Categorization in the monkey hippocampus: a possible mechanism for encoding information into memory

Persistent Interruption in Parvalbumin-Positive Inhibitory Interneurons: Biophysical and Mathematical Mechanisms

Persistent activity in excitatory pyramidal cells (PYRs) is a putative mechanism for maintaining memory traces during working memory. We have recently demonstrated persistent interruption of firing in fast-spiking parvalbumin-expressing interneurons (PV-INs), a phenomenon that could serve as a substrate for persistent activity in PYRs through disinhibition lasting hundreds of milliseconds. Here, we find that hippocampal CA1 PV-INs exhibit type 2 excitability, like striatal and neocortical PV-INs. Modeling and mathematical analysis showed that the slowly inactivating potassium current KV1 contributes to type 2 excitability, enables the multiple firing regimes observed experimentally in PV-INs, and provides a mechanism for robust persistent interruption of firing. Using a fast/slow separation of times scales approach with the KV1 inactivation variable as a bifurcation parameter shows that the initial inhibitory stimulus stops repetitive firing by moving the membrane potential trajectory onto a coexisting stable fixed point corresponding to a nonspiking quiescent state. As KV1 inactivation decays, the trajectory follows the branch of stable fixed points until it crosses a subcritical Hopf bifurcation (HB) and then spirals out into repetitive firing. In a model describing entorhinal cortical PV-INs without KV1, interruption of firing could be achieved by taking advantage of the bistability inherent in type 2 excitability based on a subcritical HB, but the interruption was not robust to noise. Persistent interruption of firing is therefore broadly applicable to PV-INs in different brain regions but is only made robust to noise in the presence of a slow variable, KV1 inactivation.

Disrupting dorsal hippocampus impairs category learning in rats

Categorization requires a balance of mechanisms that can generalize across common features and discriminate against specific details. A growing literature suggests that the hippocampus may accomplish these mechanisms by using fundamental mechanisms like pattern separation, pattern completion, and memory integration. Here, we assessed the role of the rodent dorsal hippocampus (HPC) in category learning by combining inhibitory DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) and simulations using a neural network model. Using touchscreens, we trained rats to categorize distributions of visual stimuli containing black and white gratings that varied along two continuous dimensions. Inactivating the dorsal HPC impaired category learning and generalization, suggesting that the rodent HPC plays an important role during categorization. Hippocampal inactivation had no effect on a control discrimination task that used identical trial procedures as the categorization tasks, suggesting that the impairments were specific to categorization. Model simulations were conducted with variants of a neural network to assess the impact of selective deficits on category learning. The hippocampal inactivation groups were best explained by a model that injected random noise into the computation that compared the similarity between category stimuli and existing memory representations. This model is akin to a deficit in mechanisms of pattern completion, which retrieves similar memory representations using partial information.

Patterned Hippocampal Stimulation Facilitates Memory in Patients With a History of Head Impact and/or Brain Injury

Rationale: Deep brain stimulation (DBS) of the hippocampus is proposed for enhancement of memory impaired by injury or disease. Many pre-clinical DBS paradigms can be addressed in epilepsy patients undergoing intracranial monitoring for seizure localization, since they already have electrodes implanted in brain areas of interest. Even though epilepsy is usually not a memory disorder targeted by DBS, the studies can nevertheless model other memory-impacting disorders, such as Traumatic Brain Injury (TBI). Methods: Human patients undergoing Phase II invasive monitoring for intractable epilepsy were implanted with depth electrodes capable of recording neurophysiological signals. Subjects performed a delayed-match-to-sample (DMS) memory task while hippocampal ensembles from CA1 and CA3 cell layers were recorded to estimate a multi-input, multi-output (MIMO) model of CA3-to-CA1 neural encoding and a memory decoding model (MDM) to decode memory information from CA3 and CA1 neuronal signals. After model estimation, subjects again performed the DMS task while either MIMO-based or MDM-based patterned stimulation was delivered to CA1 electrode sites during the encoding phase of the DMS trials. Each subject was sorted (post hoc) by prior experience of repeated and/or mild-to-moderate brain injury (RMBI), TBI, or no history (control) and scored for percentage successful delayed recognition (DR) recall on stimulated vs. non-stimulated DMS trials. The subject’s medical history was unknown to the experimenters until after individual subject memory retention results were scored. Results: When examined compared to control subjects, both TBI and RMBI subjects showed increased memory retention in response to both MIMO and MDM-based hippocampal stimulation. Furthermore, effects of stimulation were also greater in subjects who were evaluated as having pre-existing mild-to-moderate memory impairment. Conclusion: These results show that hippocampal stimulation for memory facilitation was more beneficial for subjects who had previously suffered a brain injury (other than epilepsy), compared to control (epilepsy) subjects who had not suffered a brain injury. This study demonstrates that the epilepsy/intracranial recording model can be extended to test the ability of DBS to restore memory function in subjects who previously suffered a brain injury other than epilepsy, and support further investigation into the beneficial effect of DBS in TBI patients.

Distributed Neural Systems Support Flexible Attention Updating during Category Learning

To accurately categorize items, humans learn to selectively attend to stimulus dimensions that are most relevant to the task. Models of category learning describe the interconnected cognitive processes that contribute to attentional tuning as labeled stimuli are progressively observed. The Adaptive Attention Representation Model (AARM), for example, provides an account whereby categorization decisions are based on the perceptual similarity of a new stimulus to stored exemplars, and dimension-wise attention is updated on every trial in the direction of a feedback-based error gradient. As such, attention modulation as described by AARM requires interactions among orienting, visual perception, memory retrieval, prediction error, and goal maintenance to facilitate learning across trials. The current study explored the neural bases of attention mechanisms using quantitative predictions from AARM to analyze behavioral and fMRI data collected while participants learned novel categories. Generalized linear model analyses revealed patterns of BOLD activation in the parietal cortex (orienting), visual cortex (perception), medial temporal lobe (memory retrieval), basal ganglia (prediction error), and pFC (goal maintenance) that covaried with the magnitude of model-predicted attentional tuning. Results are consistent with AARM's specification of attention modulation as a dynamic property of distributed cognitive systems.

A Double-Layer Multi-Resolution Classification Model for Decoding Spatiotemporal Patterns of Spikes With Small Sample Size

We build a double-layer, multiple temporal-resolution classification model for decoding single-trial spatiotemporal patterns of spikes. The model takes spiking activities as input signals and binary behavioral or cognitive variables as output signals and represents the input-output mapping with a double-layer ensemble classifier. In the first layer, to solve the underdetermined problem caused by the small sample size and the very high dimensionality of input signals, B-spline functional expansion and L1-regularized logistic classifiers are used to reduce dimensionality and yield sparse model estimations. A wide range of temporal resolutions of neural features is included by using a large number of classifiers with different numbers of B-spline knots. Each classifier serves as a base learner to classify spatiotemporal patterns into the probability of the output label with a single temporal resolution. A bootstrap aggregating strategy is used to reduce the estimation variances of these classifiers. In the second layer, another L1-regularized logistic classifier takes outputs of first-layer classifiers as inputs to generate the final output predictions. This classifier serves as a meta-learner that fuses multiple temporal resolutions to classify spatiotemporal patterns of spikes into binary output labels. We test this decoding model with both synthetic and experimental data recorded from rats and human subjects performing memory-dependent behavioral tasks. Results show that this method can effectively avoid overfitting and yield accurate prediction of output labels with small sample size. The double-layer, multi-resolution classifier consistently outperforms the best single-layer, single-resolution classifier by extracting and utilizing multi-resolution spatiotemporal features of spike patterns in the classification.

RUBubbles as a novel tool to study categorization learning

Grouping objects into discrete categories affects how we perceive the world and represents a crucial element of cognition. Categorization is a widespread phenomenon that has been thoroughly studied. However, investigating categorization learning poses several requirements on the stimulus set in order to control which stimulus feature is used and to prevent mere stimulus-response associations or rote learning. Previous studies have used a wide variety of both naturalistic and artificial categories, the latter having several advantages such as better control and more direct manipulation of stimulus features. We developed a novel stimulus type to study categorization learning, which allows a high degree of customization at low computational costs and can thus be used to generate large stimulus sets very quickly. 'RUBubbles' are designed as visual artificial category stimuli that consist of an arbitrary number of colored spheres arranged in 3D space. They are generated using custom MATLAB code in which several stimulus parameters can be adjusted and controlled separately, such as number of spheres, position in 3D-space, sphere size, and color. Various algorithms for RUBubble generation can be combined with distinct behavioral training protocols to investigate different characteristics and strategies of categorization learning, such as prototype- vs. exemplar-based learning, different abstraction levels, or the categorization of a sensory continuum and category exceptions. All necessary MATLAB code is freely available as open-source code and can be customized or expanded depending on individual needs. RUBubble stimuli can be controlled purely programmatically or via a graphical user interface without MATLAB license or programming experience.

Working Memory: From Neural Activity to the Sentient Mind

Working memory (WM) is the ability to maintain and manipulate information in the conscious mind over a timescale of seconds. This ability is thought to be maintained through the persistent discharges of neurons in a network of brain areas centered on the prefrontal cortex, as evidenced by neurophysiological recordings in nonhuman primates, though both the localization and the neural basis of WM has been a matter of debate in recent years. Neural correlates of WM are evident in species other than primates, including rodents and corvids. A specialized network of excitatory and inhibitory neurons, aided by neuromodulatory influences of dopamine, is critical for the maintenance of neuronal activity. Limitations in WM capacity and duration, as well as its enhancement during development, can be attributed to properties of neural activity and circuits. Changes in these factors can be observed through training-induced improvements and in pathological impairments. WM thus provides a prototypical cognitive function whose properties can be tied to the spiking activity of brain neurons. © 2021 American Physiological Society. Compr Physiol 11:1-41, 2021.

Hippocampal CA1 and CA3 neural recording in the human brain: validation of depth electrode placement through high-resolution imaging and electrophysiology

OBJECTIVE

Intracranial human brain recordings typically utilize recording systems that do not distinguish individual neuron action potentials. In such cases, individual neurons are not identified by location within functional circuits. In this paper, verified localization of singly recorded hippocampal neurons within the CA3 and CA1 cell fields is demonstrated.

METHODS

Macro-micro depth electrodes were implanted in 23 human patients undergoing invasive monitoring for identification of epileptic seizure foci. Individual neurons were isolated and identified via extracellular action potential waveforms recorded via macro-micro depth electrodes localized within the hippocampus. A morphometric survey was performed using 3T MRI scans of hippocampi from the 23 implanted patients, as well as 46 normal (i.e., nonepileptic) patients and 26 patients with a history of epilepsy but no history of depth electrode placement, which provided average dimensions of the hippocampus along typical implantation tracks. Localization within CA3 and CA1 cell fields was tentatively assigned on the basis of recording electrode site, stereotactic positioning of the depth electrode in comparison with the morphometric survey, and postsurgical MRI. Cells were selected as candidate CA3 and CA1 principal neurons on the basis of waveform and firing rate characteristics and confirmed within the CA3-to-CA1 neural projection pathways via measures of functional connectivity.

RESULTS

Cross-correlation analysis confirmed that nearly 80% of putative CA3-to-CA1 cell pairs exhibited positive correlations compatible with feed-forward connection between the cells, while only 2.6% exhibited feedback (inverse) connectivity. Even though synchronous and long-latency correlations were excluded, feed-forward correlation between CA3-CA1 pairs was identified in 1071 (26%) of 4070 total pairs, which favorably compares to reports of 20%-25% feed-forward CA3-CA1 correlation noted in published animal studies.

CONCLUSIONS

This study demonstrates the ability to record neurons in vivo from specified regions and subfields of the human brain. As brain-machine interface and neural prosthetic research continues to expand, it is necessary to be able to identify recording and stimulation sites within neural circuits of interest.

Involvement of TRPC4 and 5 Channels in Persistent Firing in Hippocampal CA1 Pyramidal Cells

Persistent neural activity has been observed in vivo during working memory tasks, and supports short-term (up to tens of seconds) retention of information. While synaptic and intrinsic cellular mechanisms of persistent firing have been proposed, underlying cellular mechanisms are not yet fully understood. In vitro experiments have shown that individual neurons in the hippocampus and other working memory related areas support persistent firing through intrinsic cellular mechanisms that involve the transient receptor potential canonical (TRPC) channels. Recent behavioral studies demonstrating the involvement of TRPC channels on working memory make the hypothesis that TRPC driven persistent firing supports working memory a very attractive one. However, this view has been challenged by recent findings that persistent firing in vitro is unchanged in TRPC knock out (KO) mice. To assess the involvement of TRPC channels further, we tested novel and highly specific TRPC channel blockers in cholinergically induced persistent firing in mice CA1 pyramidal cells for the first time. The application of the TRPC4 blocker ML204, TRPC5 blocker clemizole hydrochloride, and TRPC4 and 5 blocker Pico145, all significantly inhibited persistent firing. In addition, intracellular application of TRPC4 and TRPC5 antibodies significantly reduced persistent firing. Taken together these results indicate that TRPC4 and 5 channels support persistent firing in CA1 pyramidal neurons. Finally, we discuss possible scenarios causing these controversial observations on the role of TRPC channels in persistent firing.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

OBJECTIVE

We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient's own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval.

APPROACH

We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task.

MAIN RESULTS

MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information.

SIGNIFICANCE

These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Dorsal hippocampus is necessary for visual categorization in rats

The hippocampus may play a role in categorization because of the need to differentiate stimulus categories (pattern separation) and to recognize category membership of stimuli from partial information (pattern completion). We hypothesized that the hippocampus would be more crucial for categorization of low-density (few relevant features) stimuli-due to the higher demand on pattern separation and pattern completion-than for categorization of high-density (many relevant features) stimuli. Using a touchscreen apparatus, rats were trained to categorize multiple abstract stimuli into two different categories. Each stimulus was a pentagonal configuration of five visual features; some of the visual features were relevant for defining the category whereas others were irrelevant. Two groups of rats were trained with either a high (dense, n = 8) or low (sparse, n = 8) number of category-relevant features. Upon reaching criterion discrimination (≥75% correct, on 2 consecutive days), bilateral cannulas were implanted in the dorsal hippocampus. The rats were then given either vehicle or muscimol infusions into the hippocampus just prior to various testing sessions. They were tested with: the previously trained stimuli (trained), novel stimuli involving new irrelevant features (novel), stimuli involving relocated features (relocation), and a single relevant feature (singleton). In training, the dense group reached criterion faster than the sparse group, indicating that the sparse task was more difficult than the dense task. In testing, accuracy of both groups was equally high for trained and novel stimuli. However, both groups showed impaired accuracy in the relocation and singleton conditions, with a greater deficit in the sparse group. The testing data indicate that rats encode both the relevant features and the spatial locations of the features. Hippocampal inactivation impaired visual categorization regardless of the density of the category-relevant features for the trained, novel, relocation, and singleton stimuli. Hippocampus-mediated pattern completion and pattern separation mechanisms may be necessary for visual categorization involving overlapping irrelevant features.

Humans' Relationship to Flowers as an Example of the Multiple Components of Embodied Aesthetics

This paper phenomenologically and qualitatively explores the relationship between humans and flowers as a relationship that throws light on the synergetic dynamics of embodied aesthetics. Its methods include qualitative description and thematic analyses of preferred flower types, as well as concept maps of the general term ‘flower’ by 120 students in Israel. The results revealed the interactive perceptual-compositional elements, as well as embodied, relational, and socially embedded elements of the aesthetic pleasure associated with flowers. Implications of this case study are generalized to understand the multiple and interactive components of embodied aesthetic experiences as a deep source of pleasure through interactive stimulation by and connection to the natural world.

Do TRPC channels support working memory? Comparing modulations of TRPC channels and working memory through G-protein coupled receptors and neuromodulators

Working memory is a crucial ability we use in daily life. However, the cellular mechanisms supporting working memory still remain largely unclear. A key component of working memory is persistent neural firing which is believed to serve short-term (hundreds of milliseconds up to tens of seconds) maintenance of necessary information. In this review, we will focus on the role of transient receptor potential canonical (TRPC) channels as a mechanism underlying persistent firing. Many years of in vitro work have been suggesting a crucial role of TRPC channels in working memory and temporal association tasks. If TRPC channels are indeed a central mechanism for working memory, manipulations which impair or facilitate working memory should have a similar effect on TRPC channel modulation. However, modulations of working memory and TRPC channels were never systematically compared, and it remains unanswered whether TRPC channels indeed contribute to working memory in vivo or not. In this article, we review the effects of G-protein coupled receptors (GPCR) and neuromodulators, including acetylcholine, noradrenalin, serotonin and dopamine, on working memory and TRPC channels. Based on comparisons, we argue that GPCR and downstream signaling pathways that activate TRPC, generally support working memory, while those that suppress TRPC channels impair it. However, depending on the channel types, areas, and systems tested, this is not the case in all studies. Further work to clarify involvement of specific TRPC channels in working memory tasks and how they are affected by neuromodulators is still necessary in the future.

Different Levels of Category Abstraction by Different Dynamics in Different Prefrontal Areas

Categories can be grouped by shared sensory attributes (i.e., cats) or a more abstract rule (i.e., animals). We explored the neural basis of abstraction by recording from multi-electrode arrays in prefrontal cortex (PFC) while monkeys performed a dot-pattern categorization task. Category abstraction was varied by the degree of exemplar distortion from the prototype pattern. Different dynamics in different PFC regions processed different levels of category abstraction. Bottom-up dynamics (stimulus-locked gamma power and spiking) in the ventral PFC processed more low-level abstractions, whereas top-down dynamics (beta power and beta spike-LFP coherence) in the dorsal PFC processed more high-level abstractions. Our results suggest a two-stage, rhythm-based model for abstracting categories.

Spatial Responses, Immediate Experience, and Memory in the Monkey Hippocampus

Debate about the function of the hippocampus often pits theories advocating for spatial mapping against those that argue for a central role in memory. This review addresses whether research in the monkey supports the view that processing spatial information is fundamental to the function of the hippocampus. In support of spatial processing theories, neurons in the monkey hippocampal formation have striking spatial tuning, and an intact hippocampus is necessary to effectively utilize allocentric spatial relationships. However, the hippocampus also supports non-spatial processes, as its neurons acutely respond to distinct task events and hippocampal damage disrupts both expedient task acquisition and the monitoring of ongoing events in non-spatial paradigms. The features that are shared between spatial and non-spatial hippocampal-dependent tasks point toward a common mechanism underlying hippocampal function that is independent of processing spatial information. We suggest that spatial information is only one facet of immediate experience represented by the hippocampus. The current data support the idea that the hippocampus tracks many aspects of ongoing experience and the primary role of the hippocampus may be in linking experienced events into unitary episodes.

Temporal and Rate Coding for Discrete Event Sequences in the Hippocampus

Although the hippocampus is critical to episodic memory, neuronal representations supporting this role, especially relating to nonspatial information, remain elusive. Here, we investigated rate and temporal coding of hippocampal CA1 neurons in rats performing a cue-combination task that requires the integration of sequentially provided sound and odor cues. The majority of CA1 neurons displayed sensory cue-, combination-, or choice-specific (simply, "event"-specific) elevated discharge activities, which were sustained throughout the event period. These event cells underwent transient theta phase precession at event onset, followed by sustained phase locking to the early theta phases. As a result of this unique single neuron behavior, the theta sequences of CA1 cell assemblies of the event sequences had discrete representations. These results help to update the conceptual framework for space encoding toward a more general model of episodic event representations in the hippocampus.

Long-term coding of personal and universal associations underlying the memory web in the human brain

Neurons in the medial temporal lobe (MTL), a critical area for declarative memory, have been shown to change their tuning in associative learning tasks. Yet, it is unclear how durable these neuronal representations are and if they outlast the execution of the task. To address this issue, we studied the responses of MTL neurons in neurosurgical patients to known concepts (people and places). Using association scores provided by the patients and a web-based metric, here we show that whenever MTL neurons respond to more than one concept, these concepts are typically related. Furthermore, the degree of association between concepts could be successfully predicted based on the neurons' response patterns. These results provide evidence for a long-term involvement of MTL neurons in the representation of durable associations, a hallmark of human declarative memory.

Neurons in the medial temporal lobe change their firing patterns as people learn to pair items together, yet it is unclear if this pairing lasts. Here, authors find that single medial temporal lobe neurons in humans tend to respond similarly to items that are closely conceptually related.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2ⁱ–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

Expectation influences the interruptive function of pain: Behavioural and neural findings

BACKGROUND

Expectations can dramatically influence the perception of pain, as has been shown in placebo analgesia or nocebo hyperalgesia. Here, we investigated the role of expectation on the interruptive function of pain - the negative consequences of pain on cognitive task performance - in 42 healthy human subjects.

METHODS

Verbal and written instructions were used to manipulate the subjects' expectation of how pain would influence their task performance in an established visual categorization task which was performed with or without concomitant painful thermal stimulation during 3T fMRI scanning. The categorization task was followed by a surprise recognition task.

RESULTS

We observed a significant interaction between stimulation (pain/no pain) and expectancy (positive expectation/negative expectation): categorization accuracy decreased during painful stimulation in the negative expectancy group (N = 21), while no difference was observed in the positive expectancy group (N = 21). On the neural level, the positive expectancy group showed stronger activity in the anterior cingulate cortex (ACC) and hippocampus during painful stimulation compared to the negative group. Moreover, we detected a decrease in connectivity between ACC and fusiform gyrus during painful stimulation in the negative expectancy group, which was absent in the positive expectancy group.

CONCLUSION

Taken together, our data show that expectation can modulate the effect of pain on task performance and that these expectancy effects on the interruptive function of pain are mediated by activity and connectivity changes in brain areas involved in pain processing and task performance. The possibility of changing cognitive task performance by verbal information in clinical population warrants further investigation.

SIGNIFICANCE

We show that the interruptive function of pain on concurrent visual task performance is influenced by expectation. Positive expectation can abolish the detrimental effects of pain on cognition. These expectancy effects on the interruptive function of pain are mediated by changes in functional connectivity between rostral ACC, posterior fusiform cortex and the hippocampus.

An interplay of fusiform gyrus and hippocampus enables prototype- and exemplar-based category learning

The aim of the present study was to examine the contributions of different brain structures to prototype- and exemplar-based category learning using functional magnetic resonance imaging (fMRI). Twenty-eight subjects performed a categorization task in which they had to assign prototypes and exceptions to two different families. This test procedure usually produces different learning curves for prototype and exception stimuli. Our behavioral data replicated these previous findings by showing an initially superior performance for prototypes and typical stimuli and a switch from a prototype-based to an exemplar-based categorization for exceptions in the later learning phases. Since performance varied, we divided participants into learners and non-learners. Analysis of the functional imaging data revealed that the interaction of group (learners vs. non-learners) and block (Block 5 vs. Block 1) yielded an activation of the left fusiform gyrus for the processing of prototypes, and an activation of the right hippocampus for exceptions after learning the categories. Thus, successful prototype- and exemplar-based category learning is associated with activations of complementary neural substrates that constitute object-based processes of the ventral visual stream and their interaction with unique-cue representations, possibly based on sparse coding within the hippocampus.

A cognitive prosthesis for memory facilitation by closed-loop functional ensemble stimulation of hippocampal neurons in primate brain

Very productive collaborative investigations characterized how multineuron hippocampal ensembles recorded in nonhuman primates (NHPs) encode short-term memory necessary for successful performance in a delayed match to sample (DMS) task and utilized that information to devise a unique nonlinear multi-input multi-output (MIMO) memory prosthesis device to enhance short-term memory in real-time during task performance. Investigations have characterized how the hippocampus in primate brain encodes information in a multi-item, rule-controlled, delayed match to sample (DMS) task. The MIMO model was applied via closed loop feedback micro-current stimulation during the task via conformal electrode arrays and enhanced performance of the complex memory requirements. These findings clearly indicate detection of a means by which the hippocampus encodes information and transmits this information to other brain regions involved in memory processing. By employing the nonlinear dynamic multi-input/multi-output (MIMO) model, developed and adapted to hippocampal neural ensemble firing patterns derived from simultaneous recorded multi-neuron CA1 and CA3 activity, it was possible to extract information encoded in the Sample phase of DMS trials that was necessary for successful performance in the subsequent Match phase of the task. The extension of this MIMO model to online delivery of electrical stimulation patterns to the same recording loci that exhibited successful CA1 firing in the DMS Sample Phase provided the means to increase task performance on a trial-by-trial basis. Increased utility of the MIMO model as a memory prosthesis was exhibited by the demonstration of cumulative increases in DMS task performance with repeated MIMO stimulation over many sessions. These results, reported below in this article, provide the necessary demonstrations to further the feasibility of the MIMO model as a memory prosthesis to recover and/or enhance encoding of cognitive information in humans with memory disruptions resulting from brain injury, disease or aging.

The role of piriform associative connections in odor categorization

Distributed neural activity patterns are widely proposed to underlie object identification and categorization in the brain. In the olfactory domain, pattern-based representations of odor objects are encoded in piriform cortex. This region receives both afferent and associative inputs, though their relative contributions to odor perception are poorly understood. Here, we combined a placebo-controlled pharmacological fMRI paradigm with multivariate pattern analyses to test the role of associative connections in sustaining olfactory categorical representations. Administration of baclofen, a GABA(B) agonist known to attenuate piriform associative inputs, interfered with within-category pattern separation in piriform cortex, and the magnitude of this drug-induced change predicted perceptual alterations in fine-odor discrimination performance. Comparatively, baclofen reduced pattern separation between odor categories in orbitofrontal cortex, and impeded within-category generalization in hippocampus. Our findings suggest that odor categorization is a dynamic process concurrently engaging stimulus discrimination and generalization at different stages of olfactory information processing, and highlight the importance of associative networks in maintaining categorical boundaries.

DOI:http://dx.doi.org/10.7554/eLife.13732.001

Imagine bringing your groceries home and tucking them into the refrigerator. You’ll probably organize the items by categories: lemons and oranges into the fruit drawer, carrots and cauliflower into the vegetable drawer. Categorization is essential, allowing us to interact with the world in the most efficient way possible. If the differences between objects are not relevant to the task at hand, the brain will group objects together based on their shared properties and develop mental representations of the “categories”. Importantly, we are still aware of the distinctions between objects within the same category.

Categories of odor (for example, minty or fruity) are represented in a part of the brain called the olfactory (or piriform) cortex, which receives information from odor cues as well as “top-down” information from other areas of the brain. But how do these top-down pathways influence odor categorization?

Bao et al. asked how the brain solves the problem of categorizing odors. For the experiments, human volunteers smelled six familiar odors belonging to three different categories while their brain activity was monitored using a magnetic resonance imaging (fMRI) scanner. Then, half of the participants were given a drug called baclofen that prevents top-down inputs, but not odor cues, from reaching the piriform cortex, while the rest received a placebo. After five days of taking the medication, all of the volunteers had another session of fMRI where they had to categorize the same odors as before.

The experiments show that when comparing the fMRI scans before and after the drug treatment, the representations of odors belonging to the same category became more distinct in the piriform cortex in the placebo group. Put differently, as the volunteers were repeatedly exposed to odors of well-known categories, they became better at discriminating individual odors within the same category. However, these changes were disrupted in the group of volunteers that took baclofen.

Bao et al.’s findings indicate that this “practice makes perfect” approach to recognizing odors relies on top-down inputs into the piriform cortex. In future work it will be important to study the roles of these inputs in learning new categories of odors, and to investigate whether the mechanisms identified here apply to other sensory information and to more abstract knowledge.

DOI:http://dx.doi.org/10.7554/eLife.13732.002

Dream to Predict? REM Dreaming as Prospective Coding

The dream as prediction seems inherently improbable. The bizarre occurrences in dreams never characterize everyday life. Dreams do not come true! But assuming that bizarreness negates expectations may rest on a misunderstanding of how the predictive brain works. In evolutionary terms, the ability to rapidly predict what sensory input implies-through expectations derived from discerning patterns in associated past experiences-would have enhanced fitness and survival. For example, food and water are essential for survival, associating past experiences (to identify location patterns) predicts where they can be found. Similarly, prediction may enable predator identification from what would have been only a fleeting and ambiguous stimulus-without prior expectations. To confront the many challenges associated with natural settings, visual perception is vital for humans (and most mammals) and often responses must be rapid. Predictive coding during wake may, therefore, be based on unconscious imagery so that visual perception is maintained and appropriate motor actions triggered quickly. Speed may also dictate the form of the imagery. Bizarreness, during REM dreaming, may result from a prospective code fusing phenomena with the same meaning-within a particular context. For example, if the context is possible predation, from the perspective of the prey two different predators can both mean the same (i.e., immediate danger) and require the same response (e.g., flight). Prospective coding may also prune redundancy from memories, to focus the image on the contextually-relevant elements only, thus, rendering the non-relevant phenomena indeterminate-another aspect of bizarreness. In sum, this paper offers an evolutionary take on REM dreaming as a form of prospective coding which identifies a probabilistic pattern in past events. This pattern is portrayed in an unconscious, associative, sensorimotor image which may support cognition in wake through being mobilized as a predictive code. A particular dream illustrates.

Representation of memories in the cortical-hippocampal system: Results from the application of population similarity analyses

Here we consider the value of neural population analysis as an approach to understanding how information is represented in the hippocampus and cortical areas and how these areas might interact as a brain system to support memory. We argue that models based on sparse coding of different individual features by single neurons in these areas (e.g., place cells, grid cells) are inadequate to capture the complexity of experience represented within this system. By contrast, population analyses of neurons with denser coding and mixed selectivity reveal new and important insights into the organization of memories. Furthermore, comparisons of the organization of information in interconnected areas suggest a model of hippocampal-cortical interactions that mediates the fundamental features of memory.

Distributed encoding of spatial and object categories in primate hippocampal microcircuits

The primate hippocampus plays critical roles in the encoding, representation, categorization and retrieval of cognitive information. Such cognitive abilities may use the transformational input-output properties of hippocampal laminar microcircuitry to generate spatial representations and to categorize features of objects, images, and their numeric characteristics. Four nonhuman primates were trained in a delayed-match-to-sample (DMS) task while multi-neuron activity was simultaneously recorded from the CA1 and CA3 hippocampal cell fields. The results show differential encoding of spatial location and categorization of images presented as relevant stimuli in the task. Individual hippocampal cells encoded visual stimuli only on specific types of trials in which retention of either, the Sample image, or the spatial position of the Sample image indicated at the beginning of the trial, was required. Consistent with such encoding, it was shown that patterned microstimulation applied during Sample image presentation facilitated selection of either Sample image spatial locations or types of images, during the Match phase of the task. These findings support the existence of specific codes for spatial and numeric object representations in primate hippocampus which can be applied on differentially signaled trials. Moreover, the transformational properties of hippocampal microcircuitry, together with the patterned microstimulation are supporting the practical importance of this approach for cognitive enhancement and rehabilitation, needed for memory neuroprosthetics.

A neural network model of reliably optimized spike transmission

We studied the detailed structure of a neuronal network model in which the spontaneous spike activity is correctly optimized to match the experimental data and discuss the reliability of the optimized spike transmission. Two stochastic properties of the spontaneous activity were calculated: the spike-count rate and synchrony size. The synchrony size, expected to be an important factor for optimization of spike transmission in the network, represents a percentage of observed coactive neurons within a time bin, whose probability approximately follows a power-law. We systematically investigated how these stochastic properties could matched to those calculated from the experimental data in terms of the log-normally distributed synaptic weights between excitatory and inhibitory neurons and synaptic background activity induced by the input current noise in the network model. To ensure reliably optimized spike transmission, the synchrony size as well as spike-count rate were simultaneously optimized. This required changeably balanced log-normal distributions of synaptic weights between excitatory and inhibitory neurons and appropriately amplified synaptic background activity. Our results suggested that the inhibitory neurons with a hub-like structure driven by intensive feedback from excitatory neurons were a key factor in the simultaneous optimization of the spike-count rate and synchrony size, regardless of different spiking types between excitatory and inhibitory neurons.

A robust in vivo-like persistent firing supported by a hybrid of intracellular and synaptic mechanisms

Persistent firing is believed to support short-term information retention in the brain. Established hypotheses make use of the recurrent synaptic connectivity to support persistent firing. However, this mechanism is known to suffer from a lack of robustness. On the other hand, persistent firing can be supported by an intrinsic cellular mechanism in multiple brain areas. However, the consequences of having both the intrinsic and the synaptic mechanisms (a hybrid model) on persistent firing remain largely unknown. The goal of this study is to investigate whether a hybrid neural network model with these two mechanisms has advantages over a conventional recurrent network based model. Our computer simulations were based on in vitro recordings obtained from hippocampal CA3 pyramidal cells under cholinergic receptor activation. Calcium activated non-specific cationic (CAN) current supported persistent firing in the Hodgkin-Huxley style cellular models. Our results suggest that the hybrid model supports persistent firing within a physiological frequency range over a wide range of different parameters, eliminating parameter sensitivity issues generally recognized in network based persistent firing. In addition, persistent firing in the hybrid model is substantially more robust against distracting inputs, can coexist with theta frequency oscillations, and supports pattern completion.

Neurons and networks organizing and sequencing memories

Hippocampal CA1 and CA3 neurons sampled randomly in large numbers in primate brain show conclusive examples of hierarchical encoding of task specific information. Hierarchical encoding allows multi-task utilization of the same hippocampal neural networks via distributed firing between neurons that respond to subsets, attributes or "categories" of stimulus features which can be applied in events in different contexts. In addition, such networks are uniquely adaptable to neural systems unrestricted by rigid synaptic architecture (i.e. columns, layers or "patches") which physically limits the number of possible task-specific interactions between neurons. Also hierarchical encoding is not random; it requires multiple exposures to the same types of relevant events to elevate synaptic connectivity between neurons for different stimulus features that occur in different task-dependent contexts. The large number of cells within associated hierarchical circuits in structures such as hippocampus provides efficient processing of information relevant to common memory-dependent behavioral decisions within different contextual circumstances. This article is part of a Special Issue entitled SI: Brain and Memory.

Functional dynamics of primate cortico-striatal networks during volitional movements

The motor cortex and dorsal striatum (caudate nucleus and putamen) are key regions in motor processing but the interface between the cortex and striatum is not well understood. While dorsal striatum integrates information from multiple brain regions to shape motor learning and habit formation, the disruption of cortico-striatal circuits compromises the functionality of these circuits resulting in a multitude of neurologic disorders, including Parkinson's disease. To better understand the modulation of the cortico-striatal circuits we recorded simultaneously single neuron activity from four brain regions, primary motor, and sensory cortices, together with the rostral and caudal segments of the putamen in rhesus monkeys performing a visual motor task. Results show that spatial and temporal-task related firing relationships between these cortico-striatal circuit regions were modified by the independent administration of the two drugs (cocaine and baclofen). Spatial tuning and correlated firing of neurons from motor cortex and putamen were severely disrupted by cocaine and baclofen on correct trials, while the two drugs have dramatically decreased the functional connectivity of the motor cortical-striatal network. These findings provide insight into the modulation of cortical-striatal firing related to movement with implications for therapeutic approaches to Parkinson's disease and related disorders.

Facilitation of memory encoding in primate hippocampus by a neuroprosthesis that promotes task-specific neural firing

OBJECTIVE

Memory accuracy is a major problem in human disease and is the primary factor that defines Alzheimer's, ageing and dementia resulting from impaired hippocampal function in the medial temporal lobe. Development of a hippocampal memory neuroprosthesis that facilitates normal memory encoding in nonhuman primates (NHPs) could provide the basis for improving memory in human disease states.

APPROACH

NHPs trained to perform a short-term delayed match-to-sample (DMS) memory task were examined with multi-neuron recordings from synaptically connected hippocampal cell fields, CA1 and CA3. Recordings were analyzed utilizing a previously developed nonlinear multi-input multi-output (MIMO) neuroprosthetic model, capable of extracting CA3-to-CA1 spatiotemporal firing patterns during DMS performance.

MAIN RESULTS

The MIMO model verified that specific CA3-to-CA1 firing patterns were critical for the successful encoding of sample phase information on more difficult DMS trials. This was validated by the delivery of successful MIMO-derived encoding patterns via electrical stimulation to the same CA1 recording locations during the sample phase which facilitated task performance in the subsequent, delayed match phase, on difficult trials that required more precise encoding of sample information.

SIGNIFICANCE

These findings provide the first successful application of a neuroprosthesis designed to enhance and/or repair memory encoding in primate brain.

Mapping and deciphering neural codes of NMDA receptor-dependent fear memory engrams in the hippocampus

Mapping and decoding brain activity patterns underlying learning and memory represents both great interest and immense challenge. At present, very little is known regarding many of the very basic questions regarding the neural codes of memory: are fear memories retrieved during the freezing state or non-freezing state of the animals? How do individual memory traces give arise to a holistic, real-time associative memory engram? How are memory codes regulated by synaptic plasticity? Here, by applying high-density electrode arrays and dimensionality-reduction decoding algorithms, we investigate hippocampal CA1 activity patterns of trace fear conditioning memory code in inducible NMDA receptor knockout mice and their control littermates. Our analyses showed that the conditioned tone (CS) and unconditioned foot-shock (US) can evoke hippocampal ensemble responses in control and mutant mice. Yet, temporal formats and contents of CA1 fear memory engrams differ significantly between the genotypes. The mutant mice with disabled NMDA receptor plasticity failed to generate CS-to-US or US-to-CS associative memory traces. Moreover, the mutant CA1 region lacked memory traces for “what at when” information that predicts the timing relationship between the conditioned tone and the foot shock. The degraded associative fear memory engram is further manifested in its lack of intertwined and alternating temporal association between CS and US memory traces that are characteristic to the holistic memory recall in the wild-type animals. Therefore, our study has decoded real-time memory contents, timing relationship between CS and US, and temporal organizing patterns of fear memory engrams and demonstrated how hippocampal memory codes are regulated by NMDA receptor synaptic plasticity.

Conformal ceramic electrodes that record glutamate release and corresponding neural activity in primate prefrontal cortex

Conformal ceramic electrodes utilized in prior recordings of nonhuman primate prefrontal cortical layer 2/3 and layer 5 neurons were used in this study to record tonic glutamate concentration and transient release in layer 2/3 PFC. Tonic glutamate concentration increased in the Match (decision) phase of a visual delayed-match-to-sample (DMS) task, while increased transient glutamate release occurred in the Sample (encoding) phase of the task. Further, spatial vs. object-oriented DMS trials evoked differential changes in glutamate concentration. Thus the same conformal recording electrodes were capable of electrophysiological and electrochemical recording, and revealed similar evidence of neural processing in layers 2/3 and layer 5 during cognitive processing in a behavioral task.

Learning causes reorganization of neuronal firing patterns to represent related experiences within a hippocampal schema

According to schema theory as proposed by Piaget and Bartlett, learning involves the assimilation of new memories into networks of preexisting knowledge, as well as alteration of the original networks to accommodate the new information. Recent evidence has shown that rats form a schema of goal locations and that the hippocampus plays an essential role in adding new memories to the spatial schema. Here we examined the nature of hippocampal contributions to schema updating by monitoring firing patterns of multiple CA1 neurons as rats learned new goal locations in an environment in which there already were multiple goals. Before new learning, many neurons that fired on arrival at one goal location also fired at other goals, whereas ensemble activity patterns also distinguished different goal events, thus constituting a neural representation that linked distinct goals within a spatial schema. During new learning, some neurons began to fire as animals approached the new goals. These were primarily the same neurons that fired at original goals, the activity patterns at new goals were similar to those associated with the original goals, and new learning also produced changes in the preexisting goal-related firing patterns. After learning, activity patterns associated with the new and original goals gradually diverged, such that initial generalization was followed by a prolonged period in which new memories became distinguished within the ensemble representation. These findings support the view that consolidation involves assimilation of new memories into preexisting neural networks that accommodate relationships among new and existing memories.

On brain activity mapping: insights and lessons from Brain Decoding Project to map memory patterns in the hippocampus

The BRAIN project recently announced by the president Obama is the reflection of unrelenting human quest for cracking the brain code, the patterns of neuronal activity that define who we are and what we are. While the Brain Activity Mapping proposal has rightly emphasized on the need to develop new technologies for measuring every spike from every neuron, it might be helpful to consider both the theoretical and experimental aspects that would accelerate our search for the organizing principles of the brain code. Here we share several insights and lessons from the similar proposal, namely, Brain Decoding Project that we initiated since 2007. We provide a specific example in our initial mapping of real-time memory traces from one part of the memory circuit, namely, the CA1 region of the mouse hippocampus. We show how innovative behavioral tasks and appropriate mathematical analyses of large datasets can play equally, if not more, important roles in uncovering the specific-to-general feature-coding cell assembly mechanism by which episodic memory, semantic knowledge, and imagination are generated and organized. Our own experiences suggest that the bottleneck of the Brain Project is not only at merely developing additional new technologies, but also the lack of efficient avenues to disseminate cutting edge platforms and decoding expertise to neuroscience community. Therefore, we propose that in order to harness unique insights and extensive knowledge from various investigators working in diverse neuroscience subfields, ranging from perception and emotion to memory and social behaviors, the BRAIN project should create a set of International and National Brain Decoding Centers at which cutting-edge recording technologies and expertise on analyzing large datasets analyses can be made readily available to the entire community of neuroscientists who can apply and schedule to perform cutting-edge research.

On initial Brain Activity Mapping of episodic and semantic memory code in the hippocampus

It has been widely recognized that the understanding of the brain code would require large-scale recording and decoding of brain activity patterns. In 2007 with support from Georgia Research Alliance, we have launched the Brain Decoding Project Initiative with the basic idea which is now similarly advocated by BRAIN project or Brain Activity Map proposal. As the planning of the BRAIN project is currently underway, we share our insights and lessons from our efforts in mapping real-time episodic memory traces in the hippocampus of freely behaving mice. We show that appropriate large-scale statistical methods are essential to decipher and measure real-time memory traces and neural dynamics. We also provide an example of how the carefully designed, sometime thinking-outside-the-box, behavioral paradigms can be highly instrumental to the unraveling of memory-coding cell assembly organizing principle in the hippocampus. Our observations to date have led us to conclude that the specific-to-general categorical and combinatorial feature-coding cell assembly mechanism represents an emergent property for enabling the neural networks to generate and organize not only episodic memory, but also semantic knowledge and imagination.

Long-lasting intrinsic persistent firing in rat CA1 pyramidal cells: a possible mechanism for active maintenance of memory

The hippocampus is critical for memory tasks which require an active maintenance of memory for a short period of time; however, the underlying neural mechanisms remain unknown. Most theoretical and computational models, which date back to the classic proposals by Donald Hebb in , have been self-constrained by anatomy, as most models rely on the recurrent connectivity in region CA3 to support "reverberating activity" capable of memory maintenance. However, several physiological and behavioral studies have specifically implicated region CA1 in tasks which require an active maintenance of memory. Here, we demonstrate that despite limited recurrent connectivity, CA1 contains a robust cellular mechanism for active memory maintenance in the form of self-sustained persistent firing. Using in vitro whole-cell recordings, we demonstrate that brief stimulation (0.2-2 s) reliably elicits long-lasting (> 30 s) persistent firing that is supported by the calcium-activated non-selective cationic current. In contrast to more traditional ideas, these data suggest that the hippocampal region CA1 is capable of active maintenance of memory.

Acute cocaine induced deficits in cognitive performance in rhesus macaque monkeys treated with baclofen

RATIONALE

Acute and/or chronic exposure to cocaine can affect cognitive performance, which may influence rate of recovery during treatment.

OBJECTIVE

Effects of the GABA-B receptor agonist baclofen were assessed for potency to reverse the negative influence of acute, pre-session, intravenous (IV) injection of cocaine on cognitive performance in Macaca mulatta nonhuman primates.

METHODS

Animals were trained to perform a modified delayed match to sample (DMS) task incorporating two types of trials with varying degrees of cognitive load that had different decision requirements in order to correctly utilize information retained over the delay interval. The effects of cocaine (0.2, 0.4, and 0.6 mg/kg, IV) alone and in combination with baclofen (0.29 and 0.40 mg/kg, IV) were examined with respect to sustained performance levels. Brain metabolic activity during performance of the task was assessed using PET imaged uptake of [(18) F]-fluorodeoxyglucose.

RESULTS

Acute cocaine injections produced a dose-dependent decline in DMS performance selective for trials of high cognitive load. The GABA-receptor agonist baclofen, co-administered with cocaine, reversed task performance back to nondrug (saline IV) control levels. Simultaneous assessment of PET-imaged brain metabolic activity in prefrontal cortex (PFC) showed alterations by cocaine compared to PFC metabolic activation in nondrug (saline, IV) control DMS sessions, but like performance, PFC activation was returned to control levels by baclofen (0.40 mg/kg, IV) injected with cocaine.

CONCLUSIONS

The results show that baclofen, administered at a relatively high dose, reversed the cognitive deficits produced by acute cocaine intoxication that may have implications for use in chronic drug exposure.

The hippocampus is required for visually cued contextual response selection, but not for visual discrimination of contexts

The hippocampus is important for spatial navigation. Literature shows that allocentric visual contexts in the animal's background are critical for making conditional response selections during navigations. In a traditional maze task, however, it is difficult to identify exactly which subsets of visual contexts are critically used. In the current study, we tested in rats whether making conditional response selections required the hippocampus when using computer-generated visual contextual stimuli in the animal's background as in primate and human studies. We designed a new task, visual contextual response selection (VCRS) task, in which the rat ran along a linear track and encountered a touchscreen monitor at the end of the track. The rat was required to touch one of the adjacent rectangular box images depending on the visual contextual stimuli displayed in the two peripheral monitors positioned on both sides of the center touchscreen monitor. The rats with a GABA-A receptor agonist, muscimol (MUS), infused bilaterally in the dorsal hippocampi showed severe performance deficits in the VCRS task and the impairment was completely reversible with vehicle injections. The impairment in contextual response selection with hippocampal inactivations occurred regardless of whether the visual context was presented in the side monitors or in the center touchscreen monitor. However, when the same visual contextual stimuli were pitted against each other between the two side monitors and as the rats simply ran toward the visual context associated with reward on a T-shaped track, hippocampal inactivations with MUS showed minimal disruptions, if any, in performance. Our results suggest that the hippocampus is critically involved in conditional response selection using visual stimuli in the background, but it is not required for the perceptual discrimination of those stimuli.

Columnar processing in primate pFC: evidence for executive control microcircuits

A common denominator for many cognitive disorders of human brain is the disruption of neural activity within pFC, whose structural basis is primarily interlaminar (columnar) microcircuits or "minicolumns." The importance of this brain region for executive decision-making has been well documented; however, because of technological constraints, the minicolumnar basis is not well understood. Here, via implementation of a unique conformal multielectrode recording array, the role of interlaminar pFC minicolumns in the executive control of task-related target selection is demonstrated in nonhuman primates performing a visuomotor DMS task. The results reveal target-specific, interlaminar correlated firing during the decision phase of the trial between multielectrode recording array-isolated minicolumnar pairs of neurons located in parallel in layers 2/3 and layer 5 of pFC. The functional significance of individual pFC minicolumns (separated by 40 μm) was shown by reduced correlated firing between cell pairs within single minicolumns on error trials with inappropriate target selection. To further demonstrate dependence on performance, a task-disrupting drug (cocaine) was administered in the middle of the session, which also reduced interlaminar firing in minicolumns that fired appropriately in the early (nondrug) portion of the session. The results provide a direct demonstration of task-specific, real-time columnar processing in pFC indicating the role of this type of microcircuit in executive control of decision-making in primate brain.

Facilitation and restoration of cognitive function in primate prefrontal cortex by a neuroprosthesis that utilizes minicolumn-specific neural firing

OBJECTIVE

Maintenance of cognitive control is a major concern for many human disease conditions; therefore, a major goal of human neuroprosthetics is to facilitate and/or recover the cognitive function when such circumstances impair appropriate decision making.

APPROACH

Minicolumnar activity from the prefrontal cortex (PFC) was recorded from nonhuman primates trained to perform a delayed match to sample (DMS), via custom-designed conformal multielectrode arrays that provided inter-laminar recordings from neurons in the PFC layer 2/3 and layer 5. Such recordings were analyzed via a previously demonstrated nonlinear multi-input-multi-output (MIMO) neuroprosthesis in rodents, which extracted and characterized multicolumnar firing patterns during DMS performance.

MAIN RESULTS

The MIMO model verified that the conformal recorded individual PFC minicolumns responded to entrained target selections in patterns critical for successful DMS performance. This allowed the substitution of task-related layer 5 neuron firing patterns with electrical stimulation in the same recording regions during columnar transmission from layer 2/3 at the time of target selection. Such stimulation improved normal task performance, but more importantly, recovered performance when applied as a neuroprosthesis following the pharmacological disruption of decision making in the same task.

SIGNIFICANCE

These findings provide the first successful application of neuroprosthesis in the primate brain designed specifically to restore or repair the disrupted cognitive function.

Role of the hippocampus in memory formation: restorative encoding memory integration neural device as a cognitive neural prosthesis

Remind, which stands for "restorative encoding memory integration neural device," is a Defense Advanced Research Projects Agency (DARPA)-sponsored program to construct the first-ever cognitive prosthesis to replace lost memory function and enhance the existing memory capacity in animals and, ultimately, in humans. Reaching this goal involves understanding something fundamental about the brain that has not been understood previously: how the brain internally codes memories. In developing a hippocampal prosthesis for the rat, we have been able to demonstrate a multiple-input, multiple- output (MIMO) nonlinear model that predicts in real time the spatiotemporal codes for specific memories required for correct performance on a standard learning/memory task, i.e., delayed-nonmatch-to-sample (DNMS) memory. The MIMO model has been tested successfully in a number of contexts; most notably, in animals with a pharmacologically disabled hippocampus, we were able to reinstate long-term memories necessary for correct DNMS behavior by substituting a MIMO model-predicted code, delivered by electrical stimulation to the hippocampus through an array of electrodes, resulting in spatiotemporal hippocampal activity that is normally generated endogenously. We also have shown that delivering the same model-predicted code to electrode-implanted control animals with a normally functioning hippocampus substantially enhances animals memory capacity above control levels. These results in rodents have formed the basis for extending the MIMO model to nonhuman primates; this is now underway as the last step of the REMIND program before developing a MIMO-based cognitive prosthesis for humans.

Nonlinear modeling of dynamic interactions within neuronal ensembles using Principal Dynamic Modes

A methodology for nonlinear modeling of multi-input multi-output (MIMO) neuronal systems is presented that utilizes the concept of Principal Dynamic Modes (PDM). The efficacy of this new methodology is demonstrated in the study of the dynamic interactions between neuronal ensembles in the Pre-Frontal Cortex (PFC) of a behaving non-human primate (NHP) performing a Delayed Match-to-Sample task. Recorded spike trains from Layer-2 and Layer-5 neurons were viewed as the "inputs" and "outputs", respectively, of a putative MIMO system/model that quantifies the dynamic transformation of multi-unit neuronal activity between Layer-2 and Layer-5 of the PFC. Model prediction performance was evaluated by means of computed Receiver Operating Characteristic (ROC) curves. The PDM-based approach seeks to reduce the complexity of MIMO models of neuronal ensembles in order to enable the practicable modeling of large-scale neural systems incorporating hundreds or thousands of neurons, which is emerging as a preeminent issue in the study of neural function. The "scaling-up" issue has attained critical importance as multi-electrode recordings are increasingly used to probe neural systems and advance our understanding of integrated neural function. The initial results indicate that the PDM-based modeling methodology may greatly reduce the complexity of the MIMO model without significant degradation of performance. Furthermore, the PDM-based approach offers the prospect of improved biological/physiological interpretation of the obtained MIMO models.

Ensembles of human MTL neurons "jump back in time" in response to a repeated stimulus

Episodic memory, which depends critically on the integrity of the medial temporal lobe (MTL), has been described as "mental time travel" in which the rememberer "jumps back in time." The neural mechanism underlying this ability remains elusive. Mathematical and computational models of performance in episodic memory tasks provide a specific hypothesis regarding the computation that supports such a jump back in time. The models suggest that a representation of temporal context, a representation that changes gradually over macroscopic periods of time, is the cue for episodic recall. According to these models, a jump back in time corresponds to a stimulus recovering a prior state of temporal context. In vivo single-neuron recordings were taken from the human MTL while epilepsy patients distinguished novel from repeated images in a continuous recognition memory task. The firing pattern of the ensemble of MTL neurons showed robust temporal autocorrelation over macroscopic periods of time during performance of the memory task. The gradually-changing part of the ensemble state was causally affected by the visual stimulus being presented. Critically, repetition of a stimulus caused the ensemble to elicit a pattern of activity that resembled the pattern of activity present before the initial presentation of the stimulus. These findings confirm a direct prediction of this class of temporal context models and may be a signature of the mechanism that underlies the experience of episodic memory as mental time travel.

Category learning increases discriminability of relevant object dimensions in visual cortex

Learning to categorize objects can transform how they are perceived, causing relevant perceptual dimensions predictive of object category to become enhanced. For example, an expert mycologist might become attuned to species-specific patterns of spacing between mushroom gills but learn to ignore cap textures attributable to varying environmental conditions. These selective changes in perception can persist beyond the act of categorizing objects and influence our ability to discriminate between them. Using functional magnetic resonance imaging adaptation, we demonstrate that such category-specific perceptual enhancements are associated with changes in the neural discriminability of object representations in visual cortex. Regions within the anterior fusiform gyrus became more sensitive to small variations in shape that were relevant during prior category learning. In addition, extrastriate occipital areas showed heightened sensitivity to small variations in shape that spanned the category boundary. Visual representations in cortex, just like our perception, are sensitive to an object's history of categorization.

Cholinergic modulation of the CAN current may adjust neural dynamics for active memory maintenance, spatial navigation and time-compressed replay

Suppression of cholinergic receptors and inactivation of the septum impair short-term memory, and disrupt place cell and grid cell activity in the medial temporal lobe (MTL). Location-dependent hippocampal place cell firing during active waking, when the acetylcholine level is high, switches to time-compressed replay activity during quiet waking and slow-wave-sleep (SWS), when the acetylcholine level is low. However, it remains largely unknown how acetylcholine supports short-term memory, spatial navigation, and the functional switch to replay mode in the MTL. In this paper, we focus on the role of the calcium-activated non-specific cationic (CAN) current which is activated by acetylcholine. The CAN current is known to underlie persistent firing, which could serve as a memory trace in many neurons in the MTL. Here, we review the CAN current and discuss possible roles of the CAN current in short-term memory and spatial navigation. We further propose a novel theoretical model where the CAN current switches the hippocampal place cell activity between real-time and time-compressed sequential activity during encoding and consolidation, respectively.

A novel tetrode microdrive for simultaneous multi-neuron recording from different regions of primate brain

A unique custom-made tetrode microdrive for recording from large numbers of neurons in several areas of primate brain is described as a means for assessing simultaneous neural activity in cortical and subcortical structures in nonhuman primates (NHPs) performing behavioral tasks. The microdrive device utilizes tetrode technology with up to six ultra-thin microprobe guide tubes (0.1mm) that can be independently positioned, each containing reduced diameter tetrode and/or hexatrode microwires (0.02 mm) for recording and isolating single neuron activity. The microdrive device is mounted within the standard NHP cranial well and allows traversal of brain depths up to 40.0 mm. The advantages of this technology are demonstrated via simultaneously recorded large populations of neurons with tetrode type probes during task performance from a) primary motor cortex and deep brain structures (caudate-putamen and hippocampus) and b) multiple layers within the prefrontal cortex. The means to characterize interactions of well-isolated ensembles of neurons recorded simultaneously from different regions, as shown with this device, has not been previously available for application in primate brain. The device has extensive application to primate models for the detection and study of inoperative or maladaptive neural circuits related to human neurological disorders.

Restorative encoding memory integrative neural device: "REMIND"

Construction and application of a neural prosthesis device that enhances existing and replaces lost memory capacity in humans is the focus of research described here in rodents. A unique approach for the analysis and application of neural population firing has been developed to decipher the pattern in which information is successfully encoded by the hippocampus where mnemonic accuracy is critical. A nonlinear dynamic multi-input multi-output (MIMO) model is utilized to extract memory relevant firing patterns in CA3 and CA1 and to predict online what the consequences of the encoded firing patterns reflect for subsequent information retrieval for successful performance of delayed-nonmatch-to-sample (DNMS) memory task in rodents. The MIMO model has been tested successfully in a number of different contexts, each of which produced improved performance by a) utilizing online predicted codes to regulate task difficulty, b) employing electrical stimulation of CA1 output areas in the same pattern as successful cell firing, c) employing electrical stimulation to recover cell firing compromised by pharmacological agents and d) transferring and improving performance in naïve animals using the same stimulation patterns that are effective in fully trained animals. The results in rodents formed the basis for extension of the MIMO model to nonhuman primates in the same type of memory task that is now being tested in the last step prior to its application in humans.