Top-Down Regulation of Laminar Circuit via Inter-Area Signal for Successful Object Memory Recall in Monkey Temporal Cortex

Sequential involvements of the perirhinal cortex and hippocampus in the recall of item-location associative memory in macaques

The standard consolidation theory suggests that the hippocampus (HPC) is critically involved in acquiring new memory, while storage and recall gradually become independent of it. Converging studies have shown separate involvements of the perirhinal cortex (PRC) and parahippocampal cortex (PHC) in item and spatial processes, whereas HPC relates the item to a spatial context. These 2 strands of literature raise the following question; which brain region is involved in the recall process of item-location associative memory? To solve this question, this study applied an item-location associative (ILA) paradigm in a single-unit study of nonhuman primates. We trained 2 macaques to associate 4 visual item pairs with 4 locations on a background map in an allocentric manner before the recording sessions. In each trial, 1 visual item and the map image at a tilt (-90° to 90°) were sequentially presented as the item-cue and the context-cue, respectively. The macaques chose the item-cue location relative to the context-cue by positioning their gaze. Neurons in the PRC, PHC, and HPC, but not area TE, exhibited item-cue responses which signaled retrieval of item-location associative memory. This retrieval signal first appeared in the PRC, followed by the HPC and PHC. We examined whether neural representations of the retrieved locations were related to the external space that the macaques viewed. A positive representation similarity was found in the HPC and PHC, but not in the PRC, thus suggesting a contribution of the HPC to relate the retrieved location from the PRC with a first-person perspective of the subjects and provide the self-referenced retrieved location to the PHC. These results imply distinct but complementary contributions of the PRC and HPC to recall of item-location associative memory that can be used across multiple spatial contexts.

Conversion of concept-specific decision confidence into integrative introspection in primates

Introspection based on the integration of uncertain evidence is critical for acting upon abstract thinking and imagining future scenarios. However, it is unknown how confidence read-outs from multiple sources of different concepts are integrated, especially considering the relationships among the concepts. In this study, monkeys performed wagering based on an estimation of their performance in a preceding mnemonic decision. We found that the longer the response times for post-decision wagering, the more relieved the impairments having been caused by frontal disruption. This suggests the existence of a time-consuming compensatory metacognitive process. We found posterior inferior parietal lobe (pIPL) as its candidate, which was not coding the wagering per se (i.e., just high bet or low bet), but became more active when monkeys successfully chose the optimal bet option based on mnemonic decision performance. Thereafter, the pIPL prompts dorsal anterior cingulate cortex to carry the chosen wagering option. Our findings suggest a role for the pIPL in metacognitive concept integration.

Operating principles of the cerebral cortex as a six-layered network in primates: beyond the classic canonical circuit model

The cerebral cortex performs its computations with many six-layered fundamental units, collectively spreading along the cortical sheet. What is the local network structure and the operating dynamics of such a fundamental unit? Previous investigations of primary sensory areas revealed a classic "canonical" circuit model, leading to an expectation of similar circuit organization and dynamics throughout the cortex. This review clarifies the different circuit dynamics at play in the higher association cortex of primates that implements computation for high-level cognition such as memory and attention. Instead of feedforward processing of response selectivity through Layers 4 to 2/3 that the classic canonical circuit stipulates, memory recall in primates occurs in Layer 5/6 with local backward projection to Layer 2/3, after which the retrieved information is sent back from Layer 6 to lower-level cortical areas for further retrieval of nested associations of target attributes. In this review, a novel "dynamic multimode module (D3M)" in the primate association cortex is proposed, as a new "canonical" circuit model performing this operation.

Reunification of Object and View-Center Background Information in the Primate Medial Temporal Lobe

Recent work has shown that the medial temporal lobe (MTL), including the hippocampus (HPC) and its surrounding limbic cortices, plays a role in scene perception in addition to episodic memory. The two basic factors of scene perception are the object (“what”) and location (“where”). In this review, we first summarize the anatomical knowledge related to visual inputs to the MTL and physiological studies examining object-related information processed along the ventral pathway briefly. Thereafter, we discuss the space-related information, the processing of which was unclear, presumably because of its multiple aspects and a lack of appropriate task paradigm in contrast to object-related information. Based on recent electrophysiological studies using non-human primates and the existing literature, we proposed the “reunification theory,” which explains brain mechanisms which construct object-location signals at each gaze. In this reunification theory, the ventral pathway signals a large-scale background image of the retina at each gaze position. This view-center background signal reflects the first person’s perspective and specifies the allocentric location in the environment by similarity matching between images. The spatially invariant object signal and view-center background signal, both of which are derived from the same retinal image, are integrated again (i.e., reunification) along the ventral pathway-MTL stream, particularly in the perirhinal cortex. The conjunctive signal, which represents a particular object at a particular location, may play a role in scene perception in the HPC as a key constituent element of an entire scene.

Memory retrieval dynamics and storage capacity of a modular network model of association cortex with featural decomposition

The primate heteromodal cortex presents an evident functional modularity at a mesoscopic level, with physiological and anatomical evidence pointing to it as likely substrate of long-term memory. In order to investigate some of its properties, a model of multimodular autoassociator is studied. Each of the many modules represents a neocortical functional ensemble of recurrently connected neurons and operates as a Hebbian autoassociator, storing a number of local features which it can recall upon cue. The global memory patterns are made of combinations of features sparsely distributed across the modules. Intermodular connections are modelled as a finite-connectivity random graph. Any pair of features in any respective pair of modules is allowed to be involved in several memory patterns; the coarse-grained modular network dynamics is defined in such a way as to overcome the consequent ambiguity of associations. Effects of long-range homeostatic synaptic scaling on network performance are also assessed. The dynamical process of cued retrieval almost saturates a natural upper bound while producing negligible spurious activation. The extent of finite-size effects on storage capacity is quantitatively evaluated. In the limit of infinite size, the functional relationship between storage capacity and number of features per module reduces to that which other authors found by methods from equilibrium statistical mechanics, which suggests that the origin of the functional form is of a combinatorial nature. In contrast with its apparent inevitability at intramodular level, long-range synaptic scaling results to be of minor relevance to both retrieval and storage capacity, casting doubt on its existence in the neocortex. A conjecture is also posited about how statistical fluctuation of connectivity across the network may underpin spontaneous emergence of semantic hierarchies through learning.

Temporal division of the decision-making process: An EEG study

Decision-making is a process that allows individuals to choose an option or alternative in order to maximize a subjective gain or achieve a set goal by evaluating and establishing a preference based on contextual and internal information. Ernst and Paulus proposed a three-stage temporal division of this process: 1) the assessment and formation of preferences among possible options; 2) the selection and execution of an action; and 3) the experience or evaluation of an outcome. Each stage involves the participation of several brain regions, including the prefrontal, parietal, and temporal cortices. There are reports of distinct functionalities of these cortices for each stage of decision-making, but those studies focus on individual stages and do not provide any direct comparisons among them. Therefore, using a task that allows the clear temporal separation of the three stages of decision-making, we characterized the electroencephalographic activity (EEG) of those cortices in 30 healthy right-handed men during preference changes that occurred while performing a decision-making task. As the trials progressed, the preference for the stimulus shifted towards maximizing gains on the task. Forty trials sufficed to maintain these behavioral changes. Specific EEG patterns for each stage of decision-making were obtained, and it was possible to associate them with the cognitive processes involved in each one. These EEG data support the temporal division of the decision-making process proposed by Ernest and Paulus and show that the task designed could be a useful tool for determining behavioral and cerebral changes associated with stimuli preference during decision-making.

Hippocampal cells integrate past memory and present perception for the future

The ability to use stored information in a highly flexible manner is a defining feature of the declarative memory system. However, the neuronal mechanisms underlying this flexibility are poorly understood. To address this question, we recorded single-unit activity from the hippocampus of 2 nonhuman primates performing a newly devised task requiring the monkeys to retrieve long-term item-location association memory and then use it flexibly in different circumstances. We found that hippocampal neurons signaled both mnemonic information representing the retrieved location and perceptual information representing the external circumstance. The 2 signals were combined at a single-neuron level to construct goal-directed information by 3 sequentially occurring neuronal operations (e.g., convergence, transference, and targeting) in the hippocampus. Thus, flexible use of knowledge may be supported by the hippocampal constructive process linking memory and perception, which may fit the mnemonic information into the current situation to present manageable information for a subsequent action.

This study reveals that three neuronal operations in the macaque hippocampus combine retrieved memory and incoming perceptual information to construct goal-directed information; this constructive memory process may equip us to use past knowledge flexibly according to the current situation.

Perirhinal circuits for memory processing

The perirhinal cortex (PRC) serves as the gateway to the hippocampus for episodic memory formation and plays a part in retrieval through its backward connectivity to various neocortical areas. First, I present the evidence suggesting that PRC neurons encode both experientially acquired object features and their associative relations. Recent studies have revealed circuit mechanisms in the PRC for the retrieval of cue-associated information, and have demonstrated that, in monkeys, PRC neuron-encoded information can be behaviourally read out. These studies, among others, support the theory that the PRC converts visual representations of an object into those of its associated features and initiates backward-propagating, interareal signalling for retrieval of nested associations of object features that, combined, extensionally represent the object meaning. I propose that the PRC works as the ventromedial hub of a 'two-hub model' at an apex of the hierarchy of a distributed memory network and integrates signals encoded in other downstream cortical areas that support diverse aspects of knowledge about an object.

Neural network model for path-finding problems with the self-recovery property

The large-scale synchronization of neural oscillations is crucial in the functional integration of brain modules, but the combination of modules changes depending on the task. A mathematical description of this flexibility is a key to elucidating the mechanism of such spontaneous neural activity. We present a model that finds the loop structure of a network whose nodes are connected by unidirectional links. Using this model, we propose a path-finding system that spontaneously finds a path connecting two specified nodes. The solution path is represented by phase-synchronized oscillatory solutions. The model has the self-recovery property: that is, it is a system with the ability to find a new path when one of the connections in the existing path is suddenly removed. We show that the model construction procedure is applicable to a wide class of nonlinear systems arising in chemical reactions and neural networks.

Dynamic laminar rerouting of inter-areal mnemonic signal by cognitive operations in primate temporal cortex

Execution of cognitive functions is orchestrated by a brain-wide network comprising multiple regions. However, it remains elusive whether the cortical laminar pattern of inter-areal interactions exhibits dynamic routings, depending on cognitive operations. We address this issue by simultaneously recording neuronal activities from area 36 and area TE of the temporal cortex while monkeys performed a visual cued-recall task. We identify dynamic laminar routing of the inter-areal interaction: during visual processing of a presented cue, spiking activities of area 36 neurons are preferentially coherent with local field potentials at the supragranular layer of area TE, while the signal from the same neurons switches to target the infragranular layer of area TE during memory retrieval. This layer-dependent signal represents the to-be-recalled object, and has an impact on the local processing at the supragranular layer in both cognitive operations. Thus, cortical layers form a key structural basis for dynamic switching of cognitive operations.

Inter-areal interaction has been shown to support various cognitive functions. Here, the authors report that neurons in area 36 flexibly synchronize their activity with different layers of area TE within different epochs of a visually cued recall task suggesting dynamic rerouting of information.

Brain mechanisms of visual long-term memory retrieval in primates

Memorizing events or objects and retrieving them from memory are essential for daily life. Historically, memory processing was studied in neuropsychology, in which patients provided us with insights into the brain mechanisms underlying memory. Psychological hypotheses about memory processing have been further investigated using neuroscience techniques, such as functional imaging and electrophysiology. In this article, I briefly summarize recent findings on multi-scale neural circuitry for memory at the scale of single neurons and cortical layers as well as inter-area and whole-brain interactions. The key idea which connects multi-scale neural circuits is how neuronal assemblies utilize the frequency of communication between neurons, cortical layers, and brain areas. Using findings and ideas from other cognitive function studies, I discuss the plausible communication between neurons involved in memory.

Learning Task-Related Activities From Independent Local-Field-Potential Components Across Motor Cortex Layers

Motor cortical microcircuits receive inputs from dispersed cortical and subcortical regions in behaving animals. However, how these inputs contribute to learning and execution of voluntary sequential motor behaviors remains elusive. Here, we analyzed the independent components extracted from the local field potential (LFP) activity recorded at multiple depths of rat motor cortex during reward-motivated movement to study their roles in motor learning. Because slow gamma (30-50 Hz), fast gamma (60-120 Hz), and theta (4-10 Hz) oscillations temporally coordinate task-relevant motor cortical activities, we first explored the behavioral state- and layer-dependent coordination of motor behavior in these frequency ranges. Consistent with previous findings, oscillations in the slow and fast gamma bands dominated during distinct movement states, i.e., preparation and execution states, respectively. However, we identified a novel independent component that dominantly appeared in deep cortical layers and exhibited enhanced slow gamma activity during the execution state. Then, we used the four major independent components to train a recurrent network model for the same lever movements as the rats performed. We show that the independent components differently contribute to the formation of various task-related activities, but they also play overlapping roles in motor learning.

Using Laser Capture Microdissection to Isolate Cortical Laminae in Nonhuman Primate Brain

Laser capture microdissection (LCM) is a technique that allows procurement of an enriched cell population from a heterogeneous tissue sample under direct microscopic visualization. Fundamentally, laser capture microdissection consists of three main steps: (1) visualizing the desired cell population by microscopy, (2) melting a thermolabile polymer onto the desired cell populations using infrared laser energy to form a polymer-cell composite (capture method) or photovolatizing a region of tissue using ultraviolet laser energy (cutting method), and (3) removing the desired cell population from the heterogeneous tissue. In this chapter, we discuss the infrared capture method only. LCM technology is compatible with a wide range of downstream applications such as mass spectrometry, DNA genotyping and RNA transcript profiling, cDNA library generation, proteomics discovery, and signal pathway mapping. This chapter profiles the ArcturusXT^™ laser capture microdissection instrument, using isolation of specific cortical lamina from nonhuman primate brain regions, and sample preparation methods for downstream proteomic applications.

Modulatory effect of romantic love on value estimation and its neural mechanism

Any decision that is based upon personal preferences utilizes subjective values; however, for objectively equivalent items, whether romantic love modulates subjective value as well as the neural mechanism of this process remains unknown. In this functional MRI study, 30 items with equivalent value were first selected and assigned into three groups, and participants were trained to associate each group of items with their lover, a familiar person, or an unfamiliar person. Thereafter, the participant rated the values of the items during functional MRI scanning, after which they performed a post-test of memory of the associations. Behavioral results demonstrated that, although the items were well remembered, the items that were associated with the lover were rated significantly higher than the other images. Furthermore, we found higher activation related to the items associated with the lover than for those associated with a familiar person or an unfamiliar person in the striatum and the medial prefrontal cortex (related to cognitive control process). Finally, a morphometric analysis demonstrated that gray matter thickness in the striatum was positively associated with gray matter thickness in the medial prefrontal cortex but negatively correlated with the activation that was elicited by the items that were associated with the lover in the same brain area. Our results suggest that the romantic love-related brain region (the striatum) may modulate subjective value through the striatal-prefrontal pathway, further suggesting a potential bottom-up (control impulsivity) process.

Laminar Module Cascade from Layer 5 to 6 Implementing Cue-to-Target Conversion for Object Memory Retrieval in the Primate Temporal Cortex

The cerebral cortex computes through the canonical microcircuit that connects six stacked layers; however, how cortical processing streams operate in vivo, particularly in the higher association cortex, remains elusive. By developing a novel MRI-assisted procedure that reliably localizes recorded single neurons at resolution of six individual layers in monkey temporal cortex, we show that transformation of representations from a cued object to a to-be-recalled object occurs at the infragranular layer in a visual cued-recall task. This cue-to-target conversion started in layer 5 and was followed by layer 6. Finally, a subset of layer 6 neurons exclusively encoding the sought target became phase-locked to surrounding field potentials at theta frequency, suggesting that this coordinated cell assembly implements cortical long-distance outputs of the recalled target. Thus, this study proposes a link from local computation spanning laminar modules of the temporal cortex to the brain-wide network for memory retrieval in primates.

Associative-memory representations emerge as shared spatial patterns of theta activity spanning the primate temporal cortex

Highly localized neuronal spikes in primate temporal cortex can encode associative memory; however, whether memory formation involves area-wide reorganization of ensemble activity, which often accompanies rhythmicity, or just local microcircuit-level plasticity, remains elusive. Using high-density electrocorticography, we capture local-field potentials spanning the monkey temporal lobes, and show that the visual pair-association (PA) memory is encoded in spatial patterns of theta activity in areas TE, 36, and, partially, in the parahippocampal cortex, but not in the entorhinal cortex. The theta patterns elicited by learned paired associates are distinct between pairs, but similar within pairs. This pattern similarity, emerging through novel PA learning, allows a machine-learning decoder trained on theta patterns elicited by a particular visual item to correctly predict the identity of those elicited by its paired associate. Our results suggest that the formation and sharing of widespread cortical theta patterns via learning-induced reorganization are involved in the mechanisms of associative memory representation.

A multilayered story of memory retrieval

The successful retrieval of learned visual associations requires coordination of multiple brain regions involved in the encoding and association of visual images. In this issue of Neuron, Takeda et al. (2015) use a combination of modern recording and analytical methods to eavesdrop on this process.