Neural representation of visual objects: encoding and top-down activation

Knowledge or experiences are voluntarily recalled from memory by reactivation of their neural representations in the association cortex. Mnemonic representations of visual objects, located in the ventral processing stream of visual perception, provide the best indication of how neuronal codes are created, organized and reactivated. Associative codes are created by neurons that have the ability to link the representations of temporally associated stimuli. Recent experiments suggest that not only bottom-up signals from the retina but also top-down signals from the prefrontal cortex can trigger the retrieval of associative codes, which may serve as a neural basis for conscious recall.     

Neural Coding of Finger and Wrist Movements

Previous work (Schieber and Hibbard, 1993) has shown that single motor cortical neurons do not discharge specifically for a particular flexion-extension finger movement but instead are active with movements of different fingers. In addition, neuronal populations active with movements of different fingers overlap extensively in their spatial locations in the motor cortex. These data suggested that control of any finger movement utilizes a distributed population of neurons. In this study we applied the neuronal population vector analysis (Georgopoulos et al., 1983) to these same data to determine (1) whether single cells are tuned in an abstract, three-dimensional (3D) instructed finger and wrist movement space with hand-like geometry and (2) whether the neuronal population encodes specific finger movements. We found that the activity of 132/176 (75%) motor cortical neurons related to finger movements was indeed tuned in this space. Moreover, the population vector computed in this space predicted well the instructed finger movement. Thus, although single neurons may be related to several disparate finger movements, and neurons related to different finger movements are intermingled throughout the hand area of the motor cortex, the neuronal population activity does specify particular finger movements.     

Age-Related Changes in the Functional Network Underlying Specific and General Autobiographical Memory Retrieval: A Pivotal Role for the Anterior Cingulate Cortex

Age-related changes in autobiographical memory (AM) recall are characterized by a decline in episodic details, while semantic aspects are spared. This deleterious effect is supposed to be mediated by an inefficient recruitment of executive processes during AM retrieval. To date, contrasting evidence has been reported on the neural underpinning of this decline, and none of the previous studies has directly compared the episodic and semantic aspects of AM in elderly. We asked 20 young and 17 older participants to recall specific and general autobiographical events (i.e., episodic and semantic AM) elicited by personalized cues while recording their brain activity by means of fMRI. At the behavioral level, we confirmed that the richness of episodic AM retrieval is specifically impoverished in aging and that this decline is related to the reduction of executive functions. At the neural level, in both age groups, we showed the recruitment of a large network during episodic AM retrieval encompassing prefrontal, cortical midline and posterior regions, and medial temporal structures, including the hippocampus. This network was very similar, but less extended, during semantic AM retrieval. Nevertheless, a greater activity was evidenced in the dorsal anterior cingulate cortex (dACC) during episodic, compared to semantic AM retrieval in young participants, and a reversed pattern in the elderly. Moreover, activity in dACC during episodic AM retrieval was correlated with inhibition and richness of memories in both groups. Our findings shed light on the direct link between episodic AM retrieval, executive control, and their decline in aging, proposing a possible neuronal signature. They also suggest that increased activity in dACC during semantic AM retrieval in the elderly could be seen as a compensatory mechanism underpinning successful AM performance observed in aging. These results are discussed in the framework of recently proposed models of neural reorganization in aging.     

Emergence of a Stable Cortical Map for Neuroprosthetic Control

Cortical control of neuroprosthetic devices is known to require neuronal adaptations. It remains unclear whether a stable cortical representation for prosthetic function can be stored and recalled in a manner that mimics our natural recall of motor skills. Especially in light of the mixed evidence for a stationary neuron-behavior relationship in cortical motor areas, understanding this relationship during long-term neuroprosthetic control can elucidate principles of neural plasticity as well as improve prosthetic function. Here, we paired stable recordings from ensembles of primary motor cortex neurons in macaque monkeys with a constant decoder that transforms neural activity to prosthetic movements. Proficient control was closely linked to the emergence of a surprisingly stable pattern of ensemble activity, indicating that the motor cortex can consolidate a neural representation for prosthetic control in the presence of a constant decoder. The importance of such a cortical map was evident in that small perturbations to either the size of the neural ensemble or to the decoder could reversibly disrupt function. Moreover, once a cortical map became consolidated, a second map could be learned and stored. Thus, long-term use of a neuroprosthetic device is associated with the formation of a cortical map for prosthetic function that is stable across time, readily recalled, resistant to interference, and resembles a putative memory engram.     

Multisynaptic Inputs from the Medial Temporal Lobe to V4 in Macaques

Retrograde transsynaptic transport of rabies virus was employed to undertake the top-down projections from the medial temporal lobe (MTL) to visual area V4 of the occipitotemporal visual pathway in Japanese monkeys (Macaca fuscata). On day 3 after rabies injections into V4, neuronal labeling was observed prominently in the temporal lobe areas that have direct connections with V4, including area TF of the parahippocampal cortex. Furthermore, conspicuous neuron labeling appeared disynaptically in area TH of the parahippocampal cortex, and areas 35 and 36 of the perirhinal cortex. The labeled neurons were located predominantly in deep layers. On day 4 after the rabies injections, labeled neurons were found in the hippocampal formation, along with massive labeling in the parahippocampal and perirhinal cortices. In the hippocampal formation, the densest neuron labeling was seen in layer 5 of the entorhinal cortex, and a small but certain number of neurons were labeled in other regions, such as the subicular complex and CA1 and CA3 of the hippocampus proper. The present results indicate that V4 receives major input from the hippocampus proper via the entorhinal cortex, as well as “short-cut” pathways that bypass the entorhinal cortex. These multisynaptic pathways may define an anatomical basis for hippocampal-cortical interactions involving lower visual areas. The multisynaptic input from the MTL to V4 is likely to provide mnemonic information about object recognition that is accomplished through the occipitotemporal pathway.     

Remembering visual motion: neural correlates of associative plasticity and motion recall in cortical area MT

The pictorial content of visual memories recalled by association is embodied by neuronal activity at the highest processing stages of primate visual cortex. This activity is elicited by top-down signals from the frontal lobe and recapitulates the bottom-up pattern normally obtained by the recalled stimulus. To explore the generality and mechanisms of this phenomenon, we recorded motion-sensitive neurons at an early stage of cortical processing. After monkeys learned to associate directions of motion with static shapes, these neurons exhibited unprecedented selectivity for the shapes. This emergent shape selectivity reflects activation of neurons representing the motion stimuli recalled by association, and it suggests that recall-related activity may be a general feature of neurons in visual cortex.     

The Limited Utility of Multiunit Data in Differentiating Neuronal Population Activity

To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or ‘multiunit activity’ (MUA) is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types. We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) in the mouse dorsal striatum. We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings), the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.     

An experimental approach to research on the integrative properties of a single brain neuron

The difficulties in investigation of the single neuron integrative properties in mammalian brain are connected with the absence of a mean of determination of neuronal set contribution in their activity. In given paper an experimental approach to the decision of this task is proposed. It consists in neuron activity investigation in the model learning training situation under condition of partial functional isolation from nervous cells by means of decrease in extracellular calcium concentration level using ethylene glycol tetraacetate. As indicator of such isolation was a partial or total reduction of responses in investigated neurons to electric microstimulation of neighbouring (200-240 mkm) parts of neocortex. The results of analysis of neuron responses in sensomotor cortex in the rat's brain in the process of acetylcholine repetitive local application give possibility to propose that some neurons don't exhibit plasticity according to the indicator in the dynamics of impulse discharge rate in responses to transmitter.     

Towards understanding of the cortical network underlying associative memory

Declarative knowledge and experiences are represented in the association cortex and are recalled by reactivation of the neural representation. Electrophysiological experiments have revealed that associations between semantically linked visual objects are formed in neural representations in the temporal and limbic cortices. Memory traces are created by the reorganization of neural circuits. These regions are reactivated during retrieval and contribute to the contents of a memory. Two different types of retrieval signals are suggested as follows: automatic and active. One flows backward from the medial temporal lobe during the automatic retrieval process, whereas the other is conveyed as a top-down signal from the prefrontal cortex to the temporal cortex during the active retrieval process. By sending the top-down signal, the prefrontal cortex manipulates and organizes to-be-remembered information, devises strategies for retrieval and monitors the outcome. To further understand the neural mechanism of memory, the following two complementary views are needed: how the multiple cortical areas in the brain-wide network interact to orchestrate cognitive functions and how the properties of single neurons and their synaptic connections with neighbouring neurons combine to form local circuits and to exhibit the function of each cortical area. We will discuss some new methodological innovations that tackle these challenges.     

Phase locking of single neuron activity to theta oscillations during working memory in monkey extrastriate visual cortex

Working memory has been linked to elevated single neuron discharge in monkeys and to oscillatory changes in the human EEG, but the relation between these effects has remained largely unexplored. We addressed this question by measuring local field potentials and single unit activity simultaneously from multiple electrodes placed in extrastriate visual cortex while monkeys were performing a working memory task. We describe a significant enhancement in theta band energy during the delay period. Theta oscillations had a systematic effect on single neuron activity, with neurons emitting more action potentials near their preferred angle of each theta cycle. Sample-selective delay activity was enhanced if only action potentials emitted near the preferred theta angle were considered. Our results suggest that extrastriate visual cortex is involved in short-term maintenance of information and that theta oscillations provide a mechanism for structuring the recurrent interaction between neurons in different brain regions that underlie working memory.     

Learning in trance: Functional brain imaging studies and neuropsychology

This study examined the fundamental question, whether verbal memory processing in hypnosis and in the waking state is mediated by a common neural system or by distinct cortical areas. Seven right-handed volunteers (25.4 years, sd 3.1) with high-hypnotic susceptibility scores were PET-scanned while encoding/retrieving word associations either in hypnosis or in the waking state. Word-pairs were visually presented and highly imaginable, but not semantically related (e.g. monkey-street). The presentation of pseudo-words served as a reference condition. An emission scan was recorded after each intravenous administration of O-15 water. Encoding under hypnosis was associated with more pronounced bilateral activations in the occipital cortex and the prefrontal areas as compared to learning in the waking state. During memory retrieval of word-pairs which had been previously learned under hypnosis, activations were found in the occipital lobe and the cerebellum. Under both experimental conditions precuneus and prefrontal cortex showed a consistent bilateral activation which was most distinct when the learning had taken place under hypnosis. In order to further analyze the effect of hypnosis on imagery-mediated learning, we administered sets of high-imagery word-pairs and sets of abstract words. In the first experimental condition word-pair associations were presented visually. In the second condition it was found that highly hypnotisable persons recalled significantly more high-imagery words under hypnosis as compared to low-hypnotisables both in the visual and auditory modality. Furthermore, high-imagery words were also better recalled by the highly hypnotisable subjects during the non-hypnotic condition. The memory effect was consistently present under both, immediate and delayed recall conditions. Taken together, the findings advance our understanding of the neural representation that underlies hypnosis and the neuropsychological correlates of hypnotic susceptibility.     

Selectivity of neuronal adaptation does not match response selectivity: a single-cell study of the FMRI adaptation paradigm

fMRI-based adaptation paradigms (fMR-A) have been used to infer neuronal stimulus selectivities in humans. Inferring neuronal selectivities from fMR-A, however, requires an understanding of the relationship between the stimulus selectivity of neuronal adaptation and responses. We studied this relationship by recording single cells in macaque inferior temporal (IT) cortex, an area that shows fMRI adaptation. Repetition of identical object images reduced the responsiveness of single IT neurons. Presentation of an image to which the neuron was unresponsive did not alter the response to a subsequent image that activated the neuron. Successive presentation of two different images to which the neuron responded similarly produced adaptation, but less so than the repeated presentation of an image. The neuronal adaptation at the single-cell level showed a greater degree of stimulus selectivity than the responses. This complicates the interpretation of fMR-A paradigms when inferring neuronal selectivity.     

Top-down control-signal dynamics in anterior cingulate and prefrontal cortex neurons following task switching

The prefrontal cortex (PFC) and anterior cingulate cortex (ACC) have both been implicated in cognitive control, but their relative roles remain unclear. Here we recorded the activity of single neurons in both areas while monkeys performed a task that required them to switch between trials in which they had to look toward a flashed stimulus (prosaccades) and trials in which they had to look away from the stimulus (antisaccades). We found that ACC neurons had a higher level of task selectivity than PFC neurons during the preparatory period on trials immediately following a task switch. In ACC neurons, task selectivity was strongest after the task switch and declined throughout the task block, whereas task selectivity remained constant in the PFC. These results demonstrate that the ACC is recruited when cognitive demands increase and suggest a role for both areas in task maintenance and the implementation of top-down control.     

Tracking calcium dynamics from individual neurons in behaving animals

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic monitoring of neuronal activity and their subsequent functional characterization. We report the development and open-source implementation of a multi-step cellular tracking algorithm (Elastic Motion Correction and Concatenation or EMC²) that compensates for the intermittent disappearance of moving neurons by integrating local deformation information from detectable neurons. We demonstrate the accuracy and versatility of our algorithm using calcium imaging data from two-photon volumetric microscopy in visual cortex of awake mice, and from confocal microscopy in behaving Hydra, which experiences major body deformation during its contractions. We quantify the performance of our algorithm using ground truth manual tracking of neurons, along with synthetic time-lapse sequences, covering a wide range of particle motions and detectability parameters. As a demonstration of the utility of the algorithm, we monitor for several days calcium activity of the same neurons in layer 2/3 of mouse visual cortex in vivo, finding significant turnover within the active neurons across days, with only few neurons that remained active across days. Also, combining automatic tracking of single neuron activity with statistical clustering, we characterize and map neuronal ensembles in behaving Hydra, finding three major non-overlapping ensembles of neurons (CB, RP1 and RP2) whose activity correlates with contractions and elongations. Our results show that the EMC² algorithm can be used as a robust and versatile platform for neuronal tracking in behaving animals.     

Nitric Oxide Regulates Neuronal Activity via Calcium-Activated Potassium Channels

Nitric oxide (NO) is an unconventional membrane-permeable messenger molecule that has been shown to play various roles in the nervous system. How NO modulates ion channels to affect neuronal functions is not well understood. In gastropods, NO has been implicated in regulating the feeding motor program. The buccal motoneuron, B19, of the freshwater pond snail Helisoma trivolvis is active during the hyper-retraction phase of the feeding motor program and is located in the vicinity of NO-producing neurons in the buccal ganglion. Here, we asked whether B19 neurons might serve as direct targets of NO signaling. Previous work established NO as a key regulator of growth cone motility and neuronal excitability in another buccal neuron involved in feeding, the B5 neuron. This raised the question whether NO might modulate the electrical activity and neuronal excitability of B19 neurons as well, and if so whether NO acted on the same or a different set of ion channels in both neurons. To study specific responses of NO on B19 neurons and to eliminate indirect effects contributed by other cells, the majority of experiments were performed on single cultured B19 neurons. Addition of NO donors caused a prolonged depolarization of the membrane potential and an increase in neuronal excitability. The effects of NO could mainly be attributed to the inhibition of two types of calcium-activated potassium channels, apamin-sensitive and iberiotoxin-sensitive potassium channels. NO was found to also cause a depolarization in B19 neurons in situ, but only after NO synthase activity in buccal ganglia had been blocked. The results suggest that NO acts as a critical modulator of neuronal excitability in B19 neurons, and that calcium-activated potassium channels may serve as a common target of NO in neurons.     

Neuronal dynamics under periodic stimuli

The convergence characteristics of a single dissipative Hopfield-type neuron with self-interaction under periodic external stimuli are considered. Sufficient conditions are established for associative encoding and recall of the periodic patterns associated with the external stimuli. Both continuous-time-continuous-state and discrete-time-continuous-state models are discussed. It is shown that when the neuronal gain is dominated by the neuronal dissipation on average, associative recall of the encoded temporal pattern is guaranteed and this is achieved by the global asymptotic stability of the encoded pattern.     

Prefrontal cortex function, quasi-physiological stimuli, and synaptic plasticity

The prelimbic area of rat medial frontal cortex may be functionally analogous to human/primate dorsolateral prefrontal cortex. This area may be involved in selective attention to the external stimuli and the coupling of the attention to a repertory of actions. It was suggested that this function may rely on a form of long-term memory [Biol. Rev. 77 (2002) 563]. Indeed, during learning of this type of behavior, a portion of prelimbic neurons persistently change their firing characteristics [Prog. Brain Res. 126 (2000) 287]. It is therefore important to study long-term potentiation (LTP) and depression (LTD) in rat prelimbic neurons. In this article, the author first briefly reviews recent findings on the prefrontal cortex function and discusses that the prefrontal cortex may be involved in long-term memory. Second, the author will show some new results which indicate that quasi-physiological patterns of stimuli mimicking prelimbic neuronal activity during behavior can induce LTP in prelimbic pyramidal neuron synapses. These results suggest that prelimbic neuronal activity during behavior may lastingly modify prelimbic synaptic efficacy.     

The neural basis of episodic memory: evidence from functional neuroimaging

We review some of our recent research using functional neuroimaging to investigate neural activity supporting the encoding and retrieval of episodic memories, that is, memories for unique events. Findings from studies of encoding indicate that, at the cortical level, the regions responsible for the effective encoding of a stimulus event as an episodic memory include some of the regions that are also engaged to process the event 'online'. Thus, it appears that there is no single cortical site or circuit responsible for episodic encoding. The results of retrieval studies indicate that successful recollection of episodic information is associated with activation of lateral parietal cortex, along with more variable patterns of activity in dorsolateral and anterior prefrontal cortex. Whereas parietal regions may play a part in the representation of retrieved information, prefrontal areas appear to support processes that act on the products of retrieval to align behaviour with the demands of the retrieval task.     

A single spiking neuron that can represent interval timing: analysis,plasticity and multi-stability

The ability to represent interval timing is crucial for many common behaviors, such as knowing whether to stop when the light turns from green to yellow. Neural representations of interval timing have been reported in the rat primary visual cortex and we have previously presented a computational framework describing how they can be learned by a network of neurons. Recent experimental and theoretical results in entorhinal cortex have shown that single neurons can exhibit persistent activity, previously thought to be generated by a network of neurons. Motivated by these single neuron results, we propose a single spiking neuron model that can learn to compute and represent interval timing. We show that a simple model, reduced analytically to a single dynamical equation, captures the average behavior of the complete high dimensional spiking model very well. Variants of this model can be used to produce bi-stable or multi-stable persistent activity. We also propose a plasticity rule by which this model can learn to represent different intervals and different levels of persistent activity.     

Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks

During rest, the mammalian cortex displays spontaneous neural activity. Spiking of single neurons during rest has been described as irregular and asynchronous. In contrast, recent in vivo and in vitro population measures of spontaneous activity, using the LFP, EEG, MEG or fMRI suggest that the default state of the cortex is critical, manifested by spontaneous, scale-invariant, cascades of activity known as neuronal avalanches. Criticality keeps a network poised for optimal information processing, but this view seems to be difficult to reconcile with apparently irregular single neuron spiking. Here, we simulate a 10,000 neuron, deterministic, plastic network of spiking neurons. We show that a combination of short- and long-term synaptic plasticity enables these networks to exhibit criticality in the face of intrinsic, i.e. self-sustained, asynchronous spiking. Brief external perturbations lead to adaptive, long-term modification of intrinsic network connectivity through long-term excitatory plasticity, whereas long-term inhibitory plasticity enables rapid self-tuning of the network back to a critical state. The critical state is characterized by a branching parameter oscillating around unity, a critical exponent close to -3/2 and a long tail distribution of a self-similarity parameter between 0.5 and 1.