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A form of context-appropriate verificationism is proposed that distinguishes between scientific theories as evolving systems of ideas and operationally-specified, testable formal-empirical models. Theories undergo three stages (modes): a formative, exploratory, heuristic phase of theory conception, a developmental phase of theory-pruning and refinement, and a mature, rigorous phase of testing specific, explicit models. The first phase depends on Feyerabendian open possibility, the second on theoretical plausibility and internal coherence, and the third on testability (falsifiability, predictive efficacy). Multiple perspectives produce variety necessary for theory formation, whereas explicit agreement on evaluative criteria is essential for testing. Hertzian observer-mechanics of empirical-deductive scientific models are outlined that use semiotic operations of measurement/evaluation, computation, and physical action/construction. If models can be fully operationalized, then they can be intersubjectively verified (tested) irrespective of metaphysical, theoretical, value-, or culture-based disagreements. Verificationism can be expanded beyond simple predictive efficacy to incorporate testing for pragmatic, functional efficacy in engineering, medicine, and design contexts. Such a more open, pragmatist, operationalist, epistemically-constructivist perspective is suggested in which verification is contingent on the type of assertion (e.g., heuristic, analytic, empirical, pragmatic), its intended purpose, degree and reliability of model-based evidence, and existence of alternate, competing predictive models. Suggestions for epistemological hygiene amidst the world-wide pandemic of misinformation and propaganda are offered.

How and which aspects of neural activity give rise to subjective perceptual experience—i.e. conscious perception—is a fundamental question of neuroscience. To date, the vast majority of work concerning this question has come from vision, raising the issue of generalizability of prominent resulting theories. However, recent work has begun to shed light on the neural processes subserving conscious perception in other modalities, particularly audition. Here, we outline a roadmap for the future study of conscious auditory perception and its neural basis, paying particular attention to how conscious perception emerges (and of which elements or groups of elements) in complex auditory scenes. We begin by discussing the functional role of the auditory system, particularly as it pertains to conscious perception. Next, we ask: what are the phenomena that need to be explained by a theory of conscious auditory perception? After surveying the available literature for candidate neural correlates, we end by considering the implications that such results have for a general theory of conscious perception as well as prominent outstanding questions and what approaches/techniques can best be used to address them. This article is part of the themed issue ‘Auditory and visual scene analysis’.

Here we present evidence for the ubiquity of fine spike timing and temporal coding broadly observed across sensory systems and widely conserved across diverse phyla, spanning invertebrates and vertebrates. A taxonomy of basic neural coding types includes channel activation patterns, temporal patterns of spikes, and patterns of spike latencies. Various examples and types of combination temporal-channel codes are discussed, including firing sequence codes. Multiplexing of temporal codes and mixed channel-temporal codes are considered. Neurophysiological and perceptual evidence for temporal coding in many sensory modalities is surveyed: audition, mechanoreception, electroreception, vision, gustation, olfaction, cutaneous senses, proprioception, and the vestibular sense. Precise phase-locked, phase-triggered, and spike latency codes can be found in many sensory systems. Temporal resolutions on millisecond and submillisecond scales are common. General correlation-based representations and operations are discussed. In almost every modality, there is some role for temporal coding, often in surprising places, such as color vision and taste. More investigations into temporal coding are well-warranted.

Time is essential for understanding the brain. A temporal theory for realizing major brain functions (e.g., sensation, cognition, motivation, attention, memory, learning, and motor action) is proposed that uses temporal codes, time-domain neural networks, correlation-based binding processes and signal dynamics. It adopts a signal-centric perspective in which neural assemblies produce circulating and propagating characteristic temporally patterned signals for each attribute (feature). Temporal precision is essential for temporal coding and processing. The characteristic spike patterns that constitute the signals enable general-purpose, multimodal, multidimensional vectorial representations of objects, events, situations, and procedures. Signals are broadcast and interact with each other in spreading activation time-delay networks to mutually reinforce, compete, and create new composite patterns. Sequences of events are directly encoded in the relative timings of event onsets. New temporal patterns are created through nonlinear multiplicative and thresholding signal interactions, such as mixing operations found in radio communications systems and wave interference patterns. The newly created patterns then become markers for bindings of specific combinations of signals and attributes (e.g., perceptual symbols, semantic pointers, and tags for cognitive nodes). Correlation operations enable both bottom-up productions of new composite signals and top-down recovery of constituent signals. Memory operates using the same principles: nonlocal, distributed, temporally coded memory traces, signal interactions and amplifications, and content-addressable access and retrieval. A short-term temporary store is based on circulating temporal spike patterns in reverberatory, spike-timing-facilitated circuits. A long-term store is based on synaptic modifications and neural resonances that select specific delay-paths to produce temporally patterned signals. Holographic principles of nonlocal representation, storage, and retrieval can be applied to temporal patterns as well as spatial patterns. These can automatically generate pattern recognition (wavefront reconstruction) capabilities, ranging from objects to concepts, for distributed associative memory applications. The evolution of proposed neural implementations of holograph-like signal processing and associative content-addressable memory mechanisms is discussed. These can be based on temporal correlations, convolutions, simple linear and nonlinear operations, wave interference patterns, and oscillatory interactions. The proposed mechanisms preserve high resolution temporal, phase, and amplitude information. These are essential for establishing high phase coherency and determining phase relationships, for binding/coupling, synchronization, and other operations. Interacting waves can sum constructively for amplification, or destructively, for suppression, or partially. Temporal precision, phase-locking, phase-dependent coding, phase-coherence, synchrony are discussed within the context of wave interference patterns and oscillatory interactions. Sequences of mixed neural oscillations are compared with a cascade of sequential mixing stages in a single-sideband carrier suppressed (SSBCS) radio communications system model. This mechanism suggests a manner by which multiple neural oscillation bands could interact to produce new emergent information-bearing oscillation bands, as well as to abolish previously generated bands. A hypothetical example illustrates how a succession of different oscillation carriers (gamma, beta, alpha, theta, and delta) could communicate and propagate (broadcast) information sequentially through a neural hierarchy of speech and language processing stages. Based on standard signal mixing principles, each stage emergently generates the next. The sequence of oscillatory bands generated in the mixing cascade model is consistent with neurophysiological observations. This sequence corresponds to stages of speech-language processing (sound/speech detection, acoustic-phonetics, phone/clusters, syllables, words/phrases, word sequences/sentences, and concepts/understanding). The oscillatory SSBCS cascade model makes specific predictions for oscillatory band frequencies that can be empirically tested. The principles postulated here may apply broadly for local and global oscillation interactions across the cortex. Sequences of oscillatory interactions can serve many functions, e.g., to regulate the flow and interaction of bottom-up, gamma-mediated and top-down, beta-mediated neural signals, to enable cross-frequency coupling. Some specific guidelines are offered as to how the general time-domain theory might be empirically tested. Neural signals need to be sampled and analyzed with high temporal resolution, without destructive windowing or filtering. Our intent is to suggest what we think is possible, and to widen both the scope of brain theory and experimental inquiry into brain mechanisms, functions, and behaviors.

Time is of the essence in how neural codes, synchronies, and oscillations might function in encoding, representation, transmission, integration, storage, and retrieval of information in brains. This Hypothesis and Theory article examines observed and possible relations between codes, synchronies, oscillations, and types of neural networks they require. Towards reverse-engineering informational functions in brains, prospective, alternative neural architectures incorporating principles from radio modulation and demodulation, active reverberant circuits, distributed content-addressable memory, signal-signal time-domain correlation and convolution operations, spike-correlation-based holography, and self-organizing, autoencoding anticipatory systems are outlined. Synchronies and oscillations are thought to subserve many possible functions: sensation, perception, action, cognition, motivation, affect, memory, attention, anticipation, and imagination. These include direct involvement in coding attributes of events and objects through phase-locking as well as characteristic patterns of spike latency and oscillatory response. They are thought to be involved in segmentation and binding, working memory, attention, gating and routing of signals, temporal reset mechanisms, inter-regional coordination, time discretization, time-warping transformations, and support for temporal wave-interference based operations. A high level, partial taxonomy of neural codes consists of channel, temporal pattern, and spike latency codes. The functional roles of synchronies and oscillations in prospective neural codes, including oscillatory phase-offset codes, are outlined. Various forms of multiplexing neural signals are considered: time-division, frequency-division, code-division, oscillatory-phase, synchronized channels, oscillatory hierarchies, polychronous ensembles. An expandable, annotative neural spike train framework for encoding low- and high-level attributes of events and objects is proposed. Coding schemes require appropriate neural architectures for their interpretation. Time-delay, oscillatory, wave-interference, synfire chain, polychronous, and neural timing networks are discussed. Some novel concepts for formulating an alternative, more time-centric theory of brain function are discussed. As in radio communication systems, brains can be regarded as networks of dynamic, adaptive transceivers that broadcast and selectively receive multiplexed temporally-patterned pulse signals. These signals enable complex signal interactions that select, reinforce, and bind common subpatterns and create emergent lower dimensional signals that propagate through spreading activation interference networks. If memory traces share the same kind of temporal pattern forms as do active neuronal representations, then distributed, holograph-like content-addressable memories are made possible via temporal pattern resonances.

Dorsal root injury results in substantial and often irreversible loss of sensory functions as a result of the limited regenerative capacity of sensory axons and the inhibitory barriers that prevent both axonal entry into and regeneration in the spinal cord. Here, we describe previously unknown effects of the growth factor artemin after crush injury of the dorsal spinal nerve roots in rats. Artemin not only promoted re-entry of multiple classes of sensory fibers into the spinal cord and re-establishment of synaptic function and simple behavior, but it also, surprisingly, promoted the recovery of complex behavior. These effects occurred after a 2-week schedule of intermittent, systemic administration of artemin and persisted for at least 6 months following treatment, suggesting a substantial translational advantage. Systemic artemin administration produced essentially complete and persistent restoration of nociceptive and sensorimotor functions, and could represent a promising therapy that may effectively promote sensory neuronal regeneration and functional recovery after injury.

Purpose – The purpose of this paper is to outline an integrative, high-level, neurocomputational theory of brain function based on temporal codes, neural timing nets, and active regeneration of temporal patterns of spikes within recurrent neural circuits that provides a time-domain alternative to connectionist approaches. Design/methodology/approach – This conceptual-theoretical paper draws from cybernetics, theoretical biology, neurophysiology, integrative and computational neuroscience, psychology, and consciousness studies. Findings – The high-level functional organization of the brain involves adaptive cybernetic, goal-seeking, switching, and steering mechanisms embedded in percept-action-environment loops. The cerebral cortex is conceived as a network of reciprocally connected, re-entrant loops within which circulate neuronal signals that build up, decay, and/or actively regenerate. The basic signals themselves are temporal patterns of spikes (temporal codes), held in the spike correlation mass-statistics of both local and global neuronal ensembles. Complex temporal codes afford multidimensional vectorial representations, multiplexing of multiple signals in spike trains, broadcast strategies of neural coordination, and mutually reinforcing, autopoiesis-like dynamics. Our working hypothesis is that complex temporal codes form multidimensional vectorial representations that interact with each other such that a few basic processes and operations may account for the vast majority of both low- and high-level neural informational functions. These operational primitives include mutual amplification/inhibition of temporal pattern vectors, extraction of common signal dimensions, formation of neural assemblies that generate new temporal pattern primitive “tags” from meaningful, recurring combinations of features (perceptual symbols), active regeneration of temporal patterns, content-addressable temporal pattern memory, and long-term storage and retrieval of temporal patterns via a common synaptic and/or molecular mechanism. The result is a relatively simplified, signal-centric view of the brain that utilizes universal coding schemes and pattern-resonance processing operations. In neurophenomenal terms, waking consciousness requires regeneration and build up of temporal pattern signals in global loops, whose form determines the contents of conscious experience at any moment. Practical implications – Understanding how brains work as informational engines has manifold long-reaching practical implications for design of autonomous, adaptive robotic systems. By proposing how new concepts might arise in brains, the theory bears potential implications for constructivist theories of mind, i.e. how observer-actors interacting with one another can self-organize and complexify. Originality/value – The theory is highly original and heterodox in its neural coding and neurocomputational assumptions. By providing a possible alternative to standard connectionist theory of brain function, it expands the scope of thinking about how brains might work as informational systems.

How and which aspects of neural activity give rise to subjective perceptual experience—i.e. conscious perception—is a fundamental question of neuroscience. To date, the vast majority of work concerning this question has come from vision, raising the issue of generalizability of prominent resulting theories. However, recent work has begun to shed light on the neural processes subserving conscious perception in other modalities, particularly audition. Here, we outline a roadmap for the future study of conscious auditory perception and its neural basis, paying particular attention to how conscious perception emerges (and of which elements or groups of elements) in complex auditory scenes. We begin by discussing the functional role of the auditory system, particularly as it pertains to conscious perception. Next, we ask: what are the phenomena that need to be explained by a theory of conscious auditory perception? After surveying the available literature for candidate neural correlates, we end by considering the implications that such results have for a general theory of conscious perception as well as prominent outstanding questions and what approaches/techniques can best be used to address them. This article is part of the themed issue 'Auditory and visual scene analysis'.

An adaptive synchrony capture filterbank (SCFB) signal processing architecture for tracking signal frequency components was proposed in a previous paper. Detailed analysis and further improvements are presented here. The original SCFB signal processing architecture consisted of a fixed array of traditional, passive linear, gammatone filters in cascade with a bank of three adaptively tunable bandpass filters that form part of a frequency discriminator loop (FDL). The SCFB exhibits many desirable properties for processing speech, music, and other complex sounds. In this article, an improved SCFB architecture is presented along with detailed specification of parameters that yield better frequency tracking. This architecture combines a FDL with a phase-locked loop, a concept borrowed from communication systems, to acquire and track frequency components in a time-varying signal. This modified algorithm estimates frequencies with higher accuracy even in the presence of closely spaced tones in the input. The improved performance of the algorithm is demonstrated by comparing the mean square error in the frequency estimates of synthetic time-varying signals.

This chapter outlines a broad theory of sign use in natural and artificial systems that was developed over several decades within the context of theoretical biology, cybernetics, systems theory, biosemiotics, and neuroscience. Different conceptions of semiosis and information in nature are considered. General functional properties of and operations on signs, including measurement, computation, and sign-directed actions are described. A taxonomy of semiotic systems is built up from combinations of these operations. The respective functional organizations and informational capabilities of formal systems and computempiral-predictive scientific models, percept-action systems, purposive goal-seeking systems, and self-constructing systems are discussed. Semiotic relations are considered in terms of Morrisean semiotic triad of syntactics, semantics, and pragmatics. Analysis of statetransition structure is used to demarcate functional boundaries, such as epistemic and control cuts. Capabilities for open-ended behavior, combinatoric and emergent creativity, and umwelt expansion are taken up. Finally, basic problems of neurosemiotics, neural coding, and neurophenomenology are outlined.