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Whereas gamma-band neuronal oscillations clearly appear integral to visual attention, the role of lower-frequency oscillations is still being debated. Mounting evidence indicates that a key functional property of these oscillations is the rhythmic shifting of excitability in local neuronal ensembles. Here, we show that when attended stimuli are in a rhythmic stream, delta-band oscillations in the primary visual cortex entrain to the rhythm of the stream, resulting in increased response gain for task-relevant events and decreased reaction times. Because of hierarchical cross-frequency coupling, delta phase also determines momentary power in higher-frequency activity. These instrumental functions of low-frequency oscillations support a conceptual framework that integrates numerous earlier findings.

To discover meaning behind neural single unit activity has constantly been a challenge – and so it persists for the foreseeable future. As one of the most sourced strategies, detecting neural activity on high-resolution neural sensor recordings, then attributing them to their corresponding source neurons correctly, namely the process of spike sorting has been prevailing so far. Supported by ever-improving recording techniques and sophisticated algorithms for extracting worthwhile information, as well as the abundance in clustering procedures turned spike sorting into an indispensable tool in electrophysiological analysis. This review attempts to illustrate that in all stages of spike sorting algorithms, past five years’ innovations brought about concepts, results and questions worth sharing with even the non-expert user community. By thoroughly inspecting latest innovations in the field of neural sensors, recording procedures and various spike sorting strategies, a skeletonization of relevant knowledge lays here, with initiative to get one step closer to the original objective: deciphering and building upon the sense of neural transcript.

The simultaneous utilization of electrophysiological recordings and two-photon imaging allows the observation of neural activity in a high temporal and spatial resolution at the same time. The three dimensional monitoring of morphological features near the microelectrode array makes the observation more precise and complex. In vitro experiments were performed on mice neocortical slices expressing the GCaMP6 genetically encoded calcium indicator for monitoring the neural activity with two-photon microscopy around the implanted microelectrodes. A special filtering algorithm was used for data analysis to eliminate the artefacts caused by the imaging laser. Utilization of a special filtering algorithm allowed us to detect and sort single unit activities from simultaneous two-photon imaging and electrophysiological measurement.

Adaptive brain function is characterized by dynamic interactions within and between neuronal circuits, often occurring at the time scale of milliseconds. These complex interactions between adjacent and noncontiguous brain areas depend on a functional architecture that is maintained even in the absence of input. Functional MRI studies carried out during rest (R-fMRI) suggest that this architecture is represented in low-frequency (<0.1 Hz) spontaneous fluctuations in the blood oxygen level-dependent signal that are correlated within spatially distributed networks of brain areas. These networks, collectively referred to as the brain's intrinsic functional architecture, exhibit a remarkable correspondence with patterns of task-evoked coactivation as well as maps of anatomical connectivity. Despite this striking correspondence, there is no direct evidence that this intrinsic architecture forms the scaffold that gives rise to faster processes relevant to information processing and seizure spread. Here, we demonstrate that the spatial distribution and magnitude of temporally correlated low-frequency fluctuations observed with R-fMRI during rest predict the pattern and magnitude of corticocortical evoked potentials elicited within 500 ms after single-pulse electrical stimulation of the cerebral cortex with intracranial electrodes. Across individuals, this relationship was found to be independent of the specific regions and functional systems probed. Our findings bridge the immense divide between the temporal resolutions of these distinct measures of brain function and provide strong support for the idea that the low-frequency signal fluctuations observed with R-fMRI maintain and update the intrinsic architecture underlying the brain's repertoire of functional responses.

Neural probes designed for extracellular recording of brain electrical activity are traditionally implanted with an insertion speed between 1 µm/s and 1 mm/s into the brain tissue. Although the physical effects of insertion speed on the tissue are well studied, there is a lack of research investigating how the quality of the acquired electrophysiological signal depends on the speed of probe insertion. In this study, we used four different insertion speeds (0.002 mm/s, 0.02 mm/s, 0.1 mm/s, 1 mm/s) to implant high-density silicon probes into deep layers of the somatosensory cortex of ketamine/xylazine anesthetized rats. After implantation, various qualitative and quantitative properties of the recorded cortical activity were compared across different speeds in an acute manner. Our results demonstrate that after the slowest insertion both the signal-to-noise ratio and the number of separable single units were significantly higher compared with those measured after inserting probes at faster speeds. Furthermore, the amplitude of recorded spikes as well as the quality of single unit clusters showed similar speed-dependent differences. Post hoc quantification of the neuronal density around the probe track showed a significantly higher number of NeuN-labelled cells after the slowest insertion compared with the fastest insertion. Our findings suggest that advancing rigid probes slowly (~1 µm/s) into the brain tissue might result in less tissue damage, and thus in neuronal recordings of improved quality compared with measurements obtained after inserting probes with higher speeds.

The alpha rhythm is the longest-studied brain oscillation and has been theorized to play a key role in cognition. Still, its physiology is poorly understood. In this study, we used microelectrodes and macroelectrodes in surgical epilepsy patients to measure the intracortical and thalamic generators of the alpha rhythm during quiet wakefulness. We first found that alpha in both visual and somatosensory cortex propagates from higher-order to lower-order areas. In posterior cortex, alpha propagates from higher-order anterosuperior areas toward the occipital pole, whereas alpha in somatosensory cortex propagates from associative regions toward primary cortex. Several analyses suggest that this cortical alpha leads pulvinar alpha, complicating prevailing theories of a thalamic pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortical layers. Together, these results suggest that the alpha rhythm likely reflects short-range supragranular feedback, which propagates from higher- to lower-order cortex and cortex to thalamus. These physiological insights suggest how alpha could mediate feedback throughout the thalamocortical system.

•Propagation of slow waves was observed in the thalamus of anesthetized rats and mice.•Slow wave propagation occurs mainly in higher order thalamic nuclei.•Thalamic multiunit activity propagates predominantly in the ventral-to-dorsal direction.•Dorsal thalamic up-states are temporally locked to cortical up-state activity under anesthesia.•Thalamic activity propagation is less frequent and faster during natural sleep in rats. Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings collected under anesthesia demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus under anesthesia.

Decades of research support the idea that associations between a conditioned stimulus (CS) and an unconditioned stimulus (US) are encoded in the lateral amygdala (LA) during fear learning. However, direct proof for the sources of CS and US information is lacking. Definitive evidence of the LA as the primary site for cue association is also missing. Here, we show that calretinin (Calr)-expressing neurons of the lateral thalamus (Calr+LT neurons) convey the association of fast CS (tone) and US (foot shock) signals upstream from the LA in mice. Calr+LT input shapes a short-latency sensory-evoked activation pattern of the amygdala via both feedforward excitation and inhibition. Optogenetic silencing of Calr+LT input to the LA prevents auditory fear conditioning. Notably, fear conditioning drives plasticity in Calr+LT neurons, which is required for appropriate cue and contextual fear memory retrieval. Collectively, our results demonstrate that Calr+LT neurons provide integrated CS–US representations to the LA that support the formation of aversive memories.The authors describe a thalamic population, innervated by multimodal brainstem inputs, that forms a CS–US association prior to the lateral amygdala. Its fast and plastic signal defines an amygdala activity pattern necessary for adaptive fear learning.

Fever raises body temperature (T b ) from ~37°C to beyond 38.4°C to combat pathogens. While generally well tolerated below 40°C, in rare cases, fever can abnormally elevate neural activity and induce seizures in neurotypical children aged 2–5 years. This study investigates the mechanisms by which neuronal activity is maintained and stabilized during exposure to fever-range temperatures. Recordings of layer (L)4-evoked spiking in L2/3 pyramidal neurons (PNs) of mouse somatosensory cortex revealed four outcomes as temperature increased from 30°C to 36°C and 39°C (fever-range): neurons remained inactive, stayed active, ceased activity, or initiated activity. Roughly equal proportions of neurons ceased or initiated spiking, making the subset of ‘STAY’ PNs, those that remain active across temperatures, crucial for maintaining stable cortical output. STAY PNs were more prevalent at younger postnatal ages. Their firing stability was supported by a distinct ion channel composition, including the thermosensitive channel TRPV3, which enables continued spiking by adjusting depolarization to meet spike threshold. Intracellular blockade of TRPV3, but not TRPV4, significantly reduced the proportion of STAY PNs and suppressed spiking at 39°C. Moreover, in Trpv3 -/- mice, temperature increases to 39°C reduced both spiking and post-synaptic potential amplitude, and these mice exhibited a delayed seizure onset. Together, these findings suggest that TRPV3 contributes to the preservation of cortical activity during fever. Fever is a symptom of an infection during which the body temperature rises from just below 37 °C (98.6. 6 °F) to above 38 °C (100.4. 4 °F). This extra heat helps the body fight germs. For most children and adults, a higher temperature – which also affects the brain – causes only milder symptoms such as tiredness, body aches, headache or chills. However, in about 1 in 20 to 1 in 50 children aged 6 months to 5 years, a fever can trigger a seizure. Seizures happen when brain cells, called neurons, become overly active at the same time. Most studies in rodents have focused on why brain cells become overactive at very high temperatures, around 41 to 42 °C. Much less is known about why seizures are relatively rare at lower temperatures of about 38 to 39 °C. To address this gap, Shen et al. studied how neurons maintain a normal activity at lower temperatures. The researchers recorded neurons in the somatosensory cortex of mice as their body temperature increased from 30 °C to between 36 °C and 39 °C (fever-range). In young mouse brains, fever induced two simultaneous changes in brain cells: some neurons reduced their activity, allowing them to rest, while others increased their activity to compensate. Because the number of active and less active neurons was roughly balanced, the cells could keep their overall activity stable during a fever. Moreover, the researchers also identified a thermosensitive protein known as TRPV3 that enhanced its activity during fever. This allowed a sustained flow of ions into the neurons, helping active neurons to keep their firing rate. Rather than increasing seizure risk, this mechanism appears to stabilize neural circuits and prevent excessive synchronization of neurons when fever reduces or pauses activity in many neurons. In addition, active neurons were distinct in that they received greater excitatory input from neighboring neurons and underwent functional adaptations, such as maintaining ion channel expression and distribution, to help preserve effective communication and network stability during fever. Genetically modified mice lacking TRPV3 showed reduced neuronal activity and a delayed onset of seizures, indicating that TRPV3 is essential in maintaining cortical activity during fever. These findings differ from experiments conducted at very high temperatures, where neuronal overexcitation is driven by breakdowns in ion channel function and inhibitory signaling. Shen et al. uncovered previously unknown neuronal processes that help the brain continue functioning during fever. This work lays the groundwork for future studies into the causes of fever-related seizures, including whether such seizures arise when compensatory mechanisms fail or when key proteins necessary for maintaining neural balance are overexpressed during elevated body temperatures.