Neurons with stereotyped and rapid responses provide a reference frame for relative temporal coding in primate auditory cortex

The precise timing of spikes of cortical neurons relative to stimulus onset carries substantial sensory information. To access this information the sensory systems would need to maintain an internal temporal reference that reflects the precise stimulus timing. Whether and how sensory systems implement such reference frames to decode time-dependent responses, however, remains debated. Studying the encoding of naturalistic sounds in primate (Macaca mulatta) auditory cortex we here investigate potential intrinsic references for decoding temporally precise information. Within the population of recorded neurons, we found one subset responding with stereotyped fast latencies that varied little across trials or stimuli, while the remaining neurons had stimulus-modulated responses with longer and variable latencies. Computational analysis demonstrated that the neurons with stereotyped short latencies constitute an effective temporal reference for relative coding. Using the response onset of a simultaneously recorded stereotyped neuron allowed decoding most of the stimulus information carried by onset latencies and the full spike train of stimulus-modulated neurons. Computational modeling showed that few tens of such stereotyped reference neurons suffice to recover nearly all information that would be available when decoding the same responses relative to the actual stimulus onset. These findings reveal an explicit neural signature of an intrinsic reference for decoding temporal response patterns in the auditory cortex of alert animals. Furthermore, they highlight a role for apparently unselective neurons as an early saliency signal that provides a temporal reference for extracting stimulus information from other neurons

A role of the claustrum in auditory scene analysis by reflecting sensory change

The biological function of the claustrum remains speculative, despite many years of research. On the basis of its widespread connections it is often hypothesized that the claustrum may have an integrative function mainly reflecting objects rather than the details of sensory stimuli. Given the absence of a clear demonstration of any sensory integration in claustral neurons, however, we propose an alternative, data-driven, hypothesis: namely that the claustrum detects the occurrence of novel or salient sensory events. The detection of new events is critical for behavior and survival, as suddenly appearing objects may require rapid and coordinated reactions. Sounds are of particular relevance in this regard, and our conclusions are based on the analysis of neurons in the auditory zone of the primate claustrum. Specifically, we studied the responses to natural sounds, their preference to various sound categories, and to changes in the auditory scene. In a test for sound-category preference claustral neurons responded to but displayed a clear lack of selectivity between monkey vocalizations, other animal vocalizations or environmental sounds (Esnd). Claustral neurons were however able to detect target sounds embedded in a noisy background and their responses scaled with target signal to noise ratio (SNR). The single trial responses of individual neurons suggest that these neurons detected and reflected the occurrence of a change in the auditory scene. Given its widespread connectivity with sensory, motor and limbic structures the claustrum could play the essential role of identifying the occurrence of important sensory changes and notifying other brain areas—hence contributing to sensory awareness

View-Based Models of 3D Object Recognition and Class-Specific Invariances

This paper describes the main features of a view-based model of object recognition. The model tries to capture general properties to be expected in a biological architecture for object recognition. The basic module is a regularization network in which each of the hidden units is broadly tuned to a specific view of the object to be recognized

The Microvascular System of the Striate and Extrastriate Visual Cortex of the Macaque

In functional neuroimaging, neurovascular coupling is used to generate maps of hemodynamic changes that are assumed to be surrogates of regional neural activation. The aim of this study was to characterize the microvascular system of the primate cortex as a basis for understanding the constraints imposed on a region's hemodynamic response by the vascular architecture, density, as well as area- and layer-specific variations. In the macaque visual cortex, an array of anatomical techniques has been applied, including corrosion casts, immunohistochemistry, and cytochrome oxidase (COX) staining. Detailed measurements of regional vascular length density, volume fraction, and surface density revealed a similar vascularization in different visual areas. Whereas the lower cortical layers showed a positive correlation between the vascular and cell density, this relationship was very weak in the upper layers. Synapse density values taken from the literature also displayed a very moderate correlation with the vascular density. However, the vascular density was strongly correlated with the steady-state metabolic demand as measured by COX activity. This observation suggests that although the number of neurons and synapses determines an upper bound on an area's integrative capacity, its vascularization reflects the neural activity of those subpopulations that represent a "default” mode of brain steady stat

Sharp wave-ripple complexes in a reduced model of the hippocampal CA3-CA1 network of the macaque monkey

Sharp wave-ripple complexes observed in the hippocampal CA1 local field potential (LFP) are thought to play a major role in memory reactivation, transfer and consolidation. SPW-Rs are known to result from a complex interplay between local and upstream hippocampal ensembles. However, the key mechanisms that underlie these events remain partly unknown. In this work, we introduce a reduced, but realistic multi-compartmental model of the macaque monkey´s hippocampal CA3-CA1 network. The model consists of two semi-linear layers, each consisting of two-compartmental pyramidal neurons and one-compartmental perisomatic-targeting basket cells. Connections in the network were modeled as AMPA synapses, based on physiological and anatomical data. Notably, while auto-association fibers were prevalent in CA3, CA1 connectivity -inspired by recent findings- implemented a "feedback and reciprocal inhibition", dominated by recurrent inhibition and pyramidal cells-interneurons synapses. SPW-R episodes emerge spontaneously in the CA1 subfield LFP (which is assumed proportional to transmembrane currents across all compartments and medium resistivity): Episodes of short-lived high-frequency oscillations (ripples, 80-180 Hz) on top of a massive dendritic depolarization (< 20 Hz) with visual and quantitative characteristics observed experimentally [1]. Concomitantly, the CA3 subfield LFP presents episodes of quasi-synchronous neuronal bursting in the form of gamma episodes (25-75 Hz). The model reveals a lower bound for the minimal network that may generate SPW-R activity, and predicts a large number of features of in vivo hippocampal recordings in macaque monkeys [1]. Spike-LFP coherence analysis in CA1 displays reliable synchrony of spiking activity in the ripple LFP frequency band, suggesting that modeled SPW-R episodes reflect a genuine network oscillatory regime. Interestingly, interneuronal firing shows coherence increases concomitant with the beginning and the end of the SPW-R event, together with increases over gamma frequencies. The model suggests that activity of both pyramidal neurons and interneurons is critical for the local genesis and dynamics of physiological SPW-R activity. Unlike other models, we found that it is interneuronal silence, not interneuronal firing that triggers these fast oscillatory events, in line with the fact that unbalanced excitability of selected pyramidal cells marks the beginning of single network episodes. Interneuronal silence quickly increases population firing of pyramidal cells. The interneuronal population activity increases with some latency due to the unbalanced excitatory drive, becoming pivotal to pyramidal cell activity, and further pacing pyramidal cells due to interneuronal fast kinetic properties. Our modeled data suggests that this effect is possibly mediated by a silencing-and-rebound-excitation mechanism, maintaining the frequency of the field oscillation bounded to the ripple range. The reduced model suggests a simple mechanism for the occurrence of SPW-Rs, in light of recent experimental evidence. We provide new insights into the dynamics of the hippocampal CA3-CA1 network during ripples, and the relation between neuronal circuits' activity at meso- and microscopic scales. Finally, our model exhibits characteristic cell type-specific activity that might be critical for the emergence of physiological SPW-R activity and therefore, for the formation of hippocampus-dependent memory representations

Ready ... Go: Amplitude of the fMRI Signal Encodes Expectation of Cue Arrival Time

What happens when the brain awaits a signal of uncertain arrival time, as when a sprinter waits for the starting pistol? And what happens just after the starting pistol fires? Using functional magnetic resonance imaging (fMRI), we have discovered a novel correlate of temporal expectations in several brain regions, most prominently in the supplementary motor area (SMA). Contrary to expectations, we found little fMRI activity during the waiting period; however, a large signal appears after the “go” signal, the amplitude of which reflects learned expectations about the distribution of possible waiting times. Specifically, the amplitude of the fMRI signal appears to encode a cumulative conditional probability, also known as the cumulative hazard function. The fMRI signal loses its dependence on waiting time in a “countdown” condition in which the arrival time of the go cue is known in advance, suggesting that the signal encodes temporal probabilities rather than simply elapsed time. The dependence of the signal on temporal expectation is present in “no-go” conditions, demonstrating that the effect is not a consequence of motor output. Finally, the encoding is not dependent on modality, operating in the same manner with auditory or visual signals. This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals

Cortical mechanisms of sensory learning and object recognition

Learning about the world through our senses constrains our ability to recognise our surroundings. Experience shapes perception. What is the neural basis for object recognition and how are learning-induced changes in recognition manifested in neural populations? We consider first the location of neurons that appear to be critical for object recognition, before describing what is known about their function. Two complementary processes of object recognition are considered: discrimination among diagnostic object features and generalization across non-diagnostic features. Neural plasticity appears to underlie the development of discrimination and generalization for a given set of features, though tracking these changes directly over the course of learning has remained an elusive task

Neural computations underlying action-based decision making in the human brain

Action-based decision making involves choices between different physical actions to obtain rewards. To make such decisions the brain needs to assign a value to each action and then compare them to make a choice. Using fMRI in human subjects, we found evidence for action-value signals in supplementary motor cortex. Separate brain regions, most prominently ventromedial prefrontal cortex, were involved in encoding the expected value of the action that was ultimately taken. These findings differentiate two main forms of value signals in the human brain: those relating to the value of each available action, likely reflecting signals that are a precursor of choice, and those corresponding to the expected value of the action that is subsequently chosen, and therefore reflecting the consequence of the decision process. Furthermore, we also found signals in the dorsomedial frontal cortex that resemble the output of a decision comparator, which implicates this region in the computation of the decision itself

Pain outcomes in patients with bone metastases from advanced cancer: assessment and management with bone-targeting agents

Bone metastases in advanced cancer frequently cause painful complications that impair patient physical activity and negatively affect quality of life. Pain is often underreported and poorly managed in these patients. The most commonly used pain assessment instruments are visual analogue scales, a single-item measure, and the Brief Pain Inventory Questionnaire-Short Form. The World Health Organization analgesic ladder and the Analgesic Quantification Algorithm are used to evaluate analgesic use. Bone-targeting agents, such as denosumab or bisphosphonates, prevent skeletal complications (i.e., radiation to bone, pathologic fractures, surgery to bone, and spinal cord compression) and can also improve pain outcomes in patients with metastatic bone disease. We have reviewed pain outcomes and analgesic use and reported pain data from an integrated analysis of randomized controlled studies of denosumab versus the bisphosphonate zoledronic acid (ZA) in patients with bone metastases from advanced solid tumors. Intravenous bisphosphonates improved pain outcomes in patients with bone metastases from solid tumors. Compared with ZA, denosumab further prevented pain worsening and delayed the need for treatment with strong opioids. In patients with no or mild pain at baseline, denosumab reduced the risk of increasing pain severity and delayed pain worsening along with the time to increased pain interference compared with ZA, suggesting that use of denosumab (with appropriate calcium and vitamin D supplementation) before patients develop bone pain may improve outcomes. These data also support the use of validated pain assessments to optimize treatment and reduce the burden of pain associated with metastatic bone disease