Donor/recipient enhancement of memory in rat hippocampus

Brain-to-brain interface technology: A brief history, current state, and future goals

A brain-to-brain interface (BBI), defined as a combination of neuroimaging and neurostimulation methods to extract and deliver information between brains directly without the need for the peripheral nervous system, is a budding communication technique. A BBI system is made up of two parts known as the brain-computer interface part, which reads a sender's brain activity and digitalizes it, and the computer-brain interface part, which writes the delivered brain activity to a receiving brain. As with other technologies, BBI systems have gone through an evolutionary process since they first appeared. The BBI systems have been employed for numerous purposes, including rehabilitation for post-stroke patients, communicating with patients suffering from amyotrophic lateral sclerosis, locked-in syndrome and speech problems following stroke. Also, it has been proposed that a BBI system could play an important role on future battlefields. This technology was not only employed for communicating between two human brains but also for making a direct communication path among different species through which motor or sensory commands could be sent and received. However, the application of BBI systems has provoked significant challenges to human rights principles due to their ability to access and manipulate human brain information. In this study, we aimed to review the brain-computer interface and computer-brain interface technologies as components of BBI systems, the development of BBI systems, applications of this technology, arising ethical issues and expectations for future use.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall of stimulus features and categories

Objective

Here, we demonstrate the first successful use of static neural stimulation patterns for specific information content. These static patterns were derived by a model that was applied to a subject's own hippocampal spatiotemporal neural codes for memory.

Approach

We constructed a new model of processes by which the hippocampus encodes specific memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of targeted content into short-term memory. A memory decoding model (MDM) of hippocampal CA3 and CA1 neural firing was computed which derives a stimulation pattern for CA1 and CA3 neurons to be applied during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task.

Main results

MDM electrical stimulation delivered to the CA1 and CA3 locations in the hippocampus during the sample phase of DMS trials facilitated memory of images from the DMS task during a delayed recognition (DR) task that also included control images that were not from the DMS task. Across all subjects, the stimulated trials exhibited significant changes in performance in 22.4% of patient and category combinations. Changes in performance were a combination of both increased memory performance and decreased memory performance, with increases in performance occurring at almost 2 to 1 relative to decreases in performance. Across patients with impaired memory that received bilateral stimulation, significant changes in over 37.9% of patient and category combinations was seen with the changes in memory performance show a ratio of increased to decreased performance of over 4 to 1. Modification of memory performance was dependent on whether memory function was intact or impaired, and if stimulation was applied bilaterally or unilaterally, with nearly all increase in performance seen in subjects with impaired memory receiving bilateral stimulation.

Significance

These results demonstrate that memory encoding in patients with impaired memory function can be facilitated for specific memory content, which offers a stimulation method for a future implantable neural prosthetic to improve human memory.

Brain to Brain Interfaces (BBIs) in future military operations; blurring the boundaries of individual responsibility

Developments in neurotechnology took a leap forward with the demonstration of the first Brain to Brain Interface (BBI). BBIs enable direct communication between two brains via a Brain Computer Interface (BCI) and bypasses the peripheral nervous system. This discovery promises new possibilities for future battlefield technology. As battlefield technology evolves, it is more likely to place greater demands on future soldiers. Future soldiers are more likely to process large amounts of data derived from an extensive networks of humans and machines. This raises several ethical and philosophical concerns. This paper will look at BBI technology in current stages of research, future BBI applications in the military and how the potential use of BBIs in military operations challenges the way we understand the concept of responsibility. In this paper, I propose that an individual connected to a BBI ought not to be held fully responsible for her actions. The justification for this proposition is based on three key points such as an individual connected to a BBI does not have the ability to act freely, has a diminished sense of self-agency and may not be able to demonstrate authenticity of the thoughts and memories generated when connected to the interface.

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.

The future of neuromodulation: smart neuromodulation

Introduction: The International Neuromodulation Society defines neuromodulation as the alteration of nerve activity through targeted delivery of a stimulus, such as electrical stimulation or chemical agents, to specific neurological sites in the body.Areas covered: In the near future (<5 years) increasingly complex implantable neuromodulation systems will enter the market. These devices are capable of closed-loop stimulation and the delivery of novel stimulation designs, pushing the need for upgradability. But what about the near-to-far future, meaning 5-10 years from now?Expert opinion: We propose that neuromodulation in the near to far future (5-10 years) will involve integration of adaptive network neuromodulation with predictive artificial intelligence, automatically adjusted by brain and external sensors, and controlled via cloud-based applications. The components will be introduced in a phased approach, culminating in a fully autonomous brain-stimulator-cloud interface. This may, in the long future (>10 years), lead to the brain of the future, a brain with integrated artificial intelligence.

How experimental neuroscientists can fix the hard problem of consciousness

For the materialist, the hard problem is fundamentally an explanatory problem. Solving it requires explaining why the relationship between brain and experience is the way it is and not some other way. We use the tools of the interventionist theory of explanation to show how a systematic experimental project could help move beyond the hard problem. Key to this project is the development of second-order interventions and invariant generalizations. Such interventions played a crucial scientific role in untangling other scientific mysteries, and we suggest that the same will be true of consciousness. We further suggest that the capacity for safe and reliable self-intervention will play a key role in overcoming both the hard and meta-problems of consciousness. Finally, we evaluate current strategies for intervention, with an eye to how they might be improved.

Longitudinal Differences in Human Hippocampal Connectivity During Episodic Memory Processing

The question of longitudinal hippocampal functional specialization is critical to human episodic memory because an accurate understanding of this phenomenon would impact theories of mnemonic function and entail practical consequences for the clinical management of patients undergoing temporal lobe surgery. The implementation of the robotically assisted stereo electroencephalography technique for seizure mapping has provided our group with the opportunity to obtain recordings simultaneously from the anterior and posterior human hippocampus, allowing us to create an unparalleled data set of human subjects with simultaneous anterior and posterior hippocampal recordings along with several cortical regions. Using these data, we address several key questions governing functional hippocampal connectivity in human memory. First, we ask whether functional networks during episodic memory encoding and retrieval are significantly different for the anterior versus posterior hippocampus (PH). We also examine how connections differ across the 2-5 Hz versus 4-9 Hz theta frequency ranges, directly addressing the relative contribution of each of these separate bands in hippocampal-cortical interactions. While we report some overlapping connections, we observe evidence of distinct anterior versus posterior hippocampal networks during memory encoding related to frontal and parietal connectivity as well as hemispheric differences in aggregate connectivity. We frame these findings in light of the proposed AT/PM memory systems. We also observe distinct encoding versus retrieval connectivity patterns between anterior and posterior hippocampal networks, we find that overall connectivity is greater for the PH in the right hemisphere, and further that these networks significantly differ in terms of frontal and parietal connectivity. We place these findings in the context of existing theoretical treatments of human memory systems, especially the proposed AT/PM system. During memory retrieval, we observe significant differences between slow-theta (2-5 Hz) and fast-theta (4-9 Hz) connectivity between the cortex and hippocampus. Finally, we test how these distinct theta frequency oscillations propagate within the hippocampus, using phase slope index to estimate the direction slow-theta and fast-theta oscillations travel during encoding and retrieval. We uncover evidence that 2-5 Hz oscillations travel in the posterior-to-anterior direction, while 5-9 Hz oscillations travel from anterior-to-posterior. Taken together, our findings describe mnemonically relevant functional connectivity differences along the longitudinal axis of the human hippocampus that will inform interpretation of models of hippocampal function that seek to integrate rodent and human data.

An optical brain-to-brain interface supports rapid information transmission for precise locomotion control

Brain-to-brain interfaces (BtBIs) hold exciting potentials for direct communication between individual brains. However, technical challenges often limit their performance in rapid information transfer. Here, we demonstrate an optical brain-to-brain interface that transmits information regarding locomotor speed from one mouse to another and allows precise, real-time control of locomotion across animals with high information transfer rate. We found that the activity of the genetically identified neuromedin B (NMB) neurons within the nucleus incertus (NI) precisely predicts and critically controls locomotor speed. By optically recording Ca²⁺ signals from the NI of a "Master" mouse and converting them to patterned optogenetic stimulations of the NI of an "Avatar" mouse, the BtBI directed the Avatar mice to closely mimic the locomotion of their Masters with information transfer rate about two orders of magnitude higher than previous BtBIs. These results thus provide proof-of-concept that optical BtBIs can rapidly transmit neural information and control dynamic behaviors across individuals.

Delaying memory decline: different options and emerging solutions

Memory decline can be a devastating disease and increases in aging Western populations. Memory enhancement technologies hold promise for this and other conditions. Approaches include stem cell transplantation, which improved memory in several animal studies as well as vaccination against Alzheimer´s disease (AD) by β-amyloid antibodies. For a positive clinical effect, the vaccine should probably be administered over a long period of time and before amyloid pathologies manifest in the brain. Different drugs, such as erythropoietin or antiplatelet therapy, improve memory in neuropsychiatric diseases or AD or at least in animal studies. Omega-3 polyunsaturated fatty acid-rich diets improve memory through the gut-brain axis by altering the gut flora through probiotics. Sports, dancing, and memory techniques (e.g., Method of Loci) utilize behavioral approaches for memory enhancement, and were effective in several studies. Augmented reality (AR) is an auspicious way for enhancing memory in real time. Future approaches may include memory prosthesis for head-injured patients and light therapy for restoring memory in AD. Memory enhancement in humans in health and disease holds big promises for the future. Memory training helps only in mild or no impairment. Clinical application requires further investigation.

Brain-Machine Interface-Based Rat-Robot Behavior Control

Brain-machine interface (BMI) provides a bidirectional pathway between the brain and external facilities. The machine-to-brain pathway makes it possible to send artificial information back into the biological brain, interfering neural activities and generating sensations. The idea of the BMI-assisted bio-robotic animal system is accomplished by stimulations on specific sites of the nervous system. With the technology of BMI, animals' locomotion behavior can be precisely controlled as robots, which made the animal turning into bio-robot. In this chapter, we reviewed our lab works focused on rat-robot navigation. The principles of rat-robot system have been briefly described first, including the target brain sites chosen for locomotion control and the design of remote control system. Some methodological advances made by optogenetic technologies for better modulation control have then been introduced. Besides, we also introduced our implementation of "mind-controlled" rat navigation system. Moreover, we have presented our efforts made on combining biological intelligence with artificial intelligence, with developments of automatic control and training system assisted with images or voices inputs. We concluded this chapter by discussing further developments to acquire environmental information as well as promising applications with write-in BMIs.

Neurotechnologies for Human Cognitive Augmentation: Current State of the Art and Future Prospects

Recent advances in neuroscience have paved the way to innovative applications that cognitively augment and enhance humans in a variety of contexts. This paper aims at providing a snapshot of the current state of the art and a motivated forecast of the most likely developments in the next two decades. Firstly, we survey the main neuroscience technologies for both observing and influencing brain activity, which are necessary ingredients for human cognitive augmentation. We also compare and contrast such technologies, as their individual characteristics (e.g., spatio-temporal resolution, invasiveness, portability, energy requirements, and cost) influence their current and future role in human cognitive augmentation. Secondly, we chart the state of the art on neurotechnologies for human cognitive augmentation, keeping an eye both on the applications that already exist and those that are emerging or are likely to emerge in the next two decades. Particularly, we consider applications in the areas of communication, cognitive enhancement, memory, attention monitoring/enhancement, situation awareness and complex problem solving, and we look at what fraction of the population might benefit from such technologies and at the demands they impose in terms of user training. Thirdly, we briefly review the ethical issues associated with current neuroscience technologies. These are important because they may differentially influence both present and future research on (and adoption of) neurotechnologies for human cognitive augmentation: an inferior technology with no significant ethical issues may thrive while a superior technology causing widespread ethical concerns may end up being outlawed. Finally, based on the lessons learned in our analysis, using past trends and considering other related forecasts, we attempt to forecast the most likely future developments of neuroscience technology for human cognitive augmentation and provide informed recommendations for promising future research and exploitation avenues.

How the Hippocampus Represents Memories: Making Sense of Memory Allocation Studies

In recent years there has been a wealth of studies investigating how memories are allocated in the hippocampus. Some of those studies showed that it is possible to manipulate the identity of neurons recruited to represent a given memory without affecting the memory's behavioral expression. Those findings raised questions about how the hippocampus represents memories, with some researchers arguing that hippocampal neurons do not represent fixed stimuli. Herein, an alternative hypothesis is argued. Neurons in high-order brain regions can be tuned to multiple dimensions, forming complex, abstract representations. It is argued that such complex receptive fields allow those neurons to show some flexibility in their responses while still representing relatively fixed sets of stimuli. Moreover, it is pointed out that changes induced by artificial manipulation of cell assemblies are not completely redundant-the observed behavioral redundancy does not imply cognitive redundancy, as different, but similar, memories may induce the same behavior.

Plasticity and redundancy in the integration of adult born neurons in the hippocampus

Hippocampal neurogenesis (HN) is an extreme form of plasticity that inevitably rewires the hippocampal circuit and this rewiring was put forward as a possible mechanism for neurogenesis' behavioral effects. Here, I critically evaluate multiple lines of evidence to argue that structural plasticity induced by HN is, to a large extent, functionally redundant and thus has limited impact on behavior. The associative plasticity rules along with properties of immature neurons should only allow the survival of new neurons whose pre and postsynaptic partners have correlated activity, leading to functional redundancy. Moreover, non-redundant rewiring, even with its computational benefits, would impair meaningful communication between the hippocampus and other brain regions. This implies that associative plasticity rules constrain structural plasticity induced by neurogenesis, allowing the brain to balance plasticity and stability to maintain proper functioning. It also implies that behavioral effects of HN are mediated by other mechanisms apart from circuit rewiring.

Neurobionics and the brain-computer interface: current applications and future horizons

The brain-computer interface (BCI) is an exciting advance in neuroscience and engineering. In a motor BCI, electrical recordings from the motor cortex of paralysed humans are decoded by a computer and used to drive robotic arms or to restore movement in a paralysed hand by stimulating the muscles in the forearm. Simultaneously integrating a BCI with the sensory cortex will further enhance dexterity and fine control. BCIs are also being developed to: provide ambulation for paraplegic patients through controlling robotic exoskeletons; restore vision in people with acquired blindness; detect and control epileptic seizures; and improve control of movement disorders and memory enhancement. High-fidelity connectivity with small groups of neurons requires microelectrode placement in the cerebral cortex. Electrodes placed on the cortical surface are less invasive but produce inferior fidelity. Scalp surface recording using electroencephalography is much less precise. BCI technology is still in an early phase of development and awaits further technical improvements and larger multicentre clinical trials before wider clinical application and impact on the care of people with disabilities. There are also many ethical challenges to explore as this technology evolves.

The Hypothesis of Connecting Two Spinal Cords as a Way of Sharing Information between Two Brains and Nervous Systems

Direct communication between different nervous systems has been recently reported through Brain-to-Brain-Interfaces and brainet. Closed loops systems between the brain and the spinal cord from the same individual have also been demonstrated. However, the connection between different nervous systems through the spinal cord has not yet been considered. This paper raises the hypothesis that connecting two spinal cords (spinal cord - spinal cord connection) is an indirect mean for communication of two brains and a direct way of communication between two nervous systems. A concept of electrical fingerprint of a drug is introduced. The notion of connection between two parts of the same spinal cord to treat a paraplegic patient is also introduced. Possible applications of this technique are discussed in the context of psychology, psychiatry and mental health. Also, it is discussed that external information injected to a spinal cord as well as spinal cord - spinal cord connection can become new tools to (1) study the physiology of the nervous system, (2) model specific behaviors, (3) study and model disease traits (4) treat neuropsychiatric disorders and (5) share information between two nervous systems.

Neural Substrate Expansion for the Restoration of Brain Function

Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays) to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks.

An Instructor's Guide to (Some of) the Most Amazing Papers in Neuroscience

Although textbooks are still assigned in many undergraduate science courses, it is now not uncommon, even in some of the earliest courses in the curriculum, to supplement texts with primary source readings from the scientific literature. Not only does reading these articles help students develop an understanding of specific course content, it also helps foster an ability to engage with the discipline the way its practitioners do. One challenge with this approach, however, is that it can be difficult for instructors to select appropriate readings on topics outside of their areas of expertise as would be required in a survey course, for example. Here we present a subset of the papers that were offered in response to a request for the "most amazing papers in neuroscience" that appeared on the listserv of the Faculty for Undergraduate Neuroscience (FUN). Each contributor was subsequently asked to describe briefly the content of their recommended papers, their pedagogical value, and the audiences for which these papers are best suited. Our goal is to provide readers with sufficient information to decide whether such articles might be useful in their own classes. It is not our intention that any article within this collection will provide the final word on an area of investigation, nor that this collection will provide the final word for the discipline as a whole. Rather, this article is a collection of papers that have proven themselves valuable in the hands of these particular educators. Indeed, it is our hope that this collection represents the inaugural offering of what will become a regular feature in this journal, so that we can continue to benefit from the diverse expertise of the FUN community.

Computing Arm Movements with a Monkey Brainet

Traditionally, brain-machine interfaces (BMIs) extract motor commands from a single brain to control the movements of artificial devices. Here, we introduce a Brainet that utilizes very-large-scale brain activity (VLSBA) from two (B2) or three (B3) nonhuman primates to engage in a common motor behaviour. A B2 generated 2D movements of an avatar arm where each monkey contributed equally to X and Y coordinates; or one monkey fully controlled the X-coordinate and the other controlled the Y-coordinate. A B3 produced arm movements in 3D space, while each monkey generated movements in 2D subspaces (X-Y, Y-Z, or X-Z). With long-term training we observed increased coordination of behavior, increased correlations in neuronal activity between different brains, and modifications to neuronal representation of the motor plan. Overall, performance of the Brainet improved owing to collective monkey behaviour. These results suggest that primate brains can be integrated into a Brainet, which self-adapts to achieve a common motor goal.

Building an organic computing device with multiple interconnected brains

Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers.

Prefrontal cortical recordings with biomorphic MEAs reveal complex columnar-laminar microcircuits for BCI/BMI implementation

The mammalian prefrontal cortex known as the seat of high brain functions uses a six layer distribution of minicolumnar neurons to coordinate the integration of sensory information and the selection of relevant signals for goal driven behavior. To reveal the complex functionality of these columnar microcircuits we employed simultaneous recordings with several configurations of biomorphic microelectrode arrays (MEAs) within cortical layers in adjacent minicolumns, in four nohuman primates (NHPs) performing a delayed match-to-sample (DMS) visual discrimination task. We examined: (1) the functionality of inter-laminar, and inter-columnar interactions between pairs of cells in the same or different minicolumns by use of normalized cross-correlation histograms (CCH), (2) the modulation of glutamate concentration in layer 2/3, and (3) the potential interactions within these microcircuits. The results demonstrate that neurons in both infra-granular and supra-granular layers interact through inter-laminar loops, as well as through intra-laminar to produce behavioral response signals. These results provide new insights into the manner in which prefrontal cortical microcircuitry integrates sensory stimuli used to provide behaviorally relevant signals that may be implemented in brain computer/machine interfaces (BCI/BMIs) during performance of the task.

"Knock once for yes, twice for no"

Previous studies have indicated that the expression of CCN3, a member of the CCN family of proteins, was tightly regulated during central nervous development and was associated with acquisition of cognitive functions in rats (Perbal, Mol Pathol 54(2):57-79, 2001; Su et al. Sheng Li Xue Bao 52(4):290-294, 2000) therefore suggesting that CCN3 might be involved in higher levels of physiological communication in the brain. In spite of the considerable amount of progress made into the understanding of neuronal organization and communication, reducing the knowledge gap between brain cellular biology and behavioral studies remains a huge challenge. Mind-to-mind communication has been the subject of numerous science fiction writings, intense research and emotional debates for many years. Scientists have tried for a long time to achieve transmission of messages between living subjects via non intrusive protocols. Thanks to the great progress made in imagery and neurosciences, another dimension of neuronal function in communication has now been documented. Two recent experimental demonstrations of direct brain to brain communication without physical contact (Grau et al. (2014) Conscious brain-to-brain communication in humans using non-invasive technologies. PLoS One. Aug 19;9(8)- - Rao et al. (2014) A direct brain-to-brain interface in humans. PLoS One. Nov 5;9(11)) pave the road to more sophisticated applications that could profoundly affect communications of humans with other humans, animals and machines. Although the wide use of such applications might seem a long way off, they raise quite a number of ethical, legal and societal issues.

What will this do to me and my brain? Ethical issues in brain-to-brain interfacing

Recent brain-to-brain interfacing studies provide proof of principle for the feasibility of various forms of direct information transfer between two brains, and may lead to the development of new approaches involving memory, emotions, or senses. What makes brain-to-brain interfaces unique is the transfer of information representing specific messages directly from one brain to another, without involving any activity of the peripheral nervous system or senses. The article discusses ethical issues that arise in neural interfacing. The focus is on the implications that brain-to-brain interfaces may have on the individual at the recipient side.

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.

Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling

This paper presents a systems identification approach for studying the long-term synaptic plasticity using natural spiking activities. This approach consists of three modeling steps. First, a multi-input, single-output (MISO), nonlinear dynamical spiking neuron model is formulated to estimate and represent the synaptic strength in means of functional connectivity between input and output neurons. Second, this MISO model is extended to a nonstationary form to track the time-varying properties of the synaptic strength. Finally, a Volterra modeling method is used to extract the synaptic learning rule, e.g., spike-timing-dependent plasticity, for the explanation of the input-output nonstationarity as the consequence of the past input-output spiking patterns. This framework is developed to study the underlying mechanisms of learning and memory formation in behaving animals, and may serve as the computational basis for building the next-generation adaptive cortical prostheses.

Modifying cognition and behavior with electrical microstimulation: implications for cognitive prostheses

A fundamental goal of cognitive neuroscience is to understand how brain activity generates complex mental states and behaviors. While neuronal activity may predict or correlate with behavioral responses in a cognitive task, the use of electrical microstimulation presents the possibility to augment such correlational findings with direct evidence for causal relationships. Although microstimulation has been used for many years as a tool for mapping sensory and motor function, its role in learning, memory and decision-making has emerged only recently. Focal microstimulation of higher cortical areas can produce complex mental states and sequences of action. However, the relationship between the locus of stimulation and the percepts or actions evoked is often stereotyped and inflexible. The challenge is to develop stimulation systems that do not have fixed output but can flexibly contribute to complex cognitive and behavioral tasks. We discuss how microstimulation has been instrumental in manipulating a wide spectrum of cognitive functions including working memory, perceptual decisions and executive control by enhancing attention, re-ordering temporal sequence of saccades, improving associative learning or cognitive performance. For example, stimulation in prefrontal, parietal and sensory cortices may establish causal effects on decision-making, while microstimulation of inferotemporal cortex or caudate nucleus enhances associative learning. Building cognitive prosthetics based on the insights gleaned from such studies may depend on the development of multiple-input, multiple-output (MIMO) devices that allow subjects to control stimulation with their own thoughts in a closed-loop system.

Conscious brain-to-brain communication in humans using non-invasive technologies

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

Multifractal analysis of information processing in hippocampal neural ensembles during working memory under Δ⁹-tetrahydrocannabinol administration

BACKGROUND

Multifractal analysis quantifies the time-scale-invariant properties in data by describing the structure of variability over time. By applying this analysis to hippocampal interspike interval sequences recorded during performance of a working memory task, a measure of long-range temporal correlations and multifractal dynamics can reveal single neuron correlates of information processing.

NEW METHOD

Wavelet leaders-based multifractal analysis (WLMA) was applied to hippocampal interspike intervals recorded during a working memory task. WLMA can be used to identify neurons likely to exhibit information processing relevant to operation of brain-computer interfaces and nonlinear neuronal models.

RESULTS

Neurons involved in memory processing ("Functional Cell Types" or FCTs) showed a greater degree of multifractal firing properties than neurons without task-relevant firing characteristics. In addition, previously unidentified FCTs were revealed because multifractal analysis suggested further functional classification. The cannabinoid type-1 receptor (CB1R) partial agonist, tetrahydrocannabinol (THC), selectively reduced multifractal dynamics in FCT neurons compared to non-FCT neurons.

COMPARISON WITH EXISTING METHODS

WLMA is an objective tool for quantifying the memory-correlated complexity represented by FCTs that reveals additional information compared to classification of FCTs using traditional z-scores to identify neuronal correlates of behavioral events.

CONCLUSION

z-Score-based FCT classification provides limited information about the dynamical range of neuronal activity characterized by WLMA. Increased complexity, as measured with multifractal analysis, may be a marker of functional involvement in memory processing. The level of multifractal attributes can be used to differentially emphasize neural signals to improve computational models and algorithms underlying brain-computer interfaces.

What do temporal lobe epilepsy and progressive mild cognitive impairment have in common?

Temporal lobe epilepsy (TLE) and mild cognitive impairment (MCI) are both subject to intensive memory research. Memory problems are a core characteristic of both conditions and we wonder if there are analogies which would enrich the two distinct research communities. In this review we focus on memory decline in both conditions, that is, the most feared psychosocial effect. While it is clear that memory decline in MCI is highly likely and would lead to the more severe diagnosis of Alzheimer's disease, it is a debate if TLE is a dementing disease or not. As such, like for MCI, one can differentiate progressive from stable TLE subtypes, mainly depending on the age of onset. Neuroimaging techniques such as volumetric analysis of the hippocampus, entorhinal, and perirhinal cortex show evidence of pathological changes in TLE and are predictive for memory decline in MCI. Several studies emphasize that it is necessary to extend the region of interest—even whole-brain characteristics can be predictive for conversion from MCI to Alzheimer's disease. Electroencephalography is increasingly subject to computational neuroscience, revealing new approaches for analyzing frequency, spatial synchronization, and information content of the signals. These methods together with event-related designs that assess memory functions are highly promising for understanding the mechanisms of memory decline in both TLE and MCI populations. Finally, there is evidence that the potential of such markers for memory decline is far from being exhausted. Similar structural and neurophysiological characteristics are linked to memory decline in TLE and MCI. We raise the hope that interdisciplinary research and cross-talk between fields such as research on epilepsy and dementia, will shed further light on the dementing characteristics of the pathological basis of MCI and TLE and support the development of new memory enhancing treatment strategies.