Going online: Peer entrepreneur networks in a startup accelerator before and during the COVID-19 pandemic

A key value proposition of startup accelerators is the creation of social networks among participating entrepreneurs. The formation of these so-called “peer entrepreneur networks” is assumed to be strengthened by physical proximity within the accelerator, which facilitates the creation of trust and opportunities for informal, and often serendipitous, interactions. However, in response to the global spread of COVID-19, accelerators abruptly shifted their programs online, thereby allowing a rare opportunity to test the veracity of the assumption that physical proximity drives social connectivity. To understand how this shift affected peer entrepreneur networks, we compare longitudinal network data of two consecutive cohorts of the same accelerator: one offline-before, and one online-during, the COVID-19 pandemic. Drawing from the literature on physical proximity and interaction ritual theory, we show that in the online (compared to the offline) program, peer entrepreneur networks became less dense, entrepreneurs reached fewer peers via indirect connections, and clustering increased. We discuss contributions to theory on peer entrepreneur networks and startup accelerators

Fast Ripples Reflect Increased Excitability That Primes Epileptiform Spikes

The neuronal circuit disturbances that drive inter-ictal and ictal epileptiform discharges remain elusive. Using a combination of extra-operative macro-electrode and micro-electrode inter-ictal recordings in six pre-surgical patients during non-rapid eye movement sleep, we found that, exclusively in the seizure onset zone, fast ripples (200–600 Hz), but not ripples (80–200 Hz), frequently occur \u3c300 ms before an inter-ictal intra-cranial EEG spike with a probability exceeding chance (bootstrapping, P \u3c 1e−5). Such fast ripple events are associated with higher spectral power (P \u3c 1e−10) and correlated with more vigorous neuronal firing than solitary fast ripple (generalized linear mixed-effects model, P \u3c 1e−9). During the intra-cranial EEG spike that follows a fast ripple, action potential firing is lower than during an intra-cranial EEG spike alone (generalized linear mixed-effects model, P \u3c 0.05), reflecting an inhibitory restraint of intra-cranial EEG spike initiation. In contrast, ripples do not appear to prime epileptiform spikes. We next investigated the clinical significance of pre-spike fast ripple in a separate cohort of 23 patients implanted with stereo EEG electrodes, who underwent resections. In non-rapid eye movement sleep recordings, sites containing a high proportion of fast ripple preceding intra-cranial EEG spikes correlate with brain areas where seizures begin more than solitary fast ripple (P \u3c 1e−5). Despite this correlation, removal of these sites does not guarantee seizure freedom. These results are consistent with the hypothesis that fast ripple preceding EEG spikes reflect an increase in local excitability that primes EEG spike discharges preferentially in the seizure onset zone and that epileptogenic brain regions are necessary, but not sufficient, for initiating inter-ictal epileptiform discharges

Ripples Have Distinct Spectral Properties and Phase-Amplitude Coupling With Slow Waves, but Indistinct Unit Firing, in Human Epileptogenic Hippocampus

Ripple oscillations (80–200 Hz) in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200–600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both ripples and fast ripples exhibit a preferred phase angle of coupling with the trough-peak (or On-Off) state transition of the sleep slow wave in the hippocampal seizure onset zone (SOZ). Ripples on slow waves in the hippocampal SOZ also had a lower power, greater spectral frequency, and shorter duration than those in the non-SOZ. Slow waves in the mesial temporal lobe modulated the baseline firing rate of excitatory neurons, but did not significantly influence the increased firing rate associated with ripples. In summary, pathological ripples and fast ripples occur preferentially during the On-Off state transition of the slow wave in the epileptogenic hippocampus, and ripples do not require the increased recruitment of excitatory neurons.Fil: Weiss, Shennan A.. Thomas Jefferson University; Estados UnidosFil: Song, Inkyung. Thomas Jefferson University; Estados UnidosFil: Leng, Mei. University of California at Los Angeles; Estados UnidosFil: Pastore, Tomás. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Fernandez Slezak, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Waldman, Zachary. Thomas Jefferson University; Estados UnidosFil: Orosz, Iren. University of California at Los Angeles; Estados UnidosFil: Gorniak, Richard. Thomas Jefferson University; Estados UnidosFil: Donmez, Mustafa. Thomas Jefferson University; Estados UnidosFil: Sharan, Ashwini. Thomas Jefferson University; Estados UnidosFil: Wu, Chengyuan. Thomas Jefferson University; Estados UnidosFil: Fried, Itzhak. University of California at Los Angeles; Estados UnidosFil: Sperling, Michael R.. Thomas Jefferson University; Estados UnidosFil: Bragin, Anatol. University of California at Los Angeles; Estados UnidosFil: Engel, Jerome. University of California at Los Angeles; Estados UnidosFil: Nir, Yuval. Tel Aviv University; IsraelFil: Staba, Richard. University of California at Los Angeles; Estados Unido

Delta oscillation coupled propagating fast ripples precede epileptiform discharges in patients with focal epilepsy.

Epileptiform spikes are used to localize epileptogenic brain tissue. The mechanisms that spontaneously trigger epileptiform discharges are not yet elucidated. Pathological fast ripple (FR, 200-600 Hz) are biomarkers of epileptogenic brain, and we postulated that FR network interactions are involved in generating epileptiform spikes. Using macroelectrode stereo intracranial EEG (iEEG) recordings from a cohort of 46 patients we found that, in the seizure onset zone (SOZ), propagating FR were more often followed by an epileptiform spike, as compared with non-propagating FR (p \u3c 0.05). Propagating FR had a distinct frequency and larger power (p \u3c 1e-10) and were more strongly phase coupled to the peak of iEEG delta oscillation, which likely correspond with the DOWN states during non-REM sleep (p \u3c 1e-8), than non-propagating FR. While FR propagation was rare, all FR occurred with the highest probability within +/- 400 msec of epileptiform spikes with superimposed high-frequency oscillations (p \u3c 0.05). Thus, a sub-population of epileptiform spikes in the SOZ, are preceded by propagating FR that are coordinated by the DOWN state during non-REM sleep

Delta Oscillation Coupled Propagating Fast Ripples Precede Epileptiform Discharges in Patients With Focal Epilepsy

Epileptiform spikes are used to localize epileptogenic brain tissue. The mechanisms that spontaneously trigger epileptiform discharges are not yet elucidated. Pathological fast ripple (FR, 200–600 Hz) are biomarkers of epileptogenic brain, and we postulated that FR network interactions are involved in generating epileptiform spikes. Using macroelectrode stereo intracranial EEG (iEEG) recordings from a cohort of 46 patients we found that, in the seizure onset zone (SOZ), propagating FR were more often followed by an epileptiform spike, as compared with non-propagating FR (p \u3c 0.05). Propagating FR had a distinct frequency and larger power (p \u3c 1e-10) and were more strongly phase coupled to the peak of iEEG delta oscillation, which likely correspond with the DOWN states during non-REM sleep (p \u3c 1e-8), than non-propagating FR. While FR propagation was rare, all FR occurred with the highest probability within +/− 400 msec of epileptiform spikes with superimposed high-frequency oscillations (p \u3c 0.05). Thus, a sub-population of epileptiform spikes in the SOZ, are preceded by propagating FR that are coordinated by the DOWN state during non-REM sleep

Stronger Neural Modulation by Visual Motion Intensity in Autism Spectrum Disorders

Theories of autism spectrum disorders (ASD) have focused on altered perceptual integration of sensory features as a possible core deficit. Yet, there is little understanding of the neuronal processing of elementary sensory features in ASD. For typically developed individuals, we previously established a direct link between frequency-specific neural activity and the intensity of a specific sensory feature: Gamma-band activity in the visual cortex increased approximately linearly with the strength of visual motion. Using magnetoencephalography (MEG), we investigated whether in individuals with ASD neural activity reflect the coherence, and thus intensity, of visual motion in a similar fashion. Thirteen adult participants with ASD and 14 control participants performed a motion direction discrimination task with increasing levels of motion coherence. A polynomial regression analysis revealed that gamma-band power increased significantly stronger with motion coherence in ASD compared to controls, suggesting excessive visual activation with increasing stimulus intensity originating from motion-responsive visual areas V3, V6 and hMT/V5. Enhanced neural responses with increasing stimulus intensity suggest an enhanced response gain in ASD. Response gain is controlled by excitatory-inhibitory interactions, which also drive high-frequency oscillations in the gamma-band. Thus, our data suggest that a disturbed excitatoryinhibitory balance underlies enhanced neural responses to coherent motion in ASD

Evidence for Human Fronto-Central Gamma Activity during Long-Term Memory Encoding of Word Sequences

Although human gamma activity (30–80 Hz) associated with visual processing is often reported, it is not clear to what extend gamma activity can be reliably detected non-invasively from frontal areas during complex cognitive tasks such as long term memory (LTM) formation. We conducted a memory experiment composed of 35 blocks each having three parts: LTM encoding, working memory (WM) maintenance and LTM retrieval. In the LTM encoding and WM maintenance parts, participants had to respectively encode or maintain the order of three sequentially presented words. During LTM retrieval subjects had to reproduce these sequences. Using magnetoencephalography (MEG) we identified significant differences in the gamma and beta activity. Robust gamma activity (55–65 Hz) in left BA6 (supplementary motor area (SMA)/pre-SMA) was stronger during LTM rehearsal than during WM maintenance. The gamma activity was sustained throughout the 3.4 s rehearsal period during which a fixation cross was presented. Importantly, the difference in gamma band activity correlated with memory performance over subjects. Further we observed a weak gamma power difference in left BA6 during the first half of the LTM rehearsal interval larger for successfully than unsuccessfully reproduced word triplets. In the beta band, we found a power decrease in left anterior regions during LTM rehearsal compared to WM maintenance. Also this suppression of beta power correlated with memory performance over subjects. Our findings show that an extended network of brain areas, characterized by oscillatory activity in different frequency bands, supports the encoding of word sequences in LTM. Gamma band activity in BA6 possibly reflects memory processes associated with language and timing, and suppression of beta activity at left frontal sensors is likely to reflect the release of inhibition directly associated with the engagement of language functions

Good vibrations, bad vibrations: Oscillatory brain activity in the attentional blink

The attentional blink (AB) is a deficit in reporting the second (T2) of two targets (T1, T2) when presented in close temporal succession and within a stream of distractor stimuli. The AB has received a great deal of attention in the past two decades because it allows to study the mechanisms that influence the rate and depth of information processing in various setups and therefore provides an elegant way to study correlates of conscious perception in supra-threshold stimuli. Recently evidence has accumulated suggesting that oscillatory signals play a significant role in temporally coordinating information between brain areas. This review focuses on studies looking into oscillatory brain activity in the AB. The results of these studies indicate that the AB is related to modulations in oscillatory brain activity in the theta, alpha, beta, and gamma frequency bands. These modulations are sometimes restricted to a circumscribed brain area but more frequently include several brain regions. They occur before targets are presented as well as after the presentation of the targets. We will argue that the complexity of the findings supports the idea that the AB is not the result of a processing impairment in one particular process or brain area, but the consequence of a dynamic interplay between several processes and/or parts of a neural network

Delta-9-tetrahydrocannabinol, neural oscillations above 20 Hz and induced acute psychosis

Rationale: An acute challenge with delta-9-tetrahydrocannabinol (THC) can induce psychotic symptoms including delusions. High electroencephalography (EEG) frequencies, above 20 Hz, have previously been implicated in psychosis and schizophrenia. Objectives: The objective of this study is to determine the effect of intravenous THC compared to placebo on high-frequency EEG. Methods: A double-blind cross-over study design was used. In the resting state, the high-beta to low-gamma magnitude (21–45 Hz) was investigated (n=13 pairs+4 THC only). Also, the event-related synchronisation (ERS) of motor-associated high gamma was studied using a self-paced button press task (n=15). Results: In the resting state, there was a significant condition × frequency interaction (p=0.00017), consisting of a shift towards higher frequencies under THC conditions (reduced high beta [21–27 Hz] and increased low gamma [27–45 Hz]). There was also a condition × frequency × location interaction (p=0.006), such that the reduction in 21–27-Hz magnitude tended to be more prominent in anterior regions, whilst posterior areas tended to show greater 27–45-Hz increases. This effect was correlated with positive symptoms, as assessed on the Positive and Negative Syndrome Scale (PANSS) (r=0.429, p=0.042). In the motor task, there was a main effect of THC to increase 65–130-Hz ERS (p=0.035) over contra-lateral sensorimotor areas, which was driven by increased magnitude in the higher, 85–130-Hz band (p=0.02) and not the 65–85-Hz band. Conclusions: The THC-induced shift to faster gamma oscillations may represent an over-activation of the cortex, possibly related to saliency misattribution in the delusional state