Time Is of the Essence: Neural Codes, Synchronies, Oscillations, Architectures.

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. Toward 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 candidate 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.

Speech-specific tuning of neurons in human superior temporal gyrus.

How the brain extracts words from auditory signals is an unanswered question. We recorded approximately 150 single and multi-units from the left anterior superior temporal gyrus of a patient during multiple auditory experiments. Against low background activity, 45% of units robustly fired to particular spoken words with little or no response to pure tones, noise-vocoded speech, or environmental sounds. Many units were tuned to complex but specific sets of phonemes, which were influenced by local context but invariant to speaker, and suppressed during self-produced speech. The firing of several units to specific visual letters was correlated with their response to the corresponding auditory phonemes, providing the first direct neural evidence for phonological recoding during reading. Maximal decoding of individual phonemes and words identities was attained using firing rates from approximately 5 neurons within 200 ms after word onset. Thus, neurons in human superior temporal gyrus use sparse spatially organized population encoding of complex acoustic-phonetic features to help recognize auditory and visual words.

First-pass selectivity for semantic categories in human anteroventral temporal lobe.

How the brain encodes the semantic concepts represented by words is a fundamental question in cognitive neuroscience. Hemodynamic neuroimaging studies have robustly shown that different areas of posteroventral temporal lobe are selectively activated by images of animals versus manmade objects. Selective responses in these areas to words representing animals versus objects are sometimes also seen, but they are task-dependent, suggesting that posteroventral temporal cortex may encode visual categories, while more anterior areas encode semantic categories. Here, using the spatiotemporal resolution provided by intracranial macroelectrode and microelectrode arrays, we report category-selective responses to words representing animals and objects in human anteroventral temporal areas including inferotemporal, perirhinal, and entorhinal cortices. This selectivity generalizes across tasks and sensory modalities, suggesting that it represents abstract lexicosemantic categories. Significant category-specific responses are found in measures sensitive to synaptic activity (local field potentials, high gamma power, current sources and sinks) and unit-firing (multiunit and single-unit activity). Category-selective responses can occur at short latency (as early as 130 ms) in middle cortical layers and thus are extracted in the first pass of activity through the anteroventral temporal lobe. This activation may provide input to posterior areas for iconic representations when required by the task, as well as to the hippocampal formation for categorical encoding and retrieval of memories, and to the amygdala for emotional associations. More generally, these results support models in which the anteroventral temporal lobe plays a primary role in the semantic representation of words.