity constitutes a cellular mechanism that is thought to underlie information storage and memory formation in the brain, and represents a use-dependent long-lasting increase or decrease in synaptic strength. Recent findings, that the adult visual cortex undergoes dynamic synaptic plasticity that is driven by active visual experience, suggest that it may be involved in information processing that could contribute to memory formation. The visual cortex provides a crucial sensory input to the hippocampus, and is a key component for the creation of spatial memories. An understanding of how visual cortical neurons respond with synaptic plasticity to visual experience, and whether these responses influence the induction of hippocampal plasticity, is fundamental to our understanding of the neuronal mechanisms and functional consequences of visuospatial information processing. In this review, we summarize recent findings with regard to the expression of dynamic synaptic plasticity in the visual cortex and how this plasticity may influence information processing in the hippocampus.

A computational theory of hippocampal function, and empirical tests of the theory

The main aim of the paper is to present an up-to-date computational theory of hippocampal function and the predictions it makes about the different subregions (dentate gyrus, CA3 and CA1), and to examine behavioral and electrophysiological data that address the functions of the hippocampus and particularly its subregions. Based on the computational proposal that the dentate gyrus produces sparse representations by competitive learning and via the mossy fiber pathway forces new representations on the CA3 during learning (encoding), it has been shown behaviorally that the dentate gyrus supports spatial pattern separation during learning. Based on the computational proposal that CA3-CA3 autoassociative networks are important for episodic memory, it has been shown behaviorally that the CA3 supports spatial rapid one-trial learning, learning of arbitrary associations where space is a component, pattern completion, spatial short-term memory, and sequence learning by associations formed between successive items. The concept that the CA1 recodes information from CA3 and sets up associatively learned backprojections to neocortex to allow subsequent retrieval of information to neocortex, is consistent with findings on consolidation. Behaviorally, the CA1 is implicated in processing temporal information as shown by investigations requiring temporal order pattern separation and associations across time; computationally this could involve temporal decay memory, and temporal sequence memory which might also require CA3. The perforant path input to DG is implicated in learning, to CA3 in retrieval from CA3, and to CA1 in retrieval after longer time intervals ("intermediate-term memory").

Perirhinal cortex and its neighbours in the medial temporal lobe: contributions to memory and perception

As promised in the Introduction, this Special Issue presents several recurring themes concerning the perirhinal cortex and its neighbours within the medial temporal lobe (MTL). First, although orthodoxy insists that the diverse constituents of the MTL operate as a single functional entity, several papers presented here challenge that idea, although some defend it. Second, although many experts hold that the MTL subserves memory but not perception, several papers presented here point to a role for certain MTL structures in both. Third, although some researchers have invoked “species differences” to account for discrepant findings, several papers presented here document a striking convergence of findings in humans, nonhuman primates, and rodents. We close this Special Issue by high-lighting these recurring themes, acknowledging discrepant findings and pointing to future research that might resolve some current controversies.

Spatial view cells in the hippocampus, and their idiothetic update based on place and head direction

Single neuron recording studies have demonstrated the existence of spatial view neurons which encode information about the spatial location at which a primate is looking in the environment. These neurons are able to maintain their firing even in the absence of visual input. The standard neuronal network approach to model networks with memory that represent continuous spaces is that of continuous attractor neural networks. Stringer, Rolls and Trappenberg (2005) have recently shown how idiothetic (self-motion) inputs could update the activity packet of neuronal firing within a two-dimensional continuous attractor neural network of spatial view cells. However, this earlier study examined only the simplified situation in which the agent could rotate on the spot or move its eyes. In this paper we show how spatial view cells could be driven by head direction and place cells, themselves idiothetically updated. The head direction and place neurons are remapped by a competitive network with expansion recoding which self-organises so that different neurons represent different combinations of head direction and the place where the agent is located. The combination cells are then mapped by pattern association involving long-term synaptic potentiation but also long-term homosynaptic depression to spatial view cells, which during training are driven by the spatial view. After training, the spatial view cells are updated in the dark by the idiothetically driven head direction and place cells.